The Relationship Between Shift-Work, Sleep and Mental Health Among Paramedics in Australia and Saudi Arabia

The relationship between shift-work, sleep and mental health among Paramedics in Australia and Saudi Arabia

A thesis submitted in fulfillment of the degree of Doctor of Philosophy

Wahaj Anwar A. Khan BSc, (Medical Sciences, Umm Al-Qura University) MSc, (Occupational and Environmental Health, Monash University)

School of Health and Biomedical Sciences College of Science, Engineering and Health RMIT University July 2020

Declaration

I certify that except where due acknowledgement has been made, the work is that of the author alone; the work has not been submitted previously, in whole or in part, to qualify for any other academic award; the content of the thesis is the result of work which has been carried out since the official commencement date of the approved research program; any editorial work, paid or unpaid, carried out by a third party is acknowledged; and, ethics procedures and guidelines have been followed.

______Wahaj Anwar A. Khan 10/07/2020

Publications/Manuscripts that have arisen as a direct result of this thesis:

(1) Khan, Conduit, Kennedy, & Jackson. (2020). The Relationship Between Shift- work, Sleep and Mental Health Among Paramedics in Australia. Sleep Health, Journal of The National Sleep Foundation. https://www.sciencedirect.com/science/article/abs/pii/S2352721819302645?cas a_token=5doYlmAgDO4AAAAA:XAHQcCtUowSTw1-F7gfaKxxd1-

EMjSw3oSdedIGly5N-OfTmpyyzeeLqBELbqTE4MFV1fvv4D8NX

(2) Khan, W.A.A.; Conduit, R.; Kennedy, G.A.; Abdullah Alslamah, A.; Ahmad

Alsuwayeh, M.; Jackson, M.L. Sleep and Mental Health among Paramedics from

Australia and Saudi Arabia: A Comparison Study. Clocks & Sleep 2020, 2, 246-257. https://dx.doi.org/10.3390/clockssleep2020019

Manuscripts accepted pending minor revisions:

(3) Khan, W., Conduit, R., Kennedy, G. A., & Jackson, M. L. The effect of rotating shift schedules on sleep, mental health and physical activity of Australian paramedics: a field study. Submitted in April 2020, Scientific Reports – Nature.

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Conference abstracts that have arisen as a direct result of this thesis:

(1) Khan, W., Jackson, M., Conduit, R., & Kennedy, G. The effect of rotating shift schedules on sleep, mood, and stress of Australian paramedics: A field study. Abstract presented as an oral presentation in Australasian Chronobiology Society Annual

Meeting, Sydney, 2019.

(2) Khan, W., Jackson, M., Conduit, R., & Kennedy, G. The effect of rotating shift on sleep, mood, and stress of Australian paramedics: A field study. Journal of Sleep

Research, 28: e133_12913. doi:10.1111/jsr.133_12913

Abstract published and presented as a poster discussion in Australasian Sleep

Association Sleep DownUnder, Sydney, 2019. (Travel award).

(3) Khan, W., Jackson, M., Conduit, R., & Kennedy, G. The effect of rotating shift schedules on sleep, mood, stress, energy expenditure and physical activity of

Australian paramedics: a field study. Abstract presented as a poster in World Sleep

Conference, Vancouver, 2019.

(4) Khan, W., Jackson, M., Conduit, R., Kennedy, G. The effect of shift-work and sleep disorders on the mental health of Victorian paramedics. Abstract presented as an oral presentation in Sleep and Brain Health Symposium, RMIT University, Melbourne,

2018.

(5) Khan, W., Jackson, M., Conduit, R., &Kennedy, G. The relationship between

Chronotype and sleep, mental health, and well-being in paramedics. Abstract

iv presented as an oral presentation in Australasian Chronobiology Society Annual

Meeting, Brisbane, 2018. (Travel award).

(6) Khan, W, Jackson, M., Conduit, R., & Kennedy, G. The effect of shift-work and sleep disorders on the mental health of Victorian paramedics. Journal of Sleep

Research, 27: e63_12766. doi:10.1111/jsr.63_12766

Abstract published and presented as poster in Australasian Sleep Association Sleep

DownUnder, Brisbane, 2018.

Acknowledgements

This work could not be completed without the guidance, support, and encouragement of many. A very special and big thanks to my supervisors, Melinda Jackson, Russell

Conduit and Gerard Kennedy for their extraordinary support and guidance inside and outside the academic life. I greatly appreciate their understanding, handling and patience to me as an international student, especially during the first few months of my candidature. Also, their amazing support and help throughout my candidature, and during final months leading to submission. Together, they played a crucial role in the development of my research skills and I will be forever grateful for that and for everything they taught me.

I also could not have completed my study without the love and the support of my family. To my mother, wife, kids, brothers and sister, thank you very much for your endless support throughout my study. It was a very long journey, and I am really grateful for everything you have done for me. To my father, a great and wise man, thank you for everything. A very special thanks to my friends Prerna, Hailey, Ridwan,

Hasan, Bader, Baraa, Adib, Ahmad, M. Shah, M. Refae, and Rakan; your help, understanding and support throughout my study were very important to me and helped me to keep going.

To RMIT, especially the discipline of psychology, thank you for your enthusiasm and cooperation throughout the duration of my candidature. Also, a very special thanks to

Ambulance Employee Victoria Australia (AEVA) and Saudi Red Crescent Authority

(SRCA) for allowing me to conduct my research and to collect data from their paramedics and for their amazing cooperation.

Finally, to my great country Saudi Arabia, to my employer Umm Al-Qura University and to the Saudi Arabia Cultural Mission in Australia, thank you very much for your support, help and for giving me this opportunity to pursue my dreams.

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Table of contents

Declaration ...... ii Publications/Manuscripts that have arisen as a direct result of this thesis: ...... iii Conference abstracts that have arisen as a direct result of this thesis: ...... iv Acknowledgements ...... vi Table of contents ...... viii List of Tables ...... xi List of figures ...... xii Glossary of Abbreviations ...... xiii Abstract ...... 15 Chapter One : Literature review ...... 17

1.1 Paramedics ...... 17 1.2 Impact of night-shift and rotating shift on health and safety ...... 18 1.3 Sleep and circadian rhythm ...... 20 1.4 Rotating shift work and recovery ...... 21 1.5 Mental health and sleep in paramedics ...... 22 1.6 Mental health ...... 23 1.6.1 Stress ...... 23 1.6.2 Anxiety ...... 27 1.6.3 Depression ...... 27 1.6.4 Post-traumatic stress disorder ...... 28 1.7 Occupational Suicide ...... 28 1.8 Shift work and sleep disorders ...... 30 1.8.1 Shift work disorder (SWD) ...... 31 1.8.2 Insomnia ...... 32 1.8.3 Obstructive sleep apnoea (OSA) ...... 33 1.8.4 Parasomnia ...... 34 1.8.5 Narcolepsy ...... 34 1.9 Chronotype ...... 35 1.10 Objective sleep measures ...... 36 1.11 Sleep and mental health ...... 37 1.12 Paramedics from Saudi Arabia ...... 38 1.13 Accidents and work-related injuries ...... 40 1.14 The hierarchy of controls ...... 42 1.15 Summary and focus of this thesis ...... 43 1.16 Thesis Aims ...... 44

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Chapter Two : The Relationship Between Shift-work, Sleep and Mental Health Among Paramedics in Australia ...... 46

Abstract ...... 47 2.1 Introduction ...... 48 2.2 Method ...... 52 2.2.1 Participants ...... 52 2.2.2 Materials ...... 53 2.2.3 Procedure ...... 56 2.2.4 Statistical analyses ...... 56 2.3 Results ...... 57 2.3.1 The prevalence of self-reported sleep and mood disorders in paramedics compared to established normative population data...... 58 2.3.2 The association between sleep disturbances, stress, fatigue, and general health, and mental health outcomes...... 62 2.3.3 The association between self-reported sleep quality, mental health, and well-being and chronotype...... 65 2.4 Discussion ...... 67 Chapter Three : Sleep and mental health among paramedics from Australia and Saudi Arabia: a comparison study ...... 73

Abstract ...... 74 3.1 Introduction ...... 75 3.2 Method ...... 77 3.2.1 Participants ...... 77 3.2.2 Materials ...... 77 3.2.3 Procedure ...... 78 3.2.4 Statistical analyses ...... 81 3.3 Results ...... 81 3.3.1 A comparison between Saudi and Australian paramedics across sleep and mental health outcomes ...... 83 3.3.2 A comparison between Saudi and Australian paramedics across General Health Questionnaire (SF-36) subscales ...... 87 3.4 Discussion ...... 89 Chapter Four : A field investigation of the relationship between rotating shifts, sleep, mental health and physical activity of Australian paramedics ...... 98

Abstract ...... 99 4.1 Introduction ...... 100

4.2 Method ...... 102 4.2.1 Participants ...... 102 4.2.2 Materials ...... 103 4.2.3 Procedure ...... 105 4.2.4 Statistical Analyses ...... 107 4.3 Results ...... 107 4.3.1 Sleep and sleepiness ...... 108 4.3.2 Mood, stress & fatigue ...... 112 4.3.3 Physical activity ...... 117 4.4 Discussion ...... 118 Chapter Five : General discussion ...... 126

5.1 Summary of main experimental findings ...... 126 5.2 Sleep and mental health ...... 129 5.3 Paramedics from Saudi Arabia ...... 132 5.4 In-field investigation ...... 133 5.5 Acute and chronic consequences ...... 137 5.6 Limitations ...... 138 5.7 Recommendations and future directions ...... 142 5.8 Conclusions ...... 144 References ...... 146 Appendices ...... 164

List of Tables

Table 1.1. A literature summary of the prevalence of sleep and mental health

outcomes in studies of paramedics...... 24

Table 2.1. The list of the questionnaires used in the present study...... 54

Table 2.2. The list of studies containing the reference populations for each

questionnaire...... 55

Table 2.3. Scores of the SF-36 subscales from Australian paramedics compared to

Australian general population norms...... 59

Table 2.4. Correlations between mental health and sleep variables ...... 63

Table 2.5. Stepwise linear regression predictors of depression and anxiety...... 64

Table 2.6. Study outcomes across the three chronotype groups ...... 66

Table 3.1. Validated sleep and mental health questionnaires used in the study...... 79

Table 3.2. Sample characteristics using independent samples t-test with effect size.

...... 82

Table 3.3. Means and standard deviations of Saudi and Australian paramedics across

study variables...... 84

Table 3.4. Incidences of Saudi and Australian paramedics across study variables. . 85

Table 3.5. Comparison of means and standard deviations for the general health

questionnaire (SF-36) subscales...... 88

Table 4.1 shows the mean and standard errors of the outcome variables from the

PANAS…………………………………………………………………………………….113

Table 1.2. Means and standard errors of the data from the BodyMedia SenseWear

Armband…………………………………………………………………………………..117

List of figures

Figure 1.1. The hierarchy of controls, which is used in the field of occupational safety

and health...... 42

Figure 2.1. The prevalence of different sleep disorders in paramedics and in the

general population...... 60

Figure 2.2. The mean and standard errors of sleep and mental health outcomes in

paramedics and in the general population...... 61

Figure 4.1. The study procedure and duration throughout a single rotated shift

schedule...... 106

Figure 4.2. Average sleep outcomes recorded by the actigraphy...... 111

Figure 1.3. The average levels of sleepiness reported by paramedics…………….111

Figure 1.4. The average levels of stress reported by paramedics………………….114

Figure 1.5. The average levels of fatigue reported by paramedics…………………116

Figure 5.1. The general findings of the project, how rotating shift work is impacting

paramedics...... 127

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Glossary of Abbreviations

SCN Suprachiasmatic nucleus

PTSD Post-traumatic stress disorder

SWD Shift work disorder

OSA Obstructive sleep apnoea

OSHA Occupational Safety and Health Act

AEAV Ambulance Employees Australia Victoria

SF-36 General Health Questionnaire

PSS Perceived Stress Scale

BDI-SF Beck Depression Inventory-Short Form

STAI-SF State-Trait Anxiety Inventory-Short Form

SWDSQ Shift-work Disorder Screening Questionnaire

PSQI Pittsburgh Sleep Quality Index

PSQI-A Pittsburgh Sleep Quality Index-Addendum

ESS Epworth Sleepiness Scale

ISI Insomnia Severity Index

BQ Berlin Questionnaire

UNS Ullanlinna Narcolepsy Scale

FSS Fatigue Severity Scale

MEQ Horne and Ostberg Morningness-Eveningness Questionnaire

BAQ Bruxism Assessment Questionnaire

BMI Body mass index

SRCA Saudi Red Crescent Authority

MANCOVA Multivariate analysis of covariance

BSA BodyMedia SenseWear Armband

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GSR Galvanic skin response

WASO wake after sleep onset

KSS Karolinska Sleepiness Scale

PANAS Positive Affect and Negative Affect Scale

PSD Pittsburgh Sleep Diary

TST Total sleep time

TIB Time in bed

KJ Kilojoules

μS Microsiemens

CBT-I Cognitive behavioral therapy for insomnia

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Abstract

Paramedics often perform shift work duties in conflict with their natural sleep patterns, which can cause chronic circadian misalignment and numerous health problems including; insomnia, shift work disorder, depression, anxiety, and stress.

Furthermore, little is known about the cross-cultural or universal applicability of findings from studies of western paramedics for paramedics in other world regions.

This project aimed to investigate paramedics via surveys assessing the prevalence of sleep and mental health issues, the role of chronotype, and the relationship between these variables in Australian and Saudi paramedics. A field study investigated the acute effects of a rotating shift schedule on sleep, mood, stress, fatigue, sleepiness, energy expenditure, and physical activity of Australian paramedics.

A total of 136 Australian paramedics (M age = 39.1, SD = 12.1 years) and 104

Saudi paramedics (M age = 32.5, SD = 6.1 years) responded to the two surveys.

Generally, paramedics from both countries reported significant negative mental health outcomes with insomnia being a significant contributor to the burden of depression and anxiety among Australian paramedics. Significantly higher rates of depression,

PTSD, insomnia, and fatigue, along with significantly poorer physical functioning were observed among Saudi paramedics when compared to paramedics from Australia that was explained by the higher working and driving durations of the Saudi paramedics.

Also, Australian paramedics with evening chronotype reported poorer sleep and mood outcomes compared to morning types.

A total of 15 paramedics participated in the field study (M age = 39.5; SD = 10.7 years). Paramedics who worked in rotational shifts showed sleep restriction during the

15 night shift. Paramedics also reported significant levels of stress, fatigue, and sleepiness after the end of the night shift and during the entire day one of recovery.

The relationship between sleep and mental health is complex and may be bidirectional. In paramedics, sleep issues potentially exacerbate the increased burden of mental health concerns, especially depression and anxiety. Addressing sleep issues and/or matching chronotype to shift preference may help to improve the mood, sleep and well-being. Finally, there is a need to investigate the cognitive abilities of the paramedics, especially paramedics working in rotating shift.

Chapter One – Literature review

Chapter One : Literature review 1.1 Paramedics

Emergency medical services provide vital prehospital support and unplanned care to patients with serious and minor injuries. According to the Australian government, 17,800 paramedics were active in Australia in 2016, and this figure is expected to exceed 18,000 in 2020 (General Authority for Statistics, 2017).

Paramedics respond to three million requests for emergency medical support every year across Australia (Maguire, O'Meara, Brightwell, O'Neill, & Fitzgerald, 2014). From

2015–2016, Victorian paramedics received more than 800,000 requests for emergency medical support, and more than half of these required transportation to the hospital via an ambulance. In the same year, about 580,000 emergency road accidents were attended by paramedics in Victoria (which equates to an accident every minute) (Ambulance Victoria, 2017).

The role of a paramedic is crucial. Considerable knowledge and training are required as it involves serious incidents, the need to make critical decisions, and having to respond to natural disasters. The need for hospital transportation is usually determined by paramedics, and calls may not involve the hospital in some cases.

Thus, critical decisions and demands must be made within a short period to keep casualties to a minimum (Committee on Guidance for Establishing Crisis Standards of

Care for Use in Disaster Situations, 2012). Because of the continuous demand for emergency support (day and night), paramedics are obliged to work irregular schedules (nights and shift rotations) outside the standard day shift (9 a.m. to 5 p.m.)

(National Sleep Foundation, 2017).

Chapter One – Literature review

1.2 Impact of night-shift and rotating shift on health and safety

The adverse consequences of shift work have been well described in the literature, and there is now evidence to suggest that it is becoming an increasingly serious public health issue (Costa, 2010). According to Zverev and Misiri (2009), sleep deprivation is the main adverse outcome of shift work (Zverev & Misiri, 2009). In turn, sleep deprivation may contribute to the onset of many health issues, including mental health disorders (Fernandez-Mendoza & Vgontzas, 2013). Global levels of stress and depression are high among paramedics, with the implication that the health and safety of both patients and paramedics are potentially compromised (Bajraktarov et al.,

2011).

Night shift work increases the risk of not only sleep deprivation, but also fatigue, accidents, stress, depression, absenteeism, low performance, and chronic disease

(Akerstedt & Wright, 2009; Dai et al., 2019; Ferri et al., 2016; Ganesan et al., 2019;

Lee et al., 2016; van Drongelen, Boot, Hlobil, van der Beek, & Smid, 2017; Wang,

Armstrong, Cairns, Key, & Travis, 2011). Exposure to light during the day, the time in which night workers are expected to sleep, can cause sleep delays and insomnia

(Bajraktarov et al., 2011). In Australia, 15% of paramedics have reported that night shifts are too long, with no time for breaks. In the same study, 16% of the paramedics had symptoms of disruption to their circadian rhythms and poor sleep, especially just prior to the start of the shift (Paterson, Sofianopoulos, & Williams, 2014). Nurses and medical residents have reported falling asleep while driving at least once a month due to exhaustion from working a fixed night shift. The risk of car accidents was determined to be more than double on night shift compared to standard day shift (Barger et al.,

2005; Scott et al., 2007). The National Institute for Occupational Health and Safety in the United States has reported that night shift workers have an increased risk of

Chapter One – Literature review absenteeism and a lower rate of productivity than day workers (Fekedulegn et al.,

2013). Working night shifts may also increase the risk of chronic diseases such as cardiovascular disease, diabetes mellitus, and obesity (Boggild & Knutsson, 1999;

Niedhammer, Lert, & Marne, 1996; Theorell & Akerstedt, 1976). This is a significant challenge to ensuring the health and well-being of the public and workers which also negatively impacts other stakeholders.

Rotational shift work, which is the integration of a night and day shift in one schedule, is more common today than fixed shifts (Costa, 2010). Usually, some recovery time is factored into work rosters to allow for recovery from previous schedule/adaptation to the new schedule (Costa, 2010), but sleep restriction is common for both types of shifts. Greater total sleep time has been reported by those who work a normal day shift or night shift than people working rotating shifts (Akerstedt

& Wright, 2009; Zverev & Misiri, 2009). In line with this, an increased risk of work- related accidents and errors has been found in relation to workers on rotating shifts compared to standard shift workers (Gold et al., 1992). In addition, lower occupational satisfaction, higher stress levels, more fatigue, poor sleep quality, and a reduced quantity of sleep were attributed to rotational shift work among nurses in Italy (Ferri et al., 2016). Similarly, rotational shift nurses in the United States were found to experience higher stress levels than normal day shift workers. Overall productivity has been shown to be the lowest among rotational shift nurses (Coffey, Skipper, & Jung,

1988). While the outcomes of rotational shifts are understood to be adverse, further research into the unique effects in paramedics is warranted due to the already traumatic and stressful nature of this work. A better understanding of paramedic’s recovery from shift rotation, mental health and incidence of sleep disorders, will be invaluable for informing work practices and operational policy for this profession.

Chapter One – Literature review

Paramedics around the world work in various types of shifts. For example, the most prevalent shift in Australia is a combination of day (10hr) and night (14hr) duties in a single roster for four days including four days of break between shifts (Khan,

Conduit, Kennedy, & Jackson, 2020). The most common shift in the USA is the 24hr on and 48hr off (Patterson et al., 2012), In Saudi Arabia, paramedics work in a similar shift to Australian paramedics, a combination of day (12hr) and night (12hr) duties in a single roster for four days with only three days of recovery/break between shifts

(Khan; Conduit, 2020).

1.3 Sleep and circadian rhythm

The system of biological timing (circadian rhythms) in humans regulates the normal state of sleep by initiating sleep at night and wakefulness in the daytime.

Circadian rhythms are controlled by the suprachiasmatic nucleus (SCN), known as the circadian master clock, which is located in the hypothalamus (Jin, Hur, & Hong, 2017).

Normally, sleep patterns are controlled by the biological clock, which generates and controls the daily circadian rhythmicity increasing alertness during the daytime and decreasing alertness during the night time. This process of circadian rhythmicity is counteracted by a sleep homeostatic pressure that builds across waking hours.

Normally, these two processes work in harmony in a rhythm together with the light/dark cycle to sustain alertness during the day (at work) and to reduce alertness during the night to allow sleep. Working night shifts means that workers are awake when their circadian rhythms promoting sleep and decreasing alertness, and sleeping when their circadian rhythm is promoting wakefulness and increasing alertness, the exact opposite to the natural biological rhythm. This leads to sleep disturbances when attempting to sleep during the day, and excessive sleepiness while awake (S. M.

James, K. A. Honn, S. Gaddameedhi, & H. P. A. Van Dongen, 2017). Melatonin is a

Chapter One – Literature review hormone produced by the human body and controlled by the SCN to regulate the sleep/wake cycle. The release of this hormone increases at night and decreases during the day, which is related to the light/dark cycle. Working night shifts may compromise the normal level of melatonin and decreases its secretion overtime (Jin et al., 2017). Thus, shift work can compromise normal sleep and lead to the development of chronic sleep problems (Jin et al., 2017).

Therefore, irregular shift schedules, especially rotating shifts that require night work and daytime sleep, contribute directly to a disruption of the natural circadian rhythms and their interaction with the surrounding environment (e.g., the day/night cycle or light/dark cycle) (Turek, 1986). Disruption to the natural cycle causes sleep restriction (e.g., the ability to initiate or maintain sleep is harder) together with other consequences of sleep restriction, such as impaired alertness and performance, diminished working memory, compromised decision-making, and mental health disturbances (Figure 1.1) (Ferguson & Paterson, 2017). Disruption of circadian rhythms is the most critical outcome associated with working irregular shift schedules, as it can negatively impact both health and safety over the long-term.

1.4 Rotating shift work and recovery

Rotating shift workers rely heavily on breaks between shifts to recover from the consequences of shift work. Recovery is defined as the break/off days that is given after every shift to allow for improvement in occupational psychological and physical fatigue (Haluza, Schmidt, & Blasche, 2019).These consequences may include sleep restriction, stress, or mood deficits, which are all linked to sleep debt due to night shift commitments (Horrocks, Pounder, & Group, 2006). Nurses have reported significantly shorter sleep duration, higher rates of fatigue, and lower alertness levels for up to two

Chapter One – Literature review days after the end of a night shift when compared to baseline (Haluza et al., 2019).

One study indicated a need for at least three days of recovery to return to baseline functioning (Totterdell, Spelten, Smith, Barton, & Folkard, 1995). Another recent study reported that nurses also needed at least three days of recovery time after the end of night duty to recover from significant levels of fatigue and distress (Haluza et al., 2019).

In fact, one study reported that workers with disrupted circadian rhythms may need at least six days of recovery to readjust back to normal after night duty (Bjorvatn,

Kecklund, & Akerstedt, 1998). Recovery times between shifts are necessary for workers to return to normal functioning, and the time required may vary depending on the workload and type of occupation, but the majority of studies recommended at least three days of recovery between rotating shifts. After the current literature analysis and learning how valuable such information is, it appears there is a lack of studies investigating recovery time in paramedics, indicating an urgent need for more studies in this area.

1.5 Mental health and sleep in paramedics

After searching and assessing the current literature, 15 studies investigating mental health or sleep in paramedics were found (Table 1.1). Three studies were from

Australia, one from Saudi Arabia and the rest mainly from Western countries. The majority of the studies were cross-sectional and aimed to assess the prevalence of either mental health or sleep disorders. The main focus for most of the reports was to assess mental health, few investigated sleep issues. No study investigated the interaction between mental health and sleep disturbances. A more detailed review is presented in the following sections.

Chapter One – Literature review

1.6 Mental health

1.6.1 Stress

Stress is known as a physiological response to any intrinsic or extrinsic stimulus

(Yaribeygi, Panahi, Sahraei, Johnston, & Sahebkar, 2017). Stress arising from a range of factors is common in the workplace, particularly among emergency medical services (EMS) workers, as their work involves dealing with different shifts, sleep restrictions, and accidents (Ferri et al., 2016; Halpern, Maunder, Schwartz, &

Gurevich, 2014; Han, Kim, & Shim, 2012). High levels of stress and a significant elevation in stress-related hormones (cortisol and epinephrine) have been observed in paramedics during days at work as compared to days off (Dutton, Smolensky,

Leach, Lorimor, & Hsi, 1978). Elevated stress levels have been found among paramedics in Greece (Lyrakos et al., 2013), more than the levels seen for any other healthcare personnel. In Australia, 15% of paramedics reported high levels of stress

(Courtney, Francis, & Paxton, 2013). In addition, about 90% of Canadian paramedics reported significant levels of stress (Hegg-Deloye et al., 2015). Certainly, stress is common among paramedics, but this information needs further investigation and updating to help in developing appropriate control and preventive measures. Most of the studies measured stress subjectively in cross sectional designs, indicating a need to assess stress objectively in a different design (observational field studies) to allow recording day-to-day variations in stress levels.

Chapter One – Literature review

Table 1.1. A literature summary of the prevalence of sleep and mental health outcomes in studies of paramedics. Study Population Methods Measures Outcomes

Age M (SD) Prevalence % or years or M(SD) range

(Courtney et al., 2013) Australia Cross-sectional Depression Anxiety Stress Scales Stress = 15% 21; stress (>6) and anxiety (>10) (n = 150) subscales. Anxiety = 12% 40 (8.5) (Sofianopoulos, Williams, Australia Cross-sectional Beck Depression Inventory (>19), Depression = 27% Archer, & Thompson, Epworth Sleepiness Scale (>10), 2011b) (n = 60) Berlin Questionnaire, and Pittsburgh EDS = 40% Sleep Quality Index (>5) 39.7 PSQ = 68% Fatigue = 92% OSA = 21% (Paterson et al., 2014) Australia Qualitative Factors underlying fatigue in Working time, sleep, paramedics workload, health and (n = 49) well-being, work–life 38 (9.7) balance and environment (Alharthy, Alrajeh, Saudi Cross-sectional Generalized anxiety disorder-7 (>10) Anxiety = 52% Almutairi, & Alhajri, 2017) (n = 135) (30-40)

Chapter One – Literature review

(Bentley, Crawford, USA Cross-sectional Depression Anxiety Stress Scale-21 Anxiety = 7% Wilkins, Fernandez, & anxiety subscale (>7) Studnek, 2013) (n = 34,340) (Patterson, Suffoletto, USA Cross-sectional Pittsburgh Sleep Quality Index (>5), Fatigue = 45% Kupas, Weaver, & and Chalder Fatigue Questionnaire Hostler, 2010) (n = 119) (>4) PSQI = 9.2(3.7) (40-49) (Straud, Henderson, USA Cross-sectional Posttraumatic Stress Disorder PTSD = 26.2(9.5) Vega, Black, & Van Checklist–Civilian (>44), Hospital Hasselt, 2018) (n = 125) Anxiety and Depression Scale (>8), Depression = 3.6(2.6) and Pittsburgh Sleep Quality Index (> 40) Anxiety = 5.7(3.6) (>5) PSQI = 6.5(3.6) (Wild et al., 2016) UK Prospective Cohort Life Events Checklist (self-report) Depression = 11% and The Depressive Attributions (n = 453) Questionnaire (>18) PTSD = 8% 30.3 (7.7) (Hegg-Deloye et al., 2015) Canada Cross-sectional Job Content Questionnaire (>7) Stress = 90% (n = 295) 35.8 (0.6) (Guadagni, Cook, Hart, Canada Cross-sectional Pittsburgh Sleep Quality Index (>5) PSQI = 9.6(2.4) Burles, & Iaria, 2018) (n = 41) 33.2 (5.5)

Chapter One – Literature review

(Kukowski, King, & Canada Cross-sectional Posttraumatic Stress Disorder PTSD = 36.7 ± 14.2 DeLongis, 2016) Checklist–Civilian (>44) and (n = 87) Pittsburgh Sleep Quality Index (>5) PSQI = 2.9 ± 0.5 42.1 (8.3) (Fjeldheim et al., 2014) South Africa Cross-sectional Centre for Epidemiological Studies Depression = 28% Depression Scale (>16), and (n = 131) Davidson Trauma Scale (>40) PTSD = 16% 22.05 (Iranmanesh, Tirgari, & Iran Cross-sectional Mississipi scale for post-traumatic PTSD = 90% Bardsiri, 2013) stress disorder (>65) (n = 150) 29.3 (6.0) (Streb, Häller, & Michael, Germany Cross-sectional Posttraumatic Stress Diagnostic PTSD = 15% 2013) Scale (>20) (n = 668) 36.6 (8.3) (Berger et al., 2007) Brazil Cross-sectional Posttraumatic Stress Disorder PTSD = 20% Checklist–Civilian Version (>44) (n = 233)

Note, PTSD = Post-traumatic stress disorder, EDS = excessive daytime sleepiness, OSA = obstructive sleep apnea; USA = United States of America, and UK = United Kingdom. The prevalence values were assessed based on cut offs from the questionnaires.

Chapter One – Literature review

1.6.2 Anxiety

Anxiety, or a constant feeling of being overwhelmed, worried, and afraid, is one of the most prevalent mental health concerns worldwide (Bandelow, Michaelis, &

Wedekind, 2017). Anxiety can be triggered by the workplace and may cause occupational disability (Nash-Wright, 2011). Sleep disturbances and stress are among the biggest contributors to the onset of anxiety (Staner, 2003). A recent report stated that 52% of paramedics in Saudi Arabia reported significant anxiety symptoms

(Alharthy et al., 2017), while 12% of Australian paramedics reported significant signs of anxiety (Courtney et al., 2013). In the United States, 7.2% of paramedics reported elevated levels of anxiety symptoms (Bentley et al., 2013). Self-reported signs of anxiety among paramedics vary from one country to another, which may be attributed to a plethora of factors (e.g. different occupational responsibilities, or variations in stressors). It is crucial to investigate the underlying causes of anxiety among paramedics.

1.6.3 Depression

Depression is a mood disorder that causes a constant sensation of sadness and a loss of interest in things that would otherwise be enjoyed (Paykel, 2008). Similar to anxiety, depression can cause occupational disability and decreased productivity

(Battams et al., 2014). About 27% of paramedics in Australia have reported experiencing depressive symptoms (Sofianopoulos et al., 2011b). Signs of major depression were identified in 11% of newly recruited paramedics during their first week on duty in a study conducted in the United Kingdom, in which paramedics were interviewed every four months. In addition, these signs were shown to persist during the 24-month study period (Wild et al., 2016). A report from South Africa indicated

Chapter One – Literature review positive depressive signs in 28% of the paramedics (Fjeldheim et al., 2014). However, there is no information in the current body of literature about depression among paramedics in Saudi Arabia.

1.6.4 Post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is a mental disorder resulting from a traumatic incident or intense stress that can lead to chronic mental or physical disorders (Bisson, Cosgrove, Lewis, & Robert, 2015). It has a strong association with increased morbidity through workplace injuries, high blood pressure, high cholesterol levels, obesity, cardiovascular disease, anxiety, and depression (Ghisi et al., 2013;

McFarlane, 2010). It is prevalent in paramedics owing to the nature of their working environment. In Iran, 94% of paramedics reported having symptoms of PTSD

(Iranmanesh et al., 2013). The prevalence of PTSD among paramedics in Germany was cited as 15% (Streb et al., 2013), while another report revealed that 20% of

Brazilian paramedics reported positive PTSD symptoms following screening for the disorder (Berger et al., 2007). However, outcomes from a national survey reported that

8% of Australian paramedics showed signs of PTSD (David Lawrence, 2018). PTSD is common in paramedics and has been linked to the extreme levels of occupational stress and the presence of other chronic stressors that they face (Donnelly, 2012).

This supports the assumption that exposure to trauma in the workplace increases the risk of PTSD.

1.7 Occupational Suicide

Occupational or work-related suicide is a growing international crisis, and although the incidence is low, it is still a disturbing phenomenon. Occupational suicide is known as causing self-harm or severe injury with intent to die due to occupational-

Chapter One – Literature review related factors such as low occupational security, low income or occupational stress

(CDC, 2019). The highest rate of reported work-related suicide was in South Korea, followed by Hungary and Japan (Targum & Kitanaka, 2012). It has been suggested that overextension by the individual and high work-related demands and stressors directly contribute to suicide or suicide attempts (Routley & Ozanne-Smith, 2012;

Targum & Kitanaka, 2012). In Australia, from 2000 to 2012, 110 occupational suicides were recorded via the National Coronial Information System. The NCIS included professions that are at high risk and excluded all other professions due to the difficulty in identifying and separating cases (National conoronial information system (NCIS),

2010). Police officers (62 cases) accounted for the majority of suicides, followed by paramedics (26 cases) and firefighters (22 cases). More than 80% of the deceased paramedics were males aged 30–49. Depression had been formally diagnosed in 35% of the deceased paramedics, and it was found that 30% of them had a history of self- harm. Signs of depression were identified by relatives in the remaining paramedics

(National conoronial information system (NCIS), 2010). In the United States, Stanley et al. reported that paramedics were at increased risk of suicidal thoughts due to occupational stress and PTSD (Stanley, Hom, & Joiner, 2016). Police officers in the

United States who work irregular or extended shifts are at increased risk of attempting suicide or having suicidal thoughts (Violanti et al., 2008). Higher rates of mental health issues, including PTSD, depression, and stress, are the primary contributors to work- related suicides or suicidal ideation (Gradus et al., 2010; Pompili et al., 2013; Sokero et al., 2003). Occupational suicide is a complicated public health matter and is of great concern globally and working too hard or engaging in shift work can lead to sleep disturbances and mental exhaustion, thus increasing suicidal behaviour among workers. Although suicidality was not examined directly in this thesis, the impact of

Chapter One – Literature review mental health and sleep could put paramedics at risk of suicide, and therefore addressing these issues may help to reduce the prevalence of occupational suicide.

Stressors that range from mild to severe can be found in any working environment. Mostly, they relate to events inherent in the job, such as shift work, an excessive workload, and inadequate experience. However, chronic circadian misalignment is considered to be one of the main contributors to mental health disturbances, especially among paramedics, as they usually have to work according to different shift schedules, which makes them easily susceptible to chronic sleep restrictions (Institute of Medicine (US) Committee on Sleep Medicine and Research;

Colten, 2006; Krystal, 2012). Global levels of stress, anxiety, PTSD, and depression are unquestionably high in paramedics, with the implication that the health and safety of both patients and paramedics are compromised (Bajraktarov et al., 2011). In general, there is a clear relationship between mental health and sleep (Scott, Webb,

& Rowse, 2017), yet it needs more investigation when it comes to emergency medical personnel.

1.8 Shift work and sleep disorders

Performing shift work is considered to be a risk factor for many sleep disorders, including shift work disorder (SWD), insomnia, and obstructive sleep apnoea (OSA)

(Paciorek et al., 2011; Vallieres, Azaiez, Moreau, LeBlanc, & Morin, 2014; Wright,

Bogan, & Wyatt, 2013). Shift work may also worsen a current underlying condition

(Paciorek et al., 2011). Shift workers report having a number of sleep issues, including insomnia, excessive daytime sleepiness, and OSA (Rajaratnam, Howard, &

Grunstein, 2013). It has been reported that a protracted loss of sleep may also contribute to other chronic illnesses, such as obesity, diabetes mellitus, cardiovascular

Chapter One – Literature review diseases, and hypertension (Institute of Medicine (US) Committee on Sleep Medicine and Research; Colten, 2006; Schlafer, Wenzel, & Hogl, 2014).

1.8.1 Shift work disorder (SWD)

SWD is a sleep condition that triggers signs of excessive sleepiness and insomnia, which resulted from work schedule (Flo et al., 2012). Generally, the signs of

SWD include trouble sleeping, excessive sleepiness, and fatigue, all of which can affect overall performance, work and personal life (Jehan, Zizi, Pandi-Perumal, Myers, et al., 2017). It is estimated that 10% of US shift workers have SWD (Roth, 2012). This places them at an elevated risk of accidents, sleep-related issues, decreased productivity, mental health issues, cardiovascular disease, cancer, and gastrointestinal diseases (Roth, 2012). While many studies have not assessed SWD directly, they have reported on SWD symptoms, including fatigue and sleepiness. In a previous Australian report, 92% of paramedics reported significant levels of fatigue, with 40% experiencing excessive daytime sleepiness and 68% reporting poor sleep quality (Sofianopoulos et al., 2011b). In a study of paramedics in the United States,

45% reported significant levels of fatigue, and the mean sleep quality results were at unhealthy levels (Patterson et al., 2010). Among other shift workers, 63% of rotating shift workers from Japan reported significantly extreme daytime sleepiness and poor sleep quality (Taniyama, Nakamura, Yamauchi, Takeuchi, & Kuroda, 2015). About half of the nurses in a Norwegian study reported symptoms of SWD (Flo et al., 2012). The symptoms of SWD, especially poorer sleep quality, can impact mental health, and a significant association has been found between higher rates of depression and anxiety and poorer quality of sleep in the general population (Ramsawh, Stein, Belik, Jacobi,

& Sareen, 2009; Tsuno, Besset, & Ritchie, 2005). Additionally, reduced sleep quality was significantly associated with higher rates of depression and anxiety among

Chapter One – Literature review medical trainees (Rezaei, Khormali, Akbarpour, Sadeghniiat-Hagighi, & Shamsipour,

2018). SWD symptoms is triggered by shift work, and it may vary depending on the population of shift workers. While these symptoms were strongly linked to higher rates of depression and anxiety, this needs further investigation among shift workers, especially paramedics, as there is a lack of such information in the current body of literature.

1.8.2 Insomnia

Insomnia is generally defined as difficulty in obtaining adequate sleep.

However, according to the International Classification of Sleep Disorders, third edition, insomnia can only be diagnosed if the following criteria are met:

Difficulty falling asleep, staying asleep or non-restorative sleep; this

difficulty is present despite adequate opportunity and circumstance to

sleep; this impairment in sleep is associated with daytime impairment or

distress; this sleep difficulty occurs at least three times per week and has

been a problem for at least one month (Roth, 2007).

Insomnia can be triggered by shift work, especially among rotating shift workers, whose circadian rhythms are continuously disrupted (Chatterjee & Ambekar,

2017). About 12% of Australian paramedics reported insomnia symptoms according to one report (Paterson et al., 2014). Among other shift workers, about 38% of

Japanese shift workers reported symptoms of insomnia (Nakata et al., 2001). Rotating shift workers from India reported a higher frequency of and more severe insomnia

(45%) than a control group of regular shift workers (3%) (Chatterjee & Ambekar, 2017), and in another study, the prevalence of self-reported insomnia among nurses in

Norway was 55% (Øyane, Pallesen, Moen, Åkerstedt, & Bjorvatn, 2013). Certainly,

Chapter One – Literature review insomnia is common among shift workers, with rates varying from one occupational group to another. Further efforts are needed to investigate insomnia in paramedics and how this relates to mental health due to the lack of data on this topic in the current body of literature.

1.8.3 Obstructive sleep apnoea (OSA)

OSA is a common medical condition characterised by repetitive obstruction of the upper respiratory tract (airway), leading to sleep fragmentation and low oxygen levels (Patil, Schneider, Schwartz, & Smith, 2007). Shift workers with OSA were found to have more severe apnoea during the sleep that followed a night shift when compared with a control group of day workers with OSA (Paciorek et al., 2011). Having to work a night shift was also reported to be a major contributor to an increase in the number of apnoea incidents in Polish workers during the sleep following a night shift

(Laudencka, Klawe, Tafil-Klawe, & Zlomanczuk, 2007). In addition, Japanese nurses with OSA experienced an increase in the number of apnoea events during daytime sleep following a night shift (Matsumoto, Kamata, Naoe, Mutoh, & Chiba, 1996). Shift workers may be at higher risk of developing OSA through obesity, as recent reports confirming an association between shift work and obesity, and obesity is a well-known risk factor of having OSA (Grundy et al., 2017; Jehan, Zizi, Pandi-Perumal, Wall, et al., 2017). In the general population, OSA is strongly linked to an increased risk of developing mood disorders, especially depression and anxiety (Kim, Ko, & Kim, 2019).

While OSA is not a typical consequence of shift work, obesity may play an important role in developing OSA among shift workers. Also, the frequency and severity of OSA among shift workers are likely to increase as a result of sleep deprivation and sleeping during the day. Therefore, shift workers with OSA might be at increased risk of developing symptoms of depression and anxiety.

Chapter One – Literature review

1.8.4 Parasomnia

Parasomnia refers to a group of unusual behaviours related to sleep. The first type of parasomnia occurs prior to sleep or during non-rapid eye movement sleep. It includes confused arousal, sleepwalking, sleep terrors (nightmares), and sleep-related eating disorders. The second type constitutes rapid eye movement that manifests during actual sleep and consists of isolated sleep paralysis and sleep behaviour disorder (Howell, 2012). In general, parasomnia affects all age groups, but is more common in children. Risk factors includes a family history, brain disorders and sleep disorders, such as OSA and restless leg syndrome. The prevalence of all parasomnia types including nightmares, sleep terrors, and confused arousal, in particular was found to be higher among nurses working rotational shifts than what was reported for day shift nurses (Bjorvatn, Mageroy, Moen, Pallesen, & Waage, 2015). The prevalence of parasomnias among night shift workers was also observed to be higher than for day shift personnel (Thorpy, 2010). Research has not yet been conducted on the prevalence of parasomnias in shift workers in Australia and Saudi Arabia. In summary, parasomnia is a disturbing syndrome that is commonly identified in people with sleep disorders and in shift workers. Therefore, it is probable that paramedics are at risk of a higher incidence of parasomnia due to shift work and related sleep disturbances.

1.8.5 Narcolepsy

Narcolepsy is characterised by periods of severe daytime exhaustion and sudden muscle weakness. Individuals with narcolepsy present with symptoms of night sleeplessness, sudden daytime sleep, sleep-related hallucinations, and sleep paralysis. Its onset is caused by a chemical (hypocretin) imbalance in the brain, but the trigger for this mechanism in narcolepsy has not been fully elucidated (PubMed

Chapter One – Literature review

Health, 2014). Severe and continuous weariness or fatigue due to narcolepsy has an adverse effect on people’s lives and everyday performance (PubMed Health, 2014).

In one US study, 85% of people with narcolepsy reported diminished work performance compared to healthy individuals, and 19% of individuals with narcolepsy had reportedly been involved in a work-related accident, and 23% had been dismissed from their jobs due to underlying narcoleptic symptoms (Clark, 1989). The prevalence of narcolepsy in the general US population is approximately one in every 1,000 individuals (Clark, 1989). Therefore, although it is a relatively rare sleep disorder, uncontrolled narcolepsy in paramedics would increase the risk of occupational accidents and injuries. Similarly, it would increase the risk of sleep disorders in paramedic shift workers, thereby compromising the safety of both patients and paramedics. To the best of my knowledge, an exploration of the prevalence of narcolepsy in paramedics has not been performed in any study to date.

1.9 Chronotype

Sleep and wakefulness are usually tied to particular times of night and day and, thus, shift work disrupts this synchronisation (shift lag), resulting in poorer sleep and performance (S. M. James et al., 2017). There is evidence of natural variation in the timing of the sleep/wake cycle. Some individuals are naturally inclined to a morning

(morning type) pattern of activity with early rising, while others are naturally inclined to an evening (evening type) pattern of activity with late rising (Levandovski, Sasso, &

Hidalgo, 2013). It has been shown that evening types tend to have poorer sleep, poorer general health, and worse mental health outcomes in comparison to morning and intermediate types in the general population (Medeiros, Mendes, Lima, & Araujo,

2001; Yun, Ahn, Jeong, Joo, & Choi, 2015). A few studies have investigated the role of chronotype among shift workers. Antunes et al. (2010) reported no relationship

Chapter One – Literature review between chronotype and depressive symptoms in healthcare shift workers (Antunes,

Jornada, Ramalho, & Hidalgo, 2010). In contrast, Juda et al. (2013) reported an association between chronotype, social jet lag, and sleep duration among a sample of rotating shift workers from multiple occupations (Juda, Vetter, & Roenneberg, 2013).

Although there are some controversies among current shift workers studies, the existing body of literature recognises the critical role of chronotype in sleep, mental health, and overall health among the general population. However, limited studies have examined the role of chronotype among healthcare personnel, particularly in paramedics, which need to be covered in future studies.

1.10 Objective sleep measures

Although normal sleep duration may vary depending on a plethora of factors, including age and gender, the recommended duration of sleep for a healthy adult is between seven to nine hours per day (Chaput, Dutil, & Sampasa-Kanyinga, 2018). A shorter sleep duration or less total sleep time is arguably the first adverse event that shift workers face when they rotate shifts (Jehan, Zizi, Pandi-Perumal, Myers, et al.,

2017). Many of the studies of sleep in shift workers have used self-report measures

(J. Dorrian et al., 2006; Gómez-García et al., 2016; Mehrdad, Haghighi, & Esfahani,

2013). One of the best tools for objectively measuring sleep for research purposes is wrist actigraphy, which is portable and reliable (Marino et al., 2013). The day-to-day interaction between shift rotation and workers sleep has been described in a few studies that used objective measures of sleep. For instance, one study from Japan reported daily sleep patterns and physical activity across an entire rotating schedule

(Kawada et al., 2008). The main focus of the study was to investigate physical activity across day and night shifts, and it found that activity was significantly higher during day shifts than during night shifts (Kawada et al., 2008). Another study investigating

Chapter One – Literature review nurses using wrist actigraphy indicated that the nurses’ sleep did not differ significantly between day and night shifts (Geiger-Brown et al., 2012). However, the study was conducted among nurses working fixed shifts of either day or night, not rotating shifts

(Geiger-Brown et al., 2012). Another study of nurses working rotating shifts reported that nurses experienced a shorter duration of sleep on both day and night shifts equally

(Choi & Joo, 2016). There are some variations in the previous reports due to diversity in occupations, workloads, and shift types. Clearly, more efforts are needed to investigate the effects of rotating shift schedules on shift workers’ sleep duration. Such studies will inform researchers what initial or acute adverse events rotating shift workers face.

1.11 Sleep and mental health

Insomnia is strongly linked to the onset and severity of depressive and anxiety symptoms in the general population (Franzen & Buysse, 2008; Jackson, Sztendur,

Diamond, Byles, & Bruck, 2014; Khan, Juyal, Shikha, & Gupta, 2018). A four-fold increase in the risk of developing depression and anxiety was detected in students in the United States who were exhibiting symptoms of sleepiness and poor sleep quality

(Concepcion et al., 2014). Generally, such a relationship might be bidirectional, but among shift workers, mental health problems might stem from sleep problems, particularly insomnia (Vallieres et al., 2014). Although there is little data investigating the effect of sleep problems on the mental health of paramedics, Courtney et al. (2013) reported a significant association between chronic fatigue and depression among rural

Australian paramedics (Courtney et al., 2013). Studies from other shift worker populations seem to support the hypothesis, as Canadian shift workers reported a positive association between insomnia symptoms and depression and anxiety

(Vallieres et al., 2014). Similarly, higher rates of depressive symptoms were explained

Chapter One – Literature review by sleep deprivation among US firefighters (Carey, Al-Zaiti, Dean, Sessanna, &

Finnell, 2011). Another sleep issue that could impact on mental health is OSA. In the general population, OSA is strongly linked to an increased risk of developing mood disorders, especially depression and anxiety (Kim et al., 2019). While OSA is not a typical consequence of shift work, the frequency and severity of OSA among shift workers are likely to increase as a result of sleep deprivation and having to work at night. Also, SWD or its symptoms, especially poorer sleep quality, can impact mental health. Significant associations have been found between higher rates of depression and anxiety and poorer quality of sleep in the general population (Ramsawh et al.,

2009; Tsuno et al., 2005). In addition, reduced sleep quality was significantly associated with higher rates of depression and anxiety among medical trainees

(Rezaei et al., 2018). Sleep disturbances can be triggered or worsened by shift work, and it may vary depending on the population of shift workers. While sleep disorders

(e.g., insomnia and OSA) or poor sleep quality were strongly linked to higher rates of depression and anxiety in the general population, this needs further investigation among shift workers, especially paramedics, as there is a lack of such information in the current body of literature.

1.12 Paramedics from Saudi Arabia

Paramedics in Saudi Arabia encounter similar challenges to those in Australia, but with various cultural and geographical differences. One of the key differences observed in current official figures regarding paramedics in Saudi Arabia and Australia is the total population size. The total number of active paramedics in Saudi Arabia in

2017 was estimated to be 7,864 (General Authority for Statistics, 2017). In Australia, the number of paramedics is double that, with 17,800 being the official estimate in

2018 (Australian Government Job Outlook, 2016). The populations of Saudi Arabia

Chapter One – Literature review

(32,612,641) and Australia (25,180,200) estimated for the same year (Australian

Bureau of Statistics, 2019; General Authority for Statistics, 2018), suggest that in

Australia, there is one paramedic for every 1,415 citizens, while in Saudi Arabia there is one paramedic for every 4,147 citizens. Thus, a single paramedic in Saudi Arabia services four times more people than a paramedic in Australia. This suggests that

Saudi paramedics have a much greater workload and may face greater threats to their well-being than paramedics in Australia.

Another important difference between Saudi Arabia and Australia that could impact mental health and well-being is the rate of motor vehicle accidents. Saudi

Arabia has one of the highest annual fatality rates for motor vehicle accidents in the world (Mansuri, Al-Zalabani, Zalat, & Qabshawi, 2015), with approximately 24 fatalities per 100,000 people (Mansuri et al., 2015). In contrast, Australia has a motor vehicle fatality rate that is much lower at 4.6 fatalities per 100,000 people (Australian

Government, 2018). Therefore, Saudi paramedics would be dealing with more traumatic events due to higher rates of accidents, and that would put them at greater risk of developing anxiety, depression, and PTSD (MacDonald, Colotla, Flamer, &

Karlinsky, 2003; O'Donnell, Creamer, & Pattison, 2004).

Other variations between Saudi and Australian paramedics include gender, as this occupation is only available to men in Saudi Arabia. Also, the weather in most cities in Saudi Arabia is extremely hot (50 ℃) and dry throughout the year (Alkhunaizi,

2016). This is considerably challenging for paramedics because their work primarily takes place outdoors. In addition, the language barrier is a significant obstacle that must be overcome by paramedics in western Saudi Arabia. Saudi Arabian paramedics can only speak and understand Arabic and English; not other languages spoken by

Chapter One – Literature review the Turkish, Indian, or French populations who visit this region throughout the year for religious reasons (Alamri, 2016). The scarcity of paramedics has been demonstrated to affect the quality of EMS, placing a heavy workload burden on existing emergency teams (DeNicola, Aburizaize, Siddique, Khwaja, & Carpenter, 2016).

The comparison of different populations can be useful in informing researchers and adding useful knowledge to the field including: (1) awareness that different traditions/cultures can affect the perception of various occupational risks or hazards;

(2) a better understanding regarding obstacles that are of central concern in different countries; and (3) the development of more comprehensive and effective control strategies that are applicable in different countries (Department of Sociology, 1995).

There is a little known about paramedics in the Middle East, in general, and Saudi

Arabia, in particular. Therefore, comparing a Middle Eastern country where advanced rules and regulations of occupational health and safety (OHS) are emerging, to a country with well-developed OHS regulations may provide unique insights about this population, along with a better understanding of commonalities in paramedics across cultures.

1.13 Accidents and work-related injuries

Paramedics are located at specific stations in most countries. While this also applies to Australia, they are also dispatched in small teams when driving an ambulance. This means that the risk of a motor vehicle accident affecting a large number of mobile paramedics is high. Also, two studies reported that shift workers are at higher risk of crash or near-crash while driving home after a night duty (Lee et al.,

2016; Steele, Ma, Watson, Thomas, & Muelleman, 1999). Susceptibility to occupational injury is three times greater for paramedics than the national average for

Chapter One – Literature review all other professions in the United States (Maguire & Smith, 2013). It has been found that 86% of fatalities that occurred among paramedics were related to vehicle accidents and that the highest rates of work-related fatal injuries in the United States were attributed to paramedics as compared with other professions (Reichard, Marsh,

& Moore, 2011). A seven times increase in the risk of severe injury was attributed to

Australian paramedics in comparison to the national average. In fact, the rate of injuries for paramedics was found to be two times higher than police officers (Maguire et al., 2014). Besides other work-related challenges, paramedics face a greater risk of occupational injuries and motor vehicle accidents.

One important factor that could explain why paramedics are amongst the highest risk occupations for severe injuries and fatalities could be sleep problems, given that paramedics are required to work different shift schedules, leading to continuous disruption of their normal circadian rhythms and associated sleep problems (S. M. James et al., 2017). Sleep restriction has been significantly associated with a greater risk of motor vehicle accidents in the general population

(Gottlieb, Ellenbogen, Bianchi, & Czeisler, 2018), and one report suggested a greater risk of a crash for those who obtain less than seven hours of sleep per day. The risk is even higher among people who sleep less than four hours per day (Tefft, 2018).

Importantly, it is still unknown how much sleep paramedics get, especially when they rotate rosters. Among other shift workers, a recent report stated that the risk of a crash is at a peak during and after night shifts, with sleep deprivation as a probable cause of degraded driving performance (Lee et al., 2016). Also, physicians who work in emergency departments have reported a higher number of motor vehicle accidents and near-accidents after night shifts when compared to other times (Steele et al.,

1999). Sleep restriction is a known contributor to the risk of motor vehicle accidents,

Chapter One – Literature review especially among shift workers, because their sleep is under continuous disruption.

More studies are needed to investigate paramedic sleep patterns, especially when they rotate shifts, during and after night duty.

1.14 The hierarchy of controls

The Occupational Safety and Health Act (OSHA), directed by the Department of Labor in the United States, recommends the use of a hierarchy of control to prevent and manage occupational hazards and risks. The hierarchy of control is a simple inverted pyramid comprising five elements that have consistently been demonstrated to be effective in eradicating or controlling occupational challenges over time (Figure

1.1). The five hierarchal elements can be used together or separately to control hazards (Occupational Safety and Health Administration, 2017). Unfortunately, shift work cannot be eliminated, substituted, isolated, or prevented. However, some challenges of shift work can be controlled by altering schedules, educating workers about its consequences and how to deal with them, and by explaining the consequences to employers. This approach could help to reduce the adverse health effects of shift work.

Figure 1.1. The hierarchy of controls, which is used in the field of occupational safety and health.

Chapter One – Literature review

1.15 Summary and focus of this thesis

A comprehensive review of the literature has revealed that shift work is a challenging demand, and it may trigger the onset of, or worsen, the underlying condition of many sleep disorders, including insomnia, SWD, and OSA. It was suggested that chronic circadian misalignment is the first adverse event experienced by shift workers, thus increasing their risk of developing serious chronic ailments, including sleep disorders. In general, there is a clear and strong relationship between mental health and sleep, and many researchers have described this as a bidirectional relationship. In shift work, it is hypothesised that sleep disorders are a strong contributor to the increased burden of mental health problems such as depression, anxiety, stress, and PTSD. However, few studies have investigated these relationships in paramedics, suggesting a need for more studies to update the current literature and to examine the relationship between sleep and mental health. Also, among the general population, evening types have reported worse outcomes in terms of sleep and mental health compared to morning types. In shift work, few studies have investigated the role of chronotype on well-being, sleep, and mental health, but the available results seem to be consistent with those from the general population.

Nonetheless, there were no studies examining the role of chronotype on the burden of sleep or mental health among paramedics, indicating a need to do so in future work.

Most importantly, very limited research is available that has investigated

Australian and Saudi paramedics. The available literature contains limited information about paramedics from the Middle East, particularly Saudi Arabia. Only one published study investigated Saudi paramedics, with no information about sleep or mental health. There are two factors that would impact the sleep and mental health of paramedics from Saudi Arabia: (1) the proportion of paramedics to the general

Chapter One – Literature review population is tremendously more burdensome than for paramedics in Australia: and

(2) the size of the general population of Saudi Arabia is greater than Australia.

Therefore, Saudi paramedics may be facing higher demands compared to Australian paramedics.

Investigating the day-to-day variations in rotating shift schedules, using objective measures of sleep and activity, is important for identifying the acute response of such shifts on workers, especially with regard to recovery days after night work because signs of significant fatigue, sleepiness, and stress were still elevated even after the end of night shifts. Objectively measured sleep is an important way to investigate such variations. The current literature suggests a need to investigate this among shift workers, and particularly among paramedics, given that no observational study of sleep and daytime functioning has been conducted in paramedics to date.

Therefore, the present thesis focused on investigating paramedics for the prevalence of different mental health and sleep disorders, as well as investigating the mental health burden among paramedics and the role of chronotype on developing sleep or mental health concerns. In addition, this thesis aimed to investigate paramedics from Saudi Arabia, with a comparison to another developed country such as Australia, to assess possible variations in sleep or mental health outcomes. Also, assessing paramedics during duty and recovery days allowed researchers to observe the acute responses of working on rotating shifts on daytime functioning.

1.16 Thesis Aims

The present thesis aimed to investigate paramedics for sleep and mental health disturbances, in particular focusing on the relationship between sleep and mental health. Thesis aims and hypotheses are as follows:

Chapter One – Literature review

1. Examine the prevalence and the associations between sleep issues and mental

health of Australian paramedics, and to explore the role of chronotype on self-

reported scores of sleep, depression, anxiety, and general health. It is

hypothesised that: (1) the prevalence of self-reported sleep and mood disorders

would be significantly higher in paramedics in comparison to prevalence from

established normative population data; (2) sleep disturbances, stress, fatigue,

and general health would be associated with poorer mental health outcomes;

and (3) self-reported sleep quality, mental health, and well-being would be

significantly poorer among paramedics with evening chronotype compared to

morning chronotype.

2. Compare sleep and mental health problems between Saudi Arabian and

Australian paramedics. We hypothesised that Saudi Arabian paramedics would

report higher levels of sleep and mental health issues than Australian

paramedics due to greater work-load demands.

3. Investigate the acute effects of a rotating shift schedule on sleep, mood, stress,

fatigue, sleepiness, energy expenditure, and physical activity levels among

Australian paramedics. Paramedics were monitored for a period of eight

consecutive days across pre-shift day (baseline), night shift, day shift, and two

days of recovery. It was hypothesised that during night shift, compared to

baseline, day shift, and recovery days, paramedics would report lower sleep

duration, physical activity, energy expenditure, poorer mood, and higher stress,

fatigue, and sleepiness.

Chapter Two – Sleep and mental health in Australian paramedics

Chapter Two : The Relationship Between Shift-work, Sleep and Mental Health

Among Paramedics in Australia

Preface

Since there is a little known about paramedic’s sleep, mental health and well-being, especially in Australia. Particularly, how sleep and mental health are related in this population and what kind of relationship chronotype has with mental health concerns has not been fully examined. This study aimed to investigate the prevalence of sleep and mental health issues, the role of chronotype, and the relationship between these variables in Australian paramedics in a cross-sectional survey.

Publication

Khan, W, Conduit, R., Kennedy, G. A., & Jackson, M. L. The Relationship Between

Shift-work, Sleep and Mental Health Among Paramedics in Australia. 2020, Sleep

Health – Journal of the National Sleep Foundation – Elsevier.

Candidate’s contribution

Wrote the manuscript, conducted the study, and the data analyses.

Chapter Two – Sleep and mental health in Australian paramedics

Abstract

Paramedics often perform shift-work duties in conflict with their natural sleep patterns, which can cause circadian misalignment, impacting their sleep, mental health, vitality and well-being. This study aimed to investigate the prevalence of sleep and mental health issues, the role of chronotype, and the relationship between these variables in

Australian paramedics. Paramedics were invited to complete an online survey to assess stress, post-traumatic stress disorder (PTSD), depression, anxiety, daytime sleepiness, insomnia, sleep quality, shift-work disorder, bruxism, obstructive sleep apnea, narcolepsy, chronotype, fatigue, and well-being. A total of 136 paramedics responded to the survey (age = 39.1 ± 12.1 years; 45.8% men and 54.2% women;

85.4% rotating shift-workers, 7% rural shift-workers and 7.6% fixed rosters).

Paramedics reported significantly higher levels of depression symptoms, anxiety symptoms, fatigue, PTSD symptoms, insomnia symptoms, narcolepsy, and significantly poorer sleep quality and general well-being than norms from the general population of Australia and Western countries (all p < .05). From regression analyses, insomnia explained the greatest amount of variance in depression and anxiety scores, followed by fatigue and PTSD (adjusted R-squared for depression and anxiety models

= .58 and = .44 respectively, p < .001). The majority of participants were an

Intermediate chronotype (57%), followed by morning (32%), and evening type (11%).

Evening chronotypes showed significantly higher depression scores (p < .001), anxiety

(p < .05), and PTSD symptoms (p < .05), and poorer sleep quality (p < .05) and general well-being (p < .001) scores compared to morning types. Addressing sleep issues and matching chronotype to shift preference in paramedics may help to reduce the burden of depression and anxiety and improve sleep and well-being.

Keywords: sleep, insomnia, shiftwork, anxiety, chronotype, depression

Chapter Two – Sleep and mental health in Australian paramedics

2.1 Introduction

The continuous demand for 24-hour emergency support requires paramedics to work shift schedules outside of the standard 9am to 5pm day shift schedule

(National Sleep Foundation, 2017). The adverse consequences of shift-work have been described in the literature and there is now evidence to suggest that it is becoming an increasingly more serious public health issue (Costa, 2010). Working night shifts increases the risk of fatigue, accidents, stress, depression, and chronic disease (Akerstedt & Wright, 2009; Angerer, Schmook, Elfantel, & Li, 2017; Ganesan et al., 2019; Ma et al., 2015; Ramin et al., 2015). Rotational shift-work refers to the integration of night and day shift in a specific period. Usually, some recovery time is factored in between shifts to allow adaptation to the new schedule (Costa, 2010).

According to Zverev et al. (2009), sleep deprivation is experienced in both types of shifts, but more sleep hours were reported by rotational shift-workers than those who covered only the night shift (Zverev & Misiri, 2009). Higher stress and fatigue levels, lower occupational satisfaction, poor sleep quality and a reduction in sleep hours have been attributed to rotational shifts in nurses (Coffey et al., 1988; Ferri et al., 2016).

One of the key contributors to these adverse health effects in shift-workers is disrupted circadian rhythms.

Paramedics have to cope with significant challenges while performing their daily duties, including having to deal with shift-work, trauma, accidents, and death, placing them at risk of developing mental health issues. High stress levels and a significant elevation in stress-related hormones have been demonstrated in paramedics during days at work compared to days off work (Dutton et al., 1978). There is increasing evidence that post-traumatic stress disorder (PTSD) may occur due to cumulative exposure to trauma and high levels of stress (Briere, Agee, & Dietrich,

Chapter Two – Sleep and mental health in Australian paramedics

2016). The prevalence of PTSD in paramedics cohorts has been estimated between

15 – 20% (Berger et al., 2007; Streb et al., 2013). Symptoms of major depression were identified in 11% of newly recruited paramedics in the UK during their first week on duty with symptoms still persistent over 24-month follow up (Wild et al., 2016). In an

Australian sample of paramedics reports of anxiety, stress and depression were 12%,

15% and 27%, respectively (Courtney et al., 2013; Sofianopoulos, Williams, Archer, &

Thompson, 2011a). Global levels of stress, anxiety and depression are unquestionably high in paramedics, with the implication that the health and safety of patients and paramedics is potentially compromised (Bajraktarov et al., 2011). Due to the high rate of mental health concerns in paramedics, coupled with our current understanding of the bi-directional relationships with sleep (Fernandez-Mendoza &

Vgontzas, 2013; Krystal, 2012), information regarding variations in shift types, sleep characteristics and how it relates to mental health is invaluable information regarding the welfare of paramedics. More work still needs to be done to fully understand the burden of depression, anxiety and stress in paramedics, and potential factors that place some shift-workers at a higher risk of mental health issues. One such factor is sleep disturbance.

Shift-workers are at an increased risk of developing a range of sleep disorders due to their work schedules, including shift-work disorder (SWD) due to the disruption of their natural sleep cycle and circadian rhythms. SWD is a sleep condition characterized by signs of fatigue and excessive sleepiness, which results from working irregular shifts (Jehan, Zizi, Pandi-Perumal, Myers, et al., 2017). It is estimated that

10% of shift-workers suffer from SWD (Roth, 2012). In addition, shift-workers with obstructive sleep apnea (OSA), when compared to a control group with only OSA, were found to have more severe apnea, possibly due to sleep deprivation that occurs

Chapter Two – Sleep and mental health in Australian paramedics after night work (Paciorek et al., 2011). Another serious concern encountered by shift- workers is insomnia, which is difficulty getting sufficient restorative sleep characterized by difficulty falling or staying asleep (Roth, 2007). Exposure to light during the day, the time at which shift-workers are expected to sleep, can cause sleep delays (Bajraktarov et al., 2011). A study of shift-workers from the fire department in the United States found that 70% reported poor-quality sleep (Billings & Focht, 2016). In an Australian study, Rajaratnam et al. (2013) found that shift-workers reported a number of sleep issues, including insomnia, with more than 35% falling asleep at work at least once a week (Rajaratnam et al., 2013). Shift-work appears to be positively related to insomnia, SWD and OSA severity (Paciorek et al., 2011; Rajaratnam et al., 2013;

Thorpy, 2011).

The relationship between sleep and mental health is bi-directional, with data from the general population suggesting that chronic sleep restriction and insomnia can trigger depression and anxiety (Fernandez-Mendoza & Vgontzas, 2013; Krystal,

2012). Healthy adults, when exposed to a period of sleep restriction, reported significantly higher depression and anxiety outcomes compared to baseline (Short &

Louca, 2015). Previous studies confirmed a strong correlation between the severity of

OSA and mental health, particularly depression and anxiety (Jackson et al., 2019;

Kaufmann, Susukida, & Depp, 2017). Among shift-workers, shift-work disorder was strongly related to higher scores of depression and anxiety (Kalmbach, Pillai, Cheng,

Arnedt, & Drake, 2015). Collectively, these studies outline the critical role of sleep on mental health, however, a little is known about the relationship between sleep and mental health in paramedics and the integration of shift-work into the equation.

Sleep and wakefulness are usually tied to particular times of night and day and thus shift-work disrupts this synchronization (shift-lag) resulting in poorer sleep and

Chapter Two – Sleep and mental health in Australian paramedics performance. There is evidence of natural variation in the timing of the sleep/wake cycle. Some individuals are naturally inclined to a morning (morning type) pattern of activity with early rising, while others are naturally inclined to an evening (evening type) pattern of activity with late rising (Levandovski et al., 2013). It has been shown that evening types tend to have poorer sleep, general health, and mental health outcomes in comparison to morning and intermediate types in the general population

(Medeiros et al., 2001; Yun et al., 2015). A few studies investigated the role of chronotype among shift-workers, especially among paramedics. Antunes et al. (2010) reported no relationship between chronotype and depressive symptoms (Antunes et al., 2010). Also, Juda et al. (2013) reported the association between chronotype, social jet lag, and sleep duration only (Juda et al., 2013). Existing literature recognizes the critical role of chronotype on sleep, mental and general health of the general population, but limited studies have examined chronotype in paramedics, especially the role of chronotype in mental health and general well-being of the paramedics.

The current study aimed to examine the prevalence and the associations between sleep issues and mental health of Australian paramedics. Secondly, the role of chronotype on self-reported scores of sleep, depression, anxiety, and general health was investigated. It was hypothesized that: (1) the prevalence of self-reported sleep and mood disorders would be significantly higher in paramedics in comparison to prevalence from established normative population data; (2) sleep disturbances, stress, fatigue, and general health would be associated with poorer mental health outcomes; and (3) self-reported sleep quality, mental health, and well-being would be significantly poorer among paramedics with evening chronotype compared to morning chronotype.

Chapter Two – Sleep and mental health in Australian paramedics

2.2 Method

2.2.1 Participants

Ambulance Employees Australia Victoria (AEAV) facilitated the recruitment of paramedics to the study. There are 2841 active AEAV paramedics in Victoria (Victoria,

2018). A survey link was distributed to the paramedics via emails and was also posted to their web-based newsletter. Paramedics were asked to read the participants information sheet and to consent electronically before taking the actual survey. The study was restricted to active paramedics who worked in any type of shift and participation was voluntary. No incentives were provided to participants. The study was approved by the Human Research Ethics Committee at the Royal Melbourne

Institute of Technology (Approval # 21420). A total of 130 paramedics were required to meet the planned calculations based on moderate effect size (r =.30), at a significance level of (p < .05), and a power of .80 (Cohen, 1992). A total of 194 paramedics participated in the survey with a response rate of 6.8%. Although this was a convenience sample, age and shift type were representative of the current industry

(Australian Government Job Outlook, 2016). Paramedics reported working in three main types of shifts including (1) rotating shift, (2) fixed shift, and (3) rural shift.

Rotating shift was a schedule of two days of standard morning duty (10 hours per single shift) followed by two days of night duty (14 hours per single shift) with 4 days of break in-between the rosters. While the fixed shift was 4 days of either a morning duty (10 hours per single shift) or night duty (14 hours per single shift) and 4 days of break in-between the rosters. The rural shift was a special type of roster available to paramedics working in the rural areas with 8 consecutive days of morning duty (10 hours per single shift) with overnight on-call and 6 days of break in-between the rosters.

Chapter Two – Sleep and mental health in Australian paramedics

2.2.2 Materials

The online survey included a series of validated sleep, mood and health questionnaires, and took approximately 40 minutes to complete. The first part of the survey aimed to collect demographic data from the participants including age, gender, height, weight, use of cigarettes (smoking), medical history, use of medications, daily caffeine consumption, and a few work-related questions including: current shift schedule, weekly working hours, weekly driving hours for work purposes, and current role in the AEAV. A series of validated questionnaires to assess sleep, mood and general health were included in the survey (Table 2.1).

Normative data is known as data that describes what is usual in a known population at a given point in time or over a period of time and is useful in scientific research (O'Connor, 1990). For the purpose of identifying the differences between the study sample and the general population, a comparison between study findings and general population norms obtained from other published studies was reported as part of the first aim (Table 2.2).

Chapter Two – Sleep and mental health in Australian paramedics

Table 2.1. The list of the questionnaires used in the present study.

Questionnaire Cut off Items Reliability / validity General Health Questionnaire (SF-36) (Ware & NA** 36 Yes Sherbourne, 1992)

Perceived Stress Scale (Cohen, Kamarck, & (>13) 14 Yes Mermelstein, 1983) Beck Depression Inventory-Short Form (Beck, (>4) 13 Yes Steer, & Brown, 1996)

State-Trait Anxiety Inventory-Short Form (Marteau (>36) 6 Yes & Bekker, 1992)

Shift-work Disorder Screening Questionnaire NA** 4 Yes (Barger et al., 2012) Pittsburgh Sleep Quality Index (Buysse, (>5) 18 Yes Reynolds, Monk, Berman, & Kupfer, 1989)

Pittsburgh Sleep Quality Index-Addendum for (>3) 10 Yes PTSD* (Germain, Hall, Krakow, Katherine Shear, & Buysse, 2005)

Epworth Sleepiness Scale (Johns, 1991) (>10) 8 Yes

Insomnia Severity Index (Bastien, Vallières, & (>14) 7 Yes Morin, 2001) Berlin Questionnaire for OSA* (Netzer, Stoohs, NA** 10 Yes Netzer, Clark, & Strohl, 1999)

Ullanlinna Narcolepsy Scale (Hublin, Kaprio, (>14) 11 Yes Partinen, Koskenvuo, & Heikkila, 1994)

Fatigue Severity Scale (Krupp, LaRocca, Muir- (>4) 9 Yes Nash, & Steinberg, 1989)

Horne and Ostberg Morningness-Eveningness NA** 19 Yes Questionnaire for chronotype (Horne & Ostberg, 1976)

Bruxism Assessment Questionnaire (Cohen et al., NA** 8 Yes 1983)

Note. * (PTSD) post-traumatic stress disorder, (OSA) obstructive sleep apnea, ** no cut off for the SF-36 subscales, Shift-work Disorder Screening Questionnaire was calculated by a special algorithm, Berlin Questionnaire was calculated by risk criteria where 2 or more positive categories represented high-risk individuals, chronotype calculated as follow (16-41 evening type, 42-58 intermediate type, and 59-86 morning type), and Bruxism Assessment Questionnaire was calculated by risk criteria where positive responses to question 1, and/or question 2, and at least one positive from any item in question 3 represented high-risk individuals.

Chapter Two – Sleep and mental health in Australian paramedics

Table 2.2. The list of studies containing the reference populations for each questionnaire.

Study Questionnaire Population Age M(SD)

Butterworth and Crosier (2004) SF-36 Australia (n=13,055) 43(17.6)

Crawford, Cayley, Lovibond, STAI-SF Australia (n=760) 41.2(16.9) Wilson, and Hartley (2011)

Lastella, Roach, Halson, and MEQ Australia (n=88) 21.9(3.8) Sargent (2016)

Buysse et al. (2008) PSQI / ESS US (n=187) 59.5(7.2)

Germain et al. (2005) PSQI-A US (n=163) 50(12.8)

Freeman, Pugh, Vorontsova, and ISI UK (n=300) 37.7(12.5) Southgate (2009)

Zebede, Lovatsis, Alarab, and BQ Canada (n=79) 51(16) Drutz (2015)

Hublin et al. (1994) UNS Finland (n=11,354) Unknown

Aalto, Elovainio, Kivimäki, BDI-SF Finland (n=5561) Men (49.8) Uutela, and Pirkola (2012) Women (51.3)

Valko, Bassetti, Bloch, Held, and FSS Switzerland (n=454) 47(18) Baumann (2008)

Barger et al. (2015) SWSD US (n=6933) 40.4(8.9)

Note. M = mean, SD = standard deviation, (US) Unites States, (UK) United Kingdom, (SF-36) General Health Questionnaire, (STAI-SF) State-Trait Anxiety Inventory-Short Form, (MEQ) Horne and Ostberg Morningness-Eveningness Questionnaire, (PSQI) Pittsburgh Sleep Quality Index, (ESS) Epworth Sleepiness Scale, (PSQI-A) Pittsburgh Sleep Quality Index-Addendum, (ISI) Insomnia Severity Index, (BQ) Berlin Questionnaire, (UNS) Ullanlinna Narcolepsy Scale, (BDI-SF) Beck Depression Inventory-Short Form, (FSS) Fatigue Severity Scale, and (SWSD) Shift-work Disorder Screening Questionnaire.

Chapter Two – Sleep and mental health in Australian paramedics

2.2.3 Procedure

The distribution of the survey across Victoria, Australia from December 2017 until December 2018 was managed by the AEAV. The AEAV used electronic newsletters and emails to promote participation in the study, which was voluntary and anonymous. The Qualtrics website was the platform used to conduct the survey.

2.2.4 Statistical analyses

The data were analyzed using the IBM Statistical Package for the Social

Sciences (SPSS) version 24, Macintosh and Microsoft versions. Data distributions were adequate in terms of normality, linearity, and homoscedasticity. The data were also tested for outliers, missing values, and data entry errors. Data cleaning led to the elimination of 60 participants of the total 194 due to missing respondent data. Single sample t-tests were used to determine whether the sample means were statistically different from known general population means for different sleep and mental health scales. To investigate the effect of sleep disorders on the paramedics’ mental health,

(1) correlational analyses were performed to measure the magnitude of the relationships between depression, anxiety, and all continuous sleep variables; (2) categorical sleep variables were tested by an independent samples t-test to determine whether there were statistically significant differences between the depression and anxiety between the high and low risk groups for the following measurements: Berlin

Questionnaire, Shift-work Disorder Screening Questionnaire, and Bruxism

Assessment Questionnaire; (3) all significant correlations were examined further by a stepwise linear regression to identify which pool of variables predicted depression and anxiety. In addition, a One-Way ANOVA was performed to examine differences between the three chronotype groups in terms of sleep and mental health variables.

Chapter Two – Sleep and mental health in Australian paramedics

Tests to examine whether the data met the assumption of collinearity were conducted via the variance inflation factor (VIF). A value of less than 5 VIF indicates no multicollinearity issues (Vatcheva, Lee, McCormick, & Rahbar, 2016). This test indicated the assumption of multicollinearity was not violated in the depression model

(insomnia: tolerance = 0.62, VIF = 1.59; PTSD: Tolerance = 0.70, VIF = 1.42; BMI:

Tolerance = 0.97, VIF ( = 1.03; and fatigue: Tolerance = 0.79, VIF = 1.25) and anxiety model (insomnia: tolerance = 0.63, VIF = 1.57; fatigue: Tolerance = 0.80, VIF = 1.24; and PTSD: Tolerance = 0.71, VIF = 1.39).

2.3 Results

The final data set included 134 participants with complete data with 45.8% males and 54.2% females. The mean age was 39.1 years (SD=12.1 years), and the mean body mass index (BMI) was 26.7, SD= 4.9 (males M = 28.1, SD = 4.4, females

M = 25.4, SD = 5.1). The prevalence of obesity among respondents was 23.1%, 34.2% were overweight, and 42.0% had a healthy BMI. Most of the paramedics were working rotating shifts (85.4%) followed by fixed shifts (7.6%) and rural shifts (7.0%).

Paramedics worked an average of 43.8 (SD = 10.1) hours per week and drove (for work purposes) a mean of 18.9 (SD = 12.2) hours per week. Paramedics reported a number of previously diagnosed health concerns including PTSD (16.0%), anxiety

(26.0%), depression (31.0%), stress (32.0%), OSA (8.0%), and insomnia (20.0%).

There were no significant correlations between age and mental health and sleep outcomes (all p > 0.05). There were no significant gender differences in sleep and mental health outcomes (all p > 0.05).

Chapter Two – Sleep and mental health in Australian paramedics

2.3.1 The prevalence of self-reported sleep and mood disorders in paramedics compared to established normative population data.

Mean scores and standard deviations for the general health questionnaire (SF-

36) and normative population are shown in Table 2.3 Paramedics reported significantly lower means for all SF-36 items compared to means from the general population, except for physical functioning, where paramedics reported significantly better scores (Butterworth & Crosier, 2004).

Chapter Two – Sleep and mental health in Australian paramedics

Table 2.3. Scores of the SF-36 subscales from Australian paramedics compared to Australian general population norms.

Variable Paramedics Population

M(SD) M(SD) * t(df), p, 95% CI

Physical functioning 87.5(16.1) 83.2(23.1) t(158)= 3.38, p = .001, [1.8, 6.8] Role physical 69.7(37.5) 79.1(35.6) t(158)= -3.18, p = .002, [-15.3, -3.5]

Bodily pain 69.3(21.2) 74.3(25.2) t(158)= -2.98, p = .003, [-8.3, -1.6]

General health 54.9(25.8) 70.1(21.1) t(158)= -7.39, p < .001, [-19.2, -11.1]

Vitality/fatigue 43.6(20.1) 60.9(19.8) t(158)= -10.78, p < .001 , [-20.3, -14.1]

Social functioning 70.4(25.2) 81.9(23.6) t(158)= -5.77, p < .001, [-15.4, -7.5]

Role emotional 64.9(39.7) 82.1(33.1) t(158)= -5.45, p < .001, [-23.3, -10.9]

Mental health 63.3(18.7) 73.9(17.4) t(158)= -7.10, p < .001, [-13.5, -7.6]

Note. M = mean, SD = standard deviation, CI = confidence intervals, and * Australian norms (n=13,055) (Butterworth & Crosier, 2004).

The prevalence and mean scores reported in the current study and the population norms from previously published studies are illustrated in Figures 2.1 and

2.2 The mean scores of depression, anxiety, sleep quality, PTSD, insomnia, narcolepsy, and fatigue were significantly higher among paramedics compared to the general population (p < .001) (Aalto et al., 2012; Buysse et al., 2008; Crawford et al.,

2011; Freeman et al., 2009; Germain et al., 2005; Hublin et al., 1994; Valko et al.,

2008). The prevalence of high OSA risk was higher among paramedics compared to

Chapter Two – Sleep and mental health in Australian paramedics the general population, at 41.5% and 24.0%, respectively (Zebede et al., 2015). About half of the paramedics screened positive for SWD, while American firefighters reported only 9.0% (Barger et al., 2015). However, paramedics scored significantly lower daytime sleepiness than the general population (Buysse et al., 2008).

0 Obstructive Poor sleep Daytime Insomnia Narcolepsy Fatigue Shift-work Sleep Apnea quality sleepiness sleep disorder

Paramedics General population

Figure 2.1. The prevalence of different sleep disorders in paramedics and in the general population. Obstructive sleep apnea was measured by Berlin Questionnaire (2 categories or more represent positive screening), sleep quality was assessed by Pittsburgh Sleep Quality Index (cut off>5), daytime sleepiness was assessed by Epworth Sleepiness Scale (cut off>10), insomnia was measured by Insomnia Severity Index (cut off>14), narcolepsy was assessed by Ullanlinna Narcolepsy Scale (cut off>14), fatigue was screened by Fatigue Severity Scale (cut off>4), and shift-work disorder was assessed by Shift-Work Disorder Screening Questionnaire (constant of -8.859 represent at high risk group and -5.189 represent at low risk group).

Chapter Two – Sleep and mental health in Australian paramedics

0 Depression Depression Anxiety Sleep quality PTSD Daytime Insomnia Fatigue MEN WOMEN sleepiness

Paramedics General population

Figure 2.2. The mean and standard errors of sleep and mental health outcomes in paramedics and in the general population. Perceived stress measured by PSS (>13), depression measured by BDI-SF (>7), anxiety measured by SATI-SF (>36), sleep quality measured by PSQI (>5), Post- Traumatic Stress Disorder measured by PSQI-Addendum (>3), daytime sleepiness measured by ESS (>10), insomnia measured by ISI (>14), and fatigue measured by FSS (>3) for the general population and paramedics.

Chapter Two – Sleep and mental health in Australian paramedics

2.3.2 The association between sleep disturbances, stress, fatigue, and general health, and mental health outcomes.

Paramedics who were at a high risk of OSA (M = 9.6, SD = 7.4) reported significantly higher depressive symptoms (t(84.25) = -3.12, p = .02, 95% CI [-6.5, -

1.4]) than those at low risk (M = 5.6, SD = 7.6). Paramedics who were at high risk of developing SWD (M = 9.1, SD = 7.6) reported significantly higher depressive symptoms (t(99.39) = 4.1, p = .001, 95% CI [2.2, 6.5]) than those at low risk (M = 4.7,

SD = 4.2). Likewise, paramedics who screened positive for sleep bruxism (M = 8.5,

SD = 7.7) reported significantly higher depressive symptoms (t(66.11) = -2.07, p = .01,

95% CI [-5.2, -0.1]) than those who screened negative (M = 5.8, SD = 5.4). Anxiety ratings did not significantly differ between high and low risk groups of OSA, SWD, and sleep bruxism (all p’s > 0.05).

Correlation between mental health scales (depression and anxiety) and other study variables are shown in Table 2.4. Significant positive correlations of strong magnitude were found between depression and stress, fatigue, insomnia, PTSD, and sleep quality (all p < .001). Significant positive correlations of medium magnitude were also found between depression and daytime sleepiness and BMI (all p < .01). All items from the (SF-36) were strongly and significantly correlated with depression (p < .001).

In addition, a strong positive correlation (p < .001) was detected between anxiety and stress, fatigue, insomnia, daytime sleepiness, PTSD, and sleep quality. All items from the (SF-36) were strongly and significantly (p < .001) correlated with anxiety, except for physical functioning. Overall, higher scores of different sleep issues and general health issues are correlated with higher levels of depression and anxiety in paramedics.

Chapter Two – Sleep and mental health in Australian paramedics

Table 2.4. Correlations between mental health and sleep variables

Variable Depression Anxiety

Stress .33** .31**

Fatigue .49** .46**

Insomnia .54** .53**

Daytime sleepiness .28* .34**

PTSD .53** .51**

Sleep quality .49** .46**

BMI .24* .00

Physical functioning -.40** -.15

Role physical -.47** -.39**

Bodily pain -.48** -.34**

General health -.50** -.42**

Vitality -.68** -.53**

Social functioning -.57** -.49**

Role emotional -.58** -.58**

Mental health -.77** -.69**

Note. *p < .05, **p < .001, (PTSD) Post-Traumatic Stress Disorder, (BMI) Body Mass Index.

Chapter Two – Sleep and mental health in Australian paramedics

A stepwise linear regression was done to predict depression and anxiety based on all variables with moderate to strong correlations (Table 2.5). A significant regression model predicting depression included the variables insomnia, PTSD, BMI, and fatigue (F(4, 101) = 37.59, p < .001), accounting for 58.0% of the variance in depression. Similarly, anxiety was predicted by insomnia, fatigue, and PTSD with the following model equation (F(3, 102) = 28.89, p < .001), accounting for 44.0% of the variance in anxiety.

Table 2.5. Stepwise linear regression predictors of depression and anxiety.

Variable B SE B β Depression Constant -16.57 2.83 Insomnia .28 .09 .24* PTSD .75 .14 .38** BMI .42 .08 .31** Fatigue 1.59 .35 .31** Adjusted R2 .58 F 37.59** Anxiety Constant 10.46 4.49 Insomnia .84 .27 .28* Fatigue 4.08 1.07 .30** PTSD 1.42 .43 .28* Adjusted R2 .44 F 28.89**

Note. *p <.05, **p < .001, B = unstandardized regression coefficient, SE = standard error, β = standardized regression coefficient, (PTSD) Post-Traumatic Stress Disorder, (BMI) Body Mass Index.

Chapter Two – Sleep and mental health in Australian paramedics

2.3.3 The association between self-reported sleep quality, mental health, and well-being and chronotype.

The majority of the paramedics were found to be intermediate chronotype

(57.0%) followed by morning (32.0%) and evening (11.0%). Means and standard deviations of the sleep, mental health, and well-being results across the three chronotypes are shown in Table 2.6. Evening chronotypes reported significantly higher levels of depression (F(2, 136) = 9.31, p < .001) and anxiety (F(2, 136) = 7.49, p =

.001) compared to the morning chronotype. In addition, the evening chronotype reported significantly higher levels of PTSD symptoms (F(2, 120) = 6.02, p = .003) and poorer sleep quality (F(2, 121) = 3.74, p = .02) compared to the morning chronotype.

The three items of the SF-36 (1) vitality/fatigue (F(2, 135) = 10.39, p < .001) (2) mental health (F(2, 135) = 13.37, p < .001) and (3) general health (F(2, 135) = 8.21, p < .001) were significantly higher in the evening chronotype compared to the morning chronotype. Although evening types reported higher mean scores of insomnia and

BMI, differences were not statistically significant.

Chapter Two – Sleep and mental health in Australian paramedics

Table 2.6. Study outcomes across the three chronotype groups

Measure Evening Intermediate Morning M(SD), 95% CI M(SD), 95% CI M(SD), 95% CI Depression 13.3(9.2), [8.1, 6.4(5.7), [5.1, 7.6] 5.6(5.5), [3.9, 7.2] 18.3]

Insomnia 14.3(6.1), [10.3, 11.1(6.1), [9.6, 12.6] 10.3(5.6), [8.3, 18.1] 12.2]

Anxiety 54.6(15.3), [46.1, 41.7(16.9), [37.9, 36.0(14.9), [31.5, 63.1] 45.4] 40.5]

PTSD 5.7(4.1), [3.1, 3.1(3.6), [2.3, 3.9] 2.1(1.9), [1.4, 2.7] 8.3]

Sleep quality 11.1(3.5), [8.8, 8.9(4.1), [8.0, 9.9] 7.7(3.6), [6.5, 8.9] 13.3]

BMI 29.7(5.5), [26.6, 26.6(5.1), [25.5, 26.6(4.8), [24.8, 32.7] 27.8] 27.8]

Vitality* 28.9(17.6), [19.1, 40.7(19.1), [36.4, 52.5(18.4), [46.8, (fatigue) 38.6] 44.9] 58.1]

Mental health* 42.9(20.6), [30.8, 62.8(17.6), [58.9, 69.9(17.9), [64.6, 53.6] 66.7] 75.2]

General 30.9(21.6), [18.3, 55.2(26.1), [49.4, 60.3(23.8), [52.9, health* 42.2] 61.1] 67.6]

Note. M = mean, SD = standard deviation, CI = confidence intervals, *Items from the General health questionnaire SF-36, (PTSD) Post-Traumatic Stress Disorder. (BMI) Body Mass Index.

Chapter Two – Sleep and mental health in Australian paramedics

2.4 Discussion

This study investigated the prevalence of self-reported sleep complaints and mental health concerns, depression and anxiety predictors, and the impact of chronotype on sleep and mental health disturbances of paramedics in Australia.

Paramedics reported significantly higher levels of depression, anxiety, PTSD, and insomnia symptoms, fatigue, poorer sleep quality and general well-being compared to relevant reference populations estimates, which support the first hypothesis (Aalto et al., 2012; Butterworth & Crosier, 2004; Buysse et al., 2008; Crawford et al., 2011;

Freeman et al., 2009; Germain et al., 2005; Valko et al., 2008). Insomnia, OSA, and

SWD were significantly related to depression symptoms, which partially supports the second hypothesis. Evening-inclined paramedics, compared to morning, reported significantly higher levels of depression, anxiety and PTSD symptoms, and lower sleep quality and poorer general well-being, which supports the third hypothesis.

Using validated screening tools for a range of sleep disorders revealed a higher prevalence of OSA, insomnia symptoms, narcolepsy, and shift-work sleep disorder among Australian paramedics compared to the general population (Barger et al.,

2015; Freeman et al., 2009; Hublin et al., 1994; Zebede et al., 2015). Likewise, poor sleep quality was also found to be more prevalent among Australian paramedics than the general population (Buysse et al., 2008). Moreover, there were significantly higher levels of depression, anxiety, and PTSD symptoms, and poorer well-being among

Australian paramedics compared to the general population (Aalto et al., 2012;

Butterworth & Crosier, 2004; Crawford et al., 2011; Germain et al., 2005). It is possible that shift-work triggers insomnia by disrupting the normal sleep cycle, resulting in sleep deprivation, excessive daytime sleepiness, and poor quality of sleep (Richter, Acker,

Adam, & Niklewski, 2016). Comparatively, some studies have reported unhealthy

Chapter Two – Sleep and mental health in Australian paramedics levels of excessive daytime sleepiness and poor sleep quality among active U.S. paramedics (Patterson et al., 2010; Patterson et al., 2012; Pirrallo, Loomis, Levine, &

Woodson, 2012). Among other types of shift-workers, some studies indicate significant levels of insomnia (Eldevik, Flo, Moen, Pallesen, & Bjorvatn, 2013; Rajaratnam et al.,

2013; Vallieres et al., 2014). In the general population, insomnia is strongly linked to poor health, depression, and anxiety (Roth, 2007). Higher levels of insomnia, which can be triggered by shift-work, may explain the higher prevalence of depression and anxiety among paramedics compared to the general community (Aalto et al., 2012;

Crawford et al., 2011; Freeman et al., 2009).

Previous studies reported almost similar excessive daytime sleepiness prevalence among paramedics from the US and Australia with 36.0% and 30.0% respectively (Pirrallo et al., 2012; Sofianopoulos et al., 2011a), while the prevalence from the current study was slightly lower with 25.0%. Variations in daytime sleepiness may be due to variations in sample size, age, or shift types across present and previous studies. Paramedics from the present study reported higher fatigue prevalence of 75% compared to paramedics from the US with 50%; taking into consideration the variation in shift schedule between USA and Australia, as the most common shift in the USA was the 24hr on and 48hr off, while in Australia it was a rotating shift with 24hr day, 24hr night, and 4 days off (Patterson et al., 2012). The mean fatigue rating was consistent with previous Australian studies of paramedics

(Courtney et al., 2013). The average sleep quality score measured by Pittsburgh Sleep

Quality Index (PSQI) was higher than the suggested clinical cut off, which is similar to previous reports from the US and Australia (Patterson et al., 2010; Sofianopoulos et al., 2011a). The prevalence of high OSA risk among Australian paramedics increased since the last report, from 21% to 40% in the present study (Sofianopoulos et al.,

Chapter Two – Sleep and mental health in Australian paramedics

2011a). Given the established prevalence of sleep problems among paramedics, more attention must be paid to the consequences of this problem and also to identifying possible strategies for alleviation.

Depression and anxiety symptoms were significantly associated with insomnia symptoms, sleep quality, PTSD symptoms, and fatigue. Paramedics at a high risk of

OSA and SWD reported significantly higher levels of depressive symptoms compared to paramedics at low risk. In addition, the regression analysis showed insomnia symptoms, fatigue, and PTSD symptoms were significant predictors of depression and anxiety symptoms, with insomnia being a major contributor. The higher prevalence of depression and anxiety symptoms among paramedics is significantly related to sleep problems, potentially stemming from their shift-work. Although there is little data investigating the effect of sleep problems on the mental health of paramedics,

Courtney et al. (2013) reported a significant association between chronic fatigue and depression among rural Australian paramedics (Courtney et al., 2013). Other studies have focused on reporting the prevalence of depression or anxiety, rather than investigating the burden of these ailments among paramedics (Bentley et al., 2013;

Sofianopoulos et al., 2011a). Studies from other shift-worker populations seem to support the findings of this study, as Canadian shift-workers reported a positive association between insomnia symptoms and depression and anxiety (Vallieres et al.,

2014). Similarly, higher depressive symptoms were explained by sleep deprivation among U.S. firefighters (Carey et al., 2011). Despite the implications of sleep disorders, depression and anxiety are strongly related to impaired performance and safety, which impacts both caregivers and the public (Haslam, Atkinson, Brown, &

Haslam, 2005). Current findings on Australian paramedics support those on other shift-worker populations and indicate that sleep disorders (particularly insomnia) in

Chapter Two – Sleep and mental health in Australian paramedics paramedics are a possible risk factor for developing depression and anxiety symptoms.

The current study also demonstrated that the chronotype of shift-workers may also be related to their mental health. Evening-type paramedics reported significantly higher levels of depressive, anxiety, insomnia, and PTSD symptoms and worse sleep quality compared to morning-inclined paramedics. Three outcomes of the SF-36 questionnaire fatigue, mental health, and general health were significantly worse among evening-inclined paramedics compared to morning types. In support of this finding, a study of firefighters by Yun et al. (2015) found that evening-inclined individuals reported significantly higher levels of depression, PTSD, stress, and poorer sleep quality compared to morning-inclined individuals. Findings from the general population seem to be consistent with current findings and those from shift-work populations in terms of sleep and mental health outcomes in evening-inclined and morning-inclined individuals (Medeiros et al., 2001). Generally, evening types reporting more health issues than morning types because of their natural tendency to stay up late and sleep in late, causing a chronic disruption to their circadian rhythm

(Reid & Zee, 2005). As a result, chronic circadian misalignment can have a negative impact on an individual’s general well-being and mental health (Institute of Medicine

(US) Committee on Sleep Medicine and Research; Colten, 2006; Krystal, 2012).

During shift-work, regardless of chronotype, the majority of the workers reported significantly higher rates of different health issues as a result of circadian disruption, with higher rates reported by evening-type workers. Chronotype is still unrecognized in the current rostering system, making it a hidden contributor when investigating well- being, sleep, and mental health, especially among workers with late chronotype. On the other hand, a recent report stated that shift-workers tend to prefer the schedule

Chapter Two – Sleep and mental health in Australian paramedics that matches their natural chronotype (Guimarães, Pessa, & Biguelini, 2012), with preliminary evidence suggesting that matching shift schedules to the natural chronotypes of shift-workers may improve their sleep duration and quality (Uzoigwe &

Sanchez Franco, 2018). To summarize, the majority of shift-workers are working against their natural circadian rhythm, placing them at higher risk of developing mood and chronic disorders. Therefore, matching chronotype to shift preference may be a possible solution to improve shift-workers’ sleep quality, mental health, and well- being—especially for workers with evening chronotype.

The present study reported the prevalence of self-reported sleep disturbances, mental health concerns and chronotype preferences in Australian paramedics’ in a cross-sectional study. Causality cannot be evaluated with such a design, therefore prospective cohort studies are needed to examine relationships between these contributory factors. As participation was restricted to active paramedics, those with a history of diagnosed mental or sleep disorders reported in this study were included in the results. To screen-out such individuals, still in active service would under-estimate the actual prevalence of such issues in this population. Despite a moderate sample size, there was sufficient power to detect relationships and differences between the variables that were of interest in testing the current hypotheses. The sample was reflective of the industry in terms of age and shift type, however, the study cannot exclude the presence of self-selection bias as the study was voluntary (Australian

Government Job Outlook, 2016). Another limitation was the comparison to normative data from different populations. This was mainly due to limitations in the availability of

Australian data for the adopted tools. Where possible, the norms used were from

Australia or the general population of the Western countries with similar demographic profiles to Australians. Although not ideal, it provided a reasonable comparison

Chapter Two – Sleep and mental health in Australian paramedics between paramedics and the general population. Another limitation was that the majority of the paramedics (85.4%) worked in a rotating shift, with 4 days on (2 days and 2 nights) and 4 days off. Unfortunately, there was not enough data from the other shift types to conduct statistical analysis for comparing shift type on the outcome measures. Finally, one might anticipate that paramedic's work tenure could have an impact on these relationships. For example, a new worker starting a rotating shift might show different relationships to more experienced paramedics. Unfortunately, the study did not look into work tenure and its effect on the outcomes. The age range was typical of these workers so the effect of time working under these conditions would potentially be a factor unaccounted for in this study and source of variability in the results we have observed.

To conclude, the present study indicates that there is a high prevalence of mental health and sleep issues in Australian paramedics, particularly insomnia, depression, and anxiety. The levels of depression and anxiety were significantly correlated with reported insomnia. Also, paramedics in this study with an evening chronotype had poorer sleep, mental health and general health. Prospective cohort studies are needed to thoroughly investigate the associations between sleep and mental health in paramedics, and whether different shift-types are differentially affected. Considering chronotype during shift-work may reduce adverse health consequences. Identifying and treating sleep disorders in paramedics may improve their mental health.

Chapter Three – Sleep and mental health: a comparison study

Chapter Three : Sleep and mental health among paramedics from Australia and Saudi Arabia: a comparison study

Preface

From Chapter 2 (study 1), Australian paramedics reported a higher prevalence of different sleep and mental health concerns as compared to the general population, with insomnia being a significant contributor to the burden of depression and anxiety.

Insomnia and sleep issues are typical challenges that originated from continuous disruption to the normal sleep cycle because of working in different types of shifts.

However, current literature indicates that paramedics from Saudi Arabia may be facing more challenges than Australians due to higher occupational demands. This is mainly because fewer paramedics are serving a larger population when compared to

Australia. This study subjectively investigated the prevalence of sleep and mental health disorders among paramedics in Saudi Arabia and conducted a comparison between Saudi paramedics and Australian paramedics, reporting on differences in sleep and mental health parameters.

Publication

Khan, W.A.A.; Conduit, R.; Kennedy, G.A.; Abdullah Alslamah, A.; Ahmad Alsuwayeh,

M.; Jackson, M.L. Sleep and Mental Health among Paramedics from Australia and

Saudi Arabia: A Comparison Study. Clocks & Sleep 2020, 2, 246-257. https://dx.doi.org/10.3390/clockssleep2020019

Candidate’s contribution

Wrote the manuscript, conducted the study, and the data analyses.

Chapter Three – Sleep and mental health: a comparison study

Abstract

Paramedics face many challenges while on duty, one of which is working different types of shifts. Shift work has been linked to a number of health issues such as insomnia, depression, and anxiety. Besides shift work, Saudi paramedics, a group that has not been investigated for sleep or mental health issues previously, may be facing more demands than Australian paramedics due to lower numbers of paramedics in comparison to the general population. The aim of this study was to investigate the prevalence of sleep and mental health disorders among paramedics in Saudi Arabia and Australia. Paramedics were invited to complete a survey to assess stress, posttraumatic stress disorder (PTSD), depression, anxiety, daytime sleepiness, insomnia, sleep quality, shift work disorder, obstructive sleep apnoea, fatigue, and general health. A total of 104 male Saudi paramedics (M age = 32.5 ± 6.1 years) and 83 male paramedics from Australia (M age = 44.1 ± 12.1 years) responded to the survey.

Significantly higher rates of depression, PTSD, insomnia, and fatigue, along with significantly poorer physical functioning were observed among Saudi paramedics in comparison with Australian paramedics. However, Australian paramedics reported significantly poorer sleep quality and general health in comparison to Saudi paramedics. After removing the effect of driving and working durations, outcomes were no longer significant. The higher burden of depression and PTSD among Saudi paramedics may be explained by longer hours spent driving and longer work durations reported by this group. Taking into consideration the outcomes reported in this study, more investigations are needed to study their possible effects on paramedic’s cognition, performance, and safety.

Keywords: Depression, PTSD, paramedics, Saudi Arabia, occupational health

Chapter Three – Sleep and mental health: a comparison study

3.1 Introduction

The continuous demand for 24-hour emergency support requires paramedics to work shift schedules that are outside the standard 8:00 a.m. to 5:00 p.m. schedule

(National Sleep Foundation, 2017). The adverse consequences of shift work have been well described in the literature, and there is now evidence to suggest that it is becoming an increasingly serious public health issue (Costa, 2010). According to

Zverev et al. (2009), sleep deprivation is the main outcome experienced by shift workers (Zverev & Misiri, 2009). Sleep deprivation may contribute to the onset of many health issues, including mental health disorders (Fernandez-Mendoza & Vgontzas,

2013). In addition to shift work, paramedics have to cope with other significant challenges, including trauma, accidents, and death. This places them at higher risk of developing mental health issues. Global levels of stress and depression are high among paramedics, with the implication that the health and safety of patients and paramedics are potentially compromised (Bajraktarov et al., 2011). More work is required to fully understand the burden of mental health issues among paramedics.

The duties, regulations and challenges that paramedics face differ from one country to another. Such variations probably contribute to the burden of mental health and sleep disorders. The comparison of different populations can be useful in informing researchers and adding useful knowledge to the field including: (1) awareness that different traditions/cultures can affect the perception of various occupational risks or hazards; and (2) the development of more comprehensive and effective control strategies that are applicable in different countries (Department of

Sociology, 1995). There is a little known about paramedics in the Middle East, in general, and Saudi Arabia, in particular. Therefore, this study compared a Middle

Eastern country where advanced rules and regulations of occupational health and

Chapter Three – Sleep and mental health: a comparison study safety (OHS) are emerging, to a country with well-developed OHS regulations. Such a comparison may provide unique insights about this population, along with a better understanding of commonalities in paramedics across cultures.

One of the key differences observed in current official figures regarding paramedics in Saudi Arabia and Australia is the total population size. The total number of paramedics in Saudi Arabia in 2017 was estimated to be 7,864 active paramedics

(General Authority for Statistics, 2017). In Australia, the number of paramedics is double that, with 17,800 being the official estimate in 2018 (Australian Government

Job Outlook, 2016). The populations of Saudi Arabia (32,612,641) and Australia

(25,180,200) estimated for the same year (Australian Bureau of Statistics, 2019;

General Authority for Statistics, 2018), mean that in Australia, there is one paramedic for every 1,415 citizens, while in Saudi Arabia, there is one paramedic for every 4,147 citizens. Thus, a single paramedic in Saudi Arabia services four times more people than a paramedic in Australia. This suggests that Saudi paramedics have a much greater workload and may face greater threats to their wellbeing than paramedics in

Australia.

Another important difference between Saudi Arabia and Australia that could impact mental health and well-being is the rate of motor vehicle accidents. Saudi

Arabia has one of the highest annual fatality rates for motor vehicles accidents in the world (Mansuri et al., 2015), with approximately 24 fatalities per 100,000 people

(Mansuri et al., 2015). In contrast, Australia has a motor vehicle fatality rate that is much lower at 4.6 fatalities per 100,000 people (Australian Government, 2018).

Therefore, Saudi paramedics would be dealing with more traumatic events due to higher rates of accidents and would put them at greater risk of developing anxiety, depression and PTSD (MacDonald et al., 2003; O'Donnell et al., 2004).

Chapter Three – Sleep and mental health: a comparison study

The aim of this study was to compare sleep and mental health problems between Saudi Arabian and Australian paramedics. We hypothesized that Saudi

Arabian paramedics would report higher levels of sleep and mental health issues than

Australian paramedics due to greater work load demands.

3.2 Method

3.2.1 Participants

The recruitment of paramedics for this study was facilitated and supported by the Saudi Red Crescent Authority (SRCA). Printed versions were distributed to the

Saudi paramedics and electronic versions of the survey were distributed to paramedics in Australia. The study was restricted to active paramedics who worked any type of shift. A total of 100 paramedics were required to satisfy power calculations based on a moderate effect size (0.30), a significance level of p < 0.05 and at a power of .80 (Cohen, 1992). A total of 121 Saudi Arabian male paramedics (only males work in this occupation in Saudi Arabia) participated in the survey from the Western region of Saudi Arabia. The response rate to the survey was 30%. In addition, the responses of 83 males from a sample of paramedics from Victoria, Australia to the same survey in a previous study (response rate = 6.8%) (Khan et al., 2020) were included in the analyses to provide a comparison with the Saudi sample.

3.2.2 Materials

The survey contained a set of validated sleep, mood, and health questionnaires and required approximately 30 minutes to complete. The initial part of the survey gathered demographic information, including age, gender, height, weight, use of cigarettes (smoking), medical history, use of medications, daily caffeine consumption, and a few work-related questions to determine current shift schedule, weekly working

Chapter Three – Sleep and mental health: a comparison study hours, weekly driving hours for work purposes, and current position in the SRCA. The validated set of surveys included in this study are listed below. A group of validated instruments to assess sleep, mood and general health were included in the survey

(Table 3.1).

3.2.3 Procedure

The Australian survey was distributed across the state of Victoria, Australia from December 2017 until December 2018, and managed by the Ambulance

Employee Australia Victoria (AEAV). A Qualtrics survey link was distributed to the

Australian paramedics via emails and was also posted to their web-based newsletter.

Distribution of the survey across the Makkah District, Saudi Arabia, from November

2018 until January 2019 was managed by the SRCA. Saudi paramedics were actively recruited from their work stations. Paramedics were asked to read the participants information sheet and to consent before taking the actual survey. No incentives were provided to participants. The study was approved by the Human Research Ethics

Committee at the Royal Melbourne Institute of Technology (Approval # 21420).

Chapter Three – Sleep and mental health: a comparison study

Table 3.1. Validated sleep and mental health questionnaires used in the study.

Questionnaire Arabic validation Cut off Items Reliability / validity General Health Questionnaire (SF-36) (Ware & Yes (Sheikh, Yagoub, NA** 36 Yes Sherbourne, 1992) Elsatouhy, Al Sanosi, & Mohamud, 2015) Perceived Stress Scale (Cohen et al., 1983) Yes (Almadi, Cathers, (>13) 14 Yes Hamdan Mansour, & Chow, 2012) Beck Depression Inventory-Short Form (Beck et al., Yes (Al-Musawi, 2001) (>4) 13 Yes 1996)

State-Trait Anxiety Inventory-Short Form (Marteau & Yes (Marteau & Bekker, (>36) 6 Yes Bekker, 1992) 1992)

Shift-work Disorder Screening Questionnaire Yes (Zaki, 2016) NA** 4 Yes (Barger et al., 2012)

Pittsburgh Sleep Quality Index (Buysse et al., 1989) Yes (Suleiman, Yates, (>5) 18 Yes Berger, Pozehl, & Meza, 2010) Pittsburgh Sleep Quality Index-Addendum for Yes (Al-Duhoun, 2012) (>3) 10 Yes PTSD* (Germain et al., 2005)

Epworth Sleepiness Scale (Johns, 1991) Yes (Ahmed et al., 2014) (>10) 8 Yes

Insomnia Severity Index (Bastien et al., 2001) Yes (Suleiman & Yates, (>14) 7 Yes 2011)

Chapter Three – Sleep and mental health: a comparison study

Berlin Questionnaire for OSA* (Netzer et al., 1999) Yes (Saleh, Ahmad, & NA** 10 Yes Awadalla, 2011)

Fatigue Severity Scale (Krupp et al., 1989) Yes (Al-Sobayel et al., 2016) (>4) 9 Yes

Chapter Three – Sleep and mental health: a comparison study

3.2.4 Statistical analyses

The data were analysed using the IBM Statistical Package for the Social

Sciences (SPSS) version 24, Macintosh and Microsoft versions. Data distributions were adequate in terms of normality, linearity, and homoscedasticity. The data were also tested for outliers, missing values, and data entry errors. Data cleaning led to the elimination of 17 participants out of the total 121 Saudi respondents due to missing respondent data. The prevalence of sleep and mental health outcomes were presented as percentages or means and standard deviations. Independent samples t-test were used to examine group differences for sleep and mental health variables.

Age, BMI, driving hours and working hours were significantly different between the groups, therefore multivariate analysis of covariance (MANCOVA) was subsequently used to further investigate the unique differences between the two groups on the other variables while controlling for these demographic and work-related factors.

3.3 Results

A total of 104 male paramedics from Saudi Arabia who submitted complete data were included in the final data set. Data from Australian male paramedics (n = 83) that has been published previously (Khan et al., 2020) were included as a comparison to the Saudi sample. Demographics and work information for the two cohorts are presented in Table 2. The rotating shift was the most prevalent shift reported by both cohorts, with 95% of Saudi paramedics and 76% of Australian paramedics reported working in a rotating shift, while 8% of the Australian and 5% of Saudi paramedics worked in a fixed shift. Rotating shift is a roster that includes 4 days of duty with both day and night shifts in a single roster, while the fixed shift is 4 days of duty of either day or night shifts in a single roster. The rotating roster for the Saudi paramedics

Chapter Three – Sleep and mental health: a comparison study consisted of two days of standard day shifts (12 h / shift) and two days of night shifts

(12 h / shift). The rotating roster for the Australian paramedics consisted of two days of standard day shifts (10 h / shift) and two days of night shifts (14 h / shift). Sixteen percent of Australian paramedics worked a rural shift roster of 8 consecutive days of day shifts with overnight on-call. Saudi paramedics reported only three days of break/recovery in-between rosters compared to four days reported by Australian paramedics. The Saudi paramedics were significantly younger than the Australian paramedics (p < 0.001). The mean BMI was significantly higher among the Australian sample compared to Saudi sample (p < 0.05). The Saudi paramedics reported significantly longer working (p < 0.05) and driving (p < 0.001) durations (hours) per week in comparison to the Australians (Table 3.2).

Table 3.2. Sample characteristics using independent samples t-test with effect size.

Australian Saudi paramedics paramedics t(df), p,, 95% CI, Cohen’s d. M(SD) M(SD) Age (years) 44.1(12.1) 32.5(6.1) t(180)= -8.429, p < .001, [-14.3, - 8.9], d = 1.22

BMI* 27.9(4.3) 26.1(5.1) t(184)= -2.573, p = .01, [-3.2, -0.4], d = 0.38

Working 45.4(10.7) 48.3(2.5) t(170)= 2.565, p < .001, [0.4, 5.4], (hours/week) d = 0.37

Driving** 17.9(11.2) 26.2(18.7) t(170)= 3.487, p < .001, [3.7, 12.8], (hours/week) d = 0.54

Note, *(BMI) body mass index, **Ambulance driving.

Chapter Three – Sleep and mental health: a comparison study

3.3.1 A comparison between Saudi and Australian paramedics across sleep and mental health outcomes

Table 3.3. shows the means and standard deviations of the Saudi and

Australian paramedics for sleep and mental health variables. Saudi paramedics had significantly higher scores for stress, depression, PTSD and insomnia symptoms in comparison to Australians, while the Australian paramedics had significantly higher scores for fatigue and poorer sleep quality. The calculated effect size was large for depression symptoms, with small to medium effects for the rest of the variables. There were no significant differences for anxiety symptoms and daytime sleepiness between the two groups of paramedics.

For questionnaires with published criteria for “at risk” scores, the prevalence for

“at risk” individuals are shown in Table 3.4. Australian paramedics reported a greater prevalence of perceived stress, fatigue, poor sleep quality, anxiety, SWD and OSA in comparison to Saudi paramedics. However, Saudi paramedics reported higher rates of insomnia, daytime sleepiness, depression and PTSD.

Chapter Three – Sleep and mental health: a comparison study

Table 3.3. Means and standard deviations of Saudi and Australian paramedics across study variables.

Australian Saudi Questionnaire paramedics paramedics t(df), p, Cohen’s d. M(SD) M(SD) PSS 19.5(4.1) 21.9(10.3) t(168)= 1.921, p < .001, d = 0.31

BDI-SF 7.2(6.8) 17.4(11.9) t(166)= 6.523, p < .001, d = 1.05

PSQI-A 2.6(3.2) 4.6(4.3) t(157)= 3.271, p = .005, d = 0.54

ISI 11.5(5.9) 14.2(7.1) t(155)= 2.469, p = .02, d = 0.41

FSS 4.3(1.3) 3.6(1.9) t(163)= -2.797, p < .001, d = 0.45

PSQI 8.9(4.1) 6.6(4.8) t(157)= -3.215, p = .03, d = 0.53

STAI-SF 41.1(18.5) 38.9(12.7) t(164)= -.871, p = .05, d = .13

ESS 8.2(6.1) 9.9(5.1) t(153)= 1.912, p = .47, d = 0.31

Note, Perceived Stress Scale (PSS), Beck Depression Inventory-Short Form (BDI- SF), Pittsburgh Sleep Quality Index-Addendum (PSQI-A), Insomnia Severity Index (ISI), Fatigue Severity Scale (FSS), Pittsburgh Sleep Quality Index (PSQI), State-Trait Anxiety Inventory-Short Form (STAI-SF), and Epworth Sleepiness Scale (ESS). Statistical comparisons of the groups using independent samples t-test with p value and effect size (Cohen’s d) are shown.

Chapter Three – Sleep and mental health: a comparison study

Table 3.4. Incidences of Saudi and Australian paramedics across study variables.

“At risk” Australian Saudi Questionnaire Criteria paramedics paramedics PSS (Cohen et al., > 28 93% 31% 1983) BDI-SF (Beck et al., > 19 32% 41% 1996) PSQI-A (Germain et > 3 29% 42% al., 2005) ISI (Bastien et al., > 14 34% 51% 2001) FSS (Krupp et al., > 3 74% 56% 1989) PSQI (Buysse et al., > 4 81% 54% 1989) STAI-SF (Marteau & > 36 61% 53% Bekker, 1992) ESS (Johns, 1991) > 12 22% 32%

SWD* (Barger et al., NA* 54% 51% 2012) BQ** (Netzer et al., NA** 46% 36% 1999)

Note, * Calculated by a special algorithm provided by the original author (Barger et al., 2012), ** two positive groups or more indicated positive outcome, Perceived Stress Scale (PSS), Beck Depression Inventory-Short Form (BDI-SF), Pittsburgh Sleep Quality Index-Addendum (PSQI-A), Insomnia Severity Index (ISI), Fatigue Severity Scale (FSS), Pittsburgh Sleep Quality Index (PSQI), State-Trait Anxiety Inventory- Short Form (STAI-SF), Epworth Sleepiness Scale (ESS), Shift-Work Disorder (SWD), and Berlin Questionnaire (BQ) for Obstructive Sleep Apnea (OSA).

Chapter Three – Sleep and mental health: a comparison study

MANCOVAs were conducted to control for the effects of age and BMI on the outcomes of the assessments for sleep (PSQI and ISI), mental health (BDI and PSQI-

A), general health (SF-36: physical functioning, general health, and fatigue), stress

(PSS), and fatigue (FSS). Saudi paramedics reported significantly higher depression

(F (3, 114) = 6.52; p < .001; partial η2 = .15), PTSD (F (3, 114) = 9.77; p < .001; partial

η2 = .20) and insomnia (F (3, 114) = 3.17; p = .02; partial η2 = .07) symptoms, and poorer general health (F (3, 114) = 9.42; p < .001; partial η2 = .19) than Australian paramedics. Australian paramedics reported significantly higher fatigue (F (3, 114) =

14.24; p < .001; partial η2 = .27), poorer sleep quality (F (3, 114) = 3.16; p = .02; partial

η2 = .07), and lower physical functioning (F (3, 114) = 8.13; p < .001; partial η2 = .17) compared to Saudi paramedics. After controlling for the effects of age and BMI, stress;

PSS (F (3, 114) = 2.20; p = .09; partial η2 = .05) and fatigue; FSS (F (3, 114) = 0.96; p = .41; partial η2 = .02) scores were no longer significantly different between two groups of paramedics.

MANCOVAs were used to control for the effect of driving and working durations on the main outcomes of the study including sleep (ISI and PSQI), mental health (BDI and PSQI-A), and fatigue (FSS). Scores were no longer significant after controlling of driving durations for insomnia (F (1, 132) = 3.56; p = .06; partial η2 = .02), sleep quality

(F (1, 132) = 1.64; p = .06; partial η2 = .01), depression (F (3, 132) = 3.87; p = .20; partial η2 = .02), PTSD (F (3, 132) = 3.41; p = .10; partial η2 = .02), and fatigue (F (3,

132) = 0.43; p = .23; partial η2 = .01). After controlling for work duration, insomnia (F

(1, 132) = 0.24; p = .06; partial η2 = .01), sleep quality (F (1, 132) = 0.03; p = .06; partial η2 = .01), depression (F (3, 132) = 0.50; p =20 .05; partial η2 = .01), PTSD (F

(3, 132) = 0.80; p = .10; partial η2 = .01), and fatigue (F (3, 132) = 0.10; p = .23; partial

η2 = .01) symptoms were no longer difference between the two groups.

Chapter Three – Sleep and mental health: a comparison study

3.3.2 A comparison between Saudi and Australian paramedics across General

Health Questionnaire (SF-36) subscales

Results of the SF-36 general health questionnaire for the Saudi and Australian paramedics are shown in Table 3.5. Australian paramedics had a significantly higher score for physical functioning and significantly lower scores on the fatigue and general health subscales in comparison to Saudi paramedics. The calculated effect size for general health and fatigue scores were large. Scores on the other items of the SF-36, including role limitation due to physical health, role limitation due to emotional problems, emotional well-being, social functioning, and pain, were not significantly different between the two groups of paramedics.

Chapter Three – Sleep and mental health: a comparison study

Table 3.5. Comparison of means and standard deviations for the general health questionnaire (SF-36) subscales.

Australian Saudi

SF-36 subscales M(SD) M(SD) t(df), p, Cohens d

Physical functioning 87.5(15.1) 74.1(24.2) t(170)= -4.258, p < .001, d = 0.66

Role physical 72.8(33.3) 71.3(29.9) t(170)= -3.00, p = .33, d = 0.04

Bodily pain 69.1(21.6) 71.5(22.8) t(170)= .733, p = .29, d = 0.11

General health 52.5(25.1) 71.6(18.8) t(170)= 5.711, p = .005, d = 0.86

Vitality/fatigue 44.1(21.7) 67.9(21.5) t(170)= 7.241, p < .001, d = 1.10

Social functioning 72.7(26.1) 66.6(23.4) t(170)= -1.632, p = .41, d = 0.24

Role emotional 63.7(41.7) 72.4(27.7) t(170)= 1.637, p = .32, d = 0.24

Mental health 64.1(20.3) 69.3(21.4) t(170)= 1.630, p = .34, d = 0.25

Chapter Three – Sleep and mental health: a comparison study

3.4 Discussion

The present study investigated the prevalence of sleep and mental health concerns among Saudi paramedics and conducted a comparison with previously collected data from males in a sample of Australian paramedics (Khan et al., 2020).

Saudi paramedics reported significantly higher rates of perceived stress, depression,

PTSD, and insomnia compared to paramedics in Australia. In contrast, Australian paramedics reported significantly poorer sleep quality compared to Saudi Arabian paramedics, even after controlling for age and BMI. For the general health questionnaire, Saudi paramedics reported significantly higher levels of fatigue and poorer physical functioning, but better general health, compared to Australian paramedics with large effect sizes observed. However, it seems that driving and working durations have a significant effect on insomnia, sleep quality, depression,

PTSD, and fatigue levels. As after removing their effects, outcomes were no longer significant between Saudi and Australian paramedics. Saudi paramedics were significantly younger than Australian paramedics, this is represented by the fact that the average Saudi general population (30 years) is younger than the average

Australian general population (37.1 years) (Australian Bureau of Statistics, 2017;

General Authority Statistics, 2017). Changing careers is not common in Saudi Arabia as in Australia, which may also explain the significant age gap between the two populations. The amount of training/qualification was similar between the two populations.

Paramedics from Saudi Arabia revealed more mental health concerns than

Australian paramedics, including depression and PTSD. The prevalence of self- reported depression and severity of depressive symptoms among Saudi paramedics was significantly higher compared to Australian paramedics with a large effect size

Chapter Three – Sleep and mental health: a comparison study observed, with similar figures to that found in a previous Australian sample

(Sofianopoulos et al., 2011a). The prevalence and severity of self-reported PTSD were also significantly higher among Saudi paramedics (41%) compared to prevalence rates among Australian paramedics, and prevalence rates of paramedics from other countries, including Germany and Brazil with 15% and 20%, respectively (Berger et al., 2007; Streb et al., 2013). Also, perceived stress was significantly higher among

Saudi paramedics compared to Australians, but more Australian paramedics screened positive in the lower end of the perceived stress scale. The severity of self-reported anxiety was not significantly different between the two samples, with more than half of the two cohorts screened positive. Paramedics from Saudi Arabia reported higher mental health concerns than paramedics from Australia including depression, PTSD, and stress.

Saudi paramedics have in general not been investigated for sleep and mental health problems. However, a recent study evaluated the occupational challenges that

Saudi paramedics face during active duty from their own perception reported certain barriers or challenges that paramedics reported facing, including traffic congestion, harassment from family members, lack of staff competence, lack of trust and confidence, lack of independence, resistance from patients, involvement in legal issues, and impression of the paramedics on the general community and family members of patients (Alanazi, 2012). Such challenges may affect the mental health of the paramedics; for example, verbal abuse was significantly linked to higher rates of depression among nurses in the United States (Geiger-Brown, Muntaner, McPhaul,

Lipscomb, & Trinkoff, 2007). Also, traffic congestion was found to be associated with poorer mental health outcomes among bus drivers (Evans & Carrere, 1991). Another contributor to an increased burden of depression among Saudi paramedics may be

Chapter Three – Sleep and mental health: a comparison study their extremely low population (7,864 paramedics) as compared to the population of

Australian paramedics (17,800) (Australian Government Job Outlook, 2016; General

Authority for Statistics, 2017). This is particularly represented in the longer working and driving durations reported by the Saudi paramedics, which was significantly related to the depression scores of the Saudi paramedics. One study has found a significant association between longer driving hours and poorer mental health (Ding,

Gebel, Phongsavan, Bauman, & Merom, 2014). Another recent report indicated that depressive symptoms were linked to longer working duration (Weston, Zilanawala,

Webb, Carvalho, & McMunn, 2019). In addition, a five-year follow-up study reported that longer working duration is a risk factor for developing depression (Virtanen et al.,

2011).

Saudi paramedics reported significantly higher levels of PTSD than Australian paramedics, which is an indicator of greater exposure to trauma (Skogstad et al.,

2013). Higher rates of fatal car accidents in Saudi Arabia compared to Australia are likely to contribute to this burden of PTSD among Saudi paramedics. The fatality rate due to car accidents is much higher in Saudi Arabia than Australia, with 24 fatalities per 100,000 people and 4.6 fatalities per 100,000 people, respectively (Australian

Government, 2018; Mansuri et al., 2015). Other possible causes of higher PTSD rates are lack of organizational support, lack of appropriate training, and conflict with patients’ family members (Skogstad et al., 2013), which have previously been reported by Saudi paramedics to be significant challenges or barriers (Alanazi, 2012).

According to Flory (2015), trauma exposure can lead to developing both PTSD and depression (Flory & Yehuda, 2015) which are both complex disorders that are more prevalent among Saudi than Australian paramedics. Possible predictors of depression and PTSD among Saudi paramedics are higher fatal accident rates, traffic congestion,

Chapter Three – Sleep and mental health: a comparison study lack of organizational support, lack of appropriate training, and more exposure to trauma. Most importantly and supported by findings from the present study and previous shift work reports (Ding et al., 2014; Virtanen et al., 2011; Weston et al.,

2019), higher work-load represented by longer driving and working durations may have a negative relationship with on depression and PTSD scores of shift workers in general, and paramedics in particular.

There are many consequences of depression and PTSD to the health and safety of paramedics. Depressive symptoms are linked to impaired cognition, particularly impaired decision-making and problem-solving abilities, which are critical abilities for emergency support (Leykin, Roberts, & Derubeis, 2011). Greater rates of symptoms of PTSD have also been linked to impaired cognition, lowered performance, and impaired decision-making (Regehr & LeBlanc, 2017). Depression and PTSD combined can result in more prevalent and more severe cognitive impairments (Flory

& Yehuda, 2015). Impaired cognition, especially during emergency medical support, is a serious issue for the safety of both the emergency services workers and the patients. More studies are required to investigate if cognitive issues are prevalent among paramedics and if they are related to mental health outcomes or not.

Sleep and fatigue were also poor among all paramedics in this study. Insomnia was significantly higher and more prevalent among Saudi’s compared to Australian paramedics. The prevalence of excessive daytime sleepiness among Saudi paramedics, a typical sign of insomnia, was higher than Australian paramedics.

However, the rate of poor sleep quality among Saudi paramedics was lower than in the Australian cohort, with over 80% of the Australian paramedics meeting the criteria for poor sleep quality. This is similar to previous reports of 68% meeting criteria for poor sleep in Australian paramedics (Sofianopoulos et al., 2011a). Similarly, fatigue

Chapter Three – Sleep and mental health: a comparison study was less prevalent among Saudi paramedics than in Australian paramedics. The prevalence of likely OSA was higher in Australian paramedics, which could be explained by older age and the higher BMI of the Australian sample. The prevalence of SWD was particularly high in the current study compared to previous reports in firefighters from the United States (9%) (Barger et al., 2015), with over half of the Saudi and Australian paramedics at risk for this disorder. The high rates of SWD in these two samples are concerning and suggest that this occupational group may not be coping with the demands of their schedules. This may lead to higher mental health issues, as SWD was found to be a significant contributor to depression and anxiety symptoms among hospital shift workers in Australia (Booker et al.). Such variations in sleep outcomes can be influenced by many factors including age, BMI, health conditions, shift type, or work-load. This highlights the need for additional support and education about shift work, particularly in graduate paramedics who may be facing shift work for the first time.

Although sleep disorders were common among all paramedics in this study,

Saudi paramedics reported significantly higher levels of insomnia. Insomnia is one of the most important contributors to the burden of depression, especially in shift workers

(Benca & Peterson, 2008). Even though there is little data investigating the effects of insomnia on depression among paramedics, insomnia was a significant predictor to the variance of rates and severity of depression in Australian paramedics (Khan et al.,

2020). Moreover, Courtney et al. (2013) reported a significant association between chronic fatigue and depression among Australian paramedics (Courtney et al., 2013).

Other studies have focused on reporting the prevalence of depression rather than investigating the burden (Bentley et al., 2013; Sofianopoulos et al., 2011a), but studies from other shift worker populations support the proposed relationship, such as a study

Chapter Three – Sleep and mental health: a comparison study of Canadian shift workers reporting a positive association between insomnia symptoms and depression (Vallieres et al., 2014). Similarly, higher rates of depressive symptoms among US firefighters were explained by sleep deprivation (Carey et al.,

2011). Thus, the greater variance in rates of depression may be explained by higher rates of insomnia among Saudi paramedics.

Women in Saudi Arabia work in all medical fields but not in emergency medical support. Having females in the workforce may affect the prevalence of sleep and mental health concerns. In the general population, it is known that the prevalence of mental health and sleep concerns are higher in women when compared to men

(Emslie et al., 2002; Hale et al., 2009; Mallampalli & Carter, 2014). However, the role of gender may be different in shift work, as among Australian paramedics there were no significant differences between men and women for sleep and mental health issues

(Khan et al., 2020). A study of shift workers from Korea screened for sleep disorders found that men reported significantly higher levels of insomnia as compared to women

(Kang, Kwon, Choi, Kang, & Kim, 2017). In Saudi Arabia, healthcare personnel were screened for sleep disturbances (nurses, technicians, and physicians) and showed no significant gender variations in sleep quality and excessive daytime sleepiness

(Alshahrani, Baqays, Alenazi, AlAngari, & AlHadi, 2017). Other reports from Saudi

Arabia investigated nurses, but their samples were almost only females (99%) (Saquib et al., 2020; Saquib et al., 2019). Having women in the workforce may or may not affect the overall prevalence of sleep or mental health disturbances depending on the shift work population.

Longer working hours were significantly related to poorer quality of sleep, higher scores of insomnia and fatigue among the Saudi Paramedics. Similar to previous findings, higher workload was significantly related to poorer sleep quality and

Chapter Three – Sleep and mental health: a comparison study higher fatigue among nurses and rail industry workers (Dorrian, Baulk, & Dawson,

2011; Ghasemi, Samavat, & Soleimani, 2019). In physicians, higher workload was significantly related to insomnia symptoms (Győrffy, Dweik, & Girasek, 2016). It appears that workload is an important factor affecting sleep and fatigue of shift workers across difference occupations.

The implementation and the rules of occupational health and safety (OHS) in

Australia and Saudi Arabia may vary and may affect workers well-being (Committee.,

2003). The regulations are currently under development in Saudi Arabia (Al Malki,

Endacott, & Innes, 2018; Balkhyour, Ahmad, & Rehan, 2019), while in Australia, the regulations are well developed (Safe Work Australia, 2020). This is represented in the break/recovery days between shifts, as Australian paramedics reported more recovery days than Saudi paramedics, with four and three days, respectively. After working a rotating shift, sleep and alertness are strongly impacted for at least 3 days (Burgess,

2007). There is a need of at least 4 days of break between shifts to allow for better recovery from the previous shift (Burgess, 2007). Inadequate recovery time may have a long-term effect on sleep, thus, affecting the mental health and well-being of rotating shift workers (Burgess, 2007; Jehan, Zizi, Pandi-Perumal, Myers, et al., 2017). The reported differences in recovery time indicate that the Australian OHS guidelines in this field are up to date when compared to the Saudi guidelines and may be indirectly affecting Saudi paramedics mental health and well-being.

This is the first study to investigate mental health and sleep disorders in Saudi paramedics using validated instruments. The study provided robust and detailed information for this population, and the data will act as a strong base for future studies.

The current study reported the prevalence of sleep and mental health problems among

Saudi paramedics and compared the results with Australian paramedics in a cross-

Chapter Three – Sleep and mental health: a comparison study sectional study. Statistically, age and BMI impacted the levels of perceived stress and fatigue between the two cohorts. However, it was important to report the uncontrolled findings between the two populations, with this step including age and BMI as covariates being exploratory. Response bias is a common issue with such a design but can be solved by conducting follow-up or prospective cohort studies. Also, self- selection bias is another common issue that may overestimate the current findings. A comparison between rosters (rotating shift vs fixed / rural shifts) could not be done due to the fact that the majority of both samples reported working in rotating shift schedule.

The difference in the response rate for the Saudi and Australian paramedics is likely due to the recruitment procedure. The survey was conducted online for the Australian paramedics, whereas the Saudi paramedics were actively recruited at work stations with printed copies. The usage of emails for work purposes is different between Saudi and Australia. So, the recruitment procedure was conducted in such a way to make the study known to the Saudi paramedics. In addition, this study included only male paramedics from Saudi Arabia, as this occupation employs only males in Saudi Arabia, which may affect the comparison to previous findings. However, a comparison was conducted to only male paramedics from Australia. Also, due to data availability, the study could not specify the paramedic/citizen ratio for the studied states (Makkah

District in Saudi and Victoria in Australia). Generalizing to the total population sizes was the closest available way of describing this relationship.

In conclusion, in comparison to Australian paramedics, Saudi paramedics reported significantly higher rates of depression and PTSD. This could be explained by higher rates of insomnia, longer driving durations, longer working durations, and higher rates of fatal car accidents which needs to be handled by paramedics.

Depression and PTSD together may affect the safety of the paramedics and the

Chapter Three – Sleep and mental health: a comparison study patients, so future studies must focus on investigating the cognitive functions of paramedics during duty and any effects on their performance and with regards to safety. Employing more paramedics in ambulance services and implementing fatigue risk management strategies (Patterson et al., 2018) may help to improve the sleep and mental health outcomes by reducing the work-load.

Chapter Four – The effect of rotating shift: a field study

Chapter Four : A field investigation of the relationship between rotating shifts, sleep, mental health and physical activity of Australian paramedics

Preface

Paramedics reported significant levels of insomnia, depression, anxiety, and stress from the previous investigations (Chapter 2 & 3). Their mental health was significantly related to their sleep, particularly insomnia. However, such outcomes can be considered long-term or chronic consequences of shift work. The day-to-day interactions and the instant/acute effects of working in shift rotations have never been studied in paramedics. Investigating paramedics while working in the field for an entire rotating shift schedule including break/recovery days with objective measures will allow better insights into the dynamic relationships between sleep and mental health outcomes. The aim of this study was to investigate the acute effects of a rotating shift schedule across four consecutive time points including baseline, day shift, night shift, and recovery days. Outcomes including sleep, mood, stress, fatigue, sleepiness, energy expenditure and physical activity were investigated in-field for 8 consecutive days.

Publication

(Submitted to Scientific Reports, April 2020)

Candidate’s contribution

WK wrote the manuscript, and conducted the study and the data analyses.

Chapter Four – The effect of rotating shift: a field study

Abstract

Paramedics working on a rotating shift are at an increased risk of developing chronic health issues due to continuous circadian rhythm disruption. The acute effects of shift rotation and objectively measured sleep have rarely been reported in paramedics. This study investigated the relationships between a rotating shift schedule and sleep (using actigraphy), subjective reports of sleepiness, mood, stress and fatigue. Galvanic Skin

Response, energy expenditure and physical activity (BodyMedia SenseWear

Armband) were also recorded across the shift schedule. Paramedics were monitored for a period of eight consecutive days across baseline, day shift, night shift, and two days of recovery. Twelve paramedics (M age = 39.5 and SD = 10.7 years) who worked rotational shifts experienced sleep restriction during night shift compared to baseline, day shift and recovery days (p < 0.001). Night shift was also associated with higher levels of stress (p < 0.05), fatigue (p < 0.05), and sleepiness (p < 0.05). One day of recovery was related to a return to baseline functioning. Such shift-related issues have a compounding negative impact on an already stressful occupation with high rates of physical and mental health issues. Therefore, there is an urgent need to investigate methods to reduce rotating shift burden on the health of paramedics. This could be through further research aimed at providing recommendations for shift work schedules with sufficient periods for sleep and recovery from stress.

keywords: Field study, paramedics, rotating shift, sleep, physical activity.

Chapter Four – The effect of rotating shift: a field study

4.1 Introduction

There is an increasing demand for 24-hour emergency medical support, which requires paramedics to work around the clock often in rotating shifts (Courtney et al.,

2013; National Sleep Foundation, 2017). The adverse outcomes of night shift work have previously been reported, and there is a growing evidence indicating that shift work is becoming a serious public health issue (Costa, 2010). Thus, there is an increasing need to examine the impact of shift schedules on health and well-being.

A rotating shift is a combination of a night shift and a day shift in one shift schedule, with recovery days factored in between schedules to allow readjustment to the new roster (Costa, 2010). Rotating shift work is typically adopted to reduce the amount of night work as possible, as it may impact the well-being of the employees

(Knauth, 1993). Although there are a few advantages of rotating shifts over constant night shift, including more stable circadian rhythms and longer sleep times (Alward &

Monk, 1990), it has been shown to impact on a range of health and safety outcomes, including an increased risk of fatigue, accidents, stress, depression, and chronic ailments compared to day shift workers (Akerstedt & Wright, 2009; Angerer et al.,

2017; Ganesan et al., 2019; Ma et al., 2015; Ramin et al., 2015). For example, rotating shift workers reported significantly higher insomnia and excessive daytime sleepiness compared to standard day workers (Chatterjee & Ambekar, 2017). Furthermore, nurses worked in rotating rosters reported more stress as compared to nurses worked in fixed rosters (Lin et al., 2015), and engineers working the same shift reported poor sleep quality and significant levels of fatigue (Vangelova, 2008). Another study reported a strong relationship between a rotating roster and fatigue and sleep problems (De Bacquer et al., 2009). In addition, shift rotation has also been strongly linked to poorer mental health, particularly depression and anxiety (Kalmbach et al.,

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2015). The majority of these reported the possible consequences of a rotating shift in cross-sectional studies from a chronic point of view. Little is known about the immediate or acute effects of a rotating shift on workers, especially those working in the emergency medical fields such as nurses and paramedics.

The day-to-day interaction between shift rotation and workers health has been described in a few studies that used objective measures of sleep and activity. One study from Japan reported daily sleep patterns and physical activity across an entire rotating schedule (Kawada et al., 2008). Physical activity was significantly higher during day shifts than during night shifts, and total sleep time was shorter on day shifts compared to night shifts (5.8 vs 6.4 hours) (Kawada et al., 2008). Another study investigating nurses working fixed shifts indicated that the nurses’ sleep, measured using wrist actigraphy, did not differ significantly between day and night shifts (Geiger-

Brown et al., 2012). In the same study, the levels of subjective fatigue and sleepiness also did not differ significantly between day and night shifts (Geiger-Brown et al.,

2012). Another study of nurses working rotating shifts reported that nurses experienced a shorter duration of sleep on both day and night shifts equally (Choi &

Joo, 2016). However, nurses in another study slept less and reported poorer quality of sleep during night shift compared to day shift during a rotating shift schedule (Zverev

& Misiri, 2009). Thus, rotating shift work may have a more detrimental effect on sleep than fixed shifts. There are some variations in the previous reports due to diversity in occupations, workloads, and shift types. More studies are needed to investigate the effects of rotating shift schedules on health, especially with regard to acute effects contributing to long-term outcomes. In particular, paramedics, due to the traumatic and stressful nature of their work (Hegg-Deloye et al., 2014), are a group that generally need more investigation. In addition to their stressful working environment, sleep and

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Chapter Four – The effect of rotating shift: a field study circadian disruption can directly affect mental health (Walker, Walton, DeVries, &

Nelson, 2020), therefore culminating in a more significant impact on overall well-being

(James, Honn, Gaddameedhi, & Van Dongen, 2017).

The present study aimed to investigate the relationship between a rotating shift schedule on sleep, mood, stress, fatigue, sleepiness, energy expenditure, and physical activity levels among Australian paramedics. Paramedics were monitored for a period of eight consecutive days across pre-shift day (baseline), night shift, day shift, and two days of recovery. It was hypothesized that during night shift day, compared to baseline, day shift, and recovery days, paramedics would report lower sleep duration, physical activity, energy expenditure, poorer mood, and higher stress, fatigue, and sleepiness.

4.2 Method

4.2.1 Participants

Paramedics working in Victoria, Australia were invited to participate in this study through Ambulance Employees Australia Victoria (AEAV). Participation was voluntary and limited to active full-time paramedics aged at least 18 years old, working rotating shifts and without any self-reported history of/or treatment for the following conditions: insomnia, depression, and anxiety. Before consent, paramedics were asked if they have any history of/or received treatment for insomnia, depression or anxiety via phone calls or emails, then invited to the study if the previous inclusion criteria were obtained, otherwise they were excluded from the study. All participants reported working the same rotating shift type. The study was approved by the Human Research

Ethical Committee at the Royal Melbourne Institute of Technology (21420). A power analysis was conducted based on a previous field study in healthcare workers (Da

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Silva, et al. 2009), comparing baseline nocturnal total sleep time compared to daytime total sleep time following nightshift measured with actigraphy (effect size = 0.6). It was estimated that a sample size of 23 was required to detect an effect size of 0.6, with an

α=0.05 and β= 0.8 (Silva Borges & Fischer, 2003). The study used validated objective device (similar to SenseWear) to assess sleep during night duty/rest days.

4.2.2 Materials

BodyMedia SenseWear Armband

The BodyMedia SenseWear Armband (BSA) is a portable device that is connected to sensors where it can measures galvanic skin response, physical activity via step count, and energy expenditure (Sharif & BaHammam, 2013). Galvanic skin response (GSR) is a valid method to detect stress levels through changes in the electrical resistance of the skin (Perala & Sterling, 2007). The BSA was required to be worn on the non-dominant hand throughout the study.

Wrist Actigraphy

The Actiwatch-2 (Philips Respironics, Murrysville, PA, USA) was used for wrist actigraphy, and was worn on the non-dominant wrist. The data from the Actiwatch-2 were extracted via computer using Philips Respironics software. The outcome measures used were total sleep time, sleep efficiency, number of awakenings, wake after sleep onset (WASO), bedtime, get-up time, length of time in bed, and sleep onset latency (Kushida et al., 2001; Morgenthaler et al., 2007). The outcome data from the actigraphy were scored according to using the sleep diary estimated times for sleep onset and final awakening.

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Sleepiness and Stress

The Karolinska Sleepiness Scale (KSS) was used to assess subjective state sleepiness on a nine-point rating scale, with higher scores indicating greater degree of sleepiness (Akerstedt & Gillberg, 1990). Stress was assessed using the question,

‘How stressed do you feel right now?’ answered on a five-point scale from 1 to 5 with higher numbers representing higher levels of stress.

Positive Affect and Negative Affect Scale

The Positive Affect and Negative Affect Scale (PANAS) is a tool with 20 items developed to investigate daily positive and negative emotions (Watson, Clark, &

Tellegen, 1988). The present study used an abbreviated eight-item version that had been validated in a previous naturalistic study (Zohar, Tzischinsky, Epstein, & Lavie,

2005).

Fatigue

Subjective fatigue was investigated using the Samn–Perelli Fatigue Checklist

(Samn & Perelli, 1982). The checklist uses a ratings scale of 1 to 7, with higher scores indicating greater fatigue.

The Pittsburgh Sleep Diary

The Pittsburgh Sleep Diary (PSD) is a validated self-report diary consisting of two main parts (bedtime and waketime) and 21 sub-items in total that were developed to subjectively measure daily sleep quality. Daily events were reported at night in the bedtime part of the diary and information about sleep was reported just after waking up from sleep (Monk et al., 1994).

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Work related questionnaires

In addition to the subjective measurements of sleep and mood, a number of questions were asked during the day including “What was your current shift type: night/day/afternoon/on call/rest day?” “Start and end times for shift/break time and duration,” “How many hours did you spend driving for work purposes?” and “Have you encountered any significant events during the day?”

4.2.3 Procedure

Participants were invited to take part in this study after completing a previous anonymous survey (Khan et al., 2020). Fifteen paramedics accepted to participate in the study out of the 276 invitations (response rate = 5.4%). After obtaining informed consent, participants received the BSA, actigraph, and sleep and work diaries via post with a prepaid return envelope for returning the devices and diaries at the end of the study. Paramedics were asked to wear the BSA and the actigraph on their non- dominant arm for a period of eight consecutive days, starting on the day before their new shift cycle to objectively record their stress and sleep (Figure 4.1). During that time, participants were asked to complete the sleep diary twice a day (before sleep and after waking) and a customized work diary three times a day (before, during, and after work, or equivalent times on recovery days). The study investigated paramedics across five time points within their rotating shift schedules including pre-shift day

(baseline), standard day shifts, night shift/s, recovery days one and two. Data collection started 24 hours before the beginning of the shift cycle and finished three days after the shift ended.

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Days 07:00 12:00 17:00 23:00 07:00 (1) Baseline Q Q Q S S (2) Day shift 1 Q Q Q S S (3) Day shift 2 Q Q Q S S (4) Night shift 1 S S Q Q Q (5) Night shift 2 S S Q Q Q (6) Recovery 1 Q Q Q S S (7) Recovery 2 Q Q Q S S (8) Recovery 3 Q Q Q S S

Figure 4.1. The study procedure and duration throughout a single rotated shift schedule. Note, S (Pittsburgh Sleep Diary), Q (Work diary; Samn-Perelli Fatigue Checklist, Karolinska Sleepiness Scale, and self-reported stress rating), orange bars (scheduled work time), and grey bars (sleep opportunity). Days highlighted with red are included in the statistical analysis.

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Chapter Four – The effect of rotating shift: a field study

4.2.4 Statistical Analyses

The data were analyzed using the IBM Statistical Package for the Social

Sciences (SPSS) version 24. Data distributions were adequate in terms of normality, linearity, and homoscedasticity. The data were also tested for outliers, missing values, and data entry errors. Data cleaning led to the elimination of three participants due to missing data of either actigraphy or diaries, leaving a final sample of 12 participants.

Also, day shift 2, night shift 2 and recovery day 3 were excluded from the analysis as only 5 of the 12 remaining participants completed these days. Three participants were removed because actigraphy data from 1 participant was unable to be downloaded from the device. In addition, the data set from two other participants were missing the key outcomes data required for this study (total sleep time, stress, fatigue, and sleepiness). Three of the eight days were also removed because participants did not respond to the assessments (total sleep time, stress, fatigue, or sleepiness) for those days (day 2, night 2, and recovery 3). One-way repeated measures ANOVA were used to determine the effects of shift period schedule (baseline; day shift 1; night shift 1; recovery day 1 and 2) on sleep, physical activity, GSR, energy expenditure, sleepiness, fatigue, mood, and stress. Post hoc testing was done using the Bonferroni correction. All study outcomes were measured during an entire 24-h period for each time point (e.g., total sleep time during night shift equals sleep during the entire 24- hours (from 07:00h to 07:00h) including any napping opportunity during work or outside work).

4.3 Results

A total of 12 paramedics with complete data were included in the final data set.

All paramedics were working on a rotating shift schedule. The mean age was 39.5

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Chapter Four – The effect of rotating shift: a field study years (SD = 10.7 years), and there was a total of five men and seven women. The mean BMI was 24.5 (SD = 3.4).

4.3.1 Sleep and sleepiness

The average total sleep time (TST; hours) that was recorded from the current sample during the entire 24-hours for each day was as follow: baseline (M = 6.6, SD

= 1.4), day shift 1 (M = 7.2, SD = 1.1), day shift 2 (M = 6.4, SD = 2.2), night shift 1 (M

= 3.8, SD = 1.5), night shift 2 (M = 4.3, SD = 2.0), recovery day 1 (M = 7.2, SD = 1.1), recovery day 2 (M = 7.4, SD = 2.2) and recovery day 3 (M = 7.1, SD = 1.4). During night shift 1 (Day 4), five out of the twelve paramedics napped an average of 2.5 hours before the beginning of night duty (daytime sleep) and the rest of sleep time was recorded during the night shift itself. The remaining participants (n = 7) slept during the night shift 1. During night shift 2 (Day 5), only one out of five slept during the day for only 1 hour, while the rest slept on shift.

A repeated measures ANOVA determined that mean TST differed significantly across the five time points in the rotating shift schedule (F(2.06, 22.29) = 12.37, p < 0.001; η² = 0.510). Post hoc tests using the Bonferroni correction revealed that there was significantly less TST during the night shift one compared to baseline (M =

3.8, SD = 1.5 hours vs. M = 6.6, SD = 1.4 hours, p < 0.001). During the night shift one,

TST was also significantly lower in comparison to day shift one (p = 0.001), recovery day one (p = 0.01) and recovery day two (p = 0.02) (Figure 4.2A).

Similarly, the mean time in bed (TIB) differed significantly across the five time points in the rotating shift schedule (F(2.00, 16.01) = 10.18, p = 0.002; η² = 0.496).

Post hoc tests revealed that there was a significant reduction in TIB during the night shift one compared to baseline (M = 4.1, SD = 0.5 hours vs. M = 7.3, SD = 0.5 hours,

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Chapter Four – The effect of rotating shift: a field study p < 0.001). In addition, during the night shift one, the TIB was significantly less than the day shift one (p = 0.01), recovery day one (p = 0.005) and recovery day two (p =

0.04) (Figure 4.2B).

The mean number of times awakened during sleep differed significantly among the five time points in the rotating shift schedule (F(2.52, 20.14) = 4.74, p = 0.02; η² =

0.278). Post hoc tests revealed that the number of awakenings was significantly higher on recovery day one (M = 33.8, SD = 3.1; p = 0.009) as compared to the night shift one (M = 15.4, SD = 2.0) (Figure 4.2C).

WASO differed significantly among the five time points in the rotating shift schedule (F(2.73, 21.85) = 3.93, p = 0.01; η² = 0.234). Post hoc tests revealed that

WASO was significantly higher on recovery day one (M = 57.3, SD = 7.1 minutes; p =

0.02) in comparison to night shift one (M = 22.6, SD = 3.2 minutes) (Figure 4.2D).

There were no significant differences observed between the shift time points for the sleep efficiency and onset latency variables.

The sleepiness score (before-work levels during work days or morning levels during non-work days) was significantly different across the rotating shift schedule

(F(2.61, 20.89) = 4.10, p = 0.009; η² = 0.252). Post hoc tests showed significantly higher scores of sleepiness for recovery day one compared to recovery day two (p =

0.007) (Figure 4.3A).

The sleepiness score (during-work levels on work days or afternoon levels during non-work days) differed significantly across the rotating shift schedule (F(2.70,

21.61) = 5.28, p = 0.002; η² = 0.326). Post hoc tests showed significantly higher scores of sleepiness on the night shift one (p = 0.04) and recovery day one (p = 0.001) compared to baseline (Figure 4.3B).

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Chapter Four – The effect of rotating shift: a field study

The sleepiness score (after-work levels during work days or evening levels during non-work days) was significantly different across the rotating shift schedule

(F(2.89, 23.11) = 14.34, p < 0.001; η² = 0.540). Post hoc tests showed significantly higher scores of sleepiness during the night shift one as compared to baseline (p =

0.005). Also, sleepiness scores were significantly higher during the night shift one (p

< 0.001) and recovery day one (p = 0.009) compared to recovery day two (Figure

4.3C).

10.00 8.00 9.00 7.00 8.00 6.00 7.00 5.00 6.00 4.00 * 5.00 * 4.00

3.00 (hours) bed in Time

Total sleep time (hours) time sleep Total 3.00 2.00 2.00 1.00 1.00 Baseline1 Day2 1 Night3 1 Rec4 1 Rec25 Baseline1 Day2 1 3Night 1 4 Rec 1 5 Rec2 (A) (B)

40.00 70.00 * * 35.00 60.00

30.00 50.00 25.00 40.00 20.00 30.00

15.00 (minutes) WASO** Number of awakenings of Number

10.00 20.00

5.00 10.00 Baseline1 Day2 1 3 Night 1 4 Rec 1 5 Rec2 Baseline1 Day2 1 Night3 1 Rec4 1 Rec25

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Figure 4.2. Average sleep outcomes recorded by the actigraphy. Outcomes divided as follow: (A) total sleep time in hours (daytime naps included), (B) time in bed in hours, (C) number of awakenings, and (D) WASO measured by actigraphy during a rotating shift schedule across 5-time points within the schedule. Note, *(A) night shift one significantly lower than all days (p < 0.001), (B) night shift one significantly lower than all days (p < 0.05), (C) recovery one significantly higher than night shift one (p < 0.05), and (D) recovery one significantly higher than night shift one (p < 0.05). **(WASO) wake after sleep onset.

8.00 7.00 * * * 7.00 6.00 6.00 5.00 5.00 4.00 4.00 3.00 3.00 2.00 2.00 Sleepiness level (during work) (during level Sleepiness Sleepiness level (before work) (before level Sleepiness 1.00 1.00

0.00 0.00 Baseline1 Day2 1 3Night 1 4 Rec 1 5 Rec2 Baseline1 Day2 1 3Night 1 4 Rec 1 5 Rec2

(A) (B)

9.00 * 8.00 * 7.00 6.00 5.00

4.00 3.00

2.00 Sleepiness level (after work) (after level Sleepiness 1.00

0.00 Baseline1 Day2 1 Night3 1 4 Rec 1 5 Rec2

(C)

Figure 4.3. The average levels of sleepiness reported by paramedics. The levels of sleepiness reported (A) before work, (B) during work, and (C) after work during a rotating shift schedule across 5-time points within the schedule. Note, *(A) recovery one significantly higher than recovery two (p < 0.05), (B) night shift one

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Chapter Four – The effect of rotating shift: a field study and recovery one significantly higher than baseline (p < 0.05), and (C) night shift one and recovery one significantly higher than baseline and recovery two (p < 0.05).

4.3.2 Mood, stress & fatigue

The average positive and negative affect scores on the abbreviated 8-item

PANAS were recorded from the current sample twice during the entire 24-hours for each day (Table 4.1). A repeated measures ANOVA determined that mean positive and negative affect scores on the PANAS did not differed significantly across the five time points in the rotating shift schedule: positive affect (before work): (F(2.24, 15.70)

= 1.43, p = 0.26; η² = 0.07), positive affect (after work): (F(3.05, 21.35) = 1.25, p =

0.32; η² = 0.05), negative affect (before work): (F(2.50, 17.54) = 1.27, p = 0.31; η² =

0.08), and negative affect (after work): (F(1.32, 9.30) = 0.57, p = 0.51; η² = 0.04)

Stress (before-work levels during work days or morning levels during non-work days) differed significantly among the rotating shift schedule (F(2.78, 22.21) = 8.21, p

= 0.02; η² = 0.453). Post hoc tests revealed significantly higher levels of stress on recovery day one compared to baseline (p = 0.03) and day shift one (p = 0.01) (Figure

4.4A).

Likewise, stress (during-work levels on work days or afternoon levels during non-work days) differed significantly across the rotating shift schedule (F(2.92, 23.35)

= 8.43, p = 0.001; η² = 0.444). Post hoc tests revealed significantly higher levels of stress on recovery day one as compared to baseline (p = 0.006) and day shift one (p

= 0.01) (Figure 4.4B).

Stress (after-work levels during work days or evening levels during non-work days) differed significantly across the rotating shift schedule (F(2.19, 17.54) = 16.85, p < 0.001; η² = 0.628). Post hoc tests revealed significantly higher levels of stress on

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Chapter Four – The effect of rotating shift: a field study the night shift one as compared to baseline (p = 0.007) and recovery day two (p =

0.01). Also, the stress level for recovery day one was significantly higher than baseline

(p = 0.003), day shift one (p = 0.04), and recovery day two (p < 0.001) (Figure 4.4C).

Table 4.1 shows the mean and standard errors of the outcome variables from the PANAS.

Variable Baseline Day Night Recovery1 Recovery2 M(SE) M(SE) M(SE) M(SE) M(SE) Positive 8.25(1.17) 10.75(1.41) 11.00(1.51) 9.00(1.63) 9.87(1.32) Affect BW Positive 9.75(1.59) 9.37(1.19) 7.75(1.44) 8.37(1.25) 7.62(1.46) Affect AW Negative 5.25(.52) 4.87(.39) 4.75(.36) 6.00(.75) 5.37(.65) Affect BW Negative 6.37(1.81) 5.37(.32) 5.12(.47) 6.87(1.51) 5.87(.69) Affect AW

Note, * BW (before work), and AW (after work).

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4.50 * 4.00 * 4.00 3.50 3.50 3.00 3.00 2.50 2.50 2.00 2.00 1.50 1.50 1.00 Stress level (during work) (during level Stress Stress level (before work) (before level Stress 1.00

0.50 0.50 0.00 0.00 Baseline1 Day2 1 Night3 1 4 Rec 1 5 Rec2 Baseline1 Day2 1 3Night 1 4 Rec 1 5 Rec2

(B) (A)

4.50 * 4.00 * 3.50

3.00 2.50 2.00

1.50

Stress level (after work) (after level Stress 1.00 0.50

0.00 Baseline1 Day2 1 Night3 1 4 Rec 1 5 Rec2 (C)

Figure 4.4. The average levels of stress reported by paramedics. The stress levels reported (A) before work, (B) during work, and (C) after work during a rotating shift schedule across 5-time points within the schedule. Note, *(A) recovery one significantly higher than baseline and day shift one (p < 0.05), (B) recovery one significantly higher than baseline and day shift one (p < 0.05), and (C) night shift one and recovery one significantly higher than all other days (p < 0.001).

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The fatigue score (before-work levels during work days or morning levels during non-work days) was not significantly different across the rotating shift schedule

(F(2.56, 20.60) = 2.88, p = 0.06; η² = 0.195). However, post hoc tests showed significantly higher scores of fatigue for recovery day one in comparison to baseline

(p = 0.02) (Figure 4.5A).

The fatigue score (during-work levels on work days or afternoon levels during non-work days) was significantly different across the rotating shift schedule (F(3.10,

24.78) = 8.50, p < 0.001; η² = 0.378). Post hoc tests showed significantly higher scores of fatigue during the night shift one (p = 0.01) and recovery day one (p = 0.002) as compared to baseline (Figure 4.5B).

Fatigue levels (after-work levels during work days or evening levels during non- work days) also differed significantly across the rotating shift schedule (F(3.181,

25.45) = 20.45, p < 0.001; η² = 0.657). Post hoc tests revealed significantly higher scores of fatigue on the night shift one compared to baseline (p = 0.003), day shift one

(p = 0.03), and recovery day two (p = 0.002). In addition, fatigue levels were significantly higher on recovery day one compared to baseline (p = 0.001) and recovery day two (p = 0.005). Also, fatigue levels were significantly higher on the day shift one compared to the same time on recovery day two (p = 0.02) (Figure 4.5C).

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6.00 5.00 * * * 4.50 5.00 4.00 3.50 4.00 3.00 3.00 2.50 2.00 2.00 1.50 Fatigue level (during work) (during level Fatigue Fatigue level (before work) (before level Fatigue 1.00 1.00 0.50 0.00 0.00 Baseline1 Day2 1 3Night 1 4 Rec 1 5 Rec2 Baseline1 Day2 1 Night3 1 4 Rec 1 5 Rec2

(B) (A) 7.00

6.00 * *

5.00 *

4.00

3.00

2.00 Fatigue level (after work) (after level Fatigue 1.00

0.00 Baseline1 Day2 1 Night3 1 4Rec 1 5Rec2 (C)

Figure 4.5. The average levels of fatigue reported by paramedics. Fatigue levels reported (A) before work, (B) during work, and (C) after work during a rotating shift schedule across 5-time points within the schedule. Note, *(A) recovery one significantly higher than baseline (p < 0.05), (B) night shift one and recovery one significantly higher than baseline (p < 0.05), and (C) day shift one, night shift one and recovery one significantly higher than baseline and recovery two (p < 0.05).

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4.3.3 Physical activity

Data from the SenseWear are displayed in Table 4.2. The mean physical activity, measured by step count, differed significantly among the five time points in the rotating shift schedule (F(2.59, 23.26) = 1.40, p = 0.02; η² = 0.367). Post hoc tests showed that physical activity was significantly greater (p = 0.002) on the night shift one when compared to baseline. However, the average GSR and total energy expenditure were not statistically different across the time points in the shift schedule.

Table 4.2. Means and standard errors of the data from the BodyMedia SenseWear Armband.

Variable Baseline Day1 Night1 Recovery1 Recovery2 M(SE) M(SE) M(SE) M(SE) M(SE) Average .14(.02) .12(.02) .15(.04) .11(.01) .12(.02) GSR (μS)

Steps 6049(1219) 6548(1009) 9061(1125)* 7777(1468) 6639(1765)

Total 8292(1137) 9386(798) 11836(664) 10389(1322) 9480(1226) energy expenditure (kJ)

Note, GSR (Galvanic skin response), μS (microsiemens), and kJ (kilojoules). *Night shift was significantly higher compared to baseline (p < 0.05).

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4.4 Discussion

This field study investigated paramedics across an entire rotating shift schedule, starting with the baseline day (pre-shift), day shift, night shift, and two recovery days. The study investigated sleep (actigraphy and PSD), physical activity

(BSA), total energy expenditure (BSA), mood (PANAS), sleepiness (KSS), fatigue

(Samn–Perelli Fatigue Checklist), and stress (BSA and a self-reported stress scale).

All participants were from Victoria (metropolitan paramedics only), with no further details about their stations. Age from the current sample was representative to the true population but not gender, as the sample contains slightly higher proportion of females compared to the true population (Australian Government Job Outlook, 2016). The actigraphy data revealed significantly less TST during the night shift one when compared to the baseline day, day shift one, and recovery days. The number of awakenings and WASO were significantly higher during recovery day one compared to the night shift. Sleep efficiency and onset sleep latency were not statistically significantly different across the rotating shift schedule. However, paramedics reported significantly higher levels of sleepiness and fatigue during and after the night shift, and across recovery day one, as compared to baseline and the second recovery day.

Levels of stress yielded a similar trend, as paramedics reported significantly higher stress during and after the night shift, and across recovery day one, when compared to baseline, day shift one, and recovery day two. Significantly more physical activity, measured by step count, was observed during the night shift as compared to baseline.

Total energy expenditure, GSR (stress) and mood did not change significantly during the rotating shift schedule.

During the first night shift, the paramedics recorded an average of 3.8 hours of

TST, which was significantly less than the baseline day, day shift, and recovery days.

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It is plausible that since many of these paramedics were only working one night shift and were transitioning to recovery days following this shift, they did not attempt to obtain a full 7-8 hours of sleep during this period. Five of the paramedics were rostered to a second night shift (Day 5), and recorded slightly more sleep after the night shift, with an average TST of 4.3 hours, which is still considerably lower than reported in other shift worker populations. For example, nurses in the United States (Geiger-

Brown et al., 2012) and Japan (Kato, Shimada, & Hayashi, 2012) slept an average of

5.2 hours after working a night or evening shift. However, airline ground crew slept an average of 4.3 hours after the night shift, which is similar to what was recorded from our study (Shochat, Hadish-Shogan, Banin Yosipof, Recanati, & Tzischinsky, 2019).

Even under ideal conditions, simulated night shift studies have shown that sleep after a night shift is severely truncated, which is likely due to the impact of circadian processes in the early afternoon disrupting sleep (Jackson, Banks, & Belenky, 2014).

The recorded TST in our sample of paramedics reflects a period of severe sleep restriction after night shift day that was also shorter than the TST measured in other shift worker populations (Geiger-Brown et al., 2012; Kato et al., 2012; Shochat et al.,

2019). While it should be noted that this was only in a small number of paramedics in our sample, it does raise concerns given the known impact of sleep restriction on decision making and cognitive functioning more generally (Lowe, Safati, & Hall, 2017).

Other sleep parameters measured by the actigraphy were WASO and the number of awakenings, which were both significantly higher during the first recovery day compared to night duty. Although not significant, but still considerably high, WASO and the number of awakenings were recorded during the second day of recovery compared to baseline measurements. In a previous study using actigraphy, a higher

WASO was found a day after working an afternoon shift among midwives (Tremaine

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Chapter Four – The effect of rotating shift: a field study et al., 2013). Also, nurses working evening shifts scored higher WASO compared to non-shift workers (Kato et al., 2012). A greater number of awakenings were reported by rotating shift workers, especially following a shift change, in comparison to workers with fixed shifts (Ohayon, Lemoine, Arnaud-Briant, & Dreyfus, 2002). It seems that paramedics and shift workers from different cohorts share a common sleep pattern where a high WASO and number of awakenings were recorded primarily after night duty or a shift change. Higher WASO and number of awakenings indicates sleep fragmentation, which can be an indicator of elevated stress (Åkerstedt, Kecklund, &

Axelsson, 2007; Shrivastava, Jung, Saadat, Sirohi, & Crewson, 2014). It is also likely to be the result of unstable and disrupted circadian rhythms, from rapidly switching between day and night schedules. This is one of the adverse effects of working rotating shifts and switching from night to day sleep and back to night sleep every week.

The levels of stress, fatigue, and sleepiness were significantly higher during recovery days as compared to baseline measurements. It is plausible that the restricted sleep during night duty (3.8 - 4.3 hours) contributed to the increases in stress, fatigue, and sleepiness during this time. Previous studies have linked sleep restriction with stress in physicians and nurses (Morales et al., 2019; Owens, 2007).

In fact, a study that restricted sleep in a laboratory found that a shorter duration of sleep was strongly related to higher levels of stress (Liu, Verhulst, Massar, & Chee,

2015). Also, fatigue and sleepiness were strongly linked to shorter TSTs in nurses, physicians, and airline ground crew (Geiger-Brown et al., 2012; Kato et al., 2012; Papp et al., 2004; Shochat et al., 2019; Stanojevic, Simic, & Milutinovic, 2016). Although the signs of stress, fatigue, and sleepiness were not significantly higher during the second day of recovery when compared to other time points, the levels were still considerably high especially in the beginning and in the middle of recovery day two compared to

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Chapter Four – The effect of rotating shift: a field study baseline. In nurses, the signs of stress and fatigue continued beyond night duty, as they reported significant signs of fatigue and stress during two days of recovery after night duty (Haluza et al., 2019). Also, airline cabin crew reported significant signs of sleepiness for two days after the end of the shift (Åkerstedt, Kecklund, Gillberg,

Lowden, & Axelsson, 2000). The findings of the current study are consistent with previous findings, where subjective levels of stress, fatigue, and sleepiness are impacted by a shorter sleep duration. The effect continues to impact workers during recovery days, and the levels were still considerably high one to two days after the end of the shift.

The level of physical activity, which was measured by step count, was significantly higher during night duty compared to baseline. Higher physical activity may be due to longer awakening hours or higher workload. However, rotating shift workers from Japan reported significantly higher physical activity during day compared to night shifts (Kawada et al., 2008). Another recent report that compared day and night shift healthcare workers indicated no differences in physical activity as measured for 24-hours period for both groups (van de Langenberg et al., 2019). While more steps count or physical activity typically represent a healthy lifestyle, in the present study, this finding is probably due to the extended awake time and less rest/nap opportunities for paramedics during night duty. It may lead to fatigue, thus impacting their performance and safety (Barker & Nussbaum, 2011). Despite the fact that more physical activity is linked to better well-being and mental health as well as less fatigue in the general population (Yuenyongchaiwat, 2016), engaging in more physical activity while working against the normal body clock may lead to higher levels of fatigue

(Kagamiyama. & Yano, 2018).

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The mood of the participants was measured by the PANAS and did not show significant changes across the shift schedule. This finding suggests that a rotating shift has no relationship with the paramedics’ mood. The chronic mood issues reported by previous studies in paramedics may be due to the cumulative effect of shift work

(Courtney et al., 2013; Courtney, Francis, & Paxton, 2010; Khan et al., 2020;

Sofianopoulos et al., 2011a). Although in aviation and nurses the PANAS changed significantly when measured in a similar way (daily changes; Cruz, Detwiler, Nesthus,

& Boquet, 2003; Olson, Artenie, Cyr, Raz, & Lee, 2020), it did not in our sample of paramedics. It may be due to possible variations in shift type, shift length, or occupation. Based on the findings from the current sample of paramedics, a rotating shift may be related to sleep duration, stress, fatigue, and sleepiness levels but not mood.

In addition to the relationship with stress and fatigue, lack of sleep has been associated with a decline in cognitive function, judgment, and decision-making (Luber et al., 2013). In fact, less than four hours of TST during night shift simulated in a laboratory was linked to significant deficits in cognitive function when compared to groups that slept more than five hours, suggesting a dose–response relationship between sleep duration and performance (Belenky et al., 2003). Certainly, cognitive functions and performance are two of the most important abilities for healthcare shift workers, especially paramedics. Any deficits in those abilities can compromise the safety of both the workers and their patients. Future studies should focus on assessing paramedics’ performance and cognition during shift work and on recovery days as well.

Recovery from shift work is crucial in maintaining worker’s health (Merkus et al., 2015). The current rotating shift schedule for paramedics in Victoria, Australia

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Chapter Four – The effect of rotating shift: a field study includes two days of standard day shifts followed by two days of night shifts and then four days of break or recovery in-between every other roster. The amount of recovery needed in-between shifts may differ from one group of workers to another, as nurses from a recent report required at least three days of recovery (Haluza et al., 2019). Non- shift workers usually require no longer than two days to recover (Smith et al., 2015).

Also, the duration of work is an important factor in determining the amount of recovery

(Wong, Chan, & Ngan, 2019), as longer working hours are attributed to the need for longer recovery times (Ropponen, Harma, Bergbom, Natti, & Sallinen, 2018).

Outcomes of the present study seem to show improvement from recovery day 2, although not to baseline levels. The current study did not assess these outcomes beyond recovery day 2, therefore we do not know if 3 or 4 days of recovery is sufficient for sleep, mood and stress to return to baseline levels in this population. Future studies should focus on days where shift workers required to change their sleep habits, starting from night shifts until the second or third day of recovery after night work, as these appear to be the most challenging days for them.

Fixed shifts would be a solution that avoids the problems of continually having to adjust between different shifts. This could be done on the basis of assigning people to shifts based on their chronotype (Vetter, Fischer, Matera, & Roenneberg, 2015).

Chronotype was assessed in 136 ambulance workers and found that while it would be possible to staff the day shift, there would always be a shortage of staff that are true evening type to staff the night shift (evening types = 11%) (Khan et al., 2020). It may be difficult to fill workers into a fixed night shift, but it would be advantageous because they only have to adapt to a fixed work schedule and any difficulties in adjusting would result from social demands that may conflict with their permanent shift schedules.

Fixed night shift is detrimental to health and fixed day shift is not possible in some

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Chapter Four – The effect of rotating shift: a field study essential services that require 24hr coverage e.g. police, paramedics. Thus, rotating shifts have been adopted.

The present study assessed paramedics through their entire rotating roster and recovery days using wrist actigraphy to record their sleep and objective information regarding physical activity and subjective levels of stress, fatigue, and sleepiness. The sample size was not large enough to conduct further analyses to investigate the outcomes of the study during the day shift 2, night shift 2 and recovery day 3. However, from the observed TST during night shift 2, we can speculate similar outcomes to what found during night shift 1. Our sample size was small, possibly due to the intensive assessment of day-to-day data in the field and time limitations while paramedics are on duty. Further studies in larger samples of paramedics are required to confirm the current findings. This study may be underpowered, as effect sizes were small, to detect statistically significant changes from outcomes of the PANAS. Task demands need to be an important consideration when considering field investigations, especially in shift workers.

Being a field study, the shift comparisons were restricted by the shifts that were running, with night shifts being 4 hours longer than day shift. Ideally, a comparison of shifts of equal duration would be best from an experimental perspective, however it could be argued that these results have ecological validity, reflecting outcomes from shift schedules used in the industry.

This study did not assess employment history, which may be a relevant factor related to these findings, as newly recruited paramedics may react differently than paramedics with experience to rotating shift conditions. In addition, the study did not investigate whether the baseline day represented recovery day 4 from a previous shift

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Chapter Four – The effect of rotating shift: a field study or another day (e.g., last day of a vacation). Also, the self-reported measures used in the study may be subject to a response bias. The subjective stress rating used was a single question assessing the current state of stress, and it has not been previously validated.

In conclusion, this study investigated paramedics across a rotating shift schedule, including two recovery days. The duration of sleep measured using actigraphy was significantly less during night duty when compared to baseline, day shift, and recovery days one and two. The levels of stress, fatigue, and sleepiness were all related to the sleep restriction that happened during night duty. These levels started to increase significantly after the end of the night duty and peaked significantly throughout the entire recovery day one. The highest level of physical activity was detected during 24 h periods that included night shift. During these periods paramedics may be at risk of physical fatigue and exhaustion. Therefore, it was observed that working on a rotating shift was associated with sleep restriction, higher stress, fatigue, and sleepiness levels, which together may be detrimental to a worker’s health. Given these preliminary results, there is a need to investigate methods to reduce rotating shift burden on health with a particular focus on night shifts and recovery days.

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Chapter Five – General discussion

Chapter Five : General discussion 5.1 Summary of main experimental findings

The overall aim of the current studies was to obtain a better understanding of shift work and its effects on sleep and mental health among paramedics from Australia and Saudi Arabia. Three different studies were completed to achieve the overall aim.

The first study investigated Australian paramedics for the prevalence of sleep and mental health concerns, the role of chronotype, and how sleep and mental health were related. The second study investigated Saudi paramedics for sleep and mental health concerns with a comparison to male paramedics from Australia. Finally, the third study investigated Australian paramedics in the field during an entire rotating shift schedule, examining their sleep, stress, fatigue, sleepiness, physical activity, energy expenditure, and mood. The studies highlighted possible chronic and acute effects of rotating shifts among paramedics (Figure 5.1).

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Chapter Five – General discussion

Recovery day 4 Recovery day 3

Day shift Recovery day 4 Recovery day 3 Day shift Rotating shift cycle Recovery day 2 Rotating shift cycle Day shift Recovery day 2

Day shift Night shift Night shift Recovery day 1

Night shift Night shift Recovery day 1

Acute effects

1- Sleep restriction Chronic 2- High stress circadian 3- High fatigue misalignment 4- High sleepiness

5- No effect on mood Chronic

circadian 1- Sleep restriction misalignment 2- High stress 3- High fatigue 4- High sleepiness 5- No effect onHigher mood demands (among Saudi paramedics)

Higher demands Chronic effects (among Saudi paramedics)

Chronic effects Higher prevalence of: 1- Insomnia 2- Shift work disorder 3- Poor sleep quality

Higher reports of: 1- Insomnia 1- Depressive symptoms Evening chronotype 2- Shift work disorder 2- Anxiety symptoms 3- Poor sleep quality 3- PTSD symptoms Evening chronotype Figure 5.1. The general findings of the project, how rotating shift work is impacting paramedics. Acute and chronic consequences are stemming from a rotating1- Depression shift schedule, with chronic circadian misalignment, higher demands and chronotype2- Anxiety impacting on the chronic consequences. The acute effects were at peak during night3 -shifts Post -andtraumatic recovery stress day disorder one, which triggered by shifting sleep habits from night to day as required by the work schedule.

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Chapter Five – General discussion

In Study 1 (Chapter 2), paramedics reported significantly higher levels of depression symptoms, anxiety symptoms, fatigue, post-traumatic stress disorder

(PTSD) symptoms, insomnia symptoms, significantly poorer sleep quality, and worse general well-being than norms from the general population of Australia and Western countries (all p < .05). Also, the prevalence of at high risk of OSA, SWD, and narcolepsy were higher among paramedics as compared to the general population.

Paramedics who were at high risk for OSA, SWD and bruxism reported significantly higher levels of symptoms of depression (all p < .05). Also, insomnia was found to be a significant predictor of the variance in depression and anxiety scores (all p < .001).

The majority of the participants were intermediate chronotype (57%), followed by morning (32%), and evening types (11%). Evening chronotypes showed significantly higher depression scores (p < .001), anxiety (p < .05), and PTSD symptoms (p < .05), as well as poorer sleep quality (p < .05) and lower general well-being scores (p < .001) compared to morning types.

In Study 2 (Chapter 3), significantly higher rates of depression, PTSD, insomnia, and fatigue, along with significantly poorer physical functioning, were observed among Saudi paramedics in comparison to Australian paramedics (all p < .05). However, Australian paramedics reported significantly poorer sleep quality and general health in comparison to Saudi paramedics (all p < .05). After removing the effects of working and driving durations, insomnia, sleep quality, depression,

PTSD, and fatigue levels were no longer significant between Saudi and Australian paramedics. This means that work-load has a significant impact on the mental health and sleep of Saudi paramedics.

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Chapter Five – General discussion

In Study 3 (Chapter 4), paramedics who worked rotational shifts experienced sleep restriction during a night shift when compared to baseline, day shift, and recovery days (p < .001). The night shift was also associated with higher levels of stress, fatigue, and sleepiness (all p < .05), with the higher levels remaining significantly high during recovery day one (p < .05). Also, paramedics showed significantly more physical activity during the night shift (p < .05) as compared to baseline. There were no significant changes in the mood of the paramedics across the rotating shift schedules.

5.2 Sleep and mental health

Shift workers are at an increased risk of developing a range of sleep disorders due to their work schedules. In Study 1 (Chapter 2), paramedics reported more mental health and sleep issues, including insomnia, poorer quality of sleep, fatigue, depression, anxiety, and PTSD, as compared to the general population (Aalto et al.,

2012; Buysse et al., 2008; Crawford et al., 2011; Freeman et al., 2009; Germain et al.,

2005; Hublin et al., 1994; Valko et al., 2008). Paramedics also reported a greater prevalence of OSA and SWD risks compared to reference populations (Barger et al.,

2015; Zebede et al., 2015). There is an obvious increase in sleep and mental health concerns among paramedics when compared to the general population, with these significant variations possibly stemming from shift work.

Shift work affects paramedics’ sleep, and thus it also affects their mental health, as evidenced by the findings that insomnia was a significant predictor of depression and high anxiety levels among paramedics from Australia. Additionally, paramedics who scored at high risk for OSA, SWD, and sleep bruxism also reported significantly higher levels of depression as compared to paramedics who scored as low risk for

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Chapter Five – General discussion those disorders. Anxiety levels were also higher among paramedics who were at high risk of OSA, SWD, and sleep bruxism when compared to paramedics who were at low risk. Study 1 (Chapter 2) showed that the increase in the burden of mental health outcomes among Australian paramedics, particularly depression and anxiety, were strongly related to sleep issues, including insomnia, OSA, SWD, and sleep bruxism.

Previous studies that assessed paramedics did not investigate the relationship between sleep and mental health (Bentley et al., 2013; Courtney et al., 2013;

Sofianopoulos et al., 2011a), giving the present study its novelty. The current study findings on Australian paramedics support the findings from other research on shift worker populations and indicate that sleep disorders (particularly insomnia) in paramedics are a possible risk factor for developing depression and anxiety symptoms

(Carey et al., 2011; Vallieres et al., 2014).

2012). Healthy adults, when exposed to a period of sleep restriction, reported significantly higher depression and anxiety outcomes compared to baseline (Short &

Louca, 2015). Previous studies confirmed a strong association between the severity of OSA and mental health, particularly depression and anxiety (Jackson et al., 2019;

Kaufmann et al., 2017). Among shift-workers, shift-work disorder was strongly related to higher scores of depression and anxiety (Kalmbach et al., 2015). Collectively, these studies outline the critical role of sleep on mental health. The findings that insomnia was a significant predictor of depression and anxiety levels among paramedics from

Australia can be interpreted in several ways. It is widely recognised that paramedics are engaged in highly stressful work conditions that can affect their mental health and

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Chapter Five – General discussion subsequent sleep, which then has chronic effects that translate to sleep disorders

(Khashaba, El-Sherif, Ibrahim, & Neatmatallah, 2014). For example, work stress may lead to unhealthy lifestyle behaviours resulting in weight gain that might lead to OSA.

Also, work stress may develop anxiety and/or depression disorders, which could then lead to development of sleep issues, particularly insomnia. On the other hand, evidence also suggests that poor sleep may affect mental health (Freeman et al.,

2017). In the context of paramedics, shift work might result in inadequate sleep, which then may precipitate mental health issues. The results of this thesis suggest that paramedics, engaging in stressful duties impacting anxiety and depression, subsequently experience poorer sleep. However, poor sleep may also be affecting and/or exacerbating issues of mental health. This is supported by the findings that paramedics who scored as being high risk for OSA, SWD, and sleep bruxism reported higher depression and anxiety levels. Also, regardless of the etiology, treating sleep issues (e.g., insomnia) would not only improve sleep, but has the potential to improve mental health as well (Freeman et al., 2017).

Study 1 (Chapter 2) also revealed that another important factor impacting sleep and mental health that is currently nearly completely unrecognised in the body of literature is chronotype. It is known from studies conducted on the general population that evening types tend to have poorer sleep, general health, and mental health outcomes in comparison to morning and intermediate types (Medeiros et al., 2001;

Yun et al., 2015). However, studies assessing shift workers are few, and findings were inconclusive; one study reported no variations between evening and morning types and another study reported variations between chronotype and social jet lag and sleep duration only (Antunes et al., 2010; Juda et al., 2013). Another novel finding of the present study was the outcome between evening and morning types. Paramedics who

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Chapter Five – General discussion reported being an evening type had significantly higher levels of depression, anxiety, and PTSD, along with poorer sleep quality and worse well-being, when compared to the morning types. Evening types also had higher insomnia symptoms ratings and a higher body mass index (BMI), but the differences were not statistically significant.

This outlines the crucial, but unrecognised role of chronotype on sleep and mental health among shift workers, where it may have a hidden impact, especially when shift workers are on schedules different from their natural chronotype preferences.

5.3 Paramedics from Saudi Arabia

The available literature contained only one study that assessed paramedics from Saudi Arabia, which did not investigate their sleep or mental health (Alanazi,

2012). Thus, this study was the first to examine sleep and mental health symptoms in paramedics from Saudi Arabia. In Study 2 (Chapter 3), Saudi paramedics reported significantly higher rates of depression, PTSD, and insomnia as compared to paramedics from Australia. Saudi paramedics also reported significantly longer driving and working durations when compared to paramedics from Australia, all of which represent higher occupational demands or work-load. Paramedics from Australia reported significantly higher rates of fatigue and poorer quality of sleep, but these factors could be explained by the generally significantly older age and higher BMI of

Australian paramedics when compared to Saudi paramedics. However, it seems that driving and working durations have a significant effect on insomnia, sleep quality, depression, PTSD, and fatigue levels. As after removing their effects, outcomes were no longer significant between Saudi and Australian paramedics.

Higher PTSD levels among Saudi paramedics may indicate more trauma exposure, especially given that Saudi Arabia has much higher fatality rates due to

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Chapter Five – General discussion motor vehicle crashes compared to Australia (Australian Government, 2018; Mansuri et al., 2015). As reported in Study 1 (Chapter 2), insomnia and depression were strongly correlated, with insomnia being a significant predictor of depression among

Australian paramedics. The same findings could be assumed with Saudi paramedics, where their higher burden of depression is influenced by their higher rates of insomnia.

However, there were other contributors to depression burden, which affected the

Saudi paramedics significantly. Supported by our findings and findings from previous studies, longer driving and working durations significantly impacted depressive symptoms (Ding et al., 2014; Virtanen et al., 2011; Weston et al., 2019). Generally,

Saudi and Australian paramedics reported significant sleep and mental health outcomes, but paramedics from Saudi Arabia reported higher rates of insomnia, depression, and PTSD. However, this difference was attributable to the longer working and driving hours of the Saudi paramedics.

Longer working hours were significantly related to poorer quality of sleep, higher scores of insomnia and fatigue among the Saudi Paramedics. This finding is similar to previous studies which reported that higher workload was significantly related to poorer sleep quality and higher fatigue among nurses and rail industry workers (Dorrian et al., 2011; Ghasemi et al., 2019). In physicians, higher workload was significantly related to insomnia symptoms (Győrffy et al., 2016). It appears that workload is an important factor affecting sleep and fatigue of different shift workers.

5.4 In-field investigation

In Study 3 (Chapter 4), a sample of paramedics were investigated in the field over four time periods including baseline day, regular day shift, night shift, and the first two recovery days. This study measured sleep objectively and explored the dynamic relationship between sleep/rotating shift and acute effects on mental health/mood. It

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Chapter Five – General discussion is one of few studies that investigated rotating shift workers using objective sleep measures across an entire rotating shift roster including recovery days. Paramedics showed significantly shorter sleep duration after working the night shift than in any of the other days. During the first night shift, the paramedics recorded an average of 3.8 h of TST, which was significantly less than the baseline day, day shift, and recovery days. It is plausible that since many of these paramedics were only working one night shift and were transitioning to recovery days following this shift, they did not attempt to obtain a full 7-8 h of sleep during this period. Five of the paramedics were rostered to a second night shift (Day 5), and recorded slightly more sleep after the night shift, with an average TST of 4.3 h, which is still considerably lower than reported in other shift worker populations. For example, nurses in the United States (Geiger-Brown et al., 2012) and Japan (Kato et al., 2012) slept an average of 5.2 h after working a night or evening shift. However, airline ground crew slept an average of 4.3 h after the night shift, which is similar to what was recorded from our study (Shochat et al., 2019). Even under ideal conditions, simulated night shift studies have shown that sleep after a night shift is severely truncated, which is likely due to the impact of circadian processes in the early afternoon disrupting sleep (Jackson, Banks, et al., 2014). The recorded TST in our sample of paramedics reflects a period of severe sleep restriction after night shift day that was also shorter than the TST measured in other shift worker populations

(Geiger-Brown et al., 2012; Kato et al., 2012; Shochat et al., 2019).

These findings indicate that paramedics may be sleeping poorly when compared to other occupations when working the night shift. This is further supported by the physical activity results, which showed significantly higher rates of activity when paramedics were working the night shift as compared to baseline, indicating less rest or sleep opportunities. However, we cannot determine whether higher levels of

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Chapter Five – General discussion physical activity during the night shift was due to being awake for longer or if there were greater work demands during the night. Conversely, one report from Japan indicated that a sample of rotating shift workers showed significantly less physical activity during night shift compared to day shift (Kawada et al., 2008). Another study investigated physical activity in nurses worked in rotating shifts indicated similar findings; a higher level of physical activity was recorded during the night shift as compared to other time points (baseline/day shift) (Kagamiyama. & Yano, 2018).

While the study did not highlight the occupation of the sample, it may indicate that their sample of rotating shift workers either had better opportunities for rest/sleep or they had less active jobs. Generally, the current studies’ findings suggest that our sample of Australian paramedics had insufficient sleep time during the night shift, and it was accompanied by more physical activity. It could be assumed that the paramedics had less chance for sleep or rest during the night shift because the job requires workers to be highly active.

In Study 3 (Chapter 4), aside from sleep time and physical activity, paramedics reported significantly higher levels of stress, fatigue, and sleepiness during night shift, after night shift, and during the entire recovery day one as compared to baseline and day shift. Although the sleep duration on recovery day one was back to baseline, their stress, fatigue, and sleepiness levels were still significantly high. During the second recovery day, outcomes were still somewhat higher than baseline (although the difference was not statistically significant). It is plausible that restricted sleep during night duty contributed to increases in stress, fatigue, and sleepiness during this time.

Previous studies have linked sleep restriction with higher levels of stress, fatigue, and sleepiness in physicians, nurses, and airline crew (Geiger-Brown et al., 2012; Kato et al., 2012; Morales et al., 2019; Owens, 2007; Papp et al., 2004; Shochat et al., 2019;

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Stanojevic et al., 2016). In addition, nurses and airline crew workers have reported significant levels of stress, fatigue, and sleepiness for two days after the end of night shift (Åkerstedt et al., 2000; Haluza et al., 2019). The findings of Study 3 (Chapter 4) are somewhat consistent with previous findings, where subjective levels of stress, fatigue, and sleepiness were high during and after night shift. The effect continues to impact workers during recovery days, and the levels were still considerably high one to two days after the end of the shift.

Recovery from shift work is crucial in maintaining a worker’s health (Merkus et al., 2015). The current rotating shift schedule for paramedics in Victoria, Australia, includes two days of standard day shifts followed by two days of night shifts and then four days of break or recovery between every other roster. The amount of recovery needed between shifts may differ from one group of workers to another. In one recent report, nurses required at least three days of recovery (Haluza et al., 2019). Non-shift workers usually require no more than two days to recover (Smith et al., 2015). Also, the duration of work is an important factor in determining the amount of recovery

(Wong et al., 2019), as longer working hours are attributed to the need for longer recovery times (Ropponen et al., 2018). Outcomes of the present study seem to start declining from recovery day two, although not to baseline levels. A limitation of the current study is that we did not assess these outcomes beyond recovery day two; therefore, we cannot determine whether three to four days of recovery are sufficient to restore sleep, mood, and stress level to baseline in this population. Future studies should focus on days where shift workers are required to change their sleep habits, starting from night shifts until the second or third day of recovery after night work, as these appear to be the most challenging days.

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5.5 Acute and chronic consequences

Given the findings of the current studies, it is proposed that shift work may impact workers across two pathways: acute and chronic. In Study 3 (Chapter 4), the observed consequences of working night shifts in a rotating shift schedule included shorter sleep duration, more physical activity, higher levels of stress, more fatigue, and more sleepiness. From the same study, mood changes of the paramedics were not statistically significant across the rotating shift schedules. Such findings are considered to be an acute consequence of working in rotating shifts. The chronic consequences of rotating shifts were reported by paramedics in Studies 1 and 2

(Chapters 2 and 3), including insomnia, SWD, poor quality of sleep, depression, anxiety, and PTSD. Perhaps the most noticeable variation between the suggested acute and chronic effects of rotating shifts is mood, given that it was not significant when sampled in the field, but it was significant when measured in the survey. The tools used in the field study were administered to measure the current mood state, whereas the subjective measures from the surveys were used to screen for the history of a condition across a specific period (usually between one month and six months, depending on the questionnaire). Such findings may help in understanding how the mental health of a shift worker is impacted, particularly in terms of depression and anxiety, as they were among the aims of the current project.

In addition, the present findings regarding sleep and mental health may also impact paramedic performance and cognition. Studies 1 and 2 (Chapters 2 and 3) reported that mental health outcomes, including depression, anxiety, and PTSD, were linked from previous reports to impaired cognition, particularly impaired decision- making; working memory; and problem-solving abilities, which are critical abilities for emergency support workers (Flory & Yehuda, 2015; Leykin et al., 2011; Lukasik,

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Waris, Soveri, Lehtonen, & Laine, 2019; Regehr & LeBlanc, 2017). From study 3

(Chapter 4), the recorded lack of sleep may also negatively affect cognitive functions, judgment, and decision-making (Luber et al., 2013). In fact, less than four hours of

TST during a laboratory simulated night shift was linked to significant deficits in cognitive function when compared to groups that slept more than five hours, suggesting a dose-response relationship between sleep duration and performance

(Belenky et al., 2003). Certainly, cognitive functions and performance are two of the most important abilities for health care shift workers, especially paramedics. Any deficits in those abilities can compromise the safety of both the workers and their patients. However, as the current project did not measure cognitive functions, future studies should focus on assessing paramedics’ performance and cognition during shift work and on recovery days as well.

5.6 Limitations

Study 1 (Chapter 2) reported the prevalence of self-reported sleep disturbances, mental health concerns, and chronotype preferences in Australian paramedics using a cross-sectional study. Causality cannot be evaluated with such a design; therefore, prospective cohort studies are needed to examine relationships between these contributory factors. As participation was restricted to active paramedics, those with a history of diagnosed mental illnesses or sleep disorders reported in this study were included in the results. Screening out such individuals still on active service would underestimate the actual prevalence of such issues in this population. Despite a moderate sample size, there was sufficient power to detect relationships and differences between the variables that were of interest in testing the current hypotheses. The sample was reflective of the industry in terms of age and shift type; however, the study cannot exclude the presence of self-selection bias as the

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Chapter Five – General discussion study was voluntary (Australian Government Job Outlook, 2016). Another limitation was the comparison to normative data from different populations. This was mainly due to limitations in the availability of Australian data for the adopted tools. Where possible, the norms used were from Australia or the general population of Western countries with similar demographic profiles to Australia. Although not ideal, it provided a reasonable comparison between paramedics and the general population.

Another limitation was that the majority of the paramedics (85.4%) worked on a rotating shift, with four days on (two days and two nights) and four days off.

Unfortunately, there was not enough data from the other shift types to conduct statistical analyses for comparing shift type on the measures of outcome. Finally, one might anticipate that a paramedic’s work tenure could have an impact on these relationships. For example, a new worker starting a rotating shift might show different relationships than more experienced paramedics. Unfortunately, the study did not investigate work tenure and its effect on the outcomes. The age range was typical of these workers, so the effect of time spent working under these conditions would potentially be an unaccounted-for factor in this study and a source of the variability in the results we observed.

Study 2 (Chapter 3) was the first study to investigate mental health and sleep disorders in Saudi paramedics using validated instruments. The study provided robust and detailed information for this population, and the data will act as a strong base for future studies. The current study reported the prevalence of sleep and mental health problems among Saudi paramedics and compared the results with Australian paramedics in a cross-sectional study. Statistically, age and BMI impacted the levels of perceived stress and fatigue between the two cohorts. However, it was important to

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Chapter Five – General discussion report the uncontrolled findings between the two populations, with this step including age and BMI as covariates being exploratory. Response bias is a common issue with such a design but can be solved by conducting follow-up or prospective cohort studies.

Also, self-selection bias is another common issue that may overestimate the current findings. A comparison between rosters (rotating shift vs fixed / rural shifts) could not be conducted due to the fact that the majority of both samples reported working in rotating shift schedule. The difference in the response rate for the Saudi and Australian paramedics is likely due to the recruitment procedure. The survey was conducted online for the Australian paramedics, whereas the Saudi paramedics were actively recruited at work stations with printed copies, as the usage of emails for work purposes is limited in Saudi. So, the recruitment procedure was conducted in such a way to make the study known to the Saudi paramedics. In addition, this study included only male paramedics from Saudi Arabia, as this occupation employs only males in Saudi

Arabia, which may affect the comparison to previous findings. However, a comparison was conducted to only male paramedics from Australia. Also, due to data availability, the study could not specify the paramedic/citizen ratio for the studied states (Makkah

District in Saudi and Victoria in Australia). Generalizing to the total population sizes was the closest available way of describing this relationship.

Study 3 (Chapter 4) assessed paramedics through their entire rotating roster and recovery days using wrist actigraphy to record their sleep and objective information regarding physical activity, as well as subjective levels of stress, fatigue, and sleepiness.

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136 ambulance workers and found that while it would be possible to staff the day shift, there would always be a shortage of staff that are true evening type to staff the night shift (evening types = 11%) (Khan et al., 2020). It may be difficult to fill workers into a fixed night shift, but it would be advantageous because they only have to adapt to a fixed work schedule and any difficulties in adjusting would result from social demands that may conflict with their permanent shift schedules. Fixed night shift is detrimental to health and fixed day shift is not possible in some essential services that require 24hr coverage e.g. police, paramedics. Thus, rotating shifts have been adopted. The present study assessed paramedics through their entire rotating roster and recovery days using wrist actigraphy to record their sleep and objective information regarding physical activity and subjective levels of stress, fatigue, and sleepiness. Sample size was not large enough to conduct further analyses to investigate the outcomes of the study during the day shift 2, night shift 2 and recovery day 3. However, from the observed TST during night shift 2, we can speculate similar outcomes to what found during night shift 1. Although our sample size was small, this was due to the intensive assessment of day-to-day data in the field and time limitation. Further studies in larger samples of paramedics are required to confirm the current findings. This study may be underpowered to detect statistically significant changes from outcomes of the

PANAS. Being a field study, the shift comparisons were restricted by the shifts that were running, with night shifts being 4 hours longer than day shift. Ideally, a comparison of shifts of equal duration would be best from an experimental perspective, however it could be argued that these results have ecological validity, reflecting outcomes from shift schedules used in the industry. This study did not assess employment history, which may be a relevant factor related to these findings, as newly recruited paramedics may react differently than paramedics with experience to rotating

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Chapter Five – General discussion shift conditions. In addition, the study did not investigate whether the baseline day represented recovery day 4 from a previous shift or another day (e.g., last day of a vacation). Also, the self-reported measures used in the study may be subject to a response bias. The subjective stress rating used was a single question assessing the current state of stress, and it has not been previously validated.

5.7 Recommendations and future directions

The health issues discussed in this project are possibly related to sleep disturbances triggered by engaging in shift work. Insomnia is one sleep issue that was strongly linked to the increase in the burden of mental health challenges among paramedics. In the general population, insomnia treatment has reduced mental health issues, especially depression (Freeman et al., 2017). Thus, providing better screening and management of sleep issues in paramedics, particularly for insomnia, could possibly reduce some of the burden of mental health issues. This can be done through organisational level interventions such as matching chronotype to shift preferences or through interpersonal interventions such as educational sleep programs.

One solution to improve sleep and reduce the consequences of shift work is educational sleep programs. The sleep health program has been studied in multiple intervention studies in the United States (Sullivan et al., 2016). Promising results were demonstrated in one study of American firefighters, where a 24% decrease in the risk of injury and an overall improvement in sleep quality were reported (Sullivan et al.,

2016). The strong evidence-base for educational programs aiming to decrease the rate of workplace injuries and enhance sleep quality justifies the implementation of a sleep health educational program for paramedics, particularly during graduate training.

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Another possible solution to reduce the adverse effects of shift work is matching chronotype to shift preferences. This can be done by matching evening types to night shifts and morning types to day shifts. A study found a significant improvement in general well-being, duration of sleep, and quality of sleep among nurses who matched their chronotype with the shifts they worked (Vetter et al., 2015).

For those who have already developed sleep problems, cognitive behavioural therapy for insomnia (CBT-I) is another intervention that showed promising findings among shift workers. From a recent study, shift workers reported significantly lower scores of insomnia, depression and better wellbeing after four weeks of CBT-I compared to baseline (Peter, Reindl, Zauter, Hillemacher, & Richter, 2019). However, organisational actions/interventions strategies such as continuous health surveillance and social support are vital to ensure that workers are engaged in a safe and healthy work condition without significant health impairments (Costa, 2010).

Revisions to the existing OHS guidelines and policies are needed, especially among Saudi paramedics. As workload was a significant contributor to their sleep and mental health, recruiting more paramedics to the workforce may be one solution. Also, more break/recovery days may be needed to allow paramedics full recovery from the previous shift. Existing evidence suggests a need for at least four days of recovery in- between rotating shifts (Burgess, 2007).

There is a need to investigate the cognitive functions of paramedics, especially during and right after night shift duty and during the recovery days. As the findings of the project showed, a period of sleep restriction and significant levels of stress and fatigue during these times could possibly impact paramedic performance or safety.

Also, the chronic increase in sleep disturbances and/or mental health problems could

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Chapter Five – General discussion impact their performance. As a result, investigating their cognitive functions in the future will give better insight into these interactions and help other researchers to develop appropriate and specific control measures.

5.8 Conclusions

The current project investigated the sleep and mental health of Australian and

Saudi Arabian paramedics across three studies. Australian paramedics reported more sleep and mental health concerns as compared to the general population. Also, their sleep outcomes, including insomnia, SWD, and OSA, were strongly related to their burden of depression and anxiety symptoms. Paramedics with an evening chronotype reported significantly more mental health concerns and poorer sleep quality when compared to paramedics with a morning chronotype. Paramedics from Saudi Arabia reported significantly higher rates of depression and PTSD symptoms when compared to paramedics from Australia, which was significantly explained by their greater work demands.

The field investigation of paramedics from Australia showed a period of sleep restriction. When working night shift sleep was significantly shorter than all other time points within the rotating shift. A paramedic’s physical activity was significantly greater during night shift as compared to baseline. Their levels of stress, fatigue, and sleepiness were significantly high during and after night shift. Interestingly, the measures of these outcomes were still high during the recovery days, particularly recovery days one and two. This highlights the importance of investigating shift workers not only during workdays, but also during the break/recovery days that follow a shift of night duty.

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Perhaps the most challenging time for rotating shift workers is when they need to readjust their sleep and daily function, which starts from night duty until break days that follow night work. Every rotating shift cycle is a risk factor that continuously disrupts normal circadian rhythms. Going from night to day sleep and back again to night sleep can be problematic if not handled properly. The potential consequences can be divided into chronic and acute based on our findings. The chronic factors include insomnia, SWD, depression, anxiety, and PTSD. The acute consequences include shorter sleep duration, more physical activity, higher stress levels, more fatigue, and sleepiness. To conclude, paramedics are a crucial part of the healthcare system, they work around the clock in different shift schedules to provide life-saving services to communities. Shift work may affect their normal sleep patterns and put them at risk of developing sleep disorders. However, employing more paramedics in ambulance services, particularly in Saudi Arabia, and screening for and managing sleep-related challenges through educational programs may be an effective way of reducing not only sleep problems, but mental health disturbances as well.

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Appendices

Appendix A (Conferences abstracts)

(1) Abstract (poster) at the Australasian Sleep Association, Sleep DownUnder, Brisbane 2018. https://onlinelibrary.wiley.com/doi/full/10.1111/jsr.63_12766

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(2) Abstract (oral presentation) at the Australasian Chronobiology Society Annual Meeting, Brisbane 2018 (travel award).

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(3) Abstract (oral presentation) at the Sleep and Brain Health symposium, RMIT, Melbourne 2018.

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(4) Abstract (poster) at the World Sleep conference, Vancouver 2019.

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The effect of rotating shift schedules on sleep, mood, stress, energy expenditure and physical activity of Australian paramedics: a field study

Wahaj A. Khan1,3, Russell Conduit1,2, Gerard A. Kennedy1,2, Melinda L. Jackson2,4 1School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, Australia; 2Institute for Breathing and Sleep, Austin Health, VIC, Australia; 3School of Public Health and Health Informatics, Umm Al-Qura University, Makkah, Saudi Arabia; 4Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, VIC, Australia

Introduction (p < 0.001) 8.00 Shift-work disrupts normal circadian rhythmicity, which can A 7.00 have both acute and chronic effects on health and performance. Few studies have investigated, in-depth, the 6.00 acute effects of different phases within a shift schedule on 5.00 4.00 sleep, mental health, and physical activity. The current (p < 0.05) study aimed to investigate the effect of rotating shift across 3.00 (p < 0.05) four consecutive time points within the shift schedule on Total 2.00sleep time (hours) sleep, mood, stress, energy expenditure and physical 1.00 activity in Australian paramedics. Pre-shift1 day Day 2shift Night3 shift Recovery4 day 4.50 Study timeline (days) B

4.00 Methods (p < 0.05) 3.50 Paramedics working on a rotating roster were invited to (p < 0.05) take part in a field study across four consecutive time 3.00 points within their eight-day shift schedule: pre-shift day 2.50 (PSD), day shift (DS), night shift (NS), and recovery day 2.00 (p < 0.05) (RD). Participants wore an actigraphy device (Phillips Subjective Stress Rating 1.50

Actiwatch 2) and BodyMedia SenseWear Armband (BSA), 1.00 Pre-shift1 day Day 2shift Night3 shift Recovery4 day and completed the following battery of tests: Pittsburgh 9.00 Study timeline (days) C Sleep Diary, Karolinska Sleepiness Scale, Samn-Perelli 8.00 (p < 0.05) Fatigue Checklist, Positive and Negative Affect Scale and a 7.00 self-reported stress rating. Actigraphy and BSA were worn 6.00 throughout the protocol to record sleep, galvanic skin 5.00 (p < 0.05) response (GSR), energy expenditure and physical activity 4.00

(step count). The sleep diary was completed before and 3.00 after bedtime. Sleepiness, fatigue, mood and stress ratings 2.00 Karolinska Sleepiness Scale were completed before, during and after work or at the 1.00 same times during break/recovery days. Repeated Pre-shift1 day Day2 shift Night3 shift Recovery4 day 7.00 Study timeline (days) measures ANOVA were used to examine the effect of the D 6.00 shift period (PSD, DS, NS, RD) on the outcome measures. (p < 0.05) 5.00

Results 4.00 (p < 0.05) Twelve paramedics (7 women, Mean age = 39.91±11.04 3.00 years) from Victoria, Australia, participated in the study. (p < 0.05) There was a significant effect for shift periods on total sleep Fatigue Checklist Score 2.00 time (TST) measured by actigraphy (F(1.66, 13.27) = 1.00 Pre-shift1 day Day2 shift Night3 shift Recovery4 day 17.56, p < 0.001). Post hoc tests using Bonferroni Study timeline (days) 10000.00 correction revealed that TST during the NS (3.56±1.51 E 9000.00 (p < 0.05) hours) was significantly lower compared to PSD (6.36±1.35 8000.00 hours; p < .001), DS (7.15±1.28 hours; p < .05), and RD 7000.00

(7.24±1.28 hours; p < .05). Similarly, the levels of stress, 6000.00 sleepiness, and fatigue during NS were significantly higher 5000.00 compared to PSD and DS (p‘s < .05). However, the levels 4000.00 of stress and fatigue were significantly higher during the 3000.00 2000.00 RD compared to PSD (p‘s < .05). The recorded levels of Physical activity (Step count) 1000.00 physical activity were significantly higher across NS Pre-shift1 day Day2 shift Night3 shift Recovery4 day Study timeline (days) compared to PSD (p < 0.05). The levels of GSR, energy expenditure, and positive and negative affect did not Figures: Bar charts of Mean with SE: A) total sleep time (hours), B) stress, C) sleepiness D) fatigue and E) physical activity (step count) across four significantly change across the shift schedules. consecutive time points within a single rotating shift schedule Conclusion Paramedics recorded significantly less sleep when on night shift compared to other times in their schedule. Also, paramedics recorded significantly more physical activity when on night duty compared to pre-shift day, possibly due to being awake for a longer period of time. Despite reporting significantly higher levels of stress, fatigue, and sleepiness while on night shift compared to pre-shift and day shift, levels of stress and fatigue were still significantly elevated during the first recovery day compared to pre-shift. Having one day of recovery after night duty may not be enough to allow paramedics recover fully. The findings of this study may assist in developing shift schedules that lead to less sleep disruption and better control of occupational fatigue and stress. Acknowledgments Ambulance Employees Australia - Victoria

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(5) Abstract (poster presentation) at the Australasian Sleep Association, Sleep DownUnder, Sydney 2019 (travel award). https://onlinelibrary.wiley.com/doi/full/10.1111/jsr.133_12913

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(6) Abstract (oral presentation) at the Australasian Chronobiology Society Annual Meeting, Sydney 2019.

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Appendix B (Awards)

(1) Travel award from the Australasian Chronobiology Society Annual Meeting, Brisbane 2018.

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(2) Travel award from the Australasian Sleep Association, Sleep DownUnder, Sydney 2019.

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Appendix C (Ethics approvals)

Human Research Ethics Committee (HREC) Research and Innovation office NH&MRC Code: EC00237 Notice of Approval

Date: 13 July 2018

Project number: 21420

Project title: The relationship between shift-work, sleep and mental health among paramedics in Australia

Risk classification: More than low risk

Chief investigator: Dr Melinda Jackson

Approval period: From: 13 July 2018 To: 26 February 2021

The following documents have been reviewed and approved: Title Version Date 21420 Jackson appn V.2 18 June 2018 Att. 1 Advertisement May 2018 Att. 2 Instructions letter May 2018 Att. 4 Information sheet for BodyMedia Sense Wear Armband May 2018 Att. 5 Telephone screening from V.1 May 2018 Att. 6 Sleep diary May 2018 Att. 7 Work diary May 2018 PICF Final 18 June 2018 Protocol V.2 18 June 2018 Screening doc May 2018 Att. 9 Information sheet for Actiwatch May 2018

The following documents have been noted: Title Date Att. 3 Ambulance Employees Australia letter 12 October 2017

The above application has been approved by the RMIT University HREC as it meets the requirements of the National statement on ethical conduct in human research (NH&MRC, 2007).

Terms of approval: 1. Responsibilities of chief investigator It is the responsibility of the above chief investigator to ensure that all other investigators and staff on a project are aware of the terms of approval and to ensure that the project is conducted as approved by HREC. Approval is valid only whilst the chief investigator holds a position at RMIT University. 2. Amendments Approval must be sought from HREC to amend any aspect of a project. To apply for an amendment use the request for amendment form, which is available on the HREC website and submitted to the HREC secretary. Amendments must not be implemented without first gaining approval from HREC. 3. Adverse events You should notify the HREC immediately (within 24 hours) of any serious or unanticipated adverse effects of the research on participants, and unforeseen events that might affect the ethical acceptability of the project. 4. Annual reports Continued approval of this project is dependent on the submission of an annual report. Annual reports must be submitted by the anniversary of approval (13 July 2018) of the project for each full year of the project. If the project is of less than 12 months duration then a final report only is required. 5. Final report

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Human Research Ethics Committee (HREC) Research and Innovation office NH&MRC Code: EC00237 A final report must be provided within six months of the end of the project. HREC must be notified if the project is discontinued before the expected date of completion. 6. Monitoring Projects may be subject to an audit or any other form of monitoring by the HREC at any time. 7. Retention and storage of data The investigator is responsible for the storage and retention of original data according to the requirements of the Australian code for the responsible conduct of research (section 2) and relevant RMIT policies. 8. Special conditions of approval Nil.

In any future correspondence please quote the project number and project title above.

Prof Stephen Bird Chairperson RMIT HREC

cc: Dr Peter Burke, HREC secretary Mr Wahaj Khan, Research student Dr Russell Conduit, Associate supervisor Prof Gerard Kennedy, Associate supervisor

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Human Research Ethics Committee (HREC) Research Integrity, Governance & Systems

Email: [email protected] Phone: [61 3] 9925 2251 Building 91, Level 2, City Campus

19 December 2017

Dr Melinda Jackson School of Health and Biomedical Sciences RMIT University

Dear Melinda

RE: HREC21153 The relationship between shift-work, sleep and mental health among paramedics in Australia and Saudi Arabia

Thank you for re-submitting the above ethics application for consideration by the Human Research Ethics Committee (HREC) of RMIT University.

The application was considered and reviewed by the HREC at meeting 11/17 held Wednesday 12 December 2017.

Status: Approved without requirement for further amendments

In accordance with the requirements of the National statement on ethical conduct in human research, NHMRC, 2007 (NS) the HREC approved the above application for human research ethics approval.

If there is anything in this letter that you are unclear about or require further clarification upon then please contact the HREC secretary, Dr Peter Burke.

Yours sincerely

Professor Penelope Weller Deputy Chair, Human Research Ethics Committee RMIT University

cc Mr Wahaj Khan, Principal research student Dr Russell Conduit, Associate supervisor Prof Gerard Kennedy, Associate supervisor Dr Peter Burke, HREC secretary.

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Appendix D (Alternative presentations of results from chapter 4) (A) (B) Total sleep time 14 Time in bed 12 20 10 8 15 6 10 4 5 2 Total sleep time (hours)

0 Time in bed (hours) 0 0 1 2 3 4 5 6 0 1 2 3 4 5 6 Study timeline Study timeline

Series1 Series2 Series3 Series4 Series5 Series6 Series1 Series2 Series3 Series4 Series5 Series6 Series7 Series8 Series9 Series10 Series11 Series12 Series7 Series8 Series9 Series10 Series11 Series12

Number of awakenings WASO 60 120 50 100 40 80 30 60

20 WASO 40 10 20 0 0

Number of awakenings 0 1 2 3 4 5 6 0 1 2 3 4 5 6 Study timeline Study timeline

Series1 Series2 Series3 Series4 Series5 Series6 Series1 Series2 Series3 Series4 Series5 Series6 Series7 Series8 Series9 Series10 Series11 Series12 Series7 Series8 Series9 Series10 Series11 Series12

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Figure 4.2. Average sleep outcomes recorded by the actigraphy. Outcomes divided as follow: (A) total sleep time in hours (daytime naps included), (B) time in bed in hours, (C) number of awakenings, and (D) WASO measured by actigraphy during a rotating shift schedule across 5-time points within the schedule starting from (1) baseline, (2) day shift one, (3) night shift one, (4) recovery one, and (5) recovery two. Note, Series = participants, (A) night shift one significantly lower than all days (p < 0.001), (B) night shift one significantly lower than all days (p < 0.05), (C) recovery one significantly higher than night shift one (p < 0.05), and (D) recovery one significantly higher than night shift one (p < 0.05). (WASO) wake after sleep onset.

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(A) (B) Stress level (before work) Stress level (during work) 6 6

4 4

2 2

0 0 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

stress_BW_Baseline stress_BW_D1 stress_DW_Baseline stress_DW_D1 stress_BW_N1 stress_BW_RE1 stress_DW_N1 stress_DW_RE1 stress_BW_RE2 stress_DW_RE2

Stress level (after work) 6

0 1 2 3 4 5 6 7 8 9 10 11 12

stress_AW_Baseline stress_AW_D1 stress_AW_N1 stress_AW_RE1 stress_AW_RE2

(C)

Figure 4.3. The average levels of stress reported by paramedics.

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The stress levels reported (BW) before work, (DW) during work, and (AW) after work during a rotating shift schedule across 5-time points within the schedule starting from baseline, (D1) day shift one, (N1) night shift one, (RE1) recovery one, and (RE2) recovery two. Note, (A) recovery one significantly higher than baseline and day shift one (p < 0.05), (B) recovery one significantly higher than baseline and day shift one (p < 0.05), and (C) night shift one and recovery one significantly higher than all other days (p < 0.001).

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(B) (A) Fatigue level (before work) Fatigue level (during work) 8 8 6 6 4 4 2 2 0 0 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

fatigue_BW_Baseline fatigue_BW_D1 Fatigue_DW_Baseline Fatigue_DW_D1 fatigue_BW_N1 fatigue_BW_RE1 Fatigue_DW_N1 Fatigue_DW_RE1 fatigue_BW_RE2 Fatigue_DW_RE2

Fatigue level (after work) 8 6 4 2 0 1 2 3 4 5 6 7 8 9 10 11 12

fatigue_AW_Baseline fatigue_AW_D1 fatigue_AW_N1 fatigue_AW_RE1 (C) fatigue_AW_RE2

Figure 4.4. The average levels of fatigue reported by paramedics

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Fatigue levels reported (BW) before work, (DW) during work, and (AW) after work during a rotating shift schedule across 5-time points within the schedule starting from baseline, (D1) day shift one, (N1) night shift one, (RE1) recovery one, and (RE2) recovery two. Note, (A) recovery one significantly higher than baseline (p < 0.05), (B) night shift one and recovery one significantly higher than baseline (p < 0.05), and (C) day shift one, night shift one and recovery one significantly higher than baseline and recovery two (p < 0.05).

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(A) Sleepiness level (during work) Sleepiness level (before work) 10 10 8 8 6 6 4 4 2 2 0 0 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

sleepiness_BW_Baseline sleepiness_BW_D1 sleepiness_DW_Baseline sleepiness_DW_D1 sleepiness_BW_N1 sleepiness_BW_RE1 sleepiness_DW_N1 sleepiness_DW_RE1 sleepiness_BW_RE2 sleepiness_DW_RE2

Sleepiness level (after work) (B) 10

0 1 2 3 4 5 6 7 8 9 10 11 12

sleepiness_AW_Baseline sleepiness_AW_D1 sleepiness_AW_N1 sleepiness_AW_RE1 sleepiness_AW_RE2 (C)

Figure 4.5. The average levels of sleepiness reported by paramedics.

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The levels of sleepiness reported (BW) before work, (DW) during work, and (AW) after work during a rotating shift schedule across 5-time points within the schedule starting from baseline, (D1) day shift one, (N1) night shift one, (RE1) recovery one, and (RE2) recovery two. Note, (A) recovery one significantly higher than recovery two (p < 0.05), (B) night shift one and recovery one significantly higher than baseline (p < 0.05), and (C) night shift one and recovery one significantly higher than baseline and recovery two (p < 0.05).

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Table 4.3 Raw sleep data from participants in chapter 4 (baseline) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 12.43 6.26 5.43 4.19 3 75.51 40 20

2 21.22 3.57 6.35 5.53 19 89.37 22 17

3 23.29 7.58 8.29 8.28 0 99.8 0 0

4 2.5 9.2 6.3 5.23 0 82.82 48 28

5 22.58 7.13 8.15 8.14 0 99.8 0 0

6 21.3 5.17 7.58 6.43 2 84.31 61 33

7 22.49 5.43 6.54 6 6 86.96 47 22

8 22.28 6.58 8.3 7.34 1 89.02 54 21

9 2.54 9.11 8.15 6.48 59 82.42 26 16

10 22.05 5.31 7.26 6.14 17 83.86 54 35

11 12.35 7.18 6.43 6.42 0 99.75 0 0

12 22.44 8.56 10.12 9.24 0 92.16 39 31

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Table 4.4 Raw sleep data from participants in chapter 4 (day shift 1) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 12.29 6.09 5.40 5.12 .00 91.76 27.00 21.00

2 22.31 6.00 7.29 6.42 .00 89.53 46.00 30.00

3 22.33 8.01 9.28 8.24 .00 88.73 63.00 34.00

4 2.35 10.30 7.55 7.54 .00 99.79 .00 .00

5 21.50 4.39 6.49 6.19 .00 92.67 29.00 22.00

6 21.34 5.58 9.22 7.24 .00 79.00 52.00 29.00

7 21.43 7.49 10.06 9.13 .00 91.25 52.00 33.00

8 21.49 8.00 10.11 8.34 8.00 84.12 88.00 38.00

9 22.31 5.45 7.14 6.18 .00 87.10 55.00 26.00

10 21.48 6.56 9.08 8.09 18.00 89.23 40.00 30.00

11 22.52 7.13 8.21 7.06 47.00 85.03 27.00 21.00

12 21.40 5.50 9.41 8.03 9.00 93.32 31.00 17.00

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Table 4.5 Raw sleep data from participants in chapter 4 (night shift 1) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 4.00 6.52 2.52 2.31 .00 87.79 15.00 11.00

2 2.32 4.30 3.34 3.10 .00 88.79 19.00 8.00

3 8.30 14.58 6.28 5.43 .00 88.40 35.00 25.00

4 2.31 4.53 2.53 1.58 .00 68.21 11.00 8.00

5 4.08 11.06 6.58 6.01 3.00 86.36 34.00 26.00

6 7.08 12.20 5.12 4.32 12.00 87.18 27.00 16.00

7 10.45 13.14 2.15 2.00 3.00 88.80 13.00 15.00

8 9.00 12.59 3.59 3.30 9.00 71.92 17.00 16.00

9 2.17 11.00 8.43 5.23 70.00 67.35 95.00 43.00

10 8.05 12.12 4.05 4.00 .00 65.75 38.00 22.00

11 3.12 6.30 3.18 3.10 .08 94.80 10.00 4.00

12 2.19 8.59 6.40 5.39 .00 84.75 29.00 17.00

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Table 4.6 Raw sleep data from participants in chapter 4 (recovery 1) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 17.31 3.13 9.42 6.28 27.00 66.67 59.00 35.00

2 23.2 6.22 7.02 6.23 4.00 90.76 34.00 22.00

3 22.34 7.26 8.52 7.42 3.00 86.84 66.00 48.00

4 23.32 9.5 10.18 8.24 5.00 81.55 75.00 38.00

5 7.12 12.33 7.24 6.13 9.00 84.01 37.00 23.00

6 21.3 7.18 9.48 8.47 4.00 89.63 48.00 31.00

7 22.35 9.03 10.28 9.07 .00 87.1 80.00 46.00

8 23.32 6.01 6.29 5.35 1.00 86.12 46.00 27.00

9 12.59 7.23 7.38 6.24 14.00 83.84 40.00 22.00

10 21.47 7.59 10.12 8.01 31.00 78.59 94.00 47.00

11 23.59 8.52 8.52 7.54 1.00 89.1 56.00 44.00

12 1.21 10.25 9.04 8.08 12.00 89.71 43.00 35.00

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Table 4.7 Raw sleep data from participants in chapter 4 (recovery 2) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 23.02 6.00 6.58 6.21 5.00 91.15 31 24

2 23.38 8.07 8.29 7.18 11.00 86.05 49 31

3 19.05 9.38 16.47 11.45 189.00 70.01 15 7

4 21.46 6.53 9.07 8.06 3.00 88.85 57 34

5 5.11 1.04 8.48 8.1 4.00 92.8 28 22

6 22.23 8.46 10.23 8.43 16.00 83.95 73 37

7 12.21 7.16 6.55 5.57 7.00 86.02 33 17

8 2.05 10.02 11.17 9.25 4.00 83.46 81 46

9 22.42 8.03 9.21 7.06 0.00 75.94 108 48

10 1.5 7.55 6.05 5.29 9.00 90.14 20 13

11 3.57 12.06 8.09 7.04 14.00 86.71 50 25

12 22.20 5.23 6.58 6.21 8.00 92.15 34 21

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Table 4.8 Raw sleep data from participants in chapter 4 (day shift 2) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 1.30 7.00 7.58 5.32 25.00 69.46 54.00 23.00

2 12.36 7.05 6.29 5.42 9.00 87.92 36.00 23.00

4 23.04 4.17 5.13 3.38 38.00 69.65 55.00 24.00

10 23.22 8.11 8.49 7.17 4.00 82.61 87.00 34.00

12 12.55 8.37 7.42 6.43 13.00 87.23 34.00 21.00

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Table 4.9 Raw sleep data from participants in chapter 4 (night shift 2) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 4.25 8.45 5.26 2.47 .00 51.23 56.00 21.00

3 8.08 12.06 3.58 3.06 19.00 78.15 23.00 20.00

6 7.29 15.25 7.56 7.29 1.00 94.33 21.00 15.00

9 5.15 9.43 4.28 3.19 30.00 74.25 18.00 10.00

12 2.45 9.29 6.44 5.58 .00 88.61 24.00 21.00

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Table 4.10 Raw sleep data from participants in chapter 4 (recovery 3) Participant Bed time Get up time Time in bed Total sleep Onset Sleep WASO Awakening (hours) time (hours) latency efficiency (minutes) numbers (minutes) (%) 1 1.01 7.59 8.20 5.17 .00 63.40 58.00 27.00

5 21.38 4.45 7.07 6.04 .00 85.25 41.00 26.00

7 22.35 9.14 10.39 8.56 10.00 83.88 75.00 41.00

11 22.01 7.32 10.26 8.58 30.00 85.94 56.00 37.00

12 3.52 12.12 8.20 6.58 40.00 83.60 40.00 24.00

192