Thesis (Complete)

E valuation Invitation to attend the public defence of my doctoral thesis of smoking Evaluation of smoking cEssation cessation services in

disadvantaged areas of sErvicEs the Netherlands in disadvantagEd

on Friday, 19 February, 2016, at 12.00 noon in

arEas the Agnietenkapel of the University of Amsterdam. of thE n

EthErlands Agnietenkapel Oudezijds Voorburgwal 229-231 1012 EZ Amsterdam

You are warmly invited to the reception which will follow the defence.

Fiona Benson [email protected] Evaluation of smoking cEssation Paranymphs

F. E. Benson sErvicEs in disadvantagEd arEas of Jizzo Bosdriesz [email protected] thE nEthErlands F. E. Benson Anna Font-Gonzalez [email protected]

400350-L-os-Benson Processed on: 12_22_2015

Fiona E. Benson Evaluation of smoking cessation services in disadvantaged areas of the Netherlands

400350-L-bw-Benson © F.E. Benson, 2015

All rights reserved. No part of this thesis may be reproduced, stored or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or otherwise, without the written permission of the author.

ISBN: 978-94-6259-847-8

Cover design & layout: Heleen de Vos, Persoonlijkproefschrift.nl Printed by: Ipskamp Printing

The studies described in this thesis were funded by the Netherlands Organisation for Health Research and Development (ZonMw) under grant agreement number: 200120004. One study, described in chapter 5, received two additional sources of funding, which were from the SOPHIE and URBAN40 projects. The SOPHIE project received funding from European Community’s Seventh Framework Program (FP7) under grant agreement number 278173. The URBAN40 project received funding from ZonMw under the grant agreement numbers 121010009. The study described in chapter 6 used data from The Dutch Continuous Survey of Smoking Habits (DCSSH) study, which was supported by grants from the Dutch Ministry of Health, Welfare and Sports.

Printed on recycled paper.

400350-L-bw-Benson EVALUATION OF SMOKING CESSATION SERVICES IN DISADVANTAGED AREAS OF THE NETHERLANDS

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. D.C. van den Boom ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op vrijdag 19 februari 2016, te 12:00 uur

door

Fiona Elizabeth Benson geboren te Gisborne, Australië

400350-L-bw-Benson PROMOTIECOMMISSIE Promotores:

prof. dr. K. Stronks Universiteit van Amsterdam

prof. dr. M.C. Willemsen Maastricht University

Copromotor:

dr. V. Nierkens Leids Universitair Medisch Centrum

Overige leden:

prof. dr. A. Amos University of Edinburgh

prof. dr. A.E. Kunst Universiteit van Amsterdam

prof. dr. B.J.C. Middelkoop Universiteit Leiden

prof. dr. S.J.H.M. van den Putte Universiteit van Amsterdam

prof. dr. P. Baas Universiteit van Amsterdam

Faculteit der Geneeskunde

400350-L-bw-Benson For Thomas, Ian & Eliza, with love.

400350-L-bw-Benson 400350-L-bw-Benson TAbLE OF CONTENTS

Chapter 1 General introduction 9

PART 1 Evaluation of smoking cessation behavioural therapy 27 interventions in disadvantaged areas of the Netherlands.

Chapter 2 Effects of different types of smoking cessation behavioural 29 therapy in disadvantaged areas in the Netherlands: an observational study.

Chapter 3 Smoking cessation behavioural therapy in disadvantaged 49 neighbourhoods: an explorative analysis of recruitment channels.

Chapter 4 Wanting to attend isn’t just wanting to quit: Why do some 71 disadvantaged smokers regularly attend smoking cessation therapy while others do not? A qualitative study.

PART 2 The influence of the prevailing economic conditions and social 95 norms on inequalities in smoking cessation.

Chapter 5 Socioeconomic inequalities in smoking in The Netherlands before 97 and during the Global Financial Crisis.

Chapter 6 Inequalities in the impact of national reimbursement of smoking- 123 cessation pharmacotherapy and the influence of injunctive norms. An explorative study.

Chapter 7 General discussion 141

Summary 160

Samenvatting 164

Contributing authors 168

Author contributions 169

PhD portfolio 170

Acknowledgements 172

About the author 176

400350-L-bw-Benson 400350-L-bw-Benson Chapter 1 General Introduction

400350-L-bw-Benson INEqUALITIES IN SMOKING AND qUITTING The dangers of smoking are well documented: one in two smokers will die as a consequence of their tobacco use [1], smoking is the second largest modifiable risk factor for non-communi- cable disease burden worldwide [2], and smokers die considerably earlier than non-smokers [3]. However, smoking and its accompanying harms are not distributed equally throughout society. In European countries, there is a strong socioeconomic gradient in smoking, such that those of low income, educational level or those living in deprived areas smoke more than those who are classified as middle on these indicators, who, in turn, smoke more than those who have high incomes, are highly educated or are living in the most advantaged areas [4-7]. This is also cumulative, such that those who experience multiple forms of disadvantage in developed countries smoke the most [8]. This leads to a socioeconomic gradient in the harms caused by smoking [9], such as lung cancer and cardiovascular disease [10-12]. In women, cardiovascular disease accounted for 60% of the difference in total mortality between low and high socioeconomic status groups, and 39% in men. Indeed, in men, smoking is responsible for most of the inequalities in mortality [13].

Helping current smokers to quit is one major way to decrease the harms caused by smoking. However, there is also a strong socioeconomic gradient in quitting [8]. While the number of attempts made seem to be similar in high and low socioeconomic status (SES) groups [14,15], disadvantaged smokers (measured by income, education or area deprivation), make less successful quit attempts [14-18]. In high income countries inequalities in smoking prevalence and cessation appear to be increasing [16,19-21].

Success of measures to decrease inequalities in smoking prevalence and cessation Interventions at an individual and population level have been undertaken in an attempt to decrease smoking in many countries [22-26]. While many of these measures are successful in increasing quit attempts in general, there is little available evidence that any of these measures decrease inequalities, with the exception of either increasing the price/tax of tobacco products, as has been done in several countries, or offering smoking cessation behavioural therapy (SCBT) with pharmacotherapy in smoking cessation clinics specifically located in disadvantaged areas, as has been done in England [27,28]. The latter of these is an intervention at an individual level implemented on a population level. SCBT increases the success of quit attempts, with or without use of smoking cessation pharmacotherapy [25,26,29,30]. While SCBT increases the success of quit attempts in those of low SES, the effect in those of high SES is greater [31], thus increasing the social gradient. However, due to the larger throughput of low SES individuals, inequalities have probably been lessened by this policy in England [32].

SMOKING CESSATION - THE ENGLISH ExAMPLE In 1974, 45% of the British population smoked (Figure 1). The prevalence of current smoking in the United Kingdom (UK) has been decreasing for several decades, however, prevalence differs in different SES groups.

400350-L-bw-Benson Chapter 1

Figure 1: Prevalence of smokers Great Britain from 1974-2010* **

*Data is unweighted until 1998 **2014 data unavailable. Source: Office for National Statistics (ONS) [33,34] An example of this is the lower smoking prevalence in households where the reference person was in a managerial or professional occupation, compared with those households where the reference person was in a routine or manual job (Figure 2). Occupational level is one of the primary ways vof assessing SES in the UK [35].

Figure 2: Smoking prevalence per occupational status of the household reference person in Great Britain (2001-2013)

Source: ONS [34,36-39]

400350-L-bw-Benson In 1998, in response to the toll on the UK population taken by smoking, the British Government published the white paper, ‘Smoking Kills’, which had three objectives: “to reduce smoking among children and young people; to help adults – especially the most disadvantaged – to give up smoking; to offer particular help to pregnant women who smoke” (point 2.1) [40]. This White Paper outlined evidence-based policy measures to meet these objectives [40]. These measures included increasing taxation on cigarettes. As this strategy specifically targeted those of low SES, this was to be balanced by offering all smokers wishing to stop, evidence-based assistance, but specifically targeting it those living in disadvantaged areas. The offering included SCBT, and a free prescription of smoking cessation pharmacotherapy for disadvantaged smokers if combined with the SCBT [40]. In England, this was to be done by setting up a national network of smoking cessation clinics in Health Action Zones (HAZs), which covered many of England’s most deprived areas [40]. Smoking was to be seen as a critical issue for every HAZ [40]. National smoking cessation service guidelines [41] were also developed to assist these clinics, which were provided with targets [42] and mandatory reporting of results to the Health Department [43]. In 2011, a Tobacco Control Plan for England was published, outlining that the commitment to a national joined-up strategy was to continue in the coming years [44]. The overall impact of the stop smoking services was probably to decrease inequalities [32]. Over the first 10 years of operation, predominantly disadvantaged groups were reached (54% of users received free prescriptions) [43].

THE DUTCH CONTExT Smoking prevalence in the Netherlands in 1970 was 59% (Figure 3). While this prevalence of current smokers, has been decreasing over the subsequent decades, as has been the case in the UK, smoking prevalence is higher in the Netherlands than in the UK and this difference appears to have increased in the 2000’s (Figure 3).

Figure 3: Smoking prevalence in the total populations of Great Britain and the Netherlands from 1970-2010.* **

*Data not available for all years **GB data is unweighted until 1998 Source: UK [33] and Netherlands [45,46]

400350-L-bw-Benson Chapter 1

Inequalities are also clearly seen in smoking prevalence in the Netherlands on a variety of indicators, including educational level (Figure 4). Educational level is considered to be a good indicator of SES in the Netherlands [47].

Figure 4: Smoking prevalence in the Netherlands per educational level 1

Source: Dutch Continuous Survey of Smoking Habits (DCSSH) [48] Unlike in the UK, the Dutch government does not have a formal comprehensive tobacco control strategy. Instead tobacco control policies are part of general health policies in the Netherlands [49,50]. Dutch health promotion is decentralised. The central government sets the health priorities every four years and these priorities are implemented at the local district level [51]. Despite reduction in smoking having been mentioned as a priority of the central government since 2003 [49,51-53], measures are not often implemented on a local level, for a number of reasons, including that the districts feel that it is more a task for the central government [54].

The UK and the Netherlands are both signatories to the legally-binding Framework Convention on Tobacco Control [55], wherein article 14 states that there should be a national cessation strategy and national smoking cessation treatment guidelines. The Netherlands does not currently have the former [50,56], however, it does have the latter; there have been national smoking cessation guidelines since 2004 [57], which were updated in 2009 [58]. Smoking cessation infrastructure exists in several settings in the Netherlands, from hospitals (sometimes specialist clinics), primary care, community to the online settings. These are provided by trained counsellors [59], some of which are health professionals, such as General practitioners and practice nurses [60,61]. In the Netherlands, one course of SCBT is included in the basic health insurance policy, which is available to all citizens. Since 2006, the Netherlands has used a system of managed competition in the health care sector [62]. This means that individuals have compulsory private health insurance and thus a contract with an insurance company [62]. Providers of health care, including SCBT, compete with each other and negotiate individual contracts with insurance

400350-L-bw-Benson companies [62]. It is possible to receive treatment from a health care provider without a contract with one’s insurance company, but this may only be partially reimbursed [62]. A quality register of evidence-based smoking cessation offerings has been available since 2011, with a map showing smokers where these are in relation to their homes [59]. However, this infrastructure is, in general, not specifically targeted at socioeconomically disadvantaged areas or smokers. Despite Dutch tobacco control policies, educational inequalities in smoking cessation remain significant in the Netherlands (high compared with low educational level from 2002-2012: Odds Ratio (OR(95%CI)):1.44[1.09-1.91])) [16].

Evidence-based SCBT has been reimbursed since 2010 [63]. However, financial barriers to evidence-based smoking cessation pharmacotherapy, the removal of which might make smoking cessation interventions more effective in low SES groups [8], have historically been in place in the Netherlands. The evidence-based combination of smoking cessation behavioural therapy with pharmacotherapy was only partly funded until 2011.

The rationale for our study was that with the introduction of reimbursed pharmacotherapy in 2011, it was possible to test whether a smoking cessation service could be effective in a disadvantaged multi-ethnic area of the Netherlands, if the financial barrier was removed [64], as was the case in England. The removal of the financial barrier, which was a necessary pre-condition of this research, was implemented first in 2011, but not in 2012, and then again in 2013 onwards. This intermittent offering was due to changes in the Dutch government, which is one of the few governments globally to weaken previously implemented tobacco control measures [56,65].

MACRO-LEVEL INFLUENCES ON SMOKING CESSATION The role of the wider context in smoking cessation has long been acknowledged. Not only does the wider context help to determine how cigarettes are used [66] and how acceptable this use is considered by individuals and the communities in which they live [67, 68], but also, or perhaps consequently, how it is considered and approached by governments [69]. The wider context thus helps to determine the success of strategies used on both an individual and population level. The macro-level influences on smoking cessation differ per country (e.g. cigarette affordability [22]) and change over time (e.g. acceptability of smoking [70]). Better understanding the wider context might help us to understand why people in lower SES groups experience more difficulties in quitting smoking than their high SES peers. This might be a basis for further targeting of smoking cessation measures, and possibly thereby increasing their effectiveness. In this thesis we will examine two aspects of this wider context: prevailing economic conditions and social norms.

Dahlgren and Whitehead’s model of the main determinants of health (Figure 1) shows several levels at which influence on individual’s health can take place. At the highest level, there are general socioeconomic conditions. Economic recessions, such as the Global Financial Crisis (GFC), affect disadvantaged groups more than advantaged groups [71]. These impacts can in turn have an impact on health behaviours such as smoking [72]. Different socioeconomic groups

400350-L-bw-Benson Chapter 1

react differently to economic downturns, with data from past economic downturns showing that often health behaviours such as exercise, weight loss and smoking cessation, increase [73]. This is not uniform for all SES groups [73]. Also, it is thought that these effects are buffered by social protection policies in individual countries [74]. Thus it is important to look at the effect of economic crises on people at all SES levels and to consider each country separately, as social protection policies and the level of impact of the crisis varied widely throughout Europe, and 1 indeed, the world.

Figure 5: The main determinants of health

Source: [75] Original reproduced with permission Also understood within the wider context, under cultural conditions in the Dahlgren and Whitehead model, are the social norms which prevail with regard to behaviour. The importance of social norms toward smoking was acknowledged at the World Conference on Tobacco or Health in 1979 [76], and has since been targeted by national tobacco control policies in several countries [77,78], starting with California in 1989, which instigated a campaign to change the prevailing social norm [77] and thus influence tobacco usage in the state. This campaign has been found to be successful [79]. Other countries followed suit; one of the cornerstones of the Australian National Tobacco Control strategy 2006-2009 was to “change social attitudes through regulation and hard-hitting campaigns to reduce tobacco use ”(p. 18) [78] Indeed a study found that the savings accrued from the reduction in premature deaths over the preceding 30 years in Australia due to such policies were 50 x the cost of the implementation of such campaigns [80], thus real impacts on health can be realised by directly addressing social norms.

400350-L-bw-Benson There are different types of social norms with regard to smoking and quitting. These can be descriptive (perception of what other people are doing), subjective (perception of what other people think a smoker should do), or injunctive (perception of acceptability of smoking in society in general) [81]. Of these, injunctive norm has been little studied. This is particularly of interest with regard to inequalities, where the different prevalence in different SES groups can lead to different injunctive norms which in turn can influence the prevalence, in a vicious circle. Thus it is important to consider how injunctive norm toward smoking is distributed in the population and whether there is a link between this and quitting behaviour in response to smoking cessation policies, in any particular SES groups.

AIM OF THIS THESIS The general aim of this thesis was to pilot test whether the English system of placing smoking cessation clinics providing free treatment (SCBT and pharmacotherapy) in disadvantaged areas could be replicated to good effect in the Netherlands. This thesis evaluated four different types of SCBT interventions (individual face-to-face and telephone counselling, as well as, rolling and fixed group therapy), delivered in four different disadvantaged areas of the Netherlands. Two of these areas were amongst the 40 most disadvantaged areas in the Netherlands, as per a classification of the Dutch government [82], while the other two comprised areas which had catchments including disadvantaged areas, according to a ranking done by the Dutch government [83]. The specific aims of this thesis were to evaluate the effect, optimal method of recruitment, and reasons for attendance of smoking cessation interventions in a disadvantaged areas and, furthermore, to explore the influence of the prevailing economic conditions and social norms on inequalities in smoking cessation.

OUTLINE OF THIS THESIS This thesis consists of two parts. Part 1, comprising chapters 2-4, focuses on research question 1: What is the effect, optimal method of recruitment and reasons for attendance of a smoking cessation intervention in disadvantaged neighbourhoods in the Netherlands? Chapter 2 examines the effectiveness of four different type of smoking cessation behavioural therapy, namely individual face-to-face and telephone counselling, and rolling and fixed group counselling, as indicated by 12 month self-reported and CO-validated abstinence rates. It then assesses the predictors of self-reported abstinence at 12 months. Chapter 3 addresses the reach of different strategies of recruitment. It examines how participants heard about and were recruited into the interventions, and analyses the associations between recruitment channel and socio- demographic or quit success influencing factors, and whether these channels can predict attendance. Chapter 4 uses a qualitative design to examine the reasons for differing attendance levels in smokers attending the services.

Part 2, comprising chapters 5 & 6, examines two aspects of the wider context which form a backdrop against which smokers make their quit attempts. It focuses on research question 2: What is the influence of the prevailing economic conditions and social norms on inequalities in

400350-L-bw-Benson Chapter 1

smoking cessation? Chapter 5 reports on the association between the GFC and current smoking and smoking cessation. In addition, differences in association by age, gender and three SES indicators (income, education and neighbourhood deprivation) are taken into consideration. Chapter 6 focuses on injunctive norms towards smoking as a factor that influences use of pharmacotherapy in quit attempts. It reports on the inequalities in uptake of smoking cessation pharmacotherapy in quit attempts before and after reimbursement of this pharmacotherapy 1 was offered. It then looks at whether injunctive norm could explain the difference in this use.

DATA AND METHODS Table 1 gives an overview of the studies, including the data sources, analysis methods and design used in each study. Three different sources of data were used. In the first section, data collected directly from research participants or from patient dossiers in smoking cessation programmes serving disadvantaged areas were used. In the second section, two databases were used. These were the national Health Survey from Statistics Netherlands and the Dutch Continuous Survey of Smoking Habits data from STIVORO.

400350-L-bw-Benson Self-reported and CO-validated quit Self-reported and CO-validated 6 and 12 months and at initially, status follow-up. participantsHow about or were heard the programme. to referred of <4 or ≥4 sessions Attendance of attendance patterns Common and and barriersMotivations toward, participants by, social support received attendance toward smoking rates Current Smoking ratios cessation (with or quit attempt Most recent without pharmacotherapy) smokingInjunctive norm towards Outcomes Data source Data Own data Own data Own data Health Survey (HS) from Netherlands Statistics Survey Continuous Dutch of Smoking Habits (DCSSH) STIVORO from Repeated surveyRepeated and medical records research surveyRepeated Semi-structured qualitative interviews cross- Repeated sectional data cross- Repeated sectional data Method Effects of different types of smoking cessation Effects of different in the areas in disadvantaged therapy behavioural Netherlands: an observational study. in disadvan- therapy Smoking behavioural cessation of analysis taged neighbourhoods: an explorative channels. recruitment do Why quit: to just wanting isn’t attend to Wanting smoking attend smokers regularly some disadvantaged while others do not? A qualitative therapy cessation study. The Socioeconomic inequalities in smoking in and during the Global Financial Netherlands before Crisis. Inequalities of in the impact reimbursement of national smoking-cessation and the influence pharmacotherapy study. explorative An of injunctive norms. Title Overview of the topics covered in each chapter Overview covered of the topics 3 4 6 Chapter of the Netherlands. areas interventions in disadvantaged therapy of smoking behavioural 1: Evaluation Part cessation 2 conditions and social norms on inequalities in smoking economic cessation. of the prevailing influence The 2: Part 5 Table 1: Table

400350-L-bw-Benson Chapter 1

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42. Bauld L, Bell K, McCullough L, Richardson L, Greaves L. The effectiveness of NHS smoking cessation services: a systematic review. Journal of public health. 2010;32(1):71-82 doi:10.1093/pubmed/fdp074.

43. West R, May S, West M, Croghan E, McEwen A. Performance of English stop smoking services in first 10 years: analysis of service monitoring data. BMJ. 2013;347:f4921 doi:10.1136/bmj.f4921.

44. Department of Health. Healthy Lives, Healthy People: A Tobacco Control Plan for England. 2011.

45. STIVORO. Trendpublicatie Percentage Rokers Nederlandse Bevolking 1958-2009. Den Haag: STIVORO;2010.

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47. Mackenbach JP. Socioeconomic Health Differences in the Netherlands - a Review of Recent Empirical-Findings. Soc. Sci. Med. 1992;34(3):213-226 doi:Doi 10.1016/0277-9536(92)90264-Q.

48. TNS NIPO. Dutch Continuous Survey of Smoking Habits 2001-2012. Amsterdam 2013.

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49. Rijksoverheid. Alles is Gezondheid... Het nationaal programma preventie 2014-2016. Den Haag: Rijksoverheid;2013.

50. Heijndijk SW, MC. Dutch Tobacco Control: Moving towards the right track? FCTC Shadow Report 2014. Den Haag: Alliantie rookvrij Nederland (Dutch alliance for a smokefree society);2015. 1 51. Ministerie van Volksgezondheid Welzijn en Sport. Kiezen voor Gezond Leven 2007-2010. Den Haag: Ministerie van Volksgezondheid, Welzijn en Sport;2006.

52. Ministerie van Volksgezondheid Welzijn en Sport. Langer gezond leven. Ook een kwestie van gezond gedrag. Den Haag: Ministerie van Volksgezondhied, Welzijn en Sport; 2003.

53. Ministerie van Volksgezondheid Welzijn en Sport. Landelijke nota gezondheidsbeleid. Gezondhied dichtbij. .Den Haag: Ministerie van Volksgezondheid, Welzijn en Sport; 2011.

54. van der Meer RS, R; de Beer, M;. Zoeken naar Nieuwe Kansen voor Lokaal Gezondheidsbeleid en Roken. Project Structureel Aanbod Gemeenten Tabakspreventie. Eindrapportage 2011. Den Haag: STIVORO; 2012.

55. World Health Organization (WHO). WHO Framework Convention on Tobacco Control. Geneva: World Health Organisation;2005.

56. Rennen EW, M. Dutch Tobacco Control: Out of Control? FCTC Shadow Report 2011. Amsterdam: KWF Kankerbestrijding;2012.

57. Kwaliteitsinstituut voor de Gezondheidszorg CBO. Richtlijn Behandeling van Tabaksverslaving. Utrecht: Kwaliteitsinstituut voor de Gezondheidszorg CBO; 2004.

58. Partnership Stop met Roken. Richtlijn Behandeling van Tabaksverslaving herziening 2009. Den Haag: Partnership Stop met Roken;2009.

59. Kwaliteitsregister Stoppen met Roken. Goedgekeurde (geaccrediteerde) interventies. http://www.kwaliteitsregisterstopmetroken.nl/geaccrediteerde-activiteiten/interventies/. Accessed 17/2/2015.

60. Partnership Stop Met Roken. Kwaliteitsregister Stoppen met Roken. http://www.kwaliteitsregisterstopmetroken.nl/zoeken/. Accessed 25/07/2015.

61. College voor zorgverzekeringen (CVZ). Stoppen met Roken Programma: te verzekeren zorg! Diemen: College voor zorgverzekeringen (CVZ) 2009.

62. van Ginneken ES, W; Kroneman, M;. Managed Competition in the Netherlands: An example for others? Health Policy Developments.16(4):23-26.

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64. Nierkens V. ZonMw Subsidieaanvraag: A smoking cessation service in a disadvantaged neighbourhood in The Hague: an evaluation of its reach and effectiveness. 2010.

400350-L-bw-Benson 65. Arnott D, Berteletti F, Britton J, Cardone A, Clancy L, Craig L, Fong GT, Glantz SA, Joossens L, Rudolphie MT, Rutgers MR, Smith SC, Stam H, West R, Willemsen MC. Can the Dutch Government really be abandoning smokers to their fate? Lancet. 2012;379(9811):121-122 doi:Doi 10.1016/S0140-6736(11)61855-2.

66. Reijneveld SA. Neighbourhood socioeconomic context and self reported health and smoking: a secondary analysis of data on seven cities. J. Epidemiol. Community Health. 2002;56(12):935-942.

67. Paul CL, Ross S, Bryant J, Hill W, Bonevski B, Keevy N. The social context of smoking: A qualitative study comparing smokers of high versus low socioeconomic position. BMC Public Health. 2010;10:211 doi:10.1186/1471-2458-10-211.

68. ITC Project. ITC Netherlands Survey. Report on Smokers’ Awareness of the Health Risks of Smoking and Exposure to Second-hand Smoke. Ontario, Canada: University of Waterloo;2011.

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79. Zhang X, Cowling DW, Tang H. The impact of social norm change strategies on smokers’ quitting behaviours. Tob. Control. 2010;19 Suppl 1:i51-55 doi:10.1136/tc.2008.029447.

80. Applied Economics. Returns on Investment in Public Health - An Epidemiological and Economic Analysis. 2001; http://www.appliedeconomics.com.au/pubs/reports/health/ ph00.htm. Accessed 16/2/2015. 1 81. van den Putte B, Yzer MC, Brunsting S. Social influences on smoking cessation: a comparison of the effect of six social influence variables. Prev. Med. 2005;41(1):186-193 doi:10.1016/j.ypmed.2004.09.040.

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400350-L-bw-Benson 400350-L-bw-Benson Part 1 Evaluation of smoking cessation behavioural therapy interventions in disadvantaged areas of the Netherlands

400350-L-bw-Benson 400350-L-bw-Benson Chapter 2 Effects of different types of smoking cessation behavioural therapy in disadvantaged areas in the Netherlands: an observational study.

Fiona E. Benson, Vera Nierkens, Marc C. Willemsen, & Karien Stronks.

Under review

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AbSTRACT Background. Smokers in disadvantaged areas smoke more and make less successful quit attempts than smokers in other areas. It is therefore important to consider which evidence-based methods, such as smoking cessation behavioural therapy (SCBT) and pharmacotherapy, work best in this group. We investigated the effect of four different types of SCBT offered in disadvantaged areas in the Netherlands (individual face-to-face, telephone, rolling group and fixed group counselling), and explored differences of effect between intervention types.

Methods. Data from 415 participants was collected from Dutch smoking cessation programmes serving disadvantaged areas. Settings included hospital, community, and primary care. Data collection included repeated survey and medical record research. Participants self-reported and CO-validated continuous quit status per intervention type initially, and at 6 and 12 months were calculated. Predictors of continuous cessation at 12 months were analysed using logistic regression analysis.

Results. Overall, 19% of participants were of low educational level. There was a 30% overall self-reported continuous quit rate at 12 months, which was highest in rolling group counselling (41%) and individual face-to-face counselling (35%). Compared with a hospital setting, fixed group counselling given in other settings was less effective. Both group counselling types were equally effective in a hospital setting.

Conclusion. Group counselling in a hospital setting has potential to be successful in supporting smokers in disadvantaged areas to quit. Individual counselling provided face-to-face in a hospital setting also has potential. We recommend that services in disadvantaged areas concentrate on offering group counselling, given in a hospital setting, where possible.

Keywords. Smoking cessation, behavioural therapy, socioeconomic status, disadvantaged neighbourhood

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INTRODUCTION Tobacco is a risk factor for six of the eight leading causes of death worldwide and is responsible for one in every 10 adult deaths worldwide [1]. In high income countries, those living in disadvantaged areas smoke more [2-4] and make less successful quit attempts [5,6] than those living in the most advantaged areas. Intensive smoking cessation behavioural therapy (SCBT), with or without pharmacotherapy, can increase the chance of a successful quit attempt [7-10]. However, there are many types of intensive SCBT available, including courses of individual face-to-face, telephone, rolling or fixed group counselling.

Each type of SCBT has advantages and disadvantages. Group counselling, provided to a group of smokers by a trained smoking cessation counsellor, provides the opportunity for participants 2 to experience group support and social learning [8,9] but can also possibly lead to demotiva- tion due to unhelpful group processes (e.g. rivalry, envy, fear of failure / loss of face) [8,11,12]. Group counselling can be provided in a fixed group or rolling group format. In fixed (closed) group counselling, a group is assembled and no new participants enter the group once the counselling has started. Often the start date of the course is set once a minimum group number has been reached. This has the advantage of the group being able to develop a strong social support network as they see each other regularly. However, it can mean waiting to start [13] and, if there is a high level of drop-out, participants may feel demotivated as the group gets smaller [11]. Rolling group counselling involves the continuous sequential repetition of sessions throughout the year. This enables participants to stream in and out at any time (also called open group), so they can start straight away [13] and there is a chance to catch up on any session they miss because the sessions are repeated regularly. The regular change of participants may enable newcomers to learn from the experiences of experienced participants [13] however, it could also prevent the development of a strong mutual support network.

Individual counselling, either face-to-face or by telephone is provided to smokers on an individual basis by trained smoking cessation counsellors [10,14]. Individual counselling provides the opportunity for tailoring to the patients individual needs (i.e. free-choice topics can be selected by the participant based on their needs) [14] while also covering the general course material. However, it does not provide the group benefits, as mentioned previously. While both individual forms are more flexible than group counselling, allowing appointments to be scheduled when suitable for the participant, telephone counselling is very flexible, as a participant does not have to be present in a certain place at a certain time [15] and can possibly reschedule appointments at short notice [11]. This may be suited to people who find it difficult to attend set appointments in person, such as mothers with little support or people with busy or irregular jobs [11]. However, some smokers may be suspicious about the confidentiality of such a service or may not be able to envision themselves being helped over the telephone [15].

It is possible that different intervention types may differ in their effectiveness. In the UK, group counselling has been found to be more effective than individual counselling [16,17]. However, type of group counselling is also of importance, with one UK study finding that the best results in

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overall and in those of low SES could be found in rolling (open) group counselling in comparison with one-to-one, drop-in clinic, and fixed group counselling [18]. No significant effect of area disadvantage on quitting was found in this UK study [18].

The aim of this paper is to examine the effects of four different types of SCBT offered in disadvantaged areas of the Netherlands. In the Netherlands, one course of intensive SCBT per smoker (with or without pharmacotherapy) is reimbursed each year in the basic health insurance package. Evidence-based intensive behavioural therapy can be delivered in several formats, including the aforementioned individual and group counselling [19]. We will examine the effects on 12 month continuous quit status of SCBT by type of intervention (individual face-to- face, telephone, fixed group or rolling group counselling) and explore the differences of effect in different types of counselling.

METHODS Participants & counselling type Data from 415 participants of ≥18 years of age, who had commenced SCBT, was collected from four smoking cessation services located in urban areas of the Netherlands. Two of these services, located in disadvantaged areas [20] were offered in primary care (service A) and community settings (Service B). Further information on the recruitment of these participants and the sites involved can be found in Benson et al. (2015) [21]. The other two services (Services C & D), with catchment areas including disadvantaged areas, were smoking cessation clinics in hospitals. Information about the intervention offered at each site can be viewed in Tables 1 & 2. All counsellors had received training in smoking cessation counselling. Group courses had 8-15 participants. The course structure of group counselling varied between services A, B & C, who offered a standard fixed group counselling course [12] and service D, which offered a course whereby participants must first read a book or listen to a CD about smoking cessation [22,23] followed by filling in a step-by-step plan, finalising the plan and then choosing group or individual counselling. Despite this, all interventions used similar content, including self-analysis, analysis of tempting situations/pitfalls, behavioural change, rewards, cravings, dealing with social pressure and relapse prevention. Pharmacotherapy was discussed with all participants at all services early in the counselling, except for Telephone counselling at service A, where it was only discussed with those smoking >10 cigarettes per day. Some services provided participants with prescriptions for pharmacotherapy, while participants of others needed to organise the pharmacotherapy themselves (Tables 1 & 2).

400350-L-bw-Benson Chapter 2 Service D Hospital Dutch Rolling 2-3 individual sessions with the smoking counsellor cessation sessions. and then 7 group Between session 1–2 No is discussed in the pre- Topic and with the (book/CD) reading early in the counsel- counsellor must organise Participants ling. themselves. pharmacotherapy

- 2 Service C Hospital & English Dutch Fixed 14 sessions Approximately with 12 months, over spread sessions in the the first seven four months. first Between sessions 3-4 Yes is discussed with Topic participants session. in second use advised to Participants if they and, pharmacotherapy the prescrip do so, choose to Prescriptions tion is provided. by the partici-must be filled themselves. pants Service b Community Community Dutch Fixed weekly sessions. 9 standard Between session 3-4. Yes is discussed in the Topic on first session. Information is also pharmacotherapy material. in the course available must organise Participants themselves. pharmacotherapy Service A Primary care Dutch & Turkish Fixed weekly sessions. 9 standard Some had 2 additional courses topics sessions on lifestyle the participantschosen by (e.g. management). stress Session 4 Yes is discussed early in the Topic are Prescriptions counselling. participants to who provided Prescriptions use it. wish to by the partici-must be filled themselves. pants Description of the group counselling offered by each service. offered Description counselling of the group Language offered typeIntervention Number of sessions 1.5-2 hours duration. date stop of official Timing partici- keep to Permitted on if not stopped pating date stop official Pharmacotherapy Setting Table 1: Table

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Table 2: Description of the individual counselling offered by each service.

Service A Service C Service D

Setting Primary care Hospital Hospital

Language offered Dutch & Turkish Dutch & English Dutch

Intervention type Telephone Face-to-face Face-to-face

Number of sessions 7 standard sessions over Approx. 16 sessions over 7-8 sessions with the and course duration 3-4 months with up to 5 12 months, with two smoking cessation extra sessions if relapse extra sessions in the counsellor over 12 occurs or the participant second year if the partici- months, 6 of which occur has not stopped after the pant is still abstinent and in the first 4 months of first session. feels the sessions are that year. necessary. Timing of official Between sessions 1-2 After sessions 2 or 3. Between sessions 1-2. stop date Permitted to keep Yes Yes Yes, but if the agreed participating if not stop date is missed stopped on official approximately twice stop date participants must have a time-out. Permitted to Yes Yes Yes, but after approx. 2 continue if relapse relapses they must have a time-out of minimum 3 months. Session duration Session 1: 30 minutes Session 1: 1 hour. Session 1: 40 mins. (mins). Subsequent sessions: 30 Subsequent sessions: 20 Subsequent sessions: 15 mins. mins. mins. Pharmacotherapy Topic is discussed early As per group therapy at As per group therapy at in the counselling with this service. this service. participants smoking >10 cigarettes per day. The participant must organise this themselves. Forms were provided (excluding 2012) to help participants gain reimbursement for medication costs.

Data from services A & B was gained from repeated cross-sectional surveys. The surveys were taken at baseline (pre-intervention), and then 4-6 weeks, 6 months and 12 months after their agreed quit date. Informed consent was gained from all participants at these two sites. Further details can be seen at Benson et al. (2015) [21]. Data from services C & D was gained through patient medical records, where all participants from the smoking cessation clinics who had been

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referred by the GP were included. This was supplemented by follow-up data provided by the services. Under Dutch law, medical ethical approval is not required for scientific research which does not undertake an intervention [24]. Recruitment took place from May 2011-October 2013

Variables & Analysis: Socioeconomic status (SES) Highest education level attained was used as a proxy for SES. The following categories were used: no/primary/lower secondary education was considered low SES, mid/upper secondary education was considered middle SES, and tertiary education was considered high SES. This information was missing for approximately one third of participants in service C and two thirds 2 in service D.

Average cigarettes per day Average cigarettes per day was used as a proxy for nicotine dependence [25].

Quit status – Self-reported Self-reported continuous quit status was measured at 3 moments: initial, 6 and 12 months. For two of the services (C&D), self-reported follow-up was gained by phoning participants, and asking whether they had stopped smoking. For the other two services (A&B), quit status was determined through questions from the interviewer-led questionnaire. These were at 4-6 weeks: Have you smoked in the last 14 days, even if it was just one cigarette or self-rolled cigarette or only one puff? (which allowed for a 2 week grace period) [26]. And at 6 and 12 months: Have you smoked since your agreed quit date, even if it was only one cigarette or self-rolled cigarette or only one puff? Those smoking 0-5 cigarettes in the entire period were considered non-smokers, while those smoking >5 cigarettes were considered smokers [26]. Participants were categorised as smoking, quit or unknown for each measure.

The timing of the initial measurement after the agreed quit date differed between services. Service C followed up immediately, Services A & B at 4-6 weeks, and Service D 3 months.

Self-reported continuous quit rate was calculated such that participants who reported that they were smoking at a follow-up (Service C&D) or they had smoked >5 cigarettes in the entire period (Service A&B), were considered to be smokers for that period and the rest of the follow-up period. Participants who missed a follow-up at 3 or 6 months were considered to be unknown for that follow-up (neither smoker or non-smoker and remaining in the denominator). However if at a subsequent follow-up they were found to be ‘quit’, they were considered to be quit for the entire period, at that point (previous values were not altered). Participants who missed the 12 month follow-up were considered to be smokers for the entire period [26].

Quit status – CO-validated At two of the services (A&B), CO-validation of self-reported continuous quit status was done. A participant was considered CO-validated quit if they had smoked <5 cigarettes for the entire period and their CO-meter reading was ≤9ppm [26].

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Pharmacotherapy Participants who used pharmacotherapy were coded as having used pharmacotherapy if they had used either varenicline, bupropion or nicotine replacement (patches, lozenges, chewing gum or nasal spray).

Attendance When attended completely, all interventions consist of ≥7 sessions. Attendance was dichotomised as intensive (at least 4 sessions of at least 40 minutes duration in total) and non-intensive (less than 4 sessions and/or less than 40 minutes in total) according to the Dutch Guideline for Treatment of Tobacco Addiction [27].

Setting The interventions took place in one or more of three different location types. These were hospital, primary care and community settings.

Statistical Analysis Statistical analysis was performed using IBM SPSS Statistics, Version 21 (Release 21.0.0.1). Self-reported and CO-validated continuous quit rate per intervention type was calculated using: successful quitters/total participants. Univariate logistic regression analysis was used to explorer whether 12 month self-reported quit rates differed per intervention type, taking into account setting characteristics and controlling for confounders. Confounders included age [16,18], gender [28], SES [16,18], average cigarettes per day [29], pharmacotherapy use [17] and attendance [30]. Variables with a p-value of ≤0.2 in a univariate model and which changed the Odds Ratio of quitting for a specific intervention type by >10% were included in a multivariate logistic regression analysis. To prevent loss of data due to complete case analysis, in variables with large amounts of missing data, such as educational level, those with missing data were put into a separate category.

RESULTS The characteristics of participants differed between intervention types (Table 3). Fixed group and telephone counselling had the highest proportions of participants with low educational level (both 40%). Individual face-to-face counselling had the highest proportion of highly educated participants (26%). Gender was approximately evenly split in the total group, with the highest percentage of female participants being in the telephone counselling group (58%). Pharmacotherapy use in telephone coaching (45%) was lower than in other intervention types (≥53%). Average cigs per day were very similar amongst all intervention types. There was a large amount of missing data on educational level (33%), marital status (45%) and pharmacotherapy use (22%).

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Table 3: Participant characteristics, overall and per counselling type.

Characteristics All Individual Telephone Fixed group Rolling group (n=415) face-to-face (n=38) (n=78) (n=83) (n=216)

n(%) Gender Male 198(48) 99(46) 16(42) 45(58) 38(46) Female 215(52) 115(53) 22(58) 33(42) 45(54) Educational status 2 Low 79(19) 28(13) 15(40) 31(40) 5(6) Medium 120(29) 54(25) 19(50) 31(40) 16(19) High 80(19) 55(26) 4(11) 15(19) 6(7) Missing 136(33) 79(37) - - 56(68) Marital status No Partner 100(24) 42(19) 20(53) 38(49) NA Partner 87(21) 29(13) 18(47) 40(51) NA Missing 228(45) 145(67) - - NA Pharmacotherapy Yes 245(59) 137(63) 17(45) 47(60) 44(53) No 79(19) 25(12) 7(18) 16(21) 31(37) Missing 91(22) 54(25) 14(37) 15(19) 8(10) Mean (SD) Age (years) (n=408) 49.5(11.7) 49.4(11.1) 45.5(12.9) 49.4(13.2) 51.8(10.7) Cigs per day (n=379) 21.7(10.1) 21.3(9.2) 22.3(11.8) 23.4(12.2) 20.6(8.7) Sessions attended 6.2(5.0) 6.8(5.9) 2.91(1.4) 6.9(3.8) 5.0(2.9) (n=368) NA = not available Table 4 shows the self-reported and CO-validated continuous quit rates, both overall and per intervention type. Overall, the self-reported quit rate at 12 months was 29.9%. The self-reported quit rates at 12 months is highest for rolling group (41%) and individual face-to-face counselling (34.7%). Lower self-reported 12 month quit rates were reported for fixed group (15.4%) and telephone counselling (7.9%). Twelve month CO-validated quit rates were lower than the self-reported rates, namely 6.4% overall, 7% for fixed group and 5.3% for telephone counselling respectively.

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Table 4: Self-reported and CO-validated continuous quit rates initially, and at 6 and 12 months post quit date, per counselling type.

Time Self-reported quit rate (%) CO-validated* quit rate (%) period All Individual Telephone Fixed Rolling All Telephone Fixed (n=415) face-to-face (n=38) group group (n=109) (n=38) group (n=216) (n=78) (n=74) (n=71) Initial 57.6 57.9 28.9 56.4 71.1 36.7 21.1 45.1 6 months 37.6 41.2 7.9 23.1 55.4 8.3 5.3 9.9 12 months 29.9 34.7 7.9 15.4 41.0 6.4 5.3 7.0 *Only two sites did CO validation, hence the decreased total numbers in the final three columns

After controlling for individual and intervention characteristics, we found that telephone and fixed group counselling are significantly less effective than individual face-to-face counselling (Odds Ratio (OR): telephone counselling 0.18[0.05-0.66] p-value<0.05 and fixed group 0.31[0.15- 0.63] p-value<0.05)). The effect of rolling group counselling does not differ significantly from individual face-to-face counselling (OR:1.62[0.92-2.83], p-value >0.05). The effect of setting could only be examined in participants of fixed group counselling. We found that fixed group counselling is significantly more effective in a hospital setting (reference) than in a community setting (Odds Ratio(OR): 0.07[0.01-0.64], p-value <0.05) and borderline significantly more effective than a primary care setting (OR:0.15[0.02-1.03], p-value = 0.053). Within a hospital setting, fixed and rolling group counselling were equally effective (OR fixed group compared to rolling group (reference): 8.87[0.80-98.84], p-value >0.05).

In the participants as a group, approximately a third of participants dropped out (Table 5). Drop-out differed per intervention type, with the highest experienced in telephone counselling (66%) and the lowest in rolling group counselling (12%).

Table 5: Drop-out during follow-up, overall and per counselling type

Characteristic Overall Individual Telephone Fixed Group Rolling (n=415) face to face (n=38) (n=78) Group (n=216) (n=74)

Time period Initial 59 (14) 27 (12.5) 14 (36.8) 13 (17) 5 (6) n(%) At 6 months 100 (24) 45 (21) 21 (55) 26 (33) 8 (10) At 12 months 119 (29) 55 (26) 25 (66) 29 (37) 10 (12)

DISCUSSION The 12 month continuous quit rates for the group as a whole were 29.9% and 6.4% for self- reported and CO-validated methods respectively. Using self-reported quit rate, rolling group and individual face-to-face counselling had the highest 12 month quit rates in disadvantaged areas (41% and 34.7% respectively). CO-validated quit rates were lower than self-reported rates, but the effectiveness of interventions in relationship to one another were preserved. Group counselling, regardless of type, is more effective in a hospital setting.

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A strength of this study is that it provides evidence on the effect of various types of SCBT, which has been collected in “real life” settings in disadvantaged areas, rather than effects found in the often non-representative participants and carefully controlled treatment conditions of randomised controlled trials (RCT) [31]. However, a disadvantage is that it is observational data which in no way mimics an RCT. A disadvantage of not using an RCT design is that the characteristics of the participants in each counselling type might differ as a result of the area characteristics of each service or the self-selection of participants. We controlled for this in the analysis, however, it was not a complete control because there was no overlap in some cases (e.g. telephone counselling was only offered in one service). However, we would not recommend an RCT, as the aim was not to find the absolute differences in magnitude of effect between interventions. 2 A limitation of this study is missing data. In the case of the medical record research, though information on all patients visiting the service between particular dates was available, not all information which we wished to collect was always recorded by both clinics (e.g. highest educational level or Fagerström Test of Nicotine Dependence) [32]. In the case of the survey research, information was missing due to a high percentage of drop-out from the research. We do not feel that this has led to bias, however. The expectation would be that those who remained would do better than those who dropped out. However, missing data was highest in those areas where telephone and fixed-group counselling were given. The 12 month continuous quit rates in these areas were already lower than in the other intervention types.

Another limitation of this study is that all four counselling types could only be compared using self-reported rather than CO-validated quit status. Self-report can lead to socially desirable answers in smoking cessation intervention groups [33]. Though in the general population, there is some but not excessive overestimation of the quit rate using self-reported data [33,34] we are not aware of any study looking at this specifically for those of low SES. However, we would not expect the results to change if the CO-validation was available for all intervention types for two reasons. Firstly, the quit rates recorded by individual face-to-face and rolling group counselling, for which no CO-validation was available, were considerably higher than those reported by telephone counselling and fixed group counselling. While they might decrease with CO-validation, we would not expect them to drop below the levels of fixed group and telephone counselling. Secondly, the relationships found in the self-reported data were preserved in the CO-validated data for the interventions for which it was available.

Use of pharmacotherapy was highest in counselling types provided by clinics where prescriptions were provided to participants, rather than where the participants had to organise their own prescriptions. In all cases the participants had to fill the prescriptions themselves. It is possible that 12 month continuous quit rates at these clinics are therefore higher than they would otherwise be. However, neither of these clinics had the highest continuous self-reported quit rate and pharmacotherapy use was controlled for in the analysis.

By comparison with the estimated background smoking cessation rate in the general population (1-4%) [35,36], all the intervention types mentioned here had higher continuous quit rates than

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the background rate. However, the magnitude differed greatly, with rolling and individual face- to-face counselling showing much greater quit rates above the background rate than telephone and fixed group counselling. The continuous quit rates found in this study are also similar or better than those found in SCBT interventions in comparable groups elsewhere [13,18,37,38].

Rolling group counselling had the highest 12 month continuous quit rate compared with the other intervention types. This supports the results of Hiscock et al. (2013) who found that in most clients, and in particular, in most disadvantaged groups, rolling (open) group counselling gave the highest 4 week quit rates [18]. For fixed group counselling the 12 month continuous self- reported quit rate was lower than either rolling group or individual face-to-face counselling. This differs from Hiscock et al. (2013) who found that fixed-group counselling was not significantly different to individual face-to-face counselling at four weeks [18] which was also suggested for the different interventions in the UK services overall [13]. However, when employed in a hospital setting, fixed group counselling appeared to have a similar effect to rolling group counselling. Individual face-to-face counselling had a high 12 month self-reported continuous quit rate, which was similar to that found at 4 weeks in one study [18] and approximately double the CO-validated rate at 12 months found in another study [39]. Telephone counselling had a comparatively low 12 month self-reported and CO-validated quit rate compared with the other intervention types considered. Also, the highest level of drop-out from the research was experienced in this group. The 12 month self-reported continuous quit rate in this study was slightly lower than that found in European quitlines in general (9.4%) [40] and similar to that found in a study in a similar disadvantaged target group [38]. The CO-validated rate was similar to the self-reported rate for this intervention type. If we consider these similar success rates, telephone counselling, which is an efficient way to provide individual face-to-face counselling to large numbers of people [9] may also hold potential for widespread promotion and use in disadvantaged areas in the Netherlands. However, as better results were obtained in other intervention types in this study, we would recommend focusing on these first.

Both clinics in hospital settings were also specialist smoking cessation services. Specialist clinics have been found to be more effective than other service settings in the UK [17]. It is possible that the specialist nature of the clinics contributed to the results found here. However, given the large differences in the physical locations of the clinics, we are cautious to make this link. Entering a hospital for SCBT, where patients and medical staff are a visible reminder of possible future consequences of continued smoking, may have a very different effect on a smoker considering quitting, compared to entering a community centre or GP surgery, where many people are not visibly seriously ill. Hospitalization is known to be a ‘teachable moment’ for smoking cessation in patients [41] and perhaps it could also work this way for smokers motivated enough to enter the hospital for SCBT.

We targeted smokers in disadvantaged areas. However, not all participants were of low educational level. Area disadvantage predicts higher smoking prevalence and lower quit success independently of other SES measures, such as education and income [2,6]. However, if the aim of a

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study is specifically to recruit smokers with individual-level low SES characteristics, in addition to being from disadvantaged areas, then further measures must be taken to target those groups.

These results are generalisable to other disadvantaged areas in the Netherlands because of the representation of different types of disadvantaged areas, for example with respect to the proportion of ethnic minority residents. While the magnitude of the results may not be directly generalizable to other countries, it is possible that the finding that rolling group counselling is very effective at 12 months in disadvantaged areas, and that hospital setting may be influential, is generalizable to other high income countries. These findings have implications for smoking cessation practice in disadvantaged areas. Group 2 and individual face-to-face counselling offered in a hospital setting are more effective than fixed group and telephone counselling offered in a primary care and community setting respectively. Because in group counselling a greater number of smokers are seen by the therapist in the same amount of time than in individual face-to-face therapy [42] the population impact of smoking cessation services in disadvantaged areas is likely to be larger if they focus more on group therapy, and, if possible, in hospital settings. This is as long as uptake is adequate [8].

We would also recommend the development of a standard for data registered by smoking cessation services across the Netherlands, as is the case in the UK [43]. This should include recommendations for follow-up of participants in terms of techniques used (for example, using CO-validation on a sample of participants) and minimum targets (e.g. in the UK the recommen- dation is CO-validation of 85% of patients at 4 weeks) [43]. This would aid services in their quality assurance procedures by enabling direct comparison between clinics, and, would at the same time, aid research in this area.

CONCLUSION Smoking cessation behavioural therapy provided in a rolling or fixed group format in a hospital setting has the potential to be effective in assisting smokers to quit in disadvantaged areas in the Netherlands. Individual counselling was also found to be similarly effective, if provided face to face. However, given the higher number of smokers which can be treated in the same time period using group therapy in comparison with individual therapy, we recommend that services in disadvantaged areas concentrate on offering group therapy and do so in a hospital setting, where possible.

ACKNOWLEDGEMENTS The authors would like to thank Pauline Haasbroek, Roos Blom and Tiny Rooijendijk, for their kind assistance in providing (access to) data.

FUNDING This work was supported by The Netherlands Organisation for Health Research and Development (ZonMw) (Project number: 200120004).

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COMPETING INTERESTS The authors declare no conflicts of interest.

AUTHOR CONTRIbUTIONS All authors conceived the study. All authors designed the study. FB prepared and analysed the data. All authors contributed to the interpretation of the data. FB drafted the article. All authors contributed to critical revision of the manuscript. All authors approved the final version of the manuscript.

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12. de Weert B. Pakje Kans. Samen stoppen met roken handbook. Den Haag: STIVORO voor een rookvrije toekomst.; 2009.

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15. World Health Organisation (WHO). Developing and improving national toll-free tobacco quit line services. A World Health Organizaton manual. France: World Health Organisation (WHO); 12/06/15 2011. 978 92 4 150248 1.

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17. Brose LS, West R, McDermott MS, Fidler JA, Croghan E, McEwen A. What makes for an effective stop-smoking service? Thorax. 2011;66(10):924-926 doi:10.1136/ thoraxjnl-2011-200251.

18. Hiscock R, Murray S, Brose LS, McEwen A, Bee JL, Dobbie F, Bauld L. Behavioural therapy for smoking cessation: the effectiveness of different intervention types for disadvantaged and affluent smokers. Addict. Behav. 2013;38(11):2787-2796 doi:10.1016/j. addbeh.2013.07.010.

19. Partnership Stop met Roken. Kwaliteitsregister Stoppen met Roken: Goedgekeurde (geaccrediteerde) interventies. http://www.kwaliteitsregisterstopmetroken.nl/geaccrediteerde-activiteiten/interventies/. Accessed 23/02/2015.

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21. Benson FE, Nierkens V, Willemsen MC, Stronks K. Smoking cessation behavioural therapy in disadvantaged neighbourhoods: an explorative analysis of recruitment channels. Subst Abuse Treat Prev Policy. 2015:10:28. doi: 10.1186/s13011-015-0024-3.

22. Dekker P, de Kanta W. Nederland Stopt! Met Roken. Nederland: Thoeris; 2008.

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26. West R, Hajek P, Stead L, Stapleton J. Outcome criteria in smoking cessation trials: proposal for a common standard. Addiction. 2005;100(3):299-303 doi:10.1111/j.1360-0443.2004.00995.x.

27. Partnership Stop met Roken. Richtlijn Behandeling van Tabaksverslaving Herziening 2009. Den Haag: Partnership Stop met Roken;2009.

28. Weinberger AH, Pittman B, Mazure CM, McKee SA. A behavioral smoking treatment based on perceived risks of quitting: A preliminary feasibility and acceptability study with female smokers. Addiction research & theory. 2015;23(2):108-114 doi:10.3109/16066359.2 014.933813. 2 29. Vangeli E, Stapleton J, Smit ES, Borland R, West R. Predictors of attempts to stop smoking and their success in adult general population samples: a systematic review. Addiction. 2011;106(12):2110-2121 doi:10.1111/j.1360-0443.2011.03565.x.

30. Hiscock R, Judge K, Bauld L. Social inequalities in quitting smoking: what factors mediate the relationship between socioeconomic position and smoking cessation? J Public Health (Oxf). 2011;33(1):39-47 doi:10.1093/pubmed/fdq097.

31. Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet. 2005;365(9453):82-93 doi:10.1016/S0140-6736(04)17670-8.

32. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br. J. Addict. 1991;86(9):1119-1127 doi:10.1111/j.1360-0443.1991.tb01879.x.

33. Murray RP, Connett JE, Istvan JA, Nides MA, Rempel-Rossum S. Relations of cotinine and carbon monoxide to self-reported smoking in a cohort of smokers and ex-smokers followed over 5 years. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco. 2002;4(3):287-294 doi:10.1080/14622200210141266.

34. Patrick DL, Cheadle A, Thompson DC, Diehr P, Koepsell T, Kinne S. The validity of self- reported smoking: a review and meta-analysis. Am. J. Public Health. 1994;84(7):1086-1093.

35. Zhu SH, Lee M, Zhuang YL, Gamst A, Wolfson T. Interventions to increase smoking cessation at the population level: how much progress has been made in the last two decades? Tob. Control. 2012;21(2):110-118 doi:10.1136/tobaccocontrol-2011-050371.

36. West R. Background smoking cessation rates in England. 2006; www.smokinginengland. info/Ref/paper2.pdf. Accessed 19/05/2015.

37. West R, May S, West M, Croghan E, McEwen A. Performance of English stop smoking services in first 10 years: analysis of service monitoring data. BMJ. 2013;347:f4921 doi:10.1136/bmj.f4921.

38. Zhu SH, Anderson CM, Tedeschi GJ, Rosbrook B, Johnson CE, Byrd M, Gutierrez-Terrell E. Evidence of real-world effectiveness of a telephone quitline for smokers. N. Engl. J. Med. 2002;347(14):1087-1093 doi:10.1056/NEJMsa020660.

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39. Ferguson J, Bauld L, Chesterman J, Judge K. The English smoking treatment services: one-year outcomes. Addiction. 2005;100 Suppl 2:59-69 doi:10.1111/j.1360-0443.2005.01028.x.

40. Willemsen MC, van der Meer RM, Bot S. Description, effectiveness, and client satisfaction of 9 European Quitlines: Results of the European Smoking Cessation Helplines Evaluation Project (ESCHER). Den Haag: STIVORO for a smoke free future;2008.

41. McBride CM, Emmons KM, Lipkus IM. Understanding the potential of teachable moments: the case of smoking cessation. Health Educ. Res. 2003;18(2):156-170 doi:Doi 10.1093/ Her/18.2.156.

42. Becona E, Miguez M. Group Behaviour Therapy for Smoking Cessation. Journal of Groups in Addiction & Recovery. 2008;3(1-2):63-78 doi:10.1080/15560350802157528.

43. Croghan E. Local Stop Smoking Services: Service Delivery and Monitoring Guidance 2011/12. United Kingdom: Department of Health;2011.

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400350-L-bw-Benson 400350-L-bw-Benson Chapter 3 Smoking cessation behavioural therapy in disadvantaged neighbourhoods: an explorative analysis of recruitment channels.

Based on: Benson FE, Nierkens V, Willemsen MC, Stronks K. Smoking cessation behavioural therapy in disadvantaged neighbourhoods: an explorative analysis of recruitment channels. Subst Abuse Treat Prev Policy. 2015:10:28. doi: 10.1186/ s13011-015-0024-3.

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AbSTRACT background. The optimum channel(s) used to recruit smokers living in disadvantaged neighbourhoods for smoking cessation behavioural therapy (SCBT) is unknown. This paper examines the channels through which smokers participating in a free, multi-session SCBT programme heard about and were referred to this service in a disadvantaged neighbourhood, and compares participants’ characteristics and attendance between channels.

Methods. 109 participants, recruited from free SCBT courses in disadvantaged areas of two cities in the Netherlands, underwent repeated surveys. Participants were asked how they heard about the SCBT and who referred them. Participant characteristics were compared between five channels, including the General Practitioner (GP), a community organisation, word of mouth, another health professional, and media or self-referred. Whether the channels through which people heard about or were referred to the service predicted attendance of ≥4 sessions was investigated with logistic regression analysis.

Results. Over a quarter of the participants had no or primary education only, and more than half belonged to ethnic minority populations. Most participants heard through a single channel. More participants heard about (49%) and were referred to (60%) the SCBT by the (GP) than by any other channel. Factors influencing quit success, including psychosocial factors and nicotine dependence, did not differ significantly between channel through which participants heard about the SCBT. No channel significantly predicted attendance.

Conclusion. The GP was the single most important source to both hear about and be referred to smoking cessation behavioural therapy in a disadvantaged neighbourhood. A majority of participants of low socioeconomic or ethnic minority status heard about the programme through this channel. Neither the channel through which participants heard about or were referred to the therapy influenced attendance. As such, concentrating on the channel which makes use of the existing infrastructure and which is highest yielding, the GP, would be an appropriate strategy if recruitment resources were scarce.

Keywords. Socioeconomic factors, neighbourhood, reach, referral, smoking cessation, attendance.

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INTRODUCTION Smoking is the main modifiable behavioural risk factor for the global burden of non-communi- cable disease [1]. Compared with people living in advantaged areas, people living in disadvantaged areas in high-income countries, smoke more [2-4] and are less likely to quit [5]. Proven effective interventions exist, such as multi-session smoking cessation behavioural therapy (SCBT) with or without pharmacotherapy [6], however, in order to benefit from these, smokers in disadvantaged areas must first be reached and recruited [7].

Targeting reach and recruitment activities to disadvantaged areas has been shown to be successful in recruiting smokers in the UK [8]. Apart from this, however, there is currently scant evidence on how smokers in such areas are best reached and recruited [9]. A recent Cochrane review highlighted the areas within this field that need more attention, which included iden- tifying those recruitment strategies (or different combinations of particular recruitment strategies) that work better for different population groups [10].

In recruitment strategies, a distinction needs to be made between the channel through which 3 participants had their attention captured (or heard about) an intervention [11], and the channel through which they were referred to the intervention. These two steps can happen through the same channel (e.g. hearing about and being referred by the General Practitioner (GP)), or through different channels (e.g. hearing about it from the media and self-referring). Though the GP is used to recruit smokers in disadvantaged areas [12,13], the literature indicates a broad range of other channels including use of other health professionals [14], use of existing community organisations [15,16], use of media [13] and word of mouth [16].

In addition to the channels that are used by smokers in disadvantaged areas to reach smoking cessation services, the characteristics of the smokers themselves are also important to map. First, it is possible that multiple channels used in a geographically targeted area may each attract different groups of smokers, with different a priori quit success rates. We know that factors such as social support [17-20], self-efficacy [21,22], motivation [17,20,23], and nicotine dependence [17,24] can influence quit success. We also know that they can differ by individual socioeconomic status [17,25]. Different channels may deliver participants who exhibit differences in socio-demographic characteristics and nicotine dependence [11], and possibly also in psychosocial factors such as social support, self-efficacy, and motivation. This might be the case because some strategies, from the viewpoint of the smoker, are pro-active (e.g. self-referring after reading a newspaper advertisement), and others are reactive (e.g. hearing from and then being referred by the GP) [26]. It is possible that a reactive strategy (from the viewpoint of the smoker), for example being opportunistically urged to stop by an authority figure, such as the GP during an appointment about a different matter, may deliver participants who feel externally controlled and thus have lower levels of self-determination, which leads to lower levels of motivation and self-efficacy [27]. In contrast, a proactive strategy (from the viewpoint of the smoker), such as responding to a media message about a smoking cessation programme may

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deliver participants who have internalized this goal and are acting toward it, exhibiting more self-determined behaviour, and possibly higher motivation and self-efficacy [27].

Second, once a participant is successfully recruited, attending more sessions of SCBT predicts quit success [28]. It is possible that recruitment channel affects attendance through socio-demographic characteristics of those recruited through the channel [17,29,30] or through the various levels of extrinsic motivation which are possibly called into action by recruitment channel. More detailed knowledge of which participants are recruited through possible channels and how these channels influence attendance would therefore allow interventionists to be confident that they are spending their money in an effective way and might contribute to a more cost-effective intervention.

Therefore, within the context of those who are successfully recruited for smoking cessation behavioural therapy (SCBT) in disadvantaged areas, this study will explore the channels through which participants heard about the SCBT and were referred to this service, and whether these channels recruited a different group of smokers. This study uses data from an intervention carried out in disadvantaged neighbourhoods in the Netherlands. Free behavioural therapy with optional reimbursed pharmacotherapy was offered. In these geographically defined areas, campaigns were launched aiming to recruit smokers living in these areas. These included use of the GP, other health professionals, community organisations, media and word of mouth. We will consider which channels were used, the characteristics of the smokers using these channels and whether channel predicted attendance of the smoking cessation service. A descriptive approach has been used in this article due to its explorative nature, as there is little evidence that any single channel is either the most effective or the most favoured by people from lower socioeconomic status (SES) groups.

METHODS Participants The 109 participants in this study were recruited among participants in SCBT as implemented in two large cities in the Netherlands, here referred to as Cities A and B. There were two sites in each city. Three sites were amongst the 40 most disadvantaged areas in the Netherlands according to a classification of the Dutch government [31], two of which had large ethnic minority populations. City B, also included an area which scored in the lowest 10% of areas in the Netherlands when compared on education, income and job prospects of participants [32]. Recruitment of study participants took place from May 2011-October 2013.

Channels In each city, a broad range of activities were implemented to recruit participants in the SCBT through different channels, including GP, other health care professionals, and media. In one city (City A) community organisations were also approached and participants were also encouraged to recruit their own contacts.

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Local GP’s actively told their patients about, and referred them to, the SCBT. In both cities, a staff member from the SCBT provider liaised with local GPs to ensure that practices in the areas knew about the programme and would actively refer patients. In City A, this liaising staff member also held a feedback session for the GPs during the study period and sent out letters reminding GPs about the services later in the study period. Twenty-one different GPs from 13 different practices referred patients to the SCBT.

Other health professionals (HP) such as practice support nurses and pharmacists actively told patients/clients about the SCBT and referred them. In the GP practices involved, practice nurses were informed about the programme by SCBT provider staff members or their practice managers, and were able to refer patients to the programme. Information was provided in both cities by local pharmacists (one in each area) and community nurses (10 in total).

Community organisations (e.g. religious/cultural/ sporting/food bank) were targeted by the SCBT Coach or Project Leader to gain the support of the leadership or to directly approach participants. Twenty-eight community organisations (with a combined following of at least 3 3700 people) were approached leading to 90 contact moments and 36 site visits, some of which involved making presentations to the members, manning information stalls at the community organisation’s own events, or discussions with the key leaders.

Media sources were also used. Posters and flyers were available in various locations in each area including GP surgery, pharmacy, community centre and library. In City A these were also distributed at many of the community organisations mentioned above. These were available 2-3 months prior to each course (City B) or shortly before the start of the first course (City A) and remained visible for the entire recruitment period. These were in Dutch (both cities) and Turkish (City A). The local newspaper carried either a story about the programme (City A) or an advertisement of the programme (City B) during the recruitment period. Information about the course was available on a local (specific to the local SCBT provider) or national (smoking cessation organisation (STIVORO)) website. In City A only, information about the SCBT and how to sign up displayed on a television screen in the waiting room of a general practice where the SCBT was run.

Recruitment of participants through word of mouth was actively promoted in City A, where participants of the SCBT were encouraged to recruit other participants.

SCbT intervention The SCBT was offered by telephone (7 sessions) or in a group setting (9 sessions, and two additional sessions on participant-chosen lifestyle topics). A date on which participants would quit was agreed with their counsellor. City B offered group counselling only. All participants in group counselling were offered pharmacotherapy, as were those smoking >10 cigarettes per day in telephone counselling. For part of the study period (in 2011 and 2013) pharmacotherapy could be obtained free of charge, as long as there had been contact with the GP.

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Data collection All participants >18 years of age who signed up for SCBT were asked if they would participate in the research. All those who expressed interest in participating were contacted. Participants were contacted by telephone, a minimum of 4 times. If participants were unable to be contacted, or refused to take part in the research, they were categorised as ‘non-response’. Of the 270 participants who signed up for SCBT, 161 agreed to be contacted. Of those, 49 were non-response and three were excluded (due to hospitalisation, only participating to support a friend and not actually wishing to quit smoking, and because the coach did not feel that the participant was ready to quit and thus did not enrol him in the course, respectively), leaving 109 participants. Of these, 27 dropped out prior to the second questionnaire, however they were included in all of the analysis except that of attendance, which required information from the second questionnaire.

Participants in the research were invited to undertake 4 questionnaire-guided face-to-face interviews at the following intervals: prior to SCBT (baseline), and then 4-6 weeks, 6 months and 1 year after their agreed quit date. They were given a €10 honorarium per interview. Interviews took place in Dutch or Turkish, according to participant preference. Data for all variables except attendance (second questionnaire) was collected in the baseline questionnaire. Informed consent was obtained from all participants. Medical ethical approval for this study was not required under Dutch law as no intervention was undertaken by the researchers.

Measures Socio-demographic variables were measured as follows: gender (male/female), age (age at start of course), relationship status (dichotomised: ‘partner’ (married / registered partnership, living together) / ‘No partner’ (unmarried/never married, divorced or widower)), ethnicity (as per definition of Statistics Netherlands [33]: Dutch (born in the Netherlands with two parents born in the Netherlands) / non-Dutch (first generation (born outside the Netherlands with one or both parents born outside the Netherlands) or second generation (born in the Netherlands with one or both parents born outside the Netherlands)). Educational level was used as a proxy for SES, and was measured in tertiles (none or primary / secondary / tertiary).

Participants were asked: ‘How did you hear about the stop smoking programme?’ For each of the channels used, participants had to indicate whether they had heard through this channel or not.

Participants were also asked: ‘Who referred you to the stop smoking programme?’ Possible answers were: GP, member of a community organisation, or someone else. They were further asked about the name of the individual / organisation and, in the case of an answer of ‘someone else’, what their relationship was with the person.

Self-efficacy expectations were measured with 6 questions, such as: ‘You feel stressed or tense. Will you succeed in not smoking?’ These questions were developed specifically for ethnic minority groups in The Netherlands and have been validated [34,35]. Answers were on a five point Likert- type scale from ‘definitely’ to ‘definitely not’ (scored 1-5 respectively), with an additional answer of ‘don’t know’ (scored 0). Cronbach’s α was 0.85. The possible range after summation was 6-30.

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Social support expectations of partner, children, extended family and friends respectively (4 items) were measured with questions such as: ‘Will you be supported by your partner if you stop smoking?’ Questions on perceived social support, also from the same source as those of self- efficacy expectations (above), were modified by researchers to clarify how much social support people expected to receive, as this may have an impact on attendance [36] and smoking cessation behaviour [18,19]. Possible answers were ‘a lot’, ‘average’, ‘little’, ‘no’ (scored 3 – 0 respectively) or ‘not applicable’ (scored 0). Cronbach’s α was 0.46. The possible range after summation was 0-12.

Motivation to quit was measured with the question: ‘How motivated are you to stop permanently during this programme?’ This question was chosen by researchers. Answers were on a scale from 1-10, where ‘1’ was ‘not motivated’ and ‘10’ was ‘highly motivated’.

Nicotine dependence was measured with the Fagerstrøm Test for Nicotine Dependence with revised scoring [37]. The answers to the 6 questions were summed (possible range 0-10) and then participants were categorised according to score from ‘low dependence’ (0-4), moderate 3 dependence (5) and ‘high dependence’ (6-10).

Attendance was measured with the question: ‘How many group sessions have you attended?’ or ‘How many telephone conversations have you received?’ This was asked in the second questionnaire which was done 4-6 weeks after participants agreed quit date, thus at a time when participants attending fully would have completed a minimum of 5 telephone counselling sessions, or a minimum of 7 of group counselling sessions. For this reason, attendance was dichotomised at ≤3 and ≥4 sessions, according to the Dutch clinical guidelines [28]. At the time of the second questionnaire, participants falling into the first group would have had to have missed at least 2 sessions for telephone and at least 4 sessions for group counselling.

Analysis Analysis was done using IBM SPSS Statistics Version 21 (Release 21.0.0.1). To analyse which channels were used, we first sorted participants answers about the channel through which they heard about the SCBT and were referred to the SCBT into meaningful categories. We then determined how many participants heard and were referred through each channel.

To explore the characteristics of participants, characteristics were considered per channel, including socio-demographic characteristics and psychosocial variables influencing quit success. To test whether socio-demographic characteristics differed per channel (some of which contained small numbers), the extended Fisher’s Exact Test was applied. Participants who had heard from >1 source were excluded for this testing. For self-efficacy expectations, answers to all of the six questions making up this variable were summed per individual. After this, the mean and 95% Confidence Interval per reach and referral channel were determined. This method was also used for social support expectations. The mean and 95% Confidence Interval was determined for motivation to quit and nicotine dependence, per reach and referral channel. Differences were considered to be significant if confidence intervals did not overlap.

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To determine whether the channel predicted attendance of ≥4 sessions of SCBT, logistic regression analysis was used. Each of the multivariate models was corrected for age, gender, ethnicity, educational level and counselling type. A p-value of <0.05 was considered significant.

RESULTS The characteristics of the 109 participants can be found in Table 1. The average age of participants was 48 years. Approximately half were female and over half were from ethnic minority groups. Just over a quarter of the participants had no or primary education only.

Table 1: Participant characteristics

All participants (n=109)

n(%) Gender Male 57(52) Female 52(48) Relationship status Partner 57(52) No partner 52(48) Ethnicity Dutch 45(41) Non-Dutch 64(59) Educational level Low 32(29) Medium 61(56) High 15(14)

Mean(SD) Age 48 (13.2)

The channels through which participants heard about and were referred to SCBT can be viewed in Figure 1. The most common way to hear about the SCBT was through the GP (49%), The majority of participants heard about the programme through a single source (82%), which was most often the GP (39%), with a minority hearing from 2 (15%) or 3 (3%) sources. Of those who heard from >1 source, the majority heard from the GP and another source (56%), which was most often a media source (39%). When we restricted the analyses to those with no/primary education only, we found the same pattern (Figure 2). As only a small number of participants heard from a community organisation, this category has been removed from further analysis.

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Figure 1: Channels through which participants heard about and were referred to the SCBT.

Figure 2: Channels through which participants with no/primary education heard about and were referred to the SCBT.

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We observed differences in the characteristics of participants that heard about the SCBT through a particular channel (Figure 3). The percentage of participants in each channel significantly differed by ethnic background (Fisher’s Exact Test = 19.19, p-value = 0.00, two-sided, 4x2 table) and educational level (Fisher’s Exact Test = 12.22, p-value = 0.04, two-sided, 4x3 table). A greater proportion of participants of low educational level and ethnic minority background heard about the SCBT through the GP (36% and 68% respectively) and word of mouth (37% and 73% respectively), than was the case in those hearing through another HP (15% and 23% respectively) and media (19% and 37% respectively) sources.

Figure 3: Socio-demographic characteristics of participants who heard about the SCTB through a specific channel.

There were no significant differences in the motivation, self-efficacy or social support expectations or nicotine dependence of those who had heard through different channels, as determined by comparing the means and 95% Confidence Intervals (Figure 4).

Figure 4: Comparison of the means (and confidence intervals) of variables influencing quit success per channel through which participants heard about the SCTB.

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Reach and recruitment channels did not appear to predict frequency of attendance of the multiple sessions of the SCBT (≥4 sessions) (Table 2), where p-values were calculated using the Wald chi-square test. Controlling for possible correlates did not change estimations (results not shown).

Table 2: Univariate logistic regression models testing the predictive value of channel on attendance of ≥4 sessions.

Channel through which df p-value* Referral channel df p-value* participants heard about OR(95% CI) the SCbT OR(95% CI)

GP No 1.0 1 1.0 1 Yes 0.92(0.33-2.58) 0.88 0.56(0.20-1.57) 0.27 Word of mouth 3 No 1.0 1 1.0 1 Yes 1.23(0.38-3.98) 0.73 1.25(0.23-6.94) 0.80 Another HP No 1.0 1 Yes 1.53(0.29-8.17) 0.62 Media No 1.0 2 Yes 0.93(0.29-3.0) 0.91 Missing 0.45(0.14-1.44) 0.18 Self-referred No 1.0 1 Yes 2.02(0.51-8.00) 0.32

OR = Odds Ratio, CI = Confidence Interval, df = degrees of freedom. *p-values are based on the Wald chi-square test, degrees of freedom = 1 or 2 **p-value <0.05 is considered significant

DISCUSSION We have found that the GP was the main way through which participants both ‘heard about’ and were ‘referred’ to SCBT courses in a disadvantaged areas. More participants of low educational level as compared to those of high educational level heard through the GP and word of mouth. Also, the majority of participants were referred through the GP. We did not find a significant difference in motivation, self-efficacy or social support expectations and nicotine dependence in those who ‘heard about’ the SCBT through different channels. Finally, the channel through which people heard about or were referred to the SCBT did not predict attendance.

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A major strength of this study is that it was done in a usual-care setting of an SCBT intervention offered within the context of disadvantaged areas, rather than in a randomised controlled trial setting where participants are often screened by strict selection criteria and treatment is strictly monitored [38]. As such, we are confident that the responses truly indicate the various pathways through which a range of participants in the community end up at the SCBT.

Another strength of this study is that despite the two cities differing considerably in the proportion of participants from ethnic minority backgrounds, the conclusion, that the GP was the main way through which participants heard about or were referred to the SCBT, is true in both cities (data not shown here). This may make the conclusion generalisable to different types of disadvantaged areas.

Some limitations must, however, be taken into consideration when considering the results of this study. Firstly, due to changes in the Dutch basic health insurance package, during part of the study pharmacotherapy was reimbursed with a GP referral (2011 and 2013) and during the other year (2012), it was not reimbursed. This may have led to participants going to the GP for referral during the reimbursement period after hearing about the SCBT elsewhere, thus increasing the number of participants being referred through the GP. However, we would not expect this to affect the way people heard about the course in the first place.

We missed data for some questions. Due to participant drop-out (27) or missing answers (3), 30 participants (28%) lacked attendance data. Compared to the total participants (Table 1), those who lacked attendance data were more often male, married, and non-Dutch (Appendix 1), however they were reflective of the total group from City A (Appendix 2). We do not think the missing data biased our results because each group for which data were missing in one of the measurements, were similar to the other participants from their city (Appendix 1 & 2).

The Cronbach’s alpha for social support expectations was low and thus possibly not reliable. However, the results found showing lack of difference in social support expectations also mirror the relationships for other quit success influencing factors.

It is always possible that certain reach or referral channels were not exploited to their full potential, leading to low gain from that channel and thus biasing the results. For example, it is possible that some of the community organisations were visited too far in advance of the SCBT availability. We do not think that this biased the results, however, as the efforts in each of the channels were of a similar intensity, or, if of a lesser intensity (i.e. word of mouth), probably reached a similar number of motivated members of the target group.

Attendance was measured toward, but prior to, the end of the course. It is possible that some participants who had missed several sessions at the start then attended well at the end of the SCBT and were incorrectly categorised into the <4 sessions category while they actually attended more sessions. We would not expect this to lead to bias, however, because we would not expect any misclassification to be greater in any particular channel.

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Several implications for recruitment activities in disadvantaged areas arise from this research. Firstly, while a considerable proportion of the individual SES of the residents of a disadvantaged area may be low, this will not be the case for all residents [12]. Just over a quarter of our participants were of low educational level. In the UK, where geographical targeting is also used, a 10 year review of the national stop smoking services found that 54% of smokers treated belonged to disadvantaged groups (measured by eligibility for free prescriptions) [8]. This proportion is higher than we found in this study, though educational level of participants alone is not available in the UK study, thus we cannot directly compare this result with that of our own study. Because geographical targeting results in channels being open to all residents of the area, those with individual-level low SES make up only a proportion of those who participated. It is possible that further targeting of those with individual-level low SES characteristics (e.g. low income or low educational level) within disadvantaged areas is required to gain a larger proportion of participants of individual-level low socioeconomic status.

General practices are often used to recruit smokers in disadvantaged areas [12,13,39]. The 3 question posed by a recent Cochrane review, with regard to which strategies work in low SES groups [10], can be partly answered by our study, where the majority of participants of low SES both heard about and were referred to the SCBT by their GP. The findings of this review, that personalised, proactive (from the point of view of the GP) approaches with increased contact time were most effective [10] is echoed by our highest yielding channel, the GP. However, we cannot comment directly on effectiveness because we do not know how many participants were reached by this channel overall.

One of the tasks GPs are recommended to perform in the Netherlands is giving smoking cessation advice [40]. If they find a patient is willing to quit, but do not have the time to provide smoking cessation support themselves, they are recommended to refer the patient to an SCBT programme provider or to arrange a follow-up appointment with their practice nurse, if they are properly trained in provision of intensive smoking cessation counselling [40]. However, GPs do not perform this task systematically [41]; one study which videotaped general practice appointments found the Dutch GPs in 2007-2008 discussed smoking in a minority of consultations [42]. We would recommend that GPs be encouraged to follow the guidelines, and that they be made aware and regularly reminded of the SCBT offerings available in their local area to whom they can refer.

Another strategy which has been used to reach smokers in disadvantaged communities is use of existing community organisations (e.g. sports, religious or cultural [15,43]). This can be done by personally approaching members or by attempting to gain support from, or influence the attitudes of, the most influential members of these organisations. Despite interactions with many organisations, only 3% of our participants indicated that they had heard about and 6% indicated that they were referred to the SCBT through community organisations. Thus in this study, there is limited direct additional benefit from the community organisation channel.

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Personal contacts can be very important in disadvantaged areas, and especially amongst those of low socioeconomic background [44], and this has also been shown in some ethnic minority groups [45,46]. A Swiss study found that in a disadvantaged ethnic minority group the 12 month success rate was very high after recruitment using a personal contacts approach [47]. Thus it might be expected that ethnic minority participants in disadvantaged areas would hear about smoking cessation opportunities from friends and relatives. This was confirmed by our research where 28% of participants heard through ‘word of mouth’, most of whom were non-Dutch, suggesting that this channel may be better utilized in this group.

Media is also often used to recruit smokers in disadvantaged areas [13,43] and this can include posters, flyers, or advertising in newspapers etc. McDonald, in a review, found that in the general population interpersonal approaches, such as through the GP, were more effective than media, however, more effective still, was a combination of the two [48]. Though we cannot comment on effectiveness, in our study, a quarter of participants had heard about the SCBT through the media, and most of these were then referred by the GP. A majority of them were of medium and high educational level. We also found that of those who heard from more than one source, many heard from the GP and media, however, unlike McDonald, this combination was not the most successful approach, as most people only heard from a single source.

The motivation, self-efficacy and social support expectations, and nicotine dependence of those using various channels to hear about the SCBT were similar in this study. The highest yield in both hearing about and being referred, in both the total study population and those of low educational background, comes from the GP, and there is no negative impact on attendance of using this source. There were some differences in socio-demographic characteristics (e.g. a majority of participants of ethnic minority status heard through the GP), and when this is considered in the context of most participants only hearing from a single source, some groups may be under represented if this channel is used exclusively. Thus we recommend concentrating mainly on the GP channel in disadvantaged areas, and adding further channels if financially possible.

CONCLUSION The main way that most participants heard about and were referred to smoking cessation behavioural therapy in disadvantaged areas of the Netherlands was through the GP. Psychosocial factors influencing quit success and attendance were similar between channels through which participants heard about the SCBT. Focusing on reach and recruitment through the GP would be a reasonable strategy for interventionists with limited resources. When implementing smoking cessation services good contacts with the GP should be made and maintained in disadvantaged areas, such that GPs know which treatment types are available in their local area and where they can refer their patients to.

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FUNDING This study was financed by The Netherlands Organisation for Health Research and Development (ZonMw) (Project number: 200120004).

COMPETING INTERESTS The authors declare that they have no competing interests.

AUTHOR CONTRIbUTIONS FB, KS and MW conceived the study. All authors designed the study. FB prepared and analysed the data. All authors contributed to the interpretation of the data. FB drafted the article. All authors contributed to critical revision of the manuscript.

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30. Patterson F, Jepson C, Kaufmann V, Rukstalis M, Audrain-McGovern J, Kucharski S, Lerman C. Predictors of attendance in a randomized clinical trial of nicotine replacement therapy with behavioral counseling. Drug Alcohol Depend. 2003;72(2):123-131 doi:S0376871603001947 [pii].

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34. Nierkens V, Stronks K, van Oel CJ, de Vries H. Beliefs of Turkish and Moroccan immigrants in The Netherlands about smoking cessation: implications for prevention. Health Educ. Res. 2005;20(6):622-634 doi:10.1093/her/cyh026.

35. Nierkens V, Stronks K, de Vries H. Attitudes, social influences and self-efficacy expectations across different motivational stages among immigrant smokers: replication of the O pattern. Prev. Med. 2006;43(4):306-311 doi:10.1016/j.ypmed.2006.05.005.

36. Benson FE, Stronks K, Willemsen MC, Bogaerts NM, Nierkens V. Wanting to attend isn’t just wanting to quit: why some disadvantaged smokers regularly attend smoking cessation behavioural therapy while others do not: a qualitative study. BMC Public Health. 2014;14(1):695 doi:1471-2458-14-695 [pii];10.1186/1471-2458-14-695.

37. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br. J. Addict. 1991;86(9):1119-1127.

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38. Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet. 2005;365(9453):82-93 doi:10.1016/S0140-6736(04)17670-8.

39. Gilbert H, Leurent B, Sutton S, Morris R, Alexis-Garsee C, Nazareth I. Factors predicting recruitment to a UK wide primary care smoking cessation study (the ESCAPE trial). Fam. Pract. 2012;29(1):110-117 doi:cmr030 [pii];10.1093/fampra/cmr030.

40. Chavannes NHKJV, B.D.; van der Laan, J.R.; Jansen, P.W.M.; Guerrouj, S.; Drenthen, A.J.M.; Bax, W.; Wind, L.A. . NHG-Standaard Stoppen met Roken. Huisarts Wet. 2007;20(7):306-314.

41. de Korte D, van Schayck, O.C.P., van Spiegel, P., Kaptein, A.A., Sachs, A., Rutten-van Mölken, M., Chavannes, N., Tromp-Beelen, T., Bes,R., Allard, R., Peeters, G., Kliphuis, L., Schouten, J.W., van Gennip, L., van Ommen, R., Asin, J.,. Supporting smoking cessation in healthcare: obstacles in scientific understanding and tobacco addiction management. Health (N. Y.). 2010;2(11):1272-1279 doi:10.4236/health.2010.211189. 42. Verbiest ME, Crone MR, Scharloo M, Chavannes NH, van der Meer V, Kaptein AA, 3 Assendelft WJ. One-hour training for general practitioners in reducing the implementation gap of smoking cessation care: a cluster-randomized controlled trial. Nicotine Tob Res. 2014;16(1):1-10 doi:10.1093/ntr/ntt100.

43. Liao Y, Tsoh JY, Chen R, Foo MA, Garvin CC, Grigg-Saito D, Liang S, McPhee S, Nguyen TT, Tran JH, Giles WH. Decreases in smoking prevalence in Asian communities served by the Racial and Ethnic Approaches to Community Health (REACH) project. Am. J. Public Health. 2010;100(5):853-860 doi:AJPH.2009.176834 [pii];10.2105/AJPH.2009.176834.

44. Cattell V. Poor people, poor places, and poor health: the mediating role of social networks and social capital. Soc. Sci. Med. 2001;52(10):1501-1516 doi:S0277953600002598 [pii].

45. Rodriguez MD, Rodriguez J, Davis M. Recruitment of first-generation Latinos in a rural community: the essential nature of personal contact. Fam. Process. 2006;45(1):87-100.

46. Begh RA, Aveyard P, Upton P, Bhopal RS, White M, Amos A, Prescott RJ, Bedi R, Barton PM, Fletcher M, Gill P, Zaidi Q, Sheikh A. Experiences of outreach workers in promoting smoking cessation to Bangladeshi and Pakistani men: longitudinal qualitative evaluation. BMC Public Health. 2011;11:452 doi:10.1186/1471-2458-11-452.

47. Schnoz D, Schaub M, Schwappach DL, Salis GC. Developing a smoking cessation program for Turkish-speaking migrants in Switzerland: novel findings and promising effects. Nicotine Tob Res 2011;13(2):127-134 doi:ntq220 [pii];10.1093/ntr/ntq220 [doi].

48. McDonald PW. Population-based recruitment for quit-smoking programs: an analytic review of communication variables. Prev. Med. 1999;28(6):545-557 doi:S0091- 7435(98)90479-0 [pii];10.1006/pmed.1998.0479.

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APPENDIx 1: CHARACTERISTICS OF PARTICIPANTS WITH MISSING DATA

Participants missing attendance data (n=30)

n(%) Gender Male 19(6) Female 11(37) Relationship status Partner 22(73) No partner 8(27) Ethnicity Dutch 8(27) Non-Dutch 22(73) Educational level None or Primary 12(40) Secondary 15(50) Tertiary 3(10)

Mean(SD) Age 47.50(12.09)

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APPENDIx 2: CHARACTERISTICS OF PARTICIPANTS RECRUITED FROM CITIES A AND b.

City A City b (N=82) (n=27)

n(%) Gender Male 48(59) 9(33) Female 34(42) 18(67) Relationship status Partner 45(55) 12(44) No partner 37(45) 15(56) Ethnicity 3 Dutch 19(23) 26(96) Non-Dutch 63(77) 1(4) Educational level None or Primary 30(37) 2(7) Secondary 44(54) 17(63) Tertiary 8(10) 7(26)

Mean(SD) Age 46.33(11.84) 52.52(16.17)

400350-L-bw-Benson 400350-L-bw-Benson Chapter 4 Wanting to attend isn’t just wanting to quit: Why do some disadvantaged smokers regularly attend smoking cessation behavioural therapy while others do not? A qualitative study.

Based on: Benson FE, Stronks K, Willemsen MC, Bogaerts NM, Nierkens V. Wanting to attend isn’t just wanting to quit: why some disadvantaged smokers regularly attend smoking cessation behavioural therapy while others do not: a qualitative study. BMC Public Health. 2014;14:695 doi:10.1186/1471-2458-14-695.

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AbSTRACT background. Attendance of a behavioural support programme facilitates smoking cessation. Disadvantaged smokers have been shown to attend less than their more affluent peers. We need to gain in-depth insight into underlying reasons for differing attendance behaviour in disadvantaged smokers, to better address this issue. This study aims to explore the underlying motivations, barriers and social support of smokers exhibiting different patterns of attendance at a free smoking cessation behavioural support programme in a disadvantaged neighbourhood of The Netherlands.

Methods. In 29 smokers undertaking smoking cessation group therapy or telephone counselling in a disadvantaged neighbourhood, qualitative interviews were completed, coded and analysed. Major themes were motivations, barriers to attend and social support. Motivations and social support were analysed with reference to the self-determination theory. Results. Two distinct patterns of attendance emerged: those who missed up to two sessions (“frequent attenders”), and those who missed more than two sessions (“infrequent attenders”). The groups differed in their motivations to attend, barriers to attendance, and in the level of social support they received. In comparison with the infrequent attenders, frequent attenders more often had intrinsic motivation to attend (e.g. enjoyed attending), and named more self-determined extrinsic motivations to attend, such as commitment to attendance and wanting to quit. Most of those mentioning intrinsic motivation did not mention a desire to quit as a motivation for attendance. No organizational barriers to attendance were mentioned by frequent attenders, such as misunderstandings around details of appointments. Frequent attenders experienced more social support within and outside the course.

Conclusion. Motivation to attend behavioural support, as distinct from motivation to quit smoking, is an important factor in attendance of smoking cessation courses in disadvantaged areas. Some focus on increasing motivation to attend may help to prevent participants missing sessions.

Keywords. Smoking cessation, group therapy, telephone counselling, attendance, low socioeconomic status.

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INTRODUCTION Smoking is a major preventable cause of death in Europe [1]. It is of particular importance for those of low socioeconomic status (SES), as they are more likely to smoke [2-4] and have been shown to be less likely to succeed in quit attempts [5,6]. For these reasons, it is important to provide evidence-based measures to disadvantaged smokers to maximise every quit attempt’s chance of success. One such measure is the combination of behavioural support, in the form of a group therapy or telephone counselling, and pharmacotherapy.

Several studies show positive effects of behavioural support although the effect size differs [7,8]. The effect size is dependent, amongst other things, on attendance rate. A Cochrane review on the effect of behavioural support in combination with pharmacotherapy [9] found, on pooling 38 studies most of which offered 4 or more sessions, that there was a small but statistically significant positive effect of increased attendance of the behavioural therapy, be it face-to-face or by phone, on long-term quitting behaviour.

Those of low SES, in particular, have been shown to exhibit poor attendance of smoking cessation behavioural support, attending less often than their higher SES counterparts [10,11]. Hiscock et al. (2011) suggested that addressing this problem of low attendance rates would increase success rates in disadvantaged smokers [10]. 4 The existing research into attendance in community-based smoking cessation programmes gives insight into the background characteristics of participants and typically concentrates on whether quit attempts are successful, rather than participants’ attendance behaviour. Moreover, as far as they address attendance, these are mainly quantitative studies. For example, studies among Latino smokers [12,13] found that completion of the intervention or assessment was more likely when participants were less depressed, saw less ‘pro’s’ of smoking, were unemployed [12], and had less initial confidence in their ability to quit, better health in relation to peers, in addition to higher income [13]. Two qualitative studies have been identified which discuss smoking cessation and attendance [14,15]. The first, Lee et al. (2013), is a study which looks at the reasons smokers and health care professionals give for smokers’ lack of cessation. This study, however, only looks at participants who have ceased treatment (and remained smoking). Allen et al. (2012) is also a qualitative study of participants reasons for failing to complete a smoking cessation intervention, however, this intervention gives participants incentives to quit. The focus was on the effect of the incentives and, again, only participants who had missed sessions were included. None of the existing papers looks at attendance behaviour with reference to a theory of motivation, however, such a theory is necessary to deepen an understanding of motivations to attend behavioural support programmes.

Self-determination theory (SDT) [16], is a theory of motivation which has been used to consider the role of motivation in behavioural persistence in an educational setting [17] and in exercise adherence in the longer term [18]. There are three types of motivation which are part of a continuum from non-self-determined to self-determined [19] (see Table 1). The first type of

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motivation is termed “amotivation”, or non-self-determined behaviour. The second and most common type of motivation, is “extrinsic motivation”, or motivation to achieve a particular goal. And the third type of motivation is “intrinsic motivation”, which is doing something for the joy of the activity itself and is fully self-determined. Within extrinsic motivation there are four different levels of motivation, moving from less self-determined to more self-determined. “External regulation” is a behaviour performed only to satisfy an external demand or reward and is the least self-determined or autonomous. Slightly more self-determined are “Introjected regulations”, which are behaviours performed to prevent guilt or anxiety or for ego reasons, such as pride. People are motivated in order to maintain feelings of self-worth. It involves internalising some regulation, but not accepting it fully as one’s own. The next most self-determined is “Identified regulation”, in which a behavioural goal is consciously valued, so that the action is accepted or owned as personally important. And finally, the most self-determined of the extrinsic motivations, is “Integrated regulation”, which occurs when an external goal is fully internalised and assimilated with an individual’s other values and needs. This is closest to intrinsic motivation, however it is still done to satisfy an external goal. The more self-determined a behaviour is the more likely it is to be undertaken by an individual.

Table 1: The self-determination continuum

Type of Intrinsic Amotivation Extrinsic motivation motivation motivation

Type of Non-regulation External Introjected Identified Integrated Intrinsic regulation Type of Non self-determined Self-determined behaviour Adapted from Deci & Ryan (2000) [20]

Making a behaviour more self-determined can be achieved by fulfilling one or more of the three basic needs for relatedness, autonomy and competence [20]. Autonomy is the ability to guide one’s own behaviour [21]. Relatedness is feeling ‘securely connected to and esteemed by others and to belong to a larger social whole” [21], and competence is the skills which enable meaningful actions to be taken.

This theory also discusses support, which is important in attendance. Social support, from those in an individual’s environment or a counsellor, can help individuals to fulfil the three basic needs. Autonomy support helps as it involves people important to the individual creating a social environment which features “eliciting and acknowledging perspectives, supporting self-initiative, offering choice, providing relevant information and minimizing pressure and control.” [22]. Autonomy support in turn enhances feelings of competence toward a behaviour and thus an individual’s intentions toward that behaviour [22]. Relatedness, which can also be provided by autonomy supportive relationships, helps by encouraging individuals to undertake a behaviour because it is “valued by significant others to whom they [feel] (or would like to) feel connected” [19].

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Based on this theory it seems important to study underlying basic needs in relation to attendance behaviour, and to begin this work with a qualitative study to inform future quantitative studies. The aim of this study is to understand in-depth the motivations of smokers of low SES who attend many, as well as, fewer sessions of smoking cessation behavioural support, regardless of smoking status. Our research question is: Do smokers of low SES who regularly attend smoking cessation therapy differ in their motivations, barriers and social support, from those who do not?

METHODS Setting The study took place in The Hague, which is one of the four largest cities in The Netherlands, with a population of 506,366 [23]. People living in a disadvantaged, multi-ethnic neighbourhood were offered free smoking cessation behavioural support with or without pharmacotherapy. The behavioural support consisted of either group therapy or telephone counselling (see Table 2). Participants should choose their support type. Group therapy [24] consisted of 9 sessions of group training +/- two sessions of extra activities (17/29 participants). Telephone counselling [25] consisted of 7 standard sessions (12/29 participants). Participants began the behavioural support while still smoking, but were expected to stop at a certain time during the course. Both behavioural support types were available in Dutch and Turkish. 4 Study design This study is part of a larger quantitative study of the effectiveness of a smoking cessation program in a disadvantaged, multi-ethnic neighbourhood in The Hague. In this study, people who enrolled to attend smoking cessation behavioural therapy offered in a disadvantaged area of The Hague were asked to participate and were then followed-up on four occasions (a baseline interview, an interview at 4 weeks, 6 months and 1 year after their agreed quit date). In this qualitative study, in-depth interviews were used because we aimed to understand the process individuals went through with regard to attendance, as well as their behaviour and perceptions.

Recruitment Participants were recruited between October 2011 and May 2012 by purposive sampling from participants in the larger study. They were selected for their variety in attendance behaviour, from complete attendance through to attending only the intake session, and for their diversity of ethnic backgrounds, reflecting the disadvantaged neighbourhood’s population.

Recruitment for the study was done by two of the authors and two additional interviewers (see acknowledgements), who contacted participants by phone to ask if they were willing to participate. Contact was attempted five times on different days and at different times. Of the 72 participants enrolled in the quantitative study at that time, 47(65%) were asked to participate and 29(62%) took part. Recruitment was stopped when a purposive sample (i.e. gender, age, ethnicity, marital status, attendance and smoking behaviour) and data saturation were obtained. Of the 18(38%) who did not participate, 12(26%) refused due to lack of time or no

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Table 2: Characteristics of Both Behavioural Support Types Offered

Characteristic Group therapy Telephone counselling

Number of sessions 9 standard weekly sessions, 7 standard sessions over the course sometimes supplemented by +/- 2 of 3-4 months, with up to 5 extra extra sessions, in this disadvan- sessions if the participant has taged area, on open topics chosen relapsed or has not stopped after by the group, such as stress the first session. management. Number of participants 8 – 12 1

Session duration 1.5 – 2 hours Session 1: 30 minutes Subsequent sessions: 15 minutes. Timing of official stop date Session 4 Between Sessions 1 and 2.

Languages available Dutch and Turkish Dutch and Turkish

Gender of participants Offered in mixed group (in Dutch) N/A or all male and all female groups (in Dutch & Turkish). Permitted to keep Yes Yes participating if not stopped on official stop date Content of sessions The course increases motivation 1. The participant’s motivation is and teaches self-control techniques increased using motivational using learning methods such interviewing and they are as group discussion, working in prepared for the first few days pairs, role play, individual and after stopping. group exercises, visualisation, and 2. Withdrawal symptoms. homework exercises. 3. Desire to smoke. Topics include: 4. Tempting situations. • Self-observation, 5. Topic of choice (including • Analysis of tempting stress, weight gain, gloom, situations, boredom or loneliness.) • Decreasing nicotine use, 6. Prevention of relapse. • Motivation, 7. Follow – up (after 3 months • Behavioural rules, Sessions 2 – 7 all include some time • Suddenly stopping, spent on maintaining motivation. • Changing smoking behaviour, [25] • Rewarding yourself, • Coping with desire to smoke, • Cognitive restructuring, • Coping with social pressure, • Relapse prevention after a slip. [24]

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Table 3: Participant Characteristics

Characteristics Number of participants n(%)

Gender (n(%)): Male 17(59) Female 12(41) Nationality (n(%)): Dutch 9(31) Turkish 15(52) Surinamese 4(14) Antillean 1(3) Marital status (n(%)): Married 15(52) Partner 1(3) Single (unmarried / no partner) 7(23) Divorced 6(21) Therapy type (n(%)): Group therapy 17(59) Telephone counselling 12(41) Pharmacotherapy (n(%)): 4 Yes 22(76) No 7(24) Ages (years): Range 24 - 71 Mean(SD) 46.10(12.25) Self-reported smoking status after course (n(%)): Stopped 9(31) Smoked less 13(42) Unchanged 7(23) Fagerstrøm Test of Nicotine Dependence score (n(%)): Very low dependence (0-2) 5(17) Low dependence (3-4) 6(21) Medium dependence (5) 6(21) High dependence (6-7) 8(28) Very high dependence (8-10) 4(14)

Mean score(SD) 5(2.31) Participants’ estimate of the chance of success of this quit attempt measured prior to beginning behavioural support (0-10): Mean(SD) 7.75(2.05) Participants’ motivation to permanently stop during the programme measured prior to beginning behavioural support (0-10): Mean(SD) 8.70(1.35)

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interest in the subject of stopping smoking or both, 3(6%) couldn’t be contacted, 2(4%) refused due to health reasons, and 1(2%) refused due to having only done an intake interview and not the full course. Of those 18 (2 unknown), the attendance status was: present at all (3(17%)), missed >2 (8(44%)), and Intake only or dropped out prior intake (5(28%)).

Participant characteristics The characteristics of participants can be viewed in Table 3. The majority of participants used pharmacotherapy, including varenicline, bupropion or nicotine replacement patches/lozenges.

Data collection The data was collected during face-to-face (28) and telephone (1) semi-structured interviews done in the months following the behavioural support. Most face-to-face interviews were conducted in the participant’s home or, on occasion, in a public place (e.g. library). Participants received a €10 honorarium for participation. Informed consent for participation in the larger study had already been obtained from all participants. Under Dutch law medical ethical approval was not required for this study. Participants were given a participant number to ensure their anonymity and identifiable information was kept confidential.

A topic list based on themes from the literature, such as expectations of the course, social support received by participants, and depressed mood, was developed as a guide for the interviews. Open questions were asked such as: “Some participants missed sessions now and again. How did you come to attended all the sessions?”, “Did you ever consider not going?”, ”Could you tell us about the times you considered not going?”, or “Could you tell us about the times that you didn’t attend a session?”. Interviews of between 30-90 minutes were recorded and interviewers made field notes after the interviews, describing where the interviews had taken place, and indicating any occurrence which may have altered the information given in the interview, such as the presence of a family member. Interviews were transcribed verbatim into either Turkish or Dutch. All Turkish transcripts were then translated verbatim from Turkish into Dutch. Transcripts were not returned to participants for comment or correction due to the expected high proportion of participants unable to read or write to a sufficient level to undertake this task, though verifiable facts were checked with the quantitative data for veracity.

Four female interviewers undertook the interviews, all of whom had undertaken tertiary studies in Health Sciences or anthropology. Two interviewers were experienced qualitative interviewers and two had had training prior to undertaking interviews. The interviewers were not involved in executing the intervention. No researchers in this project had any competing interests.

Analysis The data was analysed using an inductive approach [26,27] which allows researchers to develop a framework of the underlying processes existing in the data [27]. Two researchers (FB) (NB), independently developed codes and refined these into a single code hierarchy based on the analysis of 6 initial interviews. Disagreements were brought to the attention of a third researcher

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(VN) for discussion and decision. A further 4 interviews were then coded by two interviewers (FB) (NB) at intervals throughout the coding process to ensure congruence. Extra themes emerging from the data were added to the coding hierarchy on the basis of these additional interviews and, subsequently, as they occurred in the remainder of the interviews. Coding was applied by researchers in the software package MAXQDA (Version 10), which aided in data retrieval. Analysis identified themes occurring in the data and thematic charts were developed which aided in synthesis and summarisation of the data and in looking for all potential associations in the data. During the initial analysis we found a pattern within the motivations to attend that fitted the self-determination theory [19]. Subsequently motivations to attend were assigned along the self-determination continuum [20] by a single researcher (FB or NB) and this was checked by a second researcher (VN). Social support was also analysed with regard to the conditions which foster self-determined behaviour [20]. Barriers were analysed with regard to the source of the barrier, and these were subsequently cross-referenced with the motivations of the individuals involved. Differences of opinions were discussed and resolved prior to finalisation.

Major themes were interview guided. These were motivations to attend the course, social support both outside and within the course, and barriers to attendance. Through thematic charting minor themes emerging from the data were identified. We present here the strongest patterns in the data which help to clarify the research question. The results are given in sections 4 for each of the major themes, and these are then subdivided by minor themes.

We also looked for the influence of other factors on attendance such as reasons to do the course, ethnicity, experiencing a stressful life event, depression, medication, gender, and expectations of the course.

RESULTS During the analysis we saw that the participants fell into one of two main groups with regard to their motivation to attend, barriers to attendance and social support. These groups were those who missed up to 2 of the scheduled sessions of group therapy or telephone counselling (frequent attenders) and those who missed more than 2 of the scheduled sessions of group therapy or telephone counselling, including those who had an intake interview only (infrequent attenders). In the case of telephone counselling, a session was not considered missed if it was re-scheduled and then took place.

Findings in the results section will be given with reference to these two groups. The groups were not evenly distributed; there were 21 frequent attenders and 8 infrequent attenders, and more infrequent attenders were male. The participant characteristics of the two groups were otherwise similar (see Table 4).

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Table 4: Participant characteristics of frequent and infrequent attenders

Characteristics Frequent attenders Infrequent attenders

Gender (n(%)): Male 10(48) 7(88) Female 11(52) 1(13) Nationality (n(%)): Dutch 6(29) 3(38) Turkish 11(52) 4(50) Surinamese 4(19) - Antillean - 1(13) Marital status (n(%)): Married 10(48) 5(63) Partner 1(4.8) - Single (unmarried / no partner) 5(24) 2(25) Divorced 5(24) 1(13) Therapy type (n(%)): Group therapy 12(57) 5(63) Telephone counselling 9(43) 3(38) Pharmacotherapy (n(%)): Yes 17(81) 5(63) No 4(19) 3(38) Ages (years): Range 24 – 66 26 – 71 Mean(SD) 45.19(11.39) 48.50(14.86) Self-reported smoking status after course (n(%)): Stopped 8(38) 1(13) Smoked less 4(19) 3(38) Unchanged 9(43) 4(50) Fagerstrøm Test of Nicotine dependence score (n(%)): Very low dependence (0-2) 2(10) 3(38) Low dependence (3-4) 5(24) 1(13) Moderate dependence (5) 4(19) 2(25) High dependence (6-7) 7(33) 1(13) Very high dependence (8-10) 3(14.3) 1(13)

Mean score(SD) 5.43(1.99) 3.88(2.85) Participants’ estimate of the chance of success of this quit attempt measured prior to beginning behavioural support (0-10): Mean(SD) 8(1.69) 7.13(2.80) Participants’ motivation to permanently stop during the programme measured prior to beginning behavioural support (0-10): Mean(SD) 8.84(1.12) 8.38(1.85)

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Motivations to attend the course Enjoyment of the course A third of the frequent attenders mentioned enjoyment of the sessions, the atmosphere and the group, as a reason for attendance. This percentage differed between the two types of courses: half of the group therapy attendees mentioned enjoyment while only one participants undertaking telephone counselling did.

Interviewer (I): And there were moments when I thought, we-e-ll.. [that you didn’t want to go?] Respondent (R): No, I always enjoyed it. I enjoyed going. (1016, male, 59, Surinamese, group therapy, stopped smoking, frequent attender)

This was in contrast with the infrequent attenders, where only one participant mentioned enjoyment of the course. These participants often named no longer enjoying the sessions after the initial few sessions. This seemed to be related to perceived barriers which will be described later. According to self-determination theory intrinsic motivation is a strong motivator to continue undertaking a behaviour. It would appear that this is the case for attendance behaviour in this group. A minority of people who mentioned enjoyment of the course mentioned their desire to stop as a motivation for attendance, thus intrinsic motivation to attend often seems to be unrelated to their motivation to quit. 4

Wanting to stop smoking Smokers’ desire to stop was mentioned by over a third of frequent attenders as a motivation for attendance. They mentioned their desire to stop smoking and alluded to the fact that this decision and taking action toward it was in their own hands, as illustrated by the below quote. The desire to stop was mentioned by a single infrequent attender.

Because I made my own decisions. I went for it. I went for it. I said “I’m going to stop” and I did stop… (1039, male, 49, Turkish, group therapy, smokes less after relapse, frequent attender)

The desire to stop and the view that this was in their own hands can be interpreted through the self-determination theory as an extrinsic motivation and one of a more self-determined nature (integrated), because participants have internalised a goal which is not inherently enjoyable, making it their own aim, and they subsequently feel autonomous in their pursuit of this goal.

Interestingly, only a minority of the frequent attenders who reported this desire to stop as a motivator for attendance were intrinsically motivated. Thus it would seem that this desire is a powerful motivator for attendance even in those who don’t report enjoying sessions.

Commitment to attendance Frequent attenders often indicated that they chose to attend of their own free will, for example, they organized their schedule around the course, they placed a high value on appointments or they would not have considered cancelling. No infrequent attenders mentioned commitment

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to attend. One frequent attender alludes to attendance being a ritual for her, and though this was only stated by her, the sense of the ritual of attendance was also present in interviews with other frequent attenders.

I had told the temping agency, you mustn’t call me on Friday, because I am doing the course. I was always there. I could stay at home and then at about 1.30 I could go and sit with my friend who lives on …nearby here. And then, at ten to 3, a quarter to 3, I would leave. It was a ritual for me. (1023, female, 66, Surinamese, group therapy, stopped smoking, frequent attender)

Another participant stressed the value he and his wife placed on appointments, no matter who they were with.

R: Well, we set great store by appointments. I: Mmm. R I mean, whether it’s the G.P. or the dentist... (1030, male, 55, Turkish, group therapy, smokes less, frequent attender)

Telephone counselling participants did not need to commit to being in a certain place at a certain time each week. They often mentioned having re-scheduled sessions for various reasons including death in the family to being currently occupied by another task. This participant indicates the flexibility involved in session scheduling.

I did, now and again, yes, yes, I did now and again. I can’t at the moment... You’re phoning at a bad time. Okay, and then mostly she would phone me back in the evening. Sometimes I was doing the shopping or I would specify a time, then she would phone me at that time. Or you could plan another appointment in the evening, a telephone appointment. (2029 male, 54, Dutch, telephone counselling, smokes less, infrequent attender)

For this, they needed to have the competence to plan convenient appointments with their counsellor, or to reschedule if required.

I put the children to bed at such and such time. Just like I did now [for this qualitative interview]. For example, I’d say “on er…Monday, for example, I won’t be at home. So I can’t talk. Tuesday one of the children sleeps at this time. The other doesn’t bother me. You can phone me, at this time, for example”. That’s how it went. (2009, Female, 33, Turkish, telephone counselling, stopped smoking, frequent attender)

Organisation of their schedule around the course, placing importance on the course and going out of their way for the course can be interpreted as an extrinsic motivation. We interpreted it as a more self-regulated extrinsic motivation because it involves placing importance on an activity which is not inherently enjoyable and then personally committing to ensuring that it is possible to meet the demands of this activity. Autonomy (the personal choice to make the course a priority) and competence (the ability to re-organise one’s personal schedule) are required

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in order to achieve this. The frequent attenders also indicated their feelings of competence (organising schedule around course) and autonomy (importance of keeping appointments) which are not typically named by Infrequent attenders. Interestingly, only some of those frequent attenders who reported this also reported enjoyment of the course or intrinsic motivation, thus commitment to attendance appears to be a powerful motivation in and of itself. This lack of intrinsic motivation, but commitment to the course, is also seen in the majority of telephone counselling participants.

Social support received by participants Social support received by participants undertaking the course came from sources either outside (e.g. partner, family, friends or people in the environment, such as colleagues or acquaintances) or within (e.g. counsellor or other participants) the course.

Social support outside the course Remarkably, both frequent and infrequent attenders faced much negativity toward their quit attempt, or attendance of the course, in the social environment outside the course. And just under half the participants in both groups told no-one or were selective in who they told about their quit attempt. Within this context, however, people also received support, as detailed below.

A minority of participants actually stated that they felt supported in the social environment 4 outside the course. In these cases they perceived support from a certain group or individual (e.g. partner, family, or friends). More often participants mentioned receiving support, despite not mentioning that they felt supported. This took many forms including encouragement, as in the quote below, which we saw as relatedness, or advice or personal stories from stoppers who were known to them, or people not purchasing cigarettes for them or not smoking around them, which we saw as autonomy support

I had a girlfriend who had also stopped and, there she was, and then she said to me every time, “I’m proud of you,” and all that, and that made me feel good. (2031, female, 48, Dutch, telephone counselling, stopped smoking, frequent attender)

The advice or personal stories allowed them to practice self-appraisal or bench-mark themselves against others, as seen here.

Well, if my father has stopped smoking, then everyone will stop. (2026, Male, 34, Turkish, telephone counselling, smokes less, frequent attender)

Almost half of the frequent attenders reported receiving autonomy support or relatedness or both, however, support often came with a lack of support within the same social group. The most common example was receiving support from non-smokers but not from smokers, as in the quote below, though this was not always the case. Infrequent attenders reported receiving little support.

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R: Most of the friends who don’t smoke... I: Mmm R: “You have done well.” I: Mmm R: “Good that you have stopped.” But them who smoke don’t say this (laughs). I: (Laughs) they won’t be satisfied. R: There were satisfied [previously]. If they smoke, I can’t smoke, so... (2027, female, 31, Turkish, telephone counselling, smokes less, frequent attender)

Social support within the course Support within the course from the counsellor is discussed below. Support from the group was only received by group therapy participants, so while it is not discussed here it is important to note that some group therapy frequent and infrequent attenders mentioned feeling supported and motivated by the group. However, negative aspects of the group were also mentioned by half of the frequent and infrequent attenders.

Support from the counsellor Many frequent and infrequent attenders felt motivated and understood by the counsellor, that the counsellor was happy to have them at sessions and that they were given individual attention or feedback. Half the participants felt that the counsellor did a good job, was enjoyable to speak to, or knew what he or she was talking about, as illustrated below.

Well, that the, let’s say, the teacher, er, the course manager, he did it really good, really very good, explains everything very well, and he motivated people, and he did an awful lot so that people stop, but the people, they didn’t come. (1063, male, 67, Antillean, group therapy, smokes less, infrequent attender)

Frequent attenders received more tips, appraisal opportunities or tangible support with organisation of medication from the counsellor than infrequent attenders. This participant describes how his counsellor helped him to get reimbursed pharmacotherapy.

I had to pay for it myself, but that woman [the counsellor] helped me so I didn’t have to pay. She got in touch with the pharmacy, the sickness fund, last year then, and then I didn’t have to pay for it. (1011, male, 43, Turkish, unchanged, frequent attender)

From the theory we see that the opportunities for appraisal, and tangible help which is perceived as support, can be seen as autonomy support. Frequent attenders reported receiving autonomy support from the counsellor more often than infrequent attenders. Feeling motivated and understood by the counsellor, and the counsellor being happy to have them at sessions and giving individual attention and feedback, can be seen as relatedness. Feelings of relatedness to the counsellor were often mentioned by both frequent and infrequent attenders. For many

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participants, the counsellor was able to build a good rapport and supply the need for autonomy support or relatedness.

More telephone counselling participants felt relatedness to the counsellor than did group therapy participants. This relatedness came in the form of feeling motivated by the counsellor or receiving compliments from the counsellor.

Negativity toward the counsellor Negative comments about the counsellor were made by some participants, especially amongst those attending group therapy. While frequent attenders seem to be commenting on the counselling style, such as the counsellor not stopping another participant from speaking at length, infrequent attenders commented on unprofessional behaviour, such as this participant describing the counsellor gossiping with participants about absent participants.

R: Yes, they were always gossiping about others. About other colleagues from the group and in fact the counsellor just got involved and I thought that was a bit, well... yeah. I: And the counsellor didn’t say something like, well, shall we get on with the lesson. R: No, she just got involved in the discussion, too. Joined in. Well, I just felt that this was, whether it was true or not, I don’t like it. (1008, male, 41, Turkish, group therapy, unchanged, infrequent attender) 4

The infrequent attenders who had these experiences with the counsellor also mentioned no longer enjoying the course after this. Thus it is possible that these experiences impact on intrinsic motivation and, as a result, on persistence of attendance behaviour. However, it is also possible that this is a rationalisation for no longer being motivated to attend..

barriers to attendance A third major theme identified was barriers to attendance. During the analysis, three types of barriers emerged: external, internal and organisational barriers.

External barriers The majority of reasons for non-attendance mentioned by frequent attenders were external reasons which were specific to the individual, such as illness, going on holiday or having to work. External reasons were also given by infrequent attenders. Those reasons were mainly given by those attending group therapy. This could be because group therapy participants were unable to re-schedule sessions.

Some frequent attenders also reported going out of their way to attend the course and overcome barriers to participate in sessions. They mentioned taking part in sessions despite illness or tiredness from work. Thus barriers which may have been a reason for non-attendance or an excuse were overcome by frequent attenders, but not by infrequent attenders. Only one of these participants who reported going out of the way for the course stated their commitment to attendance (see section on motivation). However, more self-determined motivations were seen

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in four of the six participants who mentioned overcoming barriers, where four reported wanting to stop and two of these were also intrinsically motivated to attend. No infrequent attenders mentioned going out of their way to attend sessions.

Internal barriers Only one frequent attender gave an internal reason for non-attendance, which was feeling guilty due to having relapsed, as illustrated below.

I: You didn’t attend the last session, and was it also… R: If you ask me, it was also due a bit to my, er, failure, simply, that I actually had to admit that I hadn’t quite succeeded. I: Yes R: That in fact, I, er, yes, on purpose, by accident, I forgot. I: Yes. R: That is what I shall say. The last appointment. I: Ok R: Yes I: Yes. R: Because, in fact, the only thing I could say was that that I really had not succeeded. And that upsets me an awful lot. (laughs) (2008, female, 50, Dutch, telephone counselling, unchanged, frequent attender)

It is possible that this participant did not want to tell her counsellor because she wanted to avoid confrontation or feeling uncomfortable.

In contrast to the frequent attenders, many infrequent attenders mentioned internal barriers. More than half the infrequent attenders mentioned no longer finding it enjoyable or useful to attend, as this participant indicates.

First few times it was nice [before many participants dropped out] (1063, male, 67, Antillean, smokes less, infrequent attender)

Reasons given for this loss of enjoyment included non-attendance by others (previously known to the participant or not), something occurring during sessions, or quitting and thus not finding the sessions useful any more.

We see that some infrequent attenders noted a loss of enjoyment, or intrinsic motivation, as a barrier to attendance, in comparison to the third of frequent attenders who mentioned intrinsic motivation as a motivator of behaviour seen previously. These people may have begun with intrinsic motivation to attend, but seemed to lose it during the course because of what happened during the sessions.

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Organisational barriers While no frequent attenders mentioned experiencing organisational barriers to attendance, the majority of infrequent attenders gave an organizational reason for non-attendance of at least one, if not more, of their sessions. The reasons given included that they had turned up at the agreed place and time and no-one was there, that they were not contacted about starting a course, that sessions had been cancelled, or that they had been put into an inappropriate form of training (group therapy instead of telephone counselling), as seen in the quote below.

I attended 2-3 times. I said at the time that if I am driving instructor, in fact, yes, had little time to come to the meetings and that I preferred to have it with him by telephone. (1014, male, 45, Turkish, group therapy, smokes less, infrequent attender)

Some infrequent attenders made attempts to overcome the organizational barriers, however, others did not.

Organisational barriers to attendance were not reported by frequent attenders, while almost all infrequent attenders experienced them. The near universality of this experience in Infrequent attenders suggests that these barriers may occur regularly, however, it is important to note that none of these participants experienced more self-determined motivations to attend, thus it is possible that they may have been excuses not to attend. 4

Other Themes Other factors which may have had an impact on attendance were also looked at, such as reasons to do the course, ethnicity, experiencing a stressful life event, depression, use of smoking cessation pharmacotherapy, gender, and expectations of the course. The only one of these which had an impact was gender, where we found that most women were frequent attenders. There were no additional differences to those already seen in the division between frequent and infrequent attenders.

DISCUSSION Smokers who frequently attend smoking cessation behavioural support offered in a disadvantaged neighbourhood were found to have more self-determined motivations to attend. Moreover, they had more external, rather than internal or organisational barriers to attend. Frequent attenders also experience more autonomy support and relatedness than infrequent attenders.

The main finding with regard to motivation to attend in this disadvantaged group was that frequent attenders were more likely to exhibit intrinsic motivation or more self-determined extrinsic motivations to attend, compared to infrequent attenders, despite the fact that smoking cessation is not an inherently enjoyable activity [28]. This has not been reported before in the literature. Similar to Lee et al. (2013), we found the desire to quit to be a factor in attendance, however, intrinsic motivation seemed to be an equally important factor in attendance and these two factors were not typically mentioned together, so this factor seems to be as important as a

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desire to quit. Similar to one US study on intervention participation in low SES, ethnic minority attendees of a behavioural intervention [29], we identified internal and external barriers to attendance, however, we additionally found that frequent attenders experienced no organizational barriers to attendance, while infrequent attenders almost universally experienced such barriers.

With regard to social support, most participants, regardless of attendance status, experienced much negativity about their quit attempt or their course participation in the social environment outside the course. In this context, frequent attenders, as compared with infrequent attenders, experienced more autonomy support and relatedness from the counsellor, similar to the abovementioned study [29], and also from people outside the course similar to another US study examining the role of social influence on attendance in a behavioural intervention [30], which. Our findings suggest that a supportive environment inside and outside the course can positively influence attendance behaviour.

Also, those who did group therapy exhibited more intrinsic motivation than those who did telephone counselling. It is possible that the flexibility of the sessions somehow compensated this lack of intrinsic motivation, so that many telephone counselling participants were also frequent attenders, despite undertaking what might be a less enjoyable form of counselling. To our knowledge this has not been previously mentioned in the literature.

Besides the suggestions given above, the results imply that more focus on keeping participants motivated to attend may improve attendance in people from low socioeconomic groups. Intrinsic motivation seems to be an important motivator of continued attendance. This suggests that interventionists and counsellors should make courses enjoyable to ensure maximum attendance. For example, in group therapy, regularly using techniques to increase relatedness, such as ice-breakers and re-energizers [31], could be considered. This also increases social support within the course, which may also positively influence attendance. For other participants who may not enjoy sessions, it may be possible to increase their attendance by flexible scheduling, such as through rolling groups which have been successful in disadvantaged smokers in the UK [32]. It is also possible that increasing social support outside the course, possibly through involvement of family members or friends [27], may increase attendance.

Interestingly, the relationship between attendance and smoking cessation in our study is not clear-cut and further study needs to be done to elaborate on this point.

To our knowledge this is the only European qualitative study of a multi-ethnic group in which disadvantaged smokers give underlying reasons for their patterns of attendance at non-incentive based smoking cessation behavioural therapy programmes, focussing mainly on those who frequently attend, whose perspectives have not been shown before.

However, some limitations need to be considered before drawing conclusions. Firstly, it is possible that a national change in subsidy allocation to pharmacotherapy during the study period biased the results. There was much confusion about how an individual’s pharmacotherapy would be

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paid for by insurance companies. We expected this to be a cause of poor attendance, but did not find it to be so. It may have increased the number of frequent attenders because of a feeling of needing to attend all sessions to gain the reimbursement, however, we do not feel the results were biased because only a minority of frequent attenders mentioned this issue as a motivation for attendance, despite the participants being specifically asked about it.

Secondly, in this research it was not always possible to clearly separate cause and effect. For example, most infrequent attenders mentioned organisational barriers. While removing organisational barriers to attendance through improved and more regular communication with participants both prior to and during the course may lead to increased attendance, we noted that none of the participants who experienced organisational barriers experienced more self- determined motivations to attend, so it is possible this kind of barrier could be an excuse in infrequent attenders. Participants who didn’t overcome their barriers to attend may experience cognitive dissonance [33], and it could be that organisational barriers are rationalisations which help reduce dissonance and mask a loss of motivation. This suggests that investment in increasing motivation is perhaps the most important focus in increasing attendance.

Amongst those who refused to participate in the research, the majority were infrequent attenders, while these were the minority group in our research. It is possible that this may have biased our findings, however, we don’t think this is the case because recruitment was continued 4 until data saturation was reached.

CONCLUSION Attendance behaviour is an understudied aspect of multi-session smoking cessation behavioural support, especially among smokers in disadvantaged areas. The motivations, barriers and social support of those who attend frequently are different from those who attend less frequently. If free behavioural support is offered, participants with varying levels of motivation to attend will enrol. Strategies to increase intrinsic motivation to attend counselling sessions should be an integral aspect of multi-session smoking cessation behavioural support, in addition to strategies to increase motivation to quit.

ACKNOWLEDGEMENTS We wish to acknowledge Mujde Durmaz and Arja Schreij for their role in data acquisition.

FUNDING This study was financed by The Netherlands Organisation for Health Research and Development (ZonMw) (Project number: 200120004).

COMPETING INTERESTS The authors declare that there are no conflicts of interest.

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AUTHOR CONTRIbUTIONS FB participated in study design, data acquisition, analysis and interpretation of data, and drafting the paper. KS contributed to data interpretation and drafting.MW contributed to data interpretation and drafting. NB contributed to data acquisition, analysis and interpretation. VN conceived of the study, participated in its design, contributed to data interpretation and drafting of the manuscript. All authors received and approved the final manuscript.

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REFERENCES 1. Mackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinsalu M, Kunst AE. Socioeconomic inequalities in health in 22 European countries. N.Engl.J.Med. 2008;358(23):2468-2481 doi:358/23/2468 [pii];10.1056/NEJMsa0707519.

2. Nagelhout G, de Korte D, van der Meer R, Zeegers T, van Gelder B, Willemsen M. 2011 Themapublicatie. Sociaaleconomische verschillen in roken in Nederland 1988-2010. Den Haag: STIVORO; 2011.

3. Laaksonen M, Rahkonen O, Karvonen S, Lahelma E. Socioeconomic status and smoking: analysing inequalities with multiple indicators. Eur.J.Public Health. 2005;15(3):262-269 doi:cki115 [pii];10.1093/eurpub/cki115.

4. Schaap MM, van Agt HM, Kunst AE. Identification of socioeconomic groups at increased risk for smoking in European countries: looking beyond educational level. Nicotine.Tob. Res. 2008;10(2):359-369 doi:790125799 [pii];10.1080/14622200701825098.

5. Kotz D, West R. Explaining the social gradient in smoking cessation: it’s not in the trying, but in the succeeding. Tob.Control. 2009;18(1):43-46 doi:tc.2008.025981 [pii];10.1136/ tc.2008.025981.

6. Osler M, Prescott E. Psychosocial, behavioural, and health determinants of successful 4 smoking cessation: a longitudinal study of Danish adults. Tob.Control. 1998;7(3):262-267.

7. Dorner TE, Trostl A, Womastek I, Groman E. Predictors of short-term success in smoking cessation in relation to attendance at a smoking cessation program. Nicotine.Tob.Res. 2011;13(11):1068-1075 doi:ntr179 [pii];10.1093/ntr/ntr179.

8. Hollis JF, McAfee TA, Fellows JL, Zbikowski SM, Stark M, Riedlinger K. The effectiveness and cost effectiveness of telephone counselling and the nicotine patch in a state tobacco quitline. Tob.Control. 2007;16 Suppl 1:i53-i59 doi:16/Suppl_1/i53 [pii];10.1136/ tc.2006.019794.

9. Stead LF, Lancaster T. Behavioural interventions as adjuncts to pharmacotherapy for smoking cessation. Cochrane.Database.Syst.Rev. 2012;12:CD009670 doi:10.1002/14651858.CD009670.pub2.

10. Hiscock R, Judge K, Bauld L. Social inequalities in quitting smoking: what factors mediate the relationship between socioeconomic position and smoking cessation? J.Public Health (Oxf). 2011;33(1):39-47 doi:fdq097 [pii];10.1093/pubmed/fdq097.

11. Patterson F, Jepson C, Kaufmann V, Rukstalis M, Audrain-McGovern J, Kucharski S, Lerman C. Predictors of attendance in a randomized clinical trial of nicotine replacement therapy with behavioral counseling. Drug Alcohol Depend. 2003;72(2):123-131 doi:S0376871603001947 [pii].

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12. Lee CS, Hayes RB, McQuaid EL, Borrelli B. Predictors of retention in smoking cessation treatment among Latino smokers in the Northeast United States. Health Educ.Res. 2010;25(4):687-697 doi:cyq010 [pii];10.1093/her/cyq010.

13. Nevid JS, Javier RA, Moulton JL, III. Factors predicting participant attrition in a community-based, culturally specific smoking-cessation program for Hispanic smokers. Health Psychol. 1996;15(3):226-229.

14. Lee ML, Hassali MA, Shafie AA. A qualitative exploration of the reasons for the discon- tinuation of smoking cessation treatment among Quit Smoking Clinics’ defaulters and health care providers in Malaysia. Res.Social.Adm Pharm. 2013;9(4):405-418 doi:S1551- 7411(12)00078-2 [pii];10.1016/j.sapharm.2012.05.010.

15. Allan C, Radley A, Williams B. Paying the price for an incentive: an exploratory study of smokers’ reasons for failing to complete an incentive based smoking cessation scheme. J.Health Serv.Res.Policy. 2012;17(4):212-218 doi:jhsrp.2012.011084 [pii];10.1258/ jhsrp.2012.011084.

16. Deci EL, Ryan RM. Intrinsic Motivation and Self-Determination in Human Behaviour. New York: Plenum Press; 1985.

17. Vallerand RJ, Bissonnette R. Intrinsic, Extrinsic, and Amotivational Styles as Predictors of Behaviour: A Prospective Study. J. Pers. 1992;60:3:599-620.

18. Ryan RM, Frederick CM, Lepes D, Rubio N, Sheldon KM. Intrinsic Motivation and Exercise Adherence. Int.J.Sport Psychol. 1997;28:335-354.

19. Ryan RM, Deci EL. Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemp. Educ. Psychol. 2000;25:54-67.

20. Deci EL, Ryan RM. The “What” and “Why” of Goal Pursuits: Human Needs and the Self- Determination of Behaviour. Psychol. Inq. 2000;11:4:227-268.

21. Ryan RM, Solky JA. What is Supportive about Social Support? On the Psychological Needs for Autonomy and Relatedness. In: Pierce GR, Sarason BR, Sarason IG, eds. Handbook of Social Support and the Family. New York: Plenum Press; 1996:249-267.

22. Rouse PC, Ntoumanis N, Duda JL, Jolly K, Williams GC. In the beginning: role of autonomy support on the motivation, mental health and intentions of participants entering an exercise referral scheme. Psychol.Health. 2011;26(6):729-749 doi:10.1080/08870446.201 0.492454.

23. Gemeente Den Haag. Kerncijfers van Den Haag 2013. Den Haag: Gemeente Den Haag; 2014.

24. de Weert B. Pakje Kans. Samen stoppen met roken handboek. Den Haag: STIVORO;2009.

25. van Ernst A, Weustink M. Telefonische Coaching bij Stoppen met Roken. Handleiding voor de coach. Utrecht 2008.

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26. Ritchie J, Lewis J. Qualitative Research Practice. London: SAGE Publications Ltd; 2003.

27. Thomas DR. A General Inductive Approach for Analyzing Qualitative Evaluation Data. American Journal of Evaluation. 2006;27:237-246.

28. Rosenthal L, Carroll-Scott A, Earnshaw VA, Sackey N, O’Malley SS, Santilli A, Ickovics JR. Targeting cessation: understanding barriers and motivations to quitting among urban adult daily tobacco smokers. Addict.Behav. 2013;38(3):1639-1642 doi:S0306- 4603(12)00335-8 [pii];10.1016/j.addbeh.2012.09.016.

29. Rucker-Whitaker C, Flynn KJ, Kravitz G, Eaton C, Calvin JE, Powell LH. Understanding African-American participation in a behavioral intervention: results from focus groups. Contemp.Clin.Trials. 2006;27(3):274-286 doi:S1551-7144(05)00188-6 [pii];10.1016/j. cct.2005.11.006.

30. Carson TL, Eddings KE, Krukowski RA, Love SJ, Harvey-Berino JR, West DS. Examining social influence on participation and outcomes among a network of behavioral weight- loss intervention enrollees. J.Obes. 2013;2013:480630 doi:10.1155/2013/480630.

31. Chlup DT, Collins TE. Breaking the Ice: Using Ice-breakers and Re-energizers with Adult Learners. Adult Learning. 2010;21:3-4:34-39. 4 32. Bauld L, Ferguson J, McEwen A, Hiscock R. Evaluation of a drop-in rolling- group model of support to stop smoking. Addiction. 2012;107(9):1687-1695 doi:10.1111/j.1360-0443.2012.03861.x.

33. Festinger L. A Theory of Cognitive Dissonance. Evanston, Illinois: Row, Peterson and Company; 1957.

400350-L-bw-Benson 400350-L-bw-Benson Part 2 The influence of the prevailing economic conditions and social norms on inequalities in smoking cessation

400350-L-bw-Benson 400350-L-bw-Benson Chapter 5 Socioeconomic inequalities in smoking in The Netherlands before and during the Global Financial Crisis: a repeated cross- sectional study.

Based on:

Benson FE, Kuipers MAG, Nierkens V, Bruggink JW, Stronks K, Kunst AE. Socioeconomic inequalities in smoking in The Netherlands before and during the Global Financial Crisis: a repeated cross-sectional study. BMC Public Health. 2015;15:469 doi:10.1186/s12889-015-1782-6.

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AbSTRACT background. The Global Financial Crisis (GFC) increased levels of financial strain, especially in those of low socioeconomic status (SES). Financial strain can affect smoking behaviour. This study examines socioeconomic inequalities in current smoking and smoking cessation in The Netherlands before and during the Global Financial Crisis.

Methods. Participants were 66,960 Dutch adults (≥18 years) who took part in the annual national Health Survey (2004-2011). Period was dichotomised: ‘pre-‘ and ‘during-GFC’. SES measures used were income, education and neighbourhood deprivation. Outcomes were current smoking rates (smokers/total population) and smoking cessation ratios (former smokers/ever smokers). Multilevel logistic regression models controlled for individual characteristics and tested for interaction between period and SES.

Results. In both periods, high SES respondents (in all indicators) had lower current smoking levels and higher cessation ratios than those of middle or low SES. Inequalities in current smoking increased significantly in poorly educated adults of 45-64 years of age (Odds Ratio (OR) low educational level compared with high: 2.00[1.79-2.23] compared to pre-GFC 1.67[1.50-1.86], p for interaction=0.02). Smoking cessation inequalities by income in 18-30 year olds increased with borderline significance during the GFC (OR low income compared to high income: 0.73[0.58- 0.91]) compared to pre-GFC (OR: 0.98[0.80-1.20]), p for interaction=0.051).

Conclusions. Overall, socioeconomic inequalities in current smoking and smoking cessation were unchanged during the GFC. However, current smoking inequalities by education, and smoking cessation inequalities by income, increased in specific age groups. Increased financial strain caused by the crisis may disproportionately affect smoking behaviour in some disadvantaged groups.

Keywords. Smoking, socioeconomic status, inequalities, economic recession

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INTRODUCTION In Dahlgren & Whitehead’s social model of health (Chapter 1, Figure 5), general socioeconomic conditions are one of the population-level determinants of health [1]. General socioeconomic conditions changed in many European countries after the global economy went into recession in 2008 [2,3]. This Global Financial Crisis (GFC) led to decreased public spending in many European countries [4], and to large increases in unemployment in EU member states [5]. Economic downturns, with the resulting budgetary measures and job losses disproportionately affect those of low socioeconomic status (SES) [6], putting them under increased levels of financial strain. This financial strain may impact on other aspects of their lives, such as individual lifestyle factors, including smoking behaviour.

Financial strain can affect an individual’s smoking behaviour through a mechanism described as tension reduction [7,8], which was originally developed to explain the impact of tension on alcohol use. According to this theory individuals attempt to ameliorate the effects of feeling anxiety by more frequently enacting behaviours which give temporary relief. Support for this hypothesis with regard to smoking was given by a recent longitudinal study which found that 65-74 year old male adults and those of low educational level were more likely to smoke under increased financial strain [9]. Personal financial strain also affects cessation rates; a US study, found that in Latinos, African Americans and Caucasians of predominantly low SES, smoking cessation was less likely at 26 weeks in those with higher financial strain at baseline [10].

Financial strain on a population level may also affect smoking behaviour, however, current research provides a mixed picture. One study found that during the period 1987–2000 in the US, temporary economic downturns led to a decrease in smoking [11]. In contrast, another found 5 that smoking prevalence in Italy had increased in 2009 compared with 2008 possibly due to the GFC, largely due to relapsing former smokers [12]. The effects of population-level financial strain on smoking can also differ amongst those of differing SES levels, sometimes increasing inequalities. However, the evidence for this is currently scant with no clear-cut agreement between studies. Firstly, Gallus, Ghislandi & Muttarak (2013) found that in the US population there was a decrease in current smoking in the employed and an increase in the unemployed. As a result, the overall smoking prevalence changed little, but there were changes in inequalities in smoking during this period [13]. Secondly, there were overall population reductions in smoking in Iceland as a result of the GFC [14]. However, inequalities in smoking decreased as men who had experienced a reduction in income were less likely to relapse, while those whose income had increased were more likely to do so [15].

In this study, we will use data from The Netherlands from the period 2004-2011. While the effect of the GFC on the population was more dramatic in some other European countries (e.g. Ireland and Spain) during this period [16], it was felt in The Netherlands. The Netherlands entered recession [17] during the fourth quarter of 2008 [18]. The annual unemployment rate increased from 3.1 in 2008 to 4.4 in 2011, and again to 6.7 in 2013 [19]. Also, the percentage of the total population with a decrease in purchasing power increased during the GFC, from an average of

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42% in the period 2004-2007 to 48% in the period 2008-2011 [20]. This worsened during the GFC from 42% in 2008 to 54% in 2011 [20].

The general aim of this paper was to examine inequalities in smoking in The Netherlands, before and during the GFC. The specific aim was to assess whether the pattern and magnitude of inequalities in current smoking and smoking cessation by education level, income level, and level of area deprivation changed after The Netherlands entered the GFC.

The immediate effects of the GFC were to increase male unemployment in Europe, due to segre- gation of the workforce (e.g. more men work in indicator industries such as construction) [21]. Also, there was evidence that younger, working age people were hardest hit by a downturn in employment in Europe, while their older working age colleagues suffered a less sharp rise in unemployment [22]. Such developments might increase stress particularly in these harder hit groups and could possibly lead to changes in smoking behaviour in these specific groups. Therefore, analyses were performed for subgroups of age and gender separately.

METHODS Cross-sectional data were obtained from the annual national Health Survey (HS) for the years 2004-2011. Respondents <18 years of age were excluded (n=22,175), as well as respondents with missing data on smoking (n=135), which resulted in a total study population of 66,960 individuals. The HS is a continuous cross-sectional survey of residents of private homes. It aims to give an overview of the health status, healthcare usage and preventive behaviours of the Dutch population. From 2004-2009 face-to-face interviews were conducted. In 2010-2011 respondents were asked to participate by internet. In these years non-responders were approached for telephone interviews should a phone number be available, or for face-to-face interviews if not [23]. According to the Medical Ethics Review Committee of the AMC (reference number W14_143 no. 14.170180), medical ethical approval was not required for this study because it does not fall within the scope of the Dutch Medical Research (Human Subjects) Act because the participants were not subjected to any intervention or treatment. Informed consent from participants was not required for use of the existing database for this study.

Period was dichotomised as ‘pre-GFC’ (begin 2004 – end of the third quarter 2008) and ‘during- GFC’ (fourth quarter 2008–end 2011).

Two outcome variables were used: current smoking rates defined as ‘smokers/total population’ and smoking cessation ratios defined as ‘former smokers/ever smokers’. Respondents were asked two questions: 1) ‘Do you sometimes smoke?’ (yes/no) and, amongst those answering ‘no’ 2) ‘Did you smoke cigarettes in the past?’. Smokers answered ‘yes’ to question 1. Former smokers answered ‘yes’ to question 2. Ever smokers answered yes to either question.

Three measures of SES were used: standardised disposable household income, educational level and neighbourhood deprivation. Household equivalent income was measured as net household income in euros. Income information at the level of individual respondents was

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gained from the national tax registry. Income was split into tertiles for each of the two periods, with the ‘middle’ income level for each period respectively being: pre-GFC €17,200-€24,298 and during-GFC €19,400-€27,428. Highest completed educational level was split into three levels where ‘low’ comprised no education through to lower secondary education, ‘middle’ comprised upper secondary and middle vocational education, and ‘high’ comprised higher vocational and tertiary education. Neighbourhoods were split into three categories of deprivation (‘Most- deprived’ (83 postcode areas distributed over 40 neighbourhoods), ‘Next-most-deprived’ (252 postcode areas distributed over 100 neighbourhoods), and ‘Non-deprived’ (3276 postcode areas distributed over all remaining neighbourhoods)), based on a categorisation of the Dutch government [24]. From mid-2008, the ‘most-deprived’ neighbourhoods were subject to a major urban renovation initiative [25]. When analysing each of the SES measures, we excluded individuals whose data on that specific measure were missing. Those excluded from analysis of each measure were: income (1144), education (2237) and neighbourhood deprivation (151). In the analysis of current smoking, 4807 individuals were missing, leaving a total of 62,153 individuals, and in the analysis of smoking cessation a total of 39,804 individuals (‘ever smokers’) were included in the analysis.

Some other individual characteristics were also used and were defined as follows. Age was separated into four groups: young adults (‘18–30 years’), working age (‘31-44 years’ and ‘45–64 years’), and pensioners (‘>64 years’). Ethnicity was taken from the national continuous population registry. This was separated into three groups based on the definition of Statistics Netherlands: ‘Western minorities’ (individuals without two Dutch parents, who were born in Europe (excluding Turkey), North America, Oceania, Indonesia or Japan)) [26], ‘non-Western 5 minorities’ (individuals without two Dutch parents, who were born in Africa, Latin America, Asia (excluding Indonesia or Japan) or Turkey) [27], and ‘ethnic Dutch’ (individuals with both parents born in The Netherlands, irrespective of the participant’s own country of birth) [28]. Household composition was separated into the five categories: ‘Couple, with children’; ‘Couple, without children’; ‘Single, with children’; ‘Single without children’; and, ‘Other’, for all other groups.

In the statistical analyses we applied multilevel logistic regression models containing a random intercept at the neighbourhood level. Current smoking and smoking cessation were the dependent variables. Model 1 included the following predictors: time (in years), period (pre- and during-GFC), age (in the three distinguished age groups), gender, ethnicity, and household composition. Time was included to control for secular trends in smoking. In a sensitivity analysis, in which we did not control for time, we found essentially the same results as those reported below. Model 2 also included educational level, income, and area deprivation. Associations are presented for the period before and during the GFC. Interaction between period and all covariates was tested by means of interaction terms in a model that includes all covariates. Analyses were performed for subgroups of age and gender separately and three-way interactions were tested (e.g. education level * period * gender).

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RESULTS

Respondents pre-GFC and during the GFC had similar characteristics (Table 1). The trend in the total population is towards decreasing current smoking and increasing smoking cessation (Figure 1).

Figure 1: Trends in current smoking and smoking cessation

Smoking prevalence decreased and smoking cessation increased during the GFC (Table 1). This was observed for all subgroups of gender, age, ethnicity, household composition, educational level and income. The single exception was that the quit ratio was unchanged in the Most- deprived areas.

In both periods, there are substantial inequalities in smoking according to each SES indicator. Those of high SES smoke less than those of middle SES, who in turn smoke less than those of low SES (Table 1). The pattern seen for smoking cessation is similar but in the opposite direction, with an increase in quit ratios with increasing SES (Table 1). Smoking prevalence is also seen to decrease and smoking cessation to increase with increasing age (Table 1).

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Table 1: Descriptive information, smoking prevalence and quit ratio for the study population Pre- and During-GFC.

Descriptive information Smoking prevalence Smoking cessation

Pre-GFC During-GFC Pre-GFC During-GFC Pre-GFC During-GFC N 34,981 31,979 Age (mean, SD) 48.0 ± 17.4 48.9 ± 17.5 % of respondents Total population - - 29.9 26.5 53.5 59.5 Gender Male 48.3 48.5 33.8 29.8 52.1 58.8 Female 51.7 51.5 26.3 23.5 55.0 60.4 Age 18 – 30 years of age 18.1 18.0 36.1 33.6 32.4 38.6 31 – 44 years of age 26.7 24.0 32.9 29.3 43.7 49.6 45 – 64 years of age 35.9 37.6 30.9 27.8 57.9 62.2 >64 years of age 19.2 20.4 18.0 14.8 72.5 79.4 Ethnicity Ethnic Dutch 85.7 89.5 29.4 26.4 54.8 60.4 Western Minorities 8.2 7.3 33.8 26.8 49.9 60.9 Non-Western Minorities 6.1 3.2 32.1 27.9 34.8 43.1 Household composition Couple, with children 41.6 38.8 29.7 26.3 50.7 55.9 5 Couple, no children 35.1 36.3 26.3 22.5 62.3 69.0 Single, with children 17.2 18.3 33.7 30.6 45.9 53.0 Single, no children 4.9 4.7 41.8 38.9 35.5 41.0 Other 1.3 1.9 37.9 37.7 38.5 40.6 Education level High 23.0 27.5 22.0 19.1 62.4 68.3 Middle 37.2 32.6 31.0 28.3 51.8 57.0 Low 39.8 39.9 33.4 30.2 50.5 57.2 Household income High 33.3 33.3 25.2 21.7 60.4 66.0 Middle 33.4 33.4 30.4 27.5 53.5 57.8 Low 33.3 33.3 33.4 30.4 49.7 52.8 Neighbourhood deprivation Non-deprived 86.8 87.5 29.4 25.8 54.3 60.6 Next-most-deprived (100 areas) 9.4 8.9 33.0 30.7 49.2 54.9 Most-deprived (40 areas) 3.8 3.5 34.5 34.1 45.9 45.9

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Regression based estimates of associations of current smoking and smoking cessation with covariates are shown in Table 2. In model 2, strong independent associations are observed for all socio-demographic variables, including the three socioeconomic variables. Differences according to educational level are larger than those according to income and area deprivation. There is an association with the GFC (current smoking (Odds Ratio (OR): 0.96 [0.89-1.03]) and smoking cessation (OR: 1.08 [1.0-1.18])) which persists after controlling for all covariates (OR[95%CI]:current smoking (0.97 [0.90-1.04]) and smoking cessation (OR: 1.08 [0.99-1.18])), though without statistical significance. Current smoking decreases in a graduated manner as age group increases. Smoking cessation increases in a graduated manner as age group increases, with those of >64 years of age having quit ratios significantly larger than those of 31-33 or 45-64 years of age (OR[95%CI]: >64 (7.17[6.60-7.80])) compared with 31-44 (1.53[1.43-1.65]) and 45-64 (2.66[2.49-2.85])).

In Table 3 we examined the association between covariates and smoking outcomes before and during the GFC. In most cases, associations of socio-demographic variables with smoking outcomes remained similar. One exception is that male-female differences in smoking cessation significantly declined during the GFC (ORs decreased from 1.32 to 1.18, p-value for the interaction=0.009). Smoking prevalence in western minorities compared with the ethnic Dutch significantly decreased and smoking cessation significantly increased during the GFC compared with pre-GFC (OR[95%CI]: smoking prevalence: 1.17[1.08-1.28] to 0.99[0.89-1.10] and smoking cessation: 0.85[0.76-0.94] to 1.10[0.98-1.24]). Patterns of inequalities tended to increase between the two time periods, especially between Non-deprived and the Most-deprived neighbourhoods, though without statistical significance.

In Table 4 we examine changes in the association between SES variables and smoking outcomes respectively for adults in four age groups. Overall, in income and education, inequalities in smoking were stable or tended to increase between periods. Changes in smoking inequalities as a result of the GFC were very similar in all age groups. This was confirmed by three-way interaction tests (e.g. education level*period*age), in which we found that none of the interactions were statistically significant. Among respondents aged 18-30 years, income-related inequalities in smoking cessation were borderline significantly larger during the GFC than pre-GFC (OR[95%CI]:18-30 years pre-GFC:0.98[0.80-1.20] and during-GFC:0.73[0.58-0.91], p=0.051). In those of 45-64 years of age, those of low income had significantly less decrease in current smoking during the GFC compared with pre-GFC (OR[95%CI]: pre-GFC 1.67[1.50-1.86] and during GFC: 2.00[1.79-2.23] p=0.02).

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Table 2: Association between covariates and current smoking and smoking cessation in a multilevel logistic regression model.

Current smoking Smoking cessation

Model 1 Model 2 Model 1 Model 2 Time (in years) 0.97 [0.96-0.98] 0.97 [0.96-0.99] 1.04 [1.02-1.06] 1.04 [1.02-1.06] Time period Pre-GFC 1.00 1.00 1.00 1.00 During-GFC 0.96 [0.89-1.03] 0.97 [0.90-1.04] 1.08 [1.00-1.18] 1.08 [0.99-1.18] Age 18 – 30 years of age 1.00 1.00 1.00 1.00 31 – 44 years of age 0.90 [0.86-0.95] 0.89 [0.85-0.94] 1.50 [1.40-1.60] 1.53 [1.43-1.65] 45 – 64 years of age 0.80 [0.76-0.84] 0.75 [0.71-0.79] 2.54 [2.39-2.70] 2.66 [2.49-2.85] >64 years of age 0.34 [0.32-0.37] 0.26 [0.24-0.28] 5.89 [5.45-6.37] 7.17 [6.60-7.80] Gender Male 1.00 1.00 1.00 1.00 Female 0.70 [0.68-0.73] 0.66 [0.64-0.69] 1.21 [1.16-1.26] 1.26 [1.20-1.31] Ethnicity Ethnic Dutch 1.00 1.00 1.00 1.00 Western minorities 1.12 [1.05-1.20] 1.10 [1.02-1.17] 0.92 [0.86-1.00] 0.94 [0.87-1.02] Non-western minorities 0.88 [0.81-0.95] 0.70 [0.64-0.77] 0.69 [0.62-0.77] 0.82 [0.72-0.92] Household composition 5 Couple, with children 1.00 1.00 1.00 1.00 Couple, no children 1.11 [1.06-1.16] 1.15 [1.10-1.21] 1.03 [0.98-1.09] 1.01 [0.96-1.06] Single, with children 1.68 [1.60-1.77] 1.66 [1.57-1.75] 0.55 [0.51-0.58] 0.56 [0.53-0.60] Single, no children 1.93 [1.79-2.10] 1.80 [1.65-1.95] 0.50 [0.46-0.56] 0.54 [0.49-0.60] Other 1.63 [1.42-1.86] 1.61 [1.38-1.87] 0.61 [0.51-0.73] 0.59 [0.49-0.72] Education level High 1.00 1.00 Middle 1.57 [1.49-1.65] 0.70 [0.66-0.74] Low 2.14 [2.04-2.26] 0.52 [0.49-0.55] Household income High 1.00 1.00 Middle 1.19 [1.14-1.25] 0.86 [0.82-0.91] Low 1.34 [1.27-1.40] 0.76 [0.72-0.81] Neighbourhood deprivation Non-deprived 1.00 1.00 Next-most-deprived 1.22 [1.15-1.31] 0.86 [0.80-0.93] Most-deprived 1.26 [1.13-1.40] 0.84 [0.74-0.95]

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400350-L-bw-Benson Part 2 a 0.978 0.417 0.562 0.937 0.484 0.001 0.009 0.336 0.068 0.209 0.001 p-value for p-value for interaction 0.59 [0.46-0.77] 0.53 [0.46-0.62] 0.61 [0.55-0.67] 1.07 [0.99-1.15] 0.86 [0.70-1.06] 1.00 1.10 [0.98-1.24] 1.18 [1.11-1.26] 1.00 7.49 [6.64-8.44] 1.00 2.49 [2.25-2.75] 1.46 [1.31-1.62] 1.09 [1.05-1.13] 1.00 During-GFC 0.60 [0.45-0.80] 0.55 [0.47-0.63] 0.52 [0.48-0.57] 0.97 [0.90-1.03] 1.00 0.79 [0.68-0.92] 0.85 [0.76-0.94] 1.00 1.32 [1.25-1.40] 1.00 6.94 [6.23-7.73] 2.81 [2.57-3.08] 1.60 [1.45-1.76] 1.00 1.02 [1.00-1.04] Pre-GFC Smoking cessation a 0.741 0.255 0.290 0.479 0.957 0.014 0.090 0.085 0.688 0.817 0.934 p-value for p-value for interaction 1.68 [1.37-2.06] 1.85 [1.63-2.10] 1.60 [1.48-1.73] 1.00 1.12 [1.05-1.20] 0.70 [0.60-0.82] 1.00 0.99 [0.89-1.10] 1.00 0.69 [0.65-0.73] 0.25 [0.22-0.27] 0.74 [0.69-0.80] 1.00 0.89 [0.81-0.97] 0.97 [0.89-1.05] During-GFC 1.51 [1.21-1.89] 1.76 [1.57-1.96] 1.71 [1.59-1.84] 1.00 1.18 [1.11-1.25] 0.70 [0.63-0.78] 1.00 1.17 [1.08-1.28] 1.00 0.65 [0.62-0.68] 0.27 [0.25-0.30] 0.76 [0.71-0.81] 1.00 0.90 [0.84-0.97] 0.97 [0.96-0.99] Current smoking Current Pre-GFC Association between covariates and current smoking pre- and current and smoking and during-GFC. cessation Association between covariates Other Single, no children Single, Single, with children Single, Household composition Household with children Couple, no children Couple, Non-western minorities Non-western Ethnicity Dutch Ethnic minorities Western Gender Male Female >64 years of age >64 years 45 – 64 years of age 45 – 64 years Age of age 18 – 30 years of age 31 – 44 years Time (in years) Time Table 3: Table

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400350-L-bw-Benson Chapter 5 a 0.230 0.935 0.246 0.383 0.174 0.449 0.252 0.347 0.535 p-value for p-value for interaction 0.77 [0.64-0.93] 0.86 [0.77-0.97] 0.73 [0.68-0.80] 1.00 0.83 [0.77-0.90] 0.51 [0.47-0.55] 1.00 0.68 [0.62-0.74] 1.00 During-GFC 0.89 [0.76-1.04] 0.86 [0.78-0.94] 1.00 0.78 [0.73-0.84] 0.89 [0.83-0.96] 1.00 0.53 [0.49-0.58] 0.72 [0.66-0.78] 1.00 Pre-GFC Smoking cessation a 0.316 0.210 0.414 0.897 0.939 0.254 0.305 0.351 0.354 p-value for p-value for interaction 5 1.33 [1.14-1.55] 1.00 1.26 [1.14-1.39] 1.34 [1.25-1.44] 1.00 1.23 [1.15-1.32] 2.20 [2.05-2.37] 1.00 1.61 [1.49-1.74] During-GFC 1.21 [1.06-1.38] 1.00 1.20 [1.10-1.30] 1.34 [1.25-1.42] 1.00 1.17 [1.10-1.24] 2.09 [1.95-2.24] 1.00 1.54 [1.44-1.64] Current smoking Current Pre-GFC Most-deprived Neighbourhood deprivation Non-deprived Next-most-deprived Low Household income Household High Middle Low Education level Education High Middle The p-value at the same row as the variable name refers to the test on the overall interaction between period and this variable (measured on a period between interaction and this variable (measured on the overall the test to as the variable name refers p-value the same row at The a scale) continuous

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400350-L-bw-Benson Part 2 a 0.945 0.051 0.418 0.892 0.823 0.611 0.457 0.789 Ref Ref Ref Ref 0.939 0.047 0.289 0.890 p interaction 0.33 [0.25-0.43] 0.73 [0.58-0.91] 0.95 [0.59-1.51] 0.43 [0.36-0.52] 0.63 [0.51-0.78] 0.99 [0.80-1.24] 1.08 [0.81-1.44] 0.60 [0.52-0.71] 1.00 1.00 1.00 1.00 During-GFC Smoking cessation 0.33 [0.26-0.43] 0.98 [0.80-1.20] 0.72 [0.44-1.18] 0.43 [0.36-0.50] 0.61 [0.49-0.75] 0.92 [0.76-1.12] 0.92 [0.68-1.25] 0.62 [0.54-0.72] 1.00 1.00 1.00 1.00 Pre-GFC a 0.371 0.542 0.917 0.950 0.843 0.474 0.196 0.654 0.341 Ref 0.558 Ref 0.428 Ref 0.931 Ref p interaction 3.57 [2.94-4.32] 1.33 [0.96-1.30] 1.08 [0.78-1.49] 2.82 [2.44-3.27] 1.93 [1.63-2.28] 1.18 [1.00-1.39] 1.02 [0.82-1.26] 1.80 [0.58-2.06] 1.00 1.00 1.00 1.00 During-GFC 3.18 [2.67-3.79] 1.24 [1.08-1.44] 1.10 [0.82-1.49] 2.84 [2.49-3.24] 1.88 [1.61-2.21] 1.09 [0.95-1.25] 1.24 [1.00-1.53] 1.73 [1.54-1.95] 1.00 1.00 1.00 1.00 Current smoking Current Pre-GFC Pre- and during-GFC associations between SES variables and current smoking and smoking cessation by age-group*. and during-GFC smoking by Pre- and current and smoking associationscessation between SES variables Low Low Most-deprived Low Middle Middle Next-most-deprived Middle High High Non-deprived High 18 – 30 years of age 18 – 30 years level Education Household income Neighbourhood deprivation of age 31 – 44 years level Education Table 4: Table

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400350-L-bw-Benson Chapter 5 a 0.513 0.450 0.095 0.562 0.573 0.867 0.661 0.324 0.145 0.638 Ref Ref Ref Ref Ref 0.481 0.400 0.099 0.466 0.474 p interaction 0.77 [0.65-0.85] 0.82 [0.58-1.16] 0.56 [0.50-0.64] 0.64 [0.57-0.72] 0.71 [0.53-0.95] 0.85 [0.72-1.00] 0.71 [0.57-0.89] 0.73 [0.64-0.83] 0.75 [0.67-0.84] 0.79 [0.66-0.94] 1.00 1.00 1.00 1.00 1.00 During-GFC Smoking cessation 0.72 [0.62-0.84] 0.97 [0.75-1.24] 0.65 [0.58-0.73] 0.67 [0.60-0.75] 0.80 [0.61-1.04] 0.86 [0.74-1.00] 0.76 [0.64-0.91] 0.80 [0.71-0.90] 0.84 [0.76-0.93] 0.83 [0.71-0.97] 1.00 1.00 1.00 1.00 1.00 Pre-GFC a 0.157 0.491 0.020 0.557 0.650 0.468 0.267 0.310 0.184 0.291 0.156 Ref 0.246 Ref 0.017 Ref 0.487 Ref 0.322 Ref p interaction 5 1.39 [1.21-1.53] 1.41 [1.06-1.87] 2.00 [1.79-2.23] 1.50 [1.34-1.67] 1.43 [1.10-1.84] 1.24 [1.08-1.43] 1.48 [1.23-1.78] 1.46 [1.30-1.65] 1.32 [1.19-1.46] 1.34 [1.15-1.57] 1.00 1.00 1.00 1.00 1.00 During-GFC 1.59 [1.40-1.80] 1.25 [1.02-1.53] 1.67 [1.50-1.86] 1.43 [1.29-1.59] 1.32 [1.04-1.67] 1.33 [1.18-1.50] 1.30 [1.12-1.49] 1.34 [1.20-1.50] 1.20 [1.10-1.32] 1.20 [1.04-1.38] 1.00 1.00 1.00 1.00 1.00 Current smoking Current Pre-GFC 45 – 64 years of age 45 – 64 years Low Most-deprived Low Low Most-deprived Middle Next-most-deprived Middle Middle Next-most-deprived High Non-deprived High High Non-deprived Household income Neighbourhood deprivation level Education Household income Neighbourhood deprivation

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400350-L-bw-Benson Part 2 a 0.933 0.068 0.838 0.160 0.949 Ref Ref Ref 0.829 0.086 0.168 p interaction 0.066 0.77 [0.60-0.98] 0.66 [0.43-1.00] 0.85 [0.65-1.13] 0.74 [0.59-0.79] 1.08 [0.82-1.43] 1.00 1.00 1.00 During-GFC 0.63 [0.50-0.79] Smoking cessation 0.76 [0.61-0.95] 1.10 [0.75-1.59] 0.89 [0.70-1.12] 0.92 [0.75-1.12] 1.07 [0.85-1.36] 1.00 1.00 1.00 Pre-GFC 0.81 [0.67-0.99] a 0.673 0.151 0.622 0.626 0.447 0.771 Ref 0.445 Ref 0.120 Ref p interaction 0.434 1.19 [0.95-1.48] 1.44 [0.97-2.12] 1.14 [0.89-1.46] 1.20 [0.97-1.47] 1.13 [0.88-1.45] 1.00 1.00 1.00 During-GFC 1.33 [1.09-1.62] 1.26 [1.02-1.56] 0.99 [0.70-1.40] 1.24 [0.99-1.56] 1.12 [0.92-1.35] 0.99 [0.80-1.24] 1.00 1.00 1.00 Current smoking Current Pre-GFC 1.20 [1.00-1.44] Continued Low Most-deprived Middle Middle Next most deprived High High Non-deprived >64 years of age >64 years level Education Household income Low Neighbourhood deprivation p-values in the same row as the variable name refer to the test on the overall interaction between period and this variable (measured on a continuous scale) on a continuous period between interaction and this variable (measured on the overall the test to as the variable name refer p-values in the same row * Controlled for time (in years), gender, ethnicity and household composition. gender, time (in years), for * Controlled Table 4: Table a

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400350-L-bw-Benson Chapter 5 a 0.534 0.440 0.606 0.923 0.392 0.930 0.351 0.865 Ref Ref Ref Ref 0.601 0.445 0.344 0.955 p-value for p-value for interaction 0.78 [0.72-0.85] 0.76 [0.68-0.85] 0.80 [0.63-1.02] 0.47 [0.41-0.53] 0.70 [0.63-0.79] 0.91 [0.81-1.01] 0.78 [0.67-0.91] 0.66 [0.58-0.75] 1.00 1.00 1.00 1.00 During-GFC Smoking cessation 0.60 [0.54-0.67] 0.80 [0.72-0.89] 0.88 [0.70-1.10] 0.47 [0.42-0.53] 0.75 [0.68-0.84] 0.90 [0.82-0.99] 0.86 [0.75-0.99] 0.67 [0.59-0.75] 1.00 1.00 1.00 1.00 Pre-GFC a 0.727 0.718 0.824 0.386 0.177 0.993 0.097 0.941 0.914 Ref 0.719 Ref 0.258 Ref 0.277 Ref p-value for p-value for interaction 5 2.05 [1.85-2.26] 1.29 [1.17-1.43] 1.20 [0.97-1.47] 2.45 [2.19-2.74] 1.59 [1.44-1.75] 1.16 [1.05-1.27] 1.29 [1.13-1.47] 1.66 [1.48-1.86] 1.00 1.00 1.00 1.00 During-GFC 2.00 [1.83-2.20] 1.32 [1.21-1.44] 1.16 [0.97-1.40] 2.30 [2.07-2.55] 1.46 [1.33-1.59] 1.16 [1.06-1.26] 1.11 [0.99-1.25] 1.67 [1.50-1.85] 1.00 1.00 1.00 1.00 Current smoking Current Pre-GFC Pre- and during-GFC associations between SES variables and current smoking and smoking cessation by gender*. and during-GFC smoking by Pre- and current and smoking associationscessation between SES variables Low Low Most-deprived Low Middle Middle Next-most-deprived Middle High High Non-deprived High Males level Education Household income Neighbourhood deprivation Females level Education Table 5: Table

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400350-L-bw-Benson Part 2 a 0.227 0.221 Ref 0.860 0.465 0.058 Ref 0.526 p-value for p-value for interaction 0.72 [0.55-0.94] 0.95 [0.81-1.12] 1.00 0.69 [0.61-0.78] 0.74 [0.66-0.83] 1.00 During-GFC Smoking cessation 0.81 [0.58-1.14] 1.14 [0.93-1.40] 1.00 0.73 [0.66-0.81] 0.86 [0.77-0.95] 1.00 Pre-GFC a 0.159 0.565 0.450 Ref 0.583 0.092 0.694 Ref p-value for p-value for interaction 1.53 [1.22-1.91] 1.23 [1.07-1.42] 1.00 1.37 [1.24-1.52] 1.31 [1.18-1.45] 1.00 During-GFC 1.25 [1.04-1.50] 1.30 [1.15-1.46] 1.00 1.32 [1.21-1.45] 1.17 [1.07-1.28] 1.00 Current smoking Current Pre-GFC e Continued Most-deprived Next-most-deprived Non-deprived Household incom Neighbourhood deprivation Low Middle High p-values in the same row as the variable name refer to the test on the overall interaction between period and this variable (measured on a continuous scale) on a continuous period between interaction and this variable (measured on the overall the test to as the variable name refer p-values in the same row * Controlled for time (in years), age, ethnicity and household composition. age, time (in years), for * Controlled Table 5: Table a

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In Table 5 we examined changes in the association between SES variables and smoking outcomes for males and females. Changes in smoking inequalities as a result of the GFC were very similar for males and females. This was confirmed by three-way interaction tests (e.g. education level*period*age), in which we found that none of the interactions were statistically significant. However, we observed that in females there was a tendency, although not statistically significant, towards widening inequalities in current smoking and smoking cessation in Most-deprived compared with Non-deprived areas. This non-significant trend was also observed in smoking cessation in males during the GFC.

DISCUSSION Inequalities in current smoking and smoking cessation were found both before and during the GFC. We cannot demonstrate a significant increase in inequalities overall, however, there was a general tendency to increasing inequalities during the GFC compared with pre-GFC. Especially in the 18-30 age group, we found evidence of almost significant widening poor-rich inequalities in smoking cessation, and in the 45-64 age group we found a significant widening in educational inequalities in current smoking.

The observed trends may not only be influenced by the GFC, but also by other factors such as tobacco control policies. Two new national smoking policies were introduced in The Netherlands during our study period in the ‘during-GFC’ period. Hospitality industry smoke-free workplace legislation, introduced in July 2008 [29], increased the number of successful quit attempts [30]. Free pharmacotherapy for individuals undertaking smoking cessation behavioural support, introduced in 2011, was followed by a minor (1%) decrease in smoking prevalence and a 5 modest increase in the number of successful quit attempts [31,32]. In both cases socioeconomic inequalities remained unchanged [30,33], so these policies are unlikely to have been responsible for effects found in this study.

The HS dataset is based on a continuous cross-sectional survey. Survey methods were changed to ‘mixed-mode’ in 2010, at the time of our ’during-GFC’ period. However, a Statistics Netherlands report indicated that for smoking amongst other variables, the mode effects were generally not significant [23].

The quit ratio, as used in this study, did not measure when former smokers quit, since this was not asked in the survey. The quit ratio therefore captures all former smokers, including those who have quit before the studied period and remained non-smokers since. We studied changes in the quit ratio between the two periods, within the same source population. The increase found in cessation between the two periods indicates that an additional number of people have quit smoking during the crisis. Under the assumption that the study population in both periods reflect the source population, the quit ratio was able to detect changes in smoking cessation over the two periods, but was not sensitive to the exact timing of the occurrence of change.

For many years, smoking prevalence in The Netherlands has been decreasing [34,35]. This seems to have continued during the GFC [34,35]. Such trends may have concealed an upward effect

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of the GFC on smoking. Furthermore, it is possible that changes in trends in the two periods might be missed by looking only at the overall prevalence in each period. However, our explorative analysis of trends within each period (Figure 1) found no evidence for an upward trend in smoking during the GFC.

For current smoking, our findings are similar to those found in the US [13], where the population prevalence also changed little after the onset of the GFC. In that study no change in inequalities by education were seen [13]. We, also, didn’t observe such an increase in the overall population, however, we observed an increase in inequalities for the age group 45-64 years.

McClure et al. (2012) found an effect of the GFC on smoking behaviour in Iceland, where men whose income was reduced over the period 2007-2009 were significantly less likely to relapse than men whose income increased during the same period [15]. This contrasts with our results, where inequalities according to income seemed to have increased for younger adults.

There were no significant changes in overall inequalities according to area deprivation, income or education in current smoking or in smoking cessation. Good social protection has been shown to mitigate some effects of economic crises on health [4,36,37]. As The Netherlands is one of the European countries spending most on social protections per inhabitant [38], it is possible that this may have buffered any effects of increased financial strain on smoking behaviour in the Dutch population.

We observed that current smoking amongst poorly educated 45-64 year olds decreased to a lesser extent during the GFC than amongst highly educated 45-64 year olds. Older workers and those of low educational level feel more job insecurity than younger and better educated workers respectively, regardless of levels of social protection available [39]. Self-perceived job insecurity increases psychological morbidity [40] and ill health [39]. Also, workers of this age group in The Netherlands may be considered by many Dutch employers to be too expensive due to higher pension contributions, absenteeism insurance and health care costs [41]. It is possible that this self-perceived vulnerability, with its effects on general stress among poorly educated adults, increased during the GFC. In line with the tension reduction mechanism [7,8], this might lead to increased current smoking amongst this group.

Among young adults, we found evidence to suggest that smoking cessation rates of those with low income increased to a lesser extent during the GFC than among their high income peers. While the percentage of young people (15 – 25 years of age) searching for a job in The Netherlands did not change greatly during the period studied [42], this may have occurred because young people’s response to the GFC may have been to remain in education or give up the search altogether [43]. The prospect of poor employment opportunities, particularly in individuals of low SES where job prospects were already more limited, might increase feelings of anxiety and lack of control. Even if employed, those in poorly-paid jobs feel more self-perceived job insecurity than those in better-paid jobs [39]. Increased anxiety during the GFC might have decreased the success of quit attempts [10].

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Differences in smoking prevalence and cessation rates between Most-deprived and Non-deprived areas tended to widen during the GFC compared with pre-GFC. This tendency was particularly found in those of >30 years and in women, although no statistical differences by age were found. This widening happened despite the 40 Most-deprived areas undergoing a major urban regeneration project from 2008 onwards [25]. One possible explanation for this widening is that residents of the Most-deprived areas experienced a greater increase in anxiety and financial strain, and this influenced their smoking behaviour. A qualitative study on a deprived area in Ireland found that the GFC had a substantial effect on family and community life, which were affected by anxiety due to fear of poverty [44]. It is possible that a similar but less pronounced effects occurred in the Most-deprived areas of The Netherlands.

The effects of the GFC on inequalities in current smoking and smoking cessation are generally small. One possible explanation is that part of these effects will need more time to develop. For example, though the Netherlands went into recession during the fourth quarter of 2008, government budget cuts only started to be felt by Dutch society in 2012 [45] and only since then has there been a decrease in the purchasing power of most Dutch households, an increase in the number of unemployed and people receiving social benefit, and an increase in the number of those living in poverty [46]. This delay is reflected in our data, where income did not decrease between the periods at large. Future studies should assess the long term effects of population- level financial strain on smoking trends and inequalities in The Netherlands.

CONCLUSION While inequalities in current smoking and smoking cessation were generally stable, education- 5 related inequalities in current smoking in 45-64 year old adults and income-related inequalities in smoking cessation in younger adults increased during the GFC compared with pre-GFC. This suggests that increased financial strain caused by the crisis may disproportionately affect smoking behaviour in some specific disadvantaged groups.

ACKNOWLEDGEMENTS The authors are grateful to Statistics Netherlands for preparing and providing access to the HS data used in this article.

FUNDING This study received funding from three projects. The SOPHIE project received funding from European Community’s Seventh Framework Program (FP7) under grant agreement number 278173. The URBAN40 and the ‘Stoppen met Roken’ projects received funding from The Netherlands Organisation for Health Research and Development (ZonMw) under the grant agreement numbers 121010009 and 200120004 respectively. Funders had no decision-making role in this study.

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COMPETING INTERESTS The authors declare no conflicts of interest.

AUTHOR CONTRIbUTIONS AK, KS and FB conceived the study. AK and MK designed the study. MK prepared and analysed the data. All authors contributed to the interpretation of the data. FB drafted the article. All authors contributed to critical revision of the manuscript.

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14. Asgiersdottir TL, Corman H, Noonan K, Olafsdottir P, Reichman NE. Are Recessions Good For Your Health Behaviours? Impacts of the Economic Crisis in Iceland. Cambridge, Massacheusetts;2012.

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21. European Commission. The impact of the economic crisis on the situation of women and men and on gender equality policies. Synthesis Report. Belgium: European Union (EU);2013.

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25. Droomers M, Harting J, Jongeneel-Grimen B, Rutten L, van KJ, Stronks K. Area-based interventions to ameliorate deprived Dutch neighborhoods in practice: does the Dutch District Approach address the social determinants of health to such an extent that future health impacts may be expected? Prev.Med. 2014;61:122-127 doi:S0091-7435(14)00026-7 [pii];10.1016/j.ypmed.2014.01.009.

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27. Statistics Netherlands (CBS). Begrippen: Niet-Westerse Allochtoon. 2014; http://www. cbs.nl/nl-NL/menu/methoden/begrippen/default.htm?ConceptID=1013 Accessed 7/14/2014.

28. Statistics Netherlands (CBS). Begrippen: Autochtoon. 2014; http://www.cbs.nl/nl-NL/ menu/methoden/begrippen/default.htm?ConceptID=88 Accessed 7/14/2014.

29. Verdonk-Kleinjan WM, Rijswijk PC, de VH, Knibbe RA. Compliance with the workplace-smoking ban in the Netherlands. Health Policy. 2013;109(2):200-206 doi:S0168- 8510(12)00315-6 [pii];10.1016/j.healthpol.2012.11.006.

30. Nagelhout GE, Willemsen MC, de Vries H. The population impact of smoke-free workplace and hospitality industry legislation on smoking behaviour. Findings from a national population survey. Addiction. 2011;106(4):816-823 doi:10.1111/j.1360-0443.2010.03247.x.

31. STIVORO. Kerncijfers Roken in Nederland 2011. Een overzicht van recente Nederlandse basis- gegevens over rookgedrag. Den Haag: STIVORO;2012.

32. STIVORO. Kerncijfers roken in Nederland 2010. Een overzicht van recente Nederlandse basis- gegevens over rookgedrag. Den Haag: STIVORO;2011.

33. Nagelhout GE, Hummel K, Willemsen MC, Siahpush M, Kunst AE, de VH, Fong GT, van den Putte B. Are there income differences in the impact of a national reimbursement policy for smoking cessation treatment and accompanying media attention? Findings from the International Tobacco Control (ITC) Netherlands Survey. Drug Alcohol Depend. 2014;140:183-190 doi:S0376-8716(14)00838-2 [pii];10.1016/j.drugalcdep.2014.04.012. 5 34. Statistics Netherlands (CBS). Gezondheid, leefstijl, zorggebruik; t/m 2009. 2010; http:// statline.cbs.nl/StatWeb/publication/?VW=T&DM=SLNL&PA=03799&D1=202-206,210- 214&D2=0-7&D3=0&D4=1,4-8&HD=140913-1315&HDR=G2,T&STB=G1,G3 Accessed 29/9/14.

35. Statistics Netherlands (CBS). Leefstijl, preventief onderzoek; persoonskenmerken. 2014; http://statline.cbs.nl/StatWeb/publication/?DM=SLNL&PA=81177NED&D1=0,3,42- 43&D2=0-2&D3=0&D4=a&HDR=T&STB=G1,G2,G3&VW=T Accessed 29/9/14.

36. Karanikolos M, Mladovsky P, Cylus J, Thomson S, Basu S, Stuckler D, Mackenbach JP, McKee M. Financial crisis, austerity, and health in Europe. Lancet. 2013;381(9874):1323- 1331 doi:S0140-6736(13)60102-6 [pii];10.1016/S0140-6736(13)60102-6.

37. Suhrcke M, Stuckler D. Will the recession be bad for our health? It depends. Soc.Sci.Med. 2012;74(5):647-653 doi:S0277-9536(11)00707-6 [pii];10.1016/j.socscimed.2011.12.011.

38. Eurostat. Total Social Protection Expendature in European Countries in Purchasing Power Standard per Inhabitant. 2014; http://appsso.eurostat.ec.europa.eu/nui/ submitViewTableAction.dp Accessed 29/9/14.

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39. Erlinghagen M. Self-percieved job insecurity and social context: a multi-level analysis of 17 European countries. European Sociological Reivew. 2008;24(2):183-197.

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43. International Labour Office (ILO). Global Employment Trends for Youth 2012. Geneva: International Labour Office (ILO);2012.

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400350-L-bw-Benson 400350-L-bw-Benson Chapter 6 Inequalities in the impact of national reimbursement of smoking cessation pharmacotherapy and the influence of injunctive norms. An explorative study.

Fiona E. Benson, Gera E. Nagelhout, Vera Nierkens, Marc C. Willemsen, Karien Stronks

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AbSTRACT background. In 2011, the Dutch government reimbursed pharmacotherapy with smoking cessation behavioural support for smokers who wanted to quit smoking. Previous research indicated that this did not result in a reduction in inequalities in use of pharmacotherapy during quit attempts. We will investigate whether this is due to a relatively positive injunctive norm in lower socioeconomic status (SES) groups.

Methods. Of the 75,415 participants of ≥15 years (Dutch Continuous Survey of Smoking Habits, 2009- 2012), 46,260 were current/former smokers and 29154 were non-smokers. SES was defined by education and income. Injunctive norm was determined by perceived social acceptability of smoking in the vicinity of others in Dutch society. We compared proportion of quit attempts using pharmacotherapy in two periods: 2011 (reimbursement), and all other years (no reimbursement). We examined the proportion of current and non-smokers with a mostly acceptable, neutral or mostly unacceptable injunctive norm, stratified by SES level. Multivariate logistic regression analysis tested whether period or injunctive norm predicted a quit attempt using pharma during the study period.

Results. There was no significant difference in the proportion of low SES smokers making quit attempts with pharmacotherapy compared with their middle and high SES peers, in either period. A significantly smaller proportion of low SES smokers had a mostly unacceptable injunctive norm toward smoking than high SES smokers or non-smokers of all SES levels, excepting low income smokers in all other years. Low income with a mostly acceptable injunctive norm were significantly less likely to make a quit attempt using pharmacotherapy, than those with a ‘mostly unacceptable’ injunctive norm, regardless of year.

Conclusion. In the Netherlands, reimbursement of pharmacotherapy did not increase the proportion of low SES smokers that attempted to quit using this therapy to a greater extent than the proportion of high SES smokers. A smaller proportion of smokers in low SES groups found smoking, in general, unacceptable as compared to high SES smokers, and non-smokers of all SES levels. The significantly lower use of pharmacotherapy in quit attempts in low income smokers with a positive injunctive norm toward smoking, may partly underlie the lack of uptake of reimbursed pharmacotherapy in low SES smokers.

Keywords:. Socioeconomic factors, smoking cessation, reimbursement, health policy

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INTRODUCTION Smoking is a major contributor to inequalities in health in Western Europe, with people of low socioeconomic status (SES) more likely to smoke [1]. Inequalities are also seen in making quit attempts [2,3] and successfully quitting [4,5]. Quit attempts are more successful if proven effective methods are used [6], one of which is smoking cessation behavioural therapy in combination with pharmacotherapy [7]. In 2011, Reimbursed pharmacotherapy, in combination with behavioural therapy, was introduced in the Netherlands as part of the basic health insurance package. Prior to this, pharmacotherapy was available over the counter, (e.g. nicotine replacement therapy), or by prescription, (e.g. bupropion), and was reimbursed in some supplementary health insurance packages. At the start of 2011, the Dutch government introduced this reimbursement of pharmacotherapy, which included nicotine replacement therapy (NRT), varenicline (Champix), bupropion (Zyban) and nortriptyline. At the end of 2011, after one year, reimbursement was removed with a reversion to the situation prior to 2011.

There were early indications that this reimbursement policy had been successful in increasing number of quit attempts using pharmacotherapy. The number of prescriptions written by general practitioners (GPs) and the number of dispensed prescriptions of pharmacotherapy was higher in 2011 than prior to the subsidy, or than in 2012 after the reimbursement was removed [8]. However, Nagelhout et al (2014) looked at the effects of this legislation in a longitudinal study, and found that the implementation of the reimbursement policy was followed by an increase in smoking cessation, but use of reimbursed pharmaceuticals had not increased or decreased inequalities in the use of pharmacotherapy [9].

As the cost of pharmacotherapy may hinder its uptake in lower socioeconomic groups in particular [10], it seems reasonable to expect that reimbursement policies promote quit attempts using pharmacotherapy in lower socioeconomic groups [11], and that this might occur more than in higher socioeconomic groups, where price would have been less of a barrier prior to reimbursement. We hypothesize that the fact that this has not been found in the Dutch case, 6 might be due to differences in injunctive norm between socioeconomic groups. For example, it has been suggested in a Norwegian study that more positive attitudes toward smoking may account for lower quit rates among smokers of low SES [12].

Van den Putte et al. 2005 [13] found that implicit social influence variables, such as “subjective norm” (perception of whether others whose opinion matters to us think we should quit) and “injunctive norm” (whether the smoker considers smoking to be an acceptable behaviour in society) have most effect on quit intention, while the perception of what other people actually do (descriptive norms) has less effect [13]. Thus, smokers were more motivated to quit by what they thought others expected of them or what they thought was acceptable, than by what others actually did. This study did not examine differences in injunctive norm by SES level [13]. The power of injunctive norms can also be seen in a study by Zhu et al (2007) where Chinese and Korean migrants to California moved from societies where the injunctive norm was very positive toward smoking to societies where the injunctive norm was very negative [14]. In these cases

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more than half of the ‘ever smoking’ migrants now living in California had quit. Injunctive norm can thus have a very powerful effect on quitting behaviour. A qualitative study of low and high SES smokers found differences in the collective patterns of consumption in the low SES. While high SES participants had noticed that smoking prevalence had decreased in their community and social circle over time, low SES participants noticed no decreased prevalence [15]. This could lead to different perceptions of injunctive norm in the different SES groups [15]. The same study found that low SES participants might expect financial support to use pharmacotherapeutic quitting aids, where this was not the case in the high SES [15]. It is possible that differences in injunctive norm between different SES levels formed the backdrop for the lack of differential impact of the reimbursement of smoking-cessation pharmacotherapy legislation.

We will examine the effects of the change in reimbursement of smoking cessation pharmacotherapy in 2011 in the Netherlands on inequalities in quit attempts using pharmacotherapy with repeated cross-sectional data. If we do not find a decrease in inequalities in quit attempts using pharmacotherapy after the provision of reimbursed pharmacotherapy, we hypothesize that this may be due to the social norm being more accepting of smoking in the low SES group. In summary we will compare the proportion of smokers who make quit attempts with smoking cessation pharmacotherapy in lower and higher socioeconomic groups, before and after the introduction of reimbursement of this therapy. In addition, we will assess whether differences in injunctive norm underlie the observed pattern.

METHODS Design We used data from the Dutch Continuous Survey of Smoking Habits (DCSSH) which takes continuous cross-sectional web surveys of smoking behaviours of the Dutch population of 15 years and over. Approximately 300 unique individuals are surveyed weekly with response rates ranging between 67.5% and 70.3% per year. The data is weighted to reflect the Dutch population. The data is weighted on the basis of respondents’ gender, age, education level and social class, the province in which they live, and their family size and region. Data from the period 2009 – 2012 was used. The Central Committee on Research Involving Human Subjects in the Netherlands requires no ethical approval for non-medical survey research.

Measures Quit attempt using pharmacotherapy Smoking status was determined by the question: ‘Do you (sometimes) smoke or not at all?’ Possible answers were: ‘smoke (sometimes)’, ‘not at all’, or, ‘don’t know’. Those who smoked (sometimes) were considered to be ‘current smokers’. If a participant answered ‘not at all’ to this question, they were asked: ‘Have you previously smoked?’ Possible answers were: ‘yes, previously smoked’, ‘no, never smoked’, and ‘don’t know’. Those who had previously smoked were considered to be ‘former smokers’. Those who answered ‘no, never smoked’, were considered to be ‘never smokers’.

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A quit attempt using pharmacotherapy was determined by the question: ‘You see here a number of aids and methods that you can use to help with stopping smoking. Did you, the last time that you stopped smoking (or, for those still smoking, ‘in your recent quit attempt’), use one of these aids or methods? (multiple answers possible). A list with answers was given. However, the only answers used for this study were the pharmacological aids which were potentially reimbursed, which were: ‘Nicotine Microtab’, ‘Nicotine chewing gum’, ‘nicotine patches’, ‘nicotine lozenges’, ‘Zyban/bupropion’, ‘Nortriptyline/nortrilen’, ‘Champix/Varenicline’.

Smokers or former smokers who had made their most recent quit attempt using pharmacotherapy were categorised by the year in which they had made the attempt, which was one of 2009 through 2012. The question determining the year was: ‘How long ago did you stop (was your most recent attempt to stop) smoking?’ Possible answers were: ‘In the last month’, 1-3 months (inclusive) ago’, ‘4-6 months (inclusive)’ ago, ‘7-12 months (inclusive)’ ago, ‘1-2 years (inclusive) ago’, ‘3-4 years (inclusive) ago’, ‘5-9 years (inclusive) ago’, ’10 years or longer ago’ and ‘don’t know’. We used a period of 4 weeks to indicate a month. In the first four weeks of the year, all participants were excluded, because it could not be ascertained if they stopped in December of the previous year or in January. We excluded 36,354 smokers or former smokers who had made quit attempts which either did not fall into one of the study years or which we were not certain fell into a study year. About half of them (n=19,628) were quit attempts which had occurred >10 years ago.

Socioeconomic status SES was determined separately by income and education [16] and split into three categories. SES by income used the gross income per year, with the middle SES cut points being €32,500 – €51,300. SES by education used the following categories: low was no, primary and lower secondary education, middle was mid- and upper secondary education, and high was tertiary education. 6 Injunctive norm Injunctive norm was ascertained by participants’ answer to the question: ‘Which of the following statements gives the best indication of how people in the Netherlands in general think about smoking in the vicinity of others?’ Possible answers were given on a five-point Likert-like scale from 1) ‘Socially acceptable in all situations’ through to 5) ‘Not socially acceptable in any situation’. Due to small numbers, a categorical variable with three answer categories was then created with answer categories: 1) ‘Mostly acceptable’ (answers 1 & 2), 2) ‘Neutral’ (answer 3), and 3) ‘Mostly unacceptable’ (answer 4 & 5). This question was asked of everyone interviewed in the last four weeks of each quarter.

Period We separated the study period into two time periods: ‘2011’ (when reimbursement was available) and ‘all other years’ (where no reimbursement was available).

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Statistical analyses We took the group of smokers including all current smokers, as well as, the former smokers who had made their most recent quit attempt during the study period, which we refer to as ‘smokers’. We then stratified for income and education level and examined the number of these aforementioned ‘smokers’ who used pharmacotherapy in their most recent quit attempt, as a proportion of the total ‘smokers’. This was done for both time periods. We compared the 95% Confidence Interval of the proportions. Non-overlapping confidence intervals were considered significant. We then looked at the proportion of current smokers and non-smokers (former and never smokers) with a particular injunctive norm stratified for both income and education, in each of the two time periods. Again, we compared the 95% Confidence Interval of the proportions. Significance was determined by non-overlapping confidence intervals.

We used logistic regression analyses, where the dependent variable was ‘a quit attempt with the use of pharmacotherapy during the study period’. The independent variables were educational level and income level, and year of quit attempt. We made a distinction between the year ‘2011’, when the reimbursement measure had been implemented, and ‘all other years’ (2009, 2010, 2012), when the reimbursement did not apply. Year and educational and income level were analysed as categorical variables. We also re-ran this analysis stratified for education and income (Table 4). We considered age as a possible confounder. Gender was also considered but did not change the conclusions (results not presented here).

In most variables missing values made up a small percentage of cases. However, in the case of income level, 25% of participants lacked data. The characteristics of those missing data can be seen in Appendix 1. Most characteristics were similar to those in the total population with the exception that more smokers were of low educational level (4%), and, of those missing who had quit in a given year, a lower percentage were of high educational level (7%). We have treated these as missing at random and performed complete case analyses.

RESULTS Participant characteristics can be seen in Table 1. The characteristics of the current and former smokers are very similar to those of the smokers who made quit attempts between 2009-2012, with the exception that there are fewer former smokers in the younger age groups and more in the older age groups.

There was no significant difference in the proportion of smokers of low income or education making quit attempts with pharmacotherapy in 2011 compared with all other years (Table 2). Inequalities in quitting with pharmacotherapy were unchanged in all the years studied (Table 2).

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Table 1: Participant characteristics

Total population Current smokers Former smokers Never smokers Smokers who (N=75415) (n=19902) (n=26358) (n=29154) made quit attempts in 2009-2012 (n=2438)

n(%) Gender Male 37174(49) 10366(52) 14052(53) 12756(44) 1178(48) Female 38240(51) 9537(48) 12306(47) 16398(56) 1260(52) Age 15-24 11155(15) 3193(16) 754(3) 7208(25) 547(23) 25-34 11356(15) 3495(18) 2306(9) 5555(19) 527(22) 35-44 14325(19) 4173(21) 3653(14) 6499(22) 473(19) 45-54 13570(18) 4102(21) 5088(19) 4380(15) 397(16) 55-64 11825(16) 3062(15) 6188(24) 2575(9) 315(13) 65-74 9119(12) 1469(7) 5594(21) 2056(7) 138(6) 75+ 4064(5) 408(2) 2776(11) 880(3) 41(2) Income level Low 18953(25) 5799(29) 6967(26) 6186(21) 733(30) Middle 17909(24) 4471(23) 6689(25) 6749(23) 543(22) High 19085(25) 4254(21) 6544(25) 8288(28) 549(23) Educational level Low 16208(22) 5068(26) 6009(23) 5131(18) 556(23) 6 Middle 26723(35) 7804(39) 9486(36) 9433(32) 969(40) High 31371(42) 6715(34) 10538(40) 14118(48) 881(36)

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400350-L-bw-Benson Part 2 3.0 (2.5 – 3.7) 2.8 (2.4 – 3.3) 2.7 (2.2 – 3.3) 2.7 (2.3 – 3.1) Percentage of quit attempts of quit attempts Percentage with pharmacotherapy among smokers %(95%CI) 2.8 (2.3 – 3.3) 2.6 (2.2 – 3.3) 3326 5254 3510 6174 Smokers (n=15623) 4599 3937 101 149 94 164 Number of quit attempts Number of quit attempts with pharmacotherapy (n=425) 128 104 All other years (2009,2010,2012) other years All 3.5 (2.5 – 4.8) 2.9 (2.2 – 3.9) 3.1 (2.2 – 4.3) 3.2 (2.5 – 4.1) Percentage of quit attempts of quit attempts Percentage with pharmacotherapy among smokers %(95%CI) 2.9 (2.1 – 3.9) 2.8 (2.0 – 3.9) 1040 1611 1070 1798 Smokers (n=4718) 1321 1249 36 47 33 57 2011 Number of quit attempts with pharmacotherapy (n=141) 38 35 Percentage (95% Confidence Interval) of quit attempts using smoking cessation pharmacotherapy per period, stratified for income and education. for income stratified per period, cessation pharmacotherapy using smoking of quit attempts Interval) (95% Confidence Percentage High High Middle Middle Income Low Education Low Non-overlapping confidence intervals are considered significant. considered intervals Non-overlapping are confidence Table 2: Table

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Table 3: Percentage (95% Confidence Interval) of Injunctive norm of Current Smokers and Non-smokers per period, stratified by income and education.

Current smokers Non-Smokers (n=6061) (n=17,195)

Injunctive norm category 2011 All other years 2011 All other years %(95%CI) %(95%CI) %(95%CI) %(95%CI) Income level Low (n=5814) Mostly acceptable 19(16-23) 19(17-22) 14(12-16) 18(16-19) Neutral 57(52-62) 58(55-60) 45(42-48) 45(43-47) Mostly unacceptable 23(19-28) 23(21-25) 41(38-44) 37(35-39)

Middle (n=5436) Mostly acceptable 18(14-23) 18(16-20) 12(10-14) 14(13-16) Neutral 53(47-59) 60(57-63) 44(41-47) 46(45-48) Mostly unacceptable 29(24-35) 22(20-25) 44(41-47) 39(38-41)

High (n=5939) Mostly acceptable 16(12-21) 19(16-21) 13(11-15) 15(14-16) Neutral 48(42-53) 55(52-58) 44(41-47) 53(51-55) Mostly unacceptable 36(31-42) 26(23-29) 43(40-46) 47(45-49)

Educational level Low (n=4990) Mostly acceptable 23(19-27) 20(17-22) 14(12-17) 16(14-17) Neutral 55(50-60) 61(58-64) 47(44-51) 49(47-51) Mostly unacceptable 22(18-27) 19(17-21) 39(35-42) 35(34-37)

Middle (n=8160) Mostly acceptable 21(18-25) 20(18-22) 13(12-15) 15(14-16) Neutral 53(49-58) 59(57-61) 45(42-47) 46(44-47) Mostly unacceptable 26(22-29) 21(19-23) 42(40-45) 39(37-40) 6 High (n=9727) Mostly acceptable 14(11-17) 17(15-19) 13(12-15) 14(14-15) Neutral 55(50-59) 55(53-58) 44(42-47) 45(44-46) Mostly unacceptable 32(28-36) 28(26-30) 42(40-44) 41(39-42) Non-overlapping confidence intervals are considered significant. Table 3 shows the current smokers’ and non-smokers’ injunctive norm by SES level. Approximately a fifth of smokers had a mostly acceptable injunctive norm. In 2011, significantly lower proportion of low SES (income and education) smokers had a mostly unacceptable injunctive norm compared with high SES smokers. This is also the case for SES by educational level in all other years, but not for income. In 2011, a significantly higher proportion of smokers of low educational level had a mostly acceptable injunctive norm compared with their peers of high educational level. No significant differences in the injunctive norms of non-smokers were observed across periods, and income and educational levels. In general, a small proportion

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(12-18%) have a mostly acceptable injunctive norm, and in comparison a larger proportion have a mostly unacceptable injunctive norm (35-47%). When smokers are compared with non- smokers, there are significantly less smokers than non-smokers with a mostly unacceptable injunctive norm in almost all income and educational levels. This pattern is more pronounced in low than high income and educational levels. The only exception to this is the high income level in 2011, where a similarly high proportion of smokers found smoking mostly unacceptable compared with non-smokers.

The results of the multivariate logistic regression models in Table 4 show that when injunctive norm was controlled for within each of the SES strata (in models including age), the ORs for quitting smoking with pharmacotherapy in 2011 as compared to the other years increased in almost all socioeconomic groups, with the exception of those of low educational level. As expected, smokers of low income with a ‘mostly acceptable’ injunctive norm towards smoking were significantly less likely to make a quit attempt using pharmacotherapy than those with a ‘mostly unacceptable’ injunctive norm (OR (95% CI): 0.29[0.10-0.84]), regardless of year. Paradoxically, in those of high income, those with a ‘mostly acceptable’ injunctive norm were more likely to make a quit attempt using pharmacotherapy (OR(95%CI):1.95[0.70-5.43]), however this was not significant.

DISCUSSION A similar proportion of low SES (income and education) participants compared with their middle and high SES peers, made quit attempts using pharmacotherapy during the reimbursement period in 2011. This was also the case in the other years studied. The injunctive norm of low SES smokers differed considerably from that of high SES smokers in 2011. Low SES smokers had a mostly unacceptable injunctive norm which was significantly lower than that of high SES smokers. This was also the case in smokers of high educational level in all other years. Also, in 2011, a significantly larger proportion of smokers of low educational level had a mostly acceptable injunctive norm, compared with their more highly educated peers. No differences were observed in the injunctive norm of non-smokers across periods or SES levels. Within each SES level, approximately 40% of non-smokers had a mostly unacceptable injunctive norm toward smoking and, in general, less than half of this proportion had a mostly acceptable injunctive norm. Thus a smaller proportion of smokers in low SES groups had a mostly unacceptable injunctive norm toward smoking as compared to high SES smokers, and non-smokers of all SES levels

A strength of our study is that while we have similar findings to another study [9] with regard to lack of change in inequalities in quit attempts using pharmacotherapy with the introduction of reimbursement, we add to this by looking at injunctive norms. These norms have not been studied frequently as an influence on quitting behaviour [13]. We are not aware of any other quantitative studies examining injunctive norm in smokers of differing SES levels in the context of quitting smoking.

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400350-L-bw-Benson Chapter 6 1.0 1.0 1.75 (0.92-3.35) 1.25 (0.63-2.51) 1.38 (0.53-3.60) High 1.0 1.0 1.29 (0.71-2.36) 0.66 (0.35-1.24) 0.77 (0.36-1.64) Middle 1.0 1.0 0.89 (0.39-2.02) 1.55 (0.67-3.58) 0.73 (0.21-2.48) Education Low 1.0 1.0 1.21 (0.57-2.58) 1.20 (0.51-2.82) 1.95 (0.70-5.43) High 1.0 1.0 1.20 (0.50-2.86) 2.47 (0.88-6.97) 2.31 (0.60-8.92) Middle 6 1.0 1.0 1.54 (0.74-3.21) 0.52 (0.26-1.04) 0.29 (0.10-0.84)* Income Low showing predictors (year/injunctive norm) of quit attempts using pharmacotherapy, by income and education. and education. income by using pharmacotherapy, norm) of quit attempts (year/injunctive predictors showing a Multivariate models Multivariate Year other years All Injunctive norm Smoking mostly unacceptable 2011, controlled for age for 2011, controlled Neutral Smoking mostly acceptable All models are controlled for age for controlled models are All Table 4: Table *p<0.05 a

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Some limitations of this study must, however, be considered. We selected cases in such a way that we were certain in which of the four years their most recent quit attempt took place. We did not include participants interviewed in the first four weeks of the year who indicated that they had quit in the past month, because it was not possible in these cases to tell if they had quit in January of the year in which they were interviewed or in December of the previous year. This means that we lost data on January 2012, during which ‘New Year resolution quitters’ making an attempt on or after New Year, might have used reimbursement if it was organised beforehand in late 2011. The knowledge that the reimbursement was ending, might have increased this group in 2012. It is possible that this would have an effect on overall percentages, but it would be unlikely to affect inequalities.

It is possible that the number of smokers using pharmacotherapy in a given year were under- represented because the questionnaire records the ‘most recent quit attempt’ made. Smokers often make multiple attempts [17], thus it is possible they made more than one attempt in the year in which they were interviewed and that the most recent attempt was not the one in which they used medication. Thus, it is possible that we have an underestimation of the number of quit attempts made with pharmacotherapy.

Another possible limitation is that a quarter of participants missed income data. These participants were similar to those with income data in the total group with the exception that 4% more were of low educational level. Of those who had made a most recent quit attempt during the study period, 7% less were of high educational level. It is possible that these differences biased the results, however, our results on our results on differences in use of pharmacotherapy in different income groups have also been found elsewhere [9], and educational level exhibited the same pattern of findings

We found that the introduction of reimbursement of smoking-cessation pharmacotherapy does not lead to a greater proportion of low SES smokers compared with high SES smokers using this therapy. This corresponds with the results of previous studies. Nagelhout et al. (2014) showed that inequalities in use of smoking-cessation pharmacotherapy in quit attempts were unchanged by the introduction of the reimbursement [9]. This result was not a result of differences in awareness of the reimbursement, because, as we see from previous research, the reimbursement was widely known about. For example, a campaign was run from December 2010 – March 2011 to ensure that Dutch smokers, with emphasis on those of low educational level, were aware of the reimbursement [18]. It had the following components: television and radio slots, a campaign website, banners, use of social media, posters and flyers and messages in newspapers and magazines. Approximately 80% of smokers with a quit intention had seen the campaign, and this was higher in those of low than high educational level [18]. Approximately 60% of smokers intending to quit knew that reimbursement was available after the campaign [18]. There were also no income differences in the awareness of the reimbursement between high, middle and low income groups in 2010 - 2012, and approximately 40% of participants were aware of the policy in 2011 [9].

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Those of low income with a ‘mostly acceptable’ injunctive norm were significantly less likely to make a quit attempt using pharmacotherapy than those with a ‘mostly unacceptable’ injunctive norm. Approximately 20% of the low income group in both periods have a ‘mostly acceptable’ injunctive norm, with approximately 55% having a neutral injunctive norm. Thus while those with a ‘mostly acceptable’ injunctive norm are a minority, it is possible that injunctive norm might explain the lack of uptake of the reimbursement. This could be because they might not feel much social pressure to quit (and thus to seek methods to help with quitting, such as smoking-cessation pharmacotherapy) because they have enough others around them with the same accepting norm or a neutral norm [13]. Also, those with a more accepting injunctive norm might be less ready to quit [13]. The injunctive norm of low SES smokers differs significantly from that of low SES non-smokers, who feel that smoking is significantly more unacceptable. Differences in these groups in other SES levels are less pronounced. Thus, low SES smokers have an injunctive norm which is different from all other subgroups. This is an important finding as other smokers in a smokers’ social network are highly influential. Low SES smokers tend to have more smokers in their social networks and are more likely than high SES smokers to gain smoking friends [19], which could act to maintain norms. Smokers who loose smoking friends from their social network are more likely to intend to quit, attempt to quit and succeed in quitting [20].

It is possible that a targeted attempt to change the ‘mostly neutral’ and ‘mostly acceptable’ injunctive norms amongst smokers in low SES groups to ‘mostly unacceptable’, prior to or concurrent with the availability of reimbursement, might result in greater use of pharmacotherapy in quit attempts in this group.

CONCLUSION In the Netherlands, reimbursement of smoking-cessation pharmacotherapy did not increase the proportion of low socioeconomic smokers that attempted to quit using this therapy to a greater extent than the proportion of higher socioeconomic smokers. A smaller proportion of low SES 6 smokers think that smoking is generally unacceptable in the vicinity of others in Dutch society in comparison with smokers from high SES groups or non-smokers of all SES levels. The significantly lower use of smoking cessation pharmacotherapy in quit attempts in low income smokers with a positive injunctive norm toward smoking, and a similar, though not significant pattern, seen in low educational level smokers, might partly underlie this lack of increased uptake of reimbursed smoking-cessation pharmacotherapy in low SES smokers. In order to have an equal impact over socioeconomic groups, the introduction of reimbursement should probably be accompanied by measures aimed at changing the injunctive norm towards smoking.

ACKNOWLEDGEMENTS The authors would like to thank STIVORO for the use of the DCSSH database.

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FUNDING This study was financed by The Netherlands Organisation for Health Research and Development (ZonMw) (Project number: 200120004). The DCSSH study was supported by grants from the Dutch Ministry of Health, Welfare and Sports.

COMPETING INTERESTS The authors declare that there are no conflicts of interest.

AUTHOR CONTRIbUTIONS FB, VN, MW and KS conceived the idea and participated in the design of the study. GN prepared the data. FB performed the statistical analysis and drafted the manuscript. All authors were involved in the critical revision of the manuscript. All authors read and approved the final manuscript.

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REFERENCES 1. Mackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinsalu M, Kunst AE, European Union Working Group on Socioeconomic Inequalities in H. Socioeconomic inequalities in health in 22 European countries. N. Engl. J. Med. 2008;358(23):2468-2481 doi:10.1056/NEJMsa0707519.

2. Reid JL, Hammond D, Boudreau C, Fong GT, Siahpush M, Collaboration ITC. Socioeconomic disparities in quit intentions, quit attempts, and smoking abstinence among smokers in four western countries: findings from the International Tobacco Control Four Country Survey. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco. 2010;12 Suppl:S20-33 doi:10.1093/ntr/ntq051.

3. Edwards R, McElduff P, Jenner D, Heller RF, Langley J. Smoking, smoking cessation, and use of smoking cessation aids and support services in South Derbyshire, England. Public Health. 2007;121(5):321-332 doi:10.1016/j.puhe.2006.11.002.

4. Fernandez E, Schiaffino A, Borrell C, Benach J, Ariza C, Ramon JM, Twose J, Nebot M, Kunst A. Social class, education, and smoking cessation: Long-term follow-up of patients treated at a smoking cessation unit. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco. 2006;8(1):29-36 doi:10.1080/14622200500264432.

5. Bosdriesz JR, Willemsen MC, Stronks K, Kunst AE. Socioeconomic inequalities in smoking cessation in 11 European countries from 1987 to 2012. J. Epidemiol. Community Health. 2015 doi:10.1136/jech-2014-205171.

6. Hartmann-Boyce J, Stead LF, Cahill K, Lancaster T. Efficacy of interventions to combat tobacco addiction: Cochrane update of 2012 reviews. Addiction. 2013;108(10):1711-1721 doi:10.1111/add.12291. 7. Stead LF, Lancaster T. Behavioural interventions as adjuncts to pharmacotherapy for 6 smoking cessation. Cochrane Database Syst Rev. 2012;12:CD009670 doi:10.1002/14651858. CD009670.pub2.

8. Verbiest ME, Chavannes NH, Crone MR, Nielen MM, Segaar D, Korevaar JC, Assendelft WJ. An increase in primary care prescriptions of stop-smoking medication as a result of health insurance coverage in the Netherlands: population based study. Addiction. 2013;108(12):2183-2192 doi:10.1111/add.12289.

9. Nagelhout GE, Hummel K, Willemsen MC, Siahpush M, Kunst AE, de Vries H, Fong GT, van den Putte B. Are there income differences in the impact of a national reimbursement policy for smoking cessation treatment and accompanying media attention? Findings from the International Tobacco Control (ITC) Netherlands Survey. Drug Alcohol Depend. 2014;140:183-190 doi:10.1016/j.drugalcdep.2014.04.012.

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10. Murphy JM, Mahoney MC, Hyland AJ, Higbee C, Cummings KM. Disparity in the use of smoking cessation pharmacotherapy among Medicaid and general population smokers. J. Public Health Manag. Pract. 2005;11(4):341-345.

11. Hiscock R, Bauld L, Amos A, Fidler JA, Munafo M. Socioeconomic status and smoking: a review. Ann. N. Y. Acad. Sci. 2012;1248:107-123 doi:10.1111/j.1749-6632.2011.06202.x.

12. Lund M, Lund KE, Rise J. [Socioeconomic differences in smoking cessation among adults]. Tidsskr. Nor. Laegeforen. 2005;125(5):564-568.

13. van den Putte B, Yzer MC, Brunsting S. Social influences on smoking cessation: a comparison of the effect of six social influence variables. Prev. Med. 2005;41(1):186-193 doi:10.1016/j.ypmed.2004.09.040.

14. Zhu SH, Wong S, Tang H, Shi CW, Chen MS. High quit ratio among Asian immigrants in California: implications for population tobacco cessation. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco. 2007;9 Suppl 3:S505-514 doi:10.1080/14622200701587037.

15. Paul CL, Ross S, Bryant J, Hill W, Bonevski B, Keevy N. The social context of smoking: A qualitative study comparing smokers of high versus low socioeconomic position. BMC Public Health. 2010;10:211 doi:10.1186/1471-2458-10-211.

16. Schaap MM, Kunst AE. Monitoring of socio-economic inequalities in smoking: learning from the experiences of recent scientific studies. Public Health. 2009;123(2):103-109 doi:10.1016/j.puhe.2008.10.015.

17. Cohen S, Lichtenstein E, Prochaska JO, Rossi JS, Gritz ER, Carr CR, Orleans CT, Schoenbach VJ, Biener L, Abrams D, et al. Debunking myths about self-quitting. Evidence from 10 prospective studies of persons who attempt to quit smoking by themselves. Am. Psychol. 1989;44(11):1355-1365.

18. Willems RA, Willemsen MC, Nagelhout GE, Smit ES, Janssen E, van den Putte B, de Vries H. Rapportage Evaluatie van de ‘Echt stoppen met roken kan met de juiste hulp’ campagne. Maastricht: Maastrict University, ZonMw;2012.

19. Hitchman SC, Fong GT, Zanna MP, Thrasher JF, Chung-Hall J, Siahpush M. Socioeconomic status and smokers’ number of smoking friends: findings from the International Tobacco Control (ITC) Four Country Survey. Drug Alcohol Depend. 2014;143:158-166 doi:10.1016/j. drugalcdep.2014.07.019.

20. Hitchman SC, Fong GT, Zanna MP, Thrasher JF, Laux FL. The relation between number of smoking friends, and quit intentions, attempts, and success: findings from the International Tobacco Control (ITC) Four Country Survey. Psychol. Addict. Behav. 2014;28(4):1144-1152 doi:10.1037/a0036483.

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APPENDIx 1: CHARACTERISTICS OF PARTICIPANTS MISSING DATA FOR INCOME

All Smokers during Participants whose most (n=19467) (part of) the study recent quit attempt fell period within the study period (n=5475) (n=613)

n(%) Year of inclusion 2009 4577(24) 1433(26) 194(32) 2010 5273(27) 1513(28) 152(25) 2011 4837(25) 1287(24) 140(23) 2012 4780(25) 1242(23) 127(21) Gender Male 8666(45) 2584(47) 260(42) Female 10802(56) 2891(53) 353(58) Age 15-24 3579(18) 1071(20) 165(27) 25-34 2949(15) 951(17) 138(23) 35-44 3997(21) 1198(22) 111(18) 45-54 3792(20) 1185(22) 97(16) 55-64 2801(14) 726(13) 68(11) 65-74 1659(9) 256(5) 26(4) 75+ 690(4) 87(2) 8(1) 6 Educational level Low 4992(26) 1678(31) 156(25) Middle 7174(37) 2212(41) 255(42) High 6447(33) 1334(24) 177(29) Used pharmacotherapy 136(22)

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GENERAL DISCUSSION This thesis examined the effect, optimal method of recruitment and reasons for attendance of smoking cessation interventions in disadvantaged areas of the Netherlands, and explored whether the prevailing economic factors and injunctive norm influenced inequalities in smoking cessation in the Netherlands. In this chapter, the main findings will be summarized, limitations of the research will be considered, reflections will be considered and implications for practice will be discussed.

MAIN FINDINGS The following two sections summarize the main findings for each of the research questions.

Research question 1: What is the effect, optimal method of recruitment, and reasons for attendance of smoking cessation interventions in disadvantaged areas?

In chapter 2, we explored the effects of four different types of smoking cessation behavioural therapy (SCBT) (individual face-to-face or telephone counselling, and fixed or rolling group therapy) offered to smokers in disadvantaged urban areas of the Netherlands. We found that rolling group therapy and individual counselling were the most effective therapies with a self- reported quit rate of 14% and 37.4% respectively at 12 months, compared with fixed group and telephone counselling (15.4% and 7.9%, respectively). CO-validated quit rates at 12 months were slightly lower than those of self-report, but the relationship found in the self-reported data was preserved for telephone counselling and fixed group therapy. Group therapy in a hospital setting was significantly more effective than group therapy held in other settings, and there was no significant difference in the effect of different types of group therapy (fixed and rolling group) in the hospital setting.

In chapter 3, we explored how smokers heard about and were referred to SCBT in two disadvantaged areas of the Netherlands. Both sites had used multiple channels within the local community to recruit potential participants, including one site which used a social network method. In the context of disadvantaged areas, we found that the most common channel to both hear about and be referred to SCBT was through the GP. This was true for all participants and, also for those of low socioeconomic status (SES). Participants who heard through this channel differed little from participants who heard and were referred through the other channels. Attendance of more than three sessions was also not predicted by any of the heard about or referral channels.

In chapter 4, we collected and analysed qualitative data to explore the reasons why participants did or did not attend sessions of SCBT. We analysed the data with reference to the Self- Determination Theory, which is a theory of human motivation in which motivation is divided into intrinsic and extrinsic motivation and amotivation. We found that attendees fell into two separate groups: ‘Frequent attenders’ who missed ≤2 sessions and ‘Infrequent attenders’ who missed >2 sessions. We found that many frequent attenders were intrinsically motivated to

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attend while infrequent attenders were not. Frequent attenders also displayed higher level extrinsic motivations to attend than did infrequent attenders. We also found that frequent attenders experienced more social support and no organisational barriers to attendance, by comparison with infrequent attenders.

Research question 2: What is the influence of the prevailing economic conditions and social norms on inequalities in smoking cessation?

In chapter 5, we explored the effect of the Global Financial Crisis (GCF) on inequalities in current smoking and smoking cessation. We find inequalities in current smoking and smoking cessation present in all SES indicators (income, educational level, neighbourhood deprivation). Overall inequalities did not change significantly for most SES indicators, however, income- and education-related inequalities increased in some age groups. Among respondents aged 18-30 years, income-related inequalities in smoking cessation were borderline significantly larger during the GFC than pre-GFC. Among respondents aged 45-64,the decrease in current smoking was smaller in those of low income compared to those of high income during the GFC compared with pre-GFC.

In chapter 6, we explored the effect of a national reimbursement of smoking-cessation pharmacotherapy on inequalities in pharmacotherapy use during quit attempts and, within this context, the influence of injunctive norms. We found that there was no effect of the reimbursement on inequalities in use of smoking cessation pharmacotherapy during quit attempts. We also found that smokers of low income level with a more accepting injunctive norm toward smoking were significantly less likely to try to quit with pharmacotherapy than their peers with a less accepting injunctive norm toward smoking. This trend was also present in those of low education, however this was not statistically significant.

LIMITATIONS OF THE RESEARCH In this thesis, limitations of each study have been considered in the discussion section of each article (chapters 2-6). In this section, I will consider several general points which transcend the individual articles.

Change in legislation 7 This study was originally devised to take advantage of the reimbursement of smoking cessation pharmacotherapy which was introduced by the Dutch government in 2011. This reimbursement removed financial barriers to using evidence-based smoking cessation pharmacotherapeutic aids for low SES smokers. Due to changes in the government, this reimbursement was stopped in 2012 and then reintroduced in 2013. Thus the necessary condition of removing financial barriers for those of low SES wishing to quit using evidence-based effective measures was only present during part of the data collection period. This has implications for the results because it slowed down data collection, leading to few participants being enrolled in 2012.

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Missing data Participants in low SES groups are challenging to both engage and maintain in smoking cessation research programmes [1,2]. That was certainly the case with this study, where the original study site had to be supplemented by further sites in order to reach recruitment targets. With regard to chapter 2, the drop-out rate at 12 months was 29% in all sites, but 66% in those doing telephone counselling. The internal validity may have been compromised because of this, however, when other factors were controlled for in the statistical analysis, the conclusion as to the performance of the therapy types remained similar.

With regard to chapter 3, we can say nothing about smokers who did not enrol in the research, thus it is possible that our target group was not reflective of all participants, thus possibly affecting the internal validity. To ensure that this does not happen in future research, we would recommend the use of register data (data from medical records, as was obtained from two of our sites) for future studies on these groups, with the caveat that researchers must first ensure that all data which they require is present in the register data.

Generalisability Section 1 considers smoking cessation services available to individuals in disadvantaged urban areas of the Netherlands. The studies in this section may be considered generalisable to other urban areas in the Netherlands, because they offer evidence from areas differing considerably with regard to ethnic make-up, and further to other disadvantaged urban areas in other European countries. However, Section 2 considers two macro-level factors from the Dutch perspective. Both studies in this section were based on extensive national level data, and are believed to be generalisable to the population of the Netherlands. Further generalisability may be limited by specific national factors. For example, with regard to the GFC, Dutch social protection policy is one of the strongest in Europe [3] and the Dutch population only began to experience severe effects of the crisis in 2012 [4]. Thus while this study may not be directly generalisable to other European countries, it helps, along with other single country studies, to build a picture of the effect of the GFC in Europe. The second study addresses the effects of a nationally implemented policy measure which was to take effect under the specific condition of injunctive norms found in the Netherlands. Studies show that most Dutch smokers do not often think of the harms of smoking and have a poor understanding of the harms their smoking can do to others [5], which compares poorly with other countries surveyed [5]. Thus it is possible, again, that this study adds to the understanding of the effect of national reimbursement of pharmaceuticals, but is probably only directly generalisable to other countries with a high tolerance of smoking, such as Germany [6] or Austria [7].

REFLECTIONS Effect The effect of the different intervention types examined in chapter 2 differed greatly, however, all types were more successful than the background smoking cessation rate of 1-4% [8,9] and

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were comparable to or better than results found in similar groups in other studies [10-13]. Some were more successful than others, with individual face-to-face counselling and rolling group therapy having the highest 12 month self-reported continuous quit rates. Given the difficulties faced by disadvantaged smokers attempting to quit [14], this success should be viewed as very encouraging for interventionists working in this area.

In our exploration of the differences between counselling types, we found that individual face-to-face and rolling group therapy gained similar results. When we explored differences in setting, we found that group therapy given in a hospital setting was most effective. Group therapy in a hospital setting was equally effective when provided as rolling or fixed group therapy. Despite uptake of group counselling being a factor limiting its success [15] , there is evidence from physical activity interventions in low SES groups that group format contributes to the success of intervention in these groups [16]. It is important to weigh up potential reach and success when considering which treatment types should be offered [15], and this is especially the case in disadvantaged areas where the smoking prevalence is greater than in other areas. Thus the implementation of group interventions in disadvantaged areas must be accompanied by measures to increase uptake amongst disadvantaged groups, if the full benefit of such an intervention is to be received by these groups.

Reach and recruitment It is known that individuals in low SES groups, which in the Netherlands often encompass ethnic minority groups, can be challenging to reach and recruit into interventions [17-19]. It is, therefore, noteworthy that in this research, participants of low SES were successfully recruited (chapter 3). This was mainly as a result of the use of the GP as a reach and referral source (chapter 3). Again, we can be optimistic about reaching this group, given this result. However, it must be noted that the number of participants recruited over a considerable time period remained low in absolute numbers (chapter 3). Dutch GPs raise the issue of smoking cessation less often with their patients than GPs in many other high income countries [20], so it is possible that only a proportion of the potential participants were approached by the GPs referring to the SCBT, and that better utilisation of this channel might lead to more participants. However, it is also possible that this was due to low motivation to quit in this group, which may be related to unsupportive social norms toward smoking cessation or taking part in SCBT in disadvantaged groups (chapter 4). 7

Reimbursement A point to consider with regard to reimbursement is the notion of the ‘removal’ of financial barriers. Removal of the financial barrier is an important measure as it is likely to encourage low SES smokers to quit [14]. However, when something is reimbursed, it is something which, by its very nature, has already been paid for. In this research, the reimbursement happened in several ways, but usually after, and often some time after, paying up-front for the pharmacotherapy. In some cases, participants with health insurance from a particular provider could get the pharmacotherapy without paying up-front, however, they had to go to a specific pharmacy to do

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so, which required traveling out of the local area. Thus, in reality, the immediate financial barrier with regard to pharmacotherapy remained in place for many participants. While ultimately reimbursement left some patients with no costs, it was not ‘free’ at the point of sale, and it was only fully reimbursed if smokers had used up their policy excess (‘eigen risico’). This has implications for this research because the immediate financial barrier was still in place for those who were most disadvantaged. Reimbursement may, therefore, have had less effect than would be possible if it was truly made free of any charge at the point of sale. This is generalisable to other countries where up-front payment is required.

Target group The aim of this project was to recruit low SES participants by geographical targeting of disadvantaged areas. However, the SCBT programmes were open to all residents of these disadvantaged areas, without regard to their income or educational status. We see from our data that what happens in this case is that the population which is recruited may reflect the disadvantaged area [21] or be of a higher general SES level [22] than the disadvantaged area. Thus, we do not feel that geographical targeting alone will deliver participants with at least two indicators of low SES (i.e. low income or educational level in addition to area disadvantage). If the aim is to recruit such smokers, it may be better to provide geographically targeted SCBT programmes, and then to use the GP to further target recruiting within these areas.

Social norms The role of social norms should be considered very carefully when implementing national measures to aid smoking cessation. As a WHO report stated:

‘At the heart of these [tobacco-control] efforts has been the important long-term goal of de-normalizing tobacco use. Promoting change in social norms is essential to successful smoking cessation, since the social environment provides the context for smoking cessation and encourages smokers in their attempts to quit.(p1)’ [23].

Few Dutch smokers (22%) have a negative attitude toward smoking [24]. Compared with many other countries, Dutch smokers have poor understanding of the harms of smoking to themselves or others, and think less often of the consequences of their cigarette use [5]. Adding to this picture, chapter 6 has shown that the norm in low SES smokers in the Netherlands is less unaccepting of smoking than in smokers of other SES levels or in non-smokers of all SES levels (chapter 3). This research has also shown that those of low SES with a mostly acceptable injunctive norm toward smoking are significantly less likely to make use of evidence-based smoking cessation pharmacotherapy (chapter 3) than those with a mostly unacceptable injunctive norm toward smoking. While this may not be a causal association, it is possible that implementation of measures to specifically influence this norm in those of low SES, prior to the implementation of measures such as reimbursement, may influence the use of pharmacotherapy in quit attempts in low SES groups. One possible way to achieve this would be the use of

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national media campaigns, which despite a hiatus during this research, have now recommenced. However, no campaign has currently directly targeted social norms in disadvantaged groups in the Netherlands [25]. The Californian and Australian models can be looked to as examples of taking effective and cost-effective action on social norms [26-29], though not injunctive norm. Specific measures targeted at smokers of low SES would be required in the case of injunctive norm, because of the significantly different injunctive norm found in smokers in these groups. It is also important, within the Dutch context, to specifically culturally target measures at certain ethnic minority groups, such as first generation Turkish, Surinamese and Moroccan men, where smoking prevalence is much higher than in ethnic Dutch groups [30,31]. For example, consideration of the Islamic view of smoking and the positioning of tobacco company marketing in this context in Islamic countries [32] could perhaps be included when groups contain participants with Islamic backgrounds.

National strategy Though this research focussed on individual interventions, the aim was to pilot test a system, which, if successful could be implemented nationally, to assist quitting in the most deprived and to reduce inequalities [33]. However, in considering the question of national implementation, we must first consider the population context of smoking cessation. If the aim is to reduce inequalities in smoking behaviour in the Netherlands by increasing the number of successful quit attempts made by low SES smokers, then we must first acknowledge that most successful quit attempts are made unaided [34], in both the high and low SES groups [35]. Thus measures which increase the number and success of such quit attempts particularly in the low SES, such as tobacco tax/price rises [36,37] and measures which support those who are trying to quit, such as social norm changing measures [26], provide the impetus for more smokers to try to quit. A proportion of these smokers will then use evidence-based cessation measures, as long as there is adequate knowledge and availability of these measures. This has implications for our results because, it is possible that with more national strategies encouraging smokers to quit, especially in low SES groups, more participants may have enrolled for SCBT, and consequently, in our study. Though the therapy types which we evaluated had a greater effect at 12 months than the background quit rate in the general population [8], our research on recruitment and attendance suggest that without measures in place to encourage smokers to use this therapy, 7 and to support them sufficiently during this use, it will be difficult to recruit and retain low SES smokers in SCBT programmes in the Netherlands.

Regarding this project, it was perhaps ambitious to think that it would be possible to place a smoking cessation intervention in a low SES area in the Netherlands and, without addressing the prevailing social norms and immediate affordability of pharmacotherapy, expect success with this particular target group, which is affected more by economic downturns [38] and unsupportive social norms [39], (and other factors e.g. stressful life events [40]) than other socioeconomic groups. These macro-level issues cannot be changed on a local community intervention level; they require well-implemented and government supported national strategies, such

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as significant tax/price increases [41,42], broad awareness [42,43] or social norm changing mass media campaigns [44], and more extensive health warnings on cigarette packs than are currently in place [45], to support individual level interventions offered in disadvantaged communities. Free assisted cessation, in whatever form it is offered (e.g. face-to-face, quitlines etc.), would complement the aforementioned national measures (by providing evidence-based assisted quitting opportunities for smokers intending to quit, many as a result of the aforementioned policies). There is thus a role for government at both national and district level to implement complementary policies, such that national smoking cessation promoting strategies could be implemented, while more districts could choose to focus resources on smoking cessation than is currently the case [46]. There might also be a role for Dutch private health insurance providers to support and encourage the provision of evidence-based smoking cessation services in disadvantaged areas, possibly through forming contracts with such providers. The Netherlands does not currently have a comprehensive national tobacco control policy, with national prevalence targets, sufficient budget and full government support, despite its ratification of the legally binding FCTC [47]. There are signs that the Dutch government’s approach to tobacco control is changing [25]. However, based on the current evidence, unless smoking cessation measures are implemented at a national level and complimented at the local level, and strongly financially supported by the government as is the case in the England [48], it is unlikely to specifically reduce smoking in low SES groups in the Netherlands.

Achievement of the general aim: a summary This thesis had a general aim to pilot test whether the English system of geographically targeting smoking cessation clinics to disadvantaged areas and also providing free treatment could be replicated with good effect in the Netherlands. This aim could not be fully realised due to the lack of reimbursement of pharmacotherapy in 2012, which meant that there was a partial financial barrier to treatment during that year. It was possible, however, to establish an evidence-based smoking cessation programme in one disadvantaged area, and to use data from other existing smoking cessation services in other disadvantaged areas, where, during two of the three years of data collection free treatment was provided. The effects of the programmes were greater than the background quit rate in the general population and participants of low SES were recruited. However, the wider context in which smoking cessation clinics operate in the England, with regard to clear government prioritisation of tobacco control, with funding of measures to address population knowledge and social norms, such as mass media campaigns [49], was not able to be replicated.

IMPLICATIONS For practice As already mentioned, the interventions studied were effective in comparison to both other studies on similar target groups and the background rate of smoking cessation in the general population (which is possibly higher than that in low SES groups alone). Thus, it is possible that if

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recruitment can be greatly increased, these programmes, specifically targeted to disadvantaged areas and nationally implemented, might lead to decreased inequalities in smoking cessation in the Netherlands, in the same way that this has occurred in England [50].

Results of this thesis indicate that, even when multiple strategies are used in a small geographical area, low SES participants are mainly reached and referred to smoking cessation services through existing infrastructure, i.e. the GP. Since 2007, Dutch GPs have been recommended to give smoking cessation advice [51], however, this is not done comprehensively [52,53]. It is recommended that GP organisations ensure that GPs, and especially those working with low SES populations, are aware of all smoking cessation services in their areas and that smoking cessation services make the referral process as easy as possible for GPs and give regular feedback to the GPs on the effects of their referrals. Despite the fact that several of the interventions (rolling group and individual face-to-face) gave good 12 month self-reported quit rates, small numbers were still recruited. Thus, as previously discussed, national level measures are still required to increase the numbers of people in disadvantaged areas seeking or willing to grasp the opportunity to use evidence-based smoking cessation measures.

Findings from this thesis show that low SES smokers who attend SCBT regularly, are intrinsically motivated to do so. It is recommended that interventionists make participants’ enjoyment of their interventions a priority in disadvantaged areas. Or, in other words, make the interventions fun to attend. Results from this thesis also indicate that flexibility in offering may compensate for lack of fun. It is possible that a flexible and fun offering may have the greatest effect on the attendance of participants.

Based on the results of this thesis, I would not recommend that smoking cessation services based in disadvantaged areas be rolled out throughout the Netherlands. Despite promising results indicating that participants can be reached and recruited through the GP and referred to certain interventions which have been shown to have good effect on participants in disadvantaged areas, some areas (below) require further research prior to such a move. Also, conditions supportive of success must be fostered on a national level, as previously discussed.

For future research Results of this thesis indicate that group therapy, regardless of type, provided in a hospital setting 7 and individual face-to-face counselling can be effective therapies for smokers attending services in or near disadvantaged areas. Group therapy, if it is being accessed by adequate numbers of smokers, is probably the most cost-effective of these therapy types [15]. It is therefore recommended that rolling group therapy, with additional measures to increase motivation to quit and to provide a supportive social norm, be researched further with regard to its cost-effectiveness in disadvantaged areas, where adequate numbers of participants are a particular challenge. Further research is also required on the effect of individual face-to-face therapy offered in a primary care or community setting in disadvantaged areas of the Netherlands. Whilst it might be tempting to consider the use of a randomised controlled trial, we would not recommend

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such a study, as the aim of such research is not to assess the exact difference in effect between counselling types. The current methodology seems to be appropriate, however, we would recommend the inclusion of a larger number of disadvantaged areas and service settings, such that the effect of counselling type can be considered in various settings and in disadvantaged areas with differing characteristics (e.g. ethnic diversity),

Part 1 of this thesis provides valuable evidence from a usual community setting or “real life” on the effect, optimal method of recruitment and attendance of smoking cessation therapy in disadvantaged areas in the Netherlands. This is as opposed to the often selective conditions of randomised controlled trials which can affect external validity [54]. However, the feasibility of obtaining such evidence must be considered by researchers wishing to undertake such projects in the future. Given that the difficulty of obtaining sufficient participants has implications on the power of studies in low SES smokers, efforts to obtain sufficient data are important for the ultimate generalisability of the results. High drop-out rates also affect generalisability and can affect internal validity if the drop-out is selective. Use of medical record data from existing services in disadvantaged areas is therefore recommended. Experience from this research teaches that not all services routinely record basic data, such as SES indicators or formal nicotine dependence scores, and that follow-up after the intervention often makes use of self-reported data (chapter 3). The development of quality assurance standards including guidelines for minimum data collection and follow up of at least a sample of participants for CO-validation, as exists in the UK [55], is recommended in the Netherlands to enable services to better monitor the quality of their services and to allow researchers to research the most effective therapy types in different populations of smokers. Such research and monitoring guidelines also exist for national quitlines [56].

Part 2 of this thesis showed that the GFC disproportionately affected certain low SES groups. The effect of the GFC on smoking behaviour in the Netherlands during the study period was perhaps buffered by strong social protection policies at this time. However, it was noted that these policies were cut back and that these cuts were felt by Dutch society after the study period. There is a need for further research encompassing further years to ensure that the effects of these cuts brought to light and vulnerable groups are brought to attention, where necessary.

OVERALL CONCLUSIONS Two main conclusions arise from this thesis. Firstly, smoking cessation services in disadvantaged areas of the Netherlands are able to reach the target group, smokers of low SES, mainly through existing infrastructure (GP), with interventions which increase quit success at 1 year. However, not all methods of support are equally effective and the challenges of recruitment and attendance must be effectively addressed prior to large scale implementation. Secondly, economic recession and a less unaccepting social norm both disproportionately disadvantage some low SES smokers trying to quit. Local level interventions in disadvantaged communities may succeed in increasing smoking cessation rates in disadvantaged smokers, but only under

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certain conditions. It is unlikely that large numbers of smokers from low SES groups will be assisted by the current interventions due to recruitment and retention challenges in disadvantaged areas, despite effective interventions existing. This should not be an excuse for not implementing such interventions, but rather an impetus for a different approach. These recruitment and retention issues may be addressed by policies at a national level to address macro- level factors, such as more accepting social norms toward smoking in low SES groups, which may encourage use of smoking cessation behavioural therapy in those of low SES, and also by encouraging GPs to refer patients in the target group to evidence-based smoking cessation programmes.

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53. de Korte D, van Schayck OCP, van Spiegel P, Kaptien AA, Sachs A, Rutten-van Molken M, Chavannes NH, Tromp-Beelen T, Bes R, Allard R, Peeters G, Kliphuis L, Schouten JW, van Gennip L, van Ommen R, Asin J. Supporting smoking cessation in healthcare: obstacles in scientific understanding and tobacco addiction management Health (N. Y.). 2010;2(11):1272-1279.

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400350-L-bw-Benson 400350-L-bw-Benson Summary Samenvatting Contributing authors Author contributions PhD portfolio Acknowledgements About the author

400350-L-bw-Benson Summary

SUMMARY Evaluation of smoking cessation services in disadvantaged areas of the Netherlands One in two long term smokers will die of illnesses which result from their cigarette use. There is a socioeconomic gradient in both smoking prevalence and cessation, such that those of low socioeconomic status (SES) smoke more and make less successful quit attempts than their high SES peers. Thus those of low SES shoulder a greater burden of smoking-related illness. For this reason it is important that smokers of low SES use evidence-based smoking cessation measures to enhance their chance of quit success. One such measure is smoking cessation behavioural therapy (SCBT), used with or without pharmacotherapy. In England, such therapy is offered nationally in disadvantaged areas, without financial barriers. When the Dutch government decided to reimburse the use of pharmacotherapy in 2011, the financial barrier was removed, and thus a pilot study of this approach could be trialled in disadvantaged areas in the Netherlands.

Part 1 of this thesis aimed to evaluate the effect, optimal method of recruitment, and reasons for attendance of smoking cessation interventions in disadvantaged areas. There are many forms of SCBT available. Research from the UK indicates that rolling group therapy is the most effective therapy in most disadvantaged groups, however, evidence comparing therapy types from other countries is scarce. Chapter 2 examines the success of four different types of SCBT offered by four services in disadvantaged areas of the Netherlands. These are individual face- to-face or telephone counselling, and rolling (where participants can join at any time and the sessions are regularly repeated) or fixed (where all participants begin at the start of the course and no new participants are able to join) group therapy. The SCBT was offered in three different settings: hospital, primary care and community settings. Data for this study was collected by repeated surveys (two services) and by medical record research (two services). We calculated self-reported 12 month quit rate for each intervention. All interventions had higher quit rates than the background quit rate. When interventions were compared, rolling group therapy and individual face-to-face therapy had the highest 12 month quit rates, whereas fixed group counselling and telephone counselling had significantly lower quit success. On the basis of an analysis of the different types of counselling in different settings, we concluded that that SCBT offered in a community or primary care setting was significantly less successful than that offered in a hospital setting. However, when we compared different counselling types in a hospital setting, we found that there was no significant difference in the success of these therapy types in a hospital setting. Thus we concluded that rolling group therapy and individual face-to-face therapy had potential in disadvantaged areas in the Netherlands, however, due to the lower costs of rolling group therapy, this should be the area of focus.

Reach and recruitment of smokers in disadvantaged areas, often including ethnic minority groups, is a significant challenge for interventionists offering SCBT. Because of this known difficulty, multiple reach and recruitment strategies are often enacted in a single area to ensure the greatest number of participants with the greatest mix of characteristics. Chapter 3 examines how participants heard about and were referred to SCBT offered in two disadvantaged areas of

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the Netherlands. A range of methods were used to reach and recruit participants in these areas, including GP, community organisations, word of mouth, other health professionals and media, such as posters, flyers and local newspapers. We found that in both the total participants and those of low SES, the GP was the most common way to recruit and refer participants to the SCBT. Attendance appeared not to be affected by this referral route, such that those who were reached and recruited through the GP attended a similar number of sessions as those who came through other routes.

Attendance of SCBT sessions affects the success of a quit attempt, such that those who attend more sessions are more likely to quit successfully. Participants from low SES groups attend less sessions than their high SES peers. In-depth understanding of the reasons for different attendance patterns in smokers of low SES is required to allow interventionists to better address this issue. In Chapter 4 we examine the motivations, barriers and social support with regard to attendance in smokers attending SCBT in a disadvantaged area. We completed semi-structured in-depth qualitative interviews, which were recorded, transcribed, coded and analysed. We analysed motivations and social support with regard to the Self-Determination Theory. Participants fell into two groups: frequent (missing up to 2 sessions) and infrequent attenders (missing more than 2 sessions). Frequent attenders more often had intrinsic motivation to attend (i.e. attending because it was enjoyable in and of itself) and named more self-determined motivations to attend (e.g. commitment to attendance and wanting to quit) than infrequent attenders. Frequent attenders mentioned no organisational barriers to attendance, such as not being contacted by organisers as expected. While all participants experienced negativity from their social environment with regard to either their quitting or their SCBT attendance, frequent attenders had more social support than infrequent attenders. This chapter concludes with recommendations to increase motivation to attend sessions, as this may increase the number of sessions attended by smokers in disadvantaged areas.

Part 2 of this thesis aimed to explore the influence of the prevailing economic conditions and social norms on inequalities in smoking cessation. Smoking cessation, while done on an individual level, is influenced by macro-level factors. The prevailing socioeconomic conditions and social norms are two such factors which can influence smoking cessation. In 2008 the global economy went into recession, dramatically changing the economic conditions in Europe and elsewhere. People of low SES disproportionately experience the effects of economic downturns. Chapter 5 is a population-based study which examines socioeconomic inequalities in current smoking and smoking cessation in The Netherlands before and during the Global Financial Crisis (GFC). Data from the Health Survey (2004-2011), a repeated cross-sectional survey, was used. Pre-GFC was defined as 2004 – end third quarter 2008 and during-GFC was defined as fourth quarter 2008 – end 2011. SES was measured by income, educational level and neighbourhood disadvantage. Current smoking rates and smoking cessation ratios were calculated. All SES indicators showed higher levels of current smoking and lower levels of smoking cessation in participants of low SES compared with participants of high SES. This occurred in both periods.

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Inequalities in current smoking increased significantly in poorly educated adults of 45-64 years of age, compared with their highly educated peers. Inequalities in smoking cessation increased in low income 18-30 year olds compared with their high income peers. This chapter concludes by stating that overall socioeconomic inequalities in current smoking and smoking cessation were unchanged by the GFC, however, current smoking inequalities by education and smoking cessation inequalities by income increased in specific age groups.

As we have seen, SCBT with pharmacotherapy is an evidence-based smoking cessation intervention. A financial barrier to use of this therapy can prevent those of low SES making use of such interventions. While SCBT was available as part of the basic health insurance in the Netherlands, pharmacotherapy was not included. This changed in 2011, when the Dutch government began to reimburse this therapy. This reimbursement was removed in the subsequent year, thus providing two natural experiments for the study of the effects of such reimbursement on inequalities in pharmacotherapy use in quit attempts. As a previous study had shown no changes in inequalities due to this measure, this study also considered if injunctive norm might play a role in this. Social norms toward smoking can influence quitting behaviour. Social norms can differ between countries, but also between socioeconomic groups within a country. Chapter 6 is a population- based study which examines the effect of reimbursement of smoking cessation pharmacotherapy on inequalities in their use in quit attempts, and, considers the role of injunctive norm in this use. We used data from the DHSSC, which is continuous cross-sectional data, weighted to reflect the Dutch population. We defined SES by income and educational level. Smokers who had made a most recent quit attempt in 2009-2012 were considered. The years considered were 2011 (reimbursement available) and all other years (2009, 2010, 2012) (reimbursement not available). Injunctive norm was determined by perceived social acceptability of smoking in the vicinity of others in Dutch society. This was divided into those who found it mostly acceptable, were neutral or found it mostly unacceptable. This study found that use of pharmacotherapy by smokers in low SES groups did not increase in 2011 more than in those of high SES groups. A smaller proportion smokers of low SES found smoking mostly unacceptable than smokers of either middle or high SES, or than non-smokers of all SES levels. Low SES participants with a mostly acceptable injunctive norm were significantly less likely to use pharmacotherapy. This chapter concludes that reimbursement did not increase the proportion of smokers of low SES attempting to quit using pharmacotherapy to a greater extent than in smokers of high SES. The significantly lower use of pharmacotherapy in quit attempts of smokers of low SES with a positive injunctive norm toward smoking may partially underlie this.

The general discussion, Chapter 7, summarises the findings of each chapter, considers the over- arching limitations of the studies, considers reflections on the studies and provides recommendations for practice and future research. Two counselling types in particular had high quit rates at 12 months when compared with the other counselling types in the study. They also performed well compared with the background quit rate and the results found in similar populations in other studies. The participants of low SES can be reached and recruited in disadvantaged

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areas through the GP, however, with the caveat that overall a low number of participants were recruited. It is possible that attendance may be increased by a focus on making the course more enjoyable. This gives reason for optimism, however, must be considered in the larger smoking cessation context, where most smokers quit without help. Also, smokers of low SES face considerable barriers when attempting to quit, such as unsupportive social environment and negative social norms. Thus, it is recommended that these larger issues be addressed on a national scale, before or while attempting to implement this strategy nationally. Also, GPs in disadvantaged areas need to be equipped with the knowledge of where evidence-based SCBT is provided in their local area and encouraged to refer participants to these providers. Without such actions, it is unlikely that national implementation of smoking cessation services in disadvantaged areas offering free treatment would attract sufficient participants. Both local and national government have a role to play, but this should be done in conjunction for the best results. Future research would be aided by use of medical register data and this would be further aided by national guidelines on the collection of data by smoking cessation clinics.

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SAMENVATTING Evaluatie van stoppen met roken programma’s in achterstandsgebieden van Nederland Een op de twee lange termijn rokers sterft aan een ziekte die ontstaan is als gevolg van roken. Er is ook een sociaaleconomische gradiënt in roken en stoppen met roken: mensen van lage sociaaleconomische status (SES) roken meer en hun stoppogingen zijn minder succesvol dan rokers van hogere SES groepen. Daarom hebben mensen van lage SES groepen meer rook-gere- lateerde ziektes. Voor deze reden is het van belang dat rokers uit lage SES groepen bewezen effectieve hulpmiddelen gebruiken bij het stoppen met roken om hun slaagkans te vergroten. Een van deze hulpmiddelen is stoppen met roken gedragstherapie (smoking cessation behavioural therapy of SCBT) met of zonder farmacotherapie. In Engeland wordt deze therapie landelijk aangeboden in achterstandswijken, zonder financiële barrières. Toen de Nederlandse overheid in 2011 besloot om farmacotherapie te vergoeden, verdween de financiële barrière, en kon er een pilot studie van deze aanpak uitgevoerd worden in achterstandsgebieden in Nederland.

Deel 1 van dit proefschrift heeft tot doel om stoppen met roken interventies in achterstandswijken te evalueren op hun effect, optimale manier van werving en redenen om deel te nemen. Er zijn veel vormen van SCBT mogelijk. Onderzoek uit het Verenigd Koninkrijk (VK) geeft aan dat “rolling” groepstherapie de meest effectieve therapie is voor de meeste mensen uit lage SES groepen, maar er is weinig bewijs over vergelijkingen van SCBT typen uit andere landen. Hoofdstuk 2 gaat in op het succes van vier verschillende SCBT types die worden aangeboden in achterstandsgebieden in Nederland. Deze zijn: individuele face-to-face en telefonische counseling of rolling (waar nieuwe mensen mogen gewoon instromen) en fixed groepstherapie (waar het cursus begint met een aantal deelnemers en niemand nieuw mag daarnaar instromen). De SCBT werd aangeboden in drie verschillende settings: het ziekenhuis, eerstelijnszorg en buurthuiswerk. De data voor deze studie werd verzameld via herhaalde vragenli- jsten of via medisch dossieronderzoek. Voor elke interventie hebben we een zelf-gerappor- teerde 12 maanden stopscore (gestopt met roken) berekend. Alle interventies hadden hogere stopscores dan de stopscore voor de algemene bevolking. Bij het vergelijken van de interventies hadden rolling groepstherapie en individuele face-to-face therapie de hoogste stopscores na 12 maanden, terwijl fixed groepstherapie en telefonische counseling significant minder succes bij het stoppen met roken lieten zien. Op basis van een analyse van de verschillende typen therapie in verschillende settings, constateerden we dat SCBT in een buurt of eerstelijnszorg setting significant minder succesvol waren dan in een ziekenhuis setting. We hebben qua succes echter geen significante verschillen gevonden tussen de verschillende soorten counseling in een ziekenhuis setting. Daarom hebben we geconcludeerd dat vooral rolling groepstherapie en individuele face-to-face therapie potentie hebben in achterstandsgebieden in Nederland, met rolling groepstherapie als belangrijkste focusgebied, vanwege de lagere kosten.

Rokers bereiken en werven in achterstandsgebieden, vaak met etnische minderheden, is een grote uitdaging voor zorgverleners die SCBT aanbieden. Vanwege dit bekende probleem worden er vaak verschillende strategieën voor bereik en werving in een gebied gebruikt om

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zo veel mogelijk deelnemers te krijgen met een zo groot mogelijk diversiteit. Hoofdstuk 3 kijkt naar hoe respondenten hebben gehoord over of zijn doorverwezen naar SCBT in twee achterstandswijken in Nederland. Er zijn in deze gebieden een aantal manieren om rokers te bereiken en werven gebruikt, zoals door de huisarts, door maatschappelijke organisaties, door mond tot mond reclame en door andere zorgverleners en media, zoals posters, flyers en lokale kranten. Wij hebben gevonden dat voor alle respondenten, ook voor lage SES respondenten, de huisarts de vaakst voorkomende manier was om patiënten te werven en doorverwijzen naar de SCBT. Route had geen effect op deelname, dus degene die door de huisarts kwamen, hebben dezelfde hoeveelheid sessies bijgewoond als degene die door andere routes waren gekomen.

Deelname aan SCBT sessies heeft invloed op de kans op succes van een stoppoging. Mensen die meerdere sessies bijwonen hebben een hogere slaagkans. Mensen uit lage SES groepen namen deel aan minder sessies dan mensen uit hoge SES groepen. Een beter begrip van de redenen voor verschillende patronen van deelname onder rokers van lage SES groepen is van belang om dit punt aan te pakken. In Hoofdstuk 4 kijken wij naar de motivatie, barrières en sociale ondersteuning voor deelname van rokers die deelnemen aan SCBT in achterstandswijken. Wij hebben semigestructureerde kwalitatieve diepte-interviews gedaan. Deze zijn opgenomen, uitgeschreven, gecodeerd en geanalyseerd. Wij hebben motivaties en sociale ondersteuning geanalyseerd met behulp van de Self-Determnation Theory. Participanten konden in twee groepen verdeeld worden: frequente deelnemers (tot twee sessies gemist) en infrequente deelnemers (meer dan twee sessies gemist). Frequente deelnemers hadden vaker intrinsieke motivatie tot deelname (zij kwamen omdat het leuk was om te doen) en zij noemden vaker zelf-bepaalde motivaties om deel te nemen (bijv. verbondenheid aan deelnemen en willen stoppen) dan infrequente deelnemers. Frequente deelnemers hebben geen organisatorische barrières benoemd, zoals niet gebeld worden door de aanbieders van SCBT zoals zij hadden verwacht. Terwijl alle deelnemers negatieve reacties hebben ervaren van hun sociale omgeving over stoppen met roken of deelnemen aan SCBT, kregen frequente deelnemers meer sociale ondersteuning dan infrequente deelnemers. Dit hoofdstuk sluit af met aanbevelingen om de motivatie tot deelnemen aan SCBT te verhogen, omdat dit de hoeveelheid sessies die rokers uit lage SES groepen bijwonen zou kunnen verhogen.

Deel 2 van dit proefschrift heeft tot doel om te verkennen wat de invloed is van het heersende economische klimaat en sociale normen op ongelijkheid in stoppen met roken. Hoewel stoppen met roken op een individueel niveau wordt gedaan, wordt het beïnvloed door factoren op macroniveau. Het heersende sociaaleconomische klimaat en sociale normen zijn twee factoren die van invloed kunnen zijn op stoppen met roken. In 2008 ging de wereldeconomie in recessie en dit heeft het economische klimaat in Europa en daarbuiten dramatisch veranderd. Mensen uit lage SES groepen ervaren onevenredig sterk de effecten van economische crises. Hoofdstuk 5 is een populatie-gebaseerde studie die kijkt naar sociaaleconomische ongelijkheden in roken en stoppen met roken in Nederland voor en tijdens de crisis (GFC). Daarvoor gebruikten we data van de Permanent Onderzoek Leefsituatie (POLS) (2004-2011), een herhaald cross-sectionele

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survey. Pre-GFC is gedefinieerd als 2004 tot eind derde kwartaal 2008 en tijdens-GFC is gedefinieerd als vierde kwartaal 2008 tot eind 2011. Sociaaleconomische status is gemeten door inkomen, opleidingsniveau en type wijk (achterstandswijk of niet). De prevalentie van roken en ratio’s van stoppen met roken zijn berekend. Bij alle indicatoren van SES zien we een hoger niveau van roken en lager niveau van stoppen met roken bij respondenten uit lage SES groepen, vergeleken met hoge SES groepen. Dit geldt voor in beide periodes. Ongelijkheid in roken bij volwassenen tussen 45 en 64 jaar werd significant sterker tussen mensen met een laag en mensen met een hoog opleidingsniveau. Ook de ongelijkheid tussen mensen van 18 tot 30 jaar met een laag en met een hoog inkomen werd groter. Dit hoofdstuk concludeert dat over het algemeen sociaaleconomische verschillen in roken en stoppen met roken niet veranderd zijn door de GFC. Echter, in bepaalde leeftijdscategorieën zijn ongelijkheden in roken door naar opleidingsniveau en ongelijkheden in stoppen met roken naar inkomen wel toegenomen.

Zoals wij hebben gezien is SCBT met farmacotherapie een bewezen effectieve interventie voor stoppen met roken. Een financiële barrière tot gebruik van deze therapie kan ervoor zorgen dat mensen van lage SES groepen minder gebruik maken van deze interventie. SCBT viel al langer onder het basispakket van de zorgverzekering in Nederland, maar farmacotherapie was niet daarbij niet inbegrepen. Dit veranderde in 2011, toen de Nederlandse overheid begon met het vergoeden van deze therapie. Deze vergoeding werd het volgende jaar weg echter weer afgeschaft. Dus waren er twee natuurlijke experimenten voor de studie naar de effecten van vergoeding op ongelijkheden in farmacotherapie gebruik bij stoppogingen. Een eerdere studie al had laten zien dat er geen veranderingen waren in ongelijkheden door deze maatregel, onze studie keek ook of de heersende sociale norm een rol zou kunnen spelen. Een sociale norm die negatief staat tegenover roken, kan stoppen met roken bevorderen. De sociale norm kan verschillen tussen landen, maar ook tussen sociaaleconomische groepen binnen een land. Hoofdstuk 6 is een populatie-gebaseerde studie die kijkt naar de effecten van vergoeding van het gebruik van farmacotherapie voor stoppen met roken op ongelijkheden in het gebruik tijdens stoppogingen, waarbij ook de rol van de heersende sociale norm in dit gebruik bekeken wordt. Wij hebben data van het Continu Onderzoek Rookgewonten (COR) gebruikt. Wij hebben SES gedefinieerd op basis van inkomen en opleidingsniveau. Rokers die hun meest recente stoppoging hebben gedaan in 2009-2012 werden meegenomen. De jaren 2011 (wel vergoeding) en 2009, 2010 en 2012 (geen vergoeding) zijn onderzocht. De heersende sociale norm is gemeten als de perceptie van de sociale aanvaardbaarheid van roken in de nabijheid van anderen in de Nederlandse maatschappij. Dit werd verdeeld in drie categorieën, respondenten die het overwegend acceptabel, neutraal of overwegend onacceptabel vonden. Deze studie heeft laten zien dat gebruik van farmacotherapie in 2011 door rokers in lage SES groepen niet meer veranderd is dan in hoge SES groepen. Een kleiner deel van de rokers uit lage SES groepen vond roken overwegend onacceptabel dan rokers uit middel of hoge SES groepen of niet rokers van alle SES groepen. Lage SES respondenten met een sociale norm waarin roken overwegend geaccepteerd werd maakten significant minder gebruik van farmacotherapie. Dit

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hoofdstuk concludeert dat het invoeren van vergoeding van farmacotherapie het percentage lage SES rokers dat een stoppoging deed met farmacotherapie niet is verhoogd in vergelijking met hoge SES. Het significant lagere gebruik van farmacotherapie bij stoppogingen door rokers van lage SES met een positieve sociale norm over roken kan hier misschien aan ten grondslag liggen.

De algemene discussie, hoofdstuk 7, vat de bevindingen uit elk hoofdstuk samen, beschouwt de algemene beperkingen van de studies, kijkt naar reflecties over de studies en geeft aanbevelingen voor de praktijk en toekomstig onderzoek. Twee therapie types hadden hoge stopscores bij 12 maanden in vergelijking met andere therapie typen in de studie. Deze deden het ook goed in vergelijking met de stopscore voor de algemene bevolking en met de resultaten in vergelijk- bare populaties in andere studies. De participanten met een lage SES in een achterstandswijk kunnen worden bereikt en geworven door de huisarts, echter het waren wel kleine aantallen die werden geworven. Het is mogelijk dat deelnemen aan SCBT sessies kan worden gestimuleerd door de cursus leuker te maken. Dit geeft grond voor optimisme, maar moet wel beschouwd worden in het grotere verband van stoppen met roken, omdat de meeste rokers stoppen zonder hulp. Verder ervaren rokers van lage SES groepen aanzienlijke barrières bij het doen van stoppoging, zoals negatieve sociale omgeving en sociale normen. Daarom is het aan te bevelen dat deze grotere kwesties worden aangepakt op een nationaal niveau, voor of terwijl men poogt dit landelijk te implementeren. Ook moeten huisartsen in achterstandswijken de kennis hebben over waar bewezen effectieve SCBT beschikbaar is in hun lokale omgeving en aangemoedigd worden om patiënten door te verwijzen naar deze SCBT. Zonder zulke acties is het onwaarschi- jnlijk dat nationale implementatie van SCBT in achterstandswijken zonder financiële barrières genoeg participanten zou aantrekken. Zowel de lokale als nationale overheid heeft hierin een rol te spelen, maar als maatregelen tegelijkertijd genomen worden zou dit de beste resultaten opleveren. Toekomstig onderzoek zou geholpen worden door gebruik van medische registratie data en het zou nog makkelijker gemaakt kunnen worden door nationale richtlijnen over het verzamelen van data van stoppen met roken klinieken.

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400350-L-bw-Benson Contributing authors

CONTRIbUTING AUTHORS Nina M.M. bogaerts Gera E. Nagelhout VUMC, Dept. Public and Occupational Maastricht University (CAPHRI) Health, EMGO+ Institute Dept. Health Promotion Van Der Boechorststraat 7 Minderbroedersberg 4 - 6 1081 BT Amsterdam 6211 LK Maastricht The Netherlands The Netherlands

Jan-Willem bruggink & Statistics Netherlands Dutch Alliance for a Smokefree Society CBS-weg 11 Eisenhowerlaan 108 6412 EX Heerlen 2517 KL The Hague The Netherlands The Netherlands

Mirte A. G. Kuipers Karien Stronks Academic Medical Centre, University of Academic Medical Centre, University of Amsterdam Amsterdam Dept. Public health Dept. Public Health Meibergdreef 9 Meibergdreef 9 1105 AZ Amsterdam 1105 AZ Amsterdam The Netherlands The Netherlands

Anton E. Kunst Marc C. Willemsen Academic Medical Centre, University of Maastricht University Amsterdam CAPHRI School for Public Health and Dept. Public Health Primary Care Meibergdreef 9 Dept. Health Promotion 1105 AZ Amsterdam Minderbroedersberg 4 - 6 The Netherlands 6211 LK Maastricht The Netherlands

& Dutch Alliance for a Smokefree Society Eisenhowerlaan 108 2517 KL The Hague The Netherlands

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400350-L-bw-Benson Author contributions

AUTHOR CONTRIbUTIONS Chapter 2 - Effects of different types of smoking cessation behavioural therapy in disadvantaged areas in the Netherlands: an observational study. Fiona E. Benson, Vera Nierkens, Marc C. Willemsen, & Karien Stronks. All authors conceived the study. All authors designed the study. FB prepared and analysed the data. All authors contributed to the interpretation of the data. FB drafted the article. All authors contributed to critical revision of the manuscript. All authors approved the final version of the manuscript.

Chapter 3 - Smoking cessation behavioural therapy in disadvantaged neighbourhoods: an explorative analysis of recruitment channels. Fiona E. Benson, Vera Nierkens, Marc C. Willemsen, Karien Stronks. FB, KS and MW conceived the study. All authors designed the study. FB prepared and analysed the data. All authors contributed to the interpretation of the data. FB drafted the article. All authors contributed to critical revision of the manuscript.

Chapter 4 - Wanting to attend isn’t just wanting to quit: Why do some disadvantaged smokers regularly attend smoking cessation therapy while others do not? A qualitative study. Fiona E. Benson, Karien Stronks, Marc C. Willemsen, Nina M.M. Bogaerts, Vera Nierkens. FB participated in study design, data acquisition, analysis and interpretation of data, and drafting the paper. KS contributed to data interpretation and drafting.MW contributed to data interpretation and drafting. NB contributed to data acquisition, analysis and interpretation. VN conceived of the study, participated in its design, contributed to data interpretation and drafting of the manuscript. All authors received and approved the final manuscript.

Chapter 5 - Socioeconomic inequalities in smoking in The Netherlands before and during the Global Financial Crisis: a repeated cross-sectional study. Fiona E. Benson, Mirte A.G. Kuipers, Vera Nierkens, Jan-Willem Bruggink, Karien Stronks, Anton E. Kunst AK, KS and FB conceived the study. AK and MK designed the study. MK prepared and analysed the data. All authors contributed to the interpretation of the data. FB drafted the article. All authors contributed to critical revision of the manuscript.

Chapter 6 - Inequalities in the impact of national reimbursement of smoking cessation pharmacotherapy and the influence of injunctive norms. An explorative study. Fiona E. Benson, Gera E. Nagelhout, Vera Nierkens, Marc C. Willemsen, Karien Stronks FB, VN, MW and KS conceived the idea and participated in the design of the study. GN prepared the data. FB performed the statistical analysis and drafted the manuscript. All authors were involved in the critical revision of the manuscript. All authors read and approved the final manuscript.

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400350-L-bw-Benson PhD portfolio

PHD PORTFOLIO Name PhD student: Fiona Benson

PhD period: January 2011 – July 2015

PhD supervisors: Prof. Dr. Karien Stronks,

Prof. Dr. Marc Willemsen

PhD co-supervisor: Dr. Vera Nierkens

Year Workload (ECTS)

Courses

AMC Graduate School, Academic Medical Centre, University of Amsterdam

Project Management 2012 0.06

Practical Biostatistics, AMC Graduate School 2012 1.1

Advanced biostatistics (AMC Graduate School) 2013 2.1

Educational skills training 2014 0.4

Career development 2014 0.8

EPIDM, VU University

Kwalitatief onderzoek in de praktijk van de gezondheidszorg 2011 1.0 (K78), EPIDM

Missing Data: Consequences and Solutions (WK81), EPIDM 2013 0.5

Seminars, Presentations, Project meetings

Seminars at AMC Dept. of Public health 2011 - 2015 3 (2 oral presentations)

Presentation to the Department of Public Health and Primary 2014 0.1 Care, LUMC, Leiden

Meeting of all project partners, Den Haag 2011 0.1

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400350-L-bw-Benson PhD portfolio

Year Workload (ECTS)

(Inter)national conferences

European Conference on Tobacco or Health? (ECTOH), 2011 1.25 Amsterdam, The Netherlands (poster presentation)

Nederlands Congres voor de Volksgezondheid (NCVGZ) 2011 0.25

Nederlands Congres voor de Volksgezondheid (NCVGZ), Ede, 2013 1 The Netherlands, (oral presentation)

Nederlands Netwerk van Tabaksonderzoek (NNvT), Utrecht, 2013 0.75 The Netherlands (poster presentation)

European Conference on Tobacco or Health? (ECTOH), 2014 1.5 Istanbul, Turkey (poster presentation)

ASH Wales Conference, Cardiff, Wales (oral presentation) 2014 1

Nederlandse Vereniging voor Tropische Geneeskunde en 2014 0.75 Internationale Gezondheidszorg (NVTG) (oral presentation)

Nederlands Netwerk van Tabaksonderzoek (NNvT), Utrecht, 2015 0.75 The Netherlands (oral presenation)

ASH Scotland Conference, Edinburgh, Scotland (oral 2015 1 presentation)

Teaching

Teaching assistent for “Omgaan met Culturele Verschillen” 2013 0.1 given by Dr. I. Rupp

Other

Co-creative workshop, Gemeente Rotterdam, Rotterdam 2013 0.1

Monthly meetings of research group 2011 – 2015 3 ‘Gezondheidsbevordering in achterstandsgroepen’ at Dept. of Public Health, AMC (3 oral presentations)

Peer reviewing - Medical Journal of Australia 2014 0.5

*ECTS = European Credit Transfer and Accumulation System; 1 ECTS credit = 28 hours

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400350-L-bw-Benson Acknowledgements

ACKNOWLEDGEMENTS There are many people who deserve special mention for the support and assistance which they offered me during this PhD trajectory.

I would like to thank my family. Thomas, my wonderful husband, your love and support made this thesis possible. You put up with me throughout and made me smile when the going was tough. You inspire and amaze me every day. I look forward to our next steps together.

Ian & Eliza, my delightful, mischievous, hilarious little bundles of joy and energy, you have brought so much happiness to my life and given me so many new experiences and so much to look forward to. Thank you for putting it all into perspective.

Mum & Dad, thank you for your constant love and support. You taught me to value education, and made huge sacrifices to ensure that mine was a good one. You have always been amazing examples of dedication and hard work. You have supported me, with love, through thick and thin. Thank you with all my heart.

Paulette, thank you for all your love and support over the years. Your kindness, humour and ability to bring out the best in people have enriched my life.

John, you are the best brother in the world. Thank you for always being there for me, no matter what.

Iris, thank you for your support and friendship. And, of course, for introducing me to Guildo Horn, when I needed him most.

Jaap and Hellen, the extra work in the last year wouldn’t have been possible without your help with the children. Thank you.

I would like to thank my supervisors, Prof. dr. Karien Stronks and Prof. dr. Marc Willemsen, and my co-supervisor, dr. Vera Nierkens. Karien, thank you so much for steering the whole process, and also for stepping in and being my daily supervisor for the last part of the project. It was a great privilege to work with you. I regularly stood in awe of your expertise, your clarity of thought and your ability to see the bigger picture. This thesis wouldn’t have been completed without your constant willingness to read yet another draft. I have learned a great deal from you. Thank you.

Marc, the breadth and depth of your knowledge this field is extraordinary; I benefitted greatly from it during the writing of this thesis. You were always able to put things into the wider context of the field. You always looked at points made in the articles from many angles, which really made me think. Thank you for your support and help during this process.

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Vera, thank you for being my daily supervisor for the first three years of this project and my co-supervisor. It was a great pleasure to work with you. Your patience and kindness were very much appreciated. Without your constant efforts, energy, and innovative ideas, this project would surely not have overcome the many hurdles along the way. You always looked at things from a different perspective and brought new insights, which greatly improved the work.

I would like to thank the Members of the Doctorate Committee. Thank you for taking the time to read and consider this thesis. I would like to especially thank Prof. dr. Amanda Amos, who agreed to participate despite having to travel to the Netherlands to do so.

I would like to thank my paranymphs. Jizzo, thank you for your humour, your willingness to help, and your support. You were always able to put things into perspective and offer good advice. The Dutch summary in this thesis is a linguistic triumph due to your help.

Anna, thank you for your friendship. I enjoyed our lunches so much. It was wonderful to laugh and relax, especially when things weren’t so relaxing. Thank you for being there on this journey.

I would like to thank my co-authors. Prof. dr. Anton Kunst, thank you for all your help on the crisis article. Your thorough, careful and dedicated supervision was an honour to experience.

Mirte, thank you for all your hard work on the crisis article. Without you it would never have been written. I greatly enjoyed our discussions.

Gera, thank you for your support as a co-author, and for your help in answering other questions which came up during the writing of my introduction. You always took the time to answer thoroughly, despite your busy schedule. Your help was very much appreciated.

Jan-Willem bruggink, thank you for your help with the crisis article. Your careful reading and suggestions greatly improved it.

Nina, thank you for all your help with the data collection and, also, for your help in dealing with the almost overwhelming amount of data which needed to be analysed for the attendance article. You were always careful and thorough.

I would like to thank my roommates. Thank you to you all for your support. Mirjam, it was a pleasure to share a room with you. Thank you for your kindness when I first arrived. Aimée, thank you for showing me the ropes and providing such a wonderful example of PhD completion. barbara, thank you for your commiseration during my morning sickness with my first pregnancy. Doenja, thank you for your

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friendship. I greatly enjoyed swapping tales of children with you. Danielle, thank you for your friendship and for your help and support. You were always willing to help with tricky transla- tions and searches for obscure Dutch documents. Your optimism was always appreciated. Anke, thank you for your support in the last phase. Luca, thank you for helping me to put it all into perspective.

I would like to thank the research line. Thank you to all the members of the research line, both past and present, for your helpful feedback and suggestions. Some of you deserve especial mention. Janneke, thank you for your honest, careful feedback. Your depth of knowledge of this field was always helpful. Charlotte, Marieke, Jennifer & Linda, when I first arrived I was in awe of how much you all knew. I certainly learned a lot from each of you. And, Charlotte, Jennifer & Linda, I enjoyed swapping stories about our various children. Dorothee, Kirsten, Luuk & Marcel, thank you for showing me another side of public health, and for your feedback. Dorothee, it was always a pleasure to chat with you. Thank you for your humour. Kirsten, thank you for your friendship.

I would like to thank all my colleagues at the Dept. of Public Health at the AMC. I would especially like to thank a few of you individually. Mary, thank you for your open, honest advice and for making me laugh. I enjoyed swapping stories with you and, of course, without you supervising my master’s thesis, this would probably never have happened. Henriette, Nita & Noor, thank you for your constant support and willingness to help. You always made time to help or explain things, despite your very busy schedules. Eva, thank you for holding the fort during my second maternity leave. It was a godsend to come back to such well-organised and thorough work. Adriette, I really enjoyed our early morning chats. Sanne, without you I would never have found enough interviewers. Thank you for your help. Wim, thank you for your help with the last revisions for the contacts article.

I would like to thank all the interviewers & transcribers who worked on this project. Much of the data in this thesis would not have been collected and /or transcribed without the dedicated help of Wilke, Shirin, Onur, Aysel, Jenat, Sara, Mujde, Arje, Loes & xia. I thank you all for the care and effort you put into this work.

I would like to thank all the smoking cessation professionals who supported this project. Monique, you were always willing to help and offer insights, despite your very demanding schedule. Thank you.

Remzi, you cared greatly about those who you coached. Thank you for all your efforts to recruit participants into the course.

Janneke, thank you for all your hard work and willingness to help!

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Roos, Pauline and Tiny, thank you for all for the time and effort which you put into helping me with data collection and answering questions about your programmes so that we could be sure of publishing the right details. You were always willing to help and chapter 6 could not have been written without you all.

Dewi, several of the references in this thesis would not be there without your help. Thank you.

Carl, thank you for your help, both while you were working for STIVORO and afterwards. You were always willing to help answer my questions.

I would like to thank my children’s gastouder. bregje, thanks to you, and your family, for your wonderful care of Ian & Eliza. I never had a single moment’s concern about the kids when I was working, which was a huge help.

I would like to thank my friends. Thank you all for your love & support. Lisa, thank you for making me laugh, especially when things weren’t so funny. Pat & Lionel, thank you for allowing me to get away from it all and spend time with you both. Mary, Susan & Celeste, thank you for our lovely outings.

I would like to wish each of you all the very best for the future.

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400350-L-bw-Benson About the author

AbOUT THE AUTHOR Fiona Benson grew up in New Gisborne, Australia. She completed a medical degree at The University of Melbourne in 2000. After deciding not to continue with medical training, she did a number of jobs in the corporate and third sectors. Fiona met her future husband, Thomas, in an ecovillage in Scotland, shortly after moving to London. She moved to the Netherlands in 2008 to join him, where she did a Master of Health Sciences specialising in Prevention and Public Health at the VU University in Amsterdam and graduated cum laude in 2010. She did an internship for this degree at the Department of Public Health at the Academic Medical Centre, University of Amsterdam. In 2011, she began work on her PhD thesis at the same department, and completed this work in 2015.

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E valuation Invitation to attend the public defence of my doctoral thesis

smoking Evaluation of smoking

cEssation cessation services in

disadvantaged areas of sErvicEs the Netherlands

disadvantagEd

on Friday, 19 February, 2016, at 12.00 noon in

arEas the Agnietenkapel of the University of Amsterdam.

thE n

EthErlands Agnietenkapel Oudezijds Voorburgwal 229-231 1012 EZ Amsterdam

You are warmly invited to the reception which will follow the defence.

Fiona Benson [email protected] Evaluation of smoking cEssation Paranymphs

F. E. Benson sErvicEs in disadvantagEd arEas of Jizzo Bosdriesz [email protected] thE nEthErlands F. E. Benson Anna Font-Gonzalez [email protected]

400350-L-os-Benson Processed on: 12_22_2015