New Psychoactive Substances in Australia

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NEW PSYCHOACTIVE SUBSTANCES IN AUSTRALIA

Rachel Sutherland BSocSc (Hons, Criminology)

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

National Drug and Alcohol Research Centre School of Public Health and Community Medicine Faculty of Medicine University of New South Wales

November 2018

i THESIS/DISSERTATION SHEET

Surname/Family Name Sutherland Given Name/s Rachel Anne Abbreviation for degree as give in the University calendar PhD Faculty Medicine School School of Public Health and Community Medicine Thesis Title New psychoactive substances in Australia

Abstract 350 words maximum: (PLEASE TYPE) Over the past decade, countries worldwide have observed the rapid emergence of substances collectively referred to as ‘new psychoactive substances’ (NPS). To date, hundreds of NPS have been identified; however, for the most part very little is known about these substances. The exponential growth of NPS, combined with uncertainty regarding potential harms, has generated considerable concern amongst policy makers and there is international consensus regarding the need for ongoing monitoring and research into the NPS market. However, much of the research conducted in this area originates from Europe and the United States, with Australian-specific studies relatively scarce.

This thesis aimed to address this gap in Australian specific studies using two data sources: the 2013 National Drug Strategy Household Survey (NDSHS: a general population prevalence survey) and the Ecstasy and related Drugs Reporting System (EDRS: a national survey of high frequency psychostimulant consumers). Specifically, this thesis aimed to: 1) determine if there was a distinct group of exclusive Australian NPS consumers; 2) examine rates of use of different classes of NPS amongst people who use other illicit substances; 3) examine the motivations associated with NPS use; and 4) explore the purchasing and supply patterns of NPS consumers.

A number of key findings emerged from this thesis. Firstly, using data from the NDSHS, it was found that there is no distinct group of exclusive Australian NPS consumers; rather they primarily consist of people using a range of illicit substances. Secondly, using data from the EDRS, it was found that the NPS market is highly dynamic, with the consumption of particular NPS classes changing over time. Thirdly, NPS use appears to be a marker for higher engagement in substance use, and as such, higher rates of drug-related risk behaviours. Finally, the collective findings of this thesis illustrate the heterogeneity of NPS consumers.

Taken together, these findings suggest that specialised NPS interventions may be unnecessary; rather, existing health services should screen for and be equipped to deal with NPS-related presentations. Furthermore, the diverse and rapidly changing nature of the NPS market demonstrate the need for international collaboration, combined with a rapidly responsive health framework.

Declaration relating to disposition of project thesis/dissertation I hereby grant to the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all property rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation.

I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only).

31 August 2018 Signature Witness Signature …….……………………...…….… Date The University recognises that there may be exceptional circumstances requiring restrictions on copying or conditions on use. Requests for restriction for a period of up to 2 years must be made in writing. Requests for a longer period of restriction may be considered in exceptional circumstances and require the approval of the Dean of Graduate Research.

FOR OFFICE USE Date of completion of requirements for Award: ONLY

DECLARATIONS Originality statement

I hereby declare that this submission is my own work and to the best of my knowledge contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in this thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.

Rachel Sutherland August 2018

iii Copyright

I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, known as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation.

I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only).

I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.

Rachel Sutherland August 2018

Authenticity statement

I certify that the Library deposit digital copy is a direct equivalent of the final officially approved version of my thesis. No emendation of content has occurred and if there are any minor variations in formatting, there are the result of the conversion to digital format.

Rachel Sutherland August 2018

Supervisor statement

I hereby certify that all co-authors of the published papers agree to Rachel Sutherland submitting those papers as part of her Doctoral Thesis.

Thesis by publication statement

Four papers are included in this thesis by publication. They have all been accepted to be published in peer-reviewed journals.

Lucinda Burns August 2018

v Inclusion of publications statement

UNSW is supportive of candidates publishing their research results during their candidature as detailed in the UNSW Thesis Examination Procedure. Publications can be used in their thesis in lieu of a Chapter if: • The student contributed greater than 50% of the content in the publication and is the “primary author”, ie. the student was responsible primarily for the planning, execution and preparation of the work for publication • The student has approval to include the publication in their thesis in lieu of a Chapter from their supervisor and Postgraduate Coordinator. • The publication is not subject to any obligations or contractual agreements with a third party that would constrain its inclusion in the thesis

Please indicate whether this thesis contains published material or not.

☐ This thesis contains no publications, either published or submitted for publication

Some of the work described in this thesis has been published and it has been ☐ documented in the relevant Chapters with acknowledgement

This thesis has publications (either published or submitted for publication) incorporated ☒ into it in lieu of a chapter and the details are presented below

CANDIDATE’S DECLARATION I declare that: • I have complied with the Thesis Examination Procedure • where I have used a publication in lieu of a Chapter, the listed publication(s) below meet(s) the requirements to be included in the thesis. Name Signature Date (dd/mm/yy) Rachel Sutherland 17 August 2018

Postgraduate Coordinator’s Declaration I declare that: • the information below is accurate • where listed publication(s) have been used in lieu of Chapter(s), their use complies with the Thesis Examination Procedure • the minimum requirements for the format of the thesis have been met. PGC’s Name PGC’s Signature Date (dd/mm/yy) Husna Razee 22 August 2018

Details of publication #1: Full title: Typology of new psychoactive substance use among the general Australian population Authors: Rachel Sutherland, Amy Peacock, Amanda Roxburgh, Monica J. Barratt, Lucinda Burns & Raimondo Bruno Journal or book name: Drug and Alcohol Dependence Volume/page numbers: 188; 126-134 Date accepted/ published: 3 May 2018 Status Published x Accepted and In In progress press (submitted) The Candidate’s Contribution to the Work The candidate performed the data analysis, interpreted the data, wrote the manuscript and was the corresponding author. Location of the work in the thesis and/or how the work is incorporated in the thesis: This paper is included as the second chapter in the thesis and uses general population data to determine if there is a distinct group of exclusive NPS consumers. Primary Supervisor’s Declaration I declare that: • the information above is accurate • this has been discussed with the PGC and it is agreed that this publication can be included in this thesis in lieu of a Chapter • All of the co-authors of the publication have reviewed the above information and have agreed to its veracity by signing a ‘Co-Author Authorisation’ form. Supervisor’s name Supervisor’s signature Date (dd/mm/yy) Lucinda Burns 17 August 2018

vii Details of publication #2: Full title: New psychoactive substance use among regular psychostimulant users in Australia, 2010-2015 Authors: Rachel Sutherland, Amy Peacock, Elizabeth Whittaker, Simon Lenton, Allison Matthews, Kerryn Butler, Marina Nelson, Lucinda Burns & Raimondo Bruno Journal or book name: Drug and Alcohol Dependence Volume/page numbers: 16(1), 110-118 Date accepted/ published: 3 February 2016 Status Published x Accepted and In In progress press (submitted) The Candidate’s Contribution to the Work The candidate performed the data analysis, interpreted the data, wrote the manuscript and was the corresponding author. Location of the work in the thesis and/or how the work is incorporated in the thesis: This paper is included as the third chapter in the thesis and builds upon chapter two by examining trends in use of the different NPS classes over time. Primary Supervisor’s Declaration I declare that: • the information above is accurate • this has been discussed with the PGC and it is agreed that this publication can be included in this thesis in lieu of a Chapter • All of the co-authors of the publication have reviewed the above information and have agreed to its veracity by signing a ‘Co-Author Authorisation’ form. Supervisor’s name Supervisor’s signature Date (dd/mm/yy) Lucinda Burns 17 August 2018

viii

Details of publication #3: Full title: Motivations for new psychoactive substance use among regular psychostimulant users in Australia Authors: Rachel Sutherland, Raimondo Bruno, Amy Peacock, Simon Lenton, Allison Matthews, Caroline Salom, Paul Dietze, Kerryn Butler, Lucinda Burns & Monica J. Barratt Journal or book name: International Journal of Drug Policy Volume/page numbers: 43; 23-32 Date accepted/ published: 2 February 2017 Status Published x Accepted and In In progress press (submitted) The Candidate’s Contribution to the Work The candidate performed the data analysis, interpreted the data, wrote the manuscript and was the corresponding author. Location of the work in the thesis and/or how the work is incorporated in the thesis: This paper is included as the fourth chapter in the thesis, and examines the motivations associated with different NPS in the Australian context. Primary Supervisor’s Declaration I declare that: • the information above is accurate • this has been discussed with the PGC and it is agreed that this publication can be included in this thesis in lieu of a Chapter • All of the co-authors of the publication have reviewed the above information and have agreed to its veracity by signing a ‘Co-Author Authorisation’ form. Supervisor’s name Supervisor’s signature Date (dd/mm/yy) Lucinda Burns 17 August 2018

ix Details of publication #4: Full title: New psychoactive substances: supply and purchasing patterns in Australia Authors: Rachel Sutherland, Raimondo Bruno, Amy Peacock, Paul Dietze, Courtney Breen, Lucinda Burns & Monica J. Barratt Journal or book name: Human Psychopharmacology: Clinical and Experimental Volume/page numbers: 32 (3); e2577 Date accepted/ published: 18 May 2017 Status Published x Accepted and In In progress press (submitted) The Candidate’s Contribution to the Work The candidate performed the data analysis, interpreted the data, wrote the manuscript and was the corresponding author. Location of the work in the thesis and/or how the work is incorporated in the thesis: This paper is included as the fifth chapter in the thesis and examines the purchasing and supply patterns of NPS consumers in Australia. Primary Supervisor’s Declaration I declare that: • the information above is accurate • this has been discussed with the PGC and it is agreed that this publication can be included in this thesis in lieu of a Chapter • All of the co-authors of the publication have reviewed the above information and have agreed to its veracity by signing a ‘Co-Author Authorisation’ form. Supervisor’s name Supervisor’s signature Date (dd/mm/yy) Lucinda Burns 17 August 2018

ACKNOWLEDGEMENTS

First and foremost, I would like to give my sincerest thanks to my supervisors, Lucinda Burns (supervisor), Raimondo Bruno (co-supervisor) and Monica Barratt (co-supervisor), all of whom have provided guidance, encouragement and thoughtful feedback throughout my candidature. To Lucy, thank you for the opportunity to initiate and undertake my PhD, and for your ongoing support and encouragement. To Raimondo, thank you for your intellectual guidance and integrity, and for helping me maintain focus and direction for the duration of my PhD. To Monica, thank you for your astute reflections and generosity in providing new opportunities. It has been a pleasure and a privilege to work with all of you.

To my PhD sisters, Amanda Roxburgh and Kerryn Butler: it has been a joy to share this journey with two amazing women. Your strength and intelligence are inspiring, and you have both made this journey tolerable. I have the utmost respect and admiration for the both of you (academically and personally) and am eternally grateful for your support and friendship.

To the Drug Trends team, past and present, many thanks for your ongoing support and friendship. In particular, thanks to Antonia Karlsson, Julia Uporova and Daisy Gibbs, who have kept me well fed and hydrated over the past few months and who have provided much needed respite from my studies. Your kindness and good humour makes coming into the office a pleasure.

I would also like to thank Amy Peacock, who has been a constant support throughout my PhD. Your guidance, thoughtful feedback and flexibility has certainly made the journey an easier one. I would also like to acknowledge the EDRS participants who have generously shared their knowledge and experiences with us over the years.

Many thanks to my family and friends, who have supported me through this journey. Mum and Dad, your unwavering support and generosity have certainly sustained me through some difficult times (both PhD and non-PhD related) – I could not ask for more beautiful parents.

Finally, thank you to Bec for your unconditional love and support. Your unwavering faith in my ability to complete this undertaking, as well as the endless cups of tea and hugs, has kept me going throughout this journey. We have certainly shared heartache and triumph over the past three years, and I cannot wait to have our weekends back!

xi ABSTRACT

Over the past decade, countries worldwide have observed the rapid emergence of substances collectively referred to as ‘new psychoactive substances’ (NPS). To date, hundreds of NPS have been identified; however, for the most part very little is known about these substances. The exponential growth of NPS, combined with uncertainty regarding potential harms, has generated considerable concern amongst policy makers and there is international consensus regarding the need for ongoing monitoring and research into the NPS market. However, much of the research conducted in this area originates from Europe and the United States, with Australian-specific studies relatively scarce.

This thesis aimed to address this gap in Australian specific studies using two data sources: the 2013 National Drug Strategy Household Survey (NDSHS: a general population prevalence survey) and the Ecstasy and related Drugs Reporting System (EDRS: a national survey of high frequency stimulant consumers). Specifically, this thesis aimed to: 1) determine if there is a distinct group of exclusive Australian NPS consumers; 2) examine rates of use of different classes of NPS amongst people who use other illicit substances; 3) examine the motivations associated with NPS use; and 4) explore the purchasing and supply patterns of NPS consumers.

Taken together, these findings suggest that specialised NPS interventions may be unnecessary; rather, existing health services should screen for and be equipped to deal with NPS-related presentations. Furthermore, the diverse and rapidly changing nature of the NPS market demonstrates the need for international collaboration, combined with a rapidly responsive health framework.

xii

TABLE OF CONTENTS

Thesis/dissertation sheet ...... ii

Declarations ...... iii

Originality statement ...... iii

Authenticity statement ...... iv

Supervisor statement ...... v

Thesis by publication statement ...... v

Inclusion of publications statement...... vi

Acknowledgements ...... xi

Abstract ...... xii

List of tables ...... xix

List of figures ...... xxi

List of publications included in this thesis ...... xxii

List of other publications during candidature...... xxiii

List of presentations ...... xxv

1. Introduction ...... 1

1.1 What are new psychoactive substances (NPS): the complexity of current definitions 1

1.2 How are NPS categorised? ...... 3

1.3 Number of NPS identified ...... 4

1.3.1 Number of NPS identified in Australia ...... 5

1.4 What factors have prompted the growth of the NPS market? ...... 5

1.4 Online purchasing behaviours ...... 7

1.5 Prevalence of NPS, internationally and in Australia ...... 8

1.5.1 General population surveys ...... 8

1.5.2 Wastewater-based epidemiology ...... 14

1.5.3 High risk populations ...... 15

1.5.4 Surveys using biological sampling ...... 18

xiii 1.6 Harms associated with NPS use ...... 19

1.6.1 Harms associated with synthetic cannabinoid receptor agonists ...... 21

1.6.2 Harms associated with stimulant NPS ...... 22

1.6.3 Harms associated with opioid NPS ...... 23

1.6.4. Harms associated with psychedelic NPS ...... 24

1.7 Policy responses to the NPS ‘problem’ ...... 24

1.7.1 Legislative responses ...... 24

1.7.2 Health-related responses ...... 31

1.7.3 Australian policy framework ...... 32

1.8 Summary ...... 32

1.9 Thesis structure ...... 33

1.10 References ...... 36

2. Paper one: Typology of new psychoactive substance use among the general Australian population ...... 47

2.1 Copyright statement ...... 48

2.2 Preamble...... 49

2.3 Abstract ...... 50

2.4 Introduction ...... 51

2.5 Method ...... 52

2.5.1 Study design and participants ...... 52

2.5.2 Measures relevant to the current study ...... 53

2.5.3 Statistical analysis ...... 54

2.6 Results ...... 55

2.6.1 Sample characteristics ...... 55

2.6.2 Model selection ...... 56

2.6.3 Latent Class Probabilities and Class Definitions ...... 56

2.6.4 Correlates of subgroup membership ...... 58

2.6.5 Multivariable Multinomial Regression Models ...... 61 xiv

2.7 Discussion ...... 65

2.7.1 Limitations and future research ...... 66

2.8 Conclusions ...... 68

2.9 Supplementary materials ...... 69

2.10 References ...... 72

3. Paper two: New psychoactive substance use among regular psychostimulant users in Australia, 2010-2015 ...... 75

3.1 Copyright statement ...... 76

3.2 Preamble ...... 77

3.3 Abstract ...... 78

3.4 Introduction ...... 79

3.5 Method ...... 81

3.5.1 Study design ...... 81

3.5.2 Participants and procedure ...... 81

3.5.3 Measures relevant to the current study ...... 81

3.5.4 Statistical analysis ...... 82

3.6 Results ...... 83

3.6.1 Demographics ...... 83

3.6.2 Rates of recent NPS use ...... 83

3.6.3 Correlates of NPS use ...... 85

3.7 Discussion ...... 94

3.7.1 Limitations ...... 96

3.8 Conclusions ...... 96

3.9 Supplementary materials ...... 97

3.10 References ...... 99

4. Paper three: Motivations for new psychoactive substance use among regular psychostimulant users in Australia ...... 103

4.1 Copyright statement ...... 104

xv 4.2 Preamble...... 105

4.3 Abstract ...... 106

4.4 Introduction ...... 107

4.5 Method ...... 109

4.5.1 Study design...... 109

4.5.2 Participants and procedure ...... 109

4.5.3 Measures relevant to the current study ...... 110

4.5.4 Statistical analysis ...... 110

4.6 Results ...... 111

4.6.1 Sample characteristics ...... 111

4.6.2 Rates of use ...... 111

4.6.3 Motivations ...... 113

4.7 Discussion ...... 117

4.7.1 Strengths, Limitations and Future Research ...... 119

4.8 Conclusion ...... 120

4.9 Supplementary materials ...... 122

4.10 References ...... 126

5. Paper four: New psychoactive substances: Purchasing and supply patterns in Australia .... 129

5.1 Copyright statement ...... 130

5.2 Preamble...... 131

5.3 Abstract ...... 132

5.4 Introduction ...... 133

5.5 Method ...... 135

5.5.1 Study design...... 135

5.5.2 Participants and procedure ...... 135

5.5.3 Measures relevant to the current study ...... 136

5.5.4 Statistical analysis ...... 136

5.6 Results ...... 137 xvi

5.6.1 Sample characteristics ...... 137

5.6.2 Differences in purchasing patterns across NPS consumers ...... 137

5.6.3 Differences in supply patterns across NPS consumers ...... 138

5.6.4 Main source for obtaining NPS: Online vs non-online ...... 141

5.7 Discussion ...... 143

5.7.1 Limitations ...... 145

5.8 Conclusion ...... 146

5.9 References ...... 147

6. Discussion ...... 151

6.1 Key findings ...... 151

6.2 Contribution to the literature, and policy implications ...... 154

6.2.1 The nature of the Australian NPS market, and predicting the longevity of substances ...... 154

6.2.2 The heterogeneity of NPS consumers, and the intersection with the illicit drug market ...... 157

6.2.3 NPS in the context of polysubstance use, and high-risk behaviours ...... 159

6.2.4 NPS, the internet, and social supply ...... 161

6.3 Limitations and recommendations for future research...... 163

6.3.1 Measuring unintentional NPS use through the inclusion of biological measures ...... 163

6.3.2. Examining NPS use amongst vulnerable populations ...... 165

6.3.3 Distinguishing between NPS, and generalisability of data ...... 166

6.3.4 Reflecting on the definition, and categorisations, of NPS ...... 167

6.3.5 Call for transparency and publicly available data ...... 171

6.4 References ...... 172

7. Conclusion ...... 179

8. Appendices ...... 180

Appendix A: Chapter 15: New & emerging psychoactive substances ...... 180

xvii Appendix B: NPS reported to the EMCDDA ...... 188

Appendix C: I Like the Old Stuff Better than the New Stuff? Subjective Experiences of New Psychoactive Substances...... 220

Abstract ...... 221

Introduction ...... 222

Method ...... 224

Results ...... 225

Discussion ...... 230

References ...... 233

Appendix D: New Psychoactive Substance Use among Regular Psychostimulant Users in Australia, 2010-2016 ...... 236

Key Findings ...... 237

Introduction ...... 238

Method ...... 239

Results ...... 240

Discussion ...... 246

Conclusions ...... 248

References ...... 249

Appendix E: Changing patterns of new and emerging psychoactive substances in Australia ...... 252

xviii

LIST OF TABLES

Table 1: Global prevalence of NPS ...... 11 Table 2: Legal approaches to NPS ...... 26 Table 3: Australian Commonwealth legislative responses to new psychoactive substances .... 29 Table 4: Demographics and risk behaviours according to group ...... 59 Table 5: Demographics and risk behaviours according to group, with polysubstance consumers and amphetamine and cannabis consumers as the referent groups: Multivariable models ...... 63 Table 6: Latent Class Fit Statistics for models with 1 to 8 classes for licit and illicit drug use variables (n=3309)...... 69 Table 7: Demographics and risk behaviours according to group, with polysubstance consumers and amphetamine and cannabis consumers as the referent groups: Bivariate models. ... 70 Table 8: Rates# of NPS amongst RPU, 2010-2015 ...... 84 Table 9: Correlates of recent phenethylamine use amongst RPU, 2011-2015 ...... 86 Table 10: Correlates of recent tryptamine use amongst RPU, 2011-2015 ...... 88 Table 11: Correlates of recent synthetic cannabinoid use amongst RPU, 2011-2015 ...... 90 Table 12: Correlates of recent synthetic cathinone use amongst RPU, 2011-2015 ...... 92 Table 13: Correlates of recent poly NPS use amongst RPU, 2011-2015 ...... 93 Table 14: Number of participants, 2010-2015 ...... 97 Table 15: Recent NPS use: overlap between NPS classes, 2011-2015 ...... 97 Table 16: Rates# of NPS use amongst RPU, 2010-2015 (excludes repeat participants) ...... 98 Table 17: NPS use amongst RPU (n=800), 2014 ...... 112 Table 18: Median scores and differences in motivations for most recent NPS used, 2014 ..... 114 Table 19: ‘It was legal to buy’: post-hoc comparisons across NPS, 2014 ...... 122 Table 20: ‘It was easy to buy on the internet’: post-hoc comparisons across NPS, 2014 ...... 122 Table 21: ‘It was convenient to have it posted to me after buying on the internet’: post-hoc comparisons across NPS, 2014 ...... 123 Table 22: ‘It was good value for money’: post-hoc comparisons across NPS, 2014 ...... 123 Table 23: ‘Thought it would have fewer side effects than traditional illicit drugs’: post-hoc comparisons across NPS, 2014 ...... 123 Table 24: ‘I knew the effect wouldn’t last too long’: post-hoc comparisons across NPS, 2014 124 Table 25: ‘I thought it couldn’t be detected by drug testing’: post-hoc comparisons across NPS, 2014 ...... 124

xix Table 26: ‘I thought it would be safer than traditional illicit drugs’: post-hoc comparisons across NPS, 2014 ...... 124 Table 27: ‘No other drug was available to me at the time’: post-hoc comparisons across NPS, 2014 ...... 125 Table 28: Purchasing and supply patterns across past year NPS consumers, 2016 ...... 139 Table 29: Purchasing and supply patterns among past year NPS consumers who nominated online marketplaces as their main source, 2016 ...... 142 Table 30: Summary of key findings ...... 152 Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) ...... 188 Table 32: Use of stimulant and hallucinogenic substances of interest in the last six months among regular psychostimulant consumers (N=1,260) ...... 226 Table 33: Number of participants, 2010-2016 ...... 241 Table 34: Patterns of NPS use among RPU, 2016 ...... 242 Table 35: Rates# of NPS use amongst RPU, 2010-2016 ...... 244

LIST OF FIGURES

Figure 1: Number and categories of new psychoactive substances formally notified for the first time in Europe, 2005-2017 ...... 4 Figure 2: Number of NPS reported by country, December 2017 ...... 5 Figure 3: Past 12-month licit and illicit drug use according to group for the 6-class solution ... 57 Figure 4: Model 1 – Globally unscheduled substances (GUS) ...... 170 Figure 5: Model 2 – New Psychoactive Substances (NPS) ...... 171 Figure 6: Mean ratings of stimulant drugs on last occasion of use in the last six months ...... 226 Figure 7: Mean ratings of hallucinogenic substances on last occasion of use in the last six months ...... 227 Figure 8: Matched mean ratings of ecstasy and mephedrone (n=66) and ecstasy and methylone (n=46) on last occasion of use in last six months ...... 228 Figure 9: Matched mean ratings of cocaine and mephedrone (n=33) and cocaine and methylone (n=25) on last occasion of use in last six months ...... 228 Figure 10: Matched mean ratings of LSD and 2C-B (n=89) and LSD and 2C-I (n=46) on last occasion of use in last six months ...... 229 Figure 11: Matched mean ratings of LSD and DMT on last occasion of use in last six months (n=107) ...... 229

xxi LIST OF PUBLICATIONS INCLUDED IN THIS THESIS

1. Sutherland, R., Peacock, A., Roxburgh, A., Barratt, M.J., Burns, L. & Bruno, R. (2018). Typology of new psychoactive substance use among the general Australian population. Drug and Alcohol Dependence, 188, 126-134 2. Sutherland, R., Bruno, R., Peacock, A., Lenton, S., Matthews, A., Salom, C., Dietze, P., Butler, K., Burns, L. & Barratt, M.J. (2017). Motivations for new psychoactive substance use among regular psychostimulant users in Australia. International Journal of Drug Policy, 43, pp. 23- 32 3. Sutherland, R., Bruno, R., Dietze, P., Breen, C., Burns, L. & Barratt, M.J. (2017). New psychoactive substances: supply and purchasing patterns in Australia. Human Psychopharmacology: Clinical and Experimental. 32(3) 4. Sutherland, R., Peacock, A., Whittaker, E., Roxburgh, A., Lenton, S., Matthews, A., Butler, K., Nelson, M., Burns, L. & Bruno, R. (2016). New psychoactive substance use among regular psychostimulant users in Australia, 2010-2015. Drug and Alcohol Dependence, 16(1), 110- 118

xxii

LIST OF OTHER PUBLICATIONS DURING CANDIDATURE

1. Sutherland, R. (2018). South Australian Trends in Ecstasy and Related Drug Markets 2017. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No. 195. Sydney, National Drug & Alcohol Research Centre, University of New South Wales. 2. Uporova, J., Karlsson, A., Sutherland, R. & Burns, L. (2018). Australian Trends in Ecstasy and related Drug Markets 2017. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No. 190. Sydney, National Drug and Alcohol Research Centre, UNSW Australia. 3. Sutherland, R. & Barratt, M.J. (2017) ‘New & emerging psychoactive substances’ in A Quick Guide to Drugs & Alcohol, third edition (87-93). Sydney; Drug Info, State Library of NSW 4. Bright, D.A. & Sutherland, R. (2017). “Just doing a favour for a friend”: The social supply of ecstasy through friendship networks, Journal of Drug Issues, 47 (3), 492-504 5. Butler, K., Day, C., Sutherland, R., Van Buskirk., Breen, C., Burns, L. & Larney, S. (2017). Hepatitis C testing in general practice settings: A cross-sectional study of people who inject drugs in Australia. International Journal of Drug Policy, 47, 102-106, http://dx.doi.org/10.1016/j.drugpo.2017.07.008 6. Karlsson, A., Sutherland, R., Butler, K. & Breen, C. (2017). Forms of methamphetamine used in SA and recent use over time: 2007-2016. IDRS Drug Trends Bulletin, April 2017. Sydney: National Drug and Alcohol Research Centre, University of New South Wales. 7. Sutherland, R. and Breen, C. (2017). South Australian Trends in Ecstasy and Related Drug Markets 2016. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No 177. Sydney, National Drug & Alcohol Research Centre, UNSW, Australia. 8. Matthews, A., Sutherland, R., Peacock, A., Van Buskirk, J., Whittaker, E., Burns, L. & Bruno, R. (2016). I like the old stuff better than the new stuff? Subjective experiences of new psychoactive substances, International Journal of Drug Policy, 40, 44-49, https://doi.org/10.1016/j.drugpo.2016.11.004. 9. Sutherland, R., Sindicich, N., Entwistle, G., Whittaker, E., Peacock, A., Matthews, A., Bruno, R., Alati, R., & Burns, L. (2016). Tobacco and e-cigarette use amongst illicit drug users in Australia. Drug and Alcohol Dependence, 159, 35-41, doi: http://dx.doi.org/10.1016/j.drugalcdep.2015.10.035. 10. Van Buskirk, J., Roxburgh, A., Bruno, R., Naicker, S., Lenton, S., Sutherland, R., Whittaker, E., Sindicich, N., Matthews, A., Butler, K. & Burns, L. (2016). Characterising dark net marketplace

xxiii purchasers in a sample of regular psychostimulant users, International Journal of Drug Policy, http://dx.doi.org/10.1016/j.drugpo.2016.01.010. 11. Sutherland, R. & Breen, C. (2016). South Australian Trends in Ecstasy and Related Drug Markets 2015. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No 159. Sydney, National Drug & Alcohol Research Centre, University of New South Wales. 12. Sutherland, R., Breen, C., and Bruno, R. (2016). New psychoactive substance use among regular psychostimulant users in Australia, 2010-2016. EDRS Drug Trends Bulletin, December 2016. Sydney: National Drug and Alcohol Research Centre, University of New South Wales, Australia. 13. Stafford J., Sutherland, R., Burns, L. and Breen, C. (2016). The 2016 EDRS key findings: a survey of people who regularly use psychostimulant drugs. EDRS Drug Trends Bulletin, October 2016. Sydney: National Drug and Alcohol Research Centre, University of New South Wales, Australia. 14. Sutherland, R., Entwistle, G. & Breen, C. (2016). Stimulant and depressant overdose among a sample regular psychostimulant users in Australia, 2007-2015. EDRS Drug Trends Bulletin, July 2016. Sydney: National Drug and Alcohol Research Centre, University of New South Wales. 15. Sutherland, R., Sindicich, N., Barrett, E., Whittaker, E., Peacock, A., Hickey, S., & Burns, L. (2015). Motivations, substance use and other correlates amongst property and violent offenders who regularly inject drugs. Addictive Behaviors, 45, 207-213, doi:10.1016/j.addbeh.2015.01.034. 16. Peacock, A., Sindicich, N., Dunn, M., Whittaker, E., Sutherland, R., Entwistle, G., Burns, L. & Bruno, R. (2016). Co-Ingestion of energy drinks with alcohol and other substances among a sample of people who regularly use ecstasy. Drug and Alcohol Review. 35(3): 352-8. 17. Sutherland, R. & Burns, L. (2015). SA Drug Trends 2014: Findings from the Illicit Drug Reporting System (IDRS). National Drug and Alcohol Research Centre, UNSW Australia. 18. Sutherland, R. & Burns, L. (2015). SA Trends in Ecstasy and Related Drug Markets 2014: Findings from the Ecstasy and Related Drugs Reporting System (EDRS). National Drug and Alcohol Research Centre, UNSW Australia.

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LIST OF PRESENTATIONS

1. Sutherland, R., Barratt, M.J., Burns, L. & Bruno, R. (2017). Changing patterns of new and emerging psychoactive substances in Australia. Australasian Professional Society on Alcohol and other Drugs conference, Melbourne, Australia, 13-15 November 2017

2. Sutherland, R., Peacock, A., Roxburgh, A., Barratt, M.J., Burns, L. & Bruno, R. (2017). Typology of new psychoactive substance use among illicit drug consumers in the Australian general population, Lisbon Addictions: Second European Conference on Addictive Behaviours and Dependencies, Lisbon, Portugal, 26 October 2017

3. Sutherland, R., Barratt, M.J., Burns, L. & Bruno, R. (2017). Changing patterns of new and emerging psychoactive substances in Australia. Lisbon Addictions: Second European Conference on Addictive Behaviours and Dependencies, Lisbon, Portugal, 24 October 2017

4. Sutherland, R., Peacock, A., Roxburgh, A., Barratt, M.J., Burns, L. & Bruno, R. (2017). Typology of new psychoactive substance use among illicit drug consumers in the Australian general population, Novel Psychoactive Substances conference, Vienna, Australia, 23 October 2017

5. Sutherland, R., Barratt, M.J., Burns, L. & Bruno, R. (2017). Changing patterns of new and emerging psychoactive substances in Australia. National Drug and Alcohol Research Centre Annual Symposium, Sydney, Australia, 4 October 2017

6. Sutherland, R. (2017). New Psychoactive Substance Use in Australia, presented to Indonesian Ministry of Social Affairs delegation, National Drug and Alcohol Research Centre, Sydney, Australia, 14 August 2017

7. Breen, C., Burns, L., R, Alati., Bruno, R., Dietze, P., Lenton, S., Butler, K., Entwistle, G., Roxburgh, A., Stafford, J., Sutherland, R. & Van Buskirk, J. (2016). Monitoring psychostimulant use and online markets: data from the EDRS and DNet. Symposium presentation at the 2016 Annual Scientific conference of the Australasian Professional Society on Alcohol and other Drugs (APSAD); 30 October - 2 November; Sydney, Australia. 8. Sutherland, R., Barratt, M. Burns, L. & Bruno, R. (2016). New psychoactive substances: Purchasing and supply patterns, 2016 NDARC Annual Research Symposium, Sydney, UNSW Australia, 12 September 2016 9. Bright, D. & Sutherland, R. (2015). “Just doing a favour for a friend”: Social supply of ecstasy through friendship networks, Illicit Networks Workshop, Montreal, Canada, 16-17 November 2015

xxv 10. Sutherland, R., Bruno, R. & Burns, L. (2015). New Psychoactive Substance Use in Australia, 2011-2015, 2015 National Drug Trends Conference, Customs House, Sydney, 14 October 2015 11. Sutherland, R., Bruno, R. & Burns, L. (2015). New Psychoactive Substance Use among Regular Psychostimulant Users in Australia, Lisbon Addictions 2015: First European conference on addictive behaviours and dependencies, FIL Meeting Centre, Lisbon, 25 September 2015 12. Sutherland, R., Bruno, R. & Burns, L. (2015). New Psychoactive Substance Use among Regular Psychostimulant Users in Australia, 2011-2014, 2015 Annual Research Symposium, UNSW, Sydney, 15 September 2015

13. Sutherland, R. & Burns, L. (2015). The NPS of Oz. The College on Problems of Drug Dependence 77th Annual Scientific Meeting, Arizona Biltmore, Phoenix, 16 June 2015

14. Sutherland, R., Sindicich, N. & Burns, L. (2015). New Psychoactive Substances and Offenders, Compulsory Drug Treatment Program, Parklea, 29 April 2015. 15. Sutherland, R. & Burns, L. (2015). Criminal Motivations and Substance Use Amongst Property and Violent Offenders Who Regularly Inject Drugs, 7th Australasian Drug & Alcohol Strategy Conference, Brisbane Convention & Exhibition Centre, Brisbane, 19 March 2015. 16. Sutherland, R., Sindicich, N. & Burns, L. (2015). Methamphetamine Use Amongst People Who Inject Drugs, Meth Makes Me Forum, Crown Plaza Newcastle, 3 March 2015.

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1. INTRODUCTION Over the past decade, countries worldwide have observed the rapid emergence of substances collectively referred to as ‘new psychoactive substances’ (NPS). NPS are most commonly defined as substances which do not fall under international drug controls, but which may pose a public health threat comparable to substances that are currently prohibited (European Monitoring Centre for Drugs and Drug Addiction, 2016c). To date, hundreds of NPS have been identified (European Monitoring Centre for Drugs and Drug Addiction, 2016c). For the most part, very little is known about these substances (Wood and Dargan, 2012, Wood et al., 2014); however, there have been a number of serious adverse effects associated with both acute and chronic exposures to specific NPS (e.g. European Monitoring Centre for Drugs and Drug Addiction, 2015; Palamar et al., 2016b). Not surprisingly, the exponential growth of NPS, combined with uncertainty regarding their potential harms, has generated considerable concern, with various media outlets referring to the NPS ‘epidemic’ (NZ Herald, 2017, Harvey, 2015, Miranda, 2017, Morton, 2018). Notwithstanding the sensationalist nature of such headlines, it is clear the NPS phenomenon has become a topic of international interest.

The aim of this chapter is to provide an overview of the NPS phenomenon. The chapter starts by presenting definitions and categorisations of NPS. This is followed by an overview of some of the factors that led to the rapid growth and expansion of this market. I then review existing studies which have examined the prevalence of NPS use, both in the general population and sub-samples. Finally, this chapter provides a brief overview of some of the harms associated with NPS use, as well as some of the policy responses that have been implemented to date. This will provide context for the current thesis, which aims to examine both the Australian NPS market and Australian NPS consumers.

1.1 What are new psychoactive substances (NPS): the complexity of current definitions

There are multiple terms in use that refer broadly to new, novel or emerging drugs (Sutherland and Barratt, 2017). This includes terms such as research chemicals, analogues, legal highs, herbal highs, synthetic drugs, designer drugs, bath salts, novel psychoactive substances, emerging psychoactive substances and new psychoactive substances. There is considerable variation in the terms used across countries and studies, with the previous terms often used interchangeably. This lack of standardisation can cause considerable confusion. The terms

1 ‘synthetic drugs’ and ‘legal highs’ are particularly misleading since: 1) many ‘traditional’ illicit drugs (e.g. LSD, methamphetamine, MDMA) are also synthesised; and 2) many countries (including Australia) have moved to prohibit NPS, despite remaining ‘legal’ at the international level. To add to this complexity, some of these terms, despite being used interchangeably, have slightly different definitions (Sutherland and Barratt, 2017; see Appendix A).

To promote standardisation of terminology, the term ‘new psychoactive substances’ (NPS) has been adopted by the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), and the United Nations Office on Drugs and Crime (UNODC) (European Monitoring Centre for Drugs and Drug Addiction, 2016c, United Nations Office on Drugs and Crime, 2013). In Australia, the Intergovernmental Committee on Drugs (IGCD) has also supported use of this term, acknowledging the importance of using language that is consistent with that used by major international organisations (Australian Goverment Department of Health, 2014). However, despite these attempts to standardise terminology, there remains no universally accepted definition of the term NPS, with the definition developed by the EMCDDA the closest thing to a ‘consensus’ that we have:

New Psychoactive Substances (NPS): “a new narcotic or psychotropic drug, in pure form or in preparation, that is not controlled by the 1961 United Nations Single Convention on Narcotic Drugs or the 1971 United Nations Convention on Psychotropic Substances, but which may pose a public health threat comparable to that posed by substances listed in these conventions. These substances are psychoactive in that they stimulate or depress the central nervous system” (European Monitoring Centre for Drugs and Drug Addiction, 2016c, pg.6).

However, both the EMCDDA and the UNODC have acknowledged that they do not strictly adhere to the above definition. For example, the UNODC includes ketamine as an NPS (United Nations Office on Drugs and Crime, 2013). This is despite the fact that ketamine has undergone numerous critical reviews, with the Expert Committee on Drug Dependence consistently concluding that it should not be placed under international control (Commission on Narcotic Drugs, 2015). Furthermore, the EMCDDA have noted that:

“Although a legal definition is provided here, it is also important to move beyond this (i.e. novelty of substances and international control) in order to focus additional attention on emerging drug issues and trends, new types of harm and newly emerging user groups. Therefore, the report sometimes refers to the use of drugs that are not legally classed as NPS but have a history of recreational use with new evidence of harm beginning to emerge (e.g. ketamine), and also a

2 number of controlled substances used in similar settings and target groups, especially ‘club drugs’” (European Monitoring Centre for Drugs and Drug Addiction, 2016c, pg.6).

Thus, in practice, the term NPS refers to substances that: 1) are not scheduled under the United Nations (UN) conventions, and which may or may not pose a public health threat (see section 1.6 for more details); 2) are scheduled but have not previously been well established in recreational drug markets; or 3) which have little literature relating to them. Ketamine, gamma- hydroxybutyrate (GHB), amyl nitrite and nitrous oxide are substances which are sometimes included under the NPS banner (e.g. Holloway and Bennett, 2018). These substances have been established in Australia's recreational drug market for many years (e.g. Brett, 1997, Edwards and Ujma, 1995, Jansen, 2000, Kam and Yoong, 1998), hence the chapters that present empirical work (i.e. chapters 2 to 5) do not include these substances as NPS. Conversely, dimethyltryptamine (DMT) and 4-bromo-2,5-dimethoxyphenethylamine (2C-B), although not uniformly defined as NPS, are included in this thesis as NPS because they have not been previously well-established within Australia's recreational drug market (i.e. the first peer- reviewed papers examining recreational, as opposed to religious or sacramental, use of DMT and 2C-B in Australia were published in 2010 (Cakic et al., 2010) and 2014 (Barratt et al., 2014, Burns et al., 2014a), respectively).

1.2 How are NPS categorised?

There is no standardised classification system for NPS. However, they are most often grouped together according to either psychoactive effect or chemical structure (Measham and Newcombe, 2016). The EMCDDA use of the latter of these two approaches (i.e. chemical structure) and have identified 13 categories of NPS: aminoindanes, arylalkylamines, arylcyclohexylamines, benzodiazepines, synthetic cannabinoid receptor agonists (SCRA), synthetic cathinones, indolalkylamines (i.e. tryptamines), opioids, phenethylamines, piperazine derivates, piperidines and pyrrolidines, plants and extracts, and others. SCRA and synthetic cathinones are the largest of these groups (see Figure 1; European Monitoring Centre for Drugs and Drug Addiction, 2017b). For a brief overview of these NPS categories, please refer to Appendix A (this classification system is adhered to in paper two of this thesis, with all papers distinguishing across NPS classes where possible).

In contrast, the UNODC often groups NPS into six categories, based on their pharmacological effects. These categories are as follows: synthetic cannabinoid receptor agonists (SCRA), dissociatives, hallucinogens, sedatives and hypnotics, stimulants and opioids. Using these categories, the UNODC has reported that 36% of the NPS reported from 2008 to 2017 were

3 stimulants, 32% SCRA, 16% classical hallucinogens, 4% opioids, 4% sedative/hypnotics, 3% dissociatives, and 5% were not yet assigned (United Nations Office on Drugs and Crime, 2018b).

1.3 Number of NPS identified

A defining feature of the NPS phenomenon is the unprecedented and exponential rate at which substances are emerging. To date, hundreds of NPS have been identified, with the NPS market monitored by two main organisations: the EMCDDA and the UNODC. The EMCDDA monitors NPS in the European Union (EU) through the Early Warning System (EWS), whilst the UNODC monitors NPS among its member states through the Global SMART Programme (for further details see King and Sedefov, 2007, United Nations Office on Drugs and Crime, 2018a). The EWS, run by the council of the European Union, currently monitors over 670 NPS with the number of ‘new’ substances identified increasing every year from 2005 to 2014 (see Figure 1). More recently, this growth has plateaued (98 NPS detected in 2015) and now seems to be declining (66 and 51 NPS identified in 2016 and 2017, respectively; see Table 3 for the full list of NPS reported to the EMCDDA from 2005-2017). Similarly, between 2009 and 2017, 803 NPS were reported to the UNODC, from over 110 countries and territories (United Nations Office on Drugs and Crime, 2018b). This number differs from the EMCDDA due to differences in the way NPS are classified (as previously noted in section 1.1) and the regions that are monitored.

Figure 1: Number and categories of new psychoactive substances formally notified for the first time in Europe, 2005-2017

Source: European Monitoring Centre for Drugs and Drug Addiction (2018)

Regardless of which figures are considered, it may be argued that the number of NPS identified exaggerates the NPS ‘problem’, since many of these substances are transient. As noted by the Commission on Narcotic Drugs, “many NPS have only been reported by a small number [of

4 countries] in a given year and some seem to have disappeared completely from the market” (United Nations Office on Drugs and Crime, 2016a; pg.4), with a much smaller ‘core’ group of approximately 80 NPS becoming established in the global drug market (i.e. reported every year from 2009-2015; United Nations Office on Drugs and Crime, 2018c).

1.3.1 Number of NPS identified in Australia

Australia is a member state of the UNODC, and hence reports the detection of NPS to the UNODC through the Global SMART Programme. Throughout 2009-2012 Australia reported 33 NPS to the UNODC, most of which were synthetic cathinones and phenethylamines (United Nations Office on Drugs and Crime, 2013). However, from 2013 onwards the UNODC has not made its full list of NPS publicly available, and only provides country breakdowns to early warning advisory clients. Therefore, it is unknown exactly how many (and which) NPS have been detected in Australia from 2013 onwards, although the UNODC has reported that total number of NPS detected in Australia is somewhere between 101 and 200 (see Figure 2).

Figure 2: Number of NPS reported by country, December 2017

Source: United Nations Office on Drugs and Crime (2018a), pg.5

1.4 What factors have prompted the growth of the NPS market?

The rapid growth of the NPS market has been facilitated by a number of factors, one of which was the MDMA (ecstasy) shortage that occurred in the mid-2000s. This was caused by an international crackdown on safrole (3,4-methylenedioxyallybenzene, a liquid extracted from sassafras plants), a precursor used in MDMA production (Mounteney et al., 2018). Following this

5 worldwide shortage, traffickers turned to alternative substances to meet the continuing demand for ecstasy (United Nations Office on Drugs and Crime, 2018b). Shortly thereafter, analysis of substances sold as ecstasy showed that tablets/powder had low MDMA content and often contained other substances, such as mephedrone, methylone, ethylone, MDPV, BZP, mCPP, 2C- B, 4-MEC, 4-FA and TFMPP (United Nations Office on Drugs and Crime, 2014, United Nations Office on Drugs and Crime, 2018b, Brunt et al., 2017, Guirguis et al., 2017, Brunt et al., 2011, Vogels et al., 2009). That is, consumers who thought they were using ecstasy were (unintentionally) consuming a range of NPS. In the late 2000s a similar phenomenon was observed in relation to amphetamine production, whereby a shortage of precursors resulted in two new substances, namely 4-FA and 4-methyl-BMK, being sold as amphetamine (European Monitoring Centre for Drugs and Drug Addiction, 2016b). More recently ‘new’ synthetic opioids, mainly fentanyl analogues, have been found as contaminants in heroin (Ciccarone et al., 2017, Moore et al., 2017, Quintana et al., 2017, Santacroce et al., 2018).

The ability to invent and synthesise a wide range of new substances has been expedited by improved technological capability in China and India, as well as the ability to produce new substances in small laboratories (Reuter and Pardo, 2017, European Monitoring Centre for Drugs and Drug Addiction, 2016b). Furthermore, globalised supply chains and the expansion of online drug markets have facilitated the rapid distribution of such substances. The first online drug transaction is reported to have occurred in 1971 (Buxton & Bingham, 2015), and over the past decade there has been an increasing awareness of, and interest in, surface web markets and cryptomarkets (Walsh, 2011). Surface web markets are accessible via typical search engines (e.g. Google, Yahoo), and cryptomarkets (also known as dark net markets) exist in a ‘hidden’ part of the internet not accessible through standard web browsers. Cryptomarkets host multiple sellers or vendors and have been facilitated by the development of encryption, digital currencies and anonymous browsing (Barratt & Aldridge, 2016; Mounteney, Griffiths, & Vandam, 2016; Van Buskirk, Roxburgh, et al., 2016). The expansion of these online drug markets have provided new opportunities for the supply and purchase of drugs, with internet sales of NPS now an international phenomenon and with many online stores advertising worldwide delivery (European Monitoring Centre for Drugs and Drug Addiction, 2011a).

Recognising the opportunity to purchase bulk quantities of NPS from China and the potential for considerable profit, individuals selling illicit substances have developed a range of sales channels on both the open market (i.e. bricks-and-mortar shops and web shops on the surface web) and illicit drug markets (i.e. street market and web shops on the dark net). Substances sold on the

6 open market are often labelled as ‘not for human consumption’, ‘for research only’, ‘novelty items’, ‘natural’ or ‘herbal’ extracts. They may also be sold as ‘legal’ replacements for cannabis, amphetamine, MDMA, cocaine and heroin (European Monitoring Centre for Drugs and Drug Addiction, 2016b). The finished products compete with controlled drugs but have the advantage of being sold openly in shops — known as ‘head shops’ or ‘smart shops’. However, in Australia, changes to legislation have largely funnelled the sale of popular NPS from the open market to web shops on the dark net (Van Buskirk et al., 2017). For more information on this issue the reader is directed to chapter seven of the 2016 EU Drug Markets Report (European Monitoring Centre for Drugs and Drug Addiction, 2016b).

1.4 Online purchasing behaviours

Despite NPS being readily available on online marketplaces (Van Buskirk et al., 2017), and to a lesser extent retail outlets (European Monitoring Centre for Drugs and Drug Addiction, 2016b), it remains unclear to what extent Australian consumers use these avenues to source NPS. Data from the Ecstasy and related Drugs Reporting System show that although an increasing proportion of its sample have purchased substances online, most participants continue to obtain established illicit drugs (e.g. ecstasy, LSD and cannabis) from these marketplaces, with relatively few participants reporting that they had purchased NPS (Karlsson & Burns, 2018). This is consistent with the online availability of substances, with cannabis, pharmaceuticals and MDMA the most commonly listed substances on dark net marketplaces (Roxburgh et al., 2017).

There is some evidence that NPS consumers are more likely to purchase drugs online than other drug consumers (Burns et al., 2014; Van Buskirk, Roxburgh, et al., 2016), however, for the most part they appear to obtain these substances from ‘in-person’ sources such as friends and dealers (Burns et al., 2014; European Commission, 2014; Stephenson & Richardson, 2014), although this can vary across studies and countries (for example, see Global Drug Survey, 2016; O'Brien, Chatwin, Jenkins, & Measham, 2015; Soussan & Kjellgren, 2016). Furthermore, studies examining individual types or categories of NPS suggest that differences may exist across consumers. For example, friends have been found to be the most common source for obtaining DMT (Australia; Cakic, Potkonyak, & Marshall, 2010) and mephedrone (Ireland; McElrath & O’Neill, 2011), whilst other studies have found that the internet was most common source for obtaining plant-derived NPS (Sweden; Björnstad, Hultén, Beck, & Helander, 2009) and NBOMe (international; Lawn, Barratt, Williams, Horne, & Winstock, 2014). With regards to synthetic cannabinoids, retail outlets have been found to be a common source for obtaining these substances (Barratt, Cakic, & Lenton, 2013; Gunderson, Haughey, Ait-Daoud, Joshi, & Hart,

7 2014). At present, it is unclear if such findings represent genuine differences across NPS, or if they are the result of different methodologies, geographical differences and/or other study artefacts. This question is addressed in paper four, which examines the purchasing and supply patterns amongst a sample of 296 NPS consumers in Australia.

1.5 Prevalence of NPS, internationally and in Australia

Whilst international concern about the growth of the NPS market has been expressed (e.g. European Monitoring Centre for Drugs and Drug Addiction, 2016c; United Nations Office on Drugs and Crime, 2013), the number of people who use these substances, and the harms associated with such use (section 1.6), remain unclear. Furthermore, different data collection methods and categorisations of NPS, make intercountry comparisons problematic. As such, the extent to which NPS are used globally remains uncertain, with prevalence rates varying considerably across countries (see Table 1).

1.5.1 General population surveys

1.5.1.1 Prevalence of NPS in Europe

To the best of my knowledge, only two studies have administered the same question across countries in order to measure NPS use. That question is:

“New substances that imitate the effects of illicit drugs such as cannabis, ecstasy, cocaine, etc. may now sometimes be available. They are sometimes called [INSERT ‘local name’ such as, ‘legal highs’, ‘research chemicals’] and can come in different forms, for example herbal mixtures, powders, crystals or tablets. Have you ever used such substances?” (ESPAD Group, 2016b).

The first of these studies was conducted by the European Commission and involved surveys with young Europeans aged 15 to 24 years across 28 EU countries. Data from these surveys showed that in 2014, 3% of people in the 15-24 age-group had used an NPS in the past year, with use highest in Ireland, Spain and France (5% each) and lowest in Cyprus and Malta (0%; European Commission, 2014). The second study, the European School Survey Project on Alcohol and Other Drugs; EPSAD), involved surveys with students aged 15-16 (i.e. students who turned 16 in the calendar year of the survey and were present in the classroom on the day of the survey) across 35 EU countries. Data from these surveys showed that in 2015, 3% of students had used an NPS in the past year, with use being highest in Estonia and Poland (8% each) and lowest in Finland, Moldova, Netherlands, Portugal, Norway, Former Yugoslav Republic of Macedonia, Faroes, Denmark and Belgium (1% each; ESPAD Group, 2016a).

However, these studies have not yet been replicated and it is more common for individual countries to capture NPS use through existing household or school surveys. Considerable variation occurs in the regularity - and indeed existence - of such surveys. In Ireland, 3% of adults aged 15 years and older reported lifetime use of any NPS in 2014/15, and 0.7% reported use within the last year. Use was highest in the younger age brackets, with 1.9% of people aged 15- 24 and 1.3% of people aged 25-34 reporting past year NPS use. Among people aged 35-44 the figure was 0.4%, and for people aged 45-54 it was 0.2% (National Advisory Committee on Drugs and Alcohol, 2016).

The Crime Survey for England and Wales found that 0.4% of people aged 16-59 reported past- year NPS use in 2016/17, a decrease from 0.7% in 2015/16. Mephedrone, which was not classified as an NPS in the survey, had been used by 0.1% of people aged 16-59 in 2016/17, a decrease from the 0.3% reported for 2015/16 (and down from 1.3% in 2010/11; Home Office, 2017).

1.5.1.2 Prevalence of NPS use in the United States

In the United States, the Monitoring the Future Survey (a nationally representative survey of secondary school students from grade 8-12) has been asking about the use of ‘synthetic marijuana’ and ‘bath salts (synthetic stimulants)’ since 2012. In 2017, 2.8% of adolescents (grades 8-12) reported past-year use of SCRA, and 0.5% reported past-year use of synthetic stimulants. Both figures have steadily decreased since 2012, when they were 8% (SCRA) and 0.9% (synthetic stimulants; Johnston et al., 2015, Palamar et al., 2017).

Amongst adult samples, prevalence rates are lower. The National Survey of Drug Use and Health (NSDUH) found that during 2009-2013, 1.2% of Americans aged 12-34 had used NPS in their lifetime, most commonly psychedelic tryptamines (primarily DMT) (Palamar et al., 2015). Prevalence of self-reported use of NPS increased from 2009 to 2013, however in 2015 changes were made to the NSDUH questionnaire such that substances that were previously categorised as NPS were now incorporated under broader drug headings. For example, DMT, AMT and 5- MeO-DIPT were included as hallucinogens (Center for Behavioral Health Statistics and Quality, 2016). Therefore, rates of ‘any’ NPS use are no longer reported.

1.5.1.3 Prevalence of NPS use in Asia

The prevalence of NPS use in Asia is largely unknown. In 2016, a national household survey conducted in Thailand (n=32,410) reported that 49.7% of the population had used NPS in their lifetime, with past month use being 14.9%. These figures are substantially higher than those

9 reported by other countries. This discrepancy might be partly attributable to the definition used: “unprescribed analgesics, cough syrup, sedatives, antihistamines, antihistamine cocktails, kratom leave, kratom cocktail, ecstasy, and ketamine” (Wonguppa and Kanato, 2017, pg. 112). The broad nature of this definition highlights the difficulty in trying to obtain global estimates of NPS use.

1.5.1.4. Prevalence of NPS use in Australia

In Australia, the national prevalence rates for NPS use were collected for the first time in 2013, through the National Drug Strategy Household Survey (NDSHS). The NDSHS is conducted on a triennial basis and collects data from the Australian residential population. A multistage stratified sampling methodology is used, designed to provide a close-to-random sample to obtain data on drug and alcohol use in the Australian population over 14 years of age. In 2013, 1.2% of the general population had used SCRA in the last 12 months, and 0.4% had used another NPS (Australian Institute of Health & Welfare, 2014). In 2016, past-year synthetic cannabinoid use had declined significantly to 0.3% of the population, whereas other NPS use remained stable, also at 0.3% (Australian Institute of Health & Welfare, 2017).

Summary: Excluding the Thai population survey (Wonguppa and Kanato, 2017), prevalence of lifetime NPS use ranges from 0% to 22% ; annual prevalence ranges from 0% to 5%.

Table 1: Global prevalence of NPS Country Year Sample (age) Substance Lifetime Past year Past month Source Prevalence prevalence prevalence % % % Europe EU28* 2014 15-24 ‘Any’ NPS 8 3 1 Flash Eurobarometer 401 (European Commission, 2014) EU36** 2015 15-16 ‘Any’ NPS 4 3 ESPAD Report 2015 (EMCDDA, 2016a) Ireland 2014; 2015 15-24; 15-16 ‘Any’ NPS 22; 7 5; 5 4 Flash Eurobarometer 401; ESPAD Report 2015 Spain 2014; 2015 15-24; 15-16 ‘Any’ NPS 13; 4 5; 3 3 Flash Eurobarometer 401; ESPAD Report 2015 Slovenia 2014; 2015 15-24; 15-16 ‘Any’ NPS 13; 3 4; 2 3 Flash Eurobarometer 401; ESPAD Report 2015 France 2014; 2015 15-24; 15-16 ‘Any’ NPS 12; 4 5; 4 3 Flash Eurobarometer 401; ESPAD Report 2015 United Kingdom 2014 15-24 ‘Any’ NPS 10 4 2 Flash Eurobarometer 401 Slovakia 2014; 2015 15-24; 15-16 ‘Any’ NPS 10; 4 3; 3 1 Flash Eurobarometer 401; ESPAD Report 2015 Latvia 2014; 2015 15-24; 15-16 ‘Any’ NPS 9; 7 2; 4 1 Flash Eurobarometer 401; ESPAD Report 2015 Poland 2014; 2015 15-24; 15-16 ‘Any’ NPS 9; 10 2; 8 1 Flash Eurobarometer 401; ESPAD Report 2015 Belgium 2014; 2015 15-24; 15-16 ‘Any’ NPS 8; 1 2; 1 1 Flash Eurobarometer 401; ESPAD Report 2015 Croatia 2014; 2015 15-24; 15-16 ‘Any’ NPS 7; 7 2; 6 2 Flash Eurobarometer 401; ESPAD Report 2015 Estonia 2014; 2015 15-24; 15-16 ‘Any’ NPS 7; 10 2; 8 1 Flash Eurobarometer 401; ESPAD Report 2015 Bulgaria 2014; 2015 15-24; 15-16 ‘Any’ NPS 7; 8 1; 6 1 Flash Eurobarometer 401; ESPAD Report 2015 Sweden 2014; 2015 15-24; 15-16 ‘Any’ NPS 7; 4 3; 2 1 Flash Eurobarometer 401; ESPAD Report 2015 Austria 2014; 2015 15-24; 15-16 ‘Any’ NPS 7; 3 2; 2 0 Flash Eurobarometer 401; ESPAD Report 2015 Portugal 2014; 2015 15-24; 15-16 ‘Any’ NPS 7; 1 3; 1 1 Flash Eurobarometer 401; ESPAD Report 2015 Luxembourg 2014 15-24 ‘Any’ NPS 7 2 2 Flash Eurobarometer 401 Italy 2014; 2015 15-24; 15-16 ‘Any’ NPS 6; 6 1; 5 2 Flash Eurobarometer 401; ESPAD Report 2015 Netherlands 2014; 2015 15-24; 15-16 ‘Any’ NPS 6; 2 2; 1 1 Flash Eurobarometer 401; ESPAD Report 2015 Lithuania 2014; 2015 15-24; 15-16 ‘Any’ NPS 6; 5 1; 4 1 Flash Eurobarometer 401; ESPAD Report 2015 Greece 2014; 2015 15-24; 15-16 ‘Any’ NPS 5; 3 2; 2 1 Flash Eurobarometer 401; ESPAD Report 2015 Romania 2014; 2015 15-24; 15-16 ‘Any’ NPS 5; 5 1; 3 0 Flash Eurobarometer 401; ESPAD Report 2015 Hungary 2014; 2015 15-24; 15-16 ‘Any’ NPS 5; 4 1; 3 0 Flash Eurobarometer 401; ESPAD Report 2015 Germany 2014 15-24 ‘Any’ NPS 4 1 0 Flash Eurobarometer 401 Czech Republic 2014; 2015 15-24; 15-16 ‘Any’ NPS 4; 7 2; 4 0 Flash Eurobarometer 401; ESPAD Report 2015

11 Table 1 (continued): Global prevalence of NPS Country Year Sample (age) Substance Lifetime Past year Past month Source Prevalence prevalence prevalence % % % Denmark 2014; 2015 15-24; 15-16 ‘Any’ NPS 4; 1 2; 1 1 Flash Eurobarometer 401; ESPAD Report 2015 Finland 2014; 2015 15-24; 15-16 ‘Any’ NPS 2; 1 1; 1 0 Flash Eurobarometer 401; ESPAD Report 2015 Malta 2014; 2015 15-24; 15-16 ‘Any’ NPS 2; 4 0; 3 0 Flash Eurobarometer 401; ESPAD Report 2015 Cyprus 2014; 2015 15-24; 15-16 ‘Any’ NPS 0; 4 0; 2 0 Flash Eurobarometer 401; ESPAD Report 2015 Albania 2015 15-16 ‘Any’ NPS 4 2 ESPAD Report 2015 Faroes 2015 15-16 ‘Any’ NPS 3 1 ESPAD Report 2015 FYR Macedonia 2015 15-16 ‘Any’ NPS 4 1 ESPAD Report 2015 Georgia 2015 15-16 ‘Any’ NPS 7 3 ESPAD Report 2015 Iceland 2015 15-16 ‘Any’ NPS 3 2 ESPAD Report 2015 Liechtenstein 2015 15-16 ‘Any’ NPS 4 3 ESPAD Report 2015 Moldova 2015 15-16 ‘Any’ NPS 2 1 ESPAD Report 2015 Monaca 2015 15-16 ‘Any’ NPS 4 4 ESPAD Report 2015 Montenegro 2015 15-16 ‘Any’ NPS 3 2 ESPAD Report 2015 Norway 2015 15-16 ‘Any’ NPS 1 1 ESPAD Report 2015 Ukraine 2015 15-16 ‘Any’ NPS 4 3 ESPAD Report 2015 Ireland 2014/15 15+ ‘Any’ NPS 3 0.7 0.1 Drug Prevalence Survey (National Advisory Committee on Drugs and Alcohol, 2016) England/Wales 2016/17 16-59 ‘Any’ NPS 0.4 Crime Survey for England and Wales (Home Office, 2017) England/Wales 2016/17 16-59 Mephedrone 0.1 Crime Survey for England and Wales (Home Office, 2017) United States US 2017 Grade 8-12 SCRA 2.8 Monitoring the Future Survey students (Palamar et al., 2017) US 2017 Grade 8-12 Synthetic 0.5 Monitoring the Future Survey students stimulants (Palamar et al., 2017) US 2009-2013 12-34 ‘Any’ NPS 1.2 National Survey of Drug Use and Health (Palamar et al., 2015)

Table 1 (continued): Global prevalence of NPS Country Year Sample (age) Substance Lifetime Past year Past month Source Prevalence prevalence prevalence % % % Asia Thailand 2016 15–64 ‘Any’ NPS*** 49.7 14.9 (Wonguppa and Kanato, 2017) Australia Australia 2016 14+ SCRA 2.8 0.3 National Drug Strategy Household Survey (Australian Institute of Health & Welfare, 2017) Australia 2016 14+ ‘Other’ NPS 1 0.3 National Drug Strategy Household Survey (Australian (excluding Institute of Health & Welfare, 2017) SCRA) Note: boxes are shaded grey where prevalence was not reported *Average of the 28 European countries surveyed **Average of the 36 European countries surveyed ***Defined by the survey as “unprescribed analgesics, cough syrup, sedatives, antihistamines, antihistamine cocktails, kratom leave, kratom cocktail, ecstasy, and ketamine” Please also refer to https://dataunodc.un.org/drugs/prevalence_of_nps for more detail in the European context

13 Limitations of school and household surveys: The use of general population surveys to assess substance use has several limitations. Firstly, they exclude or under-represent certain segments of the population; this includes individuals who are homeless or incarcerated, groups which tend to have high levels of substance use. Secondly, they rely on self-report data; it is possible that participants either underreport their usage, or incorrectly identify the NPS being consumed. Thirdly, the data from school and household surveys refers to intentional NPS use only (i.e. intentionally consuming what they thought was an NPS), with rates of ‘unintentional’ NPS use likely to be much higher. That is, general populations surveys do not corroborate self-report with chemical analysis, and as such unintentional NPS use (e.g. consuming what they thought was LSD but was actually 25I NBOMe) is not captured.

Finally, most of the data presented in this section measures NPS as a single entity, with general population surveys having limited capacity to detect low prevalence use of hundreds of different substances. That is, general population surveys lack detailed information on which NPS are consumed. Paper two addresses this limitation by grouping NPS by chemical structure (i.e. the classification system used by the EMCDDA) and examining Australian trends in use of the different classes over time.

1.5.2 Wastewater-based epidemiology

Wastewater analysis has increasingly been recognised as a useful tool for monitoring substance use in the population (Kinyua et al., 2015), and is often termed ‘wastewater-based epidemiology’ (WBE). WBE is a tool for determining population scale use of a particular substance; that is, the total amount of a drug used by a whole community or population, rather than by individuals or households. It is based on the chemical analysis of specific human metabolic excretion products (biomarkers) in wastewater.

González-Mariño et al. (2016b) applied WBE to investigate the presence of 17 synthetic cathinones in four European countries. They detected seven substances, with mephedrone and methcathinone being detected most often. Population-normalized loads were used to evaluate the pattern of use, which indicated the highest consumption in the United Kingdom (UK), followed by Spain and Italy; these results were congruent with the prevalence data from European population surveys (González-Mariño et al., 2016b). No analytes were found in Norway, with another study detecting very little use in Italy (González-Mariño et al., 2016a).

In Australia, WBE has been utilised to monitor NPS for several years. Results from South Australia show that levels of mephedrone and methylone peaked in 2010 and 2011 respectively, but have

declined steadily since then (Australian Criminal Intelligence Commision, 2018, Lai et al., 2013). In contrast, a study of wastewater samples in Queensland (QLD) during 2011-2013 did not detect any mephedrone, but methylone was detected in 45% of the samples (Thai et al., 2016). More recently, Tscharke et al. (2016) analysed wastewater samples from Adelaide bimonthly during 2011-2015, and assessed 11 NPS, including BZP, TFMPP, methcathinone, methylone, mephedrone, MDPV, alpha-PVP, PMA, 25C-NBOMe, 25B-NBOMe and 25I-NBOMe. They found that rates of NPS use varied significantly throughout the period, with large month-to-month fluctuations. Temporal trends revealed decreasing rates of BZP and methylone use, whereas the use of other NPS fluctuated without apparent directionality.

In June 2016, the National Wastewater Drug Monitoring Program (NWDMP) was developed as part of the ‘Framework for a National Response to New Psychoactive Substances’. Initially it monitored the consumption of 13 substances, four of which were NPS (mephedrone, methylone, JWH-018 and JWH-073). The most recent report released by the Australian Criminal Intelligence Commission stated that only a few sites showed evidence of methylone and mephedrone use. In December 2017, there were 23 national mephedrone detections (vs. 9 in 2016) and 65 national methylone detections (vs. 58 in 2016; these were mostly below quantification levels) (Australian Criminal Intelligence Commision, 2017, 2018). Neither of the synthetic cannabinoid compounds were detected in 2016 or 2017, and as such are no longer being monitored by the NWDMP (Australian Criminal Intelligence Commision, 2018).

Limitations of wastewater-based epidemiology: WBE is limited in that it can only detect a small number of NPS and only substances that are specifically searched for; that is, it cannot detect drugs that are not yet known. Furthermore, it offers no information about who are using these substances, or how the substances are consumed (e.g. route of administration, dosage or frequency of use). It also does not indicate whether the consumption was intentional or unintentional (Brunt, 2010).

There are also several technical limitations associated with WBE. These include degradation during transport, different applications of analytical techniques, leakage of wastewater in the sewer system, and methods of back-calculation of per capita consumption. For further information, see van Nuijs et al., 2011.

1.5.3 High risk populations

The limitations of general population surveys and wastewater epidemiology, outlined above, highlight the importance of supplementing these approaches with further data collection. This should include surveys of populations that are at a higher risk of substance use. Indeed, whilst

15 general population estimates of NPS use appear relatively low (and declining), research indicates that rates of use are elevated amongst certain groups (e.g. Bonar et al., 2014, Bretteville-Jensen et al., 2013, Burns et al., 2014a, European Monitoring Centre for Drugs and Drug Addiction, 2017c, Giese et al., 2015, Hope et al., 2016, Janikova et al., 2016, Kelly et al., 2013, Moore et al., 2013, Palamar et al., 2016a, Sindicich and Burns, 2014, Vento et al., 2014, Hannemann et al., 2017). These groups include young people, existing drug consumers and homeless and incarcerated populations.

1.5.3.1 NPS use among young people

The general population surveys indicate that younger people show relatively high rates of NPS use. That is, NPS consumption is self-reported most commonly among young adults. A survey of seven universities in Wales found that just under 15% of students had used NPS in the 2015- 2016 academic year, ranging from 4.5% in one university to 19.2% in another (although the definition of NPS was quite broad and included nitrous oxide, ketamine and GHB/GHL; Holloway and Bennett, 2018). Similarly, a 2014 survey of German adolescents aged 15–18 showed that 6% had consumed a herbal smoke blend containing SCRAs at least once in their life and that 1% had consumed such a blend in the past 30 days (European Monitoring Centre for Drugs and Drug Addiction, 2017d). In Australia, a 2014 survey of 1126 students from 11 secondary schools found that 3% had ever tried an NPS, with 2.4% reporting the use of SCRA and 0.4% reporting the use of a synthetic stimulant (Champion et al., 2015).

1.5.3.2 NPS use among people who use illicit drugs recreationally

There is considerable research showing that NPS use is relatively common among people who use illicit drugs and among people engaged in the night time economy, not including those who inject drugs (Bonar et al., 2014, Bretteville-Jensen et al., 2013, Burns et al., 2014a, Kelly et al., 2013, Moore et al., 2013, Palamar et al., 2016a, Sindicich and Burns, 2014, Vento et al., 2014, Hannemann et al., 2017). A study of 273 nightclub attendees in Rome reported a 35% lifetime prevalence rate of SCRA use and a 18.8% lifetime rate of mephedrone use (Vento et al., 2014). Similarly, a study of 682 adults attending electronic dance music events at nightclubs and festivals in New York City in 2015 found that 35.1% reported lifetime use of any NPS (most commonly SCRA) (Palamar et al., 2016a). With regards to NPS use over the past 12 months, a study of 1,571 nightlife attendees in Munich found that 20% reported NPS use, most commonly SCRA, methylone and MXE (Hannemann et al., 2017). A survey of 1,740 nightlife venue patrons in the US found that 8.2% had used SCRA and 1.1% had used mephedrone in the past year (Kelly et al., 2013). The 2018 Global Drug Survey (GDS), the largest international survey on substance

use, found considerable variation in past year NPS use across countries, with use highest in the United States (20%), and with 9.5% of Australian participants reporting use (Winstock et al., 2018).

1.5.3.3 NPS use among people who inject drugs

There is some evidence of NPS being used among people who inject drugs (PWID), although evidence of this seems to be largely restricted to Europe (Emmanuel and Attarad, 2006, Giese et al., 2015, Hope et al., 2016, Janikova et al., 2016, Péterfi et al., 2014, Tarján et al., 2017, Van Hout and Bingham, 2012, Wiessing and Folch, 2016). Janikova et al. (2016) found that 11 countries reported NPS use in populations of people who use drugs heavily, with the injecting of NPS reported in seven of these countries. Similarly, the EMCDDA has documented intravenous NPS use in Austria, Finland, Germany, Hungary, Latvia, Slovenia, Sweden and the UK (European Monitoring Centre for Drugs and Drug Addiction, 2017c), with the injection of NPS appearing to be most common in Hungary. Indeed, Rácz et al. (2016) found that up to 80% of clients attending Hungary’s largest needle exchange program in 2015 reported that they had used an NPS (mephedrone, MDPV, 4-MEC, pentedrone), replacing heroin and amphetamines (Hope et al., 2016, Wiessing and Folch, 2016). In Slovenia, the use of 3-MMC was reported as a replacement for cocaine among intravenous opiate users (Sande, 2016).

There is also evidence of stimulant drug injection by a subgroup of men who have sex with men (MSM), although this is largely limited to a small number of studies that have been conducted in Europe (European Monitoring Centre for Drugs and Drug Addiction, 2017c). This practice is referred to as ‘slamming’ and generally takes place in the context of sex parties.

1.5.3.4 NPS use among homeless and incarcerated populations

There is emerging evidence of NPS, especially SCRA, being used among homeless and incarcerated populations, although the empirical data are patchy. The EMCDDA has noted reports of NPS use amongst prisoners in 15 European countries, with rates of use ranging from 2% in Portugal to over 30% in some prisons in the United Kingdom (European Monitoring Centre for Drugs and Drug Addiction, 2017c). Indeed, SCRA use in prison seems to be a particular problem in the UK, with reports of ‘spice’ seizures in prisons in England and Wales increasing from 15 in 2010 to 737 in 2014. Furthermore, a survey of 1376 inmates from eight prisons in England and Wales found that ‘spice’ was the second most commonly used substance (10%) after cannabis (13%) (Newcombe and Christensen, 2016). In addition, ‘spice’ was the only drug which people reported using more often inside prison than in the two months prior to their incarceration (European Monitoring Centre for Drugs and Drug Addiction, 2017c).

17 There has also been extensive media coverage of 'spice zombies' among the UK homeless population (Alexandrescu, 2018). However, empirical research on this topic this is scant. One of the few studies in this area was conducted by Giese et al. (2015), who identified the self- reported use of alpha-PVP among homeless ‘chaotic’ PWID in Ireland, a finding which was supported by urinalysis. In addition, Ralphs et al. (2017) examined SCRA use in an English adult male prison and found there had been a rise in SRCA use, which posed a challenge to the management of offenders.

To date, there is little empirical evidence of SCRA - or any NPS - being used among homeless or incarcerated populations in Australia. In 2017, a survey of 888 PWID found that 5% of the sample reported SCRA use in the past six months (Karlsson and Burns, 2018). However, a review of the literature found no prior studies that had specifically examined NPS use among Australian homeless or incarcerated populations.

Limitations of sub-sample surveys: The studies cited above report the intentional use of NPS; that is, self-reports by people who intentionally consume what they think are NPS. However, as with any illicit substance, it is difficult to know what consumers are actually ingesting. Indeed, there is considerable evidence of NPS being used as adulterants in both traditional illicit drugs and other NPS (e.g. Guirguis et al., 2017). This evidence suggests that rates of unintentional NPS use are likely to be higher than the figures reported above. This discrepancy has raised awareness of the importance of using biological sampling to confirm self-reported NPS use, and to capture unintended NPS use.

Linking statement to empirical chapter: There is considerable evidence that rates of NPS use are relatively high amongst people who use other illicit substances. However, it remains unclear whether there is a distinct group of people who use NPS but no other illicit substances. In other words, it might be possible that NPS appeal to novice consumers. This possibility is addressed in paper one, which uses a general population sample where inclusion was not based on substance use. The paper examines the typology of illicit drug consumers in Australia and determines whether a distinct group of NPS-only consumers exists.

1.5.4 Surveys using biological sampling

Relatively few studies have used biological sampling to test for the presence of NPS, particularly in the Australian context. However, amongst the studies that have used biological sampling, the most common methods of analyses are hair sampling, blood sampling, oral fluid analysis and urinalysis.

With regards to hair sampling, a 2015 study of high-risk nightclub and dance music attendees in New York City found that of 80 samples analysed, 26 (roughly 33%) tested positive for at least one NPS, mostly butylone (25 samples). Other NPS which were detected included methylone, methoxetamine, 5/6-APB, α-PVP and 4-FA (Salomone et al., 2017). Similarly, a study which reanalysed hair samples from 2009 and 2010, which had originally tested positive for amphetamines or MDMA (n=325), found that NPS were detected in 37% of cases - although this figure included 14% ketamine. The most common NPS detected, excluding ketamine, were mCPP, 4-MMC and 4-FA (Rust et al., 2012).

In Australia, Yap and Drummer (2016) analysed blood samples from 253 Victorian fatally injured drivers during a 2-year period, 2012 to 2013, to determine the presence of NPS. The results showed that NPS were identified in 2.4% of the samples (SCRA, MDPV, and alpha-PVP), compared to 29% for the presence of all psychoactive drugs. In Belgium, a study of 558 blood and 199 oral fluid samples obtained during roadside controls from January to August 2015 reported a 7% and 11% positivity rate for NPS, respectively (Wille et al., 2017).

With regards to urine samples, Heikman et al. (2016) analysed 200 samples from patients receiving methadone or buprenorphine-naloxone medication. NPS were detected in 13% of cases, most commonly alpha-PVP (10%). In Denmark, 44 urine samples were collected from urinals at a music festival and almost no NPS were detected (Hoegberg et al., 2018). In Poland, analysis of biological materials (n=1058) including blood, urine, vitreous humour, body tissues and hair samples that had been submitted to the Institute of Forensic Research during 2012- 2014 detected NPS in 112 cases (roughly 11% of samples). The NPS most commonly detected were 3-MMC, alpha-PVP, pentedrone and MDPBP (Adamowicz et al., 2016). Similarly, a study which collected blood, urine and oral fluid samples from electronic dance music festival attendees over a two-year period (2014-2015) in the US found that 18% tested positive for NPS, typically methylone, ethylone or alpha-PVP (Mohr et al., 2016).

Overall, these studies show considerable variation regarding the presence of NPS. The findings suggest that biological sampling may have utility in measuring both intentional and unintentional rates of NPS consumption.

1.6 Harms associated with NPS use

As noted in section 1.1, NPS are broadly defined as substances which may pose a public health threat similar to that of internationally controlled substances. However, this aspect of the definition is largely speculative. Most NPS have not been subject to any animal or human trials,

19 and there is limited evidence regarding their potential acute toxicity, long-term effects and risk of use (Wood and Dargan, 2012, Wood et al., 2014). Most information regarding harms thus derives from self-report data such as internet discussion forums and user surveys (Wood et al., 2014). Individual case reports and small case series have also been used but only a few of these have been analytically confirmed (Wood and Dargan, 2012, Wood et al., 2014). In most cases, harms are unproven at the time a substance is categorised as an NPS. Indeed, an identifying feature of NPS is that little is known about them; they may pose a public health threat comparable to illicit substances, but they also may not.

Despite these complexities, certain NPS have been shown to have harmful effects (e.g. Busardo et al., 2015, European Monitoring Centre for Drugs and Drug Addiction, 2011b, European Monitoring Centre for Drugs and Drug Addiction, 2014, European Monitoring Centre for Drugs and Drug Addiction, 2016e, European Monitoring Centre for Drugs and Drug Addiction, 2017e, European Monitoring Centre for Drugs and Drug Addiction, 2017i, European Monitoring Centre for Drugs and Drug Addiction, 2017h, European Monitoring Centre for Drugs and Drug Addiction, 2017j, European Monitoring Centre for Drugs and Drug Addiction, 2017l, Karila et al., 2016, Welter et al., 2017, Wood et al., 2014, Van Amsterdam et al., 2015). The next section of this chapter focuses on the known harms associated with NPS in the SCRA, stimulant, psychedelic and opioid classes. These classes have been selected as they have arguably been associated with the most severe harms. Indeed, a study of poison control centre data from five counties of New York City and Long Island in 2011-2014 showed that most of the reported NPS exposures involved SCRA use (82.3%), followed by phenethylamine/synthetic cathinone use (10.2%; Palamar et al., 2016b). Similarly, the Global Drug Survey has repeatedly found that among people who used NPS, the overall risk of seeking emergency medical treatment was highest for those who had used synthetic cannabinoids (Winstock et al., 2017, Winstock et al., 2015). The European Drug Emergencies Network (Euro-DEN) project reported 470 presentations involving the use of at least one NPS, with cathinones (n=378) - mainly mephedrone (n=245) - being implicated in most cases (European Monitoring Centre for Drugs and Drug Addiction, 2015).

In reading the following section, two caveats should be noted: (1) considerable variation can occur within NPS classes; this section focuses on individual substances which have documented harms, and ignores the many for which little or no literature is available; (2) this review is not comprehensive, since it is beyond the scope of this thesis to canvas the literature for hundreds of different substances.

1.6.1 Harms associated with synthetic cannabinoid receptor agonists

Synthetic cannabinoid receptor agonists (SCRA) are substances that have structural features that allow binding to the cannabinoid receptors within the body. They are functionally similar to delta9-tetrahydrocannabinol (THC), the psychoactive principle of cannabis (Fattore and Fratta, 2011). However, in some cases SCRAs have proven to be more potent than THC and are associated with more severe adverse effects and toxicity (Castaneto et al., 2014, Welter et al., 2017, Mills et al., 2015). Furthermore, it has been suggested that ‘third generation’ SCRAs (e.g. AB-CHMINACA, MDMB-CHMICA) are associated with more severe clinical toxicity than earlier generation SCRAs, such as JHW-018 (Hermanns-Clausen et al., 2017).

Several reviews have focused on the adverse effects associated with SCRA and have consistently shown that the most common harms are fairly minor. They include tachycardia, agitation, nausea, arterial hypertension and hallucinations (for more details, see Castaneto et al., 2014, Hohmann et al., 2014, Lovrecic and Mercedes, 2017, Mills et al., 2015, Tait et al., 2015, Gunderson et al., 2012, Hermanns-Clausen et al., 2013). One of the most notable of these reviews was undertaken by Tait et al. (2015), who conducted a systematic review of adverse events associated with the consumption of SCRA in the medical literature and poison centre data. They identified 106 eligible studies, which included approximately 4000 cases and 26 deaths, and found that most presentations were not ‘serious’; they typically involved tachycardia, agitation and nausea and required less than 8 hours of symptomatic care. Other relatively minor toxic effects that have been reported by users of SCRA include vomiting, drowsiness, chest pain, hot flushes, dilation of pupils and a dry mouth.

There are also reports of SCRA use resulting in severe and fatal poisonings, however these are uncommon (Hohmann et al., 2014, Tait et al., 2015). Reported serious adverse effects include: cardiovascular toxicity, including sudden death; severe nervous system depression, such as rapid loss of consciousness or onset of coma; respiratory depression; seizures and convulsions; stroke; hyperemesis; mydriasis; bradycardia; somnolence; myocardial infarction; rhabdomyolsis; acute kidney injury; serotonin toxicity; urinary and faecal incontinence; respiratory acidosis; metabolic acidosis; delirium; psychotic episodes; and aggressive and violent behaviour (European Monitoring Centre for Drugs and Drug Addiction, 2017i, European Monitoring Centre for Drugs and Drug Addiction, 2017h, European Monitoring Centre for Drugs and Drug Addiction, 2017j, European Monitoring Centre for Drugs and Drug Addiction, 2017l, European Monitoring Centre for Drugs and Drug Addiction, 2017e, Barratt et al., 2013, Welter et al., 2017, Van Amsterdam et al., 2015, Wood et al., 2014).

21 More recently, a systematic review conducted by Cohen and Weinstein (2018) demonstrated an association between executive-function impairment and acute or repeated SCRA consumption. However, most of the evidence considered in this review was based on pre-clinical studies and substantial knowledge gaps remain. Evidence also suggests that withdrawal symptoms may occur when use is discontinued following regular chronic use (Miliano et al., 2016).

For more information regarding the documented harms associated with certain SCRA, readers are directed to the reviews mentioned above, and to the risk assessments that have been conducted for MDMB-CHMICA (European Monitoring Centre for Drugs and Drug Addiction, 2017e), AB-CHMINACA (European Monitoring Centre for Drugs and Drug Addiction, 2017i), ABD- CHMINACA (European Monitoring Centre for Drugs and Drug Addiction, 2017j), 5F-MDMB- PINACA (European Monitoring Centre for Drugs and Drug Addiction, 2017h) and CUMYL-4CN- BINACA (European Monitoring Centre for Drugs and Drug Addiction, 2017l).

1.6.2 Harms associated with stimulant NPS

‘Stimulant’ NPS, or those that mimic the effects of known stimulants, have a mechanism of action similar to drugs such as cocaine, amphetamine, methamphetamine and ecstasy. Synthetic cathinones are the most common NPS stimulants, both in terms of the number of substances identified and in terms of presentations with acute toxicity (Wood et al., 2014).

Several reviews have been conducted on the adverse effects associated with synthetic cathinones (see Prosser and Nelson, 2012, Rosenbaum et al., 2012, Schifano et al., 2016, Spiller et al., 2011, Valente et al., 2014). These studies have consistently shown that neurological symptoms (e.g. agitation or aggression, tremors, seizures), cardiac symptoms (e.g. shortness of breath, palpitations, chest pain) and psychiatric symptoms are the most common adverse effects reported by synthetic cathinone consumers. The most recent of these reviews was conducted by Schifano et al. (2016), who examined 82 publications. The authors found that the most common adverse reactions associated with synthetic cathinones were restlessness and anxiety, ranging from mild agitation to severe psychosis. Similarly, a review of the UK National Poisons Information Services (March 2009 and February 2010) showed that most of the telephone inquiries regarding mephedrone use were related to agitation or aggression (24%), tachycardia (22%) or chest pain (13%). Psychotic symptoms were also common (14%) (James et al., 2011). Other research, based on both user and clinical reports, showed that synthetic cathinones such as mephedrone, methylone, alpha-PVP and MDPV have been associated with impaired working memory, paranoia, blurred vision, cravings, hypertension, hyperthermia, tremors and convulsions, insomnia, depression, severe and prolonged anxiety attacks,

hallucinations, nausea or vomiting, respiratory problems and dependence (European Monitoring Centre for Drugs and Drug Addiction, 2011b, European Monitoring Centre for Drugs and Drug Addiction, 2014, European Monitoring Centre for Drugs and Drug Addiction, 2016e, Beck et al., 2015, Dargan et al., 2010, Dargan et al., 2011, Hohmann et al., 2014, Rosenbaum et al., 2012).

With regards to more serious adverse effects, there have been case reports of hyperpyrexia, myocardial infarction, rhabdomyolysis, mephedrone-related myocarditis, acute kidney injury and stroke (European Monitoring Centre for Drugs and Drug Addiction, 2011b, European Monitoring Centre for Drugs and Drug Addiction, 2014, European Monitoring Centre for Drugs and Drug Addiction, 2016e, Beck et al., 2015, Dargan et al., 2010, Dargan et al., 2011, Hohmann et al., 2014, Rosenbaum et al., 2012). However, the potential chronic health effects of prolonged use remain unknown, including reproductive toxicity, genotoxicity and carcinogenic potential (Karila et al., 2016). Multiple deaths have also occurred in the context of synthetic cathinone use, with mephedrone and MDPV identified during post-mortem toxicology. Specifically, a review of mephedrone-related fatalities found that among 18 fatal cases with analytically confirmed mephedrone in biological samples from the deceased, the death was attributed to mephedrone intoxication in half (n=9) of these cases (Busardo et al., 2015).

For more information regarding the documented harms associated with synthetic cathinones, readers are directed to the reviews mentioned above and to the risk assessments that have been conducted for alpha-PVP (European Monitoring Centre for Drugs and Drug Addiction, 2016e), MDPV (European Monitoring Centre for Drugs and Drug Addiction, 2014) and mephedrone (European Monitoring Centre for Drugs and Drug Addiction, 2011b).

1.6.3 Harms associated with opioid NPS

NPS in the opioid category make up only a small percentage of substances reported to the EMCDDA and UNODC. However, they have recently come to dominate in terms of concerns about harms. The greatest concern is focused on fentanyl analogues, which have been categorised as 'low use but high risk/harm' substances (Mounteney et al., 2015). Little research has been conducted on the adverse effects associated with fentanyl analogues and other new synthetic opioids, but reports indicate that the common features of toxicity are nausea, anxiety and agitation, depression, hallucinations, bradycardia and hypothermia (European Monitoring Centre for Drugs and Drug Addiction, 2017k, European Monitoring Centre for Drugs and Drug Addiction, 2017f, European Monitoring Centre for Drugs and Drug Addiction, 2017g, Abdulrahim and Bowden-Jones, 2018). The most serious acute risk arising from the use of fentanyl analogues

23 is rapid and severe respiratory depression, which can lead to apnoea, respiratory arrest and death. Deaths resulting from the use of fentanils are a particular concern in the United States. In 2015, there were 9580 deaths from synthetic opioids other than methadone, with fentanyl analogues implicated in 17% of these fatalities (Prekupec et al., 2017).

For more information regarding the documented harms associated with ‘new’ synthetic opioids readers are directed to the risk assessments that have been conducted for acryloylfentanyl (European Monitoring Centre for Drugs and Drug Addiction, 2017f), furanylfentanyl (European Monitoring Centre for Drugs and Drug Addiction, 2017g), carfentanil (European Monitoring Centre for Drugs and Drug Addiction, 2017k), cyclopropylfentanyl (European Monitoring Centre for Drugs and Drug Addiction, 2018b) and methoxyacetylfentanyl (European Monitoring Centre for Drugs and Drug Addiction, 2018c).

1.6.4. Harms associated with psychedelic NPS

In considering the harms associated with NPS use, it is worth briefly noting the NBOMe family. These substances are psychedelic phenethylamines which belong to the hallucinogen class. In 2015, Wood et al. reviewed the literature (1966-2014) on acute toxicity associated with NBOMe and identified 29 published cases, most of which involved 25I-NBOMe. The most commonly reported features associated with NBOMe toxicity included tachycardia (96.6%), hypertension (62.0%), agitation or aggression (48.2%), seizures (37.9%) and hyperthermia (27.6%). A small number of patients were reported to have developed acute kidney injury. 25I-NBOMe was found to have been associated with eight fatalities, although the role it played in these deaths was not determined for all cases. In Australia, several high-profile deaths have occurred which reportedly resulted from the unintentional consumption of NBOMe – that is, people consuming what they thought was LSD or MDMA but was actually NBOMe (Caldicott et al., 2013, Cowie et al., 2017, Evans, 2017).

1.7 Policy responses to the NPS ‘problem’

1.7.1 Legislative responses

The 1971 UN Convention on Psychotropic Substances provided the first mechanism for assessing new substances for international control, with the World Health Organization (WHO) tasked with providing recommendations to the UNODC for each new substance (Barratt et al., 2017). To form these recommendations, the WHO conducts an assessment of various information sources to determine whether the substance “has the capacity to produce (i) a state of dependence, and central nervous system stimulation or depression, resulting in hallucinations

or disturbances in motor function or thinking or behaviour or perception or mood, or (ii) similar abuse and similar ill effects as a substance in Schedule I, II, III or IV”, and “is being or is likely to be abused so as to constitute a public health and social problem” in light of its usefulness as a medicine (Article 2, Section 4; UN General Assembly, 1975). However, these traditional legislative responses are limited in their ability to deal with the diverse and rapidly changing nature of the NPS market for several reasons. These reasons are as follows: (1) the usual mechanism lacks the capacity to process and assess hundreds of different substances; (2) recommendations for scheduling are often based on pharmacological and toxicological information (information which does not exist for many NPS); and (3) prohibiting individual NPS often simply moves the market from one drug to the next (Barratt et al., 2017). For these reasons there has been a global search for legislative responses which go beyond the scheduling of individual compounds, with governments around the world implementing various regulatory frameworks. These frameworks have been categorised into five groups: analogue approach; neurochemical approach; general prohibition; full regulation; and restricted availability (Reuter and Pardo, 2017, United Nations Office on Drugs and Crime, 2016b). These categories are shown in Table 2. Other countries have utilised existing legislation, such as consumer protection laws, to prohibit or regulate NPS (Table 2).

25 Table 2: Legal approaches to NPS

Approach Definition Examples

Control based on chemical similarity or intended Analogue United States Federal psychoactive effects to approach Analogue Act substances already controlled by law

Control different groupings of Cannabimimetic agents substances regardless of Neurochemical under the United States chemical variation that have a approach Synthetic Drug Abuse specific neuropharmacological Prevention Act effect on brain

Irish Criminal Justice Prohibit supply, import and General (Psychoactive Substances) export of any psychoactive prohibition Act; United Kingdom substance that is not exempted Psychoactive Substances Act

Through detailed regulations, Full regulatory permit and regulate sale of New Zealand Psychoactive approach limited class of NPS that are Substances Act proven to be of low risk

Restricted Restrict NPS to limited points of New Zealand Class D availability sale, labeling, age, etc. until substances under Misuse of approach harms are established Drugs Act

NSW (Australia) introduced Utilise existing consumer an interim ban on the sale protection laws to place interim, Consumer and supply of 19 synthetic or permanent, bans on consumer protection laws drug products, listed by the products which may cause injury trade names under which to a person they were being sold

Source: Reuter and Pardo (2017), pg. 27; Australian Goverment Department of Health, 2014

The most common of these approaches have been the ‘analogue approach’ and ‘general prohibition’, both of which have been implemented in various countries around the world. The analogue approach prohibits any substance which is both structurally similar to an already controlled substance and which exerts a similar or greater effect on the central nervous system. This approach has been implemented in Australia (South Australia, Queensland), the United States, Canada, Bulgaria, Latvia and Malta (European Monitoring Centre for Drugs and Drug

Addiction, 2016d, Reuter and Pardo, 2017, United Nations Office on Drugs and Crime, 2016b). However, it is limited by the lack of a scientific method to determine pharmacological ‘similarity’ between two substances (Hibbert and Sutton, 2017, United Nations Office on Drugs and Crime, 2016b).

In contrast, the general prohibition approach prohibits all psychoactive substances that are not already regulated or belonging to exempt categories (e.g. alcohol, tobacco, caffeine and scheduled medicines). This approach has been adopted by Ireland (2010), Poland (2011), Romania (2012), New Zealand (2013), Australia (2015) and the United Kingdom (2016) (Barratt et al., 2017), and means that governments are no longer simply reactive (i.e. scheduling individual substances once harms have been established). However, this approach has been criticised for detaching penalties from harm (Reuter and Pardo, 2017, van Amsterdam et al., 2013) and for violating the theoretical underpinnings of legal regimes in which substances are meant to be scheduled according to the degree of danger they pose.

In Australia, legislation is complex with Federal, and State and Territory governments, responsible for different aspects of controlling NPS. Specifically, the Commonwealth is responsible for regulating the importation of NPS and the assessment and scheduling of prohibited substances on the Standard for the Uniform Scheduling of Medicines and Poisons (SUSMP), whilst the states and territories are responsible for regulating the manufacture, supply and advertising of NPS. At the Commonwealth level, a combination of criminal law, medicines regulation and consumer law have been utilised in an attempt to control NPS (see Table 3). In 2011-2012, several substances (e.g. JWH-018, JWH-073, mephedrone, MDPV) were scheduled as prohibited substances under the SUSMP (Australian Government Department of Health, 2014), and in 2012 the Therapeutic Goods Administration introduced a blanket ban on any type of synthetic cannabinoid that produced the same pharmacological effect as cannabis (Bright et al., 2013).

All jurisdictions have subsequently aligned their drugs and poisons legislation to cover those substances listed as prohibited under the SUSMP; however, each State and Territory retains its own laws that determine which substances are subject to criminal controls. This has resulted in different legislative frameworks across jurisdictions. New South Wales, Victoria, Queensland, Western Australia and South Australia have adopted the ‘general prohibition’ approach outlined above whereas other jurisdictions have extended analogue clauses or used consumer protection laws (Cairns et al., 2017). Given the complexity of legislation at the jurisdictional level, it is beyond the scope of this thesis to provide timelines for each state and territory; however, for

27 an overview of the state-based legislation introduced in NSW (the most populated jurisdiction in Australia), please refer to Cairns et al., 2017.

Table 3: Australian Commonwealth legislative responses to new psychoactive substances Legislation Year Description Psychotropic Substances Act 1976 1976 Ratified the 1971 UN Convention on Psychotropic Substances. If importers of psychotropic substances cannot produce an export authorisation, border officials may seize the substance. Australia commits to adding new drugs to the schedules following their addition to the UN schedules

Law and Justice Legislation Amendment 2005 Amendment to the Criminal Code 1995 (first instance of psychoactive substances within the Code) (Serious Drug Offences and Other Section 301.1 Interim regulations for up to 12 months. The Minister can add new substances to the controlled list if Measures) Act 2005 he/she is satisfied that (1) the substance “would create a substantial risk of death or serious harm or would have a physical or mental effect substantially similar” to an already listed substance, and (2) that “there is a substantial risk that the substance or plant will be taken without appropriate medical supervision” Section 301.6 Emergency determinations (similar to above but limited to 28 days) Section 314.1(2) Inserts definition of a drug analogue, based on similarity of chemical structure. Federal laws prohibiting possession, sale, import/export, and manufacturer are then also applied to drug analogues

Therapeutic Goods Amendment (2009 2009 Amendment to the Therapeutic Goods Act 1989. The Advisory Committee on Medicines Scheduling is established to Measures No. 2) Act 2009 advise the Secretary of the Therapeutic Goods Administration (Department of Health) on amendments to the Poisons Standard (Section 52D(2)). The Secretary must take into account “(a) the risks and benefits of the use of a substance; (b) the purposes for which a substance is to be used and the extent of use of a substance; (c) the toxicity of a substance; (d) the dosage, formulation, labelling, packaging and presentation of a substance; (e) the potential for abuse of a substance; (f) any other matters that the Secretary considers necessary to protect public health” (Section 52E(1))

Amendment to Poisons Standard 2011, Jul Eight synthetic cannabinoid receptor agonists (SCRA) were placed on Schedule 9 (prohibited substances) (JWH-018, JWH- 073, JWH-122, JWH-200, JWH-250, CP47,497, AM-694 & cannabicyclohexanol)

Amendment to Poisons Standard 2012, Feb 3,4-Methylenedioxypyrovalerone (MDPV) was placed on Schedule 9 Nine new entries were placed in Schedule 9 in an attempt to cover all possible SCRA. These entries included 8 structural groups (benzoylindoles, cyclohexylphenols, dibenzopyrans, naphthoylindoles, naphthylmethylindoles, naphthoylpyrroles, naphthylmethylindenes, phenylacetylindoles) and a broader category of synthetic cannabinomimetics, except when separately specified in these Schedules

29 Table 3: Australian Commonwealth legislative responses to new psychoactive substances Crimes Legislation Amendment (Serious 2012 Amendment to the Criminal Code 1995 Section 301.7 stipulates the conditions that must be met for a drug to be listed Drugs, Identity Crime and Other Measures) as a ‘serious drug’ by the Minister, who must be satisfied that: “(a) the substance or plant is likely to be taken without Act 2012 appropriate medical supervision; and (b) one or more of the following conditions is met: (i) taking the substance or plant would create a risk of death or serious harm; (ii) taking the substance or plant would have a physical or mental effect substantially similar to that caused by taking a serious drug that is already listed; (iii) the substance or plant has the capacity to cause physiological dependence; (iv) possession or conduct in relation to the substance or plant is proscribed under a law of a State, a Territory or a foreign country that has purposes similar to those of this Part; (v) the substance or plant poses a substantial risk to the health or safety of the public” Section 301.13 Emergency determinations relating to ‘serious drugs’ is inserted Section 301.16 Emergency determinations can stay in place for up to 18 months Section 301.17 Emergency determinations can be published on or before the day of determination by public announcement

Competition and Consumer Act 2010 – 2013, Jun An interim consumer protection ban prohibited the sale of a list of psychoactive substances that used specified brand Consumer Protection Notice No. 3 of 2013 – names or contained specified substances listed on Schedule 9 of the Poisons Standard, “whether or not a statement to Imposition of Interim Ban on Certain the effect that the goods are not intended for human consumption is made”. The ban was in force for 120 days and Consumer Goods Containing Synthetic Drug allowed products to be seized based on their labelling, without the need for forensic analysis of their content Substances Crimes Legislation Amendment 2015 Amendments to the Criminal Code 1995 and the Customs Act 1901 Bans the importation of all substances that have a (Psychoactive Substances and Other psychoactive effect that are not otherwise regulated Exemptions include: food, tobacco, medicines, agricultural products, Measures) Act 2015 veterinary products, industrial chemicals, plants/fungi, otherwise controlled drugs/plants, prohibited imports Defines ‘psychoactive effect’ (see Table 2, this paper) Burden of proofs lies with the importer, who must show that the substance is either not psychoactive or belong to one of the exempt categories

Source: Barratt et al., 2017, pg.18

1.7.2 Health-related responses

Responses to the NPS market have been largely regulatory. However, there has been an increasing recognition of the importance of moving beyond regulatory interventions towards health and drug-related interventions. The EMCDDA recently conducted a review of the responses to NPS use across Europe and identified six relevant intervention settings: sexual health settings, custodial settings, school and family settings, nightlife settings, treatment settings and low-threshold settings (European Monitoring Centre for Drugs and Drug Addiction, 2016c). These settings are largely focussed on the high-risk groups identified in section 1.5.3. The interventions are based on existing responses to drug use and are adapted where necessary to reflect the NPS market. The interventions range from adapting on-site drug checking facilities to account for NPS use to establishing a ‘Club Drug Clinic’ (UK). This clinic provides a community- based outpatient and drop-in service for users of club drugs who do not fit the profile of ‘typical’ drug treatment clients (for more details on these interventions, see European Monitoring Centre for Drugs and Drug Addiction, 2016c).

In the Australian context, it remains unclear whether any NPS-specific interventions have been developed - or indeed whether there is a need for NPS-specific interventions. This thesis is concerned with evaluating this issue. Champion et al. (2016) adapted an existing program to develop the ‘ecstasy and emerging drugs module’, an internet-based intervention which used cartoon storylines to convey information about harmful drug use to students in 11 secondary schools across Australia. They found that students who received the intervention were less likely to report an intention to use NPS, and displayed better knowledge about NPS in the short-term, compared to those who had not received the intervention.

With regards to harm minimisation (one of the key principles of Australia’s National Drug Strategy), there has been an increasing push for drug checking, whereby the chemical content of an illicit drug sample is tested in real-time - usually in a nightclub or festival setting. Drug checking, as a health intervention to reduce the ingestion of toxic substances, has been implemented in various European countries for many years (for further details, see European Monitoring Centre for Drugs and Drug Addiction, 2017a). However, in the Australian context there has been substantial political resistance to such a proposal, with the Australian Capital Territory (ACT) the only Australian state or territory government to publicly support a drug- checking trial. In April 2018, the first Australian pill testing pilot trial took place at the Groovin the Moo festival in Canberra (ACT). Preliminary reports claimed the trial was a success as it was 31

well-utilised, and two new substances were identified in Canberra for the first time (Fitzharris, 2018). Furthermore, a national approach has been recommended for consideration, namely a mixed-model approach to pill testing across Australia, combined with the development of a national pill testing evaluation framework (Makkai et al., 2018).

Linking statement: To date, the NPS market has not been well documented in Australia and the need for NPS-related health interventions remains unclear. It is the purpose of this thesis to provide a more detailed and coherent picture of NPS use in Australia, thus providing guidance around the development and targeting of health interventions, and harm reduction messages.

1.7.3 Australian policy framework

Taking these various legislative and health concerns into account, the Framework for a National Response to New Psychoactive Substances was developed in 2014. This framework contains 11 elements, which can be divided into four categories: (1) establishing a solid evidence base and response capabilities (including detection and identification capability; a drug monitoring system and associated data collection; and harms assessments); (2) legislative responses (including rapid response laws; uniform treatment of drug analogues; consumer protection laws; other existing laws; and a broad precautionary psychoactive substances scheme); (3) raising public awareness (including developing agreed terminology; and public awareness and education); and (4) increased national and international coordination (including; better coordination between jurisdictions; and international engagement) (Australian Goverment Department of Health, 2014). Some of these elements were actioned immediately, whereas others were subject to resourcing, policy, and legislative processes, and were implemented at a later date (e.g. the NWDMP) or are yet to be actioned.

1.8 Summary

This introductory chapter has drawn together literature to provide an overview of the NPS phenomenon. In this overview, I have demonstrated that despite the exponential growth in the number of NPS identified over the past decade, most of these substances have proven to be transient, disappearing shortly after their identification. In addition, only a fraction of the more than 800 NPS have been detected in Australia. The prevalence of NPS use appears to be relatively low among general population samples and has declined in recent years, despite being reported as an ‘epidemic’ by some media organisations (Harvey, 2015, Miranda, 2017).

Nevertheless, there remain serious concerns about NPS use. Rates of use are elevated amongst vulnerable, high-risk populations and certain NPS are associated with significant harms, including death. However, given the diverse and rapidly evolving nature of the NPS market, there has been uncertainty about how best to respond to the NPS ‘problem’. To date, responses to the NPS market have been largely regulatory, with governments around the world enacting various regulatory frameworks. Considerably less focus has been given to health-related interventions, arguably because of the uncertainty about whether NPS-specific interventions or harm reduction messages are needed, and if so, who the appropriate target groups would be.

Indeed, there remains much we do not know about the NPS market, particularly in the Australian context. To date, the NPS evidence base has focussed mainly on the number and type of people using NPS, with most studies conducted in Europe and the United States. It is the purpose of this thesis to advance the current evidence base by examining NPS use in the Australian context. Specifically, it examines: which NPS are most commonly consumed; who uses these substances (notably, does there exist a group of exclusive NPS consumers?); why people use NPS; and how they obtain them. Importantly, this thesis examines differences across NPS consumers in each of these domains, something which has been largely overlooked in much of the existing literature (which mostly treats NPS as a single entity, or which focuses on individual substances). Combined, these findings will improve our understanding of the NPS market in the Australian context, thereby providing an evidence base for future policy responses.

1.9 Thesis structure

This thesis is presented as a series of four publications, and is structured as follows:

Chapter 2: The intersection between NPS and established illicit drugs

Key question addressed: Is there a group of excusive NPS consumers – that is, people who use NPS but no other illicit substances?

Despite the low prevalence of NPS use, rates of use are elevated amongst vulnerable, high-risk populations. In particular, evidence exists that NPS use largely occurs amongst people who use other illicit substances. However, because most studies have used samples of people who consume illicit substances or have a high probability of illicit drug use, the generalisability of such findings is unclear.

Chapter 2 (paper 1) addresses this issue by using data from the 2013 National Drug Strategy Household Survey, an Australian general population sample, to: 1) identify the typology of Australian illicit drug consumers to determine if there is a distinct group of exclusive NPS consumers (i.e. people who report use of NPS but no other illicit substances), and if not, determine which consumer ‘type’ is most likely to use NPS; and 2) compare profiles across these subgroups, based on demographics and risk behaviours. The findings of this paper will improve our understanding of the intersection between established illicit drugs and NPS, and also provide guidance around the targeting of harm reduction messages in the Australian context.

Chapter 3: NPS use among a sample of people who regularly use ecstasy and/or other stimulants

Key question addressed: What are the rates and correlates of NPS use among people who use other illicit drugs?

Although the prevalence of NPS use is relatively low among general population samples, as illustrated above, research has shown that rates of use are elevated amongst high-risk populations. To date, there is little evidence of NPS use amongst Australian populations of homeless or incarcerated individuals, men who have sex with men, or people who inject drugs. However, there is evidence of NPS use amongst ‘recreational’ samples of Australian stimulant users (Bruno et al., 2012, Burns et al., 2014b). Thus, to provide a more detailed understanding of patterns of NPS use in Australia, the next series of papers (chapters 3 to 5) will use data from the Ecstasy and related Drugs Reporting System (EDRS). The EDRS was the first project to start systematically collecting information on the use of NPS in Australia. The first of these papers examines rates of NPS use amongst the EDRS sample from 2010-2015 and factors associated with use of the different NPS classes.

Chapter 4: Motivations associated with NPS use

Key question addressed: Why do people use NPS?

The rapid growth of the NPS market, combined with uncertainty regarding potential harms, has challenged traditional legislative and harm reduction responses. Governments around the world have enacted various regulatory frameworks, with less focus on health-related interventions. Arguably, this trend has resulted from uncertainty about how to most appropriately direct harm reduction messages. Understanding why people engage in certain behaviours, including

substance use, is essential if we want to modify those behaviours and/or implement appropriate policy responses. Hence, the purpose of chapter 4 (paper 3) is to explore the motivations for NPS use among the EDRS sample and to determine whether such motivations vary across substances.

Chapter 5: The purchasing and supply patterns of NPS consumers

Key question addressed: How do NPS consumers source these substances, and do they supply to others?

The rapid growth of the NPS market is often attributed, in part, to the expansion of online marketplaces. However, it remains unclear to what extent consumers actually use the internet as a source for obtaining NPS. In addition to providing opportunities for the direct purchasing of NPS for personal use, the internet may play a role in social supply – that is, the non-commercial or non-profitable distribution of drugs to non-strangers (Hough et al., 2003), where one friend within a social group may purchase NPS online to provide to others within the group, either for free, at cost price, or for profit. Chapter 5 (paper 4) addresses these issues by examining how people obtain NPS, to what extent they supply to others, and whether variation occurs in these factors across NPS.

Chapter 6: Discussion

This final chapter summarises the findings of the chapters comprising of empirical studies (i.e. chapters 2 to 5), outlines the contributions made to the literature, and discusses the associated clinical and public health implications. Strengths and limitations of the thesis are discussed and recommendations for future research detailed.

Chapter 7: Conclusion

This chapter provides a conclusion to the thesis.

1.10 References

ABDULRAHIM, D. & BOWDEN-JONES, O. 2018. The misuse of synthetic opioids: harms and clinical management of fentanyl, fentanyl analogues and other novel synthetic opioids. Information for clinicians. London: NEPTUNE. ADAMOWICZ, P., GIEROŃ, J., GIL, D., LECHOWICZ, W., SKULSKA, A. & TOKARCZYK, B. 2016. The prevalence of new psychoactive substances in biological material - a three-year review of casework in Poland. Drug Testing and Analysis, 8, 64-71. ALEXANDRESCU, L. 2018. ‘Ethnobotanicals’ and ‘Spice zombies’: new psychoactive substances in the mainstream media. Drugs: Education, Prevention and Policy, 25, 356-364. AUSTRALIAN CRIMINAL INTELLIGENCE COMMISION 2017. National Wastewater Drug Monitoring Program. Report 1, March 2017. Canberra: ACIC. AUSTRALIAN CRIMINAL INTELLIGENCE COMMISION 2018. National Wastewater Drug Monitoring Program. Report 4, March 2018. Canberra: ACIC. AUSTRALIAN GOVERMENT DEPARTMENT OF HEALTH 2014. Framework for a National Response to New Psychoactive Substances. National Drug Strategy Canberra: Australian Goverment Department of Health, . AUSTRALIAN INSTITUTE OF HEALTH & WELFARE 2014. 2013 National Drug Strategy Household Survey: Detailed Findings. Drug statistics series no. 28. Cat. no. PHE 183. Canberra: Australian Institute of Health and Welfare. AUSTRALIAN INSTITUTE OF HEALTH & WELFARE 2017. National Drug Strategy Household Survey 2016. Detailed findings. Drug Statistics series no. 31. Cat. no. PHE 214. BARRATT, M. J., & ALDRIDGE, J. 2016. Everything you always wanted to know about drug cryptomarkets* (*but were afraid to ask). International Journal of Drug Policy, 35, 1-6. doi:10.1016/j.drugpo.2016.07.005 BARRATT, M. J., CAKIC, V. & LENTON, S. 2013. Patterns of synthetic cannabinoid use in Australia. Drug and Alcohol Review, 32, 141-146. BARRATT, M. J., FERRIS, J. A. & WINSTOCK, A. R. 2014. Use of Silk Road, the online drug marketplace, in the United Kingdom, Australia and the United States. Addiction, 109, 774-783. BARRATT, M. J., SEEAR, K. & LANCASTER, K. 2017. A critical examination of the definition of ‘psychoactive effect’ in Australian drug legislation. International Journal of Drug Policy, 40, 16-25. BECK, O., FRANZEN, L., BÄCKBERG, M., SIGNELL, P. & HELANDER, A. 2015. Intoxications involving MDPV in Sweden during 2010-2014: Results from the STRIDA project. Clinical Toxicology, 53, 865-873. BJÖRNSTAD, K., HULTÉN, P., BECK, O., & HELANDER, A. (2009). Bioanalytical and clinical evaluation of 103 suspected cases of intoxications with psychoactive plant materials. Clinical Toxicology, 47(6), 566-572. doi:10.1080/15563650903037181 BONAR, E. E., ASHRAFIOUN, L. & ILGEN, M. A. 2014. Synthetic cannabinoid use among patients in residential substance use disorder treatment: prevalence, motives, and correlates. Drug Alcohol Depend, 143, 268-71. BRETT, A. 1997. Myeloneuropathy from Whipped Cream Bulbs Presenting as Conversion Disorder. Australian & New Zealand Journal of Psychiatry, 31, 131-132. BRETTEVILLE-JENSEN, A. L., TUV, S. S., BILGREI, O. R., FJELD, B. & BACHS, L. 2013. Synthetic Cannabinoids and Cathinones: Prevalence and Markets. Forensic Sci Rev, 25, 7-26. BRIGHT, S., BISHOP, B., KANE, R., MARSH, A. & BARRATT, M. 2013. Kronic hysteria: Exploring the intersection between Australian synthetic cannabis legislation, the media, and drug- related harm. International Journal of Drug Policy, 24, 231-237.

BRUNO, R., MATTHEWS, A. J., DUNN, M., ALATI, R., MCILWRAITH, F., HICKEY, S., BURNS, L. & SINDICICH, N. 2012. Emerging psychoactive substance use among regular ecstasy users in Australia. Drug and Alcohol Dependence, 124, 19-25. BRUNT, T. M. 2010. Wastewater analysis and its potential for monitoring illicit drugs, in combination with other drug monitoring approaches. Netherlands: Trimbos instituut BRUNT, T. M., NAGY, C., BÜCHELI, A., MARTINS, D., UGARTE, M., BEDUWE, C. & VENTURA VILAMALA, M. 2017. Drug testing in Europe: monitoring results of the Trans European Drug Information (TEDI) project. Drug Testing and Analysis, 9, 188-198. BRUNT, T. M., POORTMAN, A., NIESINK, R. J. & BRINK, W. V. D. 2011. Instability of the ecstasy market and a new kid on the block: mephedrone. Journal of Psychopharmacology, 25, 1543-1547. BURNS, L., ROXBURGH, A., MATTHEWS, A., BRUNO, R., LENTON, S. & VAN BUSKIRK, J. 2014a. The rise of new psychoactive substance use in Australia. Drug Testing and Analysis, 6, 846-849. BURNS, L., ROXBURGH, A., MATTHEWS, A., BRUNO, R., LENTON, S. & VAN BUSKIRK, J. 2014b. The rise of new psychoactive substance use in Australia. Drug Test Anal, 6, 846-9. BUSARDO, F. P., KYRIAKOU, C., NAPOLETANO, S., MARINELLI, E. & ZAAMI, S. 2015. Mephedrone related fatalities: a review. Eur Rev Med Pharmacol Sci, 19, 3777-90. BUXTON, J., & BINGHAM, T. (2015). The rise and challenge of dark net drug markets Policy Brief 7. Swansea University: Global Drug Policy Observatory. CAIRNS, R., BROWN, J. A., GUNJA, N. & BUCKLEY, N. A. 2017. The impact of Australian legislative changes on synthetic cannabinoid exposures reported to the New South Wales Poisons Information Centre. International Journal of Drug Policy, 43, 74-82. CAKIC, V., POTKONYAK, J. & MARSHALL, A. 2010. Dimethyltryptamine (DMT): Subjective effects and patterns of use among Australian recreational users. Drug and Alcohol Dependence, 111, 30-37. CALDICOTT, D., BRIGHT, S. & BARRATT, M. 2013. NBOMe - a very different kettle of fish. The Medical Journal of Australia, 199, 322-323. CASTANETO, M. S., GORELICK, D. A., DESROSIERS, N. A., HARTMAN, R. L., PIRARD, S. & HUESTIS, M. A. 2014. Synthetic cannabinoids: Epidemiology, pharmacodynamics, and clinical implications. Drug and Alcohol Dependence, 144, 12-41. CENTER FOR BEHAVIORAL HEALTH STATISTICS AND QUALITY 2016. 2015 National Survey on Drug Use and Health: Summary of the Effects of the 2015 NSDUH Questionnaire Redesign: Implications for Data Users. Rockville, MD: Substance Abuse and Mental Health Services Administration. CHAMPION, K. E., NEWTON, N. C., STAPINSKI, L. A. & TEESSON, M. 2016. Effectiveness of a universal internet‐based prevention program for ecstasy and new psychoactive substances: a cluster randomized controlled trial. Addiction, 111, 1396-1405. CHAMPION, K. E., TEESSON, M. & NEWTON, N. C. 2015. Patterns and correlates of new psychoactive substance use in a sample of Australian high school students. Drug and Alcohol Review. CICCARONE, D., ONDOCSIN, J. & MARS, S. G. 2017. Heroin uncertainties: Exploring users' perceptions of fentanyl-adulterated and -substituted 'heroin'. Int J Drug Policy, 46, 146- 155. COHEN, K. & WEINSTEIN, A. 2018. The Effects of Cannabinoids on Executive Functions: Evidence from Cannabis and Synthetic Cannabinoids—A Systematic Review. Brain Sciences, 8, 40. COMMISSION ON NARCOTIC DRUGS 2015. Extract from the Report of the 37th Expert Committee on Drug Dependence, convened from 16 to 20 November 2015, at WHO headquarters in Geneva. Geneva: World Health Organisation. COWIE, T., BUCCI, N. & HOUSTON, C. 2017. Police defend decision not to warn public of new drug after Melbourne club deaths. The Age, February 7.

DARGAN, P. I., ALBERT, S. & WOOD, D. M. 2010. Mephedrone use and associated adverse effects in school and college/university students before the UK legislation change. QJM, 103, 875-879. DARGAN, P. I., SEDEFOV, R., GALLEGOS, A. & WOOD, D. M. 2011. The pharmacology and toxicology of the synthetic cathinone mephedrone (4-methylmethcathinone). Drug Testing and Analysis, 3, 454-463. EDWARDS, R. J. & UJMA, J. 1995. Extreme methaemoglobinaemia secondary to recreational use of amyl nitrite. Journal of Accident & Emergency Medicine, 12, 138-142. EMMANUEL, F. & ATTARAD, A. 2006. Correlates of injection use of synthetic drugs among drug users in Pakistan: a case controlled study. J Pak Med Assoc, 56, 119-24. ESPAD GROUP, 2016a. ESPAD Report 2015. Results from the European School Survey Project on Alcohol and Other Drugs. Luxembourg: Publications Office of the European Union. ESPAD GROUP, 2016b. The European School Survey Project on Alcohol and Other Drugs: Questionnaire on Substance Use. [Online]. Available:: http://www.espad.org/sites/espad.org/files/espad-master-questionnaire.pdf [Accessed 6 November 2018] EUROPEAN COMMISSION 2014. Young people and drugs. Flash Eurobarometer 401. Flash Eurobarometer 401. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2011a. Online sales of new psychoactive substances/'legal highs': Summary of results from the 2011 multilingual snapshots. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2011b. Report on the risk assessment of mephedrone in the framework of the Council Decision on new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2014. Report on the risk assessment of MDPV in the framework of the Council Decision on new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2015. Final Report of the European Drug Emergencies Network (Euro-DEN). March 2015. Luxembourg: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016b. EU Drug Markets Report. In-depth Analysis. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016c. Health responses to new psychoactive substances. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016d. Legal approaches to controlling new psychoactive substances. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016e. Report on the risk assessment of α-PVP in the framework of the Council Decision on new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017a. Drug checking as a harm reduction tool for recreational drug users: opportunities and challenges In: BRUNT, T. M. (ed.). Luxenbourg: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017b. EMCDDA - Eurpol 2016 Annual Report on the implementation of Council Decision 2005/387/JHA. Luxembourg: Publications Office of the European Union.

EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017c. High-risk drug use and new psychoactive substances. Results from an EMCDDA trendspotter study. . Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017d. Perspectives on drugs. Synthetic cannabinoids in Europe. Luxenbourg: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017e. Report on the risk assessment of MDMB-CHMICA in the framework of the Council Decision on new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017f. Report on the risk assessment report of acryloylfentanyl in the framework of the Council Decision on new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017g. Report on the risk assessment report of furanylfentanyl in the framework of the Council Decision on new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017h. Risk assessment report on a new psychoactive substance: 5F-MDMB-PINACA; 5F-ADB. In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017i. Risk assessment report on a new psychoactive substance: AB-CHMINACA. In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017j. Risk assessment report on a new psychoactive substance: ADB-CHMINACA. In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017k. Risk assessment report on a new psychoactive substance: Carfentanil. In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017l. Risk assessment report on a new psychoactive substance: CUMYL-4CN-BINACA. In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2018a. EMCDDA - Eurpol 2017 Annual Report on the implementation of Council Decision 2005/387/JHA. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2018b. Europol Joint Report on a new psychoactive substance: N-phenyl-N-[1-(2-phenylethyl)piperidin-4- yl]cyclopropanecarboxamide (cyclopropylfentanyl). In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and

control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2018c. Risk assessment report on a new psychoactive substance 2-methoxy-N-phenyl-N-[1-(2- phenylethyl)piperidin-4-yl]acetamide (methoxyacetylfentanyl). In accordance with Article 6 of Council Decision 2005/387/JHA on the information exchange, risk assessment and control of new psychoactive substances. Lisbon: European Monitoring Centre for Drugs and Drug Addiction. EVANS, J. 2017. Woman hospitalised with seizures after fake MDMA discovered in Canberra. ABC, 24 February. FATTORE, L. & FRATTA, W. 2011. Beyond THC: The New Generation of Cannabinoid Designer Drugs. Frontiers in Behavioral Neuroscience, 5. FITZHARRIS, M. 2018. Australia’s first pill testing trial a success ACT Government. GIESE, C., IGOE, D., GIBBONS, Z., HURLEY, C., STOKES, S., MCNAMARA, S., ENNIS, O., O’DONNELL, K., KEENAN, E., DE GASCUN, C., LYONS, F., WARD, M., DANIS, K., GLYNN, R., WATERS, A. & FITZGERALD, M. 2015. Injection of new psychoactive substance snow blow associated with recently acquired hiv infections among homeless people who inject drugs in dublin, ireland, 2015. Eurosurveillance, 20. GLOBAL DRUG SURVEY. (2016). The global drug survey 2016 findings. Retrieved from https://www.globaldrugsurvey.com/past-findings/the-global-drug-survey-2016- findings/ (Archived by WebCite® at http://www.webcitation.org/6lL5SyusW) GONZÁLEZ-MARIÑO, I., GRACIA-LOR, E., BAGNATI, R., MARTINS, C. P. B., ZUCCATO, E. & CASTIGLIONI, S. 2016a. Screening new psychoactive substances in urban wastewater using high resolution mass spectrometry. Analytical and Bioanalytical Chemistry, 408, 4297-4309. GONZÁLEZ-MARIÑO, I., GRACIA-LOR, E., ROUSIS, N. I., CASTRIGNANÒ, E., THOMAS, K. V., QUINTANA, J. B., KASPRZYK-HORDERN, B., ZUCCATO, E. & CASTIGLIONI, S. 2016b. Wastewater-Based Epidemiology to Monitor Synthetic Cathinones Use in Different European Countries. Environmental Science and Technology, 50, 10089-10096. GUIRGUIS, A., CORKERY, J. M., STAIR, J. L., KIRTON, S. B., ZLOH, M. & SCHIFANO, F. 2017. Intended and unintended use of cathinone mixtures. Human Psychopharmacology, 32. GUNDERSON, E. W., HAUGHEY, H. M., AIT-DAOUD, N., JOSHI, A. S. & HART, C. L. 2012. "Spice" and "K2" herbal highs: a case series and systematic review of the clinical effects and biopsychosocial implications of synthetic cannabinoid use in humans. Am J Addict, 21, 320-6. GUNDERSON, E. W., HAUGHEY, H. M., AIT-DAOUD, N., JOSHI, A. S., & HART, C. L. (2014). A Survey of Synthetic Cannabinoid Consumption by Current Cannabis Users. Substance Abuse, 35(2), 184-189. doi:10.1080/08897077.2013.846288.HANNEMANN, T. V., KRAUS, L. & PIONTEK, D. 2017. Consumption Patterns of Nightlife Attendees in Munich: A Latent-Class Analysis. Substance Use and Misuse, 52, 1511-1521. HARVEY, A. 2015. Synthetic drugs epidemic will bring overdoses and deaths, experts warn. ABC 7:30 Report, 15 Jan 2015. HEIKMAN, P., SUNDSTRÖM, M., PELANDER, A. & OJANPERÄ, I. 2016. New psychoactive substances as part of polydrug abuse within opioid maintenance treatment revealed by comprehensive high-resolution mass spectrometric urine drug screening. Human Psychopharmacology, 31, 44-52. HERMANNS-CLAUSEN, M., KNEISEL, S., SZABO, B. & AUWÄRTER, V. 2013. Acute toxicity due to the confirmed consumption of synthetic cannabinoids: clinical and laboratory findings. Addiction, 108, 534-544. HERMANNS-CLAUSEN, M., MÜLLER, D., KITHINJI, J., ANGERER, V., FRANZ, F., EYER, F., NEURATH, H., LIEBETRAU, G. & AUWÄRTER, V. 2017. Acute side effects after consumption of the

new synthetic cannabinoids AB-CHMINACA and MDMB-CHMICA. Clinical Toxicology, 1- 8. HIBBERT, D. B. & SUTTON, J. 2017. A chemical view of analogue drug laws in Australia: what is structural similarity? Australian Journal of Forensic Sciences, 49, 605-625. HOEGBERG, L. C. G., CHRISTIANSEN, C., SOE, J., TELVING, R., ANDREASEN, M. F., STAERK, D., CHRISTRUP, L. L. & KONGSTAD, K. T. 2018. Recreational drug use at a major music festival: trend analysis of anonymised pooled urine. Clinical Toxicology, 56, 245-255. HOHMANN, N., MIKUS, G. & CZOCK, D. 2014. Effects and Risks Associated with Novel Psychoactive Substances: Mislabeling and Sale as Bath Salts, Spice, and Research Chemicals. Deutsches Ärzteblatt International, 111, 139-147. HOLLOWAY, K. & BENNETT, T. 2018. Characteristics and correlates of drug use and misuse among university students in Wales: a survey of seven universities. Addiction Research and Theory, 26, 11-19. HOME OFFICE 2017. Drug Misuse: Findings from the 2016/17 Crime Survey for England and Wales. Statistical Bulletin 11/17. London: Home Office. HOPE, V. D., CULLEN, K. J., SMITH, J., JESSOP, L., PARRY, J. & NCUBE, F. 2016. Is the recent emergence of mephedrone injecting in the United Kingdom associated with elevated risk behaviours and blood borne virus infection? Euro Surveill, 21. HOUGH, M., WARBURTON, H., FEW, B., MAY, T., MAN, L.-H., WITTON, J. & TURNBULL, P. J. 2003. A Growing Market: The Domestic Cultivation of Marijuana, York, Joseph Rowntree Foundation. JAMES, D., ADAMS, R. D., SPEARS, R., COOPER, G., LUPTON, D. J., THOMPSON, J. P. & THOMAS, S. H. L. 2011. Clinical characteristics of mephedrone toxicity reported to the UK National Poisons Information Service. Emergency Medicine Journal, 28, 686-689. JANIKOVA, B., FIDESOVA, H., VAVRINCIKOVA, L., MIOVSKY, M. & GRUND, J. P. C. 2016. New psychoactive substances among people who use drugs heavily in europe an inventory of changing drug consumption patterns, shifting drug markets and lagging policy responses. Adiktologie, 16, 93-105. JANSEN, K. L. R. 2000. A Review of the Nonmedical Use of Ketamine: Use, Users and Consequences. Journal of Psychoactive Drugs, 32, 419-433. JOHNSTON, L. D., MIECH, R. A., O'MALLEY, P. M., BACHMAN, J. G., SCHULENBERG, J. E. & PATRICK, M. E. 2015. Monitoring the Future national survey results on drug use: 1975–2017: Overview, key findings on adolescent drug use. The University of Michigan: Institute for Social Research. KAM, P. C. A. & YOONG, F. F. Y. 1998. Gamma-hydroxybutyric acid: an emerging recreational drug. Anaesthesia, 53, 1195-1198. KARILA, L., BILLIEUX, J., BENYAMINA, A., LANÇON, C. & COTTENCIN, O. 2016. The effects and risks associated to mephedrone and methylone in humans: A review of the preliminary evidences. Brain Research Bulletin, 126, 61-67. KARLSSON, A. & BURNS, L. 2018. Australian Drug Trends 2017. Findings from the Illicit Drug Reporting System (IDRS). Australian Drug Trends Series No. 181. Sydney: National Drug and Alcohol Research Centre. KELLY, B. C., WELLS, B. E., PAWSON, M., LECLAIR, A., PARSONS, J. T. & GOLUB, S. A. 2013. Novel psychoactive drug use among younger adults involved in US nightlife scenes. Drug and Alcohol Review, 32, 588-593. KING, L. A. & SEDEFOV, R. 2007. Early-warning system on new psychoactive substance. Operating guidelines. Luxembourg: European Monitoring Centre for Drugs and Drug Addiction, . KINYUA, J., COVACI, A., MAHO, W., MCCALL, A. K., NEELS, H. & NUIJS, A. L. N. 2015. Sewage‐ based epidemiology in monitoring the use of new psychoactive substances: Validation

and application of an analytical method using LC‐MS/MS. Drug Testing and Analysis, 7, 812-818. LAI, F. Y., THAI, P. K., O'BRIEN, J., GARTNER, C., BRUNO, R., KELE, B., ORT, C., PRICHARD, J., KIRKBRIDE, P., HALL, W., CARTER, S. & MUELLER, J. F. 2013. Using quantitative wastewater analysis to measure daily usage of conventional and emerging illicit drugs at an annual music festival. Drug Alcohol Rev, 32, 594-602. LOVRECIC, B. & MERCEDES, L. 2017. Novel psychoactive synthetic cannabinoids and synthetic cathinones: the never-ending story of potential clinical toxicity. MAKKAI, T., MACLEOD, M., VUMBACA, G., HILL, P., CALDICOTT, D., NOFFS, M., TZANETIS, S. & HANSEN, F. 2018. Report on the ACT GTM Pill Testing Pilot: a Harm Reduction Service. Harm Reduction Australia. MCELRATH, K., & O’NEILL, C. (2011). Experiences with mephedrone pre- and post-legislative controls: Perceptions of safety and sources of supply. International Journal of Drug Policy, 22(2), 120-127. doi:http://dx.doi.org/10.1016/j.drugpo.2010.11.001 MEASHAM, F. & NEWCOMBE, R. 2016. What’s so new about new psychoactive substances? Definitions, prevalence, motivations, user groups and a proposed new taxonomy. In: THOM, K. B. & HUNT, G. (eds.) The SAGE Handbook of Drug & Alcohol Studies. London: Sage. MILIANO, C., SERPELLONI, G., RIMONDO, C., MEREU, M., MARTI, M. & DE LUCA, M. A. 2016. Neuropharmacology of New Psychoactive Substances (NPS): Focus on the Rewarding and Reinforcing Properties of Cannabimimetics and Amphetamine-Like Stimulants. Frontiers in Neuroscience, 10. MILLS, B., YEPES, A. & NUGENT, K. 2015. Synthetic Cannabinoids. MIRANDA, C. 2017. Rise in dark web drugs sparks fears in Australia of an likely epidemic. News Corp Australia, April 9 2017. MOHR, A. L. A., FRISCIA, M. & LOGAN, B. K. 2016. Identification and prevalence determination of novel recreational drugs and discovery of their metabolites in blood, urine and oral fluid. Washington, D.C. : US Department of Justice MOORE, K., DARGAN, P. I., WOOD, D. M. & MEASHAM, F. 2013. Do Novel Psychoactive Substances Displace Established Club Drugs, Supplement Them or Act as Drugs of Initiation? The relationship between Mephedrone, Ecstasy and Cocaine. European Addiction Research, 19, 276-282. MOORE, P. Q., WEBER, J., CINA, S. & AKS, S. 2017. Syndrome surveillance of fentanyl-laced heroin outbreaks: Utilization of EMS, Medical Examiner and Poison Center databases. The American Journal of Emergency Medicine, 35, 1706-1708. MORTON, B. 2018. The spice epidemic in UK prisons is putting nurses at risk. The Guardian, 16 May 2018. MOUNTENEY, J., GIRAUDON, I., DENISSOV, G. & GRIFFITHS, P. 2015. Fentanyls: Are we missing the signs? Highly potent and on the rise in Europe. International Journal of Drug Policy, 26, 626-631. MOUNTENEY, J., GRIFFITHS, P., BO, A., CUNNINGHAM, A., MATIAS, J. & PIRONA, A. 2018. Nine reasons why ecstasy is not quite what it used to be. International Journal of Drug Policy, 51, 36-41. MOUNTENEY, J., GRIFFITHS, P., & VANDAM, L. 2016. What is the future for internet drug markets? The internet and drug markets (pp. 127-133). Luxembourg: Publications Office of the European Union. NATIONAL ADVISORY COMMITTEE ON DRUGS AND ALCOHOL 2016. Prevalence of drug use and gambling in Ireland and drug use in Northern Ireland. Dublin: Department of Health. NEWCOMBE, R. & CHRISTENSEN, L. The Bird Killer: What prisoners think about the use of spice in prison. Change, Grow, Live - North West Prisons Conference: "The Changing Face of Drug in Prison", 6 July 2016 2016 HMP Kirkham.

NZ HERALD. 2017. Seven deaths in Kiwi synthetic cannabis epidemic this month. NZ Herald, 21 July 2017. O'BRIEN, K., CHATWIN, C., JENKINS, C., & MEASHAM, F. (2015). New psychoactive substances and British drug policy: A view from the cyber-psychonauts. Drugs: Education, Prevention and Policy, 22(3), 217-223. doi:10.3109/09687637.2014.989959 PALAMAR, J. J., ACOSTA, P., SHERMAN, S., OMPAD, D. C. & CLELAND, C. M. 2016a. Self-reported use of novel psychoactive substances among attendees of electronic dance music venues. American Journal of Drug and Alcohol Abuse, 42, 624-632. PALAMAR, J. J., BARRATT, M. J., CONEY, L. & MARTINS, S. S. 2017. Synthetic Cannabinoid Use Among High School Seniors. Pediatrics, 140. PALAMAR, J. J., MARTINS, S. S., SU, M. K. & OMPAD, D. C. 2015. Self-Reported Use of Novel Psychoactive Substances in a US Nationally Representative Survey: Prevalence, Correlates, and a Call for New Survey Methods to Prevent Underreporting(). Drug and alcohol dependence, 156, 112-119. PALAMAR, J. J., SU, M. K. & HOFFMAN, R. S. 2016b. Characteristics of novel psychoactive substance exposures reported to New York City Poison Center, 2011-2014. American Journal of Drug and Alcohol Abuse, 42, 39-47. PÉTERFI, A., TARJÁN, A., HORVÁTH, G. C., CSESZTREGI, T. & NYÍRÁDY, A. 2014. Changes in patterns of injecting drug use in Hungary: A shift to synthetic cathinones. Drug Testing and Analysis, 6, 825-831. PREKUPEC, M. P., MANSKY, P. A. & BAUMANN, M. H. 2017. Misuse of Novel Synthetic Opioids: A Deadly New Trend. Journal of Addiction Medicine, 11, 256-265. PROSSER, J. M. & NELSON, L. S. 2012. The Toxicology of Bath Salts: A Review of Synthetic Cathinones. Journal of Medical Toxicology, 8, 33-42. QUINTANA, P., VENTURA, M., GRIFELL, M., PALMA, A., GALINDO, L., FORNÍS, I., GIL, C., CARBÓN, X., CAUDEVILLA, F., FARRÉ, M. & TORRENS, M. 2017. The hidden web and the fentanyl problem: Detection of ocfentanil as an adulterant in heroin. International Journal of Drug Policy, 40, 78-83. RÁCZ, J., CSÁK, R., TÓTH, K. T., TÓTH, E., ROZMÁN, K. & GYARMATHY, V. A. 2016. Veni, vidi, vici: The appearance and dominance of new psychoactive substances among new participants at the largest needle exchange program in Hungary between 2006 and 2014. Drug and Alcohol Dependence, 158, 154-158. RALPHS, R., WILLIAMS, L., ASKEW, R. & NORTON, A. 2017. Adding Spice to the Porridge11‘Porridge’ is British slang for a prison sentence. E.g. ‘Doing his porridge’. The term is most commonly thought to be an allusion to the fact that porridge is, or used to be, a common food in prison. The term is also thought to be a pun on the much older slang word for prison, ‘stir’.: The development of a synthetic cannabinoid market in an English prison. International Journal of Drug Policy, 40, 57-69. REUTER, P. & PARDO, B. 2017. Can new psychoactive substances be regulated effectively? An assessment of the British Psychoactive Substances Bill. Addiction, 112, 25-31. ROSENBAUM, C. D., CARREIRO, S. P. & BABU, K. M. 2012. Here today, gone tomorrow...and back again? A review of herbal marijuana alternatives (K2, Spice), synthetic cathinones (bath salts), kratom, Salvia divinorum, methoxetamine, and piperazines. J Med Toxicol, 8, 15- 32. ROXBURGH, A., VAN BUSKIRK, J., BURNS, L. & BRUNO, R. 2017. Drugs and the Internet, Issue 9, December 2017. Sydney: National Drug and Alcohol Research Centre. RUST, K. Y., BAUMGARTNER, M. R., DALLY, A. M. & KRAEMER, T. 2012. Prevalence of new psychoactive substances: A retrospective study in hair. Drug Testing and Analysis, 4, 402-408.

SALOMONE, A., PALAMAR, J. J., GERACE, E., DI CORCIA, D. & VINCENTI, M. 2017. Hair testing for drugs of abuse and new psychoactive substances in a high-risk population. Journal of Analytical Toxicology, 41, 376-381. SANDE, M. 2016. Characteristics of the use of 3-MMC and other new psychoactive drugs in Slovenia, and the perceived problems experienced by users. International Journal of Drug Policy, 27, 65-73. SANTACROCE, R., BOSIO, E., FERRERO, F. & MIGNONE, M. 2018. Life (and death) in Pink: The dangerous rise of synthetic opioids in the new psychoactive substances panorama. European Neuropsychopharmacology, 28, 225-226. SCHIFANO, F., PAPANTI, G. D., ORSOLINI, L. & CORKERY, J. M. 2016. Novel psychoactive substances: the pharmacology of stimulants and hallucinogens. Expert Rev Clin Pharmacol, 9, 943-54. SINDICICH, N. & BURNS, L. 2014. Australian Trends in Ecstasy and Related Drug Markets 2013. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 118. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. SOUSSAN, C., & KJELLGREN, A. (2016). The users of Novel Psychoactive Substances: Online survey about their characteristics, attitudes and motivations. International Journal of Drug Policy, 32, 77-84. doi:http://dx.doi.org/10.1016/j.drugpo.2016.03.007 SPILLER, H. A., RYAN, M. L., WESTON, R. G. & JANSEN, J. 2011. Clinical experience with and analytical confirmation of "bath salts" and "legal highs" (synthetic cathinones) in the United States. Clin Toxicol (Phila), 49, 499-505. STEPHENSON, G., & RICHARDSON, A. (2014). New psychoactive substances in England. A review of the evidence. Crime and Policing Analysis Unit: Home Office Science. SUTHERLAND, R. & BARRATT, M.J. (2017) ‘New & emerging psychoactive substances’ in A Quick Guide to Drugs & Alcohol, third edition (87-93). Sydney; Drug Info, State Library of NSW TAIT, R. J., CALDICOTT, D., MOUNTAIN, D., HILL, S. L. & LENTON, S. 2015. A systematic review of adverse events arising from the use of synthetic cannabinoids and their associated treatment. Clinical Toxicology. TARJÁN, A., DUDÁS, M., WIESSING, L., HORVÁTH, G., RUSVAI, E., TRESÓ, B. & CSOHÁN, Á. 2017. HCV prevalence and risk behaviours among injectors of new psychoactive substances in a risk environment in Hungary—An expanding public health burden. International Journal of Drug Policy, 41, 1-7. THAI, P. K., LAI, F. Y., EDIRISINGHE, M., HALL, W., BRUNO, R., O'BRIEN, J. W., PRICHARD, J., KIRKBRIDE, K. P. & MUELLER, J. F. 2016. Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia. Science of The Total Environment, 545, 250-255. TSCHARKE, B. J., CHEN, C., GERBER, J. P. & WHITE, J. M. 2016. Temporal trends in drug use in Adelaide, South Australia by wastewater analysis. Sci Total Environ, 565, 384-391. UN GENERAL ASSEMBLY, 1975. 1971 Convention on Psychotropic Substances, 9 December 1975, A/RES/3443, available at: http://www.refworld.org/docid/3b00f1ad4b.html [accessed 19 November 2018] UNITED NATIONS OFFICE ON DRUGS AND CRIME 2013. The challenge of new psychoactive substances. Global SMART Programme. Vienna: United Nations Office on Drugs and Crime. UNITED NATIONS OFFICE ON DRUGS AND CRIME 2014. Global SMART Update. Special segment: The changing nature of "ecstasy". Vienna: United Nations Office on Drugs and Crime. UNITED NATIONS OFFICE ON DRUGS AND CRIME 2016a. Global SMART update, volume 16. Post- UNGASS 2016: NPS trends, challenges and recommendations. Vienna: United Nations Office on Drugs and Crime.

UNITED NATIONS OFFICE ON DRUGS AND CRIME 2016b. New psychoactive substances: overview of trends, challenges and legal approaches Commission on Narcotic Drugs Fifty-ninth session Vienna: United Nations Office on Drugs and Crime. UNITED NATIONS OFFICE ON DRUGS AND CRIME. 2018a. The Global SMART Programme [Online]. Available: https://www.unodc.org/unodc/en/scientists/smart-new.html [Accessed 7 April 2018]. UNITED NATIONS OFFICE ON DRUGS AND CRIME 2018b. Global SMART Update. Understanding the synthetic drug market: the NPS factor. Global SMART Update. Vienna: United Nations Office on Drugs and Crime. UNITED NATIONS OFFICE ON DRUGS AND CRIME 2018c. World Drug Report 2017. Vienna: United Nations Office on Drugs and Crime. VALENTE, M. J., GUEDES DE PINHO, P., DE LOURDES BASTOS, M., CARVALHO, F. & CARVALHO, M. 2014. Khat and synthetic cathinones: a review. Arch Toxicol, 88, 15-45. VAN AMSTERDAM, J., BRUNT, T. & VAN DEN BRINK, W. 2015. The adverse health effects of synthetic cannabinoids with emphasis on psychosis-like effects. Journal of Psychopharmacology, 29, 254-263. VAN AMSTERDAM, J., NUTT, D. & VAN DEN BRINK, W. 2013. Generic legislation of new psychoactive drugs. J Psychopharmacol, 27, 317-24. VAN BUSKIRK, J., ROXBURGH, A., BRUNO, R., NAICKER, S., LENTON, S., SUTHERLAND, R., . . . BURNS, L. (2016). Characterising dark net marketplace purchasers in a sample of regular psychostimulant users. International Journal of Drug Policy, 35, 32-37. doi:http://dx.doi.org/10.1016/j.drugpo.2016.01.010. VAN BUSKIRK, J., GRIFFITHS, P., FARRELL, M. & DEGENHARDT, L. 2017. Trends in new psychoactive substances from surface and “dark” net monitoring. The Lancet Psychiatry, 4, 16-18. VAN HOUT, M. C. & BINGHAM, T. 2012. 'A costly turn on'. Patterns of use and perceived consequences of mephedrone based head shop products among Irish injectors. International Journal of Drug Policy, 23, 188-197. VAN NUIJS, A. L. N., CASTIGLIONI, S., TARCOMNICU, I., POSTIGO, C., DE ALDA, M. L., NEELS, H., ZUCCATO, E., BARCELO, D. & COVACI, A. 2011. Illicit drug consumption estimations derived from wastewater analysis: A critical review. Science of The Total Environment, 409, 3564-3577. VENTO, A. E., MARTINOTTI, G., CINOSI, E., LUPI, M., ACCIAVATTI, T., CARRUS, D., SANTACROCE, R., CHILLEMI, E., BONIFACI, L., DI GIANNANTONIO, M., CORAZZA, O. & SCHIFANO, F. 2014. Substance Use in the Club Scene of Rome: A Pilot Study. BioMed Research International, 2014, 5. VOGELS, N., BRUNT, T. M., RIGTER, S., DIJK, P. V., VERVAEKE, H. & NIESINK, R. J. M. 2009. Content of ecstasy in the Netherlands: 1993–2008. Addiction, 104, 2057-2066. WALSH, C. (2011). Drugs, the Internet and Change. Journal of Psychoactive Drugs, 43(1), 55-63. doi:10.1080/02791072.2011.566501. WELTER, S., LÜCKE, C., LAM, A. P., CUSTAL, C., MOELLER, S., SÖRÖS, P., THIEL, C. M., PHILIPSEN, A. & MÜLLER, H. H. O. 2017. Synthetic cannabinoid use in a psychiatric patient population: A pilot study. European Addiction Research, 23, 182-193. WIESSING, L. & FOLCH, C. 2016. New psychoactive substances, drug injecting and sex in recreational settings: increased risk of HIV and HCV and opportunities for prevention. Revista Enfermedades Emergentes, 15, 57-61. WILLE, S. M. R., RICHEVAL, C., NACHON-PHANITHAVONG, M., GAULIER, J. M., DI FAZIO, V., HUMBERT, L., SAMYN, N. & ALLORGE, D. 2017. Prevalence of new psychoactive substances and prescription drugs in the Belgian driving under the influence of drugs population. Drug Testing and Analysis.

WINSTOCK, A., BARRATT, M., FERRIS, J. & MAIER, L. 2017. Global Drug Survey 2017. Global overview and highlights [Online]. Available: https://www.globaldrugsurvey.com/wp- content/themes/globaldrugsurvey/results/GDS2017_key-findings-report_final.pdf [Accessed 7 April 2018]. WINSTOCK, A., BARRATT, M., MAIER, L. &FERRIS, J. 2018. Global Drug Survey 2018. Key Findings Report [Online]. Available: https://www.globaldrugsurvey.com/gds-2018/ [Accessed 15 November 2018]. WINSTOCK, A., LYNSKEY, M., BORSCHMANN, R. & WALDRON, J. 2015. Risk of emergency medical treatment following consumption of cannabis or synthetic cannabinoids in a large global sample. J Psychopharmacol, 29, 698-703. WONGUPPA, R. & KANATO, M. 2017. The prevalence and associated factors of new psychoactive substance use: A 2016 Thailand national household survey. Addictive Behaviors Reports. WOOD, D. M. & DARGAN, P. I. 2012. Understanding How Data Triangulation Identifies Acute Toxicity of Novel Psychoactive Drugs. Journal of Medical Toxicology, 8, 300-303. WOOD, D. M., HILL, S. L., THOMAS, S. H. L. & DARGAN, P. I. 2014. Using poisons information service data to assess the acute harms associated with novel psychoactive substances. Drug Testing and Analysis, 6, 850-860. WOOD, D. M., SEDEFOV, R., CUNNINGHAM, A. & DARGAN, P. I. 2015. Prevalence of use and acute toxicity associated with the use of NBOMe drugs. Clinical Toxicology, 53, 85-92. YAP, S. & DRUMMER, O. H. 2016. Prevalence of new psychoactive substances in Victorian fatally- injured drivers. Australian Journal of Forensic Sciences, 48, 230-243.

2. PAPER ONE: TYPOLOGY OF NEW PSYCHOACTIVE SUBSTANCE USE AMONG

THE GENERAL AUSTRALIAN POPULATION

Rachel Sutherland*1, Amy Peacock1,2, Amanda Roxburgh1, Monica J. Barratt1,3,4, Lucinda Burns1, Raimondo Bruno2

1National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia 2 School of Medicine (Psychology), Faculty of Health, University of Tasmania, Hobart, TAS, 7001, Australia

3National Drug Research Institute, Faculty of Health Sciences, Curtin University, Perth, WA, 6845, Australia 4Behaviours and Health Risks Program, Burnet Institute, 85 Commercial Rd, Melbourne VIC 3004, Australia

Paper one has been published in Drug and Alcohol Dependence (Sutherland et al., 2018)

2.1 Copyright statement

I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations.

Sutherland, R., Peacock, A., Roxburgh, A., Barratt, M.J., Burns, L. & Bruno, R. (2018). Typology of new psychoactive substance use among the general population. Drug and Alcohol Dependence, 188; 126-134

Rachel Sutherland August 2018

2.2 Preamble

Chapter one has shown that although prevalence of NPS use is relatively low among general population samples, rates of use are elevated amongst vulnerable, high-risk groups. In particular, there is considerable evidence that NPS use largely occurs amongst people who use other illicit substances. However, given that most of these studies are undertaken using samples of people who use drugs (or where the probability of substance use is high), the generalisability of these findings to the general population are limited.

This chapter (paper 1) will address this issue by using data from the 2013 National Drug Strategy Household Survey (an Australian general population survey, where inclusion is not based on substance use). Specifically, it will focus on examining typologies of illicit drug consumers in the general Australian population, with a view to determining: (1) if there is a distinct group of exclusive NPS consumers (i.e. people who report use of NPS but no other illicit substances); (2) if there is no distinct group of exclusive NPS consumers, what ‘type’ of consumers have the highest probability of NPS use; and (3) whether the group/s with the highest probability of NPS use differ from other consumer groups in terms of demographic characteristics and drug-related risk behaviours. The findings of this paper will improve our understanding of the intersection between established illicit drugs and NPS and provide guidance around the targeting of health messaging on NPS in the Australian context.

2.3 Abstract

Aim: The aim of this study was to examine the typology of Australian illicit drug consumers to determine whether those who use new psychoactive substances (NPS) differ from those using other illicit substances.

Methods: Data were from the 2013 National Drug Strategy Household Survey, a representative population study; analyses were limited to participants reporting past year illicit drug use (including NPS; n=3,309). Latent class analysis identified groups based on past year substance use, and a weighted multivariable, multinomial regression model was used to examine characteristics associated with group membership.

Results: Six consumer typologies were identified: cannabis consumers (46%), pharmaceutical consumers (21%), ecstasy and cocaine consumers (19%), amphetamine and cannabis consumers (7%), polysubstance consumers (6%), and inhalant consumers (2%). Sixteen participants (total sample: 0.07%; NPS consumers: 5.7%) reported exclusive NPS use. Synthetic cannabinoid receptor agonist use was highest among amphetamine and cannabis consumers and polysubstance consumers; other NPS use was highest among polysubstance consumers. Polysubstance consumers were younger than all other groups, and more likely to engage in dangerous activities while under the influence of substances, inject drugs and report hazardous alcohol consumption. Amphetamine and cannabis consumers were more likely to report trouble ceasing their drug use.

Conclusion: We found no distinct profile of NPS-only consumers; however, NPS use was a marker for more problematic patterns of use. Our findings suggest that specialised NPS interventions or harm reduction messages may not be required in the Australian context; rather, they could be based upon existing responses to drug use.

Keywords: New psychoactive substances; NPS; synthetic cannabinoids; typology; latent class analysis

2.4 Introduction

Over the past decade, the number and range of substances collectively referred to as ‘new psychoactive substances’ (NPS) has increased dramatically. NPS are defined by the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) as substances which do not fall under international drug controls, but which may pose a public health threat (European Monitoring Centre for Drugs and Drug Addiction, 2016b). However, there are a number of problems with this definition (e.g. mere psychoactivity is assumed to be a public health threat; Barratt et al., 2017), and in practicality the term ‘NPS’ has come to include drugs which have previously not been well-established in recreational drug markets, or which are not well documented. In 2016 over 600 NPS were being monitored by the European Union, of which 70% were detected in the past five years (European Monitoring Centre for Drugs and Drug Addiction, 2016b).

Despite the rapid growth of the NPS market, and associated concerns of widespread use, prevalence appears to be relatively low amongst adult general population samples (i.e. ≤1.2%; Home Office, 2017, Australian Institute of Health & Welfare, 2017, Palamar et al., 2015). The use of these substances is thought to be concentrated amongst existing illicit drug consumers (Moore et al., 2013, Sutherland et al., 2016), and other disadvantaged groups (e.g. homeless, prisoners, mentally ill, people who inject drugs; European Monitoring Centre for Drugs and Drug Addiction, 2017b, Joseph et al., 2017, Manseau et al., 2017, Rácz et al., 2016, Tarján et al., 2017). Concerns remain, however, that ‘novice’ consumers may initiate NPS use, particularly given use of the internet as a means of supply. Indeed, the argument that NPS appeal to novice consumers has been used to advocate for their prohibition, regardless of their harm profile, on the premise of preventing normalisation of NPS use and transition into other illicit drug use (Intergovernmental Committee on Drugs, 2014).

Our ability to address such concerns is limited by the fact that the comparability of NPS consumers with other illicit drug consumers has not been properly explored. Moreover, it remains unclear whether there is a distinct group of exclusive NPS consumers (i.e. people who use NPS but no other illicit substances), or whether there are particular groups of illicit drug consumers that report elevated rates of NPS use. In order to examine these questions, data from samples where inclusion is not based on illicit substance use, and where people may be consuming a broad range of substances, are required. General population data provide an important opportunity to answer this research question, with latent class analysis (LCA) a

particularly suitable method for investigating whether distinct subtypes or classes of NPS consumers exist.

In identifying NPS consumers, it is critical to explore their relative demographic and risk profile. Previous studies have shown that people who report NPS use are typically younger, more likely to be male, report higher levels of poly drug use, younger age of drug initiation, more problematic drug use (e.g. bingeing), and are more likely to report online purchasing behaviours relative to illicit drug consumers who do not use NPS (Bonar et al., 2014, Bruno et al., 2012, Lawn et al., 2014, Palamar, 2015, Palamar and Acosta, 2015, Emmanuel and Attarad, 2006). However, these studies are generally based on samples of people who use illicit drugs, limiting their capacity to identify unique NPS groups (including people using NPS but no other illicit substances).

As such, this study uses data from a general population sample to:

1) Examine the typology of Australian illicit drug consumers to determine if there is a distinct group of exclusive NPS consumers, and if not, determine which consumer ‘type’ is most likely to use NPS. 2) Compare profiles across these subgroups, based on demographics and risk behaviours. This information will improve our understanding of the profiles of NPS users, allowing for the development of more targeted harm reduction messages.

2.5 Method

2.5.1 Study design and participants

This paper uses data from the 2013 National Drug Strategy Household Survey (NDSHS; for full protocol details, see Australian Institute of Health & Welfare, 2014). The NDSHS, conducted on a triennial basis, collects data from the Australian residential population, and employs a multistage stratified sampling methodology designed to provide a close-to-random sample to obtain data on drug and alcohol use in the Australian population over 14 years of age. In 2013, 23,855 respondents participated in the survey, with analyses based on a subset of participants who reported past year use of a range of licit drugs used for non-medical purposes (e.g. opioid analgesics) and/or illicit drugs, including NPS (n=3,309; 13.9%).

2.5.2 Measures relevant to the current study

2.5.2.1 Licit and illicit drug use

Participants were asked about their lifetime and past twelve-month use of a range of licit and illicit substances, including tobacco, alcohol, pharmaceutical drugs used for non-medical purposes (i.e. pain killers/analgesics, tranquilisers/sleeping pills, steroids, methadone or buprenorphine, other opiates/opioids), methamphetamine, cannabis, heroin, cocaine, hallucinogens, ecstasy, ketamine, GHB and inhalants. The 2013 NDSHS was the first in the survey series to include questions about NPS. Specifically, participants were asked about their lifetime and past 12 month use of “synthetic cannabis/cannabinoids (e.g. K2, Spice, Kronic)” and “novel psychoactive substances (e.g. mephedrone, methylone, BZP, 2C-B, DMT, MDAI, MDPV)”. Hence, for the purposes of this paper NPS will be split into two categories: synthetic cannabinoids (hereafter referred to as synthetic cannabinoid receptor agonists; SCRA) and other NPS.

2.5.2.2 Demographics and mental health

The 2013 NDSHS survey collected a range of demographic information, including age, gender, income (AUD), employment and educational status. Relative socio-economic advantage and disadvantage was measured using the Socio-Economic Indexes for Areas (SEIFA), developed by the Australian Bureau of Statistics (Australian Bureau of Statistics, 2013). From this index, areas can be divided into quintiles, with the lowest quintile representing the most disadvantaged areas and the highest quintile representing the most advantaged. This SEIFA quintile variable was included in analyses as an area-level indicator of socio-economic status (SES), with the bottom two quintiles combined to signify the most disadvantaged quintiles.

Participants were also administered the Kessler 10 (K10) Psychological Distress Scale to assess psychological distress (Kessler et al., 2003). The K10 is a 10-item screening tool utilizing a five- point response scale (1 ‘none of the time’ to 5 ‘all of the time’); a cut-off score of ≥22 (score range 10-50) was used to measure high to very high psychological distress (Andrews and Slade, 2001).

2.5.2.3 Alcohol and drug-related risk behaviours

The 2013 NDSHS asked participants how many days of work, school, TAFE or university they had missed because of their alcohol use, and how many days they had missed because of their use of drugs other than alcohol, in the past three months. Responses to this variable were recoded into a binary variable with yes/no response options (i.e. did the participant miss any days of work, school, TAFE or university because of their alcohol and/or drug use).

They were also asked if, in the last 12 months, they had done any of the following activities while under the influence of or affected by alcohol or illicit drugs: went to work; went swimming; operated a boat; drove a motor vehicle; operated hazardous machinery; created a public disturbance or nuisance; cause damage to property; stole money, goods or property; verbally abused someone; or physically abused someone.

Participants who had used non-medicinal pain killers/analgesics, tranquilisers/sleeping pills, methamphetamine, cannabis, heroin, tobacco, steroids, buprenorphine, cocaine, hallucinogens, ecstasy or inhalants were asked if, in the past 12 months, they could not stop or cut down on their use of these substances even though they wanted to or tried to. Participants who had not used these substances were coded as ‘no’.

The Alcohol Use Disorders Identification Test Consumption questions (AUDIT-C) was administered as a validated screening measure of hazardous patterns of alcohol consumption (Bradley et al., 2007, Bush et al., 1998). This 3-item scale assesses quantity and frequency of use, with higher scores (range 0-12) indicating more hazardous use. Participants were categorised based on a cut-off indicative of high risk drinking (scores of 9 and above; Harris et al., 2010). Participants who had not consumed alcohol in the past year were given a score of ‘0’.

Participants were also asked if they had injected any drugs (where injection was the non- intended route of administration for pharmaceutical medicines) in the last 12 months.

2.5.3 Statistical analysis

To address the first aim, latent class models (one to eight classes) were estimated using past year drug and alcohol use. Specifically, the models were based on past 12 month use of the following drugs: cannabis, ecstasy, meth/amphetamine, cocaine, hallucinogens, inhalants, SCRA, other NPS, pharmaceutical drugs used for non-medical purposes (i.e. pain killers/analgesics, tranquilisers/sleeping pills, steroids, methadone or buprenorphine, other opiates/opioids combined), ketamine, GHB, tobacco (daily) and alcohol (weekly). The fit of each model was compared using MPlus version 7 (Muthén and Muthén, 2010). Following protocols adopted in past published latent class analyses (LCA) (Ramo et al., 2010), four criteria were used to assess model fit. The first criterion, the Lo-Mendell-Rubin adjusted log-likelihood ratio test (LMR-ALRT) statistic (Lo et al., 2001) was used to compare fit of a k class model with a k-1 class model, with a low p value (<.050) indicating that the latter should be rejected in favour of the model with one additional class. The second and third criteria adopted were the Akaike’s Information Criterion (AIC) and the Bayesian Information Criterion (sample-size adjusted; ssaBIC); these models balance likelihood and model fit, with lower values indicating better 54

model fit. The fourth criterion, the entropy value, was an index of classification accuracy of the given classes, with higher values (range 0.0-1.0) indicating better differentiation of individuals into classes.

To address the second aim, correlates of latent class membership were analysed using bivariate and multivariable multinomial logistic regression conducted in SAS Version 9.4: correlates found to be significant (p<.05) in the bivariate models were entered into the final multivariable model. Descriptive statistics comprised percentages for categorical data, means for normally distributed continuous variables, and medians for continuous data with significant positive skew and/or kurtosis.

Given this is a general population sample, both the LCA and regression analyses were conducted taking into account the effects of complex sampling methods. Data were weighted to correct for differential response rates and to account for over-sampling in some of the smaller jurisdictions. Strata and cluster variables were used in the analyses to account for the multilevel stratification of recruitment of the sample. For further information regarding these procedures please refer to the 2013 NDSHS technical report (Roy Morgan Research, 2014).

2.6 Results

2.6.1 Sample characteristics

Among the entire sample (n=23,855), the most commonly used illicit substance was cannabis (10.2%), followed by ecstasy (2.5%), methamphetamine (2.1%), cocaine (2.1%), hallucinogens (1.3%), SCRA (1.2%), inhalants (0.8%), NPS (excluding SCRA; 0.4%), ketamine (0.3%), heroin (0.1%) and GHB (<0.1%). Non-medicinal pharmaceutical drug use in the preceding year was reported by 4.7% of the sample, with past-year alcohol use reported by the majority (78.3%) of the sample. Very few participants (0.07% of entire sample; 5.7% of NPS consumers) reported use of SCRA and/or NPS but no other illicit substances.

Among those who reported past year use of any illicit substance (n=3,309), the sample was predominantly male (59%), with a mean age of 36 years. Participants were relatively well- educated: two-thirds (67%) had completed a trade certificate or other educational qualification, although most (63%) reported a gross (i.e. before tax) annual income of <52,000 AUD. Almost one-in-five participants (18%) reported high levels of psychological distress, almost half (47%) had engaged in some form of ‘hazardous’ behaviour (e.g. driving a vehicle, destroying property) while under the influence of alcohol and/or drugs, and one-third (34%) reported that they had experienced difficulties ceasing their drug use in the past year.

2.6.2 Model selection

Examination of model fit statistics showed that AIC and ssaBIC was lowest for the 8-class model, whilst entropy was highest for the 2-class model (Table 6 in Supplementary Material). Notably, the LMR-ALRT showed that the 6-class solution provided a significant improvement in fit over the 5-class model, but the 7-class solution did not provide a significant improvement over the 6- class model, nor did the 8-class provide any significant improvement over the 7-class model. Examination of class composition alongside fit statistics further supported selection of the 6- class model: each class was substantive and clearly distinct in their patterns of drug use.

2.6.3 Latent Class Probabilities and Class Definitions

Response probabilities for each class are shown in Figure 3 (presented across two figures to facilitate ease of interpretation). Classes are described as follows: cannabis consumers (46%) - comprising people who had a high probability of past year cannabis use (1.0) and a low probability of any other illicit drug use; pharmaceutical consumers (21%) - comprising people who had a high probability of non-medicinal pharmaceutical drug use (1.0) and a low probability of any other illicit drug use; ecstasy and cocaine consumers (19%) – comprising people who had a high probability of cocaine (0.50) and ecstasy (0.48) use, as well as cannabis (0.64) and weekly alcohol (0.73) use; and inhalant consumers (2%) – comprising people who had a high probability of inhalant use (1.0) and a low probability of any other illicit drug use.

Two additional groups of note include: amphetamine and cannabis consumers (7%) and polysubstance consumers (6%). The former had a high probability of past year amphetamine (0.58) and cannabis (0.82) use and daily tobacco (0.79) use, and the highest probability of SCRA use (0.35). The latter comprised people who had a high probability of past year use of multiple drugs. This group had the highest probability of past year ecstasy (0.997), amphetamine (0.71), cocaine (0.61), hallucinogen (0.66), GHB and ketamine (0.26), and weekly alcohol use (0.79). This group also had the highest probability of other NPS use (0.31), and the second highest probability of SCRA use (0.31).

Figure 3: Past 12-month licit and illicit drug use according to group for the 6-class solution

1 Cannabis consumers 0.9 (n=1527) 0.8 Pharmaceutica l consumers 0.7 (n=687)

0.6 Ecstasy and cocaine 0.5 consumers (n=620) 0.4 Amphetamine and cannabis 0.3 consumes (n=227) 0.2 Polydrug Proportion reporting use consumers 0.1 (n=189) 0

Figure 3 (continued): Past 12-month licit and illicit drug use according to group for the 6-class solution 1 Cannabis consumers 0.9 (n=1527) Pharmaceutica 0.8 l consumers (n=687) 0.7 Ecstasy and cocaine 0.6 consumers (n=620) 0.5 Amphetamine and cannabis 0.4 consumes (n=227) Polydrug 0.3 consumers 0.2

Proportion reporting use Inhalant 0.1 consumers (n=59) 0

2.6.4 Correlates of subgroup membership

To determine if the consumer groups with the highest rates of NPS use differed from other illicit drug consumers, the bivariate and multinominal regression models were run with both amphetamine and cannabis consumers and polysubstance consumers as the referent categories (these two groups had the highest probability of SCRA and other NPS use). In both situations, all variables were found to be significant in the bivariate analyses (see Table 7 in Supplementary Material) and were therefore included in the final multivariable multinomial regression models (see Table 5). Descriptive statistics for each group are outlined in Table 4.

Table 4: Demographics and risk behaviours according to group People who People who

had not had Pharmaceutical Ecstasy and Amphetamine Polysubstance Inhalant Cannabis consumed consumed consumers cocaine and cannabis consumers consumers consumers any illicit an illicit n=762 consumers consumers n=150 n=73 n=1541 substance substance/s n=571 n=212

N=20,024 N=3309 Demographics and Mental Health:

Mean age (years) 44.6 36.3 34.6 48.5 30.5 30.6 26.6 55.2

Male % 47.8 59.4 61.4 48.4 62.6 61.6 70.0 61.8 Completed trade or other educational 63.4 66.9 64.9 65.1 75.9 56.3 77.3 54.2 qualification % Unemployed % 6.4 10.2 10.6 6.8 7.8 19.0 15.4 11.9

Gross annual income <$52,000 % 62.3 63.3 66.0 63.1 53.9 75.6 61.3 59.5

Low SES % 36.6 38.0 39.9 41.6 25.7 52.5 28.5 49.2

K10 score ≥22 % 9.2 18.4 15.9 20.0 16.4 33.5 24.3 9.1

Risk Behaviours:

AUDIT-C score ≥9 % 17.5 14.8 6.4 24.9 27.4 35.9 7.1 Dangerous activity whilst under AOD 46.5 45.3 18.9 58.4 74.4 84.5 22.9 influence past year % Missed work/school/TAFE/university 9.7 7.0 3.9 13.6 14.5 26.9 2.4 for AOD reason in past 3 months % Trouble ceasing drug use in past year 33.8 31.7 25.8 29.0 72.3 49.9 20.6 %

Table 4 (continued): Demographics and risk behaviours according to group People who People who

N=20,024 N=3309

Injected any drug (past year) % 2.1 0.5 0.7 1.3 13.8 8.9 0

Daily cannabis 8.8 10.9 0 4.5 29.9 15.1 0

Weekly or more meth 2.2 0 0 2.4 18.5 8.7 0 Note: Figures for amphetamine and cannabis consumers, and polysubstance consumers, are bolded since they are the two referent categories (i.e. these two groups have the highest probability of SCRA and other NPS use). AUDIT-C: Alcohol Use Disorders Identification Test; K10: Kessler Psychological Distress Scale; SES: socio-economic status.

2.6.5 Multivariable Multinomial Regression Models

2.6.5.1 Amphetamine and cannabis consumers as the referent group

2.6.5.1.1 Demographics Pharmaceutical consumers, inhalant consumers and cannabis consumers were significantly older than amphetamine and cannabis consumers, whilst polysubstance consumers were significantly younger. Pharmaceutical consumers had significantly lower odds of being unemployed and ecstasy and cocaine consumers had significantly lower odds of earning a gross annual income of <$52,000, compared to the amphetamine and cannabis consumer group. All groups (except inhalant consumers) had significantly lower odds of residing in low SES areas, and inhalant consumers had significantly lower odds of reporting high levels of psychological distress, than amphetamine and cannabis consumers. 2.6.5.1.2 Risk behaviours Pharmaceutical consumers, inhalant consumers and cannabis consumers had significantly lower odds of having engaged in dangerous activities while under the influence of drugs and/or alcohol in the past year, compared to amphetamine and cannabis consumers. Conversely, polysubstance consumers had significantly higher odds of having engaged in such activities. All groups had significantly lower odds of having had trouble ceasing their drug use in the past year compared to amphetamine and cannabis consumers. Inhalant consumers and cannabis consumers also had significantly lower odds of having injected any drug in the past year. 2.6.5.2 Polysubstance consumers as the referent group

2.6.5.2.1 Demographics and mental health All groups were significantly older than polysubstance consumers, with pharmaceutical consumers also less likely to be male. Inhalant consumers and cannabis consumers had significantly lower odds of having completed a tertiary qualification, and cannabis consumers had significantly higher odds of having a gross annual income of <$52,000, compared to polysubstance consumers. Amphetamine and cannabis consumers had significantly higher odds of residing in low SES areas. 2.6.5.2.2 Alcohol and drug-related risk behaviours Cannabis consumers had significantly lower odds of scoring ≥9 on the AUDIT-C, compared to polysubstance consumers. All groups had significantly lower odds of having engaged in dangerous activities while under the influence of drugs and/or alcohol in the past year, with cannabis consumers also having lower odds of having missed work or school due to their alcohol and drug use. As noted above, amphetamine and cannabis consumers had significantly higher

odds of having had trouble ceasing their drug use in the past year, while pharmaceutical consumers had lower odds of trouble ceasing drug use. Both inhalant consumers and cannabis consumers had significantly lower odds of having injected any drug in the past year, compared to polysubstance consumers.

Table 5: Demographics and risk behaviours according to group, with polysubstance consumers and amphetamine and cannabis consumers as the referent groups: Multivariable models Polysubstance consumers vs. Amphetamine and cannabis consumers vs. Cannabis Pharmaceutical Ecstasy and Amphetamine Inhalant Cannabis Pharmaceutical Ecstasy and Polysubstance Inhalant consumers consumers cocaine and cannabis consumers consumers consumers cocaine consumer consumers Outcome AOR AOR consumers consumers AOR AOR AOR consumers AOR AOR (95% CI; p) (95% CI; p) AOR AOR (95% CI; p) (95% CI; p) (95% CI; p) AOR (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) Demographics and

Mental Health: 1.04 (1.01- 1.09 (1.06- 1.12 (1.09- 1.05 (1.02- 1.13 (1.07- 1.03 (1.01- 1.07 (1.04- 0.99 (0.97- 0.95 (0.92- 1.07 (1.02- Mean age (years) 1.08; 1.12)*** 1.16)*** 1.09; 0.004)** 1.18)*** 1.06; 0.006)** 1.10)*** 1.02; 0.57) 0.98; 0.004)** 1.12; 0.004)** 0.006)**

0.77 (0.42- 0.39 (0.20-0.78; 0.66 (0.35- 0.71 (0.33- 0.64 (0.17- 1.09 (0.61- 0.55 (0.28-1.08; 0.93 (0.49- 1.41 (0.65- 0.90 (0.23- Male % 1.42; 0.41) 0.008)** 1.24; 0.19) 1.53; 0.38) 2.49; 0.52) 1.95; 0.77) 0.08) 1.74; 0.82) 3.04; 0.38) 3.55; 0.89)

Completed 0.40 (0.19- 0.49 (0.21-1.11; 0.56 (0.26- 0.42 (0.16- 0.21 (0.05- 0.93 (0.48- 1.15 (0.54-2.44; 1.33 (0.65- 2.36 (0.90- 0.50 (0.13- trade/qualification % 0.83; 0.01)* 0.09) 1.22; 0.15) 1.11; 0.08) 0.83; 0.03)* 1.81; 0.84) 0.72) 2.70; 0.43) 6.19; 0.08) 1.94; 0.32)

0.56 (0.18- 0.18 (0.04-0.78; 0.29 (0.07- 0.77 (0.17- 3.60 (0.53- 0.73 (0.25- 0.23 (0.05-0.98; 0.37 (0.09- 1.29 (0.29- 4.65 (0.70- Unemployed % 1.74; 0.32) 0.02)* 1.14; 0.08) 3.44; 0.74) 24.65; 0.19) 2.12; 0.56) 0.046)* 1.50; 0.16) 5.73; 0.74) 31.10; 0.11)

Gross annual income 2.00 (1.10- 1.16 (0.59-2.31; 0.88 (0.46- 2.05 (0.92- 1.09 (0.31- 0.98 (0.53- 0.57 (0.28-1.15; 0.43 (0.23- 0.49 (0.22- 0.53 (0.15- <$52,000 % 3.64; 0.02)* 0.67) 1.68; 0.69) 4.55; 0.08) 3.83; 0.90) 1.78; 0.94) 0.11) 0.81; 0.009)** 1.09; 0.08) 1.89; 0.33) 1.09 (0.61- 1.04 (0.53-2.04; 0.73 (0.40- 2.30 (1.11- 1.71 (0.48- 0.47 (0.27- 0.45 (0.23-0.89; 0.32 (0.17- 0.44 (0.21- 0.75 (0.21- Low SES % 1.93; 0.78) 0.91) 1.34; 0.31) 4.77; 0.03)* 6.12; 0.41) 0.85; 0.01)* 0.02)* 0.59)*** 0.91; 0.03)* 2.62; 0.65) 0.94 (0.46- 1.74 (0.75-4.05; 0.94 (0.46- 1.48 (0.64- 0.13 (0.01- 0.64 (0.33- 1.18 (0.52-2.65; 0.64 (0.31- 0.68 (0.29- 0.09 (0.01- K10 score ≥22 % 1.90; 0.86) 0.20) 1.93; 0.87) 3.43; 0.36) 1.49; 0.10) 1.22; 0.17) 0.70) 1.29; 0.21) 1.56; 0.36) 0.99; 0.049)*

Table 5 (continued): Demographics and risk behaviours according to group, with polysubstance consumers and amphetamine and cannabis consumers as the referent groups: Multivariable models Polysubstance consumers vs. Amphetamine and cannabis consumers vs. Cannabis Pharmaceutical Ecstasy and Amphetamine Inhalant Cannabis Pharmaceutical Ecstasy and Polysubstance Inhalant consumers consumers cocaine and cannabis consumers consumers consumers cocaine consumer consumers AOR AOR consumers consumers AOR AOR AOR consumers AOR AOR (95% CI; p) (95% CI; p) AOR AOR (95% CI; p) (95% CI; p) (95% CI; p) AOR (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) Risk Behaviours: 0.54 (0.29- 0.45 (0.19-1.04; 0.79 (0.42- 0.55 (0.24- 0.53 (0.09- 0.98 (0.51- 0.81 (0.33-2.02; 1.44 (0.71- 1.83 (0.81- 0.97 (0.15- AUDIT-C score ≥9 % 0.99; 0.04)* 0.06) 1.48; 0.45) 1.23; 0.15) 3.29; 0.50) 1.89; 0.95) 0.66) 2.89; 0.31) 4.12; 0.15) 6.14; 0.98) Dangerous activity 0.14 (0.06- 0.07 (0.03- 0.23 (0.10- 0.32 (0.12- 0.08 (0.02- 0.45 (0.24- 0.22 (0.11- 0.72 (0.37- 3.18 (1.16- 0.26 (0.07- whilst under AOD 0.33)*** 0.16)*** 0.54)*** 0.86; 0.02)* 0.35)*** 0.85; 0.01)* 0.43)*** 1.43; 0.35) 8.67; 0.02)* 0.99; 0.049)* influence past year % Missed work/school/TAFE/u 0.38 (0.18- 0.42 (0.15-1.15; 0.68 (0.32- 0.57 (0.21- 0.40 (0.04- 0.66 (0.29- 0.72 (0.25-2.09; 1.19 (0.50- 1.75 (0.65- 0.70 (0.08- niversity for AOD 0.79; 0.01)* 0.09) 1.44; 0.32) 1.53; 0.27) 3.64; 0.42) 1.49; 0.32) 0.55) 2.85; 0.70) 4.67; 0.27) 6.45; 0.75) reason in past 3 months % Trouble ceasing drug 0.61 (0.32- 0.36 (0.17-0.75; 0.55 (0.29- 3.54 (1.55- 0.23 (0.05- 0.17 (0.09- 0.10 (0.05- 0.16 (0.08- 0.28 (0.12- 0.07 (0.01- use in past year % 1.14; 0.12) 0.007)** 1.05; 0.07) 8.09; 0.003)** 1.14; 0.07) 0.33)*** 0.22)*** 0.32)*** 0.65; 0.003)** 0.32)*** Injected any drug in 0.02 (0.004- 0.09 (0.01-1.00; 0.18 (0.02- 0.32 (0.08- 0.06 (0.01- 0.29 (0.03-2.75; 0.57 (0.07- 3.11 (0.81- <0.001*** <0.001*** past year % 0.11)*** 0.05) 1.66; 0.13) 1.24; 0.10) 0.36; 0.002)** 0.28) 4.37; 0.59) 11.94; 0.10) Note. An odds ratio (OR) or adjusted odds ratio (AOR) of 1 indicates the event is equally probable in each group, > 1 indicates the event is more likely to occur in the non-reference group relative to the reference group, and <1 indicates the event is less likely to occur in the non-reference group relative to the reference group. *p<.050; **p<.010; ***p<.001; exact p values not presented where <0.001. CI: confidence interval; AOD: alcohol and/or drugs; AUDIT-C: Alcohol Use Disorders Identification Test; K10: Kessler Psychological Distress Scale; SES: socio-economic status.

2.7 Discussion

We found that there was no distinct profile of exclusive SCRA or other NPS consumers, with very few participants (n=16; 5.7% of NPS consumers) reporting sole use of these substances. Rather, SCRA and NPS consumers mostly fell into the amphetamine and cannabis consumer and polysubstance consumer groups, respectively, providing support for the argument that most NPS consumers use a range of other illicit substances. Polysubstance consumers (the group most likely to use NPS) were found to be significantly younger than all other groups, and were generally more educated, with few differences in terms of income or socio-economic status. They were also more likely to engage in a range of drug- related risk behaviours, including undertaking dangerous activities while under the influence of drugs and/or alcohol (most commonly driving a motor vehicle), injecting drugs and hazardous alcohol consumption. This suggests that polysubstance consumers are a high-risk taking group, regardless of their NPS use, and as such, may not need specific NPS interventions. Rather, existing harm reduction messages surrounding drug use (e.g. the dangers of mixing substances, driving while under the influence, safe injecting practices) could be tailored for poly drug consumers more generally. Amphetamine and cannabis consumers (the group most likely to use SCRA) were also quite young, however were more disadvantaged in terms of socio-economic status. They were more likely than all other groups to report trouble ceasing their drug use. Given that persistent desire or repeated unsuccessful attempts to quit is one of the markers of substance use disorder (Hasin et al., 2013), it would seem that this is the group that may benefit most from treatment interventions. Indeed, existing treatment centres could incorporate the use of SCRA and other NPS into their screening/assessment processes, with treatment plans tailored accordingly. Amphetamine and cannabis consumers were also more likely than most other groups (excluding polysubstance and ecstasy and cocaine consumers) to engage in hazardous activity while under the influence of drugs and/or alcohol. To date, responses to the NPS market have largely been regulatory (European Monitoring Centre for Drugs and Drug Addiction, 2016c), with uncertainty regarding the most appropriate health- and drug-related interventions. More specifically, it has been unclear whether there needs to be specialised NPS interventions or harm reduction messages, and if so what these would look like. Our findings suggest that interventions could be based upon existing responses to drug use and targeted towards illicit drug consumers more generally. In contrast to Vreeker et al. (2017) (who concluded that NPS users may be considered a distinct group of users who need another approach in terms of prevention), we found that there was no distinct profile of NPS or SCRA 65

consumers, at least in the Australian population, with the probability of use of these substances highest among amphetamine and cannabis consumers and polysubstance consumer groups - both of which were found to have higher rates of drug-related harms and/or risk behaviours. Indeed, it seems that the use of SCRA or other NPS may be indicative of more problematic patterns of drug use; a ‘red flag’ which could be easily assessed by health professionals working in the drug and alcohol field. Furthermore, our findings suggest that NPS consumers are a heterogenous group. We found that people who had used SCRA in the past year were different to those who had used other forms of NPS. In particular, it appears that people who use SCRA may be more at risk of experiencing drug-related harms (e.g. dependence), whilst other NPS consumers may be more likely to engage in drug-related risk behaviours (e.g. driving while intoxicated). However, our ability to expand upon the heterogeneity of NPS consumers is limited by the fact that the NDSHS only breaks NPS down into two categories, when in fact there are different ways of categorising NPS (e.g. chemical group, effect on the central nervous system), and multiple possible classes within these approaches (European Monitoring Centre for Drugs and Drug Addiction, 2016a, The Drugs Wheel. A new model for substance awareness, 2018), with a lack of standardisation evident in the literature. It seems likely that there are further differences among NPS consumers that we have not been able to tease out (e.g. Sutherland et al., 2016) and as such, future research should examine whether correlates of use vary across NPS classes. It is also important for future research to consider differences within NPS classes, with our findings showing that people who reported SCRA use had almost equal probabilities of falling into the amphetamine and cannabis consumer and polysubstance consumer groups. 2.7.1 Limitations and future research

This study has certain limitations. Firstly, our findings are based on data from the 2013 NDSHS, as this was the first year to collect information on the use of NPS. In the intervening years, hundreds of additional NPS have been identified (265 from 2014-2016; European Monitoring Centre for Drugs and Drug Addiction, 2015, European Monitoring Centre for Drugs and Drug Addiction, 2016a, European Monitoring Centre for Drugs and Drug Addiction, 2017a), which may have changed the nature of the NPS market (although findings from the 2016 NDSHS show that past 12 month SCRA use has decreased, rather than increased; Australian Institute of Health & Welfare, 2017). Furthermore, household surveys fail to capture certain populations (e.g. prisoners, homeless) which have been shown to have elevated rates of NPS use (Joseph et al., 2017, Ralphs et al., 2017), and as such our findings cannot be generalised to these populations.

General population surveys must be accompanied by targeted surveys in order to adequately capture NPS use among marginalised, transient and institutionalized populations. Secondly, analyses are reliant upon self-report data from participants which may be subject to bias. Although evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use (Darke, 1998), it is possible that people may have under-reported rates of use. This is compounded by the fact that definitions of NPS vary across countries and studies, and that the phrasing of questions can impact upon response options. For example, Palamar et al. (2017) found that ‘gate’ questions (which utilise skip logic, such that only a ‘yes’ response to use of a specific drug class will lead to more extensive queries of drug use in that class) resulted in lower response estimates than directly asking about specific NPS. Furthermore, the data presented here refers to intentional NPS use only, and rates of ‘unintentional’ NPS consumption are likely much higher than reported. For example, wastewater analysis in Queensland detected a high frequency of methylone use (Thai et al., 2016), which was in contrast to low rates of reported use among sentinel samples of illicit drug consumers. Where possible, future studies should corroborate their findings through chemical analysis (e.g. Salomone et al., 2017). However, it should be noted that intentional and unintentional NPS use are distinct issues that require different harm reduction messages or interventions (e.g. unintentional use would be best addressed through interventions such as drug-testing and issuing health alerts when contaminants have been identified; Brunt et al., 2017). Although our findings show that most people who use SCRA or other NPS also use other illicit substances, it is unclear from this study which came first and it would be of benefit for future studies to explicitly explore this, through longitudinal analyses, or through surveys which specifically ask about age of initiation. Finally, there was a very small group of people (n=16) who reported exclusive use of SCRA and/or other NPS, and it may be of benefit for future research to examine this group in more detail, although we acknowledge that, in the Australian context at least, such small numbers could limit the ability to do so. However, complex cultural and regulatory differences mean that there could be differing typologies of NPS consumers across countries (e.g. typologies may be markedly different in countries, such as Australia, where blanket bans have been introduced, prohibiting all NPS, compared to countries where NPS use is decriminalised and/or legal), and it would be of benefit for similar analyses to be conducted on general population data in other countries.

2.8 Conclusions

This study found no distinct profile of exclusive NPS consumers; rather the probability of SCRA and other NPS use was highest among amphetamine and cannabis consumers and polysubstance consumers. These groups reported the highest rates of drug-related harms (i.e. trouble ceasing use) and drug-related risk behaviours, respectively, suggesting that the use of SCRA or other NPS could be indicative of patterns of problematic drug use. These findings suggest that there may not need to be specialised NPS interventions or harm reduction messages; rather, they could be built into existing responses to drug use and targeted towards illicit drug consumers more generally.

2.9 Supplementary materials

Table 6: Latent Class Fit Statistics for models with 1 to 8 classes for licit and illicit drug use variables (n=3309) LMR- Percentage (n) in Each Class ALRT Model AIC ssaBIC LMR-ALRT Entropy Class Class Class Class Class Class Class p Class 1 2 3 4 5 6 7 8 value 1 Class 100 31543 31578 ------(3309) 2 Class 79 21 29601 29674 1950 <.001 0.943 - - - - (2613) (696) 3 Class 21 47 32 28069 28180 1543 <.001 0.839 - - - (690) (1562) (1057) 4 Class 22 21 8 49 27599 27748 491 .0132 0.807 - - (720) (697) (271) (1620) 5 Class 21 46 6 7 21 27421 27608 202 .2040 0.796 - (680) (1519) (193) (223) (693) 6 Class 19 7 21 46 6 27268 27493 178 .0342 0.827 2 (59) (620) (227) (687) (1527) (189) 7 class 21 45 14 6 6 27219 27482 74 .5031 0.809 6 (212) 2 (59) (691) (1496) (454) (215) (182) 8 class 11 6 21 5 47 5 3 2 27162 27464 82 .6962 0.875 (353) (199) (696) (179) (1546) (179) (101) (56) Note. AIC: Akaike Information Criterion; ssaBIC: sample-size adjusted Bayesian Information Criterion; LMR-ALRT: Lo-Mendell-Rubin Adjusted Likelihood Ratio Test.

Table 7: Demographics and risk behaviours according to group, with polysubstance consumers and amphetamine and cannabis consumers as the referent groups: Bivariate models. Polysubstance consumers vs. Amphetamine and cannabis consumers vs. Cannabis Pharmaceutical Ecstasy and Amphetamine Inhalant Cannabis Pharmaceutical Ecstasy and Polysubstance Inhalant consumers consumers cocaine and cannabis consumers consumers consumers cocaine consumer consumers Outcome AOR AOR consumers consumers AOR AOR AOR consumers AOR AOR (95% CI; p) (95% CI; p) AOR AOR (95% CI; p) (95% CI; p) (95% CI; p) AOR (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) Demographics and

Mental Health:

1.06 (1.04- 1.11 (1.10- 1.03 (1.02- 1.03 (1.02- 1.14 (1.11- 1.02 (1.01- 1.08 (1.06- 1.00 (0.99- 0.97 (0.95- 1.10 (1.07- Mean age (years) 1.07)*** 1.13)*** 1.05)*** 1.05)*** 1.17)*** 1.04)*** 1.09)*** 1.01; 0.90) 0.98)*** 1.13)***

0.68 (0.44- 0.40 (0.25- 0.72 (0.45- 0.69 (0.41- 0.69 (0.34- 0.99 (0.71- 0.58 (0.41-0.84; 1.04 (0.71- 1.45 (0.86- 1.01 (0.52-1.94; Male % 1.07; 0.09) 0.64)*** 1.15; 0.17) 1.16; 0.16) 1.43; 0.32) 1.37; 0.95) 0.004)** 1.54; 0.83) 2.44; 0.16) 0.99) Completed 0.36 (0.17- 0.55 (0.34- 0.56 (0.34-0.90; 0.93 (0.56- 0.38 (0.20- 1.46 (0.97- 1.48 (0.97-2.27; 2.47 (1.56- 2.66 (1.44- 0.96 (0.48-1.93; trade/qualification 0.75; 0.88; 0.01)* 0.02)* 1.55; 0.78) 0.69; 0.002)** 2.19; 0.07) 0.07) 3.90)*** 4.89; 0.002)** 0.90) % 0.006)** 0.65 (0.34- 0.40 (0.19-0.84; 0.47 (0.22- 1.29 (0.60- 0.74 (0.19- 0.51 (0.31- 0.31 (0.17- 0.36 (0.20- 0.78 (0.36- 0.58 (0.15-2.20; Unemployed % 1.26; 0.20) 0.02)* 0.97; 0.04)* 2.78; 0.52) 2.99; 0.68) 0.83; 0.007)** 0.57)*** 0.66)*** 1.68; 0.52) 0.42) Gross annual 1.23 (0.77- 1.08 (0.66-1.76; 0.74 (0.45- 1.96 (1.03- 0.93 (0.40- 0.62 (0.41- 0.55 (0.35-0.87; 0.38 (0.24- 0.51 (0.27- 0.47 (0.20-1.11; income <$52,000 1.95; 0.39) 0.76) 1.22; 0.23) 3.74; 0.04)* 2.18; 0.87) 0.94; 0.02)* 0.01)** 0.59)*** 0.97; 0.04)* 0.08) % 1.66 (1.07- 1.79 (1.12-2.84; 0.86 (0.55- 2.77 (1.63- 2.42 (1.15- 0.60 (0.42- 0.64 (0.43-0.96; 0.31 (0.21- 0.36 (0.21- 0.87 (0.43-1.77; Low SES % 2.57; 0.02)* 0.01)* 1.37; 0.53) 4.70)*** 5.10; 0.02)* 0.86; 0.005)** 0.03)* 0.47)*** 0.61)*** 0.71) 0.59 (0.37- 0.78 (0.49-1.24; 0.61 (0.38- 1.57 (0.90- 0.31 (0.12- 0.38 (0.25- 0.50 (0.32-0.77; 0.39 (0.25- 0.64 (0.36- 0.20 (0.08-0.52; K10 score ≥22 % 0.93; 0.02)* 0.29) 0.98; 0.04)* 2.75; 0.11) 0.84; 0.02)* 0.56)*** 0.002)** 0.61)*** 1.12; 0.11) 0.001)**

Table 7 (continued): Demographics and risk behaviours according to group, with polysubstance consumers and amphetamine and cannabis consumers as the referent groups: Multivariable models Polysubstance consumers vs. Amphetamine and cannabis consumers vs. Cannabis Pharmaceutical Ecstasy and Amphetamine Inhalant Cannabis Pharmaceutical Ecstasy and Polysubstance Inhalant consumers consumers cocaine and cannabis consumers consumers consumers cocaine consumer consumers AOR AOR consumers consumers AOR AOR AOR consumers AOR AOR (95% CI; p) (95% CI; p) AOR AOR (95% CI; p) (95% CI; p) (95% CI; p) AOR (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) Risk Behaviours: 0.14 (0.04- AUDIT-C score ≥9 0.31 (0.20- 0.12 (0.07- 0.59 (0.37-0.95; 0.67 (0.39-1.18; 0.46 (0.30- 0.18 (0.10- 0.88 (0.55-1.41; 1.49 (0.85-2.60; 0.20 (0.06-0.75; 0.50; 0.49)*** 0.22)*** 0.03)* 0.17) 0.71)*** 0.33)*** 0.60) 0.17) 0.02)* % 0.003)** Dangerous activity whilst under AOD 0.15 (0.09- 0.04 (0.02- 0.26 (0.14- 0.53 (0.27-1.05; 0.05 (0.02- 0.29 (0.19- 0.08 (0.05- 0.48 (0.32- 1.88 (0.95-3.72; 0.10 (0.05- influence past year 0.27)*** 0.08)*** 0.47)*** 0.07) 0.14)*** 0.42)*** 0.13)*** 0.74)*** 0.07) 0.23)*** % Missed work/school/TAFE/ 0.21 (0.12- 0.11 (0.06- 0.43 (0.25-0.74; 0.46 (0.23-0.91; 0.07 (0.01- 0.45 (0.24-0.83; 0.24 (0.11- 0.93 (0.50-1.71; 2.17 (1.09-4.30; 0.14 (0.02-1.15; university for AOD 0.35)*** 0.22)*** 0.003)** 0.03)* 0.52; 0.01)* 0.01)* 0.52)*** 0.80) 0.03)* 0.07) reason in past 3 months % Trouble ceasing 0.26 (0.11- 0.47 (0.30- 0.35 (0.22- 0.41 (0.25- 2.63 (1.47-4.70; 0.18 (0.12- 0.13 (0.09- 0.16 (0.10- 0.38 (0.21-0.68; 0.10 (0.04- drug use in past 0.60; 0.73)*** 0.56)*** 0.67)*** 0.001)** 0.27)*** 0.21)*** 0.25)*** 0.001)** 0.22)*** year % 0.002)** Injected any drug 0.05 (0.02- 0.07 (0.03- 0.14 (0.05- 1.64 (0.78-3.46; 0.03 (0.01- 0.04 (0.02- 0.08 (0.03- 0.61 (0.29-1.30; <0.001*** <0.001*** in past year % 0.13)*** 0.212)*** 0.40)*** 0.20) 0.07)*** 0.13)*** 0.24)*** 0.20) Note. An odds ratio (OR) or adjusted odds ratio (AOR) of 1 indicates the event is equally probable in each group, > 1 indicates the event is more likely to occur in the non-reference group relative to the reference group, and <1 indicates the event is less likely to occur in the non-reference group relative to the reference group. *p<.050; **p<.010; ***p<.001; exact p values not presented where <0.001. CI: confidence interval; AOD: alcohol and/or drugs; AUDIT-C: Alcohol Use Disorders Identification Test; K10: Kessler Psychological Distress Scale; SES: socio-economic status.

2.10 References

ANDREWS, G. & SLADE, T. 2001. Interpreting scores on the Kessler Psychological Distress Scale (K10). Australian and New Zealand Journal of Public Health, 25, 494-497. AUSTRALIAN BUREAU OF STATISTICS. 2013. Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2011 [Online]. Available: http://www.abs.gov.au/Ausstats/[email protected]/0/4E5531D7B85288A9CA2577E4000E1F9E ?OpenDocument [Accessed 2 October 2017]. AUSTRALIAN INSTITUTE OF HEALTH & WELFARE 2014. 2013 National Drug Strategy Household Survey: Detailed Findings. Drug statistics series no. 28. Cat. no. PHE 183. Canberra: Australian Institute of Health and Welfare. AUSTRALIAN INSTITUTE OF HEALTH & WELFARE 2017. National Drug Strategy Household Survey 2016. Detailed findings. Drug Statistics series no. 31. Cat. no. PHE 214. BARRATT, M. J., SEEAR, K. & LANCASTER, K. 2017. A critical examination of the definition of ‘psychoactive effect’ in Australian drug legislation. International Journal of Drug Policy, 40, 16-25. BONAR, E. E., ASHRAFIOUN, L. & ILGEN, M. A. 2014. Synthetic cannabinoid use among patients in residential substance use disorder treatment: Prevalence, motives, and correlates. Drug and Alcohol Dependence, 143, 268-271. BRADLEY, K. A., DEBENEDETTI, A. F., VOLK, R. J., WILLIAMS, E. C., FRANK, D. & KIVLAHAN, D. R. 2007. AUDIT-C as a Brief Screen for Alcohol Misuse in Primary Care. Alcoholism: Clinical and Experimental Research, 31, 1208-1217. BRUNO, R., MATTHEWS, A. J., DUNN, M., ALATI, R., MCILWRAITH, F., HICKEY, S., BURNS, L. & SINDICICH, N. 2012. Emerging psychoactive substance use among regular ecstasy users in Australia. Drug and Alcohol Dependence, 124, 19-25. BRUNT, T. M., NAGY, C., BÜCHELI, A., MARTINS, D., UGARTE, M., BEDUWE, C. & VENTURA VILAMALA, M. 2017. Drug testing in Europe: monitoring results of the Trans European Drug Information (TEDI) project. Drug Testing and Analysis, 9, 188-198. BUSH, K., KIVLAHAN, D. R., MCDONELL, M. B., FIHN, S. D. & BRADLEY, K. A. 1998. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med, 158, 1789-95. DARKE, S. 1998. Self-report among injecting drug users: A review. Drug & Alcohol Dependence, 51, 253-263. EMMANUEL, F. & ATTARAD, A. 2006. Correlates of injection use of synthetic drugs among drug users in Pakistan: a case controlled study. J Pak Med Assoc, 56, 119-24. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2015. EMCDDA - Eurpol 2014 Annual Report on the implementation of Council Decision 2005/387/JHA. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016a. EMCDDA - Eurpol 2015 Annual Report on the implementation of Council Decision 2005/387/JHA. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016b. Health responses to new psychoactive substances. Luxembourg: Publications Office of the European Union. 72

EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016c. Health responses to new psychoactive substances. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017a. EMCDDA - Eurpol 2016 Annual Report on the implementation of Council Decision 2005/387/JHA. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017b. High-risk drug use and new psychoactive substances. Results from an EMCDDA trendspotter study. . Luxembourg: Publications Office of the European Union. HARRIS, A. H., BRADLEY, K. A., BOWE, T., HENDERSON, P. & MOOS, R. 2010. Associations between AUDIT-C and mortality vary by age and sex. Popul Health Manag, 13, 263-8. HASIN, D. S., O’BRIEN, C. P., AURIACOMBE, M., BORGES, G., BUCHOLZ, K., BUDNEY, A., COMPTON, W. M., CROWLEY, T., LING, W., PETRY, N. M., SCHUCKIT, M. & GRANT, B. F. 2013. DSM-5 Criteria for Substance Use Disorders: Recommendations and Rationale. The American journal of psychiatry, 170, 834-851. HOME OFFICE 2017. Drug Misuse: Findings from the 2016/17 Crime Survey for England and Wales. Statistical Bulletin 11/17. London: Home Office. INTERGOVERNMENTAL COMMITTEE ON DRUGS 2014. Frame work for a National Response to New Psychoactive Substances. Canberra: Commonwealth of Australia. JOSEPH, A. M., MANSEAU, M. W., LALANE, M., RAJPARIA, A. & LEWIS, C. F. 2017. Characteristics associated with synthetic cannabinoid use among patients treated in a public psychiatric emergency setting. American Journal of Drug and Alcohol Abuse, 43, 117-122. KESSLER, R. C., BARKER, P. R., COLPE, L. J., EPSTEIN, J. F., GFROERER, J. C., HIRIPI, E., HOWES, M. J., NORMAND, S. L., MANDERSCHEID, R. W., WALTERS, E. E. & ZASLAVSKY, A. M. 2003. Screening for serious mental illness in the general population. Arch Gen Psychiatry, 60, 184-9. LAWN, W., BARRATT, M., WILLIAMS, M., HORNE, A. & WINSTOCK, A. 2014. The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. Journal of Psychopharmacology, 28, 780-788. LO, Y., MENDELL, N. R. & RUBIN, D. B. 2001. Testing the number of components in a normal mixture. Biometrika, 88, 767-778. MANSEAU, M. W., RAJPARIA, A., JOSEPH, A., AZARCHI, S., GOFF, D., SATODIYA, R. & LEWIS, C. F. 2017. Clinical Characteristics of Synthetic Cannabinoid Use in a Large Urban Psychiatric Emergency Setting. Substance Use and Misuse, 52, 822-825. MOORE, K., DARGAN, P. I., WOOD, D. M. & MEASHAM, F. 2013. Do Novel Psychoactive Substances Displace Established Club Drugs, Supplement Them or Act as Drugs of Initiation? The relationship between Mephedrone, Ecstasy and Cocaine. European Addiction Research, 19, 276-282. MUTHÉN, L. K. & MUTHÉN, B. O. 2010. Mplus User’s Guide. Sixth Edition., Los Angeles, CA, Muthén & Muthén. PALAMAR, J. J. 2015. “Bath salt” use among a nationally representative sample of high school seniors in the United States. The American Journal on Addictions, 24, 488-491. PALAMAR, J. J. & ACOSTA, P. 2015. Synthetic cannabinoid use in a nationally representative sample of US high school seniors. Drug and Alcohol Dependence, 149, 194-202.

PALAMAR, J. J., ACOSTA, P., CALDERON, F. F., SHERMAN, S. & CLELAND, C. M. 2017. Assessing self-reported use of new psychoactive substances: The impact of gate questions. Am J Drug Alcohol Abuse, 43, 609-617. PALAMAR, J. J., MARTINS, S. S., SU, M. K. & OMPAD, D. C. 2015. Self-Reported Use of Novel Psychoactive Substances in a US Nationally Representative Survey: Prevalence, Correlates, and a Call for New Survey Methods to Prevent Underreporting(). Drug and alcohol dependence, 156, 112-119. RÁCZ, J., CSÁK, R., TÓTH, K. T., TÓTH, E., ROZMÁN, K. & GYARMATHY, V. A. 2016. Veni, vidi, vici: The appearance and dominance of new psychoactive substances among new participants at the largest needle exchange program in Hungary between 2006 and 2014. Drug and Alcohol Dependence, 158, 154-158. RALPHS, R., WILLIAMS, L., ASKEW, R. & NORTON, A. 2017. Adding Spice to the Porridge: The development of a synthetic cannabinoid market in an English prison. International Journal of Drug Policy, 40, 57-69. RAMO, D. E., GROV, C., DELUCCHI, L., KELLY, B. C. & PARSONS, J. T. 2010. Typology of club drug use among young adults recruited using time-space sampling. Drug and Alcohol Dependence, 107, 119-127. ROY MORGAN RESEARCH 2014. National Drug Strategy Household Survey 2013. Final Technical Report. Melbourne: Roy Morgan Research. SALOMONE, A., PALAMAR, J. J., GERACE, E., DI CORCIA, D. & VINCENTI, M. 2017. Hair Testing for Drugs of Abuse and New Psychoactive Substances in a High-Risk Population. J Anal Toxicol, 41, 376-381. SUTHERLAND, R., PEACOCK, A., WHITTAKER, E., ROXBURGH, A., LENTON, S., MATTHEWS, A., BUTLER, K., NELSON, M., BURNS, L. & BRUNO, R. 2016. New psychoactive substance use among regular psychostimulant users in Australia, 2010–2015. Drug and Alcohol Dependence, 161, 110-118. TARJÁN, A., DUDÁS, M., WIESSING, L., HORVÁTH, G., RUSVAI, E., TRESÓ, B. & CSOHÁN, Á. 2017. HCV prevalence and risk behaviours among injectors of new psychoactive substances in a risk environment in Hungary—An expanding public health burden. International Journal of Drug Policy, 41, 1-7. THAI, P. K., LAI, F. Y., EDIRISINGHE, M., HALL, W., BRUNO, R., O'BRIEN, J. W., PRICHARD, J., KIRKBRIDE, K. P. & MUELLER, J. F. 2016. Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia. Science of The Total Environment, 545, 250-255. THE DRUGS WHEEL. A NEW MODEL FOR SUBSTANCE AWARENESS. 2018. Available: http://www.thedrugswheel.com/?page=home [Accessed 7 March 2018]. VREEKER, A., VAN DER BURG, B. G., VAN LAAR, M. & BRUNT, T. M. 2017. Characterizing users of new psychoactive substances using psychometric scales for risk-related behavior. Addictive Behaviors, 70, 72-78.

3. PAPER TWO: NEW PSYCHOACTIVE SUBSTANCE USE AMONG REGULAR

PSYCHOSTIMULANT USERS IN AUSTRALIA, 2010-2015

Rachel Sutherland1, Amy Peacock2, Elizabeth Whittaker1, Amanda Roxburgh1, Simon Lenton3, Allison Matthews2, Kerryn Butler1, Marina Nelson3, Lucinda Burns1, Raimondo Bruno2

1National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia

2 School of Medicine (Psychology), Faculty of Health, University of Tasmania, Hobart, TAS, 7001, Australia

3National Drug Research Institute, Curtin University, Shenton Park, WA, 6845, Australia

Paper two has been published in Drug and Alcohol Dependence (Sutherland et al., 2016)

3.1 Copyright statement

I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations.

Sutherland, R., Peacock, A., Whittaker, E., Roxburgh, A., Lenton, S., Matthews, A., Butler, K., Nelson, M., Burns, L. & Bruno, R. (2016). New psychoactive substance use among regular psychostimulant users in Australia, 2010-2015. Drug and Alcohol Dependence, 161; 110-118

Rachel Sutherland August 2018

3.2 Preamble

Paper one has shown that there is no distinct profile of exclusive NPS consumers. That is, Australian NPS consumers are not ‘new’ users per se, but rather are (primarily) existing illicit drug consumers who are using a range of substances. However, this paper is limited by the fact that the NDSHS only separates NPS into two categories: SCRA and ‘other’ NPS. This restricts our ability to explore the heterogeneity of NPS consumers and lacks detail about which specific NPS are being consumed. Thus, in order to obtain a more detailed understanding of patterns of NPS use in Australia, it is essential that this data be supplemented with data from sentinel or high- risk populations of illicit drug consumers.

There are three such surveys that routinely collect information on NPS use in Australia: The Ecstasy and related Drugs Reporting System (EDRS); the Illicit Drug Reporting System (IDRS); and the Global Drug Survey (GDS). The next series of papers use data from the EDRS. This data source was chosen for three main reasons. Firstly, the EDRS was the first project to start systematically collecting information on NPS use in Australia in 2010, and as such contains the most historical data (the GDS and IDRS started collecting information on NPS use in 2012 and 2013, respectively). Secondly, the EDRS contains an exclusive Australian sample with clear eligibility criteria (i.e. participants must have consumed ecstasy or other stimulants at least six times in the preceding six months). In contrast, the GDS contains an international sample and no eligibility criteria; thus, whilst illicit drug consumption is high amongst the GDS sample, it is not a requirement for participation. Thirdly, the EDRS contains the highest rates of NPS use and as such has the greatest statistical power to be able to address the aims of this thesis.

The first of the papers using EDRS data will examine rates of NPS use from 2010-2015, and determine which factors are associated with use of the most common NPS classes. This will build upon paper one by: (1) providing more detailed information about which NPS are being consumed (i.e. examining eight NPS classes, rather than the two NPS classes captured in the NDSHS); and (2) exploring whether there are any significant differences across consumers of the most commonly used NPS (i.e. examining phenethylamine, tryptamine, synthetic cannabinoid, synthetic cathinone, and ‘poly’ NPS consumers separately). These findings will provide a more nuanced understanding of who are most at risk for using particular types of NPS, thus improving our ability to tailor harm reduction messages to the appropriate target group.

3.3 Abstract

Objective: To examine the rates and patterns of new psychoactive substance (NPS) use amongst regular psychostimulant users (RPU) in Australia.

Method: Data were obtained from the 2010-2015 Ecstasy and related Drugs Reporting System (EDRS), which comprised a total cross-sectional sample of 4,122 RPU.

Results: Recent use of ‘any’ NPS increased from 33% in 2010 to 40% in 2015, although trends of use differed significantly across NPS classes. The correlates associated with NPS use also varied across NPS classes: frequent (i.e. weekly or more) ecstasy users were more likely to report recent phenethylamine use; LSD users were more likely to report recent phenethylamine and tryptamine use; and daily cannabis users were more likely to report recent synthetic cannabinoid use than RPU who had not used NPS. ‘Poly’ NPS consumers were found to be a particularly high risk group and were significantly more likely to be younger, male, report daily cannabis use, report weekly or more ecstasy use, report recent LSD use, have higher levels of poly drug use, have overdosed on any drug in the past year, and to have engaged in past month criminal activity.

Conclusion: NPS use has been established as a significant and ongoing practice amongst our sample of RPU. It appears that RPU seek out NPS with similar properties to the illicit drugs that they are already consuming, with poly NPS consumers found to be a particularly high risk group.

Keywords: New psychoactive substances; NPS; synthetic cannabinoids; synthetic cathinones; tryptamines; phenethylamines; psychostimulants

3.4 Introduction

Over the past decade, countries worldwide have witnessed the rapid emergence of substances collectively referred to as ‘new psychoactive substances’ (NPS). NPS are substances which often do not fall under international drug controls but which may pose a public health threat (United Nations Office on Drugs and Crime (UNODC), 2013). The European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) has identified 13 categories of NPS: aminoindanes, arylalkylamines, arylcyclohexylamines, benzodiazepines, synthetic cannabinoids, synthetic cathinones, indolalkylamines (i.e. tryptamines), opioids, phenethylamines, piperazine derivates, piperidines and pyrrolidines, plants and extracts, and others (EMCDDA, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015). In 2014, over 450 NPS were being monitored by EMCDDA, the majority of which fell into the synthetic cathinone and synthetic cannabinoid categories (EMCDDA, 2015).

The extent to which NPS are used globally remains unclear, with prevalence rates varying considerably across countries. Data from the European Union indicated that, in 2014, 3% of people aged 15-24 had used an NPS in the past year, with use highest in Ireland, Spain and France (5% respectively) (European Commission, 2014). The Crime Survey for England and Wales found that 0.6% and 0.5% of 16-59 year olds reported past year use of mephedrone and salvia respectively (Home Office, 2014); in the United States, 4.8% of adolescents (grade 8-12) reported past year use of synthetic cannabinoids in 2014 and 0.8% reported use of synthetic stimulants (Miech et al., 2014). In Australia, the 2013 National Drug Strategy Household Survey showed that 1.2% of the general population had used synthetic cannabinoids in the last 12 months, and 0.4% had used another NPS (Australian Institute of Health & Welfare (AIHW), 2014).

Whilst general population estimates appear to be relatively low, rates of NPS use are elevated amongst high risk groups, such as illicit drug users and those engaged in the night time economy (Bretteville-Jensen et al., 2013; Bonar et al., 2014; Burns et al., 2014; Kelly et al., 2013; Moore et al., 2013; Stafford & Burns, 2015; Vento et al., 2014; Winstock, 2015). For example, a study of gay dance club patrons in London found that amongst those who had used ecstasy pills in the past month, 75% had also used mephedrone (Moore et al., 2013); whilst a survey of 1,740 nightlife venue patrons in the US found that 8.2% had used synthetic cannabinoids and 1.1% had used mephedrone in the past year (Kelly et al., 2013).

Presently, there is limited literature on the socio-demographic profile of NPS consumers. Studies examining the correlates of NPS use have found that those who are younger, male, had used other drugs and had higher levels of poly drug use were more likely to have used an NPS (Bonar 79

et al., 2014; Bruno et al., 2012; Burns et al., 2014; Emmanuel & Attarad, 2006; Lawn et al., 2014; Palamar, 2015; Palamar & Acosta, 2015). More detailed studies have also identified younger age of drug initiation, more problematic drug use (e.g. bingeing) and online purchasing behaviours as being correlated with NPS use (Burns et al., 2014). Given the vast array of NPS that are available, it is likely that NPS consumers are a heterogeneous group. For example, in a recent study, stimulant NPS users were found to be similar to regular ecstasy users, while psychedelic NPS users were a distinct group of users who had initiated ecstasy use at a younger age, had higher levels of poly drug use and were more likely to experience legal, psychological and social drug-related problems (Bruno et al., 2012). Given these differences, it was argued that harm reduction messages need to be tailored according to the NPS being used.

The public health risks associated with NPS are many and varied. Synthetic cannabinoids, for example, have been associated with acute and persistent psychosis, tachycardia, agitation, hallucinations, hypertension, vomiting, chest pain, seizures and myoclonia (Every-Palmer, 2010; Hermanns-Clausen, 2012); whilst mephedrone has been shown to impair working memory (Freeman et al., 2012), and has been associated with jaw clenching, reduced appetite, insomnia, agitation, tachycardia and dependence (Dargan et al., 2010; Dargan et al., 2011; Winstock et al., 2011). In addition, data from the Global Drug Survey showed that the risk of seeking emergency medical treatment was 30 times higher amongst synthetic cannabinoid users than herbal cannabis users, whilst ‘other’ NPS users were about three times more likely to seek emergency medical treatment compared to traditional illicit drug users (Winstock, 2015).

Given the different risk profiles associated with NPS use, it is essential to obtain a more nuanced understanding of who are most at risk for using these substances. This will improve our ability to tailor harm reduction messages to the appropriate target groups. Subsequently, the aims of this paper are twofold:

1) To examine the prevalence of NPS use amongst a sample of regular psychostimulant users (RPU) in Australia, from 2010-2015.

2) To determine whether correlates of use vary across the following five NPS classes; phenethylamines, tryptamines, synthetic cannabinoids, synthetic cathinones, and ‘poly’ NPS (i.e. use of more than one NPS class).

3.5 Method

3.5.1 Study design

This paper uses six years of data (2010-2015) from the Ecstasy and related Drugs Reporting System (EDRS) (for full protocol details, see Sindicich & Burns, 2015). The EDRS is a national monitoring study aimed at detecting emerging trends in illicit drug markets and has been conducted annually in all Australian jurisdictions since 2003. The EDRS has received ethical approval from the University of New South Wales Human Research Ethics Committee (HC10071, HC15015), as well as from the relevant ethics committees in each jurisdiction.

3.5.2 Participants and procedure

EDRS participants (hereafter referred to as ‘regular psychostimulant users’ (RPU)) comprised a non-random self-selected sample recruited annually through street-press advertisements, online forums and peer referral. Eligibility criteria were; at least monthly use of ecstasy or psychostimulants in the preceding six months, 16 years of age or older, and residence in the city of interview for at least 12 months prior to the interview. Face-to-face one-hour structured interviews were conducted by trained interviewers at a negotiated time and location. All information was confidential and anonymous.

3.5.3 Measures relevant to the current study

3.5.3.1 Outcome variables

From 2010-2015, participants were asked about their past six month use of 26 specific NPS (see Table 8 for a full list, with street names provided in brackets); an open text ‘other’ option was provided to capture any additional NPS not listed in the survey. These NPS have been categorised into eight of the thirteen categories identified by the EMCDDA; namely synthetic cannabinoids, synthetic cathinones (i.e. stimulant and entactogen phenethylamines), phenethylamines (i.e. psychedelic phenethylamines), tryptamines, piperazines, plant and extracts, aminoindanes and arylcyclohexylamines.

3.5.3.2 Correlates

In addition to demographic questions (i.e. age, sex, sexual orientation, employment and educational status), participants were asked about their past six-month use of licit and illicit substances; the total number of illicit drug classes used in the past six months (excluding NPS) was used to measure levels of poly drug use (maximum of 17 drug classes). Participants completed the 5-item Severity of Dependence Scale (SDS; Gossop et al., 1995) in relation to

ecstasy use, whereby a cut-off score of ≥3 was considered indicative of ecstasy dependence (Bruno et al., 2011). Participants were also asked if they had binged on stimulants in the past six months (defined as the use of stimulants for 48 hours or more without sleep).

The Alcohol Use Disorders Identification Test (AUDIT) was administered to identify participants with potential alcohol-related problems (Saunders et al., 1993). A cut-off score of ≥16 was used to measure hazardous and harmful alcohol use (Babor & Higgins-Biddle, 2000). From its inception, the EDRS has measured crime using the Criminality Scale of the Opiate Treatment Index (OTI; Darke et al., 1991). This scale gathers self-report data on four types of crime: property crime; dealing; fraud; and violent crime (in the month preceding interview).

Across all years, participants were administered the Kessler 10 (K10) Psychological Distress Scale to assess psychological distress (Kessler et al., 2003). The K10 is a 10-item screening tool utilizing a five-point response scale (1 ‘none of the time’ to 5 ‘all of the time’); a cut-off score of ≥22 (score range 10-50) was used to measure high to very high psychological distress (Andrews & Slade, 2001). Participants also answered self-report questions about their mental health over the previous six-month period.

Participants were asked if they had participated in the EDRS previously; this question was used to exclude repeat participants.

3.5.4 Statistical analysis

3.5.4.1 Rates of NPS use

Rates of use were generated by collapsing the various NPS to determine if participants had consumed ‘any’ NPS in the six months preceding interview. Using the groupings identified by the EMCDDA, rates of use were then broken down into the following classes; synthetic cannabinoids, synthetic cathinones, phenethylamines, tryptamines, piperazines, plants and extracts, aminoindanes and arylcyclohexylamines. Paired comparisons of percentages reporting use were made across adjacent years (e.g. 2010-2011; 2011-2012) with 95% confidence intervals (95% CI) reported.

3.5.4.2 Correlates of NPS use

Socio-demographic profiles were compared across the four most commonly used NPS classes (i.e. synthetic cathinones, synthetic cannabinoids, phenethylamines and tryptamines). The sample was divided into groups based on use of these substances in the six months preceding interview and compared to non NPS using participants (e.g. recent cathinone use only vs. no recent NPS use). In order to maintain distinct groups of NPS users (see Supplementary Material, 82

Table 15 for overlap between NPS classes), participants who had used more than one NPS class were excluded from this analysis and included in the ‘poly’ NPS use group. As synthetic cannabinoids were first specifically asked about in 2011, this analysis was limited to 2011-2015 data (with all repeat participants excluded from 2012-2015 data).

Between-group comparisons of categorical variables were analysed using odds ratios (OR) with 95% confidence intervals reported. For normally distributed continuous variables, t-tests were employed with means and standard deviations (SDs) reported. The Benjamini-Hochberg procedure was applied to control the false discovery rate and was used because it yields much greater power than the widely applied Bonferroni technique (Thissen et al., 2002).

Variables found to be significant based on bivariate comparisons were entered into a multivariable logistic regression model, which estimated adjusted odds ratios (AOR) after controlling for potential confounders. To allow comparability across the five NPS categories, the same variables were entered into each of the regression models (this allows us to determine if the same variables are associated with different NPS classes and if they differ in magnitude). Associations were set for statistical significance at p < 0.05. All analyses were conducted using IBM SPSS Statistics for Windows release 22.0 (IBM Corporation, 2013).

3.6 Results

3.6.1 Demographics

Across 2010-2015, 4,122 participants were recruited and interviewed for the EDRS, of which 529 were repeat participants (see Supplementary Material, Table 14). Sixty-four percent of the entire RPU cohort were male with a mean age of 23.6 years (SD 6.2; range 16-64), 97% were of English speaking background, 47% were tertiary qualified, 69% were employed in some capacity, 32% were students, 16% were unemployed and 3% were currently in drug treatment. Twelve percent of the 2010-2015 cohort identified as gay, lesbian, bisexual or transgendered (GLBT). More detailed demographics of each year’s sample have been reported elsewhere (Sindicich & Burns, 2011, 2012, 2013, 2014, 2015).

3.6.2 Rates of recent NPS use

From 2010-2015, 41.9% of the entire sample (n=1,655) reported use of ‘any’ NPS in the six months preceding interview. Specifically, one-third (32.9%) of RPU reported recent use of any NPS in 2010; this increased to 41.7% in 2011 (p=0.002), before reaching a peak of 51.6% in 2012 (p=0.002). Recent NPS use remained stable in 2013 (46.6%), before declining significantly in 2014 (40.6%; p=0.023) and then stabilising in 2015 (40.2%) (Table 8) 83

Table 8: Rates# of NPS amongst RPU, 2010-2015 2010 2011 % 2012 % 2013 % 2014 % 2015 % 2010-2015* % % (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) 95% CI; p value SYNTHETIC CATHINONES 18.5 17.7 11.4 9.2 8.0 7.7 11.6 Mephedrone (miaow, 4MMC); Methylone (bk-MDMA); (-0.04, 0.05; (0.02, 0.11; (-0.01, 0.06; (-0.02, 0.04; (-0.02, 0.03; 0.07, 0.14; MDPV (Ivory Wave); Other substituted cathinone p=0.796) p=0.004) p=0.229) p=0.466) p=0.919) p<0.001 PHENETHYLAMINES 8.0 15.6 14.6 20.7 21.3 18.6 16.9 2C-I; 2C-B (Bromo, TWOs, trystacy); 2C-E (-0.11, -0.04; (-0.03, 0.05; (-0.10, -0.02; (-0.05, 0.04; (-0.01, 0.07; -0.14, -0.07; (hummingbird, europa); 2C-Other; Benzo Fury (6-APB); p<0.001) p=0.706) p=0.008) p=0.846) p=0.210) p<0.001 PMA; DOI (death on impact); NBOMe (25I, 25B, 25C) TRYPTAMINES 7.5 14.1 14.2 14.6 14.4 10.9 12.6 DMT; 5-Meo-DMT (-0.10, -0.03; (-0.04, 0.04; (-0.04, 0.04; (-0.03, 0.04; (0.002, 0.07; -0.07, -0.003; p<0.001) p=0.960) p=0.911) p=0.962) p=0.045) p=0.037 SYNTHETIC CANNABINOIDS - 6.6 16.1 16.1 6.9 6.4 10.1 K2/Spice; Kronic; Other synthetic cannabinoid (-0.13, -0.06; (-0.04, 0.04; (0.06, 0.13; (-0.02, 0.03; -0.03, 0.03; p<0.001) p=0.960) p<0.001) p=0.797) p=0.994 PIPERAZINES 4.9 1.7 1.2 0.3 0.3 0 1.3 BZP (0.01, 0.05; (-0.01, 0.02; (0.001, 0.02; (-0.01, 0.01; (-0.003, 0.01; 0.03, 0.07; p=0.005) p=0.690) p=0.106) p=0.729) p=0.500) p<0.001 PLANTS & EXTRACTS 2.0 7.2 7.7 6.4 4.4 5.0 5.3 LSA (Hawaiian Baby); Mescaline; Salvia Divinorum; (-0.08, -0.03; (-0.04, 0.03; (-0.02, 0.04; (-0.003, 0.05; (-0.03, 0.02; -0.05, -0.01; Datura (Angel’s trumpet); Ayahuasca p<0.001) p=0.840) p=0.455) p=0.102) p=0.655) p=0.005 AMINOINDANES - - 0.9 0.7 0.5 0.4 0.6 MDAI; 5-IAI (-0.01, 0.01; (-0.01, 0.01; (-0.01, 0.01; -0.004, 0.02; p=0.977) p=0.815) p=0.950) p=0.441 ARYLCYCLOHEXYLAMINES - - 1.4 2.2 1.6 2.2 1.9 Methoxetamine (MXE) (-0.02, 0.01; (-0.01, 0.02; (-0.02, 0.01; -0.02, 0.01; p=0.408) p=0.544) p=0.494) p=0.369 ANY NPS % 32.9 41.7 51.6 46.6 40.6 40.2 41.9 (-0.14, -0.03; (-0.16, -0.04; (-0.01, 0.11; (0.01, 0.11; (-0.04, 0.05; -0.12, -0.02; p=0.002) p=0.002) p=0.092) p=0.023) p=0.915) p=0.006 #in the past six months; *for synthetic cannabinoids this refers to 2011-2015 figures; for aminoindanes and arylcyclohexylamines this refers to 2012-2015 figures; Pairwise comparisons were made across adjacent years; i.e. 2010 vs 2011; 2011 vs 2012; 2012 vs 2013; 2013 vs 2014; 2014 vs 2015; 95% CI refers to the differences across adjacent years, except for the final column where they refer to differences in 2010 vs 2015 percentages; = a significant increase in 2010 vs 2015 figures; = a significant decrease in 2010 vs 2015 figures. − no change in 2010 vs 2015 figures. Significant findings have been bolded.

Looking at the different classes of NPS (see Table 8), cathinones were originally the most prevalent NPS being used by participants, with almost one-fifth (18.5%) of RPU reporting recent (i.e. past six month) use in 2010. However, by 2015 this had declined significantly, with 7.7% reporting use of cathinones in the six months preceding interview (p<0.001). Conversely, in 2010 both phenethylamines and tryptamines had been used by 8% of RPU in the six months preceding interview; however, by 2015 rates of use had increased to 18.6% (p<0.001) and 10.9% (p=0.037) respectively, making them the two most commonly used groups of NPS in these years.

The use of synthetic cannabinoids was specifically asked about for the first time in 2011, with 6.6% of RPU reporting use within the six months preceding interview. This increased significantly in 2012 to 16.1% of the sample (p<0.001) and remained stable in 2013 (16.1%). However, in 2014 use of recent synthetic cannabinoids declined to rates observed in 2011 (6.9%; p<0.001), before stabilising in 2015 (6.4%).

The use of piperazines, plant-based NPS and aminoindanes remained uncommon across all years. Specifically, from 2010-2015, the use of piperazines declined from 4.9% to 0% (p<0.001); plant-based NPS increased from 2.0% to 5.0% (p=0.005); and there was no change in the use of aminoindanes or arylcyclohexylamines.

These trends remained consistent even when repeat participants were excluded (see Supplementary Material, Table 16).

3.6.3 Correlates of NPS use

3.6.3.1 Phenethylamines

At the bivariate level, RPU who reported recent phenethylamine use were more likely to be under the age of 25 (OR 3.41, p<0.001), male (OR 1.67, p=0.001), report weekly or more ecstasy use (OR 1.86, p<0.001), report recent (i.e., past six month) LSD use (OR 3.06, p<0.001), and report recent use of a greater number of drug classes (p<0.001), when compared to RPU who had not used any NPS in the preceding six months.

When significant bivariate correlates were entered into a multivariable logistic regression model (controlling for year), age, sex, weekly or more ecstasy use, recent LSD use and greater levels of poly drug use remained significant (see Table 9).

Table 9: Correlates of recent phenethylamine use amongst RPU, 2011-2015 Phenethylamine use past six months Multivariable No NPS use Yes OR (95%CI) p value AORb 95% CI p-value (n=1,693) (n=251) /test statistica Demographics Age (<25) % 69.2 88.4 3.41 (2.28, 5.08) <0.001* 2.66 1.71, 4.14 <0.001 Sex (male) % 60.3 71.7 1.67 (1.25, 2.23) 0.001* 1.59 1.15, 2.21 0.005 Age first tried ecstasy (<18) 46.4 54.4 1.38 (1.06, 1.80) 0.018 1.03 0.75, 1.40 0.874 Tertiary qualifications % 47.9 39.9 0.72 (0.55, 0.95) 0.019 GLBT % 11.0 9.6 0.85 (0.54, 1.33) 0.481 Unemployed % 15.3 13.1 0.84 (0.57, 1.24) 0.373 0.86 0.54, 1.36 0.513 Drug Use Daily tobacco use# % 38.6 40.0 1.06 (0.81, 1.39) 0.673 1.02 0.73, 1.42 0.910 Daily cannabis use# % 13.5 16.5 1.27 (0.88, 1.82) 0.202 1.16 0.72, 1.72 0.623 Ecstasy use# (≥weekly) % 23.0 35.7 1.86 (1.39, 2.47) <0.001* 1.69 1.21, 2.36 0.002 Methamphetamine use# % 44.8 41.0 0.86 (0.65, 1.12) 0.259 0.78 0.55, 1.09 0.146 LSD use# % 29.5 56.2 3.06 (2.34, 4.01) <0.001* 1.58 1.12, 2.23 0.009 Cocaine use# % 41.3 44.2 1.13 (0.86, 1.47) 0.379 0.71 0.51, 0.99 0.045 AUDIT score ≥16 % 38.4 32.1 0.76 (0.57, 1.01) 0.055 Binged on stimulant drug# % 32.9 34.8 1.09 (0.83, 1.44) 0.543 0.98 0.70, 1.37 0.901 Ecstasy SDS score (≥3)# % 20.0 22.8 1.18 (0.83, 1.68) 0.347 #^ Number of drug classes (mean; SD) 4.3 (1.97) 5.5 (2.11) t318=-8.67 <0.001* 1.29 1.18, 1.42 <0.001 Overdose (past year) % 35.2 40.8 1.27 (0.97, 1.67) 0.084 1.18 0.87, 1.60 0.293 Other Any crime (past month) % 30.4 42.5 1.69 (1.29, 2.22) <0.001* 1.24 0.90, 1.69 0.191 K10 score ≥22 % 27.4 24.9 0.88 (0.65, 1.19) 0.401 0.70 0.47, 1.02 0.065 Self-reported mental health problem# % 28.7 31.9 1.16 (0.87, 1.55) 0.302 1.38 0.96, 1.96 0.079 Note: OR = odds ratio; CI=confidence interval; AOR=adjusted odds ratio; SDS=severity of dependence scale; GLBT=gay, lesbian, bisexual or transgendered. *denotes significance using the Benjamini-Hochberg procedure; #in the six months preceding interview; ^Maximum of 17 drug classes (includes ecstasy, methamphetamine, illicit pharmaceutical stimulants, cocaine, LSD, MDA, ketamine, GHB, amyl nitrite, nitrous oxide, cannabis, heroin, other opioids, illicit antidepressants, illicit benzodiazepines, magic mushrooms, steroids). a Bivariate analysis were conducted, with odds ratios (OR) presented here for categorical outcomes; independent samples t-tests were conducted for parametric continuous data. b Multivariable analyses were conducted using significant variables from all five bivariate models: i.e. significant variables from the phenethylamine bivariate comparisons (age, sex, weekly or more ecstasy use, LSD use, poly drug use and past month criminal activity), and significant variables from the tryptamine, synthetic cannabinoid and poly NPS bivariate comparisons ( age of ecstasy initiation, methamphetamine use, daily tobacco use, daily cannabis use, cocaine use, binged on a stimulant drug, employment status, overdose, K10 score and mental health problem). Year was also included in the model to control for changes over time.

3.6.3.2 Tryptamines

At the bivariate level, RPU who reported recent tryptamine use were more likely to report being male (OR 1.72, p=0.008), weekly or more ecstasy use (OR 1.89, p<0.001), recent LSD use (OR 4.14, p<0.001), daily cannabis use (OR 2.89, p<0.001), having binged on a stimulant drug (OR 1.71, p=0.004), use of a greater number of drug classes (5.9 vs. 4.3, p<0.001), and past month criminal activity (OR 2.11, p<0.001), when compared to RPU who had not used any NPS in the preceding six months.

When the variables significant at the bivariate level were entered into a multivariable logistic regression model, controlling for year, the following variables remained significant; daily cannabis use, recent LSD use and greater levels of poly drug use (see Table 10).

Table 10: Correlates of recent tryptamine use amongst RPU, 2011-2015 Tryptamine use past six months Multivariable No NPS use Yes OR (95%CI) p value AORb 95% CI p-value (n=1,693) (n=123) /test statistica Demographics Age (<25) % 69.2 65.0 0.83 (0.56, 1.22) 0.335 0.80 0.51, 1.26 0.338 Sex (male) % 60.3 72.4 1.72 (1.15, 2.59) 0.008* 1.53 0.97, 2.39 0.065 Age first tried ecstasy (<18) 46.4 56.9 1.53 (1.06, 2.21) 0.024 1.10 0.73, 1.67 0.646 Tertiary qualifications % 47.9 50.4 1.11 (0.77, 1.60) 0.591 GLBT % 11.0 8.1 0.71 (0.37, 1.39) 0.315 Unemployed % 15.3 19.5 1.34 (0.84, 2.14) 0.213 0.99 0.57, 1.72 0.976 Drug Use Daily tobacco use# % 38.6 45.5 1.33 (0.92, 1.92) 0.129 0.94 0.60, 1.47 0.790 Daily cannabis use# % 13.5 31.1 2.89 (1.92, 4.35) <0.001* 2.25 1.38, 3.67 0.001 Ecstasy use# (≥weekly) % 23.0 36.1 1.89 (1.28, 2.78) 0.001* 1.24 0.79, 1.95 0.352 Methamphetamine use# % 44.8 50.4 1.25 (0.87, 1.80) 0.230 0.77 0.49, 1.21 0.255 LSD use# % 29.5 63.4 4.14 (2.83, 6.06) <0.001* 2.18 1.37, 3.46 0.001 Cocaine use# % 41.3 47.2 1.27 (0.88, 1.83) 0.203 0.82 0.53, 1.29 0.398 AUDIT score ≥16 % 38.4 30.3 0.70 (0.47, 1.04) 0.074 Binged on stimulant drug# % 32.9 45.5 1.71 (1.18, 2.47) 0.004* 1.23 0.80, 1.91 0.348 Ecstasy SDS score (≥3)# % 20.0 11.5 0.52 (0.27, 0.98) 0.041 #^ Number of drug classes (mean; SD) 4.3 (1.97) 5.9 (1.85) t1800=-8.74 <0.001* 1.31 1.16, 1.48 <0.001 Overdose (past year) % 35.2 44.7 1.49 (1.03, 2.16) 0.033 1.34 0.89, 2.01 0.160 Other Any crime (past month) % 30.4 48.0 2.11 (1.46, 3.05) <0.001* 1.51 0.99, 2.30 0.059 K10 score ≥22 % 27.4 30.0 1.13 (0.76, 1.70) 0.544 0.73 0.44, 1.20 0.212 Self-reported mental health problem# % 28.7 35.2 1.35 (0.92, 1.99) 0.124 1.38 0.86, 2.20 0.183 Note: OR = odds ratio; CI=confidence interval; AOR=adjusted odds ratio; SDS=severity of dependence scale; GLBT=gay, lesbian, bisexual or transgendered. *denotes significance using the Benjamini-Hochberg procedure; #in the six months preceding interview; ^Maximum of 17 drug classes (includes ecstasy, methamphetamine, illicit pharmaceutical stimulants, cocaine, LSD, MDA, ketamine, GHB, amyl nitrite, nitrous oxide, cannabis, heroin, other opioids, illicit antidepressants, illicit benzodiazepines, magic mushrooms, steroids). a Bivariate analysis were conducted, with odds ratios (OR) presented here for categorical outcomes; independent samples t-tests were conducted for parametric continuous data. b Multivariable analyses were conducted using the significant variables from all five bivariate models; i.e. significant variables from the tryptamine bivariate comparisons (sex, daily cannabis use, weekly or more ecstasy use, LSD use, binged on a stimulant drug, poly drug use and past month criminal activity), and significant variables from the phenethylamine, synthetic cannabinoid and poly NPS bivariate comparisons (age, age of ecstasy initiation, methamphetamine use, daily tobacco use, cocaine use, employment status, overdose, K10 score and mental health problem). Year was also included in the model to control for changes over time.

3.6.3.3 Synthetic cannabinoids

At the bivariate level, RPU who reported recent use of synthetic cannabinoids were more likely to report daily tobacco use (OR 1.76, p=0.001), daily cannabis use (OR 2.74, p<0.001), and past month criminal activity (OR 2.10, p<0.001), when compared to RPU who had not used any NPS in the preceding six months. Conversely, recent cocaine users were less likely to report recent use of synthetic cannabinoids (OR 0.46, p=0.001).

When the variables significant at the bivariate level were entered into a multivariable logistic regression model, controlling for year, the following variables were significant; daily cannabis use, recent cocaine use, past month criminal activity and greater levels of poly drug use (see Table 11).

Table 11: Correlates of recent synthetic cannabinoid use amongst RPU, 2011-2015 Synthetic cannabinoid use past six months Multivariable No NPS use Yes OR (95%CI) p value AORb 95% CI p-value (n=1,693) (n=141) /test statistica Demographics Age (<25) % 69.2 75.2 1.35 (0.91, 2.00) 0.138 1.45 0.92, 2.27 0.108 Sex (male) % 60.3 67.4 1.36 (0.94, 1.96) 0.098 1.37 0.93, 2.03 0.115 Age first tried ecstasy (<18) 46.4 56.7 1.52 (1.07, 2.14) 0.018 1.19 0.81, 1.74 0.382 Tertiary qualifications % 47.9 44.0 0.85 (0.60, 1.21) 0.371 GLBT % 11.0 12.8 1.18 (0.70, 1.98) 0.533 Unemployed % 15.3 17.7 1.19 (0.76, 1.88) 0.443 0.90 0.55, 1.49 0.682 Drug Use Daily tobacco use# % 38.6 52.5 1.76 (1.24, 2.48) 0.001* 1.30 0.87, 1.93 0.199 Daily cannabis use# % 13.5 30.0 2.74 (1.86, 4.04) <0.001* 2.13 1.37, 3.32 0.001 Ecstasy use# (≥weekly) % 23.0 23.6 1.03 (0.69, 1.55) 0.878 0.76 0.49, 1.18 0.216 Methamphetamine use# % 44.8 53.2 1.40 (0.99, 1.97) 0.055 0.95 0.63, 1.43 0.813 LSD use# % 29.5 33.3 1.19 (0.83, 1.72) 0.340 0.80 0.52, 1.25 0.330 Cocaine use# % 41.3 28.4 0.56 (0.39, 0.82) 0.003* 0.46 0.30, 0.72 0.001 AUDIT score ≥16 % 38.4 45.7 1.35 (0.95, 1.91) 0.090 Binged on stimulant drug# % 32.9 42.6 1.51 (1.07, 2.15) 0.019 1.19 0.80, 1.77 0.395 Ecstasy SDS score (≥3)# % 20.0 20.5 1.03 (0.66, 1.61) 0.898 #^ Number of drug classes (mean; SD) 4.3 (1.97) 4.70 (1.93) t1820=-2.47 0.014 1.16 1.03, 1.30 0.015 Overdose (past year) % 35.2 38.3 1.14 (0.80, 1.63) 0.456 1.16 0.76, 1.63 0.575 Other Any crime (past month) % 30.4 47.9 2.10 (1.48, 2.98) <0.001* 1.50 1.02, 2.22 0.040 K10 score ≥22 % 27.4 32.9 1.29 (0.90, 1.87) 0.169 0.88 0.56, 1.36 0.554 Self-reported mental health problem# % 28.7 36.9 1.45 (1.02, 2.08) 0.040 1.37 0.90, 2.09 0.139 Note: OR = odds ratio; CI=confidence interval; AOR=adjusted odds ratio; SDS=severity of dependence scale; GLBT=gay, lesbian, bisexual or transgendered. *denotes significance using the Benjamini-Hochberg procedure; #in the six months preceding interview; ^Maximum of 17 drug classes (includes ecstasy, methamphetamine, illicit pharmaceutical stimulants, cocaine, LSD, MDA, ketamine, GHB, amyl nitrite, nitrous oxide, cannabis, heroin, other opioids, illicit antidepressants, illicit benzodiazepines, magic mushrooms, steroids). a Bivariate analysis were conducted, with odds ratios (OR) presented here for categorical outcomes; independent samples t-tests were conducted for parametric continuous data. b Multivariable analyses were conducted using significant variables from all five bivariate models: i.e. significant variables from the synthetic cannabinoid bivariate comparisons (daily tobacco use, daily cannabis use, cocaine use and past month criminal activity), and significant variables from the phenethylamine and tryptamine bivariate comparisons (age, sex, age of ecstasy initiation, weekly or more ecstasy use, LSD use, methamphetamine use, employment status, binged on a stimulant drug, overdose, poly drug use, K10 score and mental health problem). Year was also included in the model to control for changes over time.

3.6.3.4 Synthetic cathinones

No variables were significantly correlated with recent synthetic cathinone use at the bivariate level. When a multivariable logistic regression was conducted (controlling for year), daily tobacco use and greater levels of poly drug use were found to be significantly associated with recent synthetic cathinone use. Cocaine use was also associated with recent synthetic cathinone use, although this did not reach statistical significance (see Table 12).

3.6.3.5 Poly NPS use

At the bivariate level, RPU who reported poly-NPS use in the past six months were more likely to be under the age of 25 (OR 1.77, p<0.001), male (OR 2.23, p<0.001), have initiated ecstasy use before 18 years of age (OR 2.08, p<0.001), be unemployed (OR 1.48, p=0.005), report daily tobacco (OR 1.84, p<0.001) and cannabis (OR 2.89, p<0.001) use, report weekly or more ecstasy use (OR 2.34, p<0.001), report recent methamphetamine (OR 2.20, p<0.001) and LSD (OR 6.36, p<0.001) use, have binged on a stimulant drug (OR 2.56, p<0.001), have used a greater number of drug classes (p<0.001), have overdosed on a drug in the past year (OR 1.85, p<0.001), have engaged in past month criminal activity (OR 2.68, p<0.001), have high levels of psychological distress (OR 1.45, p=0.002), and to self-report a mental health problem (OR 1.36, p=0.008), when compared to RPU who had not used any NPS in the preceding six months.

When the variables significant at the bivariate level were entered into a multivariable logistic regression model, controlling for year, the following variables remained significant; age, sex, daily cannabis use, weekly or more ecstasy use, recent LSD use, recent cocaine use, greater levels of poly drug use, past year drug overdose and past month criminal activity (see Table 13).

Table 12: Correlates of recent synthetic cathinone use amongst RPU, 2011-2015 Synthetic cathinone use past six months Multivariable No NPS use Yes OR (95%CI) p value AORb 95% CI p-value (n=1,693) (n=94) /test statistica Demographics Age (<25) % 69.2 64.9 0.82 (0.53, 1.27) 0.379 0.79 0.48, 1.30 0.352 Sex (male) % 60.3 60.6 1.01 (0.66, 1.55) 0.949 1.10 0.69, 1.76 0.680 Age first tried ecstasy (<18) 46.4 50.0 1.16 (0.76, 1.75) 0.495 1.00 0.63, 1.59 0.998 Tertiary qualifications % 47.9 58.1 1.51 (0.99, 2.30) 0.056 GLBT % 11.0 9.6 0.85 (0.42, 1.72) 0.657 Unemployed % 15.3 9.6 0.59 (0.29, 1.18) 0.130 0.58 0.28, 1.22 0.152 Drug Use Daily tobacco use# % 38.6 46.7 1.40 (0.92, 2.13) 0.120 1.65 1.03, 2.66 0.038 Daily cannabis use# % 13.5 16.0 1.21 (0.69, 2.14) 0.505 0.91 0.46, 1.78 0.782 Ecstasy use# (≥weekly) % 23.0 18.7 0.77 (0.45, 1.32) 0.338 0.71 0.40, 1.26 0.246 Methamphetamine use# % 44.8 51.1 1.28 (0.85, 1.95) 0.237 0.96 0.58, 1.58 0.858 LSD use# % 29.5 30.1 1.03 (0.65, 1.62) 0.902 0.78 0.44, 1.36 0.376 Cocaine use# % 41.3 53.2 1.62 (1.07, 2.45) 0.023 1.36 0.82, 2.24 0.230 AUDIT score ≥16 % 38.4 42.6 1.19 (0.78, 1.81) 0.426 Binged on stimulant drug# % 32.9 36.2 1.16 (0.75, 1.79) 0.441 1.02 0.62, 1.68 0.933 Ecstasy SDS score (≥3)# % 20.0 26.6 1.45 (0.87, 2.42) 0.157 #^ Number of drug classes (mean; SD) 4.3 (1.97) 4.88 (1.78) t1771=-2.87 0.004 1.16 1.01, 1.34 0.037 Overdose (past year) % 35.2 33.0 0.91 (0.58, 1.41) 0.664 0.82 0.51, 1.31 0.397 Other Any crime (past month) % 30.4 38.3 1.42 (0.93, 2.18) 0.107 1.30 0.80, 2.12 0.287 K10 score ≥22 % 27.4 29.0 1.08 (0.68, 1.72) 0.737 1.03 0.60, 1.76 0.927 Self-reported mental health problem# % 28.7 34.0 1.28 (0.83, 1.99) 0.266 1.23 0.74, 2.06 0.423 Note: OR = odds ratio; CI=confidence interval; AOR=adjusted odds ratio; SDS=severity of dependence scale; GLBT=gay, lesbian, bisexual or transgendered. *denotes significance using the Benjamini-Hochberg procedure; #in the six months preceding interview; ^Maximum of 17 drug classes (includes ecstasy, methamphetamine, illicit pharmaceutical stimulants, cocaine, LSD, MDA, ketamine, GHB, amyl nitrite, nitrous oxide, cannabis, heroin, other opioids, illicit antidepressants, illicit benzodiazepines, magic mushrooms, steroids). a Bivariate analysis were conducted, with odds ratios (OR) presented here for categorical outcomes; independent samples t-tests were conducted for parametric continuous data. b Multivariable analyses were conducted using significant variables from all five bivariate models: i.e. significant variables from the phenethylamine, tryptamine, synthetic cannabinoid and poly NPS bivariate comparisons (age, sex, age of ecstasy initiation, weekly or more ecstasy use, LSD use, daily tobacco use, daily cannabis use, cocaine use, methamphetamine use, employment status, binged on a stimulant drug, overdose, poly drug use, past month criminal activity, K10 score and mental health problem). Year was also included in the model to control for changes over time.

Table 13: Correlates of recent poly NPS use amongst RPU, 2011-2015 Poly NPS use past six months Multivariable No NPS use Yes OR (95%CI) p value AORb 95% CI p-value (n=1,693) (n=399) /test statistica Demographics Age (<25) % 69.2 79.9 1.77 (1.36, 2.32) <0.001* 1.54 1.10, 2.16 0.011 Sex (male) % 60.3 77.2 2.23 (1.73, 2.87) <0.001* 1.85 1.36, 2.52 <0.001 Age first tried ecstasy (<18) 46.4 64.3 2.08 (1.66, 2.61) <0.001* 1.28 0.96, 1.71 0.095 Tertiary qualifications % 47.9 43.1 0.83 (0.66, 1.03) 0.090 GLBT % 11.0 11.1 1.00 (0.71, 1.42) 0.996 Unemployed % 15.3 21.1 1.48 (1.12, 1.94) 0.005* 0.97 0.67, 1.39 0.858 Drug Use Daily tobacco use# % 38.6 53.7 1.84 (1.48, 2.30) <0.001* 1.15 0.86, 1.56 0.345 Daily cannabis use# % 13.5 31.2 2.89 (2.24, 3.73) <0.001* 1.67 1.19, 2.36 0.003 Ecstasy use# (≥weekly) % 23.0 41.2 2.34 (1.86, 2.95) <0.001* 1.44 1.07, 1.95 0.017 Methamphetamine use# % 44.8 64.2 2.20 (1.76, 2.76) <0.001* 0.81 0.59, 1.10 0.180 LSD use# % 29.5 72.7 6.36 (4.98, 8.11) <0.001* 2.18 1.60, 2.97 <0.001 Cocaine use# % 41.3 44.6 1.15 (0.92, 1.43) 0.226 0.47 0.34, 0.65 <0.001 AUDIT score ≥16 % 38.4 34.8 0.85 (0.68, 1.07) 0.173 Binged on stimulant drug# % 32.9 55.6 2.56 (2.05, 3.20) <0.001* 1.28 0.95, 1.72 0.108 Ecstasy SDS score (≥3)# % 20.0 23.4 1.22 (0.93, 1.62) 0.158 #^ Number of drug classes (mean; SD) 4.3 (1.97) 6.88 (2.40) t526=-19.99 <0.001* 1.56 1.44, 1.69 <0.001 Overdose (past year) % 35.2 50.1 1.85 (1.49, 2.31) <0.001* 1.56 1.19, 2.06 0.001 Other Any crime (past month) % 30.4 53.9 2.68 (2.14, 3.36) <0.001* 1.43 1.08, 1.90 0.013 K10 score ≥22 % 27.4 35.5 1.45 (1.15, 1.84) 0.002* 0.83 0.60, 1.16 0.270 Self-reported mental health problem# % 28.7 35.4 1.36 (1.08, 1.71) 0.008* 1.20 0.87, 1.66 0.261 Note: OR = odds ratio; CI=confidence interval; AOR=adjusted odds ratio; SDS=severity of dependence scale; GLBT=gay, lesbian, bisexual or transgendered. *denotes significance using the Benjamini-Hochberg procedure; #in the six months preceding interview; ^Maximum of 17 drug classes (includes ecstasy, methamphetamine, illicit pharmaceutical stimulants, cocaine, LSD, MDA, ketamine, GHB, amyl nitrite, nitrous oxide, cannabis, heroin, other opioids, illicit antidepressants, illicit benzodiazepines, magic mushrooms, steroids). a Bivariate analysis were conducted, with odds ratios (OR) presented here for categorical outcomes; independent samples t-tests were conducted for parametric continuous data. b Multivariable analyses were conducted using significant variables from all five bivariate models: i.e. significant variables from the poly NPS bivariate comparisons (age, sex, age of ecstasy initiation, weekly or more ecstasy use, LSD use, daily tobacco use, daily cannabis use, methamphetamine use, employment status, binged on a stimulant drug, overdose, poly drug use, past month criminal activity, K10 score and mental health problem), and significant variables from the phenethylamine, tryptamine and synthetic cannabinoids bivariate comparisons (cocaine use). Year was also included in the model to control for changes over time. 93

3.7 Discussion

Despite fluctuations in use of specific forms over the past six years, the use of NPS has been established as a significant and ongoing practice amongst cross-sectional samples of RPU in Australia. Whilst it is difficult to make any direct comparisons to other studies (particularly given differences in time frames, samples and categorisations of NPS), it does appear that the changes noted in our sample mirror a number of international trends (European Commission, 2014; Home Office, 2014; Miech et al., 2014). Indeed, the globalisation of drug marketplaces has increased the accessibility and volatility of drugs such as NPS (Griffiths et al., 2010), and it is essential that projects such as the EDRS continue to monitor these substances so that changing trends can be detected in a timely manner.

It is unknown what might be driving the specific trends observed in this paper; however, consumer acceptability and legislative changes are factors to consider. In 2013, EDRS participants were asked to rate the positive, negative and hangover effects of NPS, and how likely they would be to consume the substance again. DMT and 2CB received the highest ratings for pleasurability and likelihood to take again, whilst mephedrone and synthetic cannabinoids were viewed less favourably and reportedly had worse side effects (Matthews et al., 2013; Sindicich & Burns, 2014). Similarly, a self-selecting online sample of DMT and NBOMe users found that when compared to other hallucinogens (i.e. LSD, magic mushrooms and ketamine) both DMT and NBOMe were rated favourably in terms of strength of effect and pleasurability (Lawn et al., 2014; Winstock et al., 2013). In contrast, a global study of dual ‘natural’ and synthetic cannabis users found that 93% of participants preferred natural cannabis over synthetic cannabis (Winstock & Barratt, 2013). It seems likely that our sample of RPU experimented with a range of NPS, continuing to use those deemed ‘acceptable’ in terms of their psychopharmacological and side effects, and ceasing use of those that were not. This theory is supported by findings that DMT, 2C-x and NBOMe remain the most commonly sold NPS on dark net marketplaces (Van Buskirk et al., 2015), however, it would be of benefit for future research to explicitly test this hypothesis through a close examination of the motivations for consuming specific NPS.

the same pharmacological effect as cannabis (Bright et al., 2013). In 2014 there was a significant decline in the use of synthetic cannabinoids amongst our sample of RPU; however, it is unclear if this was a lagged effect of the legislation (due to practices such as stockpiling) or if it was due to other, unrelated factors such as consumer acceptability. Given that this is a sample of illicit drug users, it seems unlikely that the criminalisation of NPS use would have dissuaded use of these substances, although it would have reduced their availability. Furthermore, legislative changes fail to explain the increase in phenethylamines and tryptamines observed in this paper. Nevertheless, it is important that further research evaluate the impact of Australian legislation on the NPS marketplace to provide an evidence-base for the efficacy of these regulatory approaches.

This paper also illustrates the heterogeneity of NPS consumers, with the correlates of use varying across NPS classes. Perhaps not surprisingly, our findings suggest that RPU seek out NPS that have similar properties to the ‘traditional’ illicit drugs that they are already using. More specifically, frequent ecstasy users were more likely to report recent use of phenethylamine- type NPS, LSD users were more likely to report recent use of phenethylamines (many of which have psychedelic properties) and tryptamines, and daily cannabis users were more likely to report recent use of synthetic cannabinoids. Cocaine users were more likely to report recent use of synthetic cathinones, although this did not reach statistical significance.

Use of a larger number of ‘established’ illicit drugs emerged as the only consistent predictor of NPS use. This suggests that NPS users may represent a more innovative group of ‘psychonaut’ drug users, a term used to describe people who actively seek out new substances for the purposes of achieving altered states of consciousness (EMCCDA, 2004). It is important to note that for participants using a single NPS class this did not equate to a greater likelihood of drug- related harms. This was somewhat surprising, particularly given that clinical studies have shown that drugs such as NBOMe have been linked to a number of deaths and hospitalisations, despite its short history of human consumption (Wood et al., 2015).

Rather, poly-NPS users were found to be the riskiest group of NPS consumers; in addition to having high levels of poly-drug use, this group were also more likely to have engaged in past month criminal activity and to have overdosed on any drug in the past year. These behaviours carry serious public health implications, particularly given the ever increasing number of NPS being identified, the limited knowledge of the short- and long-term effects of these drugs, and a lack of information on how they interact with other drugs. It is recommended that credible harm reduction messages be disseminated amongst these populations, with a particular focus

on the potential risks of combining NPS and ‘traditional’ illicit drugs (for example, see Winstock et al., 2010).

3.7.1 Limitations

This study has certain limitations. Firstly, the EDRS sample is not representative, which means that our findings are not generalizable to all RPU in Australia. Rather, it is a sentinel sample which allows for the early identification of trends in illicit drug markets, which is particularly important when monitoring marketplaces which are rapidly changing (as is the case of NPS). Secondly, our analysis is reliant upon self-report data from participants which may be subject to bias. Although evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use (Darke, 1998), it is possible that participants may have incorrectly identified the NPS being consumed (i.e. it may have been sold to them as one thing, but have been something else) and it would be of benefit for future studies to corroborate their findings through chemical analysis. Finally, the EDRS only specifically asked about 26 different NPS and as such rates of use may be underestimated.

3.8 Conclusions

Whilst NPS use has been established as a significant and ongoing practice amongst our sample of RPU, it remains a highly dynamic marketplace with the popularity of NPS classes changing significantly across 2010-2015. It appears that RPU seek out NPS with similar properties to the traditional illicit drugs that they are already consuming. Poly NPS consumers were found to be a particularly high risk group and as such it is essential that credible harm reductions messages be distributed amongst these populations.

3.9 Supplementary materials

Table 14: Number of participants, 2010-2015 Total number of participants Number of repeat participants n n (%) 2010 693 115 (16.6) 2011 574 104 (18.1) 2012 607 81 (13.3) 2013 685 65 (9.5) 2014 800 81 (10.1) 2015 763 83 (10.9)

Table 15: Recent NPS use: overlap between NPS classes, 2011-2015 Phenethylamines Tryptamines Synthetic Synthetic Piperazines Plants & Aminoindanes Cannabinoids Cathinones extracts Tryptamines (n) 140 Synthetic cannabinoids (n) 86 69 Synthetic cathinones (n) 89 77 33 Piperazines (n) 5 5 5 10 Plants & extracts (n) 56 69 44 29 3 Aminoindanes (n) 7 5 4 3 1 4 Arylcyclohexylamines (n) 18 23 7 16 0 1 2 Note: For example, 140 participants had used phenethylamines and tryptamines; 86 had used phenethylamines and synthetic cannabinoids; 89 had used phenethylamines and synthetic cathinones.

Table 16: Rates# of NPS use amongst RPU, 2010-2015 (excludes repeat participants) 2010 % 2011 % 2012 % 2013 % 2014 % 2015 % 2010-2015* % (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) 95% CI; p value SYNTHETIC CATHINONES 18.5 17.5 10.6 8.5 7.4 7.4 11.3 Mephedrone (miaow, 4MMC); Methylone (bk-MDMA); MDPV (Ivory Wave); (-0.04, 0.06; (0.02, 0.11; (-0.01, 0.06; (-0.02, 0.04; (-0.03, 0.03; 0.08, 0.15; Other substituted cathinone p=0.734) p=0.003) p=0.273) p=0.547) p=0.933) p<0.001 PHENETHYLAMINES 8.0 16.3 13.7 20.7 22.0 18.5 16.8 2C-I; 2C-B (Bromo, TWOs, trystacy); 2C-E (hummingbird, europa); 2C-Other; (-0.13, -0.04; (-0.02, 0.07; (-0.11, -0.02; (-0.06, 0.03; (-0.01, 0.08; -0.14, -0.07; Benzo Fury (6-APB); PMA; DOI (death on impact); NBOMe (25I, 25B, 25C) p<0.001) p=0.318) p=0.004) p=0.609) p=0.120) p<0.001 TRYPTAMINES 7.5 14.2 13.8 14.0 14.3 10.8 12.3 DMT; 5-Meo-DMT (-0.11, -0.03; (-0.04, 0.05; (-0.04, 0.04; (-0.04, 0.04; (-0.000, 0.07; -0.06, -0.002; p<0.001) p=0.961) p=0.988) p=0.947) p=0.060) p=0.047 SYNTHETIC CANNABINOIDS - 6.6 16.6 16.0 6.7 6.5 10.1 K2/Spice; Kronic; Other synthetic cannabinoid (-0.14, -0.06; (-0.04, 0.05; (0.06, 0.13; (-0.02, 0.03; -0.03, 0.03; p<0.001) p=0.843) p<0.001) p=0.958) p=0.952 PIPERAZINES 4.9 1.6 1.2 <0.1 <0.1 0 1.3 BZP (0.01, 0.05; (-0.01, 0.02; (0.001, 0.02; (-0.01, 0.01; (-0.003, 0.01; 0.03, 0.07; p=0.008) p=0.804) p=0.069) p=0.896) p=0.503) p<0.001 PLANTS & EXTRACTS 2.0 7.9 7.7 6.0 4.5 4.4 5.1 LSA (Hawaiian Baby); Mescaline; Salvia Divinorum; Datura (Angel’s trumpet); (-0.09, -0.03; (-0.03, 0.04; (-0.01, 0.05; (-0.01, 0.04; (-0.02, 0.03; -0.04, -0.004; Ayahuasca p<0.001) p=0.981) p=0.347) p=0.254) p=0.928) p=0.030 AMINOINDANES - - 0.9 0.7 <0.1 <0.1 0.5 MDAI; 5-IAI (-0.01, 0.01; (-0.01, 0.01; (-0.01, 0.01; -0.003, 0.02; p=0.913) p=0.841) p=0.951) p=0.325 ARYLCYCLOHEXYLAMINES 1.4 2.4 1.0 1.5 1.6 Methoxetamine (MXE) (-0.03, 0.01; (0.001, 0.03; (-0.02, 0.01; -0.01, 0.01; p=0.276) p=0.062) p=0.547) p=0.902 ANY NPS % 32.9 42.7 50.8 46.6 40.5 39.6 41.5 (-0.16, -0.04; (-0.15, -0.02; (-0.02, 0.10; (0.01, 0.11; (-0.04, 0.06; -0.12, -0.02; p=0.001) p=0.019) p=0.196) p=0.029) p=0.768) p=0.013 Note: For synthetic cathinones, phenethylamines, tryptamines, piperazines, and plants & extracts, 2011-2015 figures exclude repeat participants. For synthetic cannabinoids, 2012-2015 figures exclude repeat participants. For aminoindanes and arylcyclohexylamines, 2013-2015 figures exclude repeat participants; #in the past six months; *for synthetic cannabinoids this refers to 2011-2015 figures; for aminoindanes and arylcyclohexylamines this refers to 2012-2015 figures. Pairwise comparisons made across adjacent years; i.e. 2010 vs 2011; 2011 vs 2012; 2012 vs 2013; 2013 vs 2014; 2014 vs 2015; 95% CI refers to the differences across adjacent years, except for the final column where they refer to differences in 2010 vs 2015 percentages. = a significant increase in 2010 vs 2015 figures. = a significant decrease in 2010 vs 2015 figures. − no change in 2010 vs 2015 figures. Significant findings have been bolded.

3.10 References

Andrews, G., Slade, T., 2001. Interpreting scores on the Kessler Psychological Distress Scale (K10). Australian and New Zealand Journal of Public Health. 25, 494−7. Australian Institute of Health and Welfare (AHIW), 2014. 2013 National Drug Strategy Household Survey: Detailed Findings. Canberra: Australian Institute of Health and Welfare. Babor, T., Higgins-Biddle, J., 2000. Alcohol screening and brief intervention: Dissemination strategies for medical practice and public health. Addiction. 95, 677-86. Bonar, E.E., Ashrafioun, L., Ilgen, M.A., 2014. Synthetic cannabinoid use among patients in residential substance use disorder treatment: Prevalence, motives, and correlates. Drug and Alcohol Dependence. 143, 268-271. Bretteville-Jensen, A.L., Tuv., S.S., Bilgrei, O.R., Fjeld, B., Bachs, L., 2013. Synthetic cannabinoids and cathinone: Prevalence and markets. Forensic Science Review. 25(1-2), 7-26. Bright, S.J., Bishop, B., Kane, R., Marsh, A., Barratt, M.J., 2013., Kronic hysteria: Exploring the intersection between Australian synthetic cannabis legislation, the media, and drug-related harm. International Journal of Drug Policy. doi:10.1016/j.drugpo.2012.12.002. Bruno, R., Gomez, R., Matthews, A., 2011. Choosing a cut-off on the Severity of Dependence Scale for ecstasy use. The Open Addiction Journal. 4, 13-14. Bruno, R., Matthews, A. J., Dunn, M., Alati, R., McIlwraith, F., Hickey, S., Burns, L., Sindicich, N., 2012. Emerging psychoactive substance use among regular ecstasy users in Australia. Drug and Alcohol Dependence. 124(1–2), 19-25. doi: http://dx.doi.org/10.1016/j.drugalcdep.2011.11.020. Burns, L., Roxburgh, A., Matthews, A., Bruno, R., Lenton, S., Van Buskirk, J., 2014. The rise of new psychoactive use in Australia. Drug Testing and Analysis. 6, 846-849. Dargan, P. I., Albert, S., Wood, D. M., (2010). Mephedrone use and associated adverse effects in school and college/university students before the UK legislation change. QJM. 103(11), 875-879. doi: 10.1093/qjmed/hcq134. Dargan, P. I., Sedefov, R., Gallegos, A., Wood, D. M., (2011). The pharmacology and toxicology of the synthetic cathinone mephedrone (4-methylmethcathinone). Drug Testing and Analysis. 3(7-8), 454-463. doi: 10.1002/dta.312. Darke, S., 1998. Self report among injecting drug users: A review. Drug & Alcohol Dependence. 51 (3), 253-263. Darke, S., Ward, J., Hall, W., Heather, N., Wodak, A., 1991. The Opiate Treatment Index (OTI) Researcher’s Manual. Technical Report No. 11. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Emmanual, F., Attarad, A., 2006. Correlates of injection use of synthetic drugs among drug users in Pakistan: A case controlled study. Journal of Pakistan Medical Association. 56(3), 119-124. European Commission, 2011. Youth Attitudes on Drugs. Flash Eurobarometer 330. Available from: . [1 December 2015]. European Commission, 2014. Young People and Drugs. Flash Eurobarometer 401. Available from: . [1 December 2015].

European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2004. Report on the Risk Assessment of 2C-I, 2C-T-2 and 2C-T-7 in the Framework of the Joint Action on New Synthetic Drugs. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2006. Eurpol 2005 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2007. Eurpol 2006 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2008. Eurpol 2007 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2009. Eurpol 2008 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2010. Eurpol 2009 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2011. Eurpol 2010 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2012. Eurpol 2011 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2013. New Drugs in Europe, 2012. Eurpol 2012 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2014. Eurpol 2013 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2015. Eurpol 2014 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. Every-Palmer, S. 2010. Warning: legal synthetic cannabinoid-receptor agonists such as JWH-018 may precipitate psychosis in vulnerable individuals. Addiction, 105, 1859-60. Freeman T. P., Morgan C. J. A., Vaughn-Jones J., Hussain N., Karimi K., Curran H. V., 2012. Cognitive and subjective effects of mephedrone and factors influencing use of a ‘new legal high’. Addiction. 107, 792–800. Gossop, M., Darke, S., Griffiths, P., Hando, J., Powis, B., Hall, W., Strang, J., 1995. The Severity of Dependence Scale (SDS): Psychometric properties of the SDS in English and Australian samples of heroin, cocaine and amphetamine users. Addiction. 90(5), 607-14. Griffiths, P., Sedefov, R., Gallegos, A., Lopez, D., 2010. How globalization and market innovation challenge how we think about and respond to drug use: ‘Spice’ a case study. Addiction. 105, 951- 953. Hermanns-Clausen, M., Kneisel, S., Szabo, B., Auwärter, V., 2013. Acute toxicity due to the confirmed consumption of synthetic cannabinoids: clinical and laboratory findings. Addiction. 108, 534–544. Home Office, 2014. Drug Misuse: Findings from the 2013/14 Crime Survey for England and Wales. London: Home Office. Available from: . [1 December 2015]. IBM Corporation, 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corporation. 100

Kelly, B.C., Wells, B.E., Pawson, M., Leclair, A., Parsons, J.T., Golub, S.A., 2013. Novel psychoactive substance use among younger adults involved in US nightlife scenes. Drug and Alcohol Review. 32(6), 588-593. Kessler, R.C., Barker, P.R., Colpe, L.J., Epstein, J.F., Gfroerer, J.C., Hiripi, E., Howes, M.J., Normand, S.L., Manderscheid, R.W., Walters, E.E., Zaslavsky, A.M., 2003. Screening for serious mental illness in the general population. Archives of General Psychiatry. 60(2), 184-9. Lawn, W., Barratt, M., Williams, M., Horne, A., Winstock, A., 2014. The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. Journal of Psychopharmacology. 28(8), 780-788. Matthews, A., Bruno, R., Burns, L., 2013. I like the old stuff better than the new stuff? Subjective experiences of emerging psychoactive substances. Drug and Alcohol Review. 24-27 November 2013, Brisbane, Australia, pp. 49. ISSN 1465-3362. [Conference Extract]. Miech, R.A., Johnston, L.D., O’Malley, P., Bachman, J.G., Schulenberg, J.E., 2014. Monitoring the Future. National Survey Results on Drug Use, 1975-2014: Volume I, Secondary School Students. Michigan: Institute for Social Research, University of Michigan. Moore, K., Dargan, P.I., Wood, D.M., Measham, F., 2013. Do novel psychoactive substances displace established club drugs, supplement them or act as drugs of initiation? The relationship between mephedrone, ecstasy and cocaine. European Addiction Research. 19, 276-282. National Advisory Committee on Drugs (NACD) & Public Health Information and Research Branch (PHIRB), 2012. Drug Use in Ireland and Northern Ireland. Drug Prevalence Survey 2010/11: Regional Drug Task Force (Ireland) and Health & Social Care Trust (Northern Ireland) Results, Bulletin 2. Available from: . [1 December 2015]. Palamar, J.J., 2015. “Bath salt” use among a nationally representative sample of high school seniors in the United States. The American Journal on Addictions. 24(6), 488-491. Palamar, J.J., Acosta, P., 2015. Synthetic cannabinoid use in a nationally representative sample of US high school seniors. Drug and Alcohol Dependence. 149, 194-202. Saunders, J.B., Aasland, O.G., Babor, T.F., de la Fuente, J.R., Grant, M., 1993. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detections of persons with harmful alcohol consumption. Addiction. 88, 793−804. Schechter, M.D., Glennon, R.A., 1985. Cathinone, cocaine and methamphetamine: similarity of behavioural effects. Pharmacology Biochemistry and Behavior. 22(6), 913-916. Sindicich, N., Burns, L., 2011. Australian Trends in Ecstasy and Related Drug Markets 2010. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 64. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Burns, L., 2012. Australian Trends in Ecstasy and Related Drug Markets 2011. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 82. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Burns, L., 2013. Australian Trends in Ecstasy and Related Drug Markets 2012. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 100. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Burns, L., 2014. Australian Trends in Ecstasy and Related Drug Markets 2013. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 118. Sydney: National Drug and Alcohol Research Centre, UNSW Australia.

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Sindicich, N., Burns, L., 2015. Australian Trends in Ecstasy and Related Drug Markets 2014. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 136. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Stafford, J., Burns, L., 2015. Australian Drug Trends. Findings from the 2014 Illicit Drug Reporting System (EDRS). Australian Drug Trend Series No. 127. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Thissen, D., Steinberg, L., Kuang, D., 2002. Quick and easy implementation of the Benjamini- Hochberg procedure for controlling the false positive rate in multiple comparisons. Journal of Educational and Behavioral Statistics. 27 (1), 77-83. United Nations Office on Drugs and Crime (UNODC), 2013. The Challenges of New Psychoactive Substances. A Report from the Global SMART Programme. Vienna: UNODC. Winstock, A.R., 2015. The Global Drug Survey 2015 Findings. Available from: . [1 December 2015]. Winstock, A.R., Barratt, M.J., 2013. Synthetic cannabis: A comparison of patterns of use and effect profile with natural cannabis in a large global sample. Drug and Alcohol Dependence. 131(1-2), 106-11. Winstock, A.R., Kaar, S., Borschmann, R., 2013. Dimethyltrytamine (DMT): Prevalence, user characteristics and abuse liability in a large global sample. Journal of Psychopharmacology. DOI: 10.1177/0269881113513852. Winstock, A.R., Marsden, J., Mitcheson, L., 2010. What should be done about mephedrone? British Medical Journal. 340, c1605. doi:1610.1136/bmj.c1605. Winstock A., Mitcheson, L., Ramsey, J., Davies, S., Puchnarewicz, M., Marsden, J., 2011. Mephedrone: use, subjective effects and health risks. Addiction. 106, 1991–1996. Wood, D.M., Sedefov, R., Cunningham, A., Dargan, P.I., 2015. Prevalence of use and acute toxicity associated with the use of NBOMe drugs. Clinical Toxicology. 53, 85-92. Van Buskirk, J., Roxburgh, A., Bruno, R., Burns, L., 2015. Drugs and the Internet. Issue 5, Sydney: National Drug and Alcohol Research Centre. Vento, A.E., Martinotti, G., Cinosi, E., Lupi, M., Acciavatti, T., Carrus, D., Santacroce, R., Chillemi, E., Bonifaci, L., di Giannantonio, M., Corazzam O., Schifano, F., 2014. Substance use in the club scene of Rome: A pilot study. BioMed Research International. http://dx.doi.org/10.1155/2014/617546.

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4. PAPER THREE: MOTIVATIONS FOR NEW PSYCHOACTIVE SUBSTANCE USE

AMONG REGULAR PSYCHOSTIMULANT USERS IN AUSTRALIA

Rachel Sutherland1, Raimondo Bruno1,2, Amy Peacock2, Simon Lenton3, Allison Matthews2, Caroline Salom4, Paul Dietze5, Kerryn Butler1, Lucinda Burns1, Monica J. Barratt1,3,5

1National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia 2 School of Medicine (Psychology), Faculty of Health, University of Tasmania, Hobart, TAS, Australia

3National Drug Research Institute, Curtin University, Shenton Park, WA, Australia 4School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia 5 Burnet Institute, Centre for Population Health, Melbourne, Victoria, Australia

Paper three has been published in the International Journal of Drug Policy

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4.1 Copyright statement

I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations.

Rachel Sutherland August 2018

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4.2 Preamble

The dynamic and rapidly evolving nature of the Australian NPS market (illustrated in paper two) can make it difficult to develop and implement appropriate harm reduction messages. Being able to identify which substances are likely to persist long-term, versus those which are likely to be transient, would provide invaluable guidance about how to best target policy initiatives. Exploring the motivations for NPS use may have some utility in this context and could assist in explaining some of the specific trends observed in paper two. It may be that motivations such as legality and availability suggest more opportunistic reasons for use which may not be stable over the long-term (e.g. use of a drug may only occur whilst it is perceived as legal and cease when it becomes illegal), whilst motivations based on preference or perceived ‘superiority’ over other drugs may suggest sustained popularity for a given drug over the long-term.

Indeed, if we want people to modify their substance use behaviours, we must first understand why they engage in such behaviours. Given the heterogeneity of NPS consumers (demonstrated in paper two), it is likely that motivations for use will vary across substances. However, whilst several studies have examined the motivations for use of a specific NPS, there is only one existing study which has explicitly compared motivations across NPS. In this study, Soussan and Kjellgren (2016) used an international sample of NPS consumers to examine eight potential motivations for NPS use. Most of the examined motives were intrinsic in nature or related to the ‘rewards’ associated with use, with only one motive related to external factors (i.e. ‘circumstances such as price, legal status, availability or non-detectability in screening tests’). Paper three will build upon the work by Soussan and Kjellgren (2016) by giving greater emphasis to external motivations (as opposed to intrinsic or reward-based motivations), and by focusing exclusively on Australian NPS consumers.

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4.3 Abstract

Background: Examine the motivations for new psychoactive substance (NPS) use amongst a sample of regular psychostimulant users (RPU) in Australia, and determine whether motivations differ across substances.

Method: Data were obtained from 419 RPU interviewed for the 2014 Ecstasy and related Drugs Reporting System who reported lifetime NPS use. Based on the most recent NPS used, motivations for use were rated on an 11-point scale (0 ‘no influence’ to 10 ‘maximum influence’).

Results: For NPS overall, value for money was found to be the most highly endorsed motivation for use, scoring a median of five out of ten. However, there was substantial variation in motivations for use across substance types. Availability (i.e. no other drug was available to me at the time; 6/10) was the most highly endorsed motivation for the use of synthetic cathinones, which was significantly higher than reported for DMT. Perceived legality and availability were the most highly endorsed motivations for synthetic cannabinoids (5/10); perceived legality scored higher for synthetic cannabinoids than for all the other NPS, whilst in regards to availability synthetic cannabinoids scored significantly higher than DMT only. Value for money was the most highly endorsed motivation for NBOMe (8/10) and 2C-family substances (5/10); in regards to NBOMe this scored significantly higher than all other NPS. Short effect duration was the most highly endorsed motivation for DMT (7/10), which was significantly higher than for all other NPS.

Conclusion: Synthetic cathinones and cannabinoids appear to be largely motivated by ‘opportunistic’ reasons (i.e. availability, legality), while NBOMe, 2C-family substances and DMT appear to be motivated by particular desirable qualities of a substance (i.e. value for money, short effect duration). Providing a nuanced understanding of why individuals use particular NPS improves our ability to understand the NPS phenomenon and to tailor harm reduction messages to the appropriate target groups.

Keywords: New psychoactive substances; synthetic cannabinoids; synthetic cathinones; 2C-x; NBOMe; DMT; motivations

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4.4 Introduction

The European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) has defined new psychoactive substances (NPS) as substances that are “not controlled by the 1961 Convention on Narcotic Drugs or the 1971 Convention on Psychotropic Substances, but which may pose a public health threat” (European Monitoring Centre for Drugs and Drug Addiction, 2016b, p.6). However, there is no universally accepted definition of NPS, and definitions vary across countries and jurisdictions. Indeed, it could be argued that the importance of ‘older-new’ drugs, such as those controlled by international legislation but not previously well-established in the recreational drug-using scene (e.g. dimethyltryptamine; DMT), must not be overlooked. In 2015 the European Union were monitoring over 560 different NPS, of which 70% were detected in the past five years (European Monitoring Centre for Drugs and Drug Addiction, 2016b). The rapid growth of the NPS market has been facilitated by a number of factors, including: the MDMA (ecstasy) shortage that occurred in the mid-2000s (resulting in pills with a low MDMA content, which often contained other drugs such as mephedrone, benzylpiperazine (BZP) and meta- chlorophenylpiperazine (mCPP); Brunt, Poortman, Niesink, & van den Brink, 2011; United Nations Office on Drugs and Crime, 2014; Vogels et al., 2009); improving technological capabilities in China and India; increased communication and trade via the internet; and the ability to produce new substances in small laboratories (European Monitoring Centre for Drugs and Drug Addiction, 2016a; Reuter & Pardo, 2017).

In addition to understanding the broader global factors that facilitated the growth of the NPS market, it is also important to examine individual motivations for NPS use. Understanding what is driving market changes can inform evaluation of policy changes (Reuter & Pardo, 2017) and the development of effective harm reduction campaigns, and it may also provide some insight into which NPS are likely to become established in the recreational drug scene. For example, motivations such as legality and availability suggest more opportunistic reasons for use which may not be stable over the long-term (e.g. many countries have since moved to prohibit NPS). However, motivations based on preference or perceived ‘superiority’ over other drugs, may suggest sustained popularity for a given drug over the long-term.

It has been argued that NPS appeal to three distinct groups of people: those attracted to the legality (or perceived legality) of these substances, those looking to avoid detection in drug tests, and those seeking a new and attractive experience (Reuter & Pardo, 2017). This view is partly supported by previous research. Legal status was initially considered to be an important contributor to the uptake of NPS. In the UK it was found that once mephedrone was listed as a

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controlled substance, self-reported use fell (Lader, 2015); similarly, following the prohibition of BZP in New Zealand, there was a decline in self-reported use among the general population (Wilkins & Sweetsur, 2013). However, it is unclear if such declines were the result of reduced availability following the legislative changes or if they were the result of a general deterrent effect (or both). Indeed, a number of NPS have remained relatively common despite their subsequent prohibition, and in such cases legal status is considered to be a secondary driver for use, particularly among those who already use illicit drugs (Measham & Newcombe, 2016). In addition, whilst some studies have identified the avoidance of drug use detection as a motivating factor for NPS use (Barratt, Cakic, & Lenton, 2013; Bonar, Ashrafioun, & Ilgen, 2014; Gunderson, Haughey, Ait-Daoud, Joshi, & Hart, 2014), it has generally been found that, overall, this is less important than intrinsic motivations such as pleasure and thrill seeking (Barratt, Allen, & Lenton, 2014; Orsolini, Papanti, Francesconi, & Schifano, 2015; Soussan & Kjellgren, 2015, 2016), and curiosity (Barratt et al., 2013; Bonar et al., 2014; Cakic, Potkonyak, & Marshall, 2010). This finding may be because, to-date, only a relatively small proportion of the population is subjected to workplace or other (e.g. sporting or criminal justice) drug testing. The groupings put forward by Reuter and Pardo (2017) also fail to account for people who are attracted to NPS for reasons such as price, purity, availability and perceived safety (Barnard, Russell, McKeganey, & Hamilton- Barclay, 2016; Barratt et al., 2013; Bonar et al., 2014; Lawn, Barratt, Williams, Horne, & Winstock, 2014; Soussan & Kjellgren, 2015, 2016; van Amsterdam, Nabben, Keiman, Haanschoten, & Korf, 2015; Winstock, Lawn, Deluca, & Borschmann, 2016).

Given the array of NPS available, it is likely that motivations for use vary across substances. Although a number of studies have examined the motivations for use of a specific NPS, to the best of our knowledge, there is only one existing published study which has explicitly compared motivations across NPS. Soussan and Kjellgren (2016) conducted an online survey of 619 international NPS users and their findings support the hypothesis that there are likely to be distinct motivation profiles across different substances. Although ‘pleasure and enjoyment’ was a common motivation across all NPS groups, the use of hallucinogens and dissociatives was substantially more motivated by exploration and spiritual attainment, whilst stimulants were typically used to enhance mental and physical abilities. In contrast, the use of synthetic cannabinoids was more motivated by circumstances such as price, legal status, availability and non-detectability on screening tests (Soussan & Kjellgren, 2016).

Soussan and Kjellgren (2016) examined eight different motives, most of which were intrinsic in nature (e.g. pleasure and enjoyment; self-exploration or spiritual attainment) or related to the ‘rewards’ associated with use (e.g. enhanced mental or physical abilities; self-assertion or self- 108

confidence); only one motive was related to external factors (i.e. ‘circumstances such as price, legal status, availability or non-detectability in screening tests’). We would argue that a stronger focus on external factors is important for two reasons. Firstly, most NPS users also use traditional illicit drugs (Australian Institute of Health & Welfare, 2014; Palamar, 2015; Palamar & Acosta, 2015) and many of the motivations for use of these substances are likely to overlap (e.g. the intrinsic motivations for using hallucinogenic NPS are likely the same for using 'traditional' hallucinogenic substances); as such it is more meaningful to determine what factors motivate one to use NPS over traditional illicit drugs. Secondly, external motivations are more amenable to change though policy and treatment.

As such, the objective of the current paper was to add to the work by Soussan and Kjellgren (2016) by giving greater emphasis to external motivations (and examining price, legal status and drug testing separately). Specifically, we aimed to:

1) Explore the motivations for using ‘any’ NPS among a sample of regular psychostimulant users (RPU) in Australia.

2) Determine whether there are differing motivations for use across the following NPS: synthetic cathinones, 2C-x, NBOMe, DMT and synthetic cannabinoids.

4.5 Method

4.5.1 Study design

This paper uses data from the 2014 Ecstasy and related Drugs Reporting System (EDRS) (for full study details, see Sindicich & Burns, 2015). The EDRS is a national monitoring study aimed at detecting emerging trends in illicit drug markets and has been conducted annually within all Australian capital cities since 2003. The EDRS has received ethical approval from the University of New South Wales (UNSW) Human Research Ethics Committee (HC10071, HC15015), as well as from the relevant ethics committees in other Australian jurisdictions.

4.5.2 Participants and procedure

EDRS participants (hereafter referred to as ‘regular psychostimulant users’ (RPU)) comprised a non-random self-selected sample recruited through street-press advertisements, online forums and peer referral. Eligibility criteria were: at least monthly use of ecstasy or other psychostimulants in the preceding six months, 16 years of age or older, and residence in the city of interview for at least 12 months prior to the interview. Face-to-face one-hour structured

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interviews were conducted by trained interviewers at a negotiated time and location, and participants were reimbursed AUD40.

4.5.3 Measures relevant to the current study

In addition to demographic questions (i.e., age, gender, sexual orientation, employment and educational status), participants were asked about their lifetime and past six-month use of licit and illicit substances. They were also asked about their lifetime and past six-month use of 26 specific NPS (see Table 17 for a full list); an open text ‘other’ option was provided to capture additional NPS not listed in the survey. For each NPS used in the past six months, participants were asked whether they had been offered it or specifically sought it out. Participants who reported lifetime use of NPS were asked, based on the NPS that they had used most recently, to rate on a scale of 0-10 (0 ‘no influence’ to 10 ‘maximum influence’) how much each of the following factors motivated them to use this substance: legality (i.e. they thought it was legal to purchase/consume); easy to buy on the internet; convenient to have it posted to them after purchasing on the internet; high level of purity compared to ‘traditional’ illicit substances; good value for money; better high than ‘traditional’ illicit substances; fewer side effects than ‘traditional’ illicit substances; short-lasting effects; unable to be detected by drug testing; safer than ‘traditional’ illicit substances; and availability (i.e. no other drug available to them at the time).

4.5.4 Statistical analysis

Motivations were compared between the most commonly used NPS, namely synthetic cathinones (i.e. mephedrone and methylone; n=53), the 2C-family substances (2C-x; n=101), NBOMe (n=49), DMT (n=92) and synthetic cannabinoids (n=40). Since some of the variables were skewed (i.e. skewness > ±1 or kurtosis > ±3) non-parametric tests were conducted; Mood’s median test was used due to the violation of the homogeneity of variance. For those motivations where significant differences were found between drugs (p<0.05), pairwise post-hoc analyses were conducted to determine where the differences lay. A Bonferroni correction was applied in order to control for multiple comparisons, resulting in an adjusted p-value of ≤0.005. To facilitate interpretation (given the large number of medians and interquartile ranges (IQR) which equal zero), the percentage who nominated scores of five or more out of ten (indicating strong endorsement) are also reported (Table 18). All analyses were conducted using IBM SPSS Statistics for Windows release 22.0 (IBM Corporation, 2013).

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4.6 Results

4.6.1 Sample characteristics

In 2014, 800 participants were recruited and interviewed for the EDRS. Analysis is based on a subset of participants who reported lifetime use of NPS and who were willing to answer questions about their motivations for use (n=419). Of this sub-sample, seventy-three percent of participants were male with a median age of 21 years (IQR 19-24), 96% were of English speaking background, 44% were tertiary qualified, 68% were employed in some capacity, 39% were students, 14% were unemployed and 2% were currently in drug treatment. The majority (99%) of participants reported recent (past six month) use of ecstasy, 51% reported recent methamphetamine use, 47% reported recent cocaine use, 53% reported recent LSD use and 88% reported recent cannabis use. Thirty-nine percent of participants reported using ecstasy or related drugs on a weekly or greater basis in the past month.

4.6.2 Rates of use

Seventy percent of the entire sample reported that they had used 'any' NPS in their lifetime and 41% reported use in the six months preceding interview. The most commonly used NPS within the preceding six months were DMT (14%), 2C-B (12%), NBOMe (9%) and mephedrone (5%), although frequency of use for each of these drugs was low (range: 1-2 days). Approximately half of recent DMT (49%), 2C-B (50%) and NBOMe (54%) users reported that they had sought out these substances, compared to only one-third (34%) of recent mephedrone users (Table 17).

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Table 17: NPS use amongst RPU (n=800), 2014 Lifetime Recent Median Offered*# Sought*# use use days*# % % % (n) % (n) (range) Synthetic cathinones Mephedrone (miaow, 4MMC) 16.5 (132) 4.9 (39) 2 (1-60) 65.8 34.2 Methylone (bk-MDMA) 9.4 (75) 3.0 (24) 2 (1-48) 58.3 41.7 MDPV/Ivory wave 2.9 (23) 0.8 (6) - - - Other synthetic cathinone 1.1 (9) 0.3 (2) - - - Any synthetic cathinone^ 22.1 (177) 8.0 (64) n/a n/a n/a DMT 27.4 (219) 14.0 (112) 1 (1-24) 51.5 48.5 5-MeO-DMT 2.1 (17) 0.8 (6) - - - MDAI 1.6 (13) 0.5 (4) - - - Benzo Fury 1.3 (10) 0.4 (3) - - - BZP 3.0 (24) 0.3 (2) - - - 5-IAI 0.4 (3) 0 - - - PMA 4.4 (35) 2.1 (17) 1 (1-6) 93.3 6.7 MXE 4.3 (34) 1.6 (13) 4 (1-15) 69.2 30.8 LSA 5.3 (42) 1.4 (11) 2 (1-3) 30 70 DOI 1.5 (12) 0.1 (1) - - - 2C-x 2C-B 25.9 (207) 11.5 (92) 1.5 (1-24) 50.0 50.0 2C-I 15.8 (126) 5.6 (45) 1(1-24) 57.1 42.9 2C-E 5.9 (47) 0.9 (7) - - - 2C-other 2.8 (22) 0.4 (3) - - - Any 2C-x^^ 33.0 (264) 14.5 (116) n/a n/a n/a NBOMe 12.8 (102) 9.0 (72) 2 (1-48) 45.7 54.3 Synthetic cannabis K2/spice 7.6 (61) 1.8 (14) 2.5 (1-14) 75 25 Kronic 18.0 (144) 3.1 (25) 2.5 (1-50) 68 32 Other synthetic cannabinoid 8.6 (69) 2.6 (21) 1(1-90) 55 45 Any synthetic cannabinoid^^^ 28.5 (228) 6.9 (55) n/a n/a n/a Mescaline 8.1 (65) 1.9 (15) 1 (1-3) 83.3 16.7 Salvia divinorum 10.5 (84) 1.8 (14) 1 (1-12) 58.3 41.7 Datura 3.3 (26) 0.1 (1) - - - Herbal high 17.5 (140) 4.3 (34) 1 (1-30) 33.3 66.7 *Among those who had used in the past six months #Data not presented where n<10 ^Collapses figures for mephedrone, methylone, MDPV and other synthetic cathinone. This was done for lifetime and recent use only; since participants may have used more than one type of synthetic cathinone we were unable to collapse figures for the last three columns. ^^Collapses figures for 2C-B, 2C-I. 2C-E and 2C-other. This was done for lifetime and recent use only; since participants may have used more than one type of 2C substance we were unable to collapse figures for the last three columns. ^^^Collapses figures for K2/spice, Kronic and other synthetic cannabinoids. This was done for lifetime and recent use only; since participants may have used more than one type of synthetic cathinone we were unable to collapse figures for the last three columns.

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4.6.3 Motivations

When considering NPS overall, none of the motivations asked about were rated particularly highly. Value for money was the most highly endorsed motivation for use of any NPS, scoring a median of five out of ten, and with 59% of users nominating a score of five or more. This was followed by ‘I thought it would give a better high’ (3/10; 44% nominating a score of ≥5) and ‘I thought it would have a high level of purity’ (2/10; 41% nominating a score of ≥5) (Table 18).

There was significant variation in most of the motivations for use when compared between drug types (see Table 18). However, there were no significant differences between drug types for ‘I thought it would give a better high’ or ‘I thought it would have a high level of purity’, and hence no post-hoc analyses were conducted for these motivations.

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Table 18: Median scores and differences in motivations for most recent NPS used, 2014 Any NPS (a) Synthetic (b) 2C-x (c) DMT (d) NBOMe (e) Synthetic p; Post-hoc (combined)# cathinones cannabinoids Cramer’s analyses## n=419 n=53 n=101 n=92 n=49 n=40 V

% Median % Median % Median % Median % Median % Median scored score** scored score** scored score** scored score** scored score** scored score** ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) Legal to buy 17 0 (0-0) 8 0 (0-0) 4 0 (0-0) 2 0 (0-0) 17 0 (0-0) 54 5 (0-10) <0.001; e>a,b,c,d 0.512 d>c Easy to purchase 15 0 (0-0) 10 0 (0-0) 11 0 (0-0) 14 0 (0-0) 38 0.5 3 0 (0-0) <0.001; d>a,b,c,e on internet (0-7.75) 0.337 Postage 13 0 (0-0) 10 0 (0-0) 10 0 (0-0) 12 0 (0-0) 35 0 3 0 (0-0) <0.001; d>a,b,c,e (0-7.75) 0.294 Higher purity 41 2 (0-7) 35 0 (0-6) 38 2 (0-6.5) 41 2 (0-7) 54 5 31 0 (0-5) 0.139; - (0-8.75) 0.147 Value for money 59 5 (0-8) 60 5 (0-8) 65 5 (0-8) 50 4.5 (0-7) 80 8 (5-10) 44 3 (0-5) <0.001; d>a,b,c,e; 0.286 b>e Better high 44 3 (0-7) 29 0 (0-5) 47 4 (0-7) 55 5 (0-8) 43 4 (0-6) 33 2 (0-5) 0.059; - 0.168 Fewer side 31 0 (0-5) 20 0 (0-4) 28 0 (0-5) 39 2 (0-7) 33 0 (0-5.5) 31 0 (0-5) 0.017; - effects 0.192 Effect wouldn’t 36 0 (0-6) 20 0 28 0 (0-5) 69 7 (3-10) 22 0 (0-4) 28 0 (0-5) <0.001; c>a,b,d,e last too long (0-2.25) 0.414 Drug testing 18 0 (0-1) 2 0 (0-0) 13 0 (0-0.5) 18 0 (0-1) 25 0 (0-5) 28 0 (0-5) 0.001; a

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Table 18 (continued): Median scores and differences in motivations for most recent NPS used, 2014 Any NPS (a) Synthetic (b) 2C-x (c) DMT (d) NBOMe (e) Synthetic p; Post-hoc (combined)# cathinones cannabinoids Cramer’s analyses## n=419 n=53 n=101 n=92 n=49 n=40 V

% Median % Median % Median % Median % Median % Median scored score** scored score** scored score** scored score** scored score** scored score** ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) ≥5* (IQR) Availability 32 0 (0-7) 57 6 (0-10) 31 0 (0-6) 11 0 (0-0) 20 0 (0-3) 56 5 (0-10) <0.001; ca,b,c,d indicates that for the motivation ‘legal to buy’ synthetic cannabinoid users (e) nominated a significantly higher score than synthetic cathinone (a), 2C-x (b), DMT (c) and NBOMe (d) users. Note: p≤0.005 used in the post-hoc analyses to account for multiple comparisons; significant findings bolded. *Note: No analyses were conducted on these figures; they are presented to assist with ease of interpretation, given the large number of 0 (0-0) medians and interquartile ranges (IQR). **From 0-10, with 0 being no influence and 10 being maximum influence.

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4.6.3.1 Synthetic cathinones

The most highly endorsed motivation for the use of synthetic cathinones was availability (i.e. no other drug was available to me at the time; median 6/10; 57% nominating a score of ≥5); however, this only differed significantly from DMT, which scored a median of 0/10. The second most endorsed motivation for the use of synthetic cathinones was value for money (5/10; 60% nominating a score of ≥5), although this was significantly lower than for NBOMe (8/10) and not statistically different from scores for the other NPS.

4.6.3.2 2C-x

The most highly endorsed motivation for the use of 2C-x was value for money (5/10; 65% nominating a score of ≥5); this score was significantly lower than for NBOMe which scored a median of 8/10 and significantly higher than synthetic cannabinoids which scored a median of 3/10. The second most endorsed motivation for the use of 2C-x was the perception of a better high (4/10; 47% nominating a score of ≥5), although this did not differ significantly from any of the other NPS.

4.6.3.3 DMT

The most highly endorsed motivation for the use of DMT was short effect duration (7/10; 69% nominating a score of ≥5); this score was significantly higher than for all the other NPS. The second most endorsed motivation was the perception of a better high (5/10; 55% nominating a score of ≥5), although this did not differ significantly from any of the other NPS.

4.6.3.4 NBOMe

The most highly endorsed motivation for the use of NBOMe was value for money (8/10; 80% nominating a score of ≥5); this score was significantly higher than for all the other NPS. The second most endorsed motivation was a higher level of purity (5/10; 54% nominating a score of ≥5), although this rating did not differ significantly from any of the other NPS. The ability to easily purchase NBOMe on the internet scored a median rating of 0.5 (38% nominating a score of ≥5); although this is a low rating, it was significantly higher than scored by all the other NPS.

4.6.3.5 Synthetic cannabinoids

The most highly endorsed motivations for the use of synthetic cannabinoids were legality (5/10; 54% nominating a score of ≥5) and availability (5/10; 56% nominating a score of ≥5). The rating of legality was significantly higher for synthetic cannabinoids than all other NPS, whilst in regards to availability synthetic cannabinoids scored significantly higher than DMT only.

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4.7 Discussion

We found significant variation in the motivations for using NPS. When examined as a homogenous group of drugs, it was found that the most highly endorsed motivation for using ‘any’ NPS was value for money. However, when synthetic cathinones, 2C-x, NBOMe, DMT and synthetic cannabinoids were examined individually, we found substantial differences in the primary motivations for use. These results are similar to Soussan and Kjellgren’s (2016) finding of distinct motivation profiles across NPS, and builds upon their work by giving more focus to external factors.

The most highly endorsed motivation for synthetic cathinone use was availability (i.e. no other drug available to me at the time), potentially indicative of more opportunistic use. Further, two- thirds of those who had recently used mephedrone (the most commonly used cathinone among this sample), reported that the drug had been offered to them rather than sought out. These findings are consistent with previous work showing less favourable ratings in terms of pleasurable effects and likelihood of future use for synthetic cathinones (i.e. mephedrone, methylone, methylenedioxypyrovalerone) compared to ecstasy and cocaine (Matthews et al., In Press).This suggests that synthetic cathinone use may be less likely to persist within Australia’s recreational drug scene unless there are also changes to external drivers such as the price and availability of traditional substances. Interestingly, a previous study of RPU in Australia found that although synthetic cathinones were the most commonly used NPS in 2010, by 2015 there had been a significant decline in their use (Sutherland et al., 2016); this decline was likely due to number of factors including legislative change, consumer acceptability and external market factors such as availability.

The most highly endorsed reasons for synthetic cannabinoid use were legality (or perceived legality, since many synthetic cannabinoids are now prohibited across Australia e.g. Bright, Bishop, Kane, Marsh, & Barratt, 2013), and availability. Legality as a motive scored higher for synthetic cannabinoids than for all the other NPS, whilst in regards to availability synthetic cannabinoids scored significantly higher than DMT only. The majority of synthetic cannabinoid users reported that these substances had been offered to them, rather than specifically sought out, again indicating more opportunistic use. Combined, these findings suggest that while legality and availability may have encouraged initiation of synthetic cannabinoid use, continued uptake will likely be limited among established illicit drug users – particularly since they generally have ready access to traditional cannabis. Indeed, participants in this sample largely report that both outdoor-cultivated (‘bush’) and indoor-cultivated hydroponic cannabis are ‘easy’ or ‘very

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easy’ to obtain (79% and 92% respectively) and this has remained consistent over time (Sindicich & Burns, 2015). This hypothesis is supported by studies showing significant declines in self- reported use of synthetic cannabinoids over time (Johnston, O'Malley, Bachman, Schulenberg, & Miech, 2015; Sutherland et al., 2016), as well as by studies documenting the negative effect profile of synthetic cannabinoids (Barratt et al., 2013; Winstock & Barratt, 2013).

Value for money was the most highly endorsed motivation for both NBOMe and 2C-x. This motivation was particularly prominent for NBOMe, with a significantly higher score relative to all other NPS. This is perhaps not surprising given that LSD blotters are reported to be 5-10 times more expensive than NBOMe blotters sold via online marketplaces (Erowid, 2013). The perception of a better high and a higher level of purity than traditional illicit drugs were the second most endorsed motivations for 2C-x and NBOMe, respectively (although median ratings for these motivations did not differ significantly relative to other NPS). These motivating factors are supported by studies which have shown that both NBOMe and 2CB are perceived favourably in terms of strength of effect and pleasurability - although it is important to note that LSD was rated more favourably than 2CB in terms of pleasurable effects and likelihood of using again (Lawn et al., 2014; Matthews et al., In Press). In addition, about half of recent NBOMe and 2C-x users reported that they had specifically sought out these substances. Combined, these factors suggest potential long-term, sustained popularity of both 2C-x and NBOMe. Indeed, rates of past six month phenethylamine NPS use (including NBOMe and 2C-x) among RPU were found to have increased significantly over time, from 8.0% in 2010 to 18.6% in 2015 (Sutherland et al., 2016).

The most highly endorsed motivation for DMT use was the short duration of its effects. When smoked, DMT generally reaches full effects within 10-60 seconds of inhalation and lasts approximately 5-20 minutes (Erowid, 2015). This is in stark contrast to traditional psychedelic substances (e.g. duration of LSD is 6-11 hours, magic mushrooms 4-7 hours; Erowid, 2016a, 2016b); high endorsement suggests that this is a desirable quality among this sample of RPU. Previous studies have shown that, when compared to other hallucinogens, DMT was rated favourably in terms of strength of effect and pleasure (Matthews et al., In Press; Winstock, Kaar, & Borschmann, 2014). Indeed, rates of tryptamine use (primarily DMT) among RPU increased significantly from 2010-2015 (Sutherland et al., 2016); DMT appears to have become well- established within Australia’s recreational drug scene and its popularity seems unlikely to diminish within the foreseeable future.

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4.7.1 Strengths, Limitations and Future Research

This study provides a unique insight into patterns and drivers of NPS use amongst RPU in Australia, however certain aspects of the design should be considered when interpreting the findings. The study uses a sentinel, non-representative, sample to identify trends in illicit drug markets, which is particularly important when monitoring marketplaces which are rapidly changing (as is the case for NPS). Whilst participants are recruited from all capital cities in Australia, the present findings may not be generalisable to all RPU in Australia, nor are they generalisable to all NPS users in Australia. For example, legality and availability may be more important motivating factors for ‘novice’ drug users and those without established contact with illicit subcultures and illegal economies. Similarly, the avoidance of drug use detection may be more important for individuals who are subjected to regular drug testing (e.g. prisoners and people in certain professions; Measham & Newcombe, 2016). Nevertheless, given the unique motivation profiles found in both our and Soussan and Kjellgren’s (2016) studies, it would be of benefit to develop a standardised motivation scale specific to NPS, with demonstrated validity and reliability. This would facilitate comparisons between studies, over time and across countries; this is particularly important given that differences in local drug markets, as well as differences in legal and social contexts, will likely result in country specific variations in the motivations for NPS use.

In regards to individual differences driving motivations, it is important to note that the current analyses were between-subject, where participants were grouped into NPS classes based only on the most recent substance used (i.e. not the potential full array of NPS used), and systematic differences between NPS consumer types may partly explain different motivational profiles for NPS. These factors could be explored further in future work via analyses which take into account heterogeneity in NPS consumer samples; within-subject research with polydrug NPS consumers which compares motivations for different NPS use by the same individual; and longitudinal studies which track trajectories of NPS use over time for the same individual.

Finally, our analysis is reliant upon self-report data from participants which may be subject to bias, although evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use (Darke, 1998). Our findings are also based on relatively small sample sizes and as such caution must be exercised when interpreting null results.

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4.8 Conclusion

In summary, we found significant variation in the motivations for using different NPS. Our sample of RPU were a diverse community of drug users who had used NPS for a variety of reasons. Providing a nuanced understanding of why individuals use particular NPS improves our ability to understand the NPS phenomenon and to tailor harm reduction messages to the appropriate target groups. For example, participants who use NPS for opportunistic reasons (e.g. synthetic cannabinoids because they thought it was legal, or because no other drug was available to them) might be more receptive to an education-based campaign surrounding the legal status and harms associated with these substances. However, participants who use NPS because they are perceived as a superior product, or to have desirable qualities, are less likely to cease use of these substances and may benefit more from policy responses like chill-out rooms in nightlife settings and on-site chemical analyses of drug samples (refer to European Monitoring Centre for Drugs and Drug Addiction, 2016b for a broad coverage of potential NPS interventions).

Furthermore, we found that the varying motivations appeared to correspond with trends in use over time. That is, NPS which were used for ‘opportunistic’ reasons (e.g. availability, legality) were found to have declined in use over time, while NPS use motivated by the desirable qualities of a substance (e.g. value for money, short effect duration) or the perception of a superior product (e.g. better high/purity) corresponded with increases in use over time. Our findings, combined with previous studies showing the positive and negative effect profiles of various NPS, suggest that NBOMe, 2C-x and DMT may maintain popularity within Australia’s recreational drug scene (although it is important to note that frequency of use remains extremely low: 1-2 days in past six months). In contrast, sustained use of synthetic cathinones and cannabinoids seems unlikely, unless there are also changes to external drivers such as the price and availability of traditional substances. Indeed, although the majority (70%) of NPS being monitored by the EMCDDA fall into the stimulant and synthetic cannabinoid effect classes (European Monitoring Centre for Drugs and Drug Addiction, 2016b), psychedelic NPS (i.e. DMT, NBOMe and 2C-x) remain the most commonly sold NPS on dark net marketplaces (Van Buskirk, Roxburgh, Bruno, & Burns, 2015). Furthermore, a recent study of experienced recreational drug users found that while participants were more likely to have ever used stimulant NPS, in the future they predominantly intended to try psychedelic NPS (van Amsterdam et al., 2015). This is not to say that these substances will replace traditional illicit drugs, but rather will likely complement them (Moore, Dargan, Wood, & Measham, 2013). Of course, given the rapidly evolving nature of the

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NPS marketplace it is impossible to predict its future with any certainty; in many respects, these trends will vary according to the availability of better established substances, as well as the nature of newly emergent products. In the meantime, we must remain vigilant and increase our capacity to detect and respond to new trends in a timely manner.

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4.9 Supplementary materials

Table 19: ‘It was legal to buy’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.495 0.237 0.098 <0.001 0.550 2C-x 0.560 0.007 <0.001 0.602 DMT 0.002 <0.001 0.269 0.635 NBOMe <0.001 0.405 Synthetic cannabis

Note: significance value of p≤0.005 was used to control for multiple comparisons; significant findings bolded. When significant differences were found, Cramer’s V is also reported.

Table 20: ‘It was easy to buy on the internet’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.885 0.580 <0.001 0.168 0.387 2C-x 0.618 <0.001 0.115 0.375 DMT <0.001 0.060 0.341 NBOMe <0.001 0.487 Synthetic cannabinoids

Note: significance value of p≤0.005 was used to control for multiple comparisons; significant findings bolded. When significant differences were found, Cramer’s V is also reported.

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Table 21: ‘It was convenient to have it posted to me after buying on the internet’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.902 0.853 0.001 0.159 0.325 2C-x 0.938 <0.001 0.111 0.315 DMT <0.001 0.103 0.311 NBOMe <0.001 0.436 Synthetic cannabinoids Note: significance value of p≤0.005 was used to control for multiple comparisons; significant findings bolded. When significant differences were found, Cramer’s V is also reported.

Table 22: ‘It was good value for money’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.582 0.357 0.001 0.018 0.326 2C-x 0.085 <0.001 0.002 0.307 0.262 DMT <0.001 0.505 0.336 NBOMe <0.001 0.506 Synthetic cannabinoids Note: significance value of p≤0.005 was used to control for multiple comparisons; significant findings bolded. When significant differences were found, Cramer’s V is also reported.

Table 23: ‘Thought it would have fewer side effects than traditional illicit drugs’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.087 0.022 0.112 0.453 2C-x 0.082 0.907 0.462 DMT 0.334 0.158 NBOMe 0.457 Synthetic cannabinoids Note: significance value of p≤0.005 was used to control for multiple comparisons; significant findings bolded. When significant differences were found, Cramer’s V is also reported.

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Table 24: ‘I knew the effect wouldn’t last too long’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.205 <0.001 0.122 0.197 0.377 2C-x <0.001 0.616 0.789 0.413 DMT <0.001 <0.001 0.456 0.336 NBOMe 0.863

Synthetic cannabinoids Note: significance value of p≤0.005 was used to control for multiple comparisons; significant findings bolded. When significant differences were found, Cramer’s V is also reported.

Table 25: ‘I thought it couldn’t be detected by drug testing’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.002 <0.001 <0.001 <0.001 0.260 0.298 0.428 0.391 2C-x 0.572 0.079 0.309

DMT 0.213 0.576

NBOMe 0.598

Table 26: ‘I thought it would be safer than traditional illicit drugs’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.105 0.001 0.002 0.002 0.296 0.314 0.333 2C-x 0.016 0.042 0.038

DMT 0.983 0.869

NBOMe 0.868

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Table 27: ‘No other drug was available to me at the time’: post-hoc comparisons across NPS, 2014 2C-x DMT NBOMe Synthetic cannabinoids p; Cramer’s V p; Cramer’s V p; Cramer’s V p; Cramer’s V Synthetic cathinones 0.050 <0.001 0.009 0.977 0.452 2C-x <0.001 0.815 0.033 0.285 DMT <0.001 <0.001 0.305 0.498 NBOMe 0.006

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4.10 References

Australian Institute of Health & Welfare. (2014). 2013 National Drug Strategy Household Survey: Detailed Findings. Retrieved from Canberra: Barnard, M., Russell, C., McKeganey, N., & Hamilton-Barclay, T. (2016). The highs and lows of NPS/“Legal High” use: Qualitative views from a UK online survey. Drugs: Education, Prevention and Policy, 1-7. doi:10.1080/09687637.2016.1201046 Barratt, M. J., Allen, M., & Lenton, S. (2014). “PMA Sounds Fun”: Negotiating Drug Discourses Online. Substance Use & Misuse, 49(8), 987-998. doi:10.3109/10826084.2013.852584 Barratt, M. J., Cakic, V., & Lenton, S. (2013). Patterns of synthetic cannabinoid use in Australia. Drug and Alcohol Review, 32(2), 141-146. doi:10.1111/j.1465-3362.2012.00519.x Bonar, E. E., Ashrafioun, L., & Ilgen, M. A. (2014). Synthetic cannabinoid use among patients in residential substance use disorder treatment: Prevalence, motives, and correlates. Drug and Alcohol Dependence, 143, 268-271. doi:http://dx.doi.org/10.1016/j.drugalcdep.2014.07.009 Bright, S. J., Bishop, B., Kane, R., Marsh, A., & Barratt, M. J. (2013). Kronic hysteria: Exploring the intersection between Australian synthetic cannabis legislation, the media, and drug- related harm. International Journal of Drug Policy, 24(3), 231-237. doi:http://dx.doi.org/10.1016/j.drugpo.2012.12.002 Brunt, T. M., Poortman, A., Niesink, R. J., & van den Brink, W. (2011). Instability of the ecstasy market and a new kid on the block: mephedrone. Journal of Psychopharmacology, 25(11), 1543-1547. doi:10.1177/0269881110378370 Cakic, V., Potkonyak, J., & Marshall, A. (2010). Dimethyltryptamine (DMT): Subjective effects and patterns of use among Australian recreational users. Drug and Alcohol Dependence, 111(1–2), 30-37. doi:http://dx.doi.org/10.1016/j.drugalcdep.2010.03.015 Darke, S. (1998). Self-report among injecting drug users: A review. Drug & Alcohol Dependence, 51(3), 253-263. doi:10.1016/S0376-8716(98)00028-3 Erowid. (2013). Spotlight on NBOMes: Potent Psychedelic Issues. Retrieved from https://www.erowid.org/chemicals/nbome/nbome_article1.shtml Erowid. (2015). DMT effects. Retrieved from https://www.erowid.org/chemicals/dmt/dmt_effects.shtml Erowid. (2016a). LSD effects. Retrieved from https://www.erowid.org/chemicals/lsd/lsd_effects.shtml Erowid. (2016b). Psilocybin Mushrooms effects. Retrieved from https://www.erowid.org/plants/mushrooms/mushrooms_effects.shtml European Monitoring Centre for Drugs and Drug Addiction. (2016a). EU Drug Markets Report. In-depth Analysis. Retrieved from Luxembourg: European Monitoring Centre for Drugs and Drug Addiction. (2016b). Health responses to new psychoactive substances. Retrieved from Luxembourg: Gunderson, E. W., Haughey, H. M., Ait-Daoud, N., Joshi, A. S., & Hart, C. L. (2014). A Survey of Synthetic Cannabinoid Consumption by Current Cannabis Users. Substance Abuse, 35(2), 184-189. doi:10.1080/08897077.2013.846288 IBM Corporation. (2013). IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corporation. 126

Johnston, L. D., O'Malley, P. M., Bachman, J. G., Schulenberg, J. E., & Miech, R. A. (2015). Monitoring the Future national survey results on drug use, 1975–2014: Volume 2, College students and adults ages 19–55. Retrieved from The University of Michigan: Lader, D. (2015). Drug Misuse: Findings from the 2014/15 Crime Survey for England and Wales. Retrieved from London: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attach ment_data/file/462885/drug-misuse-1415.pdf Lawn, W., Barratt, M., Williams, M., Horne, A., & Winstock, A. (2014). The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. Journal of Psychopharmacology, 28(8), 780-788. doi:10.1177/0269881114523866 Matthews, A., Sutherland, R., Peacock, A., Van Buskirk, J., Whittaker, E., Burns, L., & Bruno, R. (In Press). I like the old stuff better than the new stuff? Subjective experiences of new psychoactive substances. International Journal of Drug Policy. doi:10.1016/j.drugpo.2016.11.004 Measham, F., & Newcombe, R. (2016). What’s so new about new psychoactive substances? Definitions, prevalence, motivations, user groups and a proposed new taxonomy. In K. B. Thom & G. Hunt (Eds.), The SAGE Handbook of Drug & Alcohol Studies (Vol. 1). London: Sage. Moore, K., Dargan, P. I., Wood, D. M., & Measham, F. (2013). Do Novel Psychoactive Substances Displace Established Club Drugs, Supplement Them or Act as Drugs of Initiation? The relationship between Mephedrone, Ecstasy and Cocaine. European Addiction Research, 19(5), 276-282. Orsolini, L., Papanti, G. D., Francesconi, G., & Schifano, F. (2015). Mind Navigators of Chemicals' Experimenters? A Web-Based Description of E-Psychonauts. Cyberpsychology, Behavior, and Social Networking, 18(5), 296-300. doi:10.1089/cyber.2014.0486 Palamar, J. J. (2015). “Bath salt” use among a nationally representative sample of high school seniors in the United States. The American Journal on Addictions, 24(6), 488-491. doi:10.1111/ajad.12254 Palamar, J. J., & Acosta, P. (2015). Synthetic cannabinoid use in a nationally representative sample of US high school seniors. Drug and Alcohol Dependence, 149, 194-202. doi:http://dx.doi.org/10.1016/j.drugalcdep.2015.01.044 Reuter, P., & Pardo, B. (2017). Can new psychoactive substances be regulated effectively? An assessment of the British Psychoactive Substances Bill. Addiction, 112(1), 25-31. doi:10.1111/add.13439 Sindicich, N., & Burns, L. (2015). Australian Trends in Ecstasy and Related Drug Markets 2014. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Retrieved from Sydney: Soussan, C., & Kjellgren, A. (2015). “Chasing the high” – Experiences of ethylphenidate as described on international internet forums. Substance Abuse: Research and Treatment, 9, 9-16. doi:10.4137/SART.S22495 Soussan, C., & Kjellgren, A. (2016). The users of Novel Psychoactive Substances: Online survey about their characteristics, attitudes and motivations. International Journal of Drug Policy, 32, 77-84. doi:10.1016/j.drugpo.2016.03.007

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Sutherland, R., Peacock, A., Whittaker, E., Roxburgh, A., Lenton, S., Matthews, A., . . . Bruno, R. (2016). New psychoactive substance use among regular psychostimulant users in Australia, 2010–2015. Drug and Alcohol Dependence, 161, 110-118. doi:http://dx.doi.org/10.1016/j.drugalcdep.2016.01.024 Sutherland, R., Peacock, A., Roxburgh, A., Barratt, M. J., Burns, L., & Bruno, R. (2018). Typology of new psychoactive substance use among the general Australian population. Drug Alcohol Depend, 188, 126-134. doi:https://doi.org/10.1016/j.drugalcdep.2018.03.034 United Nations Office on Drugs and Crime. (2014). Global SMART Update. Special segment: The changing nature of "ecstasy". Retrieved from Vienna: https://www.unodc.org/documents/scientific/Global_SMART_Update_11_web.pdf van Amsterdam, J. G. C., Nabben, T., Keiman, D., Haanschoten, G., & Korf, D. (2015). Exploring the Attractiveness of New Psychoactive Substances (NPS) among Experienced Drug Users. Journal of Psychoactive Drugs, 47(3), 177-181. doi:10.1080/02791072.2015.1048840 Van Buskirk, J., Roxburgh, A., Bruno, R., & Burns, L. (2015). Drugs and the Internet, Issue 5. Sydney: National Drug and Alcohol Research Centre Vogels, N., Brunt, T. M., Rigter, S., Van Dijk, P., Vervaeke, H., & Niesink, R. J. M. (2009). Content of ecstasy in the Netherlands: 1993–2008. Addiction, 104(12), 2057-2066. doi:10.1111/j.1360-0443.2009.02707.x Wilkins, C., & Sweetsur, P. (2013). The impact of the prohibition of benzylpiperazine (BZP) ‘legal highs’ on the prevalence of BZP, new legal highs and other drug use in New Zealand. Drug and Alcohol Dependence, 127(1–3), 72-80. doi:http://dx.doi.org/10.1016/j.drugalcdep.2012.06.014 Winstock, A. R., & Barratt, M. J. (2013). Synthetic cannabis: A comparison of patterns of use and effect profile with natural cannabis in a large global sample. Drug and Alcohol Dependence, 131(1–2), 106-111. doi:http://dx.doi.org/10.1016/j.drugalcdep.2012.12.011 Winstock, A. R., Kaar, S., & Borschmann, R. (2014). Dimethyltryptamine (DMT): Prevalence, user characteristics and abuse liability in a large global sample. Journal of Psychopharmacology, 28(1), 49-54. doi:10.1177/0269881113513852 Winstock, A. R., Lawn, W., Deluca, P., & Borschmann, R. (2016). Methoxetamine: An early report on the motivations for use, effect profile and prevalence of use in a UK clubbing sample. Drug and Alcohol Review, 35(2), 212-217. doi:10.1111/dar.12259

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5. PAPER FOUR: NEW PSYCHOACTIVE SUBSTANCES: PURCHASING AND

SUPPLY PATTERNS IN AUSTRALIA

Rachel Sutherland1, Raimondo Bruno1,2, Amy Peacock1,2, Paul Dietze1,3, Courtney Breen1, Lucinda Burns1, Monica J. Barratt1,3,4

1National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia

2 School of Medicine (Psychology), Faculty of Health, University of Tasmania, Hobart, TAS, Australia

3 Burnet Institute, Centre for Population Health, Melbourne, Victoria, Australia

4National Drug Research Institute, Curtin University, Shenton Park, WA, Australia

Paper four has been published in Human Psychopharmacology: Clinical and Experimental (special issue) (Sutherland et al., 2017).

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5.1 Copyright statement

I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations.

Sutherland, R., Bruno, R., Peacock, A., Dietze, P., Breen, C., M., Burns, L. & Barratt, M.J. (2017). New psychoactive substances: Purchasing and supply patterns in Australia. Human Psychopharmacology, 32; 3.

Rachel Sutherland August, 2018

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5.2 Preamble

The preceding three papers have addressed the fundamental questions of: who uses NPS (and whether they differ to other illicit drug consumers); which NPS were being consumed (and if there were differences across NPS classes); and why people consume NPS. This final paper builds upon these by examining how NPS are being obtained. This question is of particular importance given the (often assumed) link between NPS and the internet.

Indeed, the rapid growth of the NPS market is often attributed to the expansion of online marketplaces, with NPS sometimes referred to as ‘internet drugs’. The expansion of these online drug markets have provided new opportunities for the supply and purchase of drugs, with internet sales of NPS now an international phenomenon and many online stores advertising worldwide delivery (European Monitoring Centre for Drugs and Drug Addiction, 2011). However, despite these increased opportunities to obtain and supply substances, it remains unclear to what extent Australian consumers are using the internet for this purpose. Paper four addresses this research gap by examining the purchasing and supply patterns of Australian NPS consumers. Recognising the heterogeneity of NPS consumers (illustrated in each of the preceding three papers), this paper will also determine if there are differences in purchasing and supply patterns across NPS consumers.

It should be noted that although this paper includes ‘shop’ as source for obtaining NPS, Australia started to introduce legislation prohibiting the use, sale and possession of NPS in 2011 (see Table 3 for further details). Thus, by the time of the 2016 EDRS (data on which the following paper is based), most NPS were illegal in Australia. However, despite this, there were still media reports of synthetic cannabinoids being readily available via retail outlets (e.g. Wordsworth, 2016) and hence it was of interest to determine whether participants were still obtaining NPS (in particular, SCRA) from retail outlets. Furthermore, whilst this paper includes questions on the supply of NPS, it is primarily focused on this at an individual level. It is beyond the scope of this paper to examine trafficking routes (including where the substance was originally manufactured), or the distribution of NPS via organised crime syndicates, and this is an area that requires further research.

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5.3 Abstract

Objective: To examine the purchasing and supply patterns of new psychoactive substance (NPS) consumers in Australia.

Method: Data were obtained from a self-selected sample of 296 past-year NPS consumers, with comparisons made across DMT (n=104), 2C-x (n=59), NBOMe (n=27) and synthetic cannabinoid (n=22) users.

Results: Most consumers (58%) nominated a friend as their main NPS source and almost half (46%) reported that they had supplied NPS to others in the past year (predominantly ‘social supply’). However, when comparisons were made across NPS, NBOMe users were more likely to nominate a dealer (30%) or online marketplace (22%) as their main source, and to report: supplying NPS to others (63%); supplying to strangers (29%) and acquaintances (24%); and supplying NPS for cash profit (29%).

Similarly, NPS consumers who nominated online markets as their main NPS source (9%; n=26) were more likely to have: supplied NPS to others (RR 1.57); supplied to strangers (RR 6.05) and acquaintances (RR 12.11); sold NPS for cash profit (RR 4.36); and to have exchanged NPS for something else (RR 3.27) than those who reported alternative primary sources.

Conclusion: NBOMe consumers and those who nominated online markets as their main NPS source reported greater engagement with for-profit supply; it’s unclear if these individuals have ‘drifted’ into dealing or if they were already engaged in such activities.

Keywords: New psychoactive substances; DMT; 2C-x; NBOMe; synthetic cannabinoids; online purchasing.

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5.4 Introduction

Over the past decade, the number and range of substances collectively referred to as ‘new psychoactive substances’ (NPS) has increased dramatically (European Monitoring Centre for Drugs and Drug Addiction, 2016b; EMCDDA). NPS are defined by the EMCDDA as substances which do not fall under international drug controls but which may pose a public health threat (European Monitoring Centre for Drugs and Drug Addiction, 2016b). However, there is no universally accepted way of determining whether individual substances are included within the NPS definition. ‘Older-new’ drugs, such as those currently controlled by international legislation but not previously well-established in the recreational drug-using scene (e.g. dimethyltryptamine; DMT), are also often included as NPS.

In 2015, the European Union were monitoring over 560 NPS, of which 70% were detected in the past five years (European Monitoring Centre for Drugs and Drug Addiction, 2016b). The rapid growth of the NPS market has been facilitated by a number of factors, one of which is the expansion of online marketplaces (European Monitoring Centre for Drugs and Drug Addiction, 2016a, 2016c). The first online drug transaction is reported to have occurred in 1971 (Buxton & Bingham, 2015), and over the past decade there has been an increasing awareness of, and interest in, surface web markets and cryptomarkets (Walsh, 2011). Surface web markets are accessible via typical search engines (e.g. Google, Yahoo), and cryptomarkets (also known as dark net markets) exist in a ‘hidden’ part of the internet not accessible through standard web browsers. Cryptomarkets host multiple sellers or vendors and have been facilitated by the development of encryption, digital currencies and anonymous browsing (Barratt & Aldridge, 2016a; Mounteney, Griffiths, & Vandam, 2016; Van Buskirk, Roxburgh, et al., 2016). The expansion of these online drug markets have provided new opportunities for the supply and purchase of drugs, with internet sales of NPS now an international phenomenon and many online stores advertising worldwide delivery (European Monitoring Centre for Drugs and Drug Addiction, 2011).

As surface web and cryptomarkets have grown, so too has the monitoring of such marketplaces. In 2011-2012, Bruno, Poesiat, and Matthews (2013) identified 43 unique surface web markets that were selling stimulant and psychedelic NPS to Australia, and there are currently over 20 cryptomarkets selling illicit drugs, including NPS (although not all vendors operating on these marketplaces sell to Australia; Barratt & Aldridge, 2016b; Van Buskirk, Naicker, et al., 2016). In December 2015, NPS were found to be the sixth most commonly sold substances on AlphaBay and Nucleus (the two largest cryptomarkets at that time); 2C-x, DMT and NBOMe were the most

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commonly sold substances within this category (Van Buskirk, Roxburgh, et al., 2016). Whilst the online availability of NPS largely corresponds with the main NPS used in Australia (Sindicich, Stafford, & Breen, 2016), there is little evidence regarding the relative importance of online markets as a source of supply for NPS consumers. Indeed, despite being readily available online, and despite the widely held perception that most NPS are purchased online, it appears that most Australian consumers do not source NPS in this manner. That is, despite findings that NPS users are more likely to purchase drugs online than other drug users (Burns et al., 2014; Van Buskirk, Roxburgh, et al., 2016), for the most part they appear to obtain these substances from ‘in- person’ sources such as friends and dealers (Burns et al., 2014; European Commission, 2014; Stephenson & Richardson, 2014), although this can vary across studies (for example, see Global Drug Survey, 2016; O'Brien, Chatwin, Jenkins, & Measham, 2015; Soussan & Kjellgren, 2016).

However, despite potential heterogeneity in the forms of NPS used, and in the primary sources for each NPS, many of these studies combine NPS into a single category for analysis. Studies examining individual types or categories of NPS suggest that differences may exist across consumers; for example, friends have been found to be the most common source for obtaining DMT (Australia; Cakic, Potkonyak, & Marshall, 2010) and mephedrone (Ireland; McElrath & O’Neill, 2011), whilst other studies have found that the internet was most common source for obtaining plant-derived NPS (Sweden; Björnstad, Hultén, Beck, & Helander, 2009) and NBOMe (international; Lawn, Barratt, Williams, Horne, & Winstock, 2014). In regards to synthetic cannabinoids, retail outlets have been found to be a common source for obtaining these substances (Barratt, Cakic, & Lenton, 2013; Gunderson, Haughey, Ait-Daoud, Joshi, & Hart, 2014). At present, it is unclear if such findings represent genuine differences across NPS, or if they are the result of different methodologies, geographic differences and/or other study artefacts.

In addition to the direct purchasing of NPS for personal use, the internet could play a significant role in social supply (i.e. the non-commercial or non-profit-making distribution of drugs to non- strangers; Hough et al., 2003), where one friend within a social group may purchase NPS online to provide to others within the group, either for free, at cost price, or for profit. There are some anecdotal reports of this taking place (Stephenson & Richardson, 2014), however, the overall extent to which this is happening remains unknown. Given that social supply is common among illicit drug users (Belackova & Vaccaro, 2013; Bernard & Werse, 2013; Fowler, Kinner, & Krenske, 2007; Lenton, Grigg, Scott, Barratt, & Eleftheriadis, 2015), it seems likely that this practice would extend to NPS and online marketplaces. Furthermore, little is known about the extent to which people are obtaining NPS from online sources for the purposes of dealing for cash profit. This is 134

of particular interest given that online drug marketplaces have reconfigured relationships among suppliers, intermediaries and buyers, with some evidence showing that individuals, couples and very loose networks are becoming key criminal actors in internet-facilitated drug trafficking (Lavorga, 2016).

In this paper we examined the supply and purchasing patterns of a sample of NPS consumers in Australia, with an emphasis on exploring online purchasing. Specifically, we aimed to:

1) Determine whether there were different purchasing and supply patterns across consumers of the most commonly used NPS, specifically DMT, 2C-x, NBOMe and synthetic cannabinoids; and 2) Examine whether purchasing and supply patterns differed across NPS consumers who nominated ‘online’ as their main NPS source compared to those who nominated an alternative main source.

5.5 Method

5.5.1 Study design

This paper uses data from the 2016 Ecstasy and related Drugs Reporting System (EDRS) (for full protocol details, see Sindicich et al., 2016). The EDRS is a national monitoring study aimed at detecting emerging trends in illicit drug markets which has been conducted annually within all Australian capital cities since 2003; one component involves cross-sectional surveys with ‘regular psychostimulant users’ (RPU). The EDRS received ethical approval from the University of New South Wales (UNSW) Human Research Ethics Committee (HC15015), as well as from the relevant ethics committees in other Australian jurisdictions.

5.5.2 Participants and procedure

EDRS survey participants are a self-selected sample of RPU recruited through street-press advertisements, online forums and peer referral. Eligibility criteria were: at least monthly use of ecstasy or other psychostimulants in the preceding six months, 16 years of age or older, and residence in the city of interview for at least 12 months prior to the interview. Face-to-face structured interviews of approximately one-hour duration were conducted by trained interviewers at a negotiated time and location, and participants were reimbursed AUD40 for their time and out-of-pocket expenses.

In 2016, 795 participants were recruited and interviewed for the EDRS. Analysis is based on a subset of participants who reported past year use of NPS (n=296; Table 28).

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5.5.3 Measures relevant to the current study

In addition to demographic questions (i.e., age, gender, sexual orientation, employment and educational status), participants were asked about their lifetime and past six-month use of licit and illicit substances. Participants who had used any NPS in the past year were asked to nominate the NPS used most often in that time frame and were then asked a series of questions in relation to use of that particular substance, including: how they obtained the substance (bought it/given for free/exchange; multiple responses allowed); typical and largest transaction sizes; the main source from whom they obtained this substance (friend/ dealer/workmate/acquaintance/relative/online/other) and whether they obtained any other drugs from this source (including both ‘traditional’ illicit drugs, as well as other NPS); whether they had supplied NPS to others in the past 12 months; who they supplied NPS to; and the method of supply (gave away for free/shared/provided at cost price/provided for cash profit/exchanged; multiple responses allowed).

5.5.4 Statistical analysis

To address the first aim, purchasing and supply patterns were compared across the most commonly used NPS, namely DMT (n=104), the 2C-family substances (2C-x; n=59), NBOMe (n=27) and synthetic cannabinoids (n=22). Between-group comparisons of categorical variables were analysed using chi-squared tests (χ2), and adjusted residuals were used to analyse which cell differences contributed to the overall χ2 results. An adjusted residual score of greater than 2.0 or below -2.0 indicated that the cells differed significantly.

To address the second research aim, the sample was divided into two groups based on whether participants nominated ‘online’ as their main source for obtaining their most frequently used NPS in the past year or whether they nominated a ‘non-online’ source. Between-group comparisons of categorical variables were analysed using risk ratios (RR) with 95% confidence intervals reported.

For normally distributed continuous variables, t-tests were employed and means with their standard deviations (SD) reported. Where continuous variables were skewed (i.e. skewness > ± 1 or kurtosis > ± 3) Mann–Whitney U-tests were conducted, with medians and the corresponding interquartile ranges (IQR) reported. All analyses were conducted using IBM SPSS Statistics for Windows release 22.0 (IBM Corporation, 2013).

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5.6 Results

5.6.1 Sample characteristics

The sample (n=296) had a median age of 21 years (IQR 19-24); 71% of participants were male, 97% were of English speaking background, 45% were tertiary qualified, 73% were employed in some capacity, 36% were students, 12% were unemployed and 2% were currently in drug treatment. Almost all (98%) participants reported recent (past six month) use of ecstasy, 42% reported recent methamphetamine use, 51% reported recent cocaine use, 66% reported recent LSD use and 92% reported recent cannabis use. Forty-six percent of participants reported using ecstasy or related drugs on a weekly or greater basis in the past month. The most commonly used NPS within the preceding six months were DMT (38%), 2C-B (24%), synthetic cannabinoids (11%) and NBOMe (10%), although frequency of use for each of these drugs was low (range: 1- 3 days).

5.6.2 Differences in purchasing patterns across NPS consumers

Three-fifths (61%) of all NPS consumers reported that they had purchased NPS in the past year. This was significantly higher among participants who nominated NBOMe as the main NPS used in the past year (89%), compared to those to nominated DMT (53%), 2C-x (61%) and synthetic cannabis (52%) as the main NPS used (p=0.007; Table 28). Almost half (46%) of consumers reported being given NPS for free and a small minority (7%) reported that they had received the substance in exchange for something else (e.g. other drugs), with no differences found across substances.

Most consumers (58%) nominated a friend as their main source for obtaining NPS in the past year. However, when comparisons were made across DMT, 2C-x, NBOMe and synthetic cannabinoid users it was found that NBOMe users were more likely to nominate a dealer (30%; p=0.045) or online marketplace (22%; p=0.010) as their main source, while synthetic cannabinoid users were more likely to nominate a shop (44%; p<0.001) as their main source. Over half (57%) of all NPS consumers reported that they had obtained other drugs from their main NPS source, with 2C-x consumers (71%) being more likely to have done so (p=0.029). Typical and largest transaction sizes were the same across all four NPS (hence only typical transaction sizes have been presented) and were relatively small for all substances.

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5.6.3 Differences in supply patterns across NPS consumers

Almost half (46%) of all NPS consumers reported that they had supplied NPS to other people in the past 12 months, with NBOMe (63%) and DMT (52%) consumers being more likely to have done so and 2C-x users (22%) being less likely (p=0.001; Table 28). Among those who had supplied to others, most reported that they had provided NPS to friends (96%), typically sharing them (56%) or giving away them for free (45%). However, NBOMe consumers were less likely to have supplied NPS to friends (82%; p=0.022) and to have shared with others (29%; p=0.032), and were more likely to have supplied to strangers (29%; p<0.001) and acquaintances (24%; p=0.003). They were also more likely to have sold NPS for cash profit (29%; p=0.051).

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Table 28: Purchasing and supply patterns across past year NPS consumers, 2016 Main NPS used in past year Past year NPS DMT (n=104) 2C-x (n=59) NBOMe (n=27) Synthetic p value consumers* % (adjusted % (adjusted % (adjusted cannabis (n=23) n=296 % residuals) residuals) residuals) % (adjusted residuals) In the past year How obtained substance# % Bought it 61.1 52.9 (-1.9) 61.0 (0.2) 88.9 (3.3) 52.2 (-0.8) 0.007 Given for free 46.2 56.9 47.5 37.0 47.8 0.274 Exchanged for something other than cash 7.2 6.9 0 11.1 4.3 0.125 Median typical transaction size Caps (IQR; n) 2 (1-2.5;29) - 1 (1-3; 19) - - - Pills (IQR; n) 2 (1-4;30) - 1 (1-2; 12) - - - Grams (IQR; n) 1 (0.29-3; 126) 1 (0.20-1; 62) 0.2 (0.1-1.25;10) - 3 (1-3.75; 16) - Tabs (IQR; n) 2 (1-10; 31) - - 3 (1-8.75; 24) - - Main source % Friend 57.5 66.7 69.5 48.1 52.2 0.146 Acquaintance 4.4 5.9 5.1 0 4.3 0.645 Dealer 17.0 17.6 (0.4) 15.3 (-0.3) 29.6 (2.0) 0 (-2.3) 0.045 Online## 8.8 4.9 (-1.4) 8.5 (0.3) 22.2 (3.1) 0 (-1.5) 0.010 Shop 8.8 0 (-2.0) 0 (-3.1) 0 (-1.2) 43.5 (9.3) <0.001 Other^ 3.4 - - - - - Source provided you with other drugs % 56.5 51.5 (-1.3) 71.2 (2.7) 55.6 (-0.1) 39.1 (-1.7) 0.029 Supplied NPS to others % 46.4 51.5 (2.2) 22.4 (-3.8) 63.0 (2.2) 39.1 (-0.5) 0.001 Who supplied NPS to#** % n=135 n=52 n=13 n=17 n=9^^ Friends 96.3 98.1 (1.6) 100 (0.9) 82.4 (-2.7) 0.022 Relatives 5.2 7.7 0 0 0.297 Acquaintances 6.7 1.9 (-2.1) 0 (-1.0) 23.5 (3.4) 0.003 Strangers 5.9 1.9 (-2.5) 0 (-1.1) 29.4 (3.9) <0.001

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Table 28 (continued): Purchasing and supply patterns across past year NPS consumers, 2016 Main NPS used in past year Past year NPS DMT (n=104) 2C-x (n=59) NBOMe (n=27) Synthetic p value consumers* % (adjusted % (adjusted % (adjusted cannabis (n=23) n=296 % residuals) residuals) residuals) % (adjusted residuals) Method of supply#** % Gave away for free 44.8 48.1 46.2 52.9 0.921 Shared 56.0 65.4 (1.9) 61.5 (0.3) 29.4 (-2.6) 0.032 Provided at cost price 22.4 17.3 23.1 35.3 0.297 Provided for cash profit 14.2 7.7 7.7 29.4 0.051 Exchanged 12.7 11.5 0 17.6 0.302 *Includes DMT (n=104); 2C-x (n=59); NBOMe (n=27); synthetic cannabis (n=23); herbal highs (n=18); MXE (n=16); methylone (n=9); mephedrone (n=5); PMA (n=7); salvia divinorum (n=5); etizolam (n=5); mescaline (n=4); 5-Meo-DMT (n=2); LSA (n=1); datura (n=1); 3-MeO-PCP (n=1); 5-MAPB (n=1); ayahuasca (n=1); changa (n=1); kava (n=1); 5- Meo-MIPT (n=1); NBOH (n=1); phenibut (n=1); unknown (n=2) #Multiple responses allowed, hence sum of percentages may exceed 100% ^Includes workmates (1%); relatives (0.7%); home-made/grown (1.7%); ^^Excluded from subsequent analysis, due to small numbers (n<10) ##Includes cryptomarkets (n=23) and surface web marketplaces (n=3); association remains significant even when surface web marketplaces are excluded from analysis **Among those who had supplied NPS to others in the past year. Note: significant findings bolded. Adjusted residuals only reported when p<0.05

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5.6.4 Main source for obtaining NPS: Online vs non-online

Nine percent of NPS consumers nominated online marketplaces as their main source for obtaining these substances in the past year. This mostly consisted of ‘cryptomarkets’ (n=23), with a minority nominating ‘surface web markets’ (n=3) as their main source.

Participants who nominated an online marketplace as their main source for obtaining NPS had obtained a larger number of drugs from this source (median 5 vs 2; p<0.001) and were subsequently more likely to have obtained other drugs from this source (RR 1.57 95% CI: 1.29- 1.92), when compared to participants who nominated an alternative main source (Table 29). All participants who nominated an online marketplace as their main NPS source and who had obtained other drugs online reported that they had purchased ‘traditional’ illicit drugs (mainly ecstasy, LSD, benzodiazepines and cannabis) from this source, and 55% reported that they had obtained another NPS. NPS consumers who nominated ‘online’ as their main source were also more likely to have supplied NPS to others in the past year (RR 1.57 95% CI: 1.35-2.27), and were more likely to have supplied to strangers (RR 6.05 95% CI: 1.65-22.17) and acquaintances (RR 12.11 95% CI: 3.31-44.34). Furthermore, they were more likely to have sold NPS for cash profit (RR 4.36 95% CI: 2.02-9.43) and to have exchanged it for something else (RR 3.27 95% CI: 1.37- 7.80). There were no significant differences in terms of typical NPS transaction sizes for pills, caps and grams. For ‘tabs’ of blotter paper the median typical transaction size among participants who nominated ‘online’ as their main source was 30 tabs compared to one tab for those who nominated an alternative main source (p=0.017).

These associations remained significant even when participants who nominated the ‘surface web’ as their main source for obtaining NPS were excluded from analyses.

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Table 29: Purchasing and supply patterns among past year NPS consumers who nominated online marketplaces as their main source, 2016 Main source for obtaining NPS in past year RR (95% CI)/U^ p value Online* Not online n=26 n=268 In the past year Median number of drugs 5 (26; 2-7.25) 2 (268; 1-3) 1532.5 <0.001 obtained from source (n; IQR) Median typical transaction size Pills (n; IQR) 10 (3; -) 2 (27; 1-3) 14.5 0.072 Caps (n; IQR) 1 (1; -) 2 (28; 1-2.75) 6.5 0.483 Grams (n; IQR) 1 (13; 0.5-2) 1 (112; 0.25-3) 721 0.954 Tabs (n; IQR) 30 (6; 2-3300) 1 (25; 1-4.5) 28.5 0.017 Obtained other drugs 84.6 53.8 1.57 (1.29-1.92) 0.002 from source % Type of drug obtained N=22 N=143 from source % Traditional 100 99.3 1.01 (0.99-1.02) 0.694 NPS 54.5 13.3 4.11 (2.33-7.23) <0.001 Supplied NPS to others % 76.0 43.4 1.75 (1.35-2.27) 0.002 Who supplied NPS to** N=19 N=115 % Friends 94.7 96.5 0.98 (0.88-1.10) 0.704 Relatives 15.8 3.5 4.54 (1.10-18.71) 0.025# Acquaintances 31.6 2.6 12.11 (3.31-44.34) <0.001 Strangers 21.1 3.5 6.05 (1.65-22.17) 0.003 Method of supply** % Gave away for free 63.2 42.1 1.50 (1.00-2.25) 0.088 Shared 68.4 53.5 1.28 (0.90-1.82) 0.226 Provided at cost price 21.1 22.8 0.92 (0.36-2.35) 0.865 Provided for cash profit 42.1 9.6 4.36 (2.02-9.43) <0.001 Exchanged 31.6 9.6 3.27 (1.37-7.80) 0.008 *Includes cryptomarkets (n=23) and surface web marketplaces (n=3). Associations remain significant even when surface web marketplaces are excluded from analyses (except for ‘supplying to relatives’ which loses significance) ^Risk ratios (RR) and 95% confidence intervals (95% CI) are reported for chi-square analyses; results of the Mann-Whitney U test (U) are reported for the comparison of medians **Among those who had supplied NPS to others in the past year; multiple responses allowed, hence sum of percentages may exceed 100% #This association loses significance when ‘surface web’ marketplaces are excluded from analysis Note: significant findings bolded

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5.7 Discussion

We found significant differences in purchasing and supply patterns across NPS consumers. Overall, friends were nominated as the main source for obtaining these substances; however, analysis of DMT, 2C-x, NBOMe and synthetic cannabinoids consumers showed that NBOMe users were more likely to nominate a dealer or online marketplace as their main source, whilst synthetic cannabinoid users were more likely to nominate a shop as their main source. These findings are relatively consistent with previous research (Barratt et al., 2013; Gunderson et al., 2014; Lawn et al., 2014), as well as with media reports suggesting that synthetic cannabinoids remain readily available via retail outlets (despite being largely prohibited across Australia e.g. Wordsworth, 2016).

It is unclear why NBOMe is more likely than DMT, 2C-x and synthetic cannabinoids to be purchased online, however consumer preference, availability and price are likely to all play a role. In relation to consumer preference, a study comparing the subjective experiences of NPS relative to their traditional illicit drug counterparts found that 2C-B and 2C-I were rated less favourably than LSD in terms of pleasurable effects and likelihood of taking again (Matthews et al., 2017), and a study of dual cannabis and synthetic cannabis users found a strong preference for natural cannabis over synthetic cannabis (Winstock & Barratt, 2013). In contrast, NBOMe has been found to have a very similar profile of subjective effects when compared to other hallucinogens (i.e. LSD, magic mushrooms and ketamine; Lawn et al., 2014). Given that consumers are presented with a smorgasbord of substances (and vendors) when purchasing online, it seems unlikely that they would purchase substances (e.g. 2C-x, synthetic cannabinoids) that are generally considered inferior to established illicit drugs, with psychonauts (a minority group interested in trying a wide variety of drugs; Ott, 2001) being the exception. In contrast, those purchasing from a retail outlet, friend or dealer are limited by what is available at that time and thus may be more prone to ‘opportunistic’ purchases. Indeed, a recent study found that availability (i.e. no other drug available at the time) and legality were the most highly endorsed motivations for synthetic cannabinoids use among RPU in Australia (Sutherland et al., In Press), providing some support for this theory of opportunistic purchasing.

Another factor to consider is price. Cheaper prices is reportedly one of the most common reasons for purchasing drugs online (Barratt, Ferris, & Winstock, 2014; Van Buskirk, Roxburgh, et al., 2016), although it is unclear if this varies across substances, with very few studies explicitly examining this topic. Interestingly, one of the only published studies to compare the mean prices of drugs bought online versus offline found that online prices were higher than offline prices for

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ecstasy tablets, amphetamine powders, cocaine powders, LSD, 4-FA powders and 5/6-APB powders, with no significant differences in prices for 2C-B tablets, 2C-B powders and methoxetamine powders (van der Gouwe, Brunt, van Laar, & van der Pol, 2016). However, this study was based in the Netherlands and as such these findings are probably not transferrable to the Australian context, with prices on the Dutch drug market relatively low compared to Australia (van der Gouwe et al., 2016). In addition, NBOMe, methylone and mephedrone were excluded due to small online samples, and there is a need for further research on this topic.

Alternatively, the low prices of online drugs could be attributed to bulk offers (Aldridge & Décary-Hétu, 2014), which would partially explain our finding regarding the increased likelihood of purchasing NBOMe online. More specifically, we found no significant differences in terms of typical transaction sizes for pills, caps and grams among those who nominated ‘online’ as their main NPS source and those who nominated an alternative main source. However, for tabs of blotter paper, the median typical transaction size was 30 among participants who nominated ‘online’ as their main NPS source - compared to one tab for those who nominated an alternative main source. The purchase of ‘tabs’ online was exclusively NBOMe, suggesting that those who purchase NBOMe online are more likely to buy in larger quantities due to potential discounts. For example, one participant reported purchasing 12,000 NBOMe tabs for AUD 2500, which equates to approximately 21 cents per tab. In contrast, participants who bought a single tab of NBOMe from friends and/or dealers reported paying a median of AUD 20 (range AUD 10-30 per tab).

In regards to the provision of NPS, we found that almost half of all NPS consumers had supplied these substances to others in the preceding 12 months, with NBOMe and DMT consumers being significantly more likely to have done so. Social supply was by far the most common form of supply, with most participants reporting that they had supplied to friends for no cash profit (i.e. shared, given away for free or provided at cost price). Indeed, mutual supply networks appear to be common among NPS consumers, with many individuals both sourcing from and supplying to friends. This is consistent with previous research showing that individuals within friendship groups source drugs from, and concurrently supply to, group members to ensure a consistent supply of quality product and to minimise risks of health harms and criminal justice consequences (Bright & Sutherland, Under Review; Lenton et al., 2015; Nicholas, 2008).

Although social supply was the most common form of supply reported by participants, NBOMe consumers, and those who nominated online markets as their main NPS source, were more likely to report supplying NPS to strangers and acquaintances and for cash profit. It is unclear if

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this represents a ‘drift’ into dealing for cash profit (whereby users gradually become dealers; Taylor & Potter, 2013), or if it is representative of existing dealers taking advantage of new business opportunities. As mentioned previously, ‘cheaper prices’ is one of the main reasons for sourcing drugs online, particularly amongst Australian consumers (Barratt et al., 2014; Van Buskirk, Roxburgh, et al., 2016), and it seems feasible that the potential for high profit margins could attract existing dealers and also facilitate a drift into dealing for cash profit among those who were initially purchasing for personal use and/or social supply (e.g. "My time as a scumbag NBOMe dealer," 2015). Indeed, although the typical transaction size for NBOMe was relatively small in the current study (median of three tabs), there were some individuals buying in much higher quantities.

Furthermore, it is unknown if those supplying NBOMe to others (for profit or otherwise) are supplying it at face value or as an alternative substance (i.e. LSD). When deposited on blotter paper LSD and NBOMe are virtually identical in appearance and, given the health risks associated with unwittingly ingesting NBOMe (e.g. increased risk of overdose), concerns have been raised about the possibility of NBOMe being sold as LSD (Caldicott, Bright, & Barratt, 2013; Isbister, Poklis, Poklis, & Grice, 2015). This practice has been verified in some European countries (Busardò, Pichini, Pacifici, & Karch, 2016; Giné, Espinosa, & Vilamala, 2014; "Welsh emerging drugs and identification of novel substance project," 2016), however it is still unknown to what extent this practice occurs in Australia, with further research required.

5.7.1 Limitations

Our analysis is reliant upon self-report data from participants which may be subject to bias. Although evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use (Darke, 1998), it is possible that participants may have: 1) under-reported purchasing and supply patterns and; 2) incorrectly identified the NPS being consumed (i.e. it may have been sold to them as one thing but have been something else). The latter is particularly pertinent in relation to LSD and NBOMe and future studies should corroborate self-report with chemical analysis. Additionally, the EDRS sample is not representative of all RPU consumers in Australia, although an assessment of the EDRS data in NSW did find that it had high generalisability to population estimates (Topp, Barker, & Degenhardt, 2004). Similarly, the EDRS sample is not representative of all NPS users, with supply and purchasing patterns likely to be quite different among certain subpopulations (e.g. NPS consumers who are homeless or incarcerated). In regard to supplying NPS for ‘cash profit’ it is unknown how much profit was actually made, and it is possible that this included ‘minimally commercial supply’ (Coomber &

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Moyle, 2014), whereby small financial gain is made but is not the primary driver of drug supply. It is should also be noted that it is beyond the scope of this paper to examine the distribution of NPS via organised crime syndicates and this is an area that requires further research. Furthermore, our findings relate to the main NPS used in the past year and the main source for obtaining this substance; it is important to note that some participants had used multiple NPS in the past year and would have likely obtained these substances through multiple sources. Finally, some of our findings are based on relatively small sample sizes, meaning that caution must be exercised when interpreting null results.

5.8 Conclusion

The recent proliferation of NPS, combined with their global distribution through the internet and other sources, raises important questions about how consumers and dealers engage with the market for these drugs. Our study found that most NPS consumers continue to source these substances from ‘in-person’ sources such as friends and dealers, although this varied across substances. Social supply and mutual supply networks were common, with many participants both sourcing from and supplying to friends.

Overall, nine percent of past year NPS consumers nominated online marketplaces as their main NPS source, with this being significantly higher among NBOMe consumers (22%). Participants who nominated online marketplaces as their main source for obtaining NPS were found to have different purchasing and supply patterns to those who nominated an alternative main source, with larger purchase quantities noted and an increased likelihood of NPS supply to strangers and acquaintances and for cash profit. It is unclear if this is indicative of a ‘drift’ into dealing for profit or if existing dealers are attracted to online marketplaces due to factors such as cheaper prices, all of which requires further research.

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5.9 References

Aldridge, J., & Décary-Hétu, D. (2014). Not an 'Ebay for Drugs': The Cryptomarket 'Silk Road' as a Paradigm Shifting Criminal Innovation. SSRN. doi:http://dx.doi.org/10.2139/ssrn.2436643 Barratt, M. J., & Aldridge, J. (2016a). Everything you always wanted to know about drug cryptomarkets* (*but were afraid to ask). International Journal of Drug Policy, 35, 1-6. doi:10.1016/j.drugpo.2016.07.005 Barratt, M. J., & Aldridge, J. (2016b, 2 September 2016). Explainer: what are drug cryptomarkets? The Conversation. Retrieved from https://theconversation.com/explainer- what-are-drug-cryptomarkets-64596 (Archived by WebCite® at http://www.webcitation.org/6lDZ1V4Gl) Barratt, M. J., Cakic, V., & Lenton, S. (2013). Patterns of synthetic cannabinoid use in Australia. Drug and Alcohol Review, 32(2), 141-146. doi:10.1111/j.1465-3362.2012.00519.x Barratt, M. J., Ferris, J. A., & Winstock, A. R. (2014). Use of Silk Road, the online drug marketplace, in the United Kingdom, Australia and the United States. Addiction, 109(5), 774- 783. doi:10.1111/add.12470 Belackova, V., & Vaccaro, C. A. (2013). “A Friend With Weed Is a Friend Indeed”: Understanding the Relationship Between Friendship Identity and Market Relations Among Marijuana Users. Journal of Drug Issues. doi:10.1177/0022042613475589 Bernard, C., & Werse, B. (2013). The other side of dealing drugs: Supporting personal use and social supply: Preliminary findings of a quantitative-qualitative study on socially inconspicuous drug users and dealers. Monatsschrift fur Kriminologie und Strafrechtsreform, 96(6), 447-460. Björnstad, K., Hultén, P., Beck, O., & Helander, A. (2009). Bioanalytical and clinical evaluation of 103 suspected cases of intoxications with psychoactive plant materials. Clinical Toxicology, 47(6), 566-572. doi:10.1080/15563650903037181 Bright, D., & Sutherland, R. (Under Review). "Just doing a favor for a friend": The social supply of ecstasy through friendship networks. Journal of Drug Issues. Bruno, R., Poesiat, R., & Matthews, A. J. (2013). Monitoring the Internet for emerging psychoactive substances available to Australia. Drug and Alcohol Review, 32(5), 541-544. doi:10.1111/dar.12049 Burns, L., Roxburgh, A., Matthews, A., Bruno, R., Lenton, S., & Van Buskirk, J. (2014). The rise of new psychoactive substance use in Australia. Drug Testing and Analysis, 6(7-8), 846-849. doi:10.1002/dta.1626 Busardò, F. P., Pichini, S., Pacifici, R., & Karch, S. B. (2016). The Never-Ending Public Health Issue of Adulterants in Abused Drugs. Journal of Analytical Toxicology, 40(7), 561-562. doi:10.1093/jat/bkw051 Buxton, J., & Bingham, T. (2015). The rise and challenge of dark net drug markets Policy Brief 7. Swansea University: Global Drug Policy Observatory. Cakic, V., Potkonyak, J., & Marshall, A. (2010). Dimethyltryptamine (DMT): Subjective effects and patterns of use among Australian recreational users. Drug and Alcohol Dependence, 111(1–2), 30-37. doi:http://dx.doi.org/10.1016/j.drugalcdep.2010.03.015 Caldicott, D., Bright, S., & Barratt, M. (2013). NBOMe - a very different kettle of fish. The Medical Journal of Australia, 199(5), 322-323.

147

Coomber, R., & Moyle, L. (2014). Beyond drug dealing: Developing and extending the concept of 'social supply' of illicit drugs to 'minimally commercial supply'. Drugs: Education, Prevention and Policy, 21(2), 157-164. doi:10.3109/09687637.2013.798265 Darke, S., 1998. Self report among injecting drug users: A review. Drug & Alcohol Dependence. 51 (3), 253-263. European Commission. (2014). Young people and drugs. Flash Eurobarometer 401. Retrieved from http://ec.europa.eu/public_opinion/flash/fl_401_en.pdf European Monitoring Centre for Drugs and Drug Addiction. (2011). Online sales of new psychoactive substances/'legal highs': Summary of results from the 2011 multilingual snapshots. Luxembourg: Publications Office of the European Union. European Monitoring Centre for Drugs and Drug Addiction. (2016a). EU Drug Markets Report. In-depth Analysis. Luxembourg: Publications Office of the European Union. European Monitoring Centre for Drugs and Drug Addiction. (2016b). Health responses to new psychoactive substances. Luxembourg: Publications Office of the European Union. European Monitoring Centre for Drugs and Drug Addiction. (2016c). The internet and drug markets. Luxembourg: Publications Office of the European Union. Fowler, G., Kinner, S., & Krenske, L. (2007). Containing ecstasy: analytical tools for profiling an illegal drug market Monograph Series No. 27. Hobart: National Drug Law Enforcement Research Fund. Giné, C. V., Espinosa, I. F., & Vilamala, M. V. (2014). New psychoactive substances as adulterants of controlled drugs. A worrying phenomenon? Drug Testing and Analysis, 6(7-8), 819-824. doi:10.1002/dta.1610 Global Drug Survey. (2016). The global drug survey 2016 findings. Retrieved from https://www.globaldrugsurvey.com/past-findings/the-global-drug-survey-2016-findings/ (Archived by WebCite® at http://www.webcitation.org/6lL5SyusW) Gunderson, E. W., Haughey, H. M., Ait-Daoud, N., Joshi, A. S., & Hart, C. L. (2014). A Survey of Synthetic Cannabinoid Consumption by Current Cannabis Users. Substance Abuse, 35(2), 184- 189. doi:10.1080/08897077.2013.846288 Hough, M., Warburton, H., Few, B., May, T., Man, L.-H., Witton, J., & Turnbull, P. J. (2003). A Growing Market: The Domestic Cultivation of Marijuana. York: Joseph Rowntree Foundation. Hughes, C. (2012). 'Trafficking'or 'personal use': Do regular drug users understand Australian drug trafficking laws? Paper presented at the Australasian Professional Society on Alcohol and other Drugs conference, Melbourne, Australia. IBM Corporation. (2013). IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corporation. Isbister, K. I., Poklis, A., Poklis, J. L., & Grice, J. (2015). Beware of blotting paper hallucinogens: severe toxicity with NBOMes. The Medical Journal of Australia, 203(6), 266-267. Lavorga, A. (2016). How the use of the internet is affecting drug trafficking practices The internet and drug markets (pp. 85-90). Luxembourg: Publications Office of the European Union. Lawn, W., Barratt, M., Williams, M., Horne, A., & Winstock, A. (2014). The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. Journal of Psychopharmacology, 28(8), 780-788. doi:10.1177/0269881114523866

148

Lenton, S., Grigg, J., Scott, J., Barratt, M., & Eleftheriadis, D. (2015). The social supply of cannabis among young people in Australia. Trends and Issues in Crime and Criminal Justice(503). Matthews, A., Sutherland, R., Peacock, A., Van Buskirk, J., Whittaker, E., Burns, L., & Bruno, R. (2017). I like the old stuff better than the new stuff? Subjective experiences of new psychoactive substances. International Journal of Drug Policy, 40, 44-49. doi:10.1016/j.drugpo.2016.11.004 McElrath, K., & O’Neill, C. (2011). Experiences with mephedrone pre- and post-legislative controls: Perceptions of safety and sources of supply. International Journal of Drug Policy, 22(2), 120-127. doi:http://dx.doi.org/10.1016/j.drugpo.2010.11.001 Mounteney, J., Griffiths, P., & Vandam, L. (2016). What is the future for internet drug markets? The internet and drug markets (pp. 127-133). Luxembourg: Publications Office of the European Union. Moyle, L., Coomber, R., & Lowther, J. (2013). Crushing a Walnut With a Sledge Hammer? Analysing the Penal Response to the Social Supply of Illicit Drugs. Social and Legal Studies, 22(4), 553-573. doi:10.1177/0964663913487544 My time as a scumbag NBOMe dealer. (2015). Retrieved from https://www.reddit.com/r/Drugs/comments/3iszs8/my_time_as_a_scumbag_nbome_dealer_ part_1/ (Archived by WebCite® at http://www.webcitation.org/6lDXcwpqh) Nicholas, R. (2008). The impact of social networks and not-for-profit illicit drug dealing on illicit drug markets in Australia. Hobart: National Drug Law Enforcement Research Fund. O'Brien, K., Chatwin, C., Jenkins, C., & Measham, F. (2015). New psychoactive substances and British drug policy: A view from the cyber-psychonauts. Drugs: Education, Prevention and Policy, 22(3), 217-223. doi:10.3109/09687637.2014.989959 Ott, J. (2001). Pharmañopo—Psychonautics: Human Intranasal, Sublingual, Intrarectal, Pulmonary and Oral Pharmacology of Bufotenine. Journal of Psychoactive Drugs, 33(3), 273-281. doi:10.1080/02791072.2001.10400574 Sindicich, N., & Burns, L. (2013). Australian Trends in Ecstasy and related Drug Markets 2011. Findings from the Ecstasy and Related Drugs Reporting System (EDRS) Australian Drug Trend Series No. 100. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Stafford, J., & Breen, C. (2016). Australian Trends in Ecstasy and Related Drug Markets 2015. Findings from the Ecstasy and Related Drugs Reporting System (EDRS) Australian Drug Trend Series No. 154. . Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Soussan, C., & Kjellgren, A. (2016). The users of Novel Psychoactive Substances: Online survey about their characteristics, attitudes and motivations. International Journal of Drug Policy, 32, 77-84. doi:http://dx.doi.org/10.1016/j.drugpo.2016.03.007 Stephenson, G., & Richardson, A. (2014). New psychoactive substances in England. A review of the evidence. Crime and Policing Analysis Unit: Home Office Science. Sutherland, R., Bruno, R., Peacock, A., Lenton, S., Matthews, A., Salom, C., . . . Barratt, M. (In Press). Motivations for New Psychoactive Substance Use among Regular Psychostimulant Users in Australia. International Journal of Drug Policy. Taylor, M., & Potter, G. R. (2013). From “Social Supply” to “Real Dealing”: Drift, Friendship, and Trust in Drug-Dealing Careers. Journal of Drug Issues, 43(4), 392-406. doi:10.1177/0022042612474974

149

Topp, L., Barker, B., & Degenhardt, L. (2004). The external validity of results derived from ecstasy users recruited using purposive sampling strategies. Drug and Alcohol Dependence, 73(1), 33- 40. doi:http://dx.doi.org/10.1016/j.drugalcdep.2003.09.001 Van Buskirk, J., Naicker, S., Bruno, R., Burns, L., Breen, C., & Roxburgh, A. (2016). Drugs and the Internet. Issue 6. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Van Buskirk, J., Roxburgh, A., Bruno, R., Naicker, S., Lenton, S., Sutherland, R., . . . Burns, L. (2016). Characterising dark net marketplace purchasers in a sample of regular psychostimulant users. International Journal of Drug Policy, 35, 32-37. doi:http://dx.doi.org/10.1016/j.drugpo.2016.01.010 van der Gouwe, D., Brunt, T. M., van Laar, M., & van der Pol, P. (2016). Purity, adulteration and price of drugs bought online versus offline in the Netherlands. Addiction, n/a-n/a. doi:10.1111/add.13720 Walsh, C. (2011). Drugs, the Internet and Change. Journal of Psychoactive Drugs, 43(1), 55-63. doi:10.1080/02791072.2011.566501 Welsh emerging drugs and identification of novel substance project. (2016). Retrieved from http://www.wedinos.org/db/samples/ (Archived by WebCite® at http://www.webcitation.org/6lDYih43w) Winstock, A. R., & Barratt, M. J. (2013). Synthetic cannabis: A comparison of patterns of use and effect profile with natural cannabis in a large global sample. Drug and Alcohol Dependence, 131(1–2), 106-111. doi:http://dx.doi.org/10.1016/j.drugalcdep.2012.12.011 Wordsworth, M. (2016). Deadly and illegal synthetic drugs still available over the shop counter. Australian Broadcasting Corporation. Retrieved from http://www.abc.net.au/7.30/content/2015/s4407972.htm (Archived by WebCite® at http://www.webcitation.org/6lJj8mNJi)

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6. DISCUSSION

This thesis consists of four papers, all of which contribute to providing a detailed and coherent picture of NPS use in Australia. Specifically, the papers examine: which NPS are consumed, the characteristics of people who use NPS, the intersection between NPS and established illicit drugs, the motivations for using NPS, and the purchasing and supply patterns associated with NPS. Detailed information regarding the NPS market in Australia is relatively scarce and these papers address an important research gap. The findings are of major clinical and public health interest and offer guidance for the targeting of clinical and harm reduction messages. It should be noted that since the papers in this thesis focus on people who are already using NPS, the implications are mainly relevant to harm reduction and treatment, rather than prevention.

The aims of this chapter are to briefly summarise the findings of the chapters comprising of empirical studies (Table 30), to detail the contributions this thesis makes to the literature and to discuss the implications in terms of the main themes of the thesis. The themes were as follows: 1) the nature of the Australian NPS market and predicting the longevity of substances; 2) the heterogeneity of NPS consumers, and the intersection with the illicit drug market; 3) NPS in the context of polysubstance use and high-risk behaviours; and 4) NPS, the internet, and social supply. Strengths and limitations of the thesis are discussed and recommendations for future research detailed.

6.1 Key findings

The key findings of this thesis are presented in Table 30.

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Table 30: Summary of key findings Research question Paper Findings Conclusion General population sample Is there a distinct group of exclusive NPS 1 There is no distinct profile of NPS-only consumers. NPS consumers use a range of other illicit consumers? If not, which consumer ‘type’ substances, suggesting that specialised is most likely to use NPS? SCRA use was highest among amphetamine and cannabis consumers NPS interventions or harm reduction and polysubstance consumers. messages may not be required in the Australian context. Other NPS use was highest among polysubstance consumers. Do the consumer groups with the highest 1 Polysubstance consumers were younger than all other groups and NPS use appears to be a marker for more probability of NPS use differ from other were more likely to engage in dangerous activities under the problematic patterns of use. illicit drug consumers? influence of substances, to inject drugs and to report hazardous alcohol consumption.

Amphetamine and cannabis consumers were the most likely to report trouble ceasing their drug use. Sentinel sample (i.e. EDRS sample) What are the rates of NPS use amongst 2 Recent (i.e. past six-month) use of ‘any’ NPS increased from 33% in NPS use has been established as a people who use a range of other illicit 2010 to 40% in 2015. significant and ongoing practice amongst substances? our sample. However, it remains a highly When analysed by type, recent use of phenethylamine and dynamic marketplace with the popularity tryptamine NPS was found to have increased from 2010-2015, whilst of NPS classes changing over time. recent use of synthetic cathinones decreased and recent use of SCRA fluctuated. What factors are associated with NPS use, 2 Frequent (i.e. weekly or more) ecstasy consumers were more likely It appears that NPS consumers seek out and do they vary across NPS classes? to report past six-month phenethylamine use. substances with similar properties to the illicit drugs that they are already LSD consumers were more likely to report recent phenethylamine consuming. Poly NPS consumers were and tryptamine use. found to be a particularly high-risk group.

Cannabis consumers were more likely to report recent SCRA use.

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Table 30: Summary of key findings (continued) Research question Chapter Findings Conclusion Poly-NPS consumers were more likely to be male, younger, have higher levels of polydrug use, have overdosed on any drug in the past year, and to have engaged in past month criminal activity. Why do people use NPS, and do 3 Availability (i.e. no other drug available at the time) was the most Synthetic cathinones and cannabinoids motivations differ across substances? highly endorsed motivation for the use of synthetic cathinones. appear to be largely motivated by ‘opportunistic’ reasons. In contrast, Perceived legality and availability were the most highly endorsed NBOMe, 2C-family substances and DMT motivations for SCRA. appear to be motivated by specific desirable qualities of a substance. Value for money was the most highly endorsed motivation for NBOMe and 2C-family substances.

Short effect duration was the most highly endorsed motivation for DMT. What are the purchasing and supply 4 Most consumers nominated a friend as their main NPS source and Despite the oft assumed link between NPS patterns of NPS consumers? almost half reported that they had supplied NPS to others in the past and the internet, NPS consumers mostly year (predominantly ‘social supply’). source these substances from friends.

NBOMe consumers were more likely to nominate a dealer or online Social supply and mutual supply networks marketplace as their main source. They were also more likely to were common, with many participants report the following: supplying NPS to others; supplying to strangers both sourcing from and supplying to and acquaintances; and supplying for cash profit. friends. Do NPS consumers who nominate ‘online’ 4 NPS consumers who nominated online markets as their main NPS It is unclear if online purchasing may as their main NPS source have different source were more likely to have: supplied NPS to others; supplied to facilitate a ‘drift’ into dealing for profit. It purchasing and supply patterns than those strangers and acquaintances; sold NPS for cash profit; and to have could also be that existing dealers are who nominate an alternative main exchanged NPS for something else, compared to those who attracted to online marketplaces due to source? reported other primary sources. factors such as cheaper prices.

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6.2 Contribution to the literature, and policy implications

6.2.1 The nature of the Australian NPS market, and predicting the longevity of substances

Several surveys have commenced the routine collection of information on NPS use in Australia. This thesis adds to the evidence base by being the first to document rates of use of the different NPS classes over time in Australia. Data from the EDRS showed that although certain NPS have become established in Australia’s recreational drug market, it remains a highly dynamic marketplace with the popularity of NPS classes changing over time. Specifically, it was found that from 2010-2015, past six-month use of phenethylamines (8% vs. 18.6%; p<0.001) and tryptamines (7.5% vs. 10.9%; p=0.037) increased, whilst use of synthetic cathinones decreased (18.5% vs. 7.7%; p<0.001) and use of other NPS classes (e.g. SCRA) fluctuated. These trends continued in 2016-2017 (see Appendices B and C) and appear to match a number of international trends. For example, DMT and other tryptamine use has increased in the United States, whereas the use of mephedrone and SCRA has decreased (Johnston et al., 2018, Palamar, 2015, Palamar et al., 2017b, Palamar and Le, 2018 (in press).

These findings illustrate the importance of ongoing drug monitoring systems, such as the EDRS, so that changing trends can be detected in a timely manner. In such a rapidly changing market, it is essential to know which substances are being used so that health services and policy makers are prepared to respond where necessary (e.g. an increase in SCRA use may pre-empt an increase in calls to poisons centres or emergency department presentations). Indeed, the dynamic nature of the NPS market can make it difficult to develop and implement appropriate harm reduction messages; being able to identify which substances are likely to persist long-term, versus those which are likely to be transient, would provide invaluable guidance about how best to target policy initiatives. Papers two and three (and Appendix C) demonstrate that this can be achieved by combining trend analyses with the motivational profiling or pleasure testing of individual substances. That is, consumption that is motivated by the desirable aspects of a substance, or a substance that is rated highly in terms of pleasurable effects, may be more likely to persist long-term. Indeed, paper one showed that NPS consumers are mainly existing illicit drug consumers who experiment with a range of different substances; as such, it is likely that they will continue to use substances which are deemed pleasurable and cease use of those which are not.

However, recognising the pleasure associated with substance use is something that is often overlooked in AOD research (Ritter, 2014, Duff, 2008, Lancaster et al., 2017, Moore, 2008, O'Malley and Valverde, 2004, Schnuer, 2013), despite this being one of the main reasons for

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drug consumption (Boys et al., 2001, Glavak Tkalić et al., 2013, Peters and Kok, 2009, Rigg, 2017). Rather, the dominant discourse around substance use focusses on harms and problematic patterns of use (Barratt et al., 2014). It could be argued that this is particularly so for NPS which incorporates potential harms into its very definition, thus framing these substances as harmful from the outset (despite very little being known about their pharmacology and toxicology). Only rarely is it acknowledged that some NPS could offer pleasurable or therapeutic benefits (Barratt et al., 2017b, Orsolini et al., 2015, Soussan et al., 2018). Indeed, the EDRS is one of the few surveys that has attempted to measure the pleasure and harms associated with NPS use. In 2012 and 2013, participants were asked to rate the pleasurable and negative effects associated with taking NPS (and ecstasy, cocaine and LSD for comparative purposes); they were also asked to rate the likelihood of consuming these substances again. In 2014, participants were asked about their motivations for NPS use.

The findings from these surveys suggest that the motivations (paper three) and pleasure ratings (see Appendix C) endorsed for different substances correspond with the trends observed in paper one. Specifically, paper three showed that DMT, NBOMe and 2C-x consumers were motivated by the desirable qualities of the substance, whilst other research has shown that when compared to their ‘classical’ counterparts, these substances have relatively positive effect profiles (Lawn et al., 2014, Matthews et al., 2016 ). Given the positive experiences endorsed by these consumers, it perhaps not surprising that these substances were then found to have increased in use over time, and it seems likely that they will continue to persist in Australia's recreational drug markets.

In contrast, SCRA consumers (paper three) were found to be motivated by opportunistic reasons (i.e. because they thought it was legal, or because no other drug was available to them). Other research has shown that SCRA are rated less favourably than natural cannabis (Barratt et al., 2013, Winstock and Barratt, 2013b). Paper two found that SCRA use declined sharply in 2014, with rates of use remaining low in the subsequent years. This finding was consistent with those of the NDSHS, in which past 12-month SCRA use declined from 1.2% in 2013 to 0.3% in 2016 (Australian Institute of Health & Welfare, 2017). Combined, these findings indicate that SCRA are unlikely to become established in Australia’s recreational drug market - an assertion which is supported by the existence of a natural cannabis market that provides high quality, easily accessible products (Australian Criminal Intelligence Commission, 2017). Indeed, most of Australia’s cannabis is domestically produced, with both bush and hydro cannabis consistently endorsed as being ‘easy’ to ‘very easy’ to obtain and of ‘high’ quality (Karlsson and Burns, 2018, Uporova et al., 2018). Furthermore, cannabis is decriminalised (to varying degrees) in all 155

Australian jurisdictions (Hughes et al., 2016), thus removing some of the incentive to initiate SCRA use. In countries where natural cannabis is expensive or difficult to access, or in which there are stricter penalties for cannabis use, there may be more incentive for people to experiment with a ‘legal’, cheaper alternative (as has been evidenced in the United Kingdom; European Monitoring Centre for Drugs and Drug Addiction, 2017b).

It is important to note that the trends observed in paper 2 are likely attributable, in part, to changes in Australian legislation (with NPS now prohibited in all Australian jurisdictions; see Table 3 for further details). Given the varying legislative frameworks across jurisdictions and the different dates of implementation, it is beyond the scope of this paper to determine whether the scheduling of NPS may have contributed to the trends observed in this thesis. However, it seems likely that legislative changes may have contributed to some of these changes. For example, in 2012, the Australian Therapeutic Goods Administration introduced a blanket ban on any type of synthetic cannabinoid that produced the same pharmacological effect as cannabis (Bright et al., 2013), and in 2014 there was a significant decline in the use of synthetic cannabinoids amongst our EDRS sample. However, it is unclear if this was a lagged effect of the legislation (due to practices such as stockpiling) or if it was due to other, unrelated factors such as consumer acceptability.

Previous research indicates that the prohibition of NPS, in certain cases, has led to a decline in use. In the UK it was found that once mephedrone was listed as a controlled substance, self- reported use fell (Lader, 2015); similarly, following the prohibition of BZP in New Zealand, there was a decline in self-reported use among the general population (Wilkins & Sweetsur, 2013). There is little research that has explored this in the Australian context, however a study by Cairns et al (2017) examined the impact of Australian legislative changes on synthetic cannabinoid exposures reported to the New South Wales Poisons Information Centre. They found that although Commonwealth legislation (see Table 3) had little impact of call volumes, state-based legislation introduced in 2013 (which banned specific brands in SCRA products) was followed by a dramatic, sustained decrease in calls. In all of these studies, it is unclear if such declines were the result of reduced availability following the legislative changes or if they were the result of a general deterrent effect (or both). Furthermore, a number of NPS have remained relatively common despite their subsequent prohibition, and in such cases legal status is considered to be a secondary driver for use, particularly among those who already use illicit drugs (Measham & Newcombe, 2016). As such, it is important that further research evaluate the impact of Australian legislation on the NPS marketplace to provide an evidence-base for the efficacy of these regulatory approaches. 156

Key messages:

. Australia’s NPS market is dynamic and rapidly evolving, highlighting the importance of ongoing drug monitoring systems. . Examining the motivations and pleasure ratings associated with NPS appears to have some predictive value in determining which NPS are likely to persist in recreational drug markets. . Using this approach, it appears that DMT, NBOMe and 2C-x will continue to persist in Australia’s recreational drug market, whereas SCRA will not.

6.2.2 The heterogeneity of NPS consumers, and the intersection with the illicit drug market

A key finding of this thesis is that there is no distinct profile of exclusive NPS consumers, at least not in the Australian context. Paper one showed that only 0.07% of Australians aged 14 years or older reported past year use of NPS but no other illicit substances (although given the small number of people who reported NPS use, it is important to note that this is a point estimate; see section 6.3 for further details regarding the limitations associated with the NDSHS). Rather, most NPS consumers had also used a range of other substances. This finding is consistent with previous studies that have shown that NPS use occurs mainly in the context of other drug use (e.g. Moore et al., 2013). That is, NPS consumers do not appear to be ‘new’ users per se, but rather are mainly existing drug consumers who expand their repertoire to include NPS.

However, paper one was limited by the fact that the NDSHS only separates NPS into two categories - SCRA and ‘other’ NPS. This restricts our ability to explore the heterogeneity of NPS consumers. Paper two addressed these limitations by using data from the EDRS to examine the correlates associated with use of various NPS classes. The findings from paper two indicate that consumers experiment with NPS that are of similar functionality to the other illicit drugs they consume. That is, frequent (i.e. weekly or more) ecstasy users were more likely to report past six-month phenethylamine use; LSD users were more likely to report recent phenethylamine and tryptamine use; and cannabis consumers were more likely to report recent SCRA use. This pattern is perhaps not surprising given that NPS are often marketed as drugs which mimic the effects of traditional illicit drugs (European Monitoring Centre for Drugs and Drug Addiction, 2016a).

However, there is a concern that since NPS are sometimes marketed as legal alternatives to illicit drugs, people might assume that NPS are safer than illicit drugs. Certain studies, including paper three of this thesis, have shown that perceived safety can be a secondary motivation for NPS use (Barnard et al., 2016, Corazza et al., 2014, Soussan and Kjellgren, 2015, Winstock et al., 2016). Such perceptions are particularly problematic in cases where a specific NPS has been 157

shown to be more dangerous than the substance it was intended to replace (e.g. 5F-PB-22, MDMB or AB-FUBINACA versus natural cannabis). In such cases, it seems pertinent to provide targeted education campaigns about the harms associated with these substances. The unfavourable consumer reports associated with SCRA use (Barratt et al., 2013, Winstock and Barratt, 2013b), combined with the finding that perceived safety was most commonly endorsed as a motivation by SCRA consumers (paper three), suggest that cannabis consumers may be a particularly important target group for educational campaigns about SCRA-related harms.

Given the positive experiences endorsed by consumers of DMT, NBOMe and 2C-x, such consumers might be less likely to cease use of these substances - especially in the face of education campaigns (often from government organisations) that are inconsistent with their personal experiences. Indeed, despite being used for decades as a method for substance use behavioural change, evidence regarding the efficacy of mass-media campaigns (often using scare tactics and fear-based campaigns) is mixed (Allara et al., 2015, Beck, 1998, Esrick et al., 2018, Hill et al., 1998, Simpson, 2017, Soames Job, 1988, Wakefield et al., 2010, Witte and Allen, 2000). A recent systematic review of peer-reviewed studies during 2005-2017, found that most of the study interventions (i.e. fear-based messages and scare tactics) included in their analysis showed some evidence of effectiveness in influencing substance-use related measures; however, the outcomes were generally focused on intention to use and perceptions, rather than actual drug use (Esrick et al., 2018). In several studies, although the intervention was more effective than the control, it was less effective than ‘gain-framed’ messages – that is, messages designed to create positive emotion. Furthermore, Esrick et al. (2018) noted that all messages included in their review focussed on providing accurate information about the dangers associated with a specific substance, rather than preventing substance use overall. None of the messages directly called for complete abstinence, signifying a shift from older mass education campaigns. Indeed, public health campaigns are generally premised upon the assumption that people aspire (or should aspire) to be healthy above all other desires (Crossley, 2002), and it has been argued that health promotion campaigns that neglect to acknowledge the pleasure incentive may be resisted and could paradoxically serve as motivation for engagement in drug use (Barratt et al., 2014). Conversely, health promotion campaigns that acknowledge the dynamics between pleasure and harms, and which include strategies for how to minimize the risks associated with NPS use (e.g. Linnell, 2017; pg. 6), are likely to be deemed more acceptable and credible by individuals already using these substances (Pennay, 2015, Race, 2008, Soussan et al., 2018).

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For health promotion campaigns to be maximally effective, concurrent availability of and access to key services is essential (Wakefield et al., 2010). This could include drug-checking services (using mass spectrometry or liquid chromatography methods), whereby individuals submit samples of their drugs to have their contents identified and analysed for purity. The results are provided to the consumer (enabling them to make a more informed decision about whether they intend to consume the substance) and provide an important opportunity for health professionals to engage with consumers who do not typically present at drug treatment services. Furthermore, the results obtained through drug checking services can have harm reduction benefits that extend beyond the individual. Specifically, they can be used to: monitor trends in NPS availability and use (providing an evidence base for appropriate public health responses); monitor trends in unintentional NPS use (i.e. what proportion of substances contain NPS as adulterants); identify emerging hazards associated with specific NPS and the formulations available; improve the knowledge base for effective clinical management of acute and chronic presentations; and also provide intelligence that could influence supply dynamics (Butterfield et al., 2016). That is, drug-checking (if implemented appropriately) could mitigate the severity and impact of NPS-related adverse effects. It would enable rapid dissemination of information about NPS to potential consumers, warning them about specific products and batches; and to clinicians, guiding them on the predicted toxidrome and management of affected patients (Butterfield et al., 2016).

Key messages:

. There is no distinct profile of NPS-only consumers. . Rather, NPS consumers use a range of other illicit substance, and appear to seek out NPS with similar properties to the illicit drugs they are already consuming . The heterogeneity of NPS consumers highlights the need for a mixed harm reduction approach. This should include credible information regarding the harms associated with NPS use (where such harms exist), combined with services such as drug-checking.

6.2.3 NPS in the context of polysubstance use, and high-risk behaviours

Paper two examined the characteristics associated with the use of various NPS classes. Polydrug use was found to be the only consistent predictor of past six-month use of the different NPS classes. This finding was consistent with that of paper one, which showed that polysubstance consumers had the highest probability of ‘other’ NPS use (i.e. non-SCRA NPS). In both papers, the polysubstance-use groups had a higher likelihood of having engaged in a range of drug- related risk behaviours, such as overdose, injecting and engaging in dangerous activities (e.g.

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driving) whilst under the influence of drugs and/or alcohol. It was also found that amphetamine and cannabis consumers (the group with the highest probability of SCRA use) had the highest probability of experiencing drug-related harms, such as trouble ceasing their drug use.

However, given the low frequency at which NPS are consumed, it seems unlikely that the above problems were a direct consequence of NPS use. Results from the 2017 EDRS showed that most NPS were consumed on a median of 1-2 days in a six-month period, which is considerably less than the frequency of cannabis (median: 60 days) and ecstasy (median: 14 days) use, although comparable with that of cocaine and LSD use (median: three days respectively) (Karlsson and Burns, 2018). These findings suggest low levels of NPS-related substance use disorder. Rather, NPS use appears to be a marker for greater engagement in substance use, and also for risky patterns of use which could result in acute medical presentations. Indeed, between 2010 and 2015 there were 146 SCRA-related exposures reported to the NSW Poisons Information Centre (PIC) (Cairns et al., 2017). In 2014, 11 SCRA-related exposures were reported to the QLD PIC (Children’s Health Queensland Hospital and Health Service, 2014), and in 2016, 24 SCRA-related exposures and three cathinone-related exposures were reported the VIC PIC (Austin Health, 2016). In Europe, NPS (as a whole) fell into the top 20 drugs recorded in emergency presentations in 2015 (European Monitoring Centre for Drugs and Drug Addiction, 2017a); unfortunately, comparable information is not available in the Australian context and is mostly self-report (e.g. Winstock and Barratt, 2013a).

As such, it appears that specialised interventions for NPS-related dependency are unnecessary. Rather, existing health services - particularly those that provide acute care - should be equipped to deal with NPS-related presentations. Given the link between NPS use, polydrug use and high- risk behaviours, it is likely that NPS consumers will come into contact with a range of health professionals and services, including general practitioners, emergency departments, sexual health services, HIV services, mental health services and drug treatment services. It is essential that health professionals working in each of these fields are familiar with NPS and have the capacity and confidence to screen for these substances. At present, no recognised screening tools for NPS use exist (Abdulrahim and Bowden-Jones, 2015) and it is not feasible for front-line professionals to screen clients for hundreds of different substances. In this situation, combining NPS by effect profile (e.g. drugs that mimic the effects of cannabis) seems a practical solution (note: this approach differs from our research recommendation that future studies should ask about the use of individual NPS, rather than grouping them together).

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Once a person’s use has been determined (i.e. they have disclosed the use of an NPS), existing guidelines, such as the drug misuse and dependence UK guidelines on clinical management (Clinical Guidelines on Drug Misuse and Dependence Update 2017 Independent Expert Working Group, 2017), can be used to assess the level of use, risk factors and symptoms of dependence. This information is used to determine the most appropriate response. In the UK, the NEPTUNE project has been developed to improve clinical practice regarding the detection, assessment and management of harms resulting from the use of novel psychoactive substances. These guidelines suggest that once NPS use has been assessed, health professionals should be prepared to offer any, or all, of the following three options: 1) information and brief advice; 2) signposting to sources of other information; and 3) referral to formal treatment services (for more information, see Abdulrahim and Bowden-Jones, 2015). Key messages

. NPS use appears to be a marker for higher engagement in substance use (and as such higher risk patterns of use), with little evidence of NPS-related substance use disorder. . These findings suggest that specialised interventions for NPS-related dependency are not needed. Rather, existing (primarily acute) health services should be equipped to deal with NPS-related presentations.

6.2.4 NPS, the internet, and social supply

This thesis fills an important research gap regarding the importance of online markets as a source of supply for NPS consumers. Sometimes dubbed ‘internet drugs’ (e.g. Khaled et al., 2016, Liechti, 2015), the link between the internet and NPS is often assumed rather than empirically proven. Paper four showed that in-person sources, such as friends and dealers, remain the main avenue for sourcing NPS, which is consistent with the purchasing patterns of illicit drug consumers more generally (Australian Institute of Health & Welfare, 2017, Belackova and Vaccaro, 2013, Fowler et al., 2007, Karlsson and Burns, 2018, Uporova et al., 2018). Indeed, recent findings from the 2017 EDRS showed that friends were the most common source across all drug types (ecstasy, methamphetamine, cocaine, ketamine, LSD and cannabis), followed by a known dealer (Karlsson and Burns, 2018).

With regards to online purchasing, more than a fifth of the 2017 EDRS sample reported having purchased an illicit drug online in their lifetime, with 16% having done so in the past year. The main substances purchased online in the preceding year were ecstasy and LSD, with a much smaller proportion having purchased an NPS (mainly 2C-x, DMT or NBOMe). Indeed, despite the common association between NPS and the internet, it is ‘traditional’ illicit drugs (i.e. cannabis,

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pharmaceuticals, MDMA and cocaine) that dominate online drug markets, with NPS being far less common (Roxburgh et al., 2017). However, there are signs of the re-emergence of Australian surface web stores selling NPS (e.g. https://www.intenseincenseoz.com/shop-cjg9) and this is something that should be monitored in the future, particularly given the finding in paper three that ‘availability’ was the main motivation endorsed by synthetic cathinone and SCRA consumers.

Paper four also found that almost half of NPS consumers had supplied these substances to another person, although this was largely ‘social supply’ (i.e. supplying to friends for no cash profit). These findings are consistent with those reported in studies of other illicit drug consumers. Such studies have repeatedly shown that individuals within friendship groups source their drugs from - and concurrently supply to - group members. These practices ensure a consistent supply of quality product and minimise the risk of health harms and criminal justice consequences (Belackova and Vaccaro, 2013, Bright and Sutherland, 2017, Grigg et al., 2015, Nicholas, 2008). However, whilst previous research has suggested that social supply may be used as harm minimisation strategy, it is possible that this is undermined by a lack of knowledge regarding thresholds for possession versus supply (e.g. Sindicich and Burns, 2013, Hughes, 2012). That is, by purchasing larger quantities (to enable supply to their friendship group), individuals may unwittingly expose themselves to more severe penalties if arrested.

This is demonstrated by an Australian survey of 823 people who inject drugs (PWID), in which less than half (44%) of the participants could correctly identify the importance of quantity in Australian drug trafﬁcking laws. They were also unable to nominate trafficable quantities that did not exceed the actual thresholds for deemed supply (Hughes et al., 2014b). Such knowledge is likely to be even poorer regarding NPS, which are sometimes marketed as ‘legal highs’. In 2015, 57% of the EDRS sample were ‘unsure’ of the legal status of NBOMe and 2% incorrectly believed it was legal (Sindicich et al., 2016). Indeed, much of the legal information regarding NPS use, possession and supply in Australia is non-specific (instead stating that they are “subject to similar criminal penalties as traditionally prohibited substances”; Hughes, 2014; pg.7). There is a concerning lack of clarity regarding the current trafficking thresholds and how these were derived (see Hughes et al., 2014a for previous work examining trafficable drug thresholds).

Key messages

. The internet is not a main source of supply for Australian NPS consumers. . Rather, mutual supply networks are common, whereby consumers both source from and supply to friends.

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. Given the ambiguity of NPS trafficking thresholds, it is possible that individuals who engage in social supply are unwittingly exposing themselves to severe criminal penalties.

6.3 Limitations and recommendations for future research

6.3.1 Measuring unintentional NPS use through the inclusion of biological measures

Much of the previous research on NPS use (including the papers included in this thesis) have relied on self-report data, which may be subject to bias. It is possible that EDRS and NDSHS participants might have intentionally under-reported their rates of NPS use. However, given that any information provided during these studies is confidential and anonymous, the incentive to do so is minimal. Furthermore, existing evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use. Darke (1998) reviewed studies which had assessed the reliability and validity of self-reported substance use. Studies which had conducted test- retest analyses (i.e. administered the same questions at two timepoints) and concordance analyses (i.e. same questions administered by different interviewers) demonstrated sufficiently reliability. Surveys which compared self-report substance use against biomarkers (primarily hair and urine samples) demonstrated sufficient validity. Whilst some discrepancy was noted, it occurred in both directions (i.e. under-estimating and over-estimating drug use), and in the case of validity was potentially attributable to the time limitations associated with urinalysis (i.e. drugs are typically only detected in urine for 72 hours).

The findings presented in this thesis refer to intentional NPS use only, with unintentional NPS use in Australia remaining a largely unresearched phenomenon. Unintentional NPS use is of concern given that there is a greater risk of harm when substances are consumed unexpectedly - consumers are unaware of appropriate dosages and cannot apply drug-specific harm-reduction practices. International studies indicate high levels of such unintentional use in ecstasy-using populations. For example, a survey of nightclub and festival-attending young adults in New York City (NYC) showed that among those who reported no lifetime NPS use (and who provided a hair sample; n=34), two-fifths (41%) tested positive for an NPS (mostly commonly butylone; Palamar et al., 2016). Similarly, a 2016 survey of 90 past-year ecstasy consumers in NYC found that 51% tested positive for a drug not self-reported, most commonly synthetic cathinones, methamphetamine, other stimulant NPS or new disassociatives (Palamar et al., 2017c).

No similar projects have yet been conducted in the Australian context, however, there is some anecdotal evidence of unintentional NPS consumption. In three jurisdictions and during a period spanning two summers (2016–2018), capsules sold as ‘ecstasy’ caused poisoning, hospitalisations and deaths (Cowie et al., 2017, Energy Control, 2017, Evans, 2017, Ferguson, 163

2018, Roberts, 2016). These samples were later found to contain a mix of 4-FA, 25CNBOMe and MDMA (Cowie et al., 2017, Energy Control, 2017). Whilst pills sold as ‘ecstasy’ commonly contain adulterants (Morelato et al., 2014, Verweij, 1992), the vast array of NPS that are now available have heightened the risk of consuming an adulterant that could result in an adverse event. There have also been deaths following the consumption of ‘LSD’ that contained an unexpected NBOMe derivative (Caldicott et al., 2013).

However, in these situations the best available information is often from media reports. Thus, a more systematic data-collection approach is urgently needed, and I would argue that current monitoring systems should be accompanied by biological sampling (i.e. self-report data and biological samples collected from the same individuals so that discordance can be assessed). Although the detection of NPS in biological matrices can be difficult since the exact compounds of interest may not be known, methods for the determination of these substances are continually emerging and improving (Favretto et al., 2013, Kyriakou et al., 2017). Indeed, there have been significant advances in the screening capabilities of toxicology laboratories, and in the development of rapid, versatile yet specific assays able to identify new molecules. The most recent advances in mass spectrometry technology, introducing instruments capable of detecting hundreds of compounds at nanomolar concentrations, are expected to give a fundamental contribution to broaden the diagnostic spectrum of the toxicological screening to include not only all these continuously changing molecules but also their metabolites (Favretto et al., 2013, Kyriakou et al., 2017). Presently, the most feasible type of biological sampling is arguably hair sampling, as it offers the longest detection window (detectable from 7–10 days post drug use to several years), with substances able to remain in hair for substantial periods of time without significant degradation (Boumba et al., 2017). In contrast, other biological testing options are only able to detect current or very recent consumption (e.g. blood and urine) or have limited capacity to detect compounds that are active at micro-doses (e.g. oral fluid).

Of course, the ability to incorporate biological testing into existing monitoring systems may be limited by a number of factors, including resource requirements (e.g. the financial costs associated with forensic toxicology). Furthermore, there are a number of ethical implications associated with conserving biological samples, including: the principles of information, the consent of the persons concerned (and future uses of samples), fate of exported samples, the confidentiality about the personal data, and in some cases discrimination and stigmatisation (Tazzite et al., 2009, Tindana et al., 2014). These are all factors which must be given serious consideration if biological testing were to be incorporated into existing monitoring system. In the Australian context, this would be mean adhering to the guidelines outlined in the National 164

Statement on Ethical Conduct in Human Research (National Statement on Ethical Conduct in Human Research 2007, updated 2018).

Alternatively, as discussed in section 6.2.2, drug-checking services could also be utilised to assess unintentional NPS use (i.e. by monitoring the number of substances which contain NPS as adulterants). Drug-checking has been operating in this capacity for over 25 years in Europe (Barratt et al., 2018, Brunt, 2017), however is more contentious in the Australian context (Groves, 2018). Indeed, although Australia’s first drug-checking service was piloted at the Groovin the Moo festival in Canberra earlier this year (April 2018), there remains considerable political resistance to a national roll-out of such services. Furthermore, little attention has been given to drug-checking services operating at fixed-sites (such as Needle and Syringe Programs), as opposed to on-site (e.g. festivals, nightclubs and other mass gatherings; Barratt et al., 2018). This is somewhat surprising given the current synthetic opioid crisis in the US (Prekupec et al., 2017), with a recent pilot study - which conducted urinalysis amongst heroin users attending the Medically Supervised Injecting Centre (Sydney) in October 2017 - finding that consumer acceptability was high (i.e. clients were interested in finding out whether their heroin contained fentanyl; Barratt et al., 2017a), Thus, expanding drug-checking services to fixed sites, such as Needle and Syringe Programs, is an area that requires further research.

6.3.2. Examining NPS use amongst vulnerable populations

The papers included in this thesis utilise two samples: a general population sample and a sentinel sample of regular stimulant (primarily ecstasy) consumers. Both these samples either under- represent or exclude vulnerable populations, such as incarcerated and homeless persons. International studies have identified elevated rates of NPS use amongst both these populations, however there do not appear to be any existing studies which have examined NPS use among these populations in Australia and this an area that requires further research.

International research has also identified problematic NPS use among samples of men who have sex with men (MSM). Although sexual orientation was included as a potential predictor of NPS use in paper two (with 12% of the sample identifying as non-heterosexual), NPS use among MSM was not closely examined in this thesis. There are a small number of studies that have collected information on mephedrone use among LGBTI populations in Australia, all of which have detected very little use (Hull et al., 2014, Lea et al., 2011, Mullens et al., 2017). However, these studies are limited by the fact that they only asked about mephedrone; rates and practices of NPS use among MSM (and LGBTI populations more generally) remain largely unknown.

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With regards to NPS use among people who inject drugs (PWID), it is interesting to note that the Illicit Drug Reporting System (IDRS) has detected relatively little NPS use. From 2013-2017 the IDRS has reported rates of past six-month NPS use below 10%. SCRA were the most commonly used of these substances, with past six-month synthetic opioid use reported by <1% of the sample (Karlsson and Burns, 2018). Interestingly, a recent pilot study which conducted urinalysis amongst heroin users attending the Medically Supervised Injecting Centre (Sydney) in October 2017, found no evidence of fentanyl-laced heroin (Barratt et al., 2017a). It thus appears that the synthetic opioid crisis in the United States, in which thousands of people have died (Prekupec et al., 2017), has not reached any sort of parallel in Australia. However, given the dynamic and volatile nature of the NPS market, this area must continue to be closely monitored.

6.3.3 Distinguishing between NPS, and generalisability of data

As illustrated by this thesis, considerable heterogeneity exists in the NPS market and amongst NPS consumers. Grouping NPS together into a single category, or into broad classes, can obscure important differences. Thus, it is recommended that where possible, future studies should endeavour to distinguish between NPS by asking about specific substances. This recommendation is supported by two studies, both of which showed that asking about individual substances resulted in higher response estimates than generic or ‘gated’ questions (which utilise skip logic, such that only a ‘yes’ response to use of a specific drug class will lead to more extensive queries of drug use in that class; Drapalova and Belackova, 2018, Palamar et al., 2017a). Given the large number of NPS available, guidance regarding the main NPS that require monitoring is essential. This could be achieved by having a globally consistent list of NPS, as well as transparency around which substances have been identified in which countries (see section 6.3.5). Where it is not feasible to ask about a large number of substances, it may be appropriate to accompany ‘gated’ questions (e.g. have you used substances that mimic the effects of cannabis?) with a check-list or flashcard of the most common (or high-priority) substances.

Additionally, as noted in the chapters containing empirical work, the findings presented in this thesis are not necessarily generalisable to other populations or countries. Complex cultural and regulatory differences may occur across such contexts. As discussed in section 6.2.1, the decline of the SCRA market in Australia has likely been facilitated, in part, by the existence of a decriminalised natural cannabis market, which provides high quality, easily accessible products (Australian Criminal Intelligence Commission, 2017, Hughes et al., 2016). However, in countries where natural cannabis is expensive or difficult to access, or which have stricter penalties for cannabis use, people might have greater incentives to experiment with a ‘legal’ cheaper

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alternative. Indeed, Australia has not witnessed the same level of mephedrone or SCRA use that has been documented in the UK (European Monitoring Centre for Drugs and Drug Addiction, 2017b, Home Office, 2017), nor have we been affected by the synthetic opioid crisis observed in the United States (Prekupec et al., 2017), thus demonstrating important inter-country differences.

Finally, as outlined in section 6.3.2, both samples utilised in this thesis under-represent disadvantaged and vulnerable populations whom may be more incentivised to use NPS for reasons such as cheaper prices, and the avoidance of drug use detection. Indeed, patterns of use, motivations for use and purchasing and supply patterns are likely to differ substantially amongst different groups.

6.3.4 Reflecting on the definition, and categorisations, of NPS

The overarching aim of this thesis was to explore the NPS market in Australia, thereby providing an evidence base for measured policy responses. Although this goal has been achieved, it has become increasingly evident that there needs to be further consideration as to how NPS are defined. The EMCDDA, UNODC and IGCD have all acknowledged the importance of consistent terminology, however, it seems that the importance of using a consistent definition has been overlooked. Many studies continue to measure NPS as a single entity (without clearly outlining which substances are included; Australian Institute of Health & Welfare, 2017, European Commission, 2014, National Advisory Committee on Drugs and Alcohol, 2016), some include substances such as amyl nitrate, nitrous oxide, GHB and ketamine (e.g. Holloway and Bennett, 2018, Kinyua et al., 2016), whilst others explicitly exclude these substances (e.g. Gao et al., 2017). Some studies have even included ecstasy as an NPS (e.g. Wonguppa and Kanato, 2017). These discrepancies illustrate the difficulty in comparing findings across studies. Indeed, there is limited utility in using consistent terminology if the composition of NPS varies markedly from study to study.

Currently, NPS are defined as substances that are not controlled by the 1961 United Nations Single Convention on Narcotic Drugs or the 1971 United Nations Convention on Psychotropic Substances, but which may pose a public health threat comparable to substances listed in these conventions (European Monitoring Centre for Drugs and Drug Addiction, 2016c). As mentioned in the introduction, there are two main problems with this definition. Firstly, harms are not assessed before classifying a substance as an NPS. As such, it seems misleading to define this as a group of drugs which may pose a public health threat comparable to currently scheduled substances when not enough evidence exists to either support or refute this statement (indeed,

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mere psychoactivity has not been established for many NPS). Secondly, once there is enough evidence to prove that a specific NPS poses a public health threat, it will likely be scheduled. However, once scheduled, it is not moved out of the NPS category, despite no longer meeting the definitional requirements. This leads to a ‘net-widening’ problem in which the list of NPS expands to include both controlled and uncontrolled substances (see Table 3), thus undermining the validity of the NPS definition.

Furthermore, in 2016 the EMCDDA broadened the scope of the NPS definition to include “emerging drug issues and trends, new types of harm and newly emerging user groups” (European Monitoring Centre for Drugs and Drug Addiction, 2016b, pg.6). Throughout this thesis, this convention has been adhered to and substances that are scheduled under UN conventions, but which have little evidence of recreational use (e.g. DMT and 2C-B), have been included as NPS. Whilst it is important to monitor these substances, it has become clear that expanding the definition in this manner has introduced considerable ambiguity. Drug markets are rarely static and including ‘emerging drug issues and trends’ potentially encompasses a broad array of substances and issues, from the diversification of the ecstasy market (European Monitoring Centre for Drugs and Drug Addiction, 2016b, Uporova et al., 2018) to the emergence of high-risk fentanyl analogues (Prekupec et al., 2017). The utility of combining these very separate issues under one heading is unclear, and rather than broadening the definition to a point where it becomes almost meaningless, I would argue that we need to give serious consideration to what the defining characteristics of NPS are and restrict the definition accordingly. That is, there need to be clear, objective criteria for what constitutes an NPS, as well as for when a substance ceases to be an NPS.

Whilst it is beyond the scope of this thesis to consider this in detail, below I briefly outline two possible models.

Model 1: Globally unscheduled substances

If legal status was determined to be the defining characteristic of NPS, the current definition would remain largely intact, albeit with the existing reference to harms removed. The result would be as follows: “A psychoactive substance, in pure form or in preparation, that is not controlled by the 1961 United Nations Single Convention on Narcotic Drugs or the 1971 United Nations Convention on Psychotropic Substances.” It is important to emphasis here that this model refers to the international legal status of these substances, rather than national or jurisdictional legal status. That is, although many countries have introduced various legislative frameworks prohibiting NPS, most NPS have not yet been scheduled under the 1961 United

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Nations Single Convention on Narcotic Drugs or the 1971 United Nations Convention on Psychotropic Substances.

Given that little is known about these substances (another defining characteristic of the NPS phenomenon), and acknowledging that psychoactivity in and of itself does not necessarily translate to harm, it may be appropriate to then have sub-categories which reflect varying levels of harm. This could potentially include three categories, such as: 1) unknown harms (most NPS would likely fall into this group); 2) low risk (i.e. evaluated by the Expert Committee on Drug Dependence and determined not to meet the criteria for scheduling; e.g. ketamine, GBL); and 3) high-risk (i.e. serious adverse effects reported, but not yet enough evidence to warrant scheduling; e.g. some of the fentanyl analogues). These sub-categories would be dynamic with substances able to move across categories. Substances in the high-risk category would be highest priority and would necessitate diligent monitoring. For example, they could be incorporated into surveys and wastewater analyses.

When does a substance cease being an NPS?

Once scheduled under either of the UN drug conventions, that particular substance should immediately be removed from the NPS category, thus preserving the integrity of the above definition.

What happens when a substance ceases being an NPS?

The importance of monitoring these substances does not dissipate once a substance no longer meets the criteria to be called an NPS. As such, there could be an argument for having an interim category of ‘recently scheduled substances’. This would include substances that have been scheduled in the past five years (or other agreed upon time-frame). An example of a definition here might be: “A psychoactive substance, in pure form or in preparation, that has been controlled by the 1961 United Nations Single Convention on Narcotic Drugs or the 1971 United Nations Convention on Psychotropic Substances within the preceding five years”. The five-year period is an arbitrary time frame that could be amended; however, this is arguably a sufficient period for a substance to cease being ‘novel’ or ‘emerging’. The progression between the different stages of this proposed model is outlined in Figure 4, with the term ‘globally unscheduled substances’ used instead of NPS.

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Figure 4: Model 1 – Globally unscheduled substances (GUS)

Model 2: New psychoactive substances

However, if it were determined that the defining characteristics of NPS were not their legal status and potential harms, but rather their ‘newness’, a different model would need to be considered. In this situation, ‘newness’ would not relate to the date of synthesis or discovery but rather to self-administered use in a recreational or non-medical context. For this model, a possible definition could be as follows:

A psychoactive substance, in pure form or in preparation

1) that was first reported to the EMCDDA or the UNODC; or 2) for which reports of recreational or un-prescribed use were first documented within the past 15 years.

This definition would include encapsulate most of the NPS that are currently listed but would remove some of the ‘old psychoactive substances’ (e.g. ketamine, GHB) that are sometimes included as NPS. Again, the 15-year period is a somewhat arbitrary time-frame, after which substances would cease being ‘new’. After this period, they could move into one of two categories depending on their prevalence (or other established measure). For example, if a specific substance had an annual prevalence of ≥0.2% in two or more countries, it could be considered an ‘established’ psychoactive substance. If not, it could be classified as an unestablished psychoactive substance (see Figure 5). The suggested figure of 0.2% is based on 170

prevalence figures for other illicit substances; for example, heroin - one of the least prevalent drugs - has an annual prevalence rate of 0.2% in several countries, including Australia and the US.

Figure 5: Model 2 – New Psychoactive Substances (NPS)

New psychoactive substances

After 15 years, prevalence is accessed

If annual prevalence is If annual prevalence is ≥0.2% <0.2% in two or more countries Unestablished psychoactive substances Established psychoactive substances

6.3.5 Call for transparency and publicly available data

Intertwined with the importance of a globally consistent NPS definition, it seems prudent to put forward a call for more transparent and open sharing of data. Although the EMCDDA provides a list of all newly identified NPS in the appendices of their (publicly available) annual reports, UNODC data are more restricted. That is, the UNODC reports on how many NPS have been reported by its member states, but the names of these substances are not publicly disclosed. Hence, although ‘over 800’ NPS were reported to the UNODC during 2009-2017, the identities of those substances remain unknown.

The UNODC does provide a full list of reported NPS upon request. However, only early warning advisory members can obtain more detailed information, such as country breakdowns. This ‘gatekeeping’ of information seems unnecessary and I would argue that there would be considerable benefit in making these data publicly available. Indeed, knowing the names of the substances that have been identified, and the countries and year/s in which they were detected, would in understanding of the NPS market - both internationally and within individual countries. The NPS market is a global phenomenon and as such there needs to be global cooperation.

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6.4 References

ABDULRAHIM, D. & BOWDEN-JONES, O. 2015. Guidance on the Management of Acute and Chronic Harms of Club Drugs and Novel Psychoactive Substances. In: GROUP, O. B. O. T. N. E. (ed.). London: Novel Psychoactive Treatment UK Network (NEPTUNE). ALLARA, E., FERRI, M., BO, A., GASPARRINI, A. & FAGGIANO, F. 2015. Are mass-media campaigns effective in preventing drug use? A Cochrane systematic review and meta-analysis. BMJ Open, 5. AUSTIN HEALTH 2016. Victorian Poisons Information Centre. Annual Report 2016. Heidelberg: Austin Hospital. AUSTRALIAN CRIMINAL INTELLIGENCE COMMISSION 2017. Illicit Drug Data Report 2015-16. Canberra: Australian Criminal Intelligence Commission. AUSTRALIAN INSTITUTE OF HEALTH & WELFARE 2017. National Drug Strategy Household Survey 2016. Detailed findings. Drug Statistics series no. 31. Cat. no. PHE 214. BARNARD, M., RUSSELL, C., MCKEGANEY, N. & HAMILTON-BARCLAY, T. 2016. The highs and lows of NPS/“Legal High” use: Qualitative views from a UK online survey. Drugs: Education, Prevention and Policy, 1-7. BARRATT, M. J., ALLEN, M. & LENTON, S. 2014. “PMA Sounds Fun”: Negotiating Drug Discourses Online. Substance Use & Misuse, 49, 987-998. BARRATT, M. J., CAKIC, V. & LENTON, S. 2013. Patterns of synthetic cannabinoid use in Australia. Drug and Alcohol Review, 32, 141-146. BARRATT, M. J., KOWALSKI, M., MAIER, L. J. & RITTER, A. 2018. Global review of drug checking services operating in 2017. Drug Policy Modelling Program Bulletin No. 24. Sydney: National Drug and Alcohol Research Centre. BARRATT, M. J., LATIMER, J., JAUNCEY, M., TAY, E. & NIELSEN, S. 2017a. Establishing a surveillance study for early detection of fentanyl-laced heroin in Australia. The 2017 Australasian Professional Society on Alcohol & other Drugs Conference, 12-15 November 2017, Melbourne, Australia BARRATT, M. J., SEEAR, K. & LANCASTER, K. 2017b. A critical examination of the definition of ‘psychoactive effect’ in Australian drug legislation. International Journal of Drug Policy, 40, 16-25. BECK, J. 1998. 100 Years of "Just Say No" Versus "Just Say Know":Reevaluating Drug Education Goals for the Coming Century. Evaluation Review, 22, 15-45. BELACKOVA, V. & VACCARO, C. A. 2013. “A Friend With Weed Is a Friend Indeed”: Understanding the Relationship Between Friendship Identity and Market Relations Among Marijuana Users. Journal of Drug Issues. BOUMBA, V. A., DI RAGO, M., PEKA, M., DRUMMER, O. H. & GEROSTAMOULOS, D. 2017. The analysis of 132 novel psychoactive substances in human hair using a single step extraction by tandem LC/MS. Forensic Sci Int, 279, 192-202. BOYS, A., MARSDEN, J. & STRANG, J. 2001. Understanding reasons for drug use amongst young people: a functional perspective. Health Education Research, 16, 457-469. BRIGHT, S.J., BISHOP, B., KANE, R., MARSH, A., BARRATT, M.J., 2013., Kronic hysteria: Exploring the intersection between Australian synthetic cannabis legislation, the media, and drug- related harm. International Journal of Drug Policy. doi:10.1016/j.drugpo.2012.12.002.

172

BRIGHT, D. & SUTHERLAND, R. 2017. "Just doing a favor for a friend": The social supply of ecstasy through friendship networks. Journal of Drug Issues, 47, 492-504. BRUNT, T. 2017. Drug checking as a harm reduction tool for recreational drug users: opportunities and challenges Luxenbourg: European Monitoring Centre for Drugs and Drug Addiction. BUTTERFIELD, R. J., BARRATT, M. J., EZARD, N. & DAY, R. O. 2016. Drug checking to improve monitoring of new psychoactive substances in Australia. Med J Aust, 204, 144-5. CAIRNS, R., BROWN, J. A., GUNJA, N. & BUCKLEY, N. A. 2017. The impact of Australian legislative changes on synthetic cannabinoid exposures reported to the New South Wales Poisons Information Centre. International Journal of Drug Policy, 43, 74-82. CALDICOTT, D., BRIGHT, S. & BARRATT, M. 2013. NBOMe - a very different kettle of fish. The Medical Journal of Australia, 199, 322-323. CHILDREN’S HEALTH QUEENSLAND HOSPITAL AND HEALTH SERVICE 2014. Queensland Poisons Information Centre. Annual Report 2014. South Brisbane: Children’s Health Queensland Hospital and Health Service. CLINICAL GUIDELINES ON DRUG MISUSE AND DEPENDENCE UPDATE 2017 INDEPENDENT EXPERT WORKING GROUP (2017). Drug misuse and dependence: UK guidelines on clinical management. London: Department of Health CORAZZA, O., SIMONATO, P., CORKERY, J., TRINCAS, G. & SCHIFANO, F. 2014. "Legal highs": Safe and legal "heavens"? A study on the diffusion, knowledge and risk awareness of novel psychoactive drugs among students in the UK. Rivista di Psichiatria, 49, 89-94. COWIE, T., BUCCI, N. & HOUSTON, C. 2017. Police defend decision not to warn public of new drug after Melbourne club deaths. The Age, February 7. CROSSLEY, M. L. 2002. Introduction to the Symposium 'Health Resistance': The limits of contemporary health promotion. Health Education Journal, 61, 101-112. DARKE, S. 1998. Self-report among injecting drug users: A review. Drug & Alcohol Dependence, 51, 253-263. DRAPALOVA, E. & BELACKOVA, V. 2018. How to ask about use of new psychoactive substances to increase validity of results in self-report prevalence surveys. The International Society for the Study of Drug Policy. Vancouver, Canada. DUFF, C. 2008. The pleasure in context. International Journal of Drug Policy, 19, 384-392. ENERGY CONTROL 2017. Our International Drug Testing Service detects a dangerous mixture from Australia. [updated February 4. Available from: http://energycontrol- international.org/our-international-drug-testing-service-detects-a-dangerous-mixture- from-australia/. ESRICK, J., KAGAN, R. G., CARNEVALE, J. T., VALENTI, M., ROTS, G. & DASH, K. 2018. Can scare tactics and fear-based messages help deter substance misuse: a systematic review of recent (2005–2017) research. Drugs: Education, Prevention and Policy, 1-10. EUROPEAN COMMISSION 2014. Young people and drugs. Flash Eurobarometer 401. Flash Eurobarometer 401. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016a. EU Drug Markets Report. In-depth Analysis. Luxembourg: Publications Office of the European Union.

173

EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016b. Recent changes in Europe's MDMA/ecstasy market. Results from an EMCDDA trendspotter study. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2016c. Health responses to new psychoactive substances. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017a. European Drug Report 2017: Trends and Developments. Luxembourg: Publications Office of the European Union. EUROPEAN MONITORING CENTRE FOR DRUGS AND DRUG ADDICTION 2017b. United Kingdom. Country Drug Report 2017. Luxenbourg: European Monitoring Centre for Drugs and Drug Addiction. EVANS, J. 2017. Woman hospitalised with seizures after fake MDMA discovered in Canberra. ABC, 24 February. FAVRETTO, D., PASCALI, J. P. & TAGLIARO, F. 2013. New challenges and innovation in forensic toxicology: Focus on the “New Psychoactive Substances”. Journal of Chromatography A, 1287, 84-95. FERGUSON, R. 2018. Teenager in critical condition after PMA overdose. The Australian, 29 January 2018. FOWLER, G., KINNER, S. & KRENSKE, L. 2007. Containing ecstasy: analytical tools for profiling an illegal drug market. Monograph Series No. 27. Hobart: National Drug Law Enforcement Research Fund. GAO, T., DU, P., XU, Z. & LI, X. 2017. Occurrence of new psychoactive substances in wastewater of major Chinese cities. Science of the Total Environment, 575, 963-969. GLAVAK TKALIĆ, R., SUČIĆ, I. & DEVIĆ, I. 2013. Motivation for Substance Use: Why Do People Use Alcohol, Tobacco and Marijuana? Društvena istraživanja, 22, 601-625. GRIGG, J., LENTON, S., SCOTT, J. & BARRATT, M. 2015. Social supply of cannabis in Australia. Canberra: National Drug Law Enforcement Research Fund. GROVES, A. 2018. ‘Worth the test?’ Pragmatism, pill testing and drug policy in Australia. Harm Reduction Journal, 15, 12. HILL, D., CHAPMAN, S. & DONOVAN, R. 1998. The return of scare tactics. Tobacco Control, 7, 5- 8. HOLLOWAY, K. & BENNETT, T. 2018. Characteristics and correlates of drug use and misuse among university students in Wales: a survey of seven universities. Addiction Research and Theory, 26, 11-19. HOME OFFICE 2017. Drug Misuse: Findings from the 2016/17 Crime Survey for England and Wales. Statistical Bulletin 11/17. London: Home Office. HUGHES, C. 2012. 'Trafficking'or 'personal use': Do regular drug users understand Australian drug trafficking laws? Australasian Professional Society on Alcohol and other Drugs conference. Melbourne, Australia. HUGHES, C. 2014. Drugs & the law. What you need to know. Sydney: National Drug and Alcohol Research Centre.

174

HUGHES, C., RITTER, A., CHALMERS, J., LANCASTER, K., BARRATT, M. J. & MOXHAM-HALL, V. 2016. Decriminalisation of drug use and possession in Australia – A briefing note. Sydney: Drug Policy Modelling Program, NDARC, UNSW Australia. HUGHES, C., RITTER, A., COWDERY, N. & PHILLIPS, B. 2014a. Evaluating Australian drug trafficking thresholds: Proportionate, equitable and just? Canberra: Australian Institute of Criminology. HUGHES, C. E., RITTER, A., COWDERY, N. & SINDICICH, N. 2014b. ‘Trafficking’ or ‘personal use’: Do people who regularly inject drugs understand Australian drug trafficking laws? Drug and Alcohol Review, 33, 658-666. HULL, P., MAO, L., ROSSTEUSCHER, K., MARION-LANDAIS, S., PRESTAGE, G., ZABLOTSKA, I., DE WIT, J. & HOLT, M. 2014. Gay Community Periodic Survey: Canberra 2013. Sydney: Centre for Social Research in Health, UNSW Australia. JOHNSTON, L. D., MIECH, R. A., O'MALLEY, P. M., BACHMAN, J. G., SCHULENBERG, J. E. & PATRICK, M. E. 2018. Monitoring the Future national survey results on drug use: 1975–2017: Overview, key findings on adolescent drug use. The University of Michigan: Institute for Social Research. KARLSSON, A. & BURNS, L. 2018. Australian Drug Trends 2017. Findings from the Illicit Drug Reporting System (IDRS). Australian Drug Trends Series No. 181. Sydney: National Drug and Alcohol Research Centre. KHALED, S. M., HUGHES, E., BRESSINGTON, D., ZOLEZZI, M., RADWAN, A., BADNAPURKAR, A. & GRAY, R. 2016. The prevalence of novel psychoactive substances (NPS) use in non- clinical populations: a systematic review protocol. Systematic Reviews, 5, 195. KINYUA, J., NEGREIRA, N., MISEREZ, B., CAUSANILLES, A., EMKE, E., GREMEAUX, L., DE VOOGT, P., RAMSEY, J., COVACI, A. & VAN NUIJS, A. L. N. 2016. Qualitative screening of new psychoactive substances in pooled urine samples from Belgium and United Kingdom. Sci Total Environ, 573, 1527-1535. KYRIAKOU, C., PELLEGRINI, M., GARCÍA-ALGAR, O., MARINELLI, E. & ZAAMI, S. 2017. Recent Trends in Analytical Methods to Determine New Psychoactive Substances in Hair. Current neuropharmacology, 15, 663-681. LADER, D. (2015). Drug Misuse: Findings from the 2014/15 Crime Survey for England and Wales. Retrieved from London: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attach ment_data/file/462885/drug-misuse-1415.pdf LANCASTER, K., SEEAR, K. & RITTER, A. 2017. Making medicine; producing pleasure: A critical examination of medicinal cannabis policy and law in Victoria, Australia. International Journal of Drug Policy, 49, 117-125. LAWN, W., BARRATT, M., WILLIAMS, M., HORNE, A. & WINSTOCK, A. 2014. The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. Journal of Psychopharmacology, 28, 780-788. LEA, T., REYNOLDS, R. & DE WIT, J. 2011. Mephedrone use among same-sex attracted young people in Sydney, Australia. Drug and Alcohol Review, 30, 438-440. LIECHTI, M. 2015. Novel psychoactive substances (designer drugs): overview and pharmacology of modulators of monoamine signaling. Swiss Med Wkly, 145, w14043. LINNELL, M. 2017. Spice: Synthetic Cannabinoids (SCRAs). New Psychoactive Substances. Briefing for professionals. Manchester: Manchester Health & Care Commissioning. 175

MATTHEWS, A., SUTHERLAND, R., PEACOCK, A., VAN BUSKIRK, J., WHITTAKER, E., BURNS, L. & BRUNO, R. 2016 I like the old stuff better than the new stuff? Subjective experiences of new psychoactive substances. International Journal of Drug Policy, 40, 44-49. MOORE, D. 2008. Erasing pleasure from public discourse on illicit drugs: On the creation and reproduction of an absence. International Journal of Drug Policy, 19, 353-358. MORELATO, M., BEAVIS, A., TAHTOUH, M., RIBAUX, O., KIRKBRIDE, P. & ROUX, C. 2014. The use of organic and inorganic impurities found in MDMA police seizures in a drug intelligence perspective. Sci Justice, 54, 32-41. MULLENS, A. B., RAY, M. & FEIN, E. 2017. 'Queensland Chemsex Study': Results from a cross- sectional survey of gay and other homosexually active men in Queensland - substance use and sexual activity. Industry report in partnership with the Queensland AIDS Council. Ipswich: University of Southern Queensland. NATIONAL ADVISORY COMMITTEE ON DRUGS AND ALCOHOL 2016. Prevalence of drug use and gambling in Ireland and drug use in Northern Ireland. Dublin: Department of Health. NATIONAL STATEMENT ON ETHICAL CONDUCT IN HUMAN RESEARCH 2007 (Updated 2018). The National Health and Medical Research Council, the Australian Research Council and Universities Australia. Commonwealth of Australia, Canberra NICHOLAS, R. 2008. The impact of social networks and not-for-profit illicit drug dealing on illicit drug markets in Australia. Hobart: National Drug Law Enforcement Research Fund. O'MALLEY, P. & VALVERDE, M. 2004. Pleasure, Freedom and Drugs: The Uses of 'Pleasure' in Liberal Governance of Drug and Alcohol Consumption. Sociology, 38, 25-42. ORSOLINI, L., PAPANTI, G. D., FRANCESCONI, G. & SCHIFANO, F. 2015. Mind Navigators of Chemicals' Experimenters? A Web-Based Description of E-Psychonauts. Cyberpsychology, Behavior, and Social Networking, 18, 296-300. PALAMAR, J. J. 2015. “Bath salt” use among a nationally representative sample of high school seniors in the United States. The American Journal on Addictions, 24, 488-491. PALAMAR, J. J., ACOSTA, P., CALDERON, F. F., SHERMAN, S. & CLELAND, C. M. 2017a. Assessing self-reported use of new psychoactive substances: The impact of gate questions. Am J Drug Alcohol Abuse, 43, 609-617. PALAMAR, J. J., BARRATT, M. J., CONEY, L. & MARTINS, S. S. 2017b. Synthetic Cannabinoid Use Among High School Seniors. Pediatrics, 140. PALAMAR, J. J. & LE, A. 2018 (in press). Trends in DMT and other tryptamine use among young adults in the United States. The American Journal on Addictions. PALAMAR, J. J., SALOMONE, A., GERACE, E., DI CORCIA, D., VINCENTI, M. & CLELAND, C. M. 2017c. Hair testing to assess both known and unknown use of drugs amongst ecstasy users in the electronic dance music scene. Int J Drug Policy, 48, 91-98. PALAMAR, J. J., SALOMONE, A., VINCENTI, M. & CLELAND, C. M. 2016. Detection of "bath salts" and other novel psychoactive substances in hair samples of ecstasy/MDMA/"Molly" users. Drug Alcohol Depend, 161, 200-5. PENNAY, A. 2015. “What goes up must go down”: An exploration of the relationship between drug-related pleasure and harm experienced by a sample of regular “party drug” users. Drugs: Education, Prevention and Policy, 22, 185-192. PETERS, G.-J. Y. & KOK, G. 2009. A structured review of reasons for ecstasy use and related behaviours: pointers for future research. BMC Public Health, 9, 230. 176

PREKUPEC, M. P., MANSKY, P. A. & BAUMANN, M. H. 2017. Misuse of Novel Synthetic Opioids: A Deadly New Trend. Journal of Addiction Medicine, 11, 256-265. RACE, K. 2008. The use of pleasure in harm reduction: perspectives from the history of sexuality. Int J Drug Policy, 19, 417-23. RIGG, K. K. 2017. Motivations for Using MDMA (Ecstasy/Molly) among African Americans: Implications for Prevention and Harm-Reduction Programs. Journal of Psychoactive Drugs, 49, 192-200. RITTER, A. 2014. Where is the pleasure? Addiction, 109, 1587-1588. ROBERTS, G. 2016. N Bomb, NPS's among hundreds of deadly new 'party drugs' on Australian market for summer, experts warn. ABC Online, 6 November 2016. ROXBURGH, A., VAN BUSKIRK, J., BURNS, L. & BRUNO, R. 2017. Drugs and the Internet, Issue 9, December 2017. Sydney: National Drug and Alcohol Research Centre. SCHNUER, G. 2013. Pleasure and excess: Using Georges Bataille to locate an absent pleasure of consumption. Addiction Research and Theory, 21, 258-268. SIMPSON, J. K. 2017. Appeal to fear in health care: appropriate or inappropriate? Chiropractic & Manual Therapies, 25, 27. SINDICICH, N. & BURNS, L. 2013. Australian Trends in Ecstasy and related Drug Markets 2011. Findings from the Ecstasy and Related Drugs Reporting System (EDRS) Australian Drug Trend Series No. 100. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. SINDICICH, N., STAFFORD, J. & BREEN, C. 2016. Australian Trends in Ecstasy and Related Drug Markets 2015. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 154. . Sydney: National Drug and Alcohol Research Centre, UNSW Australia. SOAMES JOB, R. F. 1988. Effective and ineffective use of fear in health promotion campaigns. American Journal of Public Health, 78, 163-167. SOUSSAN, C., ANDERSSON, M. & KJELLGREN, A. 2018. The diverse reasons for using Novel Psychoactive Substances - A qualitative study of the users' own perspectives. International Journal of Drug Policy, 52, 71-78. SOUSSAN, C. & KJELLGREN, A. 2015. “Chasing the high” – Experiences of ethylphenidate as described on international internet forums. Substance Abuse: Research and Treatment, 9, 9-16. TAZZITE, A., ROKY, R. & AVARD, D. 2009. The ethical implications of conserving biological samples. J Int Bioethique, 20, 87-96, 150-1. TINDANA, P., MOLYNEUX, C. S., BULL, S. & PARKER, M. 2014. Ethical issues in the export, storage and reuse of human biological samples in biomedical research: perspectives of key stakeholders in Ghana and Kenya. BMC Medical Ethics, 15, 76. UPOROVA, J., KARLSSON, A., SUTHERLAND, R. & BURNS, L. 2018. Australian Trends in Ecstasy and related Drug Markets 2017. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No. 190. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. VERWEIJ, A. 1992. Impurities in Illicit Drug Preparation: 3, 4-(Methylenedioxy) amphetamine and 3, 4-(Methylenedioxy) methamphetamine. Forensic Science Review, 4, 137-137. 177

WAKEFIELD, M. A., LOKEN, B. & HORNIK, R. C. 2010. Use of mass media campaigns to change health behaviour. Lancet, 376, 1261-1271. WILKINS, C., & SWEETSUR, P. (2013). The impact of the prohibition of benzylpiperazine (BZP) ‘legal highs’ on the prevalence of BZP, new legal highs and other drug use in New Zealand. Drug and Alcohol Dependence, 127(1–3), 72-80. doi:http://dx.doi.org/10.1016/j.drugalcdep.2012.06.014 WINSTOCK, A. R. & BARRATT, M. J. 2013a. The 12-month prevalence and nature of adverse experiences resulting in emergency medical presentations associated with the use of synthetic cannabinoid products. Human Psychopharmacology: Clinical and Experimental, 28, 390-393. WINSTOCK, A. R. & BARRATT, M. J. 2013b. Synthetic cannabis: A comparison of patterns of use and effect profile with natural cannabis in a large global sample. Drug and Alcohol Dependence, 131, 106-111. WINSTOCK, A. R., LAWN, W., DELUCA, P. & BORSCHMANN, R. 2016. Methoxetamine: An early report on the motivations for use, effect profile and prevalence of use in a UK clubbing sample. Drug and Alcohol Review, 35, 212-217. WITTE, K. & ALLEN, M. 2000. A Meta-Analysis of Fear Appeals: Implications for Effective Public Health Campaigns. Health Education & Behavior, 27, 591-615. WONGUPPA, R. & KANATO, M. 2017. The prevalence and associated factors of new psychoactive substance use: A 2016 Thailand national household survey. Addictive Behaviors Reports.

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7. CONCLUSION

The overall aim of this thesis was to examine NPS in the Australian context. Although there has been international interest in the NPS phenomenon, much of the research in this area either: (1) originates from Europe and the United States (with Australian-specific studies relatively scarce); or (2) examines NPS as a single entity or focuses on an individual NPS, thus limiting the ability to examine differences across NPS. Combined, the findings presented in this thesis address these research gaps, providing a more detailed picture of both the Australian NPS market and Australian NPS consumers.

With regards to the Australian NPS market, this thesis contains the first documentation of trends in use of different NPS classes (2010-2017). Paper two found that the popularity of NPS classes had changed significantly over time, concluding that Australia’s NPS market is dynamic and rapidly evolving. Importantly, the trends documented in paper two appear to correspond with the motivations (paper three) and pleasure ratings (Appendix C) endorsed for specific substances, such that substances motivated by ‘opportunistic’ reasons were found to have declined in use over time, whilst substances motivated by the pleasurable or desirable qualities of that substance had increased in use. Taken together, these findings suggest that DMT, NBOMe and 2C-x will likely persist within Australia’s recreational drug markets, whilst SCRA will not. Of course, given the dynamic nature of the NPS market it is impossible to predict its future with any certainty, and it is essential that existing drug monitoring systems continue to track the evolution of these substances. Such monitoring systems should also develop the capacity to measure unintentional NPS use, either through biological sampling or drug checking, so that harmful substances can be identified more quickly.

With regards to NPS consumers, this thesis identified that there was no distinct group of exclusive NPS consumers (i.e. consumers who use NPS but no other illicit substances), at least in the Australian context. Rather, Australian NPS consumers were found to be a heterogenous group of (primarily) existing drug consumers. There were substantial differences in characteristics, motivations and purchasing and supply patterns across NPS classes, highlighting the importance of recognising NPS consumers as a diverse group. Importantly, however, the findings detailed in this thesis suggest that NPS use may be a marker for higher engagement in substance use, and as such higher risk patterns of use. This suggests that there may not need to be specialised NPS interventions, but rather, that existing (primarily acute) health services should screen for and be equipped to deal with NPS-related presentations.

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8. APPENDICES Appendix A: Chapter 15: New & emerging psychoactive substances

Rachel Sutherland1 & Monica J. Barratt1,3,4

1National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia 3National Drug Research Institute, Faculty of Health Sciences, Curtin University, Perth, WA, 6845, Australia 4Behaviours and Health Risks Program, Burnet Institute, 85 Commercial Rd, Melbourne VIC 3004, Australia

Sutherland, R. & Barratt, M.J. (2017) ‘New & emerging psychoactive substances’ in A Quick Guide to Drugs & Alcohol, third edition (87-93). Sydney; Drug Info, State Library of NSW https://yourroom.health.nsw.gov.au/publicationdocuments/quick-guide-ed3.pdf

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CHAPTER 15: NEW & EMERGING PSYCHOACTIVE SUBSTANCES

(otherwise known as) research chemicals, analogues, legal highs, herbal highs, synthetic drugs, designer drugs, novel psychoactive substances, bath salts

What are new and emerging psychoactive substances?

There are multiple terms in use globally that refer broadly to new, novel or emerging drugs. Terms such as ‘designer drugs’, ‘research chemicals’ and ‘emerging psychoactive substances’ are often used interchangeably with ‘NPS’ (new psychoactive substances), however as outlined below, they have slightly different definitions.

New Psychoactive Substances (NPS)

These are substances that are not controlled by the 1961 Convention on Narcotic Drugs or the 1971 Convention of Psychotropic Substances, but which may pose a public health threat similar to drugs that are listed in these conventions.

Designer drugs

Designer drugs are manufactured to mimic the effects of a controlled substance. These close copies are referred to as ‘analogues’. The purpose of creating these analogues is to avoid detection or classification as ‘illegal’.

Emerging psychoactive substances (EPS)

This is a term used to describe psychoactive drugs that are relatively new to recreational drug markets. This term captures all NPS as well as drugs that may not be newly invented, but have recently experienced a resurgence, or increase in use.

Research chemicals

These are experimental chemicals not approved for human use; many of these chemicals were discovered in labs and examined in test-tubes (in vitro) or in low-level animal studies.

The terms ‘synthetic drugs’ and ‘legal highs’ can cause confusion when used to refer to NPS. This confusion stems from:

1. the fact that many ‘traditional’ illegal drugs, such as LSD, methamphetamine and MDMA (ecstasy), are also synthesised; and 2. many countries (including Australia) have moved to prohibit these substances, despite remaining ‘legal’ at the international level.

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This chapter focuses on NPS as defined above; however, it also looks at some EPS (2C series, DMT). The NPS market has grown rapidly over the past decade and currently encompasses hundreds of different substances, which can be classified into a number of different categories (outlined below). In Australia, synthetic cannabinoids have been the most widely used NPS, although stimulant and psychedelic NPS are also relatively common.

Synthetic cannabinoids

Synthetic cannabinoids (eg, Spice, K2, Kronic, Northern Lights, Kaos) are substances that are functionally similar to the primary substance responsible for the psychoactive effects of cannabis. They are generally sold in foil sachets and typically contain 1-3 grams of dried plant matter onto which the synthetic cannabinoid has been sprayed. More recently, liquid products containing synthetic cannabinoids have emerged for use with electronic cigarettes.

While the side effects of cannabis are well known, information on the health risks associated with synthetic cannabinoid use remains limited. Research to date suggests that the adverse effects of synthetic cannabinoid use may include:

• cardiovascular events • acute kidney injury • seizures • psychiatric problems • persistent severe vomiting • abnormally fast heartbeat (tachycardia) • agitation • nausea.

Phenethylamines

Phenethylamines refer to a class of drugs with psychoactive and stimulant effects and includes amphetamine, methamphetamine and MDMA (ecstasy) — all of which are controlled under the 1971 Convention of Psychotropic Substances and are therefore not classified as NPS. Examples of phenethylamine NPS in Australia include the ‘2C series’, the NBOMe series, PMMA, and benzodifurans (Bromo-Dragonfly).

The 2C series are a group of psychedelic phenethylamines, with 2C-B being the most frequently reported ‘new’ phenethylamine. 2C-B has been described as a cross between LSD and ecstasy and is usually consumed in either powder or pill form. 2C-B first gained popularity internationally in the mid-1980s and was brought under international control in 2001, which means that it is no

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longer strictly classified as an NPS (as is the case with a number of the 2C series). However, in the Australian context, 2C-B is often still considered to be an ‘emerging’ psychoactive substance due to the fact that it is relatively new to the recreational drug scene.

The NBOMe series are a group of phenethylamines that contain an N-methoxybenzyl group. The most common of the NBOMe series are derivatives of the 2C-series (but more potent) and appeared on recreational markets in 2010. Compounds of the NBOMe series are not active when swallowed, and are usually taken by placing them under the tongue (sublingually). There have been reports of NBOMe being sold as LSD (when deposited on blotter paper LSD and NBOMe are virtually identical in appearance), which is concerning given that the effects of NBOMe are active at very low doses. Information on the health risks associated with use of these drugs is limited, however research suggests that the adverse effects of NBOMe toxicity may include:

• cardiovascular complications • agitation • seizures • elevated body temperature (hyperthermia) • imbalance of acids in the body (metabolic acidosis) • abnormally fast heartbeat (tachycardia) • organ failure • death.

Synthetic cathinones

Synthetic cathinones are closely related to the phenethylamine family and typically have an amphetamine-type analogue. Examples of synthetic cathinones in Australia include Mephedrone (‘Meow Meow’, ‘M-CAT’); Methylone; MDPV (‘Ivory wave’); alpha-PVP (‘flakka’). Synthetic cathinones first appeared in drug markets in the mid-2000s, with methylone the first to be reported. Mephedrone is perhaps the most well-known of the synthetic cathinones — it first appeared online as an NPS between 2007 and 2009 (although reported to have first been synthesised in 1929). Mephedrone became increasingly common in Europe; however, it never gained much prominence in Australia. Mephedrone is mostly available in powder form, although it can also be pressed into pill form, and is usually snorted or ingested.

Research suggests that some of the health risks associated with the use of synthetic cathinones may include:

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• anxiety • agitation • chest pain • abnormal sensation, typically tingling or prickling of the skin (paraesthesia) • heart palpitations • seizures • abnormally fast heartbeat (tachycardia) • high blood pressure (hypertension) • dependence.

Tryptamines

Some tryptamines are natural neurotransmitters (brain chemicals), but most are psychoactive hallucinogens found in plants, fungi and animals. For information on natural tryptamines, see Chapter 14, Natural hallucinogens page 83.

DMT does not fall under the NPS definition mentioned above, but it could be classified as an emerging psychoactive substance in that it is relatively new to Australia’s recreational drug scene. 5-Meo-DMT is a powerful psychedelic that is found in a wide variety of plant species, and in the venom of the Bufo alvarius toad. It has been used by South American shamans for thousands of years, and was first synthesised in 1936. It is similar to DMT in effects, however it is substantially more potent and is usually smoked or snorted. Little is currently known about the short and long-term health effects of tryptamine use.

Piperazines

Piperazines have been described as ‘failed pharmaceuticals’, and are frequently sold as ecstasy due to their central nervous system stimulant properties. They are usually available in pill, capsule or powder form and are usually swallowed. Benzylpiperazine (BZP) is one of the most commonly reported piperazine NPS and was initially developed as a potential antidepressant drug. However, it was found to have similar properties to amphetamine and was therefore considered liable to abuse. BZP is often used in combination with trifuoromethylphenylpiperazine (TFMPP) to produce similar effects to ecstasy, however with less potency. Many of the piperazine NPS have limited information regarding the short and long term health effects of their use.

Research suggests that some of the health harms associated with BZP and TFMPP use may include:

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• headaches • tremors • poor concentration • palpitations • vomiting • anxiety • confusion • increased body temperature (hyperthermia) • destruction of muscle cells • kidney failure • seizures • dizziness • dilation of the pupils • insomnia • urine retention.

Novel benzodiazepines

Novel benzodiazepines are less well categorised and understood than other NPS; their interaction with the human body, as well as how similar they are to established agents, remain relatively unknown. Pyrazolam was the first novel benzodiazepine to appear as an NPS, having originally been a research trial drug that did not proceed to clinical use. Other novel benzodiazepines that have appeared online include:

• diclazepam • fubromazepam • clonazolam • deschloroetizolam • fubromazolam • nifoxipam • meclonazepam • etizolam.

None of these have been approved for medicinal use in any country. Little is currently known about the short and long-term health effects associated with the use of novel benzodiazepines.

Other NPS

There are a range of other NPS categories including: 185

• aminoindanes (for example, MDAI) • arylcyclohexylamines (for example, Methoxetamine); a class of compounds which typically produce dissociative anaesthesia, a form of anaesthesia that does not necessarily cause unconsciousness but produces other affects such as analgesia, catatonia and amnesia • ketamine; classified as a NPS since it is not controlled under UN conventions (see page 76 for further information) • opioids (for example, fentanyl analogues) • plant-based NPS (plants with psychoactive properties; for example, kratom, khat, Salvia divinorum; see page 83).

NPS and the law

The laws surrounding NPS are complex and vary across jurisdictions. In 2011, Western Australia was the first government to ban individual synthetic cannabinoids. Most Australian jurisdictions followed suit shortly thereafter, and in July 2011 it became a federal offence to possess eight specific cannabinoid agonists. In 2012, the Therapeutic Goods Administration introduced a blanket ban on any type of synthetic cannabinoid that produces the same pharmacological effect as cannabis.

In order to deal with the rapid growth in the number of NPS, from 2013 onwards some Australian states (including Queensland, NSW, South Australia and Western Australia) introduced blanket bans on possessing or selling any substance that has a psychoactive effect (exempting alcohol, tobacco and food). In other Australian jurisdictions, specific NPS are banned with additional NPS regularly added to the list. Commonwealth laws are also in place that ban any substance with a psychoactive effect that is not otherwise covered by existing legislation. It is the importer’s responsibility to prove that a substance falls into an exemption category.

Effects

There is currently limited information available on the short and long term health risks associated with NPS use, their addiction potential, interaction with other drugs and their impact upon driving behaviour. Some of the adverse effects of specific NPS are outlined in the sections above.

A difficulty of understanding the effects of these new substances is that they are not always consumed intentionally. For example, it was reported that the NPS 25I-NBOMe was being sold as LSD in Australia. Monitoring systems that do not include forensic analysis of drug samples or testing of bodily fluids will 186

not be able to accurately match reported effects and adverse events with the substances consumed.

NPS and pregnancy

Little is known about the effects of NPS on an unborn child. However, many drugs and medications taken during pregnancy cross the placenta or are present in breast milk. Therefore, it is likely that NPS may be dangerous to pregnant women and their unborn babies.

It is generally considered risky to take any drug while pregnant or breastfeeding without medical advice.

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Appendix B: NPS reported to the EMCDDA

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 4-MTA (4-Methylthioamphetamine) <2005 √ I, 1971 2C-I (2,5-Dimethoxy-4-iodophenethylamine) <2005 √ 2C-D (2,5-Dimethoxy-4-methylphenethylamine) <2005 2C-E (2,5-Dimethoxy-4-ethylphenethylamine) <2005 √ 2C-H (2,5-Dimethoxyphenethylamine) <2005 2C-T-2 (2,5-Dimethoxy-4-ethylthiophenethylamine) <2005 2C-T-7 (2,5-Dimethoxy-4-propylthiophenethylamine) <2005 MBDB (1,3-Benzodioxolyl-N-methylbutanamine) <2005 √ × TMA-2 (2,4,5-Trimethoxyamphetamine) <2005 PMMA (para-Methoxymethamphetamine) <2005 √ I, 1971 Chloro-MDMA <2005 DPT (N,N-di-n-propyltryptamine) <2005 AMT (α-Methyltryptamine) <2005 √ × 5-MeO-DMT (5-methoxy-N,N-dimethyltryptamine) <2005 5-MeO-AMT (5-methoxy-α-methyltryptamine) <2005 5-MeO-DIPT (5-Methoxy-N,N-diisopropyltryptamine) <2005 5-MeO-T (5-Methoxytryptamine) <2005 4-AcO-DET (4-Acetoxy-N,N-diethyltryptamine) <2005 5-MeO-MIPT (5-Methoxy-N-methyl-N-isopropyltryptamine) <2005 √ 5-MeO-DET (5-methoxy-N,N-diethyltryptamine) <2005 5-HO-DMT (N,N-dimethylserotonin) <2005 4-HO-MIPT (4-Hydroxy-N-methyl-N-isopropyltryptamine) <2005 4-AcO-MIPT (4-Acetoxy-N-methyl-N-isopropyltryptamine) <2005 Ketamine <2005 √ × GHB (γ-Hydroxybutyric acid) <2005 √ II, 1971 MOPPP (4-methoxy-α-pyrrolidinopropiophenone) <2005 BZMeP (1-benzyl-4-methyl-piperazine) <2005

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Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ TFMPP (m-trifluoromethylphenylpiperazine) <2005 √ × √ BZP (benzylpiperazine) <2005 √ II, 1971 √ PEA (1-phenethylamine) <2005 N-Me-PEA (N-methyl-1-phenethylamine) <2005 4-Me-PEA (4-methyl-1-phenethyl-amine) <2005 1-phenyl-3-butanamine <2005 N-AcAp (N-acetylamphetamine) <2005 NOHA (N-hydroxyamphetamine) <2005 Dimethylamphetamine <2005 MDDMA <2005 37# mCPP (1-(3-chlorophenyl)piperazin)/CPP (chlor-phenyl-piperazine) 2005 √ × 4-HO-DIPT (4-hydroxy-N,N-diisopropyltryptamine) 2005 methylone (3,4-methylenedioxymethcathinone) 2005 √ II, 1971 √ 4-HO-DET (4-hydroxy-N,N-diethyltryptamine) 2005 DIPT (diisopropyltryptamine) 2005 MeOPP 1-(4-methoxyphenyl)-piperazine 2005 √ × MDHOET (3,4-methylenedioxy-N-(2-hydroxyethyl)amphetamine 2005 2C-P (2,5-dimethoxy-4-(n)-propylphenethylamine) 2005 5MeO-AMT (5-Methoxy--methyltryptamine) 2005 5MeO-DET (5-Methoxy-N,N-diethyltryptamine) 2005 MIPT (N-Methyl-N-isopropyltryptamine) 2005 2C-T-4 (2,5-dimethoxy-4-isopropylthiophenethylamine) 2005 4-AcO-DIPT (4-acetoxy-N,N-diisopropyltryptamin) 2005 DPIA (Di-(-phenylisopropyl)amine) 2005 14 pFPP (p-Fluorophenylpiperazine) 2006

189

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ pCPP (1-4 chloro phenyl piperazine) 2006 DBZP (1, 4-Dibenzylpiperazine) 2006 2,4-DMA (2,4-dimethoxy-alpha-methylbenzeneethanamine) (or 2,5-DMA (2,5- 2006 dimethoxy-alpha-methylbenzeneethanamine)) 2-aminoindan (1H-Inden-2-amine, 2,3-dihydro; or 1-aminoindan (1H-Inden-1- 2006 amine, 2,3-dihydro) Bromo-Dragonfly (Bromo-benzodifuranyl-isoprophylamine) 2006

DOI (4-iodo-2,5-dimethoxyamphetamine) 2006 √ 7 2C-B-Fly (8-bromo-2,3,6,7-benzo-dihydro-difuran-ethylamine) 2007 5-MeO-Dalt (N,N-diallyl-5-methoxytryptamine) 2007 √ N-ethyl-2C-B (N-ethyl- 4-Bromo-2,5-dimethoxybenzeneethanamine) 2007 Vanoxerine (1-[2-[bis(4-fluorophenyl)methoxy]ethyl]-4-(3- 2007 phenylpropyl)piperazine) D2PM (proposed code name) ((S)-(-)-,-Diphenyl-2-pyrrolidinylmethanol) 2007 N-Acetyl-DOB (N-Acetyl-4-bromo-2,5-dimethoxyamphetamine) 2007 1-PEA (1-Phenylethylamine) 2007 Gelbes (working name) (1-(3-chlorophenyl)-4-(3Chloropropyl)piperazine 2007 hydrochloride) NMPEA (proposed code name) (N methyl Phenylethylamine) 2007 Glaucine (International non-proprietary name) ((6aS)-1,2,9,10- 2007 tetramethoxyaporphine) Fenazepam (7-brom-5/o-chlorphenyl/1,2-dihydro-3H-1,4-benzodiazepin-2-on) 2007 Nimetazepam (2-methyl-9-nitro-6-phenyl-2,5-diazabicyclo[5.4.0]undeca-5,8,10,12- 2007 √ IV, 1971 tetraen-3-one) N-desmethylsibutramine 2007 Bufotenine (3-(2-dimethylaminoethyl)-1H-indol-5-ol) 2007 Harmine (7-Methoxy-1-methyl-9H-pyrido[3,4-b]indole) 2007 Salvia Divinorum 2007

190

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 16 bk-MBDB (2-methylamino-1-(3,4-methylenedioxyphenyl)butan-1-one) 2008 √ Ethylcathinone/Subcoca I (2-Ethylamino-1-phenylpropan-1-one) 2008 Mephedrone/Subcoca II (2-Methylamino-1-p-tolylpropan-1-one) 2008 √ II, 1971 √ Kratom (Mitragynin/7α-Hydroxy-7H-mitragynin/Paynanthein) 2008 4-HO-MET (4-hydroxy-N-methyl-N-ethyltryptamin) 2008 Kava (Piper methysticum) 2008 Flephedrone (p-fluormethcathinone); 4-FMC 2008 √ × 3-Fluoromethcathinone 2008 LSA ((8β)-9,10-didehydro-6-methyl-ergoline-8-carboxamide) 2008 pFBT (3-pseudotropyl-4-fluorobenzoate) 2008 MDPV (1-(3,4-methylenedioxyphenyl)-2-pyrrolidinyl-pentan-1-one) 2008 √ II, 1971 √ p-Fluoramphetamine (1-(4-fluorophenyl)propan-2-amine); 4-FA 2008 √ II, 1971* √ JWH-018 (Naphthalen-1-yl-(1-pentylindol-3-yl)methanon) 2008 √ II, 1971 13 2- or 3-fluoroamphetamine 2009 PPP (α-pyrrolidinopropiophenone) 2009 2-DPMP (2-diphenylmethylpiperidine) 2009 CP 47,497 (5-(1,1-dimethylheptyl)-2-[(1R,3S)-3-hydroxycyclohexyl]-phenol) 2009 CP 47,497-C6 homologue (5-(1,1-dimethylhexyl)-2-[(1R,3S)-3-hydroxycyclohexyl]- 2009 phenol) CP 47,497-C8 homologue (5-(1,1-dimethyloctyl)-2-[(1R,3S)-3-hydroxycyclohexyl]- 2009 phenol) CP 47,497-C9 homologue (5-(1,1-dimethylnonyl)-2-[(1R,3S)-3-hydroxycyclohexyl]- 2009 phenol) JWH-073 (1-butyl-3-(1-naphthoyl)indole) 2009 √ × 4-AcO-MET (4-acetoxy-N-methyl-N-ethyltryptamine) 2009

191

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ TMA-6 (2,4,6-trimethoxyamphetamine) 2009 HU-210 (1,1-dimethylheptyl-11-hydroxytetrahydrocannabinol) 2009 ODT (o-desmethyltramadol) 2009 4-AcO-DMT (4-acetoxy-N,N-dimethyltryptamine) 2009 2-PEA (2-phenethylamine) 2009 JWH-398 (1-pentyl-3-(4-chloro-1-naphthoyl)indole) 2009 JWH-250 (1-pentyl-3-(2-methoxyphenylacetyl)indole) 2009 √ × bk-PMMA / methedrone (4-Methoxymethcathinone) 2009 Etaqualone (3-(2-ethylphenyl)-2-methyl-quinazolin-4-one) 2009 MDPPP (3',4'-methylenedioxy-α-pyrrolidinopropiophenone) 2009 Metamfepramone (N,N-dimethylcathinone) 2009 3-FMA (3-fluoromethamphetamine) 2009 JWH-200 (1-[2-(4-morpholino)ethyl]-3-(1-naphthoyl)indole) 2009 4-MA (4-methylamphetamine) 2009 Pregabalin ((S)-3-(aminomethyl)-5-methylhexanoic acid) 2009 √ × 24 2C-B-BZP (1-(4-bromo-2,5-dimethoxybenzyl)piperazine) 2010 MDAI (5,6-methylenedioxy-2-aminoindane) – 2010 √ β-Me-PEA (2-phenylpropan-1-amine) 2010 N-benzyl-1-phenethylamine 2010 N,N-dimethylphenethylamine 2010 √ 4-FMA (4-fluoromethamphetamine) 2010 RCS-4 ((4-methoxyphenyl)(1-pentyl-1H-indol-3-yl)methanone) 2010 √ × JWH-081 (1-pentyl-3-(4-methoxy-1-naphthoyl)indole) 2010 Naphyrone (naphthylpyrovalerone) 2010 Iso-ethcathinone (1-ethylamino-1-phenyl-propan-2-one) 2010 DMAA (1,3-dimethylamylamine) 2010 √ Dimethocaine ((3-diethylamino-2,2-dimethylpropyl)-4-aminobenzoate) 2010 JWH-073 methyl derivative (1-Butyl-3-(1-(4-methyl)naphthoyl)indole)) 2010 Buphedrone (2-(methylamino)-1-phenylbutan-1-one) 2010

192

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 4-methylethcathinone (2-Ethylamino-1-(4-methylphenyl)-1-propanone); 4-MEC 2010 √ II, 1971 √ AM-694 (1-[(5-fluoropentyl)-1H-indol-3-yl]-(2-iodophenyl)methanone) 2010 JWH-122 (1-pentyl-3-(4-methyl-1-naphthoyl)indole) ) 2010 MPBP (4’-methyl--pyrrolidinobutyrophenone) 2010 JWH-015 (1-propyl-2-methyl-3-(1-naphthoyl)indole) ) 2010 4-MBC (4-methyl-N-benzylcathinone) 2010 MPPP (4'-Methyl--pyrrolidinopropiophenone) 2010 √ CP47,497 (C8 + C2) variant 2010 1-naphthalen-1-yl-2-pyrrolidin-1-yl-pentan-1-one 2010 Pentylone (2-Methylamino-1-(3,4-methylenedioxyphenyl)pentan-1-one) 2010 √ M-ALPHA (1-methylamino-1-(3,4-methylenedioxy-phenyl)propane) 2010 5-MeO-DPT (5-methoxy-N,N-dipropyltryptamine) 2010 β-Ethyl-Methcathinone (2-methylamino-1-phenyl-1-pentanone); pentedrone 2010 √ II, 1971 JWH- 210 (4-ethylnaphthalen-1-yl-(1-pentylindol-3-yl)methanone) 2010 3,4-Dimethylmethcathinone (1-(3,4-dimethylphenyl)-2-(methylamino)propan-1- 2010 √ one) JWH-203 (2-(2-chlorophenyl)-1-(1-pentylindol-3-yl)ethanone) 2010 JWH-019 (1-hexyl-3-(1-naphthoyl)indole) 2010 Methoxetamine (2-(3-methoxyphenyl)-2-(ethylamino)cyclohexanone) – 2010 √ II, 1971 3-(4-Hydroxymethylbenzoyl)-1-pentylindole 2010 MDPBP (3',4'-methylenedioxy--pyrrolidinobutyrophenone) 2010 √ 3-MeO-PCE (3-methoxyeticyclidine) 2010 DiButylone or bk-MMBDB (2-dimethylamino-1-(3,4-methylenedioxyphenyl)-butan- 2010 1-one) Arecoline (methyl methyl-1,2,5,6-tetrahydropyridine-3-carboxylate) – 2010 BMDP (2-benzylamino-1-(3,4-methylenedioxyphenyl)propan-1-one) 2010 BMDB (2-benzylamino-1-(3,4-methylenedioxyphenyl)butan-1-one) 2010

193

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 5-APB (5-(2-aminopropyl)benzofuran) 2010 Desoxy-D2PM (2-(diphenylmethyl)pyrrolidine) 2010 41 CRA-13 (naphthalen-1-yl-(4-pentyloxynaphthalen-1-yl)methanone) 2011 √ 4-MeO-PCP (4-methoxyphencyclidine) 2011 Methylthienylpropamine (N-methyl-1-(thiophen-2-yl)propan-2-amine); MPA 2011 √ II, 1971 √ AM-2201 (1-(5-fluoropentyl)-3-(1-naphthoyl)indole) 2011 √ II, 1971 N,N-dimethylamphetamine (N,N-dimethyl-1-phenylpropan-2-amine) 2011 JWH-251 (2-(2-methylphenyl)-1-(1-pentyl-1H-indol-3-yl)methanone) 2011 JWH-018 adamantoyl derivative (1-adamantoyl(1-pentyl-1H-indol-3- 2011 yl)methanone) JWH-182 (1-pentyl-3-(4-ethyl-1-naphthoyl)indole) 2011 5-IAI (5-iodo-2-aminoindane) 2011 JWH-250 derivative (1-(2-methylene-N-methylpiperidyl)-3-(2- 2011 methoxyphenylacetyl) indole) DMMA (3,4-dimethoxymethamphetamine) 2011 α-PVP (α-pyrrolidinopentiophenone) 2011 √ II, 1971 RCS-4 ortho isomer ((2-methoxyphenyl)(1-pentyl-1H-indol-3-yl)methanone) 2011 JWH-007 (1-pentyl-2-methyl-3-(1-naphthoyl)indole) 2011 AM-1220 (1-[(1-methylpiperidin-2-yl)methyl]-1H-indol-3-yl}(naphthyl)-methanone) 2011 AM-1220 azepane isomer (1-(1-methylazepan-3-yl)-1H-indol-3- 2011 √ yl](naphthyl)methanone) 5-HTP (5-hydroxytryptophan) 2011 WIN 48,098 / pravadoline ((4-methoxyphenyl)-[2-methyl-1-(2-morpholin-4- 2011 ylethyl)indol-3- yl]methanone 2C-C-NBOMe (2-(4-chloro-2,5-dimethoxyphenyl)-N-[(2- 2011 √ I, 1971 √ methoxyphenyl)methyl]ethanamine) Ostarine (3-(4-cyanophenoxy)-N-[4-cyano-3-(trifluoromethyl)phenyl]-2-hydroxy-2- 2011 methylpropanamide) JWH-122 fluoropentyl derivative (1-(5-fluoropentyl)-3-(4-methyl-naphthoyl)indole) 2011

194

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 6-APB (6-(2-aminopropyl)benzofuran) 2011 √ 4-APB (4-(2-aminopropyl)benzofuran) 2011 RCS-4(C4) (4-methoxyphenyl-(1-butyl-1H-indol-3-yl)methanone) 2011 Phenazepam (7-bromo-5-(2-chlorophenyl)-1,3-dihydro-1,4-benzodiazepin-2-one) 2011 √ IV, 1971 JWH-387 (1-pentyl-3-(4-bromo-1-naphthoyl)indole) 2011 JWH-412 (1-pentyl-3-(4- fluoro-1-naphthoyl)indole) 2011 JWH-307 ((5-(2-fluorophenyl)-1-pentylpyrrol-3-yl)-naphthalen-1-ylmethanone) 2011 AM-2233 (1-[(N-methylpiperidin-2-yl)methyl]-3-(2-iodobenzoyl)indole) 2011 Org27569 (5-Chloro-3-ethyl-1H-indole-2-carboxylic acid [2-(4-piperidin-1-yl- 2011 phenyl)-ethyl]- amide)) Org 27759 (3-Ethyl-5-fluoro-1H-indole-2-carboxylic acid [2-94-dimethylamino- 2011 phenyl)-ethyl]- amide) Org 29647 (5-Chloro-3-ethyl-1H-indole-2-carboxylic acid (1-benzyl-pyrrolidin-3-yl)- 2011 amide, 2- enedioic acid salt) N-ethylbuphedrone (2-(ethylamino)-1-phenylbutan-1-one) 2011 Brephedrone (1-(4-bromophenyl)-2-methylaminopropan-1-one) 2011 √ Iso-pentedrone (1-methylamino-1-phenyl-pentan-2-one) 2011 4-Ethylmethcathinone ((RS)-2-methylamino-1-(4-ethylphenyl)propane-1-one) 2011 4-Benzylpiperidine ((phenylmethyl)piperidine) 2011 bk-MDDMA (1-(1,3-benzodioxol-5-yl)-2-(dimethylamino)propan-1-one) 2011 4-methylbuphedrone (2-(methylamino)-1-(4-methylphenyl)butan-1-one) 2011 Methoxyphenamine (1-(2-methoxyphenyl)-N-methylpropan-2-amine) 2011 Ethylphenidate (ethyl 2-phenyl-2-(piperidin-2-yl)acetate 2011 √ II, 1971 √ Camfetamine (N-methyl-3-phenylbicyclo[2.2.1]heptan-2-amine 2011 JWH-022 (naphthalen-1-yl(2-(pent-4-enyl)-1H-indol-3-yl)methanone 2011 Etizolam (4-(2-chlorophenyl)-2-ethyl-9-methyl-6H-thieno[3,2- f][1,2,4]triazolo[4,3- 2011 √ × a][1,4]diazepine)

195

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ AM-2232 (5-[3-(1-naphthoyl)-1H-indol-1-yl]pentanenitrile) 2011 3-amino-1-phenyl-butane 2011 α-PBP (1-phenyl-2-pyrrolidino-butanone) 2011 AM-694 chloro derivative (1-(5-chloropentyl)-3-(2-iodobenzoyl)indole) 2011 1-phenyl-1-propanamine 2011 49 HU-331 ((3S,4R)-3-hydroxy-2-p-mentha-(1,8)-dien-3- yl-5-pentyl-3,4-p- 2012 benzoquinone) AM-679 ((2-iodophenyl)(1-pentyl-1H-indol-3-yl) methanone) 2012 WIN 55212-2 ((R)-(+)-[2,3-dihydro-5-methyl-3-(4- 2012 morpholinylmethyl)pyrrolo[1,2,3-de]-1,4-benzoxazin-6- yl]-1- napthalenylmethanone) UR-144 ((1-pentyl-1H-indol-3-yl)-(2,2,3,3-tetramethylcyclopropyl)methanone) 2012 √ II, 1971* √ JWH-370 ([5-(2-methylphenyl)-1-pentyl-1H-pyrrol-3- yl]-1-naphthalenyl- 2012 methanone) N-propylamphetamine (N-(1-phenylpropan-2-yl) propan-1-amine) 2012 3-(p-Methoxybenzoyl)-N-methylindole 2012 trans-Diastereomer of CP 47,497-C8 homologue 2012 1-Cyclohexyl-x-methoxybenzene 2012 3-Fluoro-isomethcathinone (1-(3-fluorophenyl)-1- (methylamino)-2-propanone) 2012 1-(3-Methylbenzyl)piperazine 2012 2-Fluoroamphetamine (1-(2-fluorophenyl)propan-2- amine 2012 Thienoamphetamine (1-(thiophen-2-yl)propan-2-amine) 2012 URB754 (6-methyl-2-[(4-methylphenyl)amino]-1- benzoxazin-4-one) 2012 5-APDB (5-(2-aminopropyl)-2,3-dihydrobenzofuran) 2012 Phenibut (4-amino-3-phenyl-butyric acid) 2012 6-APDB (6-(2-aminopropyl)-2,3-dihydrobenzofuran) 2012 2-FMA (2-fluoro-N-methyl-amphetamine) 2012 ECX (1-ethynyl-1-cyclohexanol) 2012 4-Fluoroephedrine (1-(4-fluorophenyl)-2-(methylamino) propan-1-ol) 2012

196

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 3-MeO-PCP (1-[1-(3-methoxyphenyl)cyclohexyl] piperidine) 2012 5FUR-144 ((1-(5-fluoropentyl)-1H-indol-3-yl) (2,2,3,3- 2012 √ II, 1971 tetramethylcyclopropyl)methanone); XLR-11 25D-NBOMe (2-(2,5-dimethoxy-4-methylphenyl)-N-(2- 2012 methoxybenzyl)ethanamine) A-796,260 ([1-[2-(4-morpholinyl)ethyl]-1H-indol-3-yl](2, 2,3,3- 2012 tetramethylcyclopropyl)methanone) 4-AcO-DALT (4-acetoxy-N,N-diallyltryptamine) 2012 1-Phenyl-2-(piperidin-1-yl)butan-1-one 2012 2,4,5-Trimethylmethcathinone / 2,4,5-TMMC (2-methylamino-1-(2,4,5- 2012 trimethylphenyl)propan-1- one)) APINACA (N-(1-adamantyl)-1-pentyl-1H-indazole-3- carboxamide) 2012 √ × 5-IT (5-(2-aminopropyl)indole) 2012 Zopiclone (6-(5-chloro-2-pyridyl)-6,7-dihydro-7-oxo-5Hpyrrolo[3,4-b]pyrazin-5-yl 4- 2012 √ × methylpiperazine-1- carboxylate) UR-144 (-2H) ([1-(pent-4-en-1-yl)-1H-indol-3-yl] (2,2,3,3- 2012 tetramethylcyclopropyl)methanone) 25I-NBOMe (4-iodo-2,5-dimethoxy-N-(2- methoxybenzyl)phenethylamine) 2012 √ I, 1971 4-HO-DPT (4-hydroxy-N,N-dipropyltryptamine) 2012 5-MeO-MET (5-methoxy-N-ethyl-N-methyl-tryptamine) 2012 STS-135 (N-(1-adamantyl)-1-(5-fluoropentyl)-1Hindole-3-carboxamide) 2012 MPHP (1-(4-methylphenyl)-2-(pyrrolidin-1-yl)-hexan-1- one) 2012 APICA (N-(1-adamantyl)-1-pentyl-1H-indole-3- carboxamide) 2012 JWH-018 carboxamide derivative (1-pentyl-N- (naphthalen-1-yl)-1H-indole-3- 2012 carboxamide) MDDM (3,4-methylenedioxy-N,Ndimethylamphetamine) 2012

197

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ MAM-2201 chloropentyl derivative ([1-(5-chloropentyl)-1H-indol-3-yl](4-methyl-1- 2012 naphthalenyl)methanone) JWH-122 pentenyl 2-methylindole derivative ((4-methylnaphthalen-1-yl)[2-methyl- 2012 1-(pent-4-en-1-yl)- 1H-indol-3-yl)]methanone) JWH-122 pentenyl derivative ((4-methylnaphthalen-1- yl)(1-(pent-4-en-1-yl)-1H- 2012 indol-3-yl)methanone) AM-694 methyl substituted for iodine (1-(5-fluoropentyl)-3-(2- 2012 methylbenzoyl)indole) AM-694 ethyl substituted for iodine (1-(5-fluoropentyl)-3-(2-ethylbenzoyl)indole) 2012 JWH-018 N-(5-chloropentyl) derivative ([1-(5-chloropentyl)-1H-indol-3- 2012 yl](naphthalen-1-yl) methanone) JWH-018 N-(5-bromopentyl) derivative ([1-(5-bromopentyl)-1H-indol-3- 2012 yl](naphthalen-1-yl) methanone) AH-7921 (3,4-dichloro-N-[[1-(dimethylamino) cyclohexyl]methyl]benzamide) 2012 √ I, 1961 4-AcO-DPT (4-acetoxy-N,N-dipropyltryptamine) 2012 Pyrazolam (8-bromo-1-methyl-6-phenyl-4H- [1,2,4] 2012 triazolo[4,3a][1,4]benzodiazepine) 2-MeO-Ketamine (2-(2-methoxyphenyl)-2- (methylamino)cyclohexanone) 2012 Hydroxyamphetamine (4-(2-aminopropyl)phenol) 2012 3-Methylmethcathinone / 3-MMC (1-(3-methylphenyl)- 2-(methylamino)propan-1- 2012 √ × one) N-Ethylnorketamine (2-(2-chlorophenyl)-2-(ethylamino) cyclohexanone) 2012 5-APDI (1-(2,3-dihydro-1H-inden-5-yl)propan-2-amine) 2012 AM-1248 (1-[(N-methylpiperidin-2-yl)methyl]-3- (adamant-1-oyl)indole) 2012 AKB-48F (N-(1-adamantyl)-1-(5-fluoropentyl)-1Hindazole-3-carboxamide) 2012 √ II, 1971 AM-2201 indazolecarboxamide analogue (N-1- naphthalenyl-1-(5-fluoropentyl)- 2012 1H-indazole-3- carboxamide JWH-018 carboxylate analogue, quinolinyl derivative (quinolin-8-yl 1-pentyl-1H- 2012 indole-3-carboxylate)

198

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ AB-005 ([1-[(1-methyl-2-piperidinyl)methyl]-1H-indol- 3-yl](2,2,3,3- 2012 tetramethylcyclopropyl)methanone) AB-005 azepane isomer ((1-(1-methylazepan-2-yl)-1Hindol-3-yl)(2,2,3,3- 2012 tetramethylcyclopropyl)methanone) 4-HTMPIPO (4-hydroxy-3,3,4-trimethyl-1-(1-pentyl-1Hindol-3-yl)pentan-1-one) 2012 (Iso)butyryl-F-fentanyl N-benzyl analogue (N-(1- benzylpiperidin-4-yl)-N-(x- 2012 fluorophenyl)-butanamide) (Iso)butyryl fentanyl (2-methyl-N-phenyl-N-[1-(1- phenylpropan-2-yl)piperidin-4- 2012 yl]propanamide) UR-144 N-(5-chloropentyl) analogue ((1-(5-chloropentyl)-1H-indol-3-yl) (2,2,3,3- 2012 tetramethylcyclopropyl)methanone) 4-CA/4-chloroamphetamine (1-(4-chlorophenyl) propan-2-amine) 2012 25B-NBOMe (2-(4-bromo-2,5-dimethoxyphenyl)-N-(2- 2012 √ I, 1971 methoxybenzyl)ethanamine) 2C-G (1-(2,5-dimethoxy-3,4-dimethylphenyl)propan-2- amine) 2012 2C-N (2,5-dimethoxy-4-nitrophenethylamine) 2012 25E-NBOMe (2-(4-ethyl-2,5-dimethoxyphenyl)-N-[(2- 2012 methoxyphenyl)methyl]ethanamine) 25G-NBOMe (2-(2,5-dimethoxyphenyl-3,4-dimethyl)- N-[(2- 2012 methoxyphenyl)methyl]ethanamine) 25N-NBOMe (2-(2,5-dimethoxyphenyl-4-nitro)-N-[(2- 2012 methoxyphenyl)methyl]ethanamine) 4,4’-DMAR (4-Methylaminorex p-methyl derivative) 2012 √ II, 1971 4-Methylphendimetrazine 2012 JWH-302 (1-pentyl-3-(3-methoxyphenylacetyl)indole) 2012 73 5-MAPB (1-(benzofuran-5-yl)-N-methylpropan-2-amine) 2013

199

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 4-Fluorocathinone (2-amino-1-(4-fluorophenyl)propan-1-one) 2013 JWH-methylcyclohexane-8quinolinol (Quinolin-8-yl 1-(cyclohexylmethyl)-1H- 2013 indole-3- carboxylate) A-834,735 ([1-(tetrahydropyran-4-ylmethyl)indol-3-yl]-(2,2,3,3- 2013 tetramethylcyclopropyl) methanone) JWH-368 ([5-(3-fluorophenyl)-1-pentyl-pyrrol-3-yl]-(1-naphthyl)methanone) 2013 Carfentanil (methyl 1-(2-phenylethyl)-4-[phenyl(propionyl)amino]-4- 2013 √ IV, 1961* piperidinecarboxylate) EAM-2201 ((4-ethyl-1-naphthyl)-[1-(5-fluoropentyl)indol-3-yl]methanone) 2013 Flubromazepam (7-bromo-5-(2-fluorophenyl)-1,3-dihydro-2H-1,4-benzodiazepin- 2013 2-one) 5F-PB22 (8-quinolyl 1-(5-fluoropentyl)indole-3-carboxylate) 2013 √ II, 1971* JWH-307 brominated derivative ((5-(2-bromophenyl)-1-pentyl-1H-pyrrol-3-yl) 2013 (naphthalen-1-yl)methanone) JWH-030 (naphthalen-1-yl(1-pentyl-1H-pyrrol-3-yl)methanone) 2013 JWH-145 (naphthalen-1-yl(1-pentyl-5-phenyl-1H-pyrrol-3-yl)methanone) 2013 UR-144 heptyl derivative ((1-heptyl-1H-indol-3-yl)(2,2,3,3-tetramethylcyclopropyl)- 2013 methanone) 3,4-dichloromethylphenidate (methyl (2R)-2-(3,4-dichlorophenyl)-2-[(2R)- 2013 piperidin-2- yl]acetate) 25H-NBOMe (2-(2,5-dimethoxyphenyl)-N-(2-methoxybenzyl)ethanamine) 2013 URB-597 ([3-(3-carbamoylphenyl)phenyl] N-cyclohexylcarbamate) 2013 N-ethyl-1-phenylbutan-2-amine 2013 AB-PINACA (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-pentyl-1H-indazole-3- 2013 √ II, 1971* carboxamide) α-PVT (2-(pyrrolidin-1-yl)-1-(thiophen-2-yl)pentan-1-one) 2013 A-836,339 (N-[3-(2-methoxyethyl)-4,5-dimethyl-1,3-thiazol-2-ylidene]-2,2,3,3- 2013 tetramethylcyclopropane-carboxamide) 4-methylbuphedrone, N-benzyl derivative (2-(benzylamino)-1-(4-methylphenyl) 2013 butan-1-one)

200

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 2-Me-DMT (N,N-dimethyl-2-(2-methyl-1H-indol-3-yl)ethanamine) 2013 4-MeO-α-PVP (1-(4-methoxyphenyl)-2-(pyrrolidin-1-yl)pentan-1-one) 2013 NMP (1-methylpyrrolidin-2-one) 2013 Tropicamide (N-ethyl-3-hydroxy-2-phenyl-N-(pyridin-4-ylmethyl)propanamide) 2013 RH-34 (3-[2-(2-methoxybenzylamino)ethyl]-1H-quinazoline-2,4-dione) 2013 2-(2,3-dimethoxyphenyl)-N-(3,4,5-trimethoxybenzyl)ethanamine 2013 JTE-907 (N-(benzo[1,3]dioxol-5-ylmethyl)-7-methoxy-2-oxo-8-pentyloxy-1,2- 2013 dihydroquinolin-3-carboxamide) AB-FUBINACA (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(4-fluorobenzyl)-1H- 2013 indazole- 3-carboxamide) 5F-AB-PINACA (N-(1-carbamoyl-2-methyl-propyl)-1-(5-fluoropentyl)indazole-3- 2013 carboxamide) Mebroqualone (3-(2-bromophenyl)-2-methylquinazolin-4(3H)-one) 2013 Allylescaline (4-allyloxy-3,5-dimethoxy-phenethylamine) 2013 α-PEP (1-phenyl-2-(1-pyrrolidinyl)heptan-1-one) 2013 5-EAPB (1-(1-benzofuran-5-yl)-N-ethylpropan-2-amine) 2013 Mephtetramine (2-((methylamino)methyl)-3,4-dihydronaphthalen-1(2H)-one) 2013 Escaline (3,5-dimethoxy-4-ethoxyphenethylamine) 2013 βk-PBDB (1-(1,3-benzodioxol-5-yl)-2-(propylamino)butan-1-one) 2013 Proscaline (2-(3,5-dimethoxy-4-propoxyphenyl)ethanamine) 2013 W-15 ((E)-4-chloro-N-(1-phenethylpiperidin-2-ylidene)benzenesulfonamide) 2013 Nitracaine (3-(N,N-diethylamino)-2,2-dimethylpropyl-4-nitrobenzoate) 2013 Diclazepam (7-chloro-5-(2-chlorophenyl)-1-methyl-1,3-dihydro-2H-1,4- 2013 benzodiazepin- 2-one) Methoxetamine brominated derivative (2-(2-bromo-5-methoxy-phenyl)-2- 2013 √ (ethylamino) cyclohexanone)

201

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 25iP-NBOMe (2-[2,5-dimethoxy-4-(propan-2-yl)phenyl]-N-(2-methoxybenzyl) 2013 ethanamine) 3C-P (1-(3,5-dimethoxy-4-propoxyphenyl)propan-2-amine) 2013 3C-E (1-(4-ethoxy-3,5-dimethoxyphenyl)propan-2-amine) 2013 25I-NBMD (N-(1,3-benzodioxol-4-ylmethyl)-2-(4-iodo-2,5-dimethoxy-phenyl) 2013 ethanamine) 6-MAPB (1-(benzofuran-6-yl)-N-methylpropan-2-amine) 2013 LY2183240 (N,N-dimethyl-5-[(4-biphenyl)methyl]tetrazole-1-carboxamide) 2013 Methoxypiperamide ((4-methoxyphenyl)(4-methylpiperazine-1-yl)methanone) 2013 bk-MPA (2-(methylamino)-1-(thiophenyl-2-yl)propan-1-one) 2013 AM-1248 azepane isomer ((adamant-1-yl)[1-(1-methylazepan-3-yl)-1H-indol-3-yl] 2013 methanone) Methallylescaline (2-[3,5-dimethoxy-4-[(2-methyl-prop-2-en-1-yl)oxy]phenyl] 2013 ethanamine) C30-NBOMe (2-(4-chloro-2,5-dimethoxy-phenyl)-N-[(3,4,5- 2013 trimethoxyphenyl)methyl] ethanamine) ADBICA (N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-pentyl-1H-indole-3- 2013 carboxamide) Gabapentin (2-[1-(aminomethyl)cyclohexyl]acetic acid) 2013 Sibutramine (1-[1-(4-chlorophenyl)cyclobutyl]-N,N,3-trimethyl-1-butanamine) 2013 Venlafaxine (1-[(2-dimethylamino)-1-(4-methoxyphenyl)ethyl]cyclohexanol) 2013 2-FMC (1-(2-fluorophenyl)-2-(methylamino)propan-1-one) 2013 25B-N(BOMe)2 (2-(4-bromo-2,5-dimethoxyphenyl)-N,N-bis(2-methoxybenzyl) 2013 ethanamine) Diphenhydramine (2-(diphenylmethoxy)-N,N-dimethylethanamine) 2013 Atomoxetine ((3R)-N-methyl-3-(2-methylphenoxy)-3-phenylpropan-1-amine) 2013 Ocfentanil (N-(2-fluorophenyl)-2-methoxy-N-[1-(2-phenylethyl)-4-piperidinyl] 2013 √ I, 1961* acetamide) 6-EAPB (1-(benzofuran-6-yl)-N-ethylpropan-2-amine) 2013

202

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ AM-6527 5-fluoropentyl derivative (1-(5-fluoropentyl)-N-(napthalen-2-yl)-1H- 2013 indole- 3-carboxamide) 4-MMA (N-methyl-1-(4-methylphenyl)propan-2-amine) 2013 AM-2201 indazole analogue ([1-(5-fluoropentyl)-1H-indazol-3-yl](naphthalen-1-yl) 2013 methanone) N-methyl-2-aminoindane (N-methylindan-2-amine) 2013 Embutramide (N-[2-ethyl-2-(3-methoxyphenyl)butyl]-4-hydroxy-butanamide) 2013 ADB-FUBINACA (N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(4-fluorobenzyl)- 2013 1Hindazole-3-carboxamide) ADB-PINACA (N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-pentyl-1H-indazole-3- 2013 carboxamide) βk-2C-B (2-amino-1-(4-bromo-2,5-dimethoxyphenyl)ethan-1-one) 2013 Butorphanol (17-cyclobutylmethyl-morphinan-3,14-diol) 2013 MT-45 (1-cyclohexyl-4-(1,2-diphenylethyl)-piperazine) 2013 √ I, 1961 Lysergic acid 2,4-dimethylazetidide (‘LSZ’) ([(2S,4S)-2,4-dimethylazetidin-1-yl]- 2013 [(9R)- 7-methyl-6,6a,8,9-tetrahydro-4H-indolo[4,3-fg]quinoline-9-yl]methanone) N,N-diethyl-2-(1-pentyl-1H-indol-3-yl)-4-thiazole-methanamine 2013 N-(2-methoxyethyl)-N-(1-methylethyl)-2-(1-pentyl-1H-indol-3-yl)-4- 2013 thiazolemethanamine 1-(Cyclohexylmethyl)-2-[(4-ethoxyphenyl)methyl]-N,N-diethyl-1H-benzimidazole- 2013 5- carboxamide A-796,260 isomer, ((E)-3,4,4-trimethyl-1-[1-(2-morpholinoethyl)indol-3-yl]pent-2- 2013 en-1- one) SDB-006 (N-benzyl-1-pentyl-1H-indole-3-carboxamide) 2013 5F-SDB-006 (N-benzyl-1-(5-fluoropentyl)-1H-indole-3-carboxamide) 2013 FUB-PB-22 (8-quinolyl 1-[(4-fluorophenyl)methyl]-3H-indole-3-carboxylate) 2013 81

203

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 6-Bromo-MDMA (1-(6-bromo-1,3-benzodioxol-5-yl)-N-methylpropan-2-amine) 2014 2-MeO-diphenidine (1-(1-(2-methoxyphenyl)-2-phenylethyl)piperidine) 2014 Tramadol ((+)-cis-2-[(dimethylamino)methyl]-1-(m-methoxyphenyl)cyclohexanol: 2014 √ tramadol) N-methyl-2C-B (4-bromo-N-methyl-2,5-dimethoxyphenethylamine) 2014 Diphenidine (1-(1,2-diphenylethyl)piperidine) 2014 PB-22 indazole analogue (quinolin-8-yl 1-pentyl-1H-indazole-3-carboxylate) 2014 5F-PB-22 indazole analogue (quinolin-8-yl 1-(5-fluoropentyl)-1H-indazole-3- 2014 carboxylate) 4-Methyl-N-ethylnorpentedrone (2-(ethylamino)-1-(4-methylphenyl)pentan-1- 2014 one) 4F-α-PVP (1-(4-fluorophenyl)-2-(pyrrolidin-1-yl)pentan-1-one) 2014 2-APB (1-(1-benzofuran-2-yl)propan-2-amine) 2014 2-MAPB (2-(N-methyl-2-aminopropyl)-1-benzofuran) 2014 3,4-DMeO-α-PVP (1-(3,4-dimethoxyphenyl)-2-(pyrrolidin-1-yl)pentan-1-one) 2014 4-BEC (1-(4-bromophenyl)-2-(ethylamino)propan-1-one) 2014 FDU-PB-22 (1-naphthyl 1-[(4-fluorophenyl)methyl]indole-3-carboxylate) 2014 JWH-018 indazole analogue (1-naphthalenyl(1-pentyl-1H- indazol-3-yl)- 2014 methanone) 3,4-dimethylethcathinone / 3,4-DMEC (1-(3,4-dimethylphenyl)-2-(ethylamino) 2014 propan-1-one) Mepirapim ((4-methylpiperazin-1-yl)-(1-pentylindol-3-yl)methanone) 2014 Quetiapine (2-[2-(4-dibenzo[b,f][1,4]thiazepin-11-yl-1-piperazinyl)ethoxy]ethanol) 2014 α-Ethylaminopentiophenone (2-(ethylamino)-1-phenyl-pentan-1-one) 2014 Eutylone (1-(1,3-benzodioxol-5-yl)-2-(ethylamino)butan-1-one) 2014 Mesembrine ((3aS,7aS)-3a-(3,4-dimethoxyphenyl)-1-methyl- 2014 2,3,4,5,7,7ahexahydroindol-6-one) α-Pyrrolidinohexanophenone / α-PHP (2-(pyrrolidin-1-yl)-1-(phenyl)hexan-1-one) 2014 4-Fluoro butyrfentanyl (N-(4-fluorophenyl)-N-[(1-(2-phenylethyl)-4-piperidinyl)] 2014 butanamide)

204

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ Hexedrone (2-(methylamine)-1-(phenyl)hexan-1-one) 2014 4’-Chloro-α-PPP (1-(4-chlorophenyl)-2-(1-pyrrolidinyl)propan-1-one) 2014 2-Methoxyamphetamine (1-(2-methoxyphenyl)propan-2-amine 2014 4-Fluoro-N-isopropylnorpentedrone (1-(4-fluorophenyl)-2-(1-methylethylamino) 2014 pentan-1-one 3-Methoxymethcathinone / 3-MeOMC (1-(3-methoxyphenyl)-2-(methylamino) 2014 propane-1-one Alprazolam triazolobenzophenone derivative ((2-(3-(aminomethyl)-5-methyl-4-H- 2014 1,2,4-triazol-4-yl)-5-chlorophenyl)(phenyl)methanone) AM-2201 benzimidazole analogue / FUBIMINA ((1-(5-fluoropentyl)-1H-benzo[d] 2014 imidazol-2-yl)(naphthalen-1-yl)methanone) 4-Bromoamphetamine (1-(4-bromophenyl)propan-2-amine) 2014 AB-CHMINACA (N-[(1S)-1-(aminocarbonyl)-2-methylpropyl]-1- (cyclohexylmethyl)- 2014 √ II, 1971* 1Hindazole-3-carboxamide) 5F-AMBICA (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-1H-indole- 2014 3- carboxamide) 2-Methylmethcathinone (1-(2-methylphenyl)-2-(methylamino)propane-1-one) 2014 Orphenadrine (N,N-dimethyl-2-(2-methylbenzhydryloxy)ethylamine) 2014 DL-4662 (1-(3,4-dimethoxyphenyl)-2-(ethylamino)pentan-1-one) 2014 1-(4-fluorophenyl)-2-(piperidin-1-yl)pentan-1-one 2014 5-MeO-MALT (N-[2-(5-methoxy-1H-indol-3-yl)ethyl]-N-methyl-prop-2-en-1-amine) 2014 4-Methylpentedrone (1-(4-methylphenyl)-2-methylamino-pentan-1-one) 2014 5F-AMB (methyl 2-({[1-(5-fluoropentyl)-1H-indazol-3-yl]carbonyl}amino)-3- 2014 methylbutanoate) JWH-071 ((1-ethyl-1H-indol-3-yl)-1-naphthalenyl-methanone) 2014 NEDPA (N-ethyl-1,2-diphenyl-ethanamine) 2014 NPDPA (N-(1,2-diphenylethyl)propan-2-amine) 2014

205

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ EG-018 (naphthalen-1-yl(9-pentyl-9H-carbazol-3-yl)methanone) 2014 Dipentylone (1-(1,3-benzodioxol-5-yl)-2-(dimethylamino)-pentan-1-one) 2014 4-Fluoropentedrone (1-(4-fluorophenyl)-2-(methylamino)pentan-1-one) 2014 3-MEC (2-(ethylamino)-1-(3-methylphenyl)propan-1-one) 2014 MN-18 (N-(naphthalen-1-yl)-1-pentyl-1H-indazol-3-carboxamide) 2014 Bupropion (1-((±)-1-(3-chlorophenyl)-2-[(1,1-dimethylethyl)amino]-1-propanone) 2014 FUB-AKB48 (N-((3s,5s,7s)-adamantan-1-yl)-1-(4-fluorobenzyl)-1H-indazole-3- 2014 carboxamide AB-FUBINACA 2-fluorobenzyl isomer (N-[(1S)-1-(aminocarbonyl)-2-methylpropyl]- 2014 1- [(2-fluorophenyl)methyl]-1H-indazole-3-carboxamide) Clephedrone (1-(4-chlorophenyl)-2-(methylamino)propan-1-one) 2014 2-EAPB (1-(1-benzofuran-2-yl)-N-ethylpropan-2-amine) 2014 5-MeO-NiPT (N-[2-(5-methoxy-1H-indol-3-yl)ethyl]-propan-2-amine) 2014 4-MeO-α-PBP (1-(4-methoxyphenyl)-2-(pyrrolidin-1-yl)butan-1-one) 2014 Meclonazepam ((S)-5-(2-chlorophenyl)-3-methyl-7-nitro-1,3-dihydro-2H-1,4- 2014 benzodiazepin-2-one) MET (N-methyl-N-ethyltryptamine) 2014 NM-2201 (naphthalen-1-yl 1-(5-fluoropentyl)-1H-indol-3-carboxylate) 2014 Deschloroetizolam 2014 Fentanyl butanamide analogue (N-phenyl-N-[1-(2-phenylethyl)-4-piperidinyl]- 2014 butanamide) 5F-SDB-005 (naphthalen-1-yl-1-(5-fluoropentyl)-1H-indazole-3-carboxylate) 2014 W-18 (4-chloro-N-(1-[2-(4-nitrophenyl)ethyl]-piperidin-2- 2014 ylidene)benzenesulfonamide) α-PBT (2-(pyrrolidin-1-yl)-1-(thiophen-2-yl)butan-1-one) 2014 4F-α-PEP (1-(4-fluorophenyl)-2-(pyrrolidin-1-yl)heptan-1-one) 2014 ADB-CHMINACA (N-[1-(aminocarbonyl)-2,2-dimethylpropyl]-1-(cyclohexylmethyl)- 2014 1Hindazole-3-carboxamide) MDMB-CHMICA (N-[[1-(cyclohexylmethyl)-1H-indol-3-yl]carbonyl]-3-methyl- 2014 II, 1971 valine, methyl ester)

206

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 3F-Phenmetrazine (2-(3-fluorophenyl)-3-methylmorpholine) 2014 4-Methyl-N,N-dimethylcathinone (2-dimethylamino-1-(4-methylphenyl)propan-1- 2014 one) EFLEA (N-(1-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)propan-2-yl)- 2014 Nmethylhydroxylamine) Acetylfentanyl/desmethylfentanyl (N-(1-phenethylpiperidin-4-yl)- 2014 I, IV, 1961 Nphenylacetamide) 3,4-MDPA (α-methyl-N-propyl-1,3-benzodioxole-5-ethanamine) 2014 α-POP (1-phenyl-2-(pyrrolidin-1-yl)octan-1-one) 2014 CUMYL-BICA (1-butyl-N-(2-phenylpropan-2-yl)-1H-indole-3-carboxamide) 2014 CUMYL-PINACA (1-pentyl-N-(2-phenylpropan-2-yl)-1H-indazole-3-carboxamide) 2014 ADB-CHMICA (N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(cyclohexylmethyl)- 2014 1Hindole-3-carboxamide) CUMYL-5FPICA (1-(5-fluoropentyl)-N-(2-phenylpropan-2-yl)-1H-indole-3- 2014 carboxamide) CUMYL-THPINACA (N-(2-phenylpropan-2-yl)-1-((tetrahydro-2H-pyran-4-yl)methyl)- 2014 1- H-indazole-3-carboxamide) CUMYL-PICA (1-pentyl-N-(2-phenylpropan-2-yl)-1H-indole-3-carboxamide) 2014 Adrafinil (2-[(diphenylmethyl]sulfinyl]-N-hydroxiacetamide) 2014 4F-α-POP (1-(4-fluorophenyl)-2-(pyrrolidin-1-yl)octan-1-one) 2014 DALT (N-allyl-N-[2-(1H-indol-3-yl)ethyl]prop-2-en-1-amine) 2014 5-MeO-EIPT (N-ethyl-N-[2-(5-methoxy-1H-indol-3-yl)ethyl]propan-2-amine) 2014 CUMYL-5FPINACA (1-(5-fluoropentyl)-N-(1-methyl-1-phenylethyl)-1H-indazole-3- 2014 carboxamide) 3-Chloromethcathinone or 3-CMC (1-(3-chlorophenyl)-2-(methylamino)propan-1- 2014 one 5-APB NBOMe (1-(benzofuran-5-yl)-N-[(2-methoxyphenyl)methyl]propan-2-amine) 2014

207

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 4-MMA NBOMe (N-[(2-methoxyphenyl)methyl]-N-methyl-1-(p-tolyl)propan-2- 2014 amine) 4-EA NBOMe (1-(4-ethylphenyl)-N-[(2-methoxyphenyl)methyl]propan-2-amine) 2014 3,4-DMA NBOMe (1-(3,4-dimethoxyphenyl)-N-[(2-methoxyphenyl)methyl]propan- 2014 2- amine) 4-Methyl-N,N-diethylcathinone (2-diethylamino-1-(4-methylphenyl)propan-1-one) 2014 Afloqualone (6-amino-2-(fluoromethyl)-3-(2-methylphenyl)-3H-quinazolin-4-one) 2014 Flubromazolam (8-bromo-6-(2-fluorophenyl)-1-methyl-4H-[1,2,4]triazolo- 2014 [4,3a][1,4] benzodiazepine) Modafiendz (2-{[bis(4-fluorophenyl)methyl]sulfinyl}-N-methylacetamide (N- 2014 methyl- 4,4-difluoro-modafinil)) Methylmethaqualone (3-(2,4-dimethylphenyl)-2-methylquinazolin-4(3H)-one) 2014 5F-APP-PINACA (N-(2-amino-1-benzyl-2-oxo-ethyl)-1-(5-fluoropentyl)indazole-3- 2014 carboxamide) APP-FUBINACA (N-(2-amino-1-benzyl-2-oxo-ethyl)-1-[(4-fluorophenyl)methyl] 2014 indazole-3-carboxamide) MDPHP (1-(1,3-benzodioxol-5-yl)-2-pyrrolidin-1-yl-hexan-1-one) 2014 4-MeO-α-PEP (1-(4-methoxyphenyl)-2-pyrrolidin-1-yl-heptan-1-one) 2014 5F-APP-PICA (N-(1-amino-1-oxo-3-phenylpropan-2-yl)-1-(5-fluoropentyl)-1H- 2014 indole-3- carboxamide) 5F-AMB-PICA (methyl (1-(5-fluoropentyl)-1H-indole-3-carbonyl)-L-valinate) 2014 Flibanserin (1-(2-(4-[3-(trifluormethyl)phenyl]piperazine-1-yl)ethyl)-1,3-dihydro- 2014 2Hbenzimidazole-2-one) AMB-FUBINACA (methyl-2-(1-(4-fluorobenzyl)-1H-indazole-3-carboxamide)-3- 2014 methylbutanoate) 101 5F-MDMB-PINACA (methyl-[2-(1-(5-fluoropentyl)-1H-indazole-3-carboxamido)-3,3- 2015 dimethylbutanoate]), Nifoxipam (5-(2-fluorophenyl)-3-hydroxy-7-nitro-1H-benzo[e][1,4]diazepin-2(3H)- 2015 one)

208

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ NSI-189 ((4-benzylpiperazin-1-yl)-[2-(3-methylbutylamino)pyridin-3-yl]methanone) 2015 Clonazolam (6-(2-chlorophenyl)-1-methyl-8-nitro-4H-[1,2,4]triazolo[4,3-a][1,4] 2015 benzodiazepine) U-47700 (3,4-dichloro-N-[2-(dimethylamino)cyclohexyl]-N-methylbenzamide) 2015 √ I, 1961 bk-IVP (1-(2,3-dihydro-1H-inden-5-yl)-2-(ethylamino)pentan-1-one), 2015 N-methyl-bk-MMDA-2 (1-(6-methoxy-1,3-benzodioxol-5-yl)-2-(methylamino) 2015 propan-1-one) ADAMANTYL-THPINACA 2015 (N-(1-adamantyl)-1-(tetrahydropyran-4-ylmethyl) indazole-3-carboxamide) 2-Chloro-4,5-MDMA (1-(6-chloro-1,3-benzodioxol-5-yl)-N-methyl-propan-2-amine) 2015 1-(2,3-dihydro-1H-inden-5-yl)-2-phenyl-2-(pyrrolidinyl-1-yl)ethan-1-one 2015 4-FEC (2-(ethylamino)-1-(4-fluorophenyl)propan-1-one 2015 (4-fluoroethcathinone) 5-DBFPV (1-(2,3-dihydrobenzofuran-5-yl)-2-(pyrrolidin-1-yl)pentan-1-one) 2015 25I-NB34MD (2-(4-iodo-2,5-dimethoxyphenyl)-N-[(3,4-methylenedioxyphenyl) 2015 methyl]ethanamine) FUB -14 4 ([1-[(4-fluorophenyl)methyl]indol-3-yl]-(2,2,3,3-tetramethylcyclopropyl) 2015 methanone) 4F-PBP (1-(4-fluorophenyl)-2-(1-pyrrolidinyl)-1-butanone) 2015 25I-NBF 2-(4-iodo-2,5-dimethoxyphenyl)-N-[(2-fluorophenyl)methyl]ethanamine 2015 CUMYL-5F-P7AICA (1-(5-fluoropentyl)-N-(2-phenylpropan-2-yl)-7-azaindole-3- 2015 carboxamide) Alpha-PNP (alpha-pyrrolidinononaphenone) 2015 4-methylpentan-2-amine (DMBA) 2015 HDMP-28 (methylnaphthidate) (methyl 2-(2-naphthyl)-2-(2-piperidyl)acetate) 2015 Isopropylphenidate (isopropyl 2-phenyl-2-(2-piperidyl)acetate) 2015

209

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 1p-LSD (N,N-diethyl-7-methyl-4-propanoyl-6,6a,8,9-tetrahydroindolo[4,3- 2015 fg]quinoline-9-carboxamide) M-CHMIC (1-(cyclohexylmethyl)-2-methyl-indole-3-carboxylate) 2015 Deschloroketamine (2-(methylamino)-2-phenyl-cyclohexanone) 2015 Modafinil sulphone (2-benzhydrylsulfonylacetamide) 2015 4Br-α-PVP (1-(4-bromophenyl)-2-pyrrolidin-1-yl-pentan-1-one) 2015 DB-MDBP 2015 (1-((2,2-difluorobenzo[D][1,3]dioxol-5-yl)methyl)piperazine), AL-LAD ((6aR,9R)-7-allyl-N,N-diethyl-6,6a,8,9-tetrahydro-4H-indolo[4,3- 2015 fg]quinoline-9-carboxamide) SDB-005 (N a p h t h a l e n - 1-y l -1-p e n t y l - 1H- indazole- 3- 2015 carboxylate) 5F-ADB-PINACA (N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-1H- 2015 √ II,1971* indazole-3-carboxamide) AB-PINACA N-(2-fluoropentyl) isomer (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(2- 2015 fluoropentyl)-1H-indazole-3-carboxamide) APP-CHMINACA (N-(2-amino-1-benzyl-2-oxo-ethyl)-1-(cyclohexylmethyl)indazole- 2015 3-carboxamide) 2C -TFM (2-[2,5-dimethoxy-4-(trifluoromethyl)phenyl]ethanamine), 2015 5-BPDi (1-indan-5-yl-2-pyrrolidin-1-yl-hexan-1-one) 2015 MDMB-FUBICA (methyl 2-(1-(4-fluorobenzyl)-1H-indol-3-carboxamide)- 2015 3,3-dimethylbutanoate), 4-methylmethylphenidate 2015 (methyl 2-(2-piperidyl)-2-(p-tolyl)acetate), 4-ethylethcathinone or 4-EEC 2015 (2-(ethylamino)-1-(4-ethylphenyl)propan-1-one) DOIP (1-(4-isopropyl-2,5-dimethoxy-phenyl)propan-2-amine), 2015 AMB-CHMINACA (Methyl 2-(1-(cyclohexylmethyl)-1H-indazole-3-carboxamide)-3- 2015 methylbutanoate) 4-MeO-α-PV9 (1-(4-methoxyphenyl)-2-(pyrrolidin-1-yl)octan-1-one) 2015

210

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 3,4-DMeO-α-PHP (1-(3,4-dimethoxyphenyl)-2-(pyrrolidin-1-yl)hexan-1-one), 2015 Propylphenidate (Propyl-2-phenyl-2-(piperidin-2-yl)acetate) 2015 5F-AB-FUPPYCA (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-5-(4- 2015 fluorophenyl)-1H-pyrazole-3-carboxamide) 5F-PY-PICA (1-(5-fluoropentyl)-3-(pyrrolidine-1-carbonyl)-1-H-indole), 2015 FUB-JWH-018 (1-(4-fluorobenzyl)-1H-indol-3-yl)(naphthalen-1-yl)methanone) 2015 Nor-mephedrone (2-amino-1-(4-methylphenyl)-1-propanone) 2015 Despropionyl-2-fluoro fentanyl (N-(2-Fluorophenyl)-1-(2-phenylethyl)piperidin-4- 2015 amine) 5C-AKB48 (N-(2-adamantyl)-1-(5-chloropentyl)indazole-3-carboxamide) 2015 5F-EMB-PINACA (ethyl 2-[[1-(5-fluoropentyl)indazole-3-carbonyl]amino]-3-methyl- 2015 butanoate) 5F-PY-PINACA ([1-(5-fluoropentyl)indazol-3-yl]-pyrrolidin-1-yl-methanone) 2015 EMB-FUBINACA (ethyl 2-[[1-[(4-fluorophenyl)methyl]indazole-3-carbonyl]amino]- 2015 3-methyl-butanoate) Ethylnaphthidate (ethyl 2-(2-naphthyl)-2-(2-piperidyl)acetate), 2015 CBL- 018(naphthalen-1-yl 1-pent yl-1H-indole-3-carboxylate) 2015 N-methyl aminorex derivative (5-phenyl-2-amino-N-methyl-oxazoline) 2015 5-Fluoropentyl-3-pyridinoylindole ([1-(5-fluoropentyl)-1H-indol-3-yl](pyridin-3- 2015 yl)methanone) Methamnetamine (N-methyl-1-(naphthalen-2-yl)propan-2-amine), 2015 AB-CHMFUPPYCA (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(cyclohexylmethyl)-3- 2015 (4-fluorophenyl)-1H-pyrazole-5-carboxamide) 3-MeO-PCMo (4-[1-(3-methoxyphenyl)cyclohexyl]morpholine), 2015 McPT (N-(2-(1H-indol-3-yl)ethyl-N-methylcyclopropanamine) 2015 TH-PVP (2-pyrrolidin-1-yl-1-tetralin-6-yl-pentan-1-one) 2015 2,3-XP (1-(2,3-dichlorophenyl)piperazine) 2015

211

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 4-MeO-BF or 4-methoxybutyrfentanyl (N-(4-methoxyphenyl)-N-[1-(2- 2015 phenylethyl)piperidin-4-yl] butanamide) DOPR (1-(2,5-dimethoxy-4-propylphenyl)propan-2-amine) 2015 DOF (1-(4-fluoro-2,5-dimethoxyphenyl)propan-2-amine) 2015 Mexedrone (3-methoxy-2-(methylamino)-1-(4-methylphenyl)propan-1-one) 2015 4-CMA (1-(4-chlorophenyl)-N-methylpropan-2-amine) 2015 Propylcathinone (1-phenyl-2-(propylamino)propan-1-one) 2015 2,4-DMMC (1-(2,4-dimethylphenyl)-2-(methylamino)propan-1-one) 2015 2,4-DMEC (1-(2,4-dimethylphenyl)-2-(ethylamino)propan-1-one) 2015 3,4-DMAR (3,4-dimethyl-5-phenyl-1,3-oxazolidin-2-imine), 2015 4-chloro-N,N-dimethylcathinone (1-(4-chlorophenyl)-2-(N,N- 2015 dimethylamino)propan-1-one) 2-MEC (2-(ethylamino)-1-(2-methylphenyl)propan-1-one) 2015 AMB-CHMICA (methyl 2-[[1-(cyclohexylmethyl)indole-3-carbonyl]amino]-3- 2015 methyl-butanoate) MDMB-CHMCZCA (methyl 2-(9-(cyclohexylmethyl)-9H-carbazole-3-carboxamido)- 2015 3,3-dimethylbutanoate) 25C-NBF (2-(4-chloro-2,5-dimethoxyphenyl)-N-[(2- 2015 fluorophenyl)methyl]ethanamine) 4-MPH (3-methyl-2-(p-tolyl)morpholine) 2015 5-PPDi (1-(2,3-dihydro-1H-inden-5-yl)-2-(pyrrolidin-1-yl)butan-1-one) 2015 Furanylfentanyl (N-phenyl-N-[1-(2-phenylethyl)piperidin-4-yl]-furan-2- 2015 √ I, 1961* carboxamide) 4-Cl-α-PVP (1-(4-chlorophenyl)-2-pyrrolidin-1-yl-pentan-1-one) 2015 4-F-α-PHP (1-(4-fluorophenyl)-2-(pyrrolidin-1-yl)hexan-1-one) 2015 Phenetrazine (3-ethyl-2-phenyl-morpholine) 2015 Bk-IBP (1-(2,3-dihydro-1H-inden-5-yl)-2-(ethylamino)butan-1-one) 2015 4-fluoromethylphenidate (methyl 2-(4-fluorophenyl)-2-(piperidin-2-yl)acetate) 2015 tBuONE (1-(1,3-Benzodioxol-5-yl)-2-(tert-butylamino)propan-1-one) 2015 Epirocaine ([2-methyl-2-(propylamino)propyl] benzoate) 2015

212

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ Modafinil (2-[(diphenylmethyl)sulfinyl]acetamide) 2015 Adinazolam (1-(8-chloro-6-phenyl-4H-[1,2,4]triazolo[4,5-a][1,4]benzodiazepin-1- 2015 yl)- N,N-dimethylmethanamine) JWH-018 cyclohexymethyl derivative ([1-(cyclohexylmethyl)-1H-indol-3- 2015 yl](naphthalen-1-yl)methanone) 5-MAPDB (1-(2,3-dihydrobenzofuran-5-yl)-N-methylpropan-2-amine) 2015 Iso-phenmetrazine (5-methyl-2-phenylmorpholine), 2015 5-MBPB (1-(benzofuran-5-yl)-N-methylbutan-2-amine) 2015 α-TMT ((2-(1H-indol-3-yl)-1-methyl-ethyl)dimethylamine) 2015 3F-Phenetrazine (3-ethyl-2-(3-fluorophenyl)morpholine) 2015 Metizolam 4-(2-chloro-phenyl)-2-ethyl-6H-thieno[3, 2-f][1,2,4]triazolo[4,3- 2015 a][1,4]diazepine Nitrazolam 1-methyl-8-nitro-6-phenyl-4H-[1,2,4]triazolo[4,3-a][1,4]benzodiazepine 2015 Bromantane N-(4-bromophenyl)adamantan-2-amine 2015 NiPP 2-(isopropylamino)-1-phenylpentan-1-one (NiPP) 2015 5-MeO-DIBF 2-(5-methoxy-1-benzofuran-3-yl)ethyl]bis(propan-2-yl)amine 2015 98 MDMB-FUBINACA (methyl 2-[[1-[(4-fluorophenyl) methyl]indazole-3-carbonyl] 2016 amino]-3,3-dimethyl-butanoate) Viloxazine (2-[(2-ethoxyphenoxy)methyl]morpholine) 2016 Fladrafinil (2-[bis(4-fluorophenyl)methylsulfinyl]-N-hydroxyacetamide) 2016 Cloniprazepam (5-(2-chlorophenyl)-1-(cyclopropylmethyl)-7-nitro-1,3-dihydro-2H- 2016 [1,4]-benzodiazepin-2-one) 25C-NBOH (2-[[2-(4-chloro-2,5-dimethoxy-phenyl)ethylamino]methyl]phenol) 2016 Ephylone (1-(2H-1,3-benzodioxol-5-yl)-2-(ethylamino)pentan-1-one) 2016 2,4-DMPPP (1-(2,4-dimethylphenyl)-2-pyrrolidin-1-yl-propan-1-one) 2016

213

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 4-CEC (1-(4-chlorophenyl)-2-(ethylamino)propan-1-one) 2016 N-ethylhexedrone (NEH) (2-(ethylamino)-1-1phenylhexan-1-one) 2016 PDM-35 (3,5-dimethyl-2-phenylmorpholine) 2016 3,6-DMPM (3,6-dimethyl-2-phenyl-morpholine) 2016 EG-2201 ((9-(5-fluoropentyl)-9H-carbazol-3-yl)(1-naphthalenyl)methanone) AKB-57 (1-adamantyl 1-pentylindazole-3-carboxylate) 2016 LTI -701 (1-(5-fluoropentyl)-N-phenyl-indole-3-carboxamide) 2016 4Br-α-PPP (1-(4-bromophenyl)-2-pyrrolidin-1-yl-propan-1-one) 2016 25I-NBOH (2-[[2-(4-iodo-2,5-dimethoxy-phenyl)ethylamino]methyl]phenol) 2016 4-CIC (1-(4-chlorophenyl)-2-(isopropylamino)propan-1-one) 2016 CUMYL-4CN-BINACA (1-(4-cyanobutyl)-N-(1-methyl-1-phenyl-ethyl)indazole-3- 2016 carboxamide) 3-CEC (1-(3-chlorophenyl)-2-(ethylamino)propan-1-one) 2016 TH-PHP (2-pyrrolidin-1-yl-1-tetralin-6-yl-hexan-1-one) 2016 Valerylfentanyl (N-phenyl-N-[1-(2-phenylethyl)-4-piperidyl]pentanamide), 2016 4-Fluoroethylphenidate (ethyl 2-(4-fluorophenyl)-2-(2-piperidyl)acetate) 2016 Propylone (1-(1,3-benzodioxol-5-yl)-2-(propylamino)propan-1-one) 2016 ALD-52 ((8β)-1-acetyl-N,N-diethyl-6-methyl-9,10-didehydroergoline-8- 2016 carboxamide) Memantine (3,5-dimethyladamantan-1-amine) 2016 3-Hydroxyphenazepam(7-bromo-5-(2-chlorophenyl)-3-hydroxy-1,3-dihydro-2H- 2016 1,4-benzodiazepin-2-one) Benocyclidine (1-[1-(1-benzothiophen-2-yl)cyclohexyl]piperidine) 2016 Fonazepam (5-(2-fluorophenyl)-1,3-dihydro-7-nitro-2H-1,4-benzodiazepin-2-one) 2016 Tiletamine (2-ethylamino-2-(2-thienyl)cyclohexanone) 2016 25B-NBF (2-(4-bromo-2,5-dimethoxyphenyl)-N-[(2- 2016 fluorophenyl)methyl]ethanamine) 25B-NBOH (2-[[2-(4-bromo-2,5-dimethoxy-phenyl)ethylamino]methyl]phenol) 2016 2-MABB (1-(1-benzofuran-2-yl)-N-methylbutan-2-amine) 2016 4F-NEB (2-(ethylamino)-1-(4-fluorophenyl)butan-1-one) 2016

214

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 6-IT (2-(1H-indol-6-yl)-1-methyl-ethylamine) 2016 3-Methylphenmetrazine (3-methyl-2-(3-methylphenyl)morpholine) 2016 Acryloylfentanyl (N-(1-phenethylpiperidin-4-yl)-N-phenylacrylamide) 2016 √ I, 1961* G-130 (5,5-dimethyl-2-phenyl-morpholine) 2016 Methylmorphenate (2-(morpholin-3-yl)-2-phenylacetate) 2016 PRE-084 (2-(morpholin-4-yl)ethyl 1-phenylcyclohexane-1-carboxylate) 2016 2-Fluorofentanyl (N-(2-fluorophenyl)-N-[1-(2-phenylethyl)-4-piperidinyl]- 2016 propanamide) Deschloro-N-ethyl-ketamine (2-(ethylamino)-2-phenyl-cyclohexanone) 2016 ETH-LAD ((6aR,9R)-N,N-diethyl-7-ethyl-4,6,6a,7,8,9-hexahydroindolo-[4,3- 2016 fg]quinoline-9-carboxamide) 4Cl-iBF (N-(4-chlorophenyl)-2-methyl-N-[1-(2-phenylethyl)-4-piperidyl] 2016 propanamide) N-methyl-bk-MMDA-5 (1-(7-methoxybenzo[d][1,3]dioxol-5-yl)-2- 2016 (methylamino)propan-1-one) 4F-iBF (N-(4-fluorophenyl)-2-methyl-N-[1-(2-phenylethyl)piperidin-4- 2016 √ I, 1961* yl]propanamide) 4-chlorodiazepam (7-chloro-5-(4-chlorophenyl)-1-methyl-3H-1,4-benzodiazepin-2- 2016 one) FUB-NPB-22 (quinolin-8-yl-(4-fluorobenzyl)-1H-indazole-3-carboxylate) 2016 5F-EDMB-PINACA (ethyl-2-[1-(5-fluoropentyl)-1H-indazole-3-carboxamido]-3,3- 2016 dimethylbutanoate) 5-MAPDI (1-(2,3-dihydro-1H-inden-5-yl)-N-methylpropan-2-amine) 2016 5F-MDMB-PICA (methyl 2-[[1-(5-fluoropentyl)indole-3-carbonyl]amino]-3,3- 2016 dimethyl-butanoate) AMB-FUBICA (methyl 2-[[1-[(4-fluorophenyl)methyl]indole-3-carbonyl]amino]-3- 2016 methyl-butanoate)

215

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 3-Fluorofentanyl (N-(3-fluorophenyl)-N-[1-(2-phenylethyl)-4- 2016 piperidyl]propanamide) 2-Fluorodeschloroketamine (2-(2-fluorophenyl)-2-methylamino-cyclohexanone) 2016 1-Phenethyl-4-hydroxypiperidine (1-(2-phenylethyl)piperidin-4-ol) 2016 Flunitrazolam (6-(2-fluorophenyl)-1-methyl-8-nitro-4H-[1,2,4]triazolo[4,3- 2016 a][1,4]benzodiazepine) N-methylbenzedrone (2-[benzyl(methyl)amino]-1-(4-methylphenyl)-1-propanone) 2016 MDA 19 (N-[(Z)-(1-hexyl-2-oxoindol-3-ylidene)amino]benzamide) 2016 Bromazolam (8-bromo-1-methyl-6-phenyl-4H-[1,2,4]triazolo[4,3- 2016 a][1,4]benzodiazepine) 3-MeO-PCMMo (4-[[1-(3-methoxyphenyl)cyclohexyl]methyl]morpholine) 2016 α-PPP-MeO (3-methoxy-1-phenyl-2-(pyrrolidin-1-yl)propan-1-one) 2016 α-PHiP (4-methyl-1-phenyl-2-pyrrolidin-1-yl-pentan-1-one) Methoxyacetylfentanyl (2-methoxy-N-phenyl-N-[1-(2-phenylethyl)piperidin-4- 2016 yl]acetamide) U-49,900 (3,4-dichloro-N-[2-(diethylamino)cyclohexyl]-N-methylbenzamide) 2016 Dichloropane (RTI-111) methyl 3-(3,4-dichlorophenyl)-8-methyl-8- 2016 azabicyclo[3.2.1]octane-2-carboxylate MO-CHMINACA (1-methoxy-3,3-dimethyl-1-oxobutan-2-yl 1-(cyclohexylmethyl)- 2016 1H-indazole-3-carboxylate) Tetrahydrofuranylfentanyl (N-phenyl-N-[1-(2-phenylethyl)piperidin-4- 2016 √ I, 1961* yl]tetrahydrofuran-2-carboxamide) 66 Cyclopentylfentanyl (N-phenyl-N-[1-(2-phenylethyl)-4- 2017 piperidyl]cyclopentanecarboxamide) NiPH (2-(isopropylamino)-1-phenyl-hexan-1-one 2017 U-51,754 (2-(3,4-dichlorophenyl)-N-[2-(dimethylamino)cyclohexyl]-N-methyl- 2017 acetamide) Norfludiazepam (7-chloro-5-(2-fluorophenyl)-1,3-dihydro-1,4-benzodiazepin-2- 2017 one)

216

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 25I-NB4OMe (2-(4-iodo-2,5-dimethoxyphenyl)-N-(4-methoxybenzyl)ethanamine) 2017 CUMYL-PeGACLONE (2-(1-methyl-1-phenyl-ethyl)-5-pentyl-pyrido[4,3-b]indol-1- 2017 one) NDTDI (N,N-diethyl-3-[methyl(1,3,4,5-tetrahydrobenzo[cd]indol-4- 2017 yl)amino]propanamide) Ru-28306 (N,N-dimethyl-1,3,4,5-tetrahydrobenzo[cd]indol-4-amine) 2017 Benzodioxole-fentanyl (N-phenyl-N-[1-(2-phenylethyl)piperidin-4-yl]-2H-1,3- 2017 benzodioxole-5-carboxamide) 5-Chloropentyl JWH 018 indazole analogue ([1-(5-chloropentyl)-1H-indazol-3- 2017 yl](naphthalen-1-yl)methanone) 4-Chloropentedrone (1-(4-chlorophenyl)-2-(methylamino)pentan-1-one) 2017 3-Methylflephedrone (1-(4-chlorophenyl)-2-(methylamino)pentan-1-one) 2017 5Cl-AB-PINACA (N-[(1S)-1-(aminocarbonyl)-2-methylpropyl]-1-(5-chloropentyl)1H- 2017 Indazole-3-carboxamide) MDMB-PCZCA (methyl 3,3-dimethyl-2-(9-pentyl-9H-carbazole-3- 2017 carboxamido)butanoate) Octodrine (6-methylheptan-2-amine) 2017 5F-NNEI-2 (1-(5-fluoropentyl)-N-(naphthalen-2-yl)-1H-indole-3-carboxamide) 2017 SDB-006 N-phenyl analogue (1-pentyl-N- phenyl-1H-indole-3-carboxamide) 2017 Benzoylfentanyl (N-phenyl-N-[1-(2-phenylethyl)piperidin-4-yl]benzamide 2017 4-fluoro-N-ethylpentedrone (2-(ethylamino)-1-(4-fluorophenyl)pentan-1-one) 2017 3-phenylpropanoylfentanyl (N-phenyl-N-[1-(2-phenylethyl)piperidin-4-yl]-3- 2017 phenylpropanamide) 4-chloro-N-butylcathinone (2-(butylamino)-1-(4-chlorophenyl)propan-1-one) 2017 5F-3,5-AB-PFUPPYCA (N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-3- 2017 (4-fluorophenyl)-1H-pyrazole-5-carboxamide) 2-methylamphetamine (2-MA;1-(2-methylphenyl)propan-2-amine) 2017

217

Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ 5Cl-MDMB-PINACA/5Cl-ADB (methyl 2-{[1-(5-chloropentyl)-1H-indazole-3- 2017 carbonyl]amino}-3,3-dimethylbutanoate) Tetramethylcyclopropanefentanyl (N-phenyl-N-[1-(2-phenylethyl)piperidin-4-yl]- 2017 2,2,3,3-tetramethylcyclopropane-1-carboxamide) CUMYL-4CN-B7AICA (1-(4-cyanobutyl)-N-(2-phenylpropan-2-yl)-1H-pyrrolo[2,3- 2017 b]pyridin-3-carboxamide) Ro 07-4065 (7-chloro-5-(2,6-difluorophenyl)-1-methyl-3H-1,4-benzodiazepin-2- 2017 one) Cyclopropylfentanyl (N-phenyl-N-[1-(2-phenylethyl)-4- 2017 piperidyl]cyclopropanecarboxamide) U-48800 (2-(2,4-dichlorophenyl)-N-(2-(dimethylamino)cyclohexyl)-N- 2017 methylacetamide) 1P-ETH-LAD (N,N,7-triethyl-4-propionyl-4,6,6a,7,8,9-hexahydroindolo[4,3- 2017 fg]quinoline-9-carboxamide) Thionordazepam (7-chloro-5-phenyl-1,3-dihydro-2H-1,4-benzodiazepin-2-thione) 2017 4-EAPB (1-(1-benzofuran-4-yl)-N-ethylpropan-2-amine) 2017 4F-α-PHiP (1-(4-fluorophenyl)-4-methyl-2-(pyrrolidin-1-yl)pentan-1-one) 2017 NEiH (2-(ethylamino)-4-methyl-1-phenylpentan-1-one) 2017 N-propylnorpentedrone (1-phenyl-2-(propylamino)-1-pentanone) 2017 DOT (1-[2,5-dimethoxy-4-(methylthio)phenyl]propan-2-amine) 2017 3-bromomethcathinone/3-BMC (1-(3-bromophenyl)-2-(methylamino)propan-1- 2017 one) 5-MeO-pyr-T (5-methoxy-3-(2-pyrrolidin-1-ylethyl)-1H-indole) 2017 Thiophenefentanyl (N-(1-phenethylpiperidin-4-yl)-N-phenylthiophene-2- 2017 carboxamide) 3,4-dichloroethcathinone/3,4-DCEC (1-(3,4-dichlorophenyl)-2-(ethylamino)propan- 2017 1-one) 3-HO-PCE (3-(1-(ethylamino)cyclohexyl)phenol) 2017 Benzylfentanyl (N-phenyl-N-[1-(phenylmethyl)-4-piperidinyl]-propanamide) 2017 Bromadoline (U 4793e; 4-bromo-N-(2-(dimethylamino)cyclohexyl)benzamide) 2017

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Table 31: NPS reported to the EMCDDA, and those detected in Australia (2009-2012^) Name Year reported Assessed by Scheduled Detected in ECDD Australia^ Bk-IMP (1-(2,3-dihydro-1H-inden-5-yl)-2(methylamino)propan-1-one) 2017 1-(1,3-diphenylpropan-2-yl)pyrrolidine 2017 3,4-Dichloro-N,N-cyclohexylmethylmethcathinone (2-[cyclohexyl(methyl)amino]-1- 2017 (3,4-dichlorophenyl)propan-1-one) 3-Fluoroethamphetamine/3-FEA (N-ethyl-1-(3-fluorophenyl)propan-2-amine) 2017 Zaleplon (N-[3-(3-cyanopyrazolo[1,5-a]pyrimidin-7-yl)phenyl]-N-ethylacetamide) 2017 Benzoyloylbenzylfentanyl (N-(1-benzyl-4-piperidyl)-N-phenyl-benzamide) 2017 Acetylbenzylfentanyl (N-(1-benzyl-4-piperidyl)-N-phenyl-acetamide) 2017 5F-Cumyl-PeGaClone (5-(5-fluoropentyl)-2-(1-methyl-1-phenylethyl)-pyrido[4,3- 2017 b]indol-1-one) 51 Substances which have recently been scheduled but which are not listed in the EMCDDA reports Butyrfentanyl (N-(1-phenethylpiperidin-4-yl)-N-phenylbutyramide) √ I, 1961* 4-fluoroisobutyrfentanyl (N-(4-fluorophenyl)-N-(1-phenethylpiperidin-4- √ I, 1961* yl)isobutyramide Ethylone (3,4-methylenedioxy-N-ethylcathinone; bk-MDEA; MDEC) √ II, 1971 √ ^From 2009-2012; It is unknown which NPS have been detected in Australia from 2013 onwards, however the UNODC reports the total number of NPS detected in Australia to be between 101-200 (see Figure 2). *Recommended for scheduling at the 39th Expert Committee on Drug Dependence (ECDD) meeting (Nov 2017), but recommendation has not yet been formally approved Note: (1) This list of substances has been obtained from the Europol Annual Reports on the Implementation of Council Decision 2005/387/JHA (2005-2017: http://www.emcdda.europa.eu/publications-database?f[0]=field_series_type:551); NPS reported prior to 2005 (i.e. <2005) were obtained from King and Sedefov (2007), but please note that this is not an exhaustive list; (2) whether NPS were assessed (pre-review or critical review) and/or scheduled by the World Health Organisation ECDD was determined by looking at the meeting reports (http://www.who.int/medicines/access/controlled-substances/ecdd/en/); (3) whether these substances have been detected in Australia was determined using the UNODC report, ‘The challenge of new psychoactive substances’ (United Nations Office on Drugs and Crime, 2013) – note: this only covers the period 2009- 2012. Khat, ethcathinone, PMA, 3,4-Dimethylmethcathinone and ethylone were reported to the UNODC as having been detected in Australia, but these are not included as NPS by the EMCDDA.

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Appendix C: I Like the Old Stuff Better than the New Stuff? Subjective Experiences of New Psychoactive Substances.

Allison Matthews1, Rachel Sutherland3, Amy Peacock1,3, Joe Van Buskirk3, Elizabeth Whittaker3, Lucinda Burns3, & Raimondo Bruno1

1 School of Medicine (Psychology), University of Tasmania, Private Bag 30, Hobart, Tasmania 7004, Australia

3National Drug and Alcohol Research Centre, UNSW Australia, 22-32 King St, Randwick, NSW, 2052, Australia

This paper has been published in International Journal of Drug Policy (Matthews et al., 2017)

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Abstract

Background: Over the past decade, monitoring systems have identified the rapid emergence of new psychoactive substances (NPS). While the use of many NPS are minimal and transitory, little is known about which products have potential for capturing the attention of significant proportions of the drug consuming market. The aim of this study was to explore self-reported experiences of three commonly used NPS classes within the Australian context (synthetic cathinones, hallucinogenic phenethylamines and hallucinogenic tryptamines) relative to traditional illicit drug counterparts.

Methods: Frequent psychostimulant consumers interviewed for the Australian Ecstasy and related Drugs Reporting System (EDRS) (n=1,208) provided subjective ratings of the pleasurable and negative (acute and longer-term) effects of substances used in the last six months on the last occasion of use, and the likelihood of future use.

Results: Stimulant-type NPS (e.g., mephedrone, methylone) were rated less favourably than ecstasy and cocaine in terms of pleasurable effects and likelihood of future use. DMT (a hallucinogenic tryptamine) showed a similar profile to LSD in terms of pleasurable effects and the likelihood of future use, but negative effects (acute and comedown) were rated lower. Hallucinogenic phenethylamines (e.g., 2C-B) showed a similar negative profile to LSD, but were rated as less pleasurable and less likely to be used again.

Conclusion: The potential for expanded use of stimulant-type NPS may be lower compared to commonly used stimulants such as ecstasy and cocaine. In contrast, the potential of DMT may be higher relative to LSD given the comparative absence of negative effects.

Key words: new psychoactive substances; subjective ratings; mephedrone; psychostimulant consumers

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Introduction

New psychoactive substances (NPS) have emerged rapidly on global drug markets over the past decade (EMCDDA, 2015). NPS are comprised of both synthetic and naturally occurring substances, which are often analogous in their effects to traditional controlled substances such as ecstasy/MDMA, cocaine and lysergic acid diethylamide (LSD). For many NPS there has been little research examining their effects and associated risks for consumers, both in the short-term and long-term (Sumnall, Evans-Brown, & McVeigh, 2011). In 2014, NPS were detected at a rate of two per week in the European Union, with over 450 different NPS currently being monitored by the European Centre for Drugs and Drug Addiction (EMCDDA, 2015). While the availability and use of many NPS is short-lived, some of these substances remain popular with continued use noted among regular psychostimulant consuming populations (Sumnall et al., 2011).

Given the ongoing access to NPS it is important to understand the consumers’ potential willingness to substitute traditional illicit drugs with NPS, and consequently maintain their popularity on the illicit drug market. Among regular consumers, preference for particular NPS has previously been linked to a number of variables including: preference for stimulant or psychedelic effects, perceived quality and purity relative to traditional substances, low probability of short-term and long-term harms, and positive ratings by peers or on the internet (Freeman et al., 2012; Moore, Dargan, Wood, & Measham, 2013; Sumnall et al., 2011; van Amsterdam, Nabben, Keiman, Haanschoten, & Korf, 2015). The present study will focus on subjective experiences of the positive and negative effects of NPS and how these compare to traditional illicit psychostimulant substances.

Among Australian samples of regular psychostimulant consumers, the use of NPS in the last six months has risen significantly from 33% in 2010 to 42% in 2015 (Sutherland et al., 2016). The most commonly used NPS classes within this context were hallucinogenic phenethylamines (e.g., 2C-I, 2C-B, 2C-E), hallucinogenic tryptamines (e.g., DMT, 5-meo-DMT), and synthetic cathinones (e.g. mephedrone, methylone, and MDPV/Ivory wave), and while recent use of synthetic cathinones decreased over this six year period (18.5% vs 7.7%), there were overall increases in the recent use of hallucinogenic phenethylamines (8.5% vs 18.6%) and tryptamines (7.5% vs 10.9%) (Sutherland et al., 2016).

The synthetic cathinone class includes substances such as mephedrone, methylone, and MDPV. Originally mephedrone (4-methylmethcathinone; ‘MCAT’; ‘meow-meow’; ‘plant food’) was marketed as a ‘legal high’ and was largely sold online or in specialty shops (Brunt, Poortman, Niesink, & Van den Brink, 2010; Davey, Corazza, Schifano, & Deluca, 2010;

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Newcombe, & Welch, 2010), and despite the introduction of legislative controls, it has remained available via traditional face-to-face dealing in addition to online purchases (Winstock, Mitcheson, & Marsden, 2010a). In contrast, other NPS such as MDPV and methylone have not necessarily had such a pervasive or lasting presence.

Several studies have examined consumers’ subjective reports of the positive and negative effects of mephedrone (Winstock et al., 2011; Winstock et al., 2010b), but few studies have directly compared these subjective reports to other traditional illicit substances (Carhart-Harris, King, & Nutt, 2011; Kapitany-Foveny et al., 2013; Winstock et al., 2010b), and there has been little research into the subjective effects of other popular synthetic cathinone derivatives such as methylone and MDPV. In one study examining the subjective effects of mephedrone (n=145), the overall profile of subjective effects were rated as similar to MDMA, but positive and negative effects were not compared (Kapitany-Foveny et al., 2013). Similarly, among a sample who had consumed both ecstasy and mephedrone, almost three-quarters (73%) indicated that they preferred the effects of MDMA, but the specific profile of effects was not directly compared (Carhart-Harris et al., 2011). In contrast, in a study comparing the subjective effects of mephedrone and cocaine, over one-half of the sample reported that the quality (55%) and duration (65%) of the ‘high’ was greater for mephedrone (Winstock et al., 2010b). In the only study to compare subjective ratings among recent consumers of ecstasy, cocaine, and mephedrone, ecstasy was rated as highest in terms of the pleasurable ‘high’ and lowest in terms of acute negative effects (Uosukainen, Tacke, & Winstock, 2015).

In relation to hallucinogenic NPS, few studies have evaluated the subjective effects of hallucinogenic tryptamines such as DMT (N,N-dimethyltryptamine), and to our knowledge, no previous research has compared hallucinogenic phenethylamines (e.g., 2C-I, 2C-B, 2C-E) to more commonly used hallucinogenic substances such as LSD. One previous study compared the effect and risk profile among first-time users of DMT (n=472), magic mushrooms (n=1,157), LSD (n=1,130) or ketamine (n=993) (Winstock, Kaar, & Borschmann, 2014). DMT was reported to have a desirable effect profile characterised by a high strength of pleasurable effects, and a lack of negative effects (Winstock et al., 2014).

The aim of the present study was to explore subjective experiences of specific substances within the three most commonly used NPS classes among regular psychostimulant consumers in Australia: synthetic cathinones, hallucinogenic phenethylamines and hallucinogenic tryptamines. The research complements previous studies which have examined subjective ratings of specific NPS in comparison to substances that are already established in the illicit drug

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market (Uosukainen et al., 2015; Winstock et al., 2014). However, previous studies have not conducted statistical tests to directly compare subjective ratings among the same group of participants. Thus, in the present study subjective ratings were compared among matched samples who report recent use of each substance. To this end, synthetic cathinones were compared to ecstasy and cocaine, and hallucinogenic phenethylamines and tryptamines were compared to LSD.

Method

Participants and Procedure

The current study comprised regular psychostimulant consumers (n=1,260) interviewed as part of the Australian Ecstasy and Related Drugs Reporting System (EDRS) in 2012 (n=607) or 2013 (n=653). To ensure independence, participants who completed the survey in 2012 (n=33) were excluded from the 2013 sample. Inclusion criteria comprised: aged 16 years or older; at least monthly use of ecstasy or other psychostimulant drugs in the last six months; and residence in the Australian capital city of recruitment for the preceding 12 months.

Recruitment was via posters/flyers, internet forums, and word of mouth. Participants contacted the researchers and confidential face-to-face structured interviews (~60 mins) were conducted in public locations. Participants received $AUD40 reimbursement for their time and out-of- pocket expenses.

The EDRS is a national Australian study which aims to examine trends in ecstasy and related drug use and associated risk behaviours and health-related harms among regular psychostimulant consumers in Australian capital cities on a yearly basis. A full description on the methods and survey instrument can be found elsewhere (Sindicich & Burns, 2013, 2014).

Key Measures

If participants had used any specified NPS in the last six months, they were asked to report number of days of use and provide subjective ratings of their effects on the last occasion of use. Those who had used ecstasy, cocaine or LSD in the last six months also provided days of use and subjective ratings for these substances. Subjective rating scales were devised by the authors and referred to the pleasurable and negative effects ‘during the high’ and the negative effects during the ‘comedown’ on the last occasion of use (from 0 ‘no effect’ to 10 ‘best/worst ever had (any drug)’ and the likelihood that they would use the drug again if offered (0 ‘definitely not’ to 10 ‘definitely yes’).

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Design and Analysis

Mean subjective ratings were examined for stimulant (mephedrone, methylone, MDPV) and hallucinogenic (2C-B, 2C-I, 2C-E, DMT, mescaline) NPS. Statistical comparisons (paired t-tests) were conducted for matched samples (n>20) who had used one of these NPS substances as well as other common psychostimulant (ecstasy and cocaine) or hallucinogenic (LSD) substances during this time. The matched samples were as follows: ecstasy and mephedrone (n=66); ecstasy and methylone (n=46); cocaine and mephedrone (n=33); cocaine and methylone (n=25); LSD and 2CB (n=89); LSD and 2CI (n=46); LSD and DMT (n=107).

Results

Demographics and substance use

The mean age of the sample was 22 years (SD=6.5) and two thirds (66%) were male. Participants had completed a median of 12 years formal education, one-half (49%) were currently employed on a full-time or part-time/casual basis, and one-quarter (25%) were currently studying full-time or part-time. In the last month, two-fifths (40%) had consumed psychostimulant drugs weekly or more often, one-third (35%) at least fortnightly, and the remainder (25%) monthly or less often.

In 2012/2013, the most commonly used NPS stimulants among the sample were mephedrone and methylone and the most commonly used NPS hallucinogens were hallucinogenic phenethylamines (e.g., 2C-B, 2C-I, 2C-E) and DMT. Further information regarding the use of other NPS (Sindicich & Burns, 2013, 2014) and trends in NPS use over time (Sutherland et al., 2016) can be found elsewhere.

Table 31 shows the proportion of the sample reporting recent use and their frequency of use for the stimulant and hallucinogenic substances of interest. Almost the entire sample had used ecstasy in the last six months, at a median frequency of 12 days. This equates to approximately fortnightly use and suggests a pattern of largely recreational or weekend use. Two-fifths had recently used cocaine or LSD, and smaller proportions (13% or less) reported use of the NPS of interest. For cocaine, LSD, and NPS, frequency of use was relatively low at 1-3 days in the preceding six months.

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Table 32: Use of stimulant and hallucinogenic substances of interest in the last six months among regular psychostimulant consumers (N=1,260) % used in last six Median days of use in months (n) last 6 months (IQR)

Stimulant substances Ecstasy 99 (1,243) 13 (8-24) Cocaine 38 (478) 2 (1-5) Mephedrone (4MMC, Meow, M-cat) 6 (70) 2 (1-5) Methylone (bk-MDMA) 4 (50) 2 (1-4) MDPV 2 (23) 2 (1-2) Hallucinogenic substances LSD 39 (485) 3 (1-6) DMT 13 (165) 2 (1-3) 2C-B 12 (147) 1 (1-3) 2C-I 5 (65) 2 (1-4) 2C-E 2 (19) 1 (1-2) Mescaline 3 (32) 1 (1-1) IQR=Interquartile range

Subjective ratings of stimulant NPS

Figure 6 shows subjective ratings for the stimulant substances of interest. In general, all NPS were rated less favourably than ecstasy and cocaine in terms of pleasurable effects and the likelihood that they would be used again. Acute negative effects and comedown effects were generally rated higher (i.e., more negative) for NPS relative to ecstasy and cocaine, particularly in the case of MDPV.

Figure 6: Mean ratings of stimulant drugs on last occasion of use in the last six months

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Subjective ratings of hallucinogenic NPS

Figure 7 shows subjective ratings for the hallucinogenic substances of interest. In general, hallucinogenic phenethylamines (2C-B, 2C-I, 2C-E, mescaline) were rated as less pleasurable and less likely to be used again compared to LSD, with a similar profile of negative effects, aside from mescaline in which comedown effects were rated as lower (i.e., less negative). DMT showed a similar profile to LSD for pleasurable effects and the likelihood of using again, but DMT showed a more favourable profile in terms of negative (acute and comedown) effects.

Figure 7: Mean ratings of hallucinogenic substances on last occasion of use in the last six months

Matched sample comparisons

Where sufficient data points were available (n>20), paired t-tests were conducted to examine differences in mean rating between traditional illicit substances and NPS. Among those who had used both ecstasy and mephedrone in the last six months (5%, n=66), ecstasy was rated as more positive than mephedrone in terms of pleasurable effects, t(65)=-6.3, p<.001, d=1.14, and likelihood of using again, t(65)=-5.6, p<.001, d=0.92, with a lower rating for acute negative effects, t(65)=2.4, p=.018, d=0.41, and no significant difference in come down effects, t(65)=1.16, p=.25, d=.17 (Figure 8). Among those who had used both ecstasy and methylone in the last six months (4%, n=46), ecstasy was rated more positively than methylone in terms of pleasurable effects, t(45)=-4.5, p<.001, d=0.77, and likelihood of using again, t(45)=-4.03, p<.001, d=0.80, with no significant differences in mean ratings of acute, t(45)=0.23, p=.82, d=0.05, or longer term, t(45)=-0.60, p=.55, d=0.10, negative effects (Figure 8).

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Figure 8: Matched mean ratings of ecstasy and mephedrone (n=66) and ecstasy and methylone (n=46) on last occasion of use in last six months

Cocaine was rated as more positive than mephedrone in terms of pleasurable effects, t(32)=- 2.1, p=.04, d=0.54, and likelihood of using again, t(32)=-4.0, p<.001, d=0.99, amongst those who had used both in the preceding six months (3%, n=33), with a lower rating for negative ‘come down’ effects, t(32)=3.2, p=.003, d=0.68, and no significant difference in acute negative effects, t(32)=1.52, p=.14, d=0.33 (Figure 9). Similarly, cocaine was rated as more positive than methylone in terms of pleasurable effects, t(24)=-3.8, p=.001, d=.95, and likelihood of using again, t(24)=-3.3, p=.003, d=0.82, amongst those who had used both in the preceding six months (2%, n=25), with no significant differences in ratings of acute negative effects, t(25)=1.13, p=.27, d=0.25, or comedown effects, t(25)=0.95, p=.35, d=0.24 (Figure 9).

Figure 9: Matched mean ratings of cocaine and mephedrone (n=33) and cocaine and methylone (n=25) on last occasion of use in last six months

Among those who had used both LSD and 2-CB in the last six months (7%, n=89), LSD was rated as more positive than 2C-B in terms of pleasurable effects, t(88)=5.4, p<.001, d=0.77, and likelihood of using again, t(88)=4.7, p<.001, d=0.58, with no significant differences in terms of 228

acute negative effects, t(88)=-0.68, p=.49, d=0.10 or ‘comedown’ effects, t(88)=-1.9, p=.065, d=.23 (Figure 10). Similarly, among those who had used both LSD and 2-CI in the last six months (4%, n=46), LSD was rated as more positive than 2C-I in terms of pleasurable effects, t(45)=5.4, p<.001, d=1.10, and likelihood of using again, t(45)=5.8, p<.001, d=1.0, with no significant differences in acute negative, t(45)=-0.79, p=.44, d=0.14, or comedown effects, t(45)=5.4, p=.97, d=0.01 (Figure 10).

Figure 10: Matched mean ratings of LSD and 2C-B (n=89) and LSD and 2C-I (n=46) on last occasion of use in last six months

Amongst those who had used both LSD and DMT in the last six months (9%, n=107), there were no significant differences in ratings of pleasurable effects, t(106)=0.31, p=.76, d=.04, or likelihood of using again, t(106)=-1.3, p=.19, d=.16, but acute negative effects, t(106)=3.5, p=.001, d=0.44, and comedown effects, t(106)=7.0, p<.001, d=0.86, were rated as lower for DMT relative to LSD (Figure 11).

Figure 11: Matched mean ratings of LSD and DMT on last occasion of use in last six months (n=107)

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Discussion

The aim of the present study was to examine subjective experiences of NPS among regular psychostimulant consumers and to compare these to other traditional illicit substances. Consideration of the positive and negative subjective perceptions of substances is likely to help predict which substances have potential for transitioning from niche to generalised products, and which substances may expand if there is a decline in availability of more commonly used substances.

The pleasurable effects of two commonly used substances (ecstasy and cocaine) were rated higher than two synthetic cathinones (mephedrone and methylone) among people who had recently used both substances. Similarly, participants indicated that they would be more likely to use ecstasy and cocaine if the opportunity arose. However, mephedrone was rated as more negative than ecstasy in terms of acute negative effects and more negative than cocaine in terms of comedown effects. These findings are broadly consistent with previous research comparing ratings of mephedrone to traditional substances among different groups of people (Uosukainen et al., 2015), and provides further contextual information with regard to methylone. However, the present findings are in contrast to previous research in which mephedrone was rated more favourably in comparison to cocaine (Winstock et al., 2010b).

Similar effects were found for the comparison of hallucinogenic phenethylamines with LSD. The effects of LSD were rated as more pleasurable than both 2C-I and 2C-B and likelihood of further use was rated as higher for LSD. The come down effects were also rated lower for LSD relative to 2C-B. In contrast, there were no differences between LSD and DMT in terms of positive effects, but DMT was rated as lower in terms of acute negative effects and negative come down effects.

The subjective profile of mephedrone and methylone suggests that these are unlikely to become more widely used than ecstasy or cocaine based on drug effects alone. This is consistent with the finding that use of synthetic cathinones among Australian psychostimulant users declined over a six-year period, from 18.5% in 2010 to 7.4% in 2015 (Sutherland et al., 2016). Similarly, although mephedrone remains readily available online, there has been a slight decline in the number of retailers selling this substance to Australia (Van Buskirk et al., 2016). It is possible that the differences between these substances is driven by differences in their pharmacodynamic effects. Synthetic cathinones are thought to have similar psychostimulant effects as ecstasy and cocaine, and similar entactogen effects as ecstasy (Carhart-Harris et al., 2011; Kapitany-Foveny et al., 2013). However, the stimulant effects of mephedrone are considered to be lower in

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potency (due to a lower propensity to cross the blood brain barrier) and shorter in duration relative to phenethylamines such as ecstasy (EMCDDA, 2016). In terms of drug dependence as a potential driver for continued use, some research suggests mephedrone is associated with greater feelings of craving in comparison to MDMA (Brunt et al., 2010), and higher ratings of addictiveness than cocaine (Winstock, Mitcheson, Deluca et al., 2010). However, other research shows that consumers of MDMA and mephedrone are equally likely to report dependence symptoms (Uosukainen et al., 2015).

Subjective effects aside, market factors such as price, availability and purity are also likely to be important factors in the uptake and use of NPS substances (McElrath & Van Hout, 2011). Indeed, amongst Australian psychostimulant consumers, the relative ‘availability’ of mephedrone in comparison to other substances has been reported to be the most common motivation for use (Sutherland et al., submitted for publication). Furthermore, it is notable that increased use of mephedrone on global and Australian drug markets occurred at a time when the purity and availability of ecstasy was considered to be low (Brunt et al., 2010; EMCDDA, 2012), whereas more recent market indicators suggest a return to higher availability and purity of ecstasy (EMCDDA, 2015; Sindicich & Burns, 2014; UNODC, 2014). Factors such as drug purity are also likely to have direct effects on ratings of subjective drug effects. Together the subjective effect profile and market indicator data suggest that NPS such as mephedrone are most likely to temporarily complement, rather than substitute, the use of traditional illicit drugs such as MDMA/ecstasy (Moore et al., 2013).

The subjective profile of DMT (characterised by high ratings of positive effects and low ratings of negative effects) was consistent with previous research comparing first-time users of DMT and other hallucinogens (magic mushrooms, LSD, ketamine) (Winstock et al., 2014). Thus, there may be more potential for the use of DMT to expand among regular drug users. However, the risk of DMT dependence is likely to remain low. For example, DMT was not rated higher in terms of the ‘urge to use more’ among first time users of the drug, suggesting a low potential for abuse, which is a characteristic common to hallucinogenic substances (Winstock et al., 2014). Similarly, the likelihood of using again was rated the same for LSD and DMT among those who had recently used both substances in the present study. DMT is also characterised by a shorter time to peak effect and a shorter duration of effect (Winstock et al., 2014) which may limit potential negative experiences, and this has been noted as a primary motivation for use by Australian psychostimulant consumers (Sutherland et al., submitted for publication).

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The comparisons made between LSD and hallucinogenic phenethylamines are novel to the present study and suggest a relatively low potential for expanded use, particularly in terms of the lower ratings of pleasurable effects. While this is consistent with the plateau in the use of hallucinogenic phenethylamines among regular psychostimulant users in Australia over the past five years, substances from this drug class remain one of the most common NPS consumed among this cohort (Sutherland et al., 2016) or sold on online market places (Van Buskirk et al., 2015). While the present study has focused on 2C-x substances, recent research suggests that NBOMe compounds have a similar positive profile in comparison to LSD, but may have more negative acute effects (Lawn, Barratt, Williams, Horne, & Winstock, 2014). Thus, further research into NBOMe is warranted.

While self-report data may be subject to recall basis, evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use (Darke, 1998). However, participants in the present study were a self-selecting sample of regular psychostimulant users and may not be representative of the NPS using population. A further limitation is that the exact composition and purity of substances are unknown and a majority of the sample were regular users of multiple other substances. Furthermore, given the subjective nature of the rating scales, the pleasurable and negative effects associated with each drug, and the other potential drivers for use (e.g., price, purity, availability) are unknown, and are largely dependent on the individual experiences of each consumer.

Given that NPS continue to emerge at an exponential rate, it is important that we can quickly identify which ones are most attractive to consumers. The present findings have important implications for understanding the potential of NPS to gain further popularity in illicit psychostimulant drug markets and may help to inform policy and frontline workers. The results suggest the popularity of stimulants such as mephedrone and methylone may be lower when compared to commonly used stimulants such as ecstasy and cocaine. Similar findings were found for 2C-I and 2C-B when compared to LSD. In contrast, the potential for DMT to gain continued popularity may be greater given the relatively lower subjective negative effects reported in comparison to LSD.

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References

Brunt, T. M., Poortman, A., Niesink, R. J. M., & Van den Brink, W. (2010). Instability of the ecstasy market and a new kid on the block: Mephedrone. Journal of Psychopharmacology, 24, doi: 10.1177/0269881110378370 Carhart-Harris, R. L., King, L. A., & Nutt, D. J. (2011). A web-based survey on mephedrone. Drug and Alcohol Dependence, 118, 19-22. doi: 10.1016/j.drugalcdep.2011.02.011 Darke, S. (1998). Self-report among injecting drug users: a review. Drug and Alcohol Dependence, 51, 253-263. Davey, Z., Corazza, O., Schifano, F., & Deluca, P. (2010). Mass-information: mephedrone, myths, and the new generation of legal highs. Drugs and Alcohol Today, 10, 24-28. EMCDDA (2012). The state of the drug problem in Europe: Annual report 2012. Luxembourg: European Monitoring Centre for Drugs and Drug Addiction. . Retrieved from http://www.emcdda.europa.eu/attachements.cfm/att_190854_EN_TDAC12001ENC_. pdf. EMCDDA (2015). European Drug Report: Trends and developments 2015. Luxembourg: European Monitoring Centre for Drugs and Drug Addiction. EMCDDA (2016). Synthetic cathinones drug profile. European Monitoring Centre for Drugs and Drug Addiction. . Retrieved from http://www.emcdda.europa.eu/ publications/drug- profiles/synthetic-cathinones. Favretto, D., Pascali, J. P. & Tagliaro, F. 2013. New challenges and innovation in forensic toxicology: Focus on the “New Psychoactive Substances”. Journal of Chromatography A, 1287, 84-95. Freeman, T. P., Morgan, C. J., Vaughn-Jones, J., Hussain, N., Karimi, K., & Curran, H. V. (2012). Cognitive and subjective effects of mephedrone and factors influencing use of a 'new legal high'. Addiction, 107, 792-800. doi: 10.1111/j.1360-0443.2011.03719.x Kapitany-Foveny, M., Kertesz, M., Winstock, A. R., Deluca, P., Corazza, O., Farkas, J., . . . Demetrovics, Z. (2013). Substitutional potential of mephedrone: an analysis of the subjective effects. Hum Psychopharmacol, 28, 308-316. doi: 10.1002/hup.2297 Kyriakou, C., Pellegrini, M., Garcia-Algar, O., Marinelli, E. & Zaami, S. 2017. Recent Trends in Analytical Methods to Determine New Psychoactive Substances in Hair. Current neuropharmacology, 15, 663-681. Lawn, W., Barratt, M., Williams, M., Horne, A., & Winstock, A. (2014). The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. J Psychopharmacol, 28, 780-788. doi: 10.1177/0269881114523866 McElrath, K., & Van Hout, M. C. (2011). A preference for mephedrone: Drug markets, drugs of choice and the emerging legal high scene. The Journal of Drug Issues, 41, 487–507. Measham, F., Moore, K., Newcombe, R., & Welch, Z. (2010). Tweaking, bombing, dabbing and stockpiling: the emergence of mephedrone and the perversity of prohibition. Drugs and Alcohol Today, 10, 14-21. Moore, K., Dargan, P. I., Wood, D. M., & Measham, F. (2013). Do novel psychoactive substances displace established club drugs, supplement them or act as drugs of initiation? The relationahip between mephedrone, ecstasy and cocaine. European Addiction Research, 19, 276-282. 233

Nisbet, Lorna A. (2015) The analysis and detection of new psychoactive substances in biological matrices. PhD thesis, University of Glasgow. Roxburgh, A., Van Buskirk, J., Burns, L. & Bruno, R. (2017). Drugs and the internet, issue 9. Sydney, Australia: National Drug and Alcohol Research Centre. Sindicich, N., & Burns, L. (2013). Australian Trends in Ecstasy and Related Drug Markets 2012: Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No. 82. Sydney: National Drug and Alcohol Research Centre, University of New South Wales. Sindicich, N., & Burns, L. (2014). Australian Trends in Ecstasy and Related Drug Markets 2013: Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trends Series No. 118. Sydney: National Drug and Alcohol Research Centre, University of New South Wales. Sumnall, H. R., Evans-Brown, M., & McVeigh, J. (2011). Social, policy, and public health perspectives on new psychoactive substances. Drug Test Anal, 3, 515-523. doi: 10.1002/dta.310 Sutherland, R., Bruno, R., Peacock, A., Lenton, S., Matthews, A., Salom, C. . . . Barratt, M.. Motivations for new psychoactive substance use among regular psychostimulant users in Sutherland, R., Peacock, A., Whittaker, E., Rioxburgh, A., Lenton, S., Matthews, A., . . . Bruno, R. (2016). New Psychoactive Substance Use among Regular Psychostimulant Users in Australia, 2010-2015. Drug and Alcohol Dependence, 161, 110-118. Tazzite, A., Roky, R. & Avard, D. 2009. [The ethical implications of conserving biological samples]. J Int Bioethique, 20, 87-96, 150-1. Tindana, P., Molyneux, C. S., Bull, S. & Parker, M. 2014. Ethical issues in the export, storage and reuse of human biological samples in biomedical research: perspectives of key stakeholders in Ghana and Kenya. BMC Medical Ethics, 15, 76. UNODC (2014). Global smart update volume 11: The changing nature of ecstasy. Vienna, Austria: UnitedNationsOffice on Drugs and Crime. . Retreived fromhttps://www. unodc.org/documents/scientific/Global_SMART_Update_11_web.pdf. Uosukainen, H., Tacke, U., & Winstock, A. R. (2015). Self-reported prevalence of dependence of MDMA compared to cocaine, mephedrone and ketamine among a sample of recreational poly-drug users. The International Journal on Drug Policy, 26, 78-83. doi: 10.1016/j.drugpo.2014.07.004 van Amsterdam, J. G., Nabben, T., Keiman, D., Haanschoten, G., & Korf, D. (2015). Exploring the Attractiveness of New Psychoactive Substances (NPS) among Experienced Drug Users. J Psychoactive Drugs, 47, 177-181. doi: 10.1080/02791072.2015.1048840 Van Buskirk, J., Naicker, S., Bruno, R., Burns, L., Breen, C., & Roxburgh, A. (2016). Drugs and the internet, issue 6. Sydney, Australia: National Drug and Alcohol Research Centre. Van Buskirk, J., Roxburgh, A., Bruno, R., & Burns, L. (2015). Drugs and the Internet, Issue 5. Sydney, Australia: National Drug and Alcohol Research Centre. Winstock, A. R., Kaar, S., & Borschmann, R. (2014). Dimethyltryptamine (DMT): prevalence, user characteristics and abuse liability in a large global sample. J Psychopharmacol, 28, 49- 54. doi: 10.1177/0269881113513852 Winstock, A. R., Mitcheson, L., & Marsden, J. (2010a). Mephedrone: still available and twice the price. Lancet, 376, 1537-1537. 234

Winstock, A. R., Mitcheson, L., Ramsey, J., Davies, S., Puchnarewicz, M., & Marsden, J. (2011). Mephedrone: use, subjective effects and health risks. Addiction, 106, 1991-1996. doi: 10.1111/j.1360-0443.2011.03502.x Winstock, A. R., Mitcheson, L. R., Deluca, P., Davey, Z., Corazza, O., & Schifano, F. (2010b). Mephedrone, new kid for the chop? Addiction, doi:10.1111/j.1360-0443.2010.03130.x.

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Appendix D: New Psychoactive Substance Use among Regular Psychostimulant Users in Australia, 2010-2016

Rachel Sutherland1, Courtney Breen1 & Raimondo Bruno1

1National Drug and Alcohol Research Centre, UNSW Australia, 22-32 King St, Randwick, NSW, 2052, Australia

Sutherland, R., Breen, C, and Bruno, R. (2016). New psychoactive substance use among regular psychostimulant users in Australia, 2010-2016. EDRS Drug Trends Bulletin, December 2016. Sydney: National Drug and Alcohol Research Centre, University of New South Wales, Australia. https://dlnstorage.blob.core.windows.net/drt101/1832/edrs-december-2016_final.pdf

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Key Findings

. Across 2010-2016, 40.5% of RPU reported use of ‘any’ NPS in the preceding six months; this fluctuated considerably over the years.

. Synthetic cathinones were the most prevalent NPS used by RPU in 2010 (18.5%) but had declined significantly by 2016 (3.3%; p<0.001).

. In 2010 both phenethylamine and tryptamine NPS had been used by 8% of RPU in the six months preceding interview; this increased to 14.2% (p<0.001) and 15.6% (p<0.001) respectively in 2016, making them the two most commonly used groups of NPS.

. Rates of synthetic cannabinoid use fluctuated over the years, with 4.2% of RPU reporting recent use in 2016.

. Recent use of plant-based NPS increased from 2.0% in 2010 to 5.2% in 2016 (p=0.003).

. Recent use of benzylpiperazine declined from 4.9% in 2010 to 0% in 2016 (p<0.001).

. Recent use of methoxetamine and aminoindanes (i.e. MDAI, 5-IAI) remained stable and uncommon across all years.

. NPS markets remain highly dynamic, with the popularity of NPS classes changing over time.

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Introduction

Over the past decade, countries worldwide have witnessed the rapid emergence of substances collectively referred to as ‘new psychoactive substances’ (NPS). NPS are defined by the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) as substances which do not fall under international drug controls but which may pose a public health threat (EMCDDA, 2016a). However, there is no universally accepted way of determining whether individual substances are included within the NPS definition. ‘Older-new’ drugs, such as those currently controlled by international legislation but not previously well-established in the recreational drug-using scene (e.g. dimethyltryptamine; DMT), are also often included as NPS.

In 2015, the European Union were monitoring over 560 NPS, of which 70% were detected in the past five years (EMCDDA, 2016a). The EMCDDA has identified 13 categories of NPS: aminoindanes, arylalkylamines, arylcyclohexylamines, benzodiazepines, synthetic cannabinoids, synthetic cathinones, indolalkylamines (i.e. tryptamines), opioids, phenethylamines, piperazine derivates, piperidines and pyrrolidines, plants and extracts, and others (EMCDDA, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015). The majority of NPS fall into the synthetic cathinone and synthetic cannabinoid categories (EMCDDA, 2016a).

The extent to which NPS are used globally remains unclear, with prevalence rates varying considerably across countries. Data from the European Union found that, in 2014-15, 4% of students aged 15-16 had used an NPS in their lifetime, with use highest in Estonia and Poland (10% each) (EMCDDA 2016b). In regards to past year use it was found that, in 2014, 3% of people aged 15-24 had used an NPS, with use highest in Ireland, Spain and France (5% respectively) (European Commission, 2014). The Crime Survey for England and Wales found that 0.7% of 16- 59 year olds reported past year use of NPS (Home Office, 2016); in the United States, 4.2% of adolescents (grade 8-12) reported past year use of synthetic cannabinoids in 2015 and 0.7% reported use of synthetic stimulants (Johnston et al., 2016). In Australia, the 2013 National Drug Strategy Household Survey showed that 1.2% of the general population had used synthetic cannabinoids in the last 12 months, and 0.4% had used another NPS (Australian Institute of Health & Welfare (AIHW), 2014).

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past month, 75% had also used mephedrone (Moore et al., 2013); whilst a survey of 1,740 nightlife venue patrons in the US found that 8.2% had used synthetic cannabinoids and 1.1% had used mephedrone in the past year (Kelly et al., 2013).

The Ecstasy and related Drugs Reporting System (EDRS) has been monitoring the use of NPS and ‘older-new’ drugs since 2010. Use of these substances have been established as a significant and ongoing practice among this sample, however it remains a highly dynamic marketplace with the popularity of NPS classes changing over time. A previous study looking at trends in NPS classes across 2010-2015 found that there were significant declines in the use of synthetic cathinones and synthetic cannabinoids among EDRS participants, whilst the use of phenethylamines, tryptamines and plant-based NPS had increased over time (Sutherland et al., 2016). Given the size and the rapidly evolving nature of the NPS market, it is important that these trends continue to be monitored. The current bulletin builds upon our previous work by examining the rates of NPS and ‘older-new’ substance use (hereafter referred to as NPS) amongst a sample of regular psychostimulant users (RPU) in Australia, from 2010-2016.

Method

Study design

This paper uses seven years of data (2010-2016) from the Ecstasy and related Drugs Reporting System (EDRS) (for full protocol details, see Sindicich et al., 2016). The EDRS is a national monitoring study aimed at detecting emerging trends in illicit drug markets and has been conducted annually in all Australian jurisdictions since 2003. The EDRS has received ethical approval from the University of New South Wales Human Research Ethics Committee (HC10071, HC15015), as well as from the relevant ethics committees in each jurisdiction.

Participants and procedure

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Measures relevant to the current study

From 2010-2016, participants were asked about their past six month use of 30 specific NPS (see Table 34 for a full list, with street names provided in brackets); an open text ‘other’ option was provided to capture any additional NPS not listed in the survey. These NPS have been categorised into nine of the thirteen categories identified by the EMCDDA; namely synthetic cannabinoids, synthetic cathinones (i.e. stimulant and entactogen phenethylamines), phenethylamines (i.e. psychedelic phenethylamines), tryptamines, piperazines, plant and extracts, aminoindanes, arylcyclohexylamines and benzodiazepines.

Statistical analysis

Rates of use were generated by collapsing the various NPS to determine if participants had consumed ‘any’ NPS in the six months preceding interview. Using the groupings identified by the EMCDDA, rates of use were then broken down into the following classes; synthetic cannabinoids, synthetic cathinones, phenethylamines, tryptamines, piperazines, plants and extracts, aminoindanes, arylcyclohexylamines and benzodiazepines. Paired comparisons of percentages reporting use were made across adjacent years (e.g. 2010-2011; 2011-2012) with 95% confidence intervals (95% CI) reported. Associations were set for statistical significance at p < 0.05. All analyses were conducted using IBM SPSS Statistics for Windows release 22.0 (IBM Corporation, 2013).

Results

Demographics

Across 2010-2016, 4,917 participants were recruited and interviewed for the EDRS, of which 631 were repeat participants (see Table 32). Sixty-four percent of the entire RPU cohort were male with a median age of 22 years (IQR 19-25), 97% were of English speaking background, 46% were tertiary qualified, 69% were employed in some capacity, 33% were students, 15% were unemployed and 3% were currently in drug treatment. Twelve percent of the 2010-2016 cohort identified as gay, lesbian, bisexual or transgendered (GLBT). More detailed demographics of each year’s sample have been reported elsewhere (Sindicich & Burns, 2011, 2012, 2013, 2014, 2015; Sindicich et al., 2016).

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Table 33: Number of participants, 2010-2016 Total number of participants Number of repeat participants n n (%) 2010 693 115 (16.6) 2011 574 104 (18.1) 2012 607 81 (13.3) 2013 685 65 (9.5) 2014 800 81 (10.1) 2015 763 83 (10.9) 2016 795 102 (12.8)

Patterns of the most commonly used NPS in 2016

In 2016, the most commonly used NPS were DMT, 2C-B, synthetic cannabinoids and NBOMe, although frequency of use was low for all these substances (range 1-3 days). Most NPS consumers reported obtaining these substances through friends and dealers, except for synthetic cannabinoid users who had mostly sourced these substances from a retail outlet. Smoking was the most common route of administration (ROA) reported by DMT and synthetic cannabinoid users, and swallowing was the most common ROA among 2C-B and NBOMe consumers. DMT consumers mostly reported using this substance in crystal (46%) and/or plant matter (41%) form; synthetic cannabinoid users reported exclusive use of plant matter form (100%); and NBOMe consumers mostly reported use of tabs of blotter paper (94%). Almost equal proportions of 2C-B consumers reported use of capsules (36%), powder (30%) and pills (23%).

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Table 34: Patterns of NPS use among RPU, 2016 DMT 2C-B Synthetic NBOMe cannabinoids Lifetime use % 27.3 21.8 19.5 11.3 Past 6 month use % 15.0 8.9 4.2 3.9 Median days of 1.0 (1-15) 1.0 (1-28) 3.0 (1-72) 1.0 (1-12) use* (range) Last source* % N=118 N=71 N=33 N=31 Shop 0 0 51.5 0 Internet 9.3 14.1 0 22.6 Dealer 20.3 22.5 6.1 41.9 Friend 55.1 52.1 30.3 32.3 Gift 11.9 7.0 9.1 0 Other 3.4 4.2 3.0 3.2 ROA*# % N=119 N=71 N=32 N=30 Swallow 1.7 69.0 0 96.7 Inject 0 2.8 0 3.3 Smoke 94.1 0 100 0 Snort 3.4 39.4 0 3.3 Forms used*# % N=116 N=70 N=30 N=31 Pills 0.9 22.9 0 3.2 Capsules 0 35.7 0 0 Tabs 0 8.6 0 93.5 Plant matter 41.4 0 100 0 Powder 17.2 30.0 0 3.2 Crystal 45.7 5.7 0 0 Liquid 2.6 4.3 0 0 Other 4.3 0 0 0 *In the past six months # Multiple responses allowed; hence sum of percentages may exceed 100% Note: ROA = route of administration

Rates of recent NPS use

From 2010-2016, 40.5% of the entire sample (n=1,923) reported use of ‘any’ NPS in the six months preceding interview. Specifically, one-third (32.9%) of RPU reported recent use of any NPS in 2010; this increased to 41.7% in 2011 (p=0.002), before reaching a peak of 51.6% in 2012 (p=0.002). Recent NPS use remained stable in 2013 (46.6%), before declining significantly in 2014 (40.6%; p=0.023) and then stabilising in 2015 (40.2%). In 2016, there was another significant decline in recent NPS use (33.8%; p=0.011), returning to levels of use observed in 2010 (Table 34).

Looking at the different classes of NPS (Table 34), cathinones were originally the most prevalent NPS being used by participants, with almost one-fifth (18.5%) of RPU reporting recent (i.e. past six month) use in 2010. However, by 2016 this had declined significantly, with 3.3% reporting use of cathinones in the six months preceding interview (p<0.001). Conversely, in 2010 both

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phenethylamines and tryptamines had been used by 8% of RPU in the six months preceding interview; however, by 2016 rates of use had increased to 14.2% (p<0.001) and 15.6% (p<0.001) respectively, making them the two most commonly used groups of NPS in these years. Despite the overall increase in recent phenethylamine use from 2010-2016, it is interesting to note that there was a significant decrease in its use in 2016 (after having remained stable for the preceding couple of years).

The use of synthetic cannabinoids was asked about for the first time in 2011, with 6.6% of RPU reporting use within the six months preceding interview. This increased significantly in 2012 to 16.1% of the sample (p<0.001) and remained stable in 2013 (16.1%). However, in 2014 use of recent synthetic cannabinoids declined to rates observed in 2011 (6.9%; p<0.001), before stabilising in 2015 (6.4%) and 2016 (4.2%).

The use of piperazines, plant-based NPS and aminoindanes remained uncommon across all years. Specifically, from 2010-2016, the use of piperazines declined from 4.9% to 0% (p<0.001); plant-based NPS increased from 2.0% to 5.2% (p=0.003); and there was no change in the use of aminoindanes or arylcyclohexylamines. Etizolam (a novel benzodiazepine) was asked about for the first time in 2016, with 0.9% of the sample reporting use in the six months preceding interview.

These trends remained consistent even when repeat participants were excluded.

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Table 35: Rates# of NPS use amongst RPU, 2010-2016 2010 % 2011 % 2012 % 2013 % 2014 % 2015 % 2016 % 2010-2016## % (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) 95% CI; p value SYNTHETIC CATHINONES 18.5 17.7 11.4 9.2 8.0 7.7 3.3 10.2 Mephedrone (miaow, 4MMC); Methylone (bk- (-0.04, 0.05; (0.02, 0.11; (-0.01, 0.06; (-0.02, 0.04; (-0.02, 0.03; (0.02, 0.07; ↓ 0.12,0.19; MDMA); 4-MEC; Alpha-PVP (flakka); MDPV p=0.796) p=0.004)* p=0.229) p=0.466) p=0.919) p<0.001)* p<0.001* (Ivory Wave); Other substituted cathinone PHENETHYLAMINES 8.0 15.6 14.6 20.7 21.3 18.6 14.2 16.4 2C-I; 2C-B (Bromo, TWOs, trystacy); 2C-E (-0.11, -0.04; (-0.03, 0.05; (-0.10, -0.02; (-0.05, 0.04; (-0.01, 0.07; (0.01, 0.08; ↑ -0.09,0.03; (hummingbird, europa); 2C-Other; Benzo Fury p<0.001)* p=0.706) p=0.008)* p=0.846) p=0.210) p=0.02)* p<0.001* (6-APB); PMA; DOI (death on impact); NBOMe (25I, 25B, 25C); 4-FA TRYPTAMINES 7.5 14.1 14.2 14.6 14.4 10.9 15.6 13.1 DMT; 5-Meo-DMT; 4-AcO-DMT (-0.10, -0.03; (-0.04, 0.04; (-0.04, 0.04; (-0.03, 0.04; (0.002, 0.07; (-0.08, -0.01; ↑ -0.11, -0.05; p<0.001)* p=0.960) p=0.911) p=0.962) p=0.045)* p=0.008)* p<0.001* SYNTHETIC CANNABINOIDS n/a 6.6 16.1 16.1 6.9 6.4 4.2 9.0 K2/Spice; Kronic; Other synthetic (-0.13, -0.06; (-0.04, 0.04; (0.06, 0.13; (-0.02, 0.03; (0.004, 0.05; 0.0001, cannainoid p<0.001)* p=0.960) p<0.001)* p=0.797) p=0.058) 0.05; p=0.065 PIPERAZINES 4.9 1.7 1.2 0.3 0.3 0 0 1.1 BZP (0.01, 0.05; (-0.01, 0.02; (0.001, 0.02; (-0.01, 0.01; (-0.003, ↓ 0.03, 0.07; p=0.005)* p=0.690) p=0.106) p=0.729) 0.01; p<0.001* p=0.500) PLANTS & EXTRACTS 2.0 7.2 7.7 6.4 4.4 5.0 5.2 5.3 LSA (Hawaiian Baby); Mescaline; Salvia (-0.08, -0.03; (-0.04, 0.03; (-0.02, 0.04; (-0.003, 0.05; (-0.03, 0.02; (-0.02, 0.02; ↑ -0.05, -0.01; Divinorum; Datura (Angel’s trumpet); p<0.001)* p=0.840) p=0.455) p=0.102) p=0.655) p=0.965) p=0.003* Ayahuasca AMINOINDANES n/a n/a 0.9 0.7 0.5 0.4 0.3 0.5 MDAI; 5-IAI (-0.01, 0.01; (-0.01, 0.01; (-0.01, 0.01; (-0.006, 0.009; -0.002, 0.02; p=0.977) p=0.815) p=0.950) p=0.963) p=0.227 ARYLCYCLOHEXYLAMINES n/a n/a 1.4 2.2 1.6 2.2 3.0 2.1 Methoxetamine (MXE) (-0.02, 0.01; (-0.01, 0.02; (-0.02, 0.01; (-0.02, 0.009; -0.03, 0.0004; p=0.408) p=0.544) p=0.494) p=0.414) p=0.077

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Table 35 (continued): Rates# of NPS use amongst RPU, 2010-2016 2010 % 2011 % 2012 % 2013 % 2014 % 2015 % 2016 % 2010-2016## % (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) (95% CI; p) 95% CI; p value BENZODIAZEPINES n/a n/a n/a n/a n/a n/a 0.9 n/a Etizolam ANY NPS % 32.9 41.7 51.6 46.6 40.6 40.2 33.8 40.5 (-0.14, -0.03; (-0.16, -0.04; (-0.01, 0.11; (0.01, 0.11; (-0.04, 0.05; (0.02, 0.11; -0.06, 0.04; p=0.002)* p=0.002)* p=0.092) p=0.023)* p=0.915) p=0.011)* p=0.753 #in the past six months; ##for synthetic cannabinoids this refers to 2011-2016 figures; for aminoindanes and arylcyclohexylamines this refers to 2012-2016 figures; *Significant differences found (significant findings have also been bolded); Pairwise comparisons were made across adjacent years; i.e. 2010 vs 2011; 2011 vs 2012; 2012 vs 2013; 2013 vs 2014; 2014 vs 2015; 2015 vs 2016; 95% CI refers to the differences across adjacent years, except for the final column where they refer to differences in 2010 vs 2016 percentages; = a significant increase in 2010 vs 2016 figures; = a significant decrease in 2010 vs 2016 figures. − no change in 2010 vs 2016 figures. n/a=not asked in these years.

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Discussion

The use of NPS has been established as a significant and ongoing practice amongst cross- sectional samples of RPU in Australia, although there has been fluctuation in specific NPS use over the years. Specifically, the use of synthetic cathinones and synthetic cannabinoids have declined, whilst the use of psychedelic NPS (i.e. phenethylamines and tryptamines) appear to have become relatively well-established. It is difficult to make any direct comparisons to other studies (particularly given differences in time frames, samples and categorisations of NPS), however it appears that the changes noted in our sample mirror a number of international trends (European Commission, 2014; Home Office, 2016; Johnston et al., 2016). For example, in the United States there were significant declines in past year use of synthetic cannabinoids and synthetic stimulants among adolescents from 2012 to 2015 (Johnston et al., 2016), whilst in the United Kingdom past year use of mephedrone among 16 to 59 year olds declined between 2010/11 to 2015/16 (Home Office, 2016). Indeed, although the majority (70%) of NPS being monitored by the EMCDDA fall into the stimulant and synthetic cannabinoid effect classes (EMCDDA, 2016a), psychedelic NPS (i.e. DMT, NBOMe and 2C-x) remain the most commonly sold NPS on dark net marketplaces (Van Buskirk et al., 2016). Furthermore, a recent study of experienced recreational drug users in the Netherlands found that while participants were more likely to have ever used stimulant NPS, in the future they predominantly intended to try psychedelic NPS (van Amsterdam et al., 2015).

It is unknown what might be driving the specific trends observed in this paper; however, consumer acceptability and legislative changes are factors to consider. In 2013, EDRS participants were asked to rate the positive, negative and hangover effects of NPS, and how likely they would be to consume the substance again. DMT and 2CB received the highest ratings for pleasurability and likelihood to take again, whilst mephedrone and synthetic cannabinoids were viewed less favourably and reportedly had worse side effects (Matthews et al., 2016; Sindicich & Burns, 2014). Similarly, a self-selecting online sample of DMT and NBOMe users found that when compared to other hallucinogens (i.e. LSD, magic mushrooms and ketamine) both DMT and NBOMe were rated favourably in terms of strength of effect and pleasurability (Lawn et al., 2014; Winstock et al., 2013). In contrast, a global study of dual ‘natural’ and synthetic cannabis users found that 93% of participants preferred natural cannabis over synthetic cannabis (Winstock & Barratt, 2013). It seems likely that our sample of RPU experimented with a range of NPS, continuing to use those deemed ‘acceptable’ in terms of their psychopharmacological and side effects, and ceasing use of those that were not. This theory is supported by findings that DMT, 2C-x and NBOMe remain the most commonly sold 246

NPS on dark net marketplaces (Van Buskirk et al., 2016), however, it would be of benefit for future research to explicitly test this hypothesis through a close examination of the motivations for consuming specific NPS.

Another factor to consider is the impact of legislative changes. Given the varying legislative frameworks across jurisdictions and the different dates of implementation, it is beyond the scope of this paper to determine whether the scheduling of NPS may have contributed to the trends observed in this paper. For example, in 2012, the Australian Therapeutic Goods Administration introduced a blanket ban on any type of synthetic cannabinoid that produced the same pharmacological effect as cannabis (Bright et al., 2013). In 2014 there was a significant decline in the use of synthetic cannabinoids amongst our sample of RPU; however, it is unclear if this was a lagged effect of the legislation (due to practices such as stockpiling) or if it was due to other, unrelated factors such as consumer acceptability. Studies in other countries have found that rates of NPS use fell following their prohibition. For example, in the UK it was found that once mephedrone was listed as a controlled substance, self-reported use fell (Lader, 2015); similarly, following the prohibition of BZP in New Zealand, there was a decline in self-reported use among the general population (Wilkins & Sweetsur, 2013). However, it is unclear if such declines were the result of reduced availability following the legislative changes or if they were the result of a general deterrent effect (or both). Indeed, a number of NPS have remained relatively common despite their subsequent prohibition, and in such cases legal status is considered to be a secondary driver for use, particularly among those who already use illicit drugs (Measham & Newcombe, in press). It would be of interest for future research to evaluate the impact of Australian legislation on the NPS marketplace to provide an evidence-base for the efficacy of these regulatory approaches.

Limitations

This study has certain limitations. Firstly, the EDRS sample is not representative, which means that our findings are not generalizable to all RPU in Australia. Rather, it is a sentinel sample which allows for the early identification of trends in illicit drug markets, which is particularly important when monitoring marketplaces which are rapidly changing (as is the case of NPS). Secondly, our analysis is reliant upon self-report data from participants which may be subject to bias. Although evidence points to sufficient validity and reliability of self-report in studies assessing illicit drug use (Darke, 1998), it is possible that participants may have incorrectly identified the NPS being consumed (i.e. it may have been sold to them as one thing, but have been something else). Indeed, the data presented in this bulletin refers only to the intentional consumption of NPS,

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and rates of unintentional use could potentially be much higher; it would be of benefit for future studies to corroborate their findings through chemical analysis. Finally, the EDRS only specifically asked about 30 different NPS and as such rates of use may be underestimated.

Conclusions

Whilst NPS use has been established as a significant and ongoing practice amongst our sample of RPU, it remains a highly dynamic marketplace with the popularity of NPS classes changing significantly across 2010-2016. Indeed, the globalisation of drug marketplaces has increased the accessibility and volatility of drugs such as NPS (Griffiths et al., 2010), and it is essential that projects such as the EDRS continue to monitor these substances so that changing trends can be detected in a timely manner.

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References

Australian Institute of Health and Welfare (AHIW), 2014. 2013 National Drug Strategy Household Survey: Detailed Findings. Canberra: Australian Institute of Health and Welfare. Bonar, E.E., Ashrafioun, L., Ilgen, M.A., 2014. Synthetic cannabinoid use among patients in residential substance use disorder treatment: Prevalence, motives, and correlates. Drug and Alcohol Dependence. 143, 268-271. Bretteville-Jensen, A.L., Tuv., S.S., Bilgrei, O.R., Fjeld, B., Bachs, L., 2013. Synthetic cannabinoids and cathinone: Prevalence and markets. Forensic Science Review. 25(1-2), 7-26. Bright, S.J., Bishop, B., Kane, R., Marsh, A., Barratt, M.J., 2013., Kronic hysteria: Exploring the intersection between Australian synthetic cannabis legislation, the media, and drug-related harm. International Journal of Drug Policy. doi:10.1016/j.drugpo.2012.12.002. Burns, L., Roxburgh, A., Matthews, A., Bruno, R., Lenton, S., Van Buskirk, J., 2014. The rise of new psychoactive use in Australia. Drug Testing and Analysis. 6, 846-849. Darke, S., 1998. Self report among injecting drug users: A review. Drug & Alcohol Dependence. 51 (3), 253-263. European Commission, 2014. Young People and Drugs. Flash Eurobarometer 401. Available from: . [1 December 2015]. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2006. Eurpol 2005 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2007. Eurpol 2006 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2008. Eurpol 2007 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2009. Eurpol 2008 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2010. Eurpol 2009 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2011. Eurpol 2010 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2012. Eurpol 2011 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2013. New Drugs in Europe, 2012. Eurpol 2012 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2014. Eurpol 2013 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2015. Eurpol 2014 Annual Report on the Implementation of Council Decision 2005/387/JHA. Lisbon: EMCDDA. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2016a. Health responses to new psychoactive substances. Luxembourg: Publications Office of the European Union.

249

European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2016b. ESPAD Report 2015. Results from the European School Survey Project on Alcohol and Other Drugs. Luxembourg: Publications Office of the European Union. Griffiths, P., Sedefov, R., Gallegos, A., Lopez, D., 2010. How globalization and market innovation challenge how we think about and respond to drug use: ‘Spice’ a case study. Addiction. 105, 951- 953. Home Office, 2016. Drug Misuse: Findings from the 2015/16 Crime Survey for England and Wales. Statistical Bulletin 07/16. London: Home Office. Available from: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/564760/dru g-misuse-1516.pdf [8 November 2016]. IBM Corporation, 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corporation. Johnston, L.D., O’Malley, P., Miech, R.A., Bachman, J.G. & Schulenberg, J.E., 2016. Monitoring the Future National Survey Results on Drug Use, 1975-2015. 2015 Overview: Key Findings on Adolescent Drug Use. Ann Arbor: Institute for Social Research, University of Michigan. Kelly, B.C., Wells, B.E., Pawson, M., Leclair, A., Parsons, J.T., Golub, S.A., 2013. Novel psychoactive substance use among younger adults involved in US nightlife scenes. Drug and Alcohol Review. 32(6), 588-593. Lader, D. (2015). Drug Misuse: Findings from the 2014/15 Crime Survey for England and Wales. Retrieved from https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/462885/dru g-misuse-1415.pdf Lawn, W., Barratt, M., Williams, M., Horne, A., Winstock, A., 2014. The NBOMe hallucinogenic drug series: Patterns of use, characteristics of users and self-reported effects in a large international sample. Journal of Psychopharmacology. 28(8), 780-788. Matthews, A., Sutherland, R., Peacock, A., Van Buskirk, J., Whittaker, E., Burns, L. & Bruno, R. 2016. I like the old stuff better than the new stuff? Subjective experiences of new psychoactive substances. International Journal of Drug Policy, (Under Review). Measham, F., & Newcombe, R. (in press). What’s so new about new psychoactive substances? Definitions, prevalence, motivations, user groups and a proposed new taxonomy. In K. B. Thom & G. Hunt (Eds.), The SAGE Handbook of Drug & Alcohol Studies (Vol. 1). London: Sage. Moore, K., Dargan, P.I., Wood, D.M., Measham, F., 2013. Do novel psychoactive substances displace established club drugs, supplement them or act as drugs of initiation? The relationship between mephedrone, ecstasy and cocaine. European Addiction Research. 19, 276-282. Sindicich, N., Burns, L., 2011. Australian Trends in Ecstasy and Related Drug Markets 2010. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 64. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Burns, L., 2012. Australian Trends in Ecstasy and Related Drug Markets 2011. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 82. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Burns, L., 2013. Australian Trends in Ecstasy and Related Drug Markets 2012. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 100. Sydney: National Drug and Alcohol Research Centre, UNSW Australia.

250

Sindicich, N., Burns, L., 2014. Australian Trends in Ecstasy and Related Drug Markets 2013. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 118. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Burns, L., 2015. Australian Trends in Ecstasy and Related Drug Markets 2014. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 136. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sindicich, N., Stafford, J. & Breen, C., 2016. Australian Trends in Ecstasy and Related Drug Markets 2015. Findings from the Ecstasy and Related Drugs Reporting System (EDRS). Australian Drug Trend Series No. 154. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Stafford, J., Burns, L., 2015. Australian Drug Trends. Findings from the 2014 Illicit Drug Reporting System (EDRS). Australian Drug Trend Series No. 127. Sydney: National Drug and Alcohol Research Centre, UNSW Australia. Sutherland, R., Peacock, A., Whittaker, E., Roxburgh, A., Lenton, S., Matthews, A., Butler, K., Nelson, M., Burns, L. & Bruno, R. (2016). New psychoactive substance use among regular psychostimulant users in Australia, 2010–2015. Drug and Alcohol Dependence, 161, 110-118. doi: http://dx.doi.org/10.1016/j.drugalcdep.2016.01.024 United Nations Office on Drugs and Crime (UNODC), 2013. The Challenges of New Psychoactive Substances. A Report from the Global SMART Programme. Vienna: UNODC. Wilkins, C., & Sweetsur, P. (2013). The impact of the prohibition of benzylpiperazine (BZP) ‘legal highs’ on the prevalence of BZP, new legal highs and other drug use in New Zealand. Drug and Alcohol Dependence, 127(1–3), 72-80. doi:http://dx.doi.org/10.1016/j.drugalcdep.2012.06.014 Winstock, A.R., 2015. The Global Drug Survey 2015 Findings. Available from: . [1 December 2015]. Winstock, A.R., Barratt, M.J., 2013. Synthetic cannabis: A comparison of patterns of use and effect profile with natural cannabis in a large global sample. Drug and Alcohol Dependence. 131(1-2), 106-11. Winstock, A.R., Kaar, S., Borschmann, R., 2013. Dimethyltrytamine (DMT): Prevalence, user characteristics and abuse liability in a large global sample. Journal of Psychopharmacology. DOI: 10.1177/0269881113513852. Van Buskirk, J., Naicker, S., Bruno, R., Burns, L., Breen, C. & Roxburgh, A. 2016. Drugs and the Internet. Issue 7, Sydney: National Drug and Alcohol Research Centre. Vento, A.E., Martinotti, G., Cinosi, E., Lupi, M., Acciavatti, T., Carrus, D., Santacroce, R., Chillemi, E., Bonifaci, L., di Giannantonio, M., Corazzam O., Schifano, F., 2014. Substance use in the club scene of Rome: A pilot study. BioMed Research International. http://dx.doi.org/10.1155/2014/617546. van Amsterdam, J. G. C., Nabben, T., Keiman, D., Haanschoten, G., & Korf, D. (2015). Exploring the Attractiveness of New Psychoactive Substances (NPS) among Experienced Drug Users. Journal of Psychoactive Drugs, 47(3), 177-181. doi:10.1080/02791072.2015.104884

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Appendix E: Changing patterns of new and emerging psychoactive substances in Australia

Ms Rachel Sutherland1 1National Drug and Alcohol Research Centre, UNSW Australia, 22-32 King St, Randwick, NSW, 2052, Australia

Presented at the 2017 NDARC Annual Research Symposium, 4th October 2017, UNSW, Sydney

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Abstract

Aim: This paper examines rates of new and emerging psychoactive substance (NPS) use amongst a sample of people who regularly use psychostimulants in Australia, over the time period 2010 to 2017.

Method: Data were obtained from the Ecstasy and related Drugs Reporting System (EDRS), an annual national monitoring study aimed at detecting emerging trends in illicit drug markets, and examined over the years 2010 to 2017.

Results: Results from 2010-2017 (n=5,703) show that recent use of ‘any’ NPS has fluctuated over time, peaking at 52% in 2012 and declining steadily in recent years (to 33% in 2017). In 2010, synthetic cathinones were the most commonly used NPS (19%), but had declined significantly by 2017 (5%; p<0.001). Conversely, both phenethylamine and tryptamine NPS had been used by 8% of the sample in the six months preceding interview; this increased to 14% (p<0.001) and 18% (p<0.001) respectively in 2017, making them the two most commonly used groups of NPS. Rates of synthetic cannabinoid use have fluctuated over the years, with 2% of the sample reporting recent use in 2017. Recent use of plant-based NPS increased from 2% in 2010 to 5% in 2017 (p=0.007), whilst recent use of benzylpiperazine declined from 5% in 2010 to <1% in 2017 (p<0.001). Recent use of methoxetamine and aminoindanes (i.e. MDAI, 5-IAI) remained stable and uncommon across all years.

Conclusions: Despite ‘blanket ban’ regulations across Australia, intentional NPS use has been established as a significant and ongoing practice amongst our sample of people who regularly use psychostimulants. However, it remains a highly dynamic marketplace, with the popularity of NPS classes changing over time. Rates of ‘unintentional’ NPS use in Australia remain largely unknown, with further research required on this topic.

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