Improving sleep health in paramedics through an app-based intervention: a randomised waitlist control pilot trial.

BACKGROUND: Due to work commitments, shiftworkers often obtain inadequate sleep, consequently experiencing negative health, wellbeing, and safety outcomes. Given shiftworkers may have limited control over their work commitments, lifestyle and environmental factors within their control may present an intervention opportunity. However, such interventions require tailoring to ensure applicability for this sleep-vulnerable population. METHODS: A randomised waitlist control pilot trial investigated the effectiveness of mobile health application Sleepfit, which delivered a tailored sleep health intervention aimed at improving sleep health and sleep hygiene outcomes amongst paramedic shiftworkers. Outcome measures of self-reported sleep health (sleep need, duration, and quality, fatigue, Insomnia Severity Index, Fatigue Severity Scale, and Epworth Sleepiness Scale scores) and sleep hygiene (Sleep Hygiene Index score) were collected at baseline, post-intervention, and 3-month follow-up. RESULTS: Fifty-eight paramedics (aged 33.4 ± 8.0 years; 50% male) were recruited, and trialed Sleepfit for a 14-day intervention period between August 2021-January 2022. For all participants, there was a significant reduction in Insomnia Severity Index and Sleep Hygiene index scores after intervention engagement. Regression models demonstrated no significant intervention effect on sleep health or sleep hygiene outcomes (intervention versus waitlist control group). A high study drop-out rate (91.4%) prevented assessment of outcomes at 3-month follow-up. CONCLUSIONS: Pilot trial findings demonstrate that Sleepfit may elicit improvements in sleep health and sleep hygiene outcomes amongst paramedic shiftworkers. However, low enrolment and retention means that findings should be interpreted with caution, further highlighting potential engagement challenges, especially among paramedics who are particularly in need of support for improved sleep. TRIAL REGISTRATION: Prospectively registered with the Australian New Zealand Clinical Trial Registry 24/01/2020 (reference no. ACTRN12620000059965).

Symptoms of sleep problems and adherence to dietary guidelines in older women: evidence from the Australian Longitudinal Study on Women's Health.

OBJECTIVE: This study examined adherence to dietary guidelines and symptoms of sleep problems (e.g. taking a long time to fall sleep or waking up early) and their associations in a sample of older Australian women (68-73 years of age). DESIGN: This was a population-based cross-sectional study. Adherence to the dietary guidelines was measured using a validated FFQ and reported as a diet quality score. Symptoms of sleep problems were measured using five questions and a total score was derived. Multivariate linear regression was used to investigate the association between these outcomes, adjusted for the potential confounding influence of demographic (i.e. age and marital status) and lifestyle (i.e. physical activity, stress, alcohol intake, sleep medication use) variables. SETTING: Respondents from the 1946-1951 cohort of the Australian Longitudinal Study on Women's Health who completed Survey 9 were included. PARTICIPANTS: Data from n 7956 older women (mean age ± sd: 70·8 ± 1·5) were included. RESULTS: 70·2 % reported having at least one symptom and 20·5 % had between 3 and 5 symptoms of sleep problems (mean score ± sd: 1·4 ± 1·4, range 0-5). Adherence to dietary guidelines was poor with an average diet quality score of 56·9 ± 10·7 (range 0-100). Better adherence to dietary guidelines was associated with fewer sleep problem symptoms (ß: -0·065, 95 % CI: -0·012, -0·005) and remained significant after adjusting for confounding influences. CONCLUSIONS: These findings support the evidence that adherence to dietary guidelines is associated with symptoms of sleep problems in older women.

"I need to be alert at night to provide care": Factors associated with problematic sleep among young Australian caregivers.

OBJECTIVES: There is increased recognition that young people (<25 years) may occupy a carer role for family or others with health conditions or disability. This is often in addition to study and social activities. This means competing demands on time, and insufficient sleep. Our aim was to determine the contribution of caring duties to problematic sleep in young carers. METHODS: A survey of Australian carers was conducted, including questions on demographics, characteristics of the carer and care recipient, and sleep quality and quantity. Participants were eligible if they reported sleep time <7 hr or dissatisfaction with their sleep, and were aged 15-24 years. RESULTS: A total of 110 participants (71.8%_female = 79, 15-17 years = 62, 18-24 years = 48) were included in analysis; 55.5% (n= 61) reporting dissatisfaction with their sleep and 62.7% (n= 69) reporting typically less than 7 hr sleep per night. Sleep duration was significantly shorter for those who reported 1-2 or ≥3 awakenings to provide care, compared with no awakenings (p_< .05). Sleep quality, as described by scores on the Pittsburgh Sleep Quality Index (PSQI) was also significantly worse for those who were frequently awoken by their care recipient (p < .05). Worrying about the care recipient, being woken by the care recipient, and listening out for the care recipient were the most frequently identified factors impacting on sleep. CONCLUSION: Young carers experience reduced sleep duration and poor sleep quality. Strategies to alleviate the burden of care work on young carer's sleep would benefit the health and safety of this group.

Self-collected versus medic-collected sampling for human papillomavirus testing among women in Lagos, Nigeria: a comparative study.

OBJECTIVE: To evaluate the feasibility and performance of self-collected vaginal swab samples for HPV screening among women in Lagos, Nigeria. METHODS: A cross-sectional study was implemented from March to August 2020 among sexually active women. Study participants provided same-day paired vaginal swab samples. Medic-sampling and poster-directed self-sampling methods were used to collect the two samples per participant. A real-time PCR assay detected HPV 16, HPV 18, other-high-risk (OHR) HPV, and the human ß-globin gene. The self-collected samples' sensitivity, specificity, and accuracy were determined against the medic-collected samples using the MedCalc Online Diagnostic Calculator. RESULTS: Of the 213 women aged 16 ~ 63-year-old recruited, 187 (88%) participants had concordant results, while 26 (12%) participants had discordant results. Among the 187 concordant results, 35 (19%) were HPV positive, 150 (80%) participants were HPV negative, and two (1%) were invalid. 18 (69%) out of the 26 discordant samples were invalid. The self-collected sample was invalid for 14 (54%) participants. Two (8%) medic-collected samples were invalid. Compared to the medic-collected sample, the self-collected sample was 89.80% (95% CI: 77.77 ~ 96.60%) sensitive and 98.21% (95% CI: 94.87 ~ 99.63%) specific, with an accuracy of 96.31% (95% CI: 92.87 ~ 98.40%). The mean age for HPV positive and negative participants were 39 and 40, respectively, with an ANOVA p-value of 0.3932. The stratification of HPV infection by the age group was not statistically significant (P > 0.05). CONCLUSIONS: With high accuracy of 96%, self-collected sampling is adequate when tested with real-time PCR and may increase the uptake of HPV testing. Though more self-collected samples were invalid than medic-collected samples, most likely due to poor collection, they could be identified for repeat testing. Future implementation can avoid this error with improved guidance and awareness.

A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving.

Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver's recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data collected during a simulated driving task to classify recent sitting and sleep history. Participants (n = 84, Mean ± SD age = 23.5 ± 4.8, 49% Female) completed a seven-day laboratory study. Raw accelerometry data were collected from a thigh-worn accelerometer during a 20-min simulated drive (8:10 h and 17:30 h each day). Two convolutional neural networks (CNNs; ResNet-18 and DixonNet) were trained to classify accelerometry data into four classes (sitting or breaking up sitting and 9-h or 5-h sleep). Accuracy was determined using five-fold cross-validation. ResNet-18 produced higher accuracy scores: 88.6 ± 1.3% for activity (compared to 77.2 ± 2.6% from DixonNet) and 88.6 ± 1.1% for sleep history (compared to 75.2 ± 2.6% from DixonNet). Class activation mapping revealed distinct patterns of movement and postural changes between classes. Findings demonstrate the suitability of CNNs in classifying sitting and sleep history using thigh-worn accelerometer data collected during a simulated drive. This approach has implications for the identification of drivers at risk of fatigue-related impairment.

The effect of a short burst of exercise during the night on subsequent sleep.

When on-call workers wake during the night to perform work duties, they may experience reduced alertness and impaired performance as a result of sleep inertia. After performing their duties, on-call workers may have the opportunity to return to sleep. Thus, it is important that sleep inertia countermeasures do not affect subsequent sleep. Exercise may be a suitable countermeasure; however, the impact on subsequent sleep is untested. Healthy participants (n = 15) completed three conditions in a counterbalanced order: sedentary, low-intensity exercise or high-intensity exercise, performed for 2 min upon awakening. Sleep was recorded 2 hr later using polysomnography, the Karolinska Sleepiness Scale was administered to measure subjective sleepiness, and core body temperature was measured continuously. Results indicate there was no effect of condition on most sleep variables; however, three variables had small differences, with longer total sleep time (p = .006), higher sleep efficiency (p = .006) and shorter N3 latency (p < .001) in the low-intensity exercise condition. There was no difference in subjective sleepiness (p = .124) or core body temperature (p = .216) 90 min after the exercise intervention. These results indicate that using a short burst of exercise to counteract sleep inertia when woken during the night may be a suitable countermeasure for on-call workers who not only need to be alert upon waking but also need quality sleep when returning to bed. Future research could include participants of other ages and health statuses to investigate whether the results are generalizable.

What Factors Influence the Sleep of On-call Workers?

Objective: On-call work is becoming increasingly common in response to service demands. This study had two aims; 1) describe the demographic profile of on-call workers in Australia, and 2) establish the impacts of on-call work on workers' sleep. Methods: A cross-sectional study was conducted using an online questionnaire completed by Australian on-call workers (n = 228) from various professions. The questionnaire included items on i) demographic and work characteristics, ii) rumination about on-call factors, iii) sleep quantity and quality. Analyses were conducted using mixed effects ordinal regression and multivariable logistic regression. Results: Workers slept <7 hours per night when on-call (80%), and reported sleep was impacted on-call even when no-calls were received (56%). On-call workers rated interruptions to family/leisure time (70%), missing a call (69%), preplanning in case of a call (69%), and not able to make plans (67%) as the main factors they ruminated about. Female on-call workers were more likely to think about the likelihood of being called, report frequent thoughts about what they would need to do if called, and think about interruptions to family/leisure time as a result of a call. Younger workers were more likely to think about the likelihood of being called compared to older adults, however middle-aged workers were less likely to plan for a call compared to younger workers. Conclusions: This study is the first to describe Australia's on-call population, including factors that specifically impact sleep. Future studies should implement tailored education and support strategies to address the unique challenges facing on-call workers.

The Discrepancy between Knowledge of Sleep Recommendations and the Actual Sleep Behaviour of Australian Adults.

Introduction: Inadequate sleep is a major public health concern, with large economic, health, and operational costs to Australia. Despite the implementation of public sleep health campaigns, approximately 40% of Australian adults do not obtain the recommended 7-9 hours of sleep. Thus, while people may know how much sleep is required, this knowledge may not be adequately translated to actual sleep behavior. Consequently, this study aims to examine the discrepancy between knowledge of sleep recommendations and self-reported sleep behaviors.Methods: A sample of 1265 Australian adults (54% female, aged 18-65) completed a phone interview as part of the 2017 National Social Survey and were asked questions about their knowledge of sleep guidelines and their actual sleep behavior. Binary logistic regression was used to determine the factors associated with awareness of sleep recommendations and whether this corresponded with reported sleep duration.Results: The final sample size was 998. Although 94% of the sample were aware of current sleep recommendations, 23% of participants did not self-report regularly obtaining 7-9 h sleep per night. These participants were less likely to want to obtain more sleep, less likely to view sleep as a priority before stressful events, and less likely to self-report good health.Conclusion: Although a majority of the sample were aware of sleep recommendations, almost a quarter of the participants' behavior did not align with their knowledge. Future sleep health campaigns should consider options beyond education, including emphasis on practical strategies and modifiable lifestyle factors to assist individuals to obtain the recommended amount of sleep.

Exercise before bed does not impact sleep inertia in young healthy males.

Sleep inertia is the transitional state marked by impaired cognitive performance and reduced vigilance upon waking. Exercising before bed may increase the amount of slow-wave sleep within the sleep period, which has previously been associated with increased sleep inertia. Healthy males (n = 12) spent 3 nights in a sleep laboratory (1-night washout period between each night) and completed one of the three conditions on each visit - no exercise, aerobic exercise (30 min cycling at 75% heart rate), and resistance exercise (six resistance exercises, three sets of 10 repetitions). The exercise conditions were completed 90 min prior to bed. Sleep was measured using polysomnography. Upon waking, participants completed five test batteries every 15 min, including the Karolinska Sleepiness Scale, a Psychomotor Vigilance Task, and the Spatial Configuration Task. Two separate linear mixed-effects models were used to assess: (a) the impact of condition; and (b) the amount of slow-wave sleep, on sleep inertia. There were no significant differences in sleep inertia between conditions, likely as a result of the similar sleep amount, sleep structure and time of awakening between conditions. The amount of slow-wave sleep impacted fastest 10% reciprocal reaction time on the Psychomotor Vigilance Task only, whereby more slow-wave sleep improved performance; however, the magnitude of this relationship was small. Results from this study suggest that exercise performed 90 min before bed does not negatively impact on sleep inertia. Future studies should investigate the impact of exercise intensity, duration and timing on sleep and subsequent sleep inertia.

How to manage travel fatigue and jet lag in athletes? A systematic review of interventions.

OBJECTIVES: We investigated the management of travel fatigue and jet lag in athlete populations by evaluating studies that have applied non-pharmacological interventions (exercise, sleep, light and nutrition), and pharmacological interventions (melatonin, sedatives, stimulants, melatonin analogues, glucocorticoids and antihistamines) following long-haul transmeridian travel-based, or laboratory-based circadian system phase-shifts. DESIGN: Systematic review Eligibility criteria Randomised controlled trials (RCTs), and non-RCTs including experimental studies and observational studies, exploring interventions to manage travel fatigue and jet lag involving actual travel-based or laboratory-based phase-shifts. Studies included participants who were athletes, except for interventions rendering no athlete studies, then the search was expanded to include studies on healthy populations. DATA SOURCES: Electronic searches in PubMed, MEDLINE, CINAHL, Google Scholar and SPORTDiscus from inception to March 2019. We assessed included articles for risk of bias, methodological quality, level of evidence and quality of evidence. RESULTS: Twenty-two articles were included: 8 non-RCTs and 14 RCTs. No relevant travel fatigue papers were found. For jet lag, only 12 athlete-specific studies were available (six non-RCTs, six RCTs). In total (athletes and healthy populations), 11 non-pharmacological studies (participants 600; intervention group 290; four non-RCTs, seven RCTs) and 11 pharmacological studies (participants 1202; intervention group 870; four non-RCTs, seven RCTs) were included. For non-pharmacological interventions, seven studies across interventions related to actual travel and four to simulated travel. For pharmacological interventions, eight studies were based on actual travel and three on simulated travel. CONCLUSIONS: We found no literature pertaining to the management of travel fatigue. Evidence for the successful management of jet lag in athletes was of low quality. More field-based studies specifically on athlete populations are required with a multifaceted approach, better design and implementation to draw valid conclusions. PROSPERO registration number The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42019126852).

The effects of anticipating a high-stress task on sleep and performance during simulated on-call work.

On-call work is used to manage around the clock working requirements in a variety of industries. Often, tasks that must be performed while on-call are highly important, difficult and/or stressful by nature and, as such, may impact the level of anxiety that is experienced by on-call workers. Heightened anxiety is associated with poor sleep, which affects next-day cognitive performance. Twenty-four male participants (20-35 years old) spent an adaptation, a control and two counterbalanced on-call nights in a time-isolated sleep laboratory. On one of the on-call nights they were told that they would be required to do a speech upon waking (high-stress condition), whereas on the other night they were instructed that they would be required to read to themselves (low-stress condition). Pre-bed anxiety was measured by the State Trait Anxiety Inventory form x-1, and polysomnography and quantitative electroencephalogram analyses were used to investigate sleep. Performance was assessed across each day using the 10-min psychomotor vigilance task (09:30 hours, 12:00 hours, 14:30 hours, 17:00 hours). The results indicated that participants experienced no significant changes in pre-bed anxiety or sleep between conditions. However, performance on the psychomotor vigilance task was best in the high-stress condition, possibly as a result of heightened physiological arousal caused by performing the stressful task that morning. This suggests that performing a high-stress task may be protective of cognitive performance to some degree when sleep is not disrupted.

Adding sleep restriction to the equation: impact on wildland firefighters' work performance and physiology in hot conditions.

PURPOSE: To examine the effects of sleep restriction on firefighters' physical task performance, physical activity, and physiological and perceived exertion during simulated hot wildfire conditions. METHODS: 31 firefighters were randomly allocated to either the hot (n = 18, HOT; 33 °C, 8-h sleep opportunity) or hot and sleep restricted (n = 13, HOT + SR; 33 °C, 4-h sleep opportunity) condition. Intermittent, self-paced work circuits of six firefighting tasks were performed for 3 days. Firefighters self-reported ratings of perceived exertion. Heart rate, core temperature, and physical activity were measured continuously. Fluids were consumed ad libitum, and all food and fluids consumed were recorded. Urine volume and urine specific gravity (USG) were analysed and sleep was assessed using polysomnography (PSG). RESULTS: There were no differences between the HOT and HOT + SR groups in firefighters' physical task performance, heart rate, core temperature, USG, or fluid intake. Ratings of perceived exertion were higher (p < 0.05) in the HOT + SR group for two of the six firefighting tasks. The HOT group spent approximately 7 min more undertaking moderate physical activity throughout the 2-h work circuits compared to the HOT + SR group. CONCLUSION: Two nights of sleep restriction did not influence firefighters' physical task performance or physiological responses during 3 days of simulated wildfire suppression. Further research is needed to explore firefighters' pacing strategies during real wildfire suppression.

Associations between firefighters' physical activity across multiple shifts of wildfire suppression.

The aim of this study was to examine the associations between firefighters' physical activity levels across consecutive wildfire suppression shifts and to determine whether sleep duration moderated these associations. Forty volunteer firefighters (31 males, 9 females) wore an activity monitor to concurrently measure physical activity and sleep duration. Sedentary time and time spent in light- (LPA), moderate- (MPA), and vigorous-intensity physical activity (VPA) during each shift were determined using monitor-specific cut points. During any given shift, every additional 60 min spent in LPA was associated with 7.2 min more LPA and 27.6 min MPA the following shift. There were no other significant positive or negative associations. No significant moderating effect of total sleep time was observed. Firefighters are able to maintain and/or increase their physical activity intensity between consecutive shifts. Further research is needed to understand firefighters pacing and energy conservation strategies during emergency wildfire deployments. Practitioner Summary: To examine associations between firefighters' physical activity levels across consecutive shifts during a multi-day emergency wildfire and determine whether sleep duration moderated these associations. Firefighters are able to maintain and/or increase their physical activity intensity between consecutive shifts. No significant moderating effect of total sleep time was observed.

Fighting fire and fatigue: sleep quantity and quality during multi-day wildfire suppression.

This study examined firefighters' sleep quantity and quality throughout multi-day wildfire suppression, and assessed the impact of sleep location, shift length, shift start time and incident severity on these variables. For 4 weeks, 40 volunteer firefighters' sleep was assessed using wrist actigraphy. Analyses revealed that the quantity of sleep obtained on fire days was restricted, and pre- and post-sleep fatigue ratings were higher, compared to non-fire days. On fire days, total sleep time was less when: (i) sleep location was in a tent or vehicle, (ii) shifts were greater than 14 h and (iii) shifts started between 05:00 and 06:00 h. This is the first empirical investigation providing objective evidence that firefighters' sleep is restricted during wildfire suppression. Furthermore, sleep location, shift length and shift start time should be targeted when designing appropriate controls to manage fatigue-related risk and preserve firefighters' health and safety during wildfire events. Practitioner Summary: During multi-day wildfire suppression, firefighters' sleep quantity was restricted, and pre- and post-sleep fatigue ratings were higher, compared to non-fire days. Furthermore, total sleep time was less when: (i) sleep occurred in a tent/vehicle, (ii) shifts were >14 h and (iii) shifts started between 05:00 and 06:00 h.

'It's satisfying but destructive': A qualitative study on the experience of bedtime procrastination in new career starters.

BACKGROUND: Bedtime procrastination, the volitional delay of going to bed without any external circumstances causing the delay, is linked to multiple indicators of inadequate sleep. Intervening to reduce bedtime procrastination may be an important avenue to improve sleep outcomes, yet the phenomenon remains poorly understood in populations at risk for bedtime procrastination. New career starters, those who have graduated from tertiary education and started a new full-time job within the past 12 months, may be susceptible to problematic bedtime procrastination and are at an opportune time for a 'fresh start' to change behaviour. AIMS: The objectives of this study were to understand how bedtime procrastination is experienced and perceived by new career starters, to identify the enablers and barriers to behaviour change in new career starters and to explore themes for future interventions. MATERIALS & METHODS: Data were collected through in-depth semi-structured interviews with 28 participants. RESULTS: Inductive thematic analysis was used to find seven themes: (1) negative feelings before and during bedtime procrastination; (2) wanting to versus knowing I shouldn't; (3) difficulty falling asleep; (4) influence of automatic processes; (5) consequences of bedtime procrastination; (6) lack of self-control and (7) technology captures late-night attention. Participants emphasised the need for me-time, self-negotiation to continue procrastinating and knowledge of the value of sleep. DISCUSSION & CONCLUSION: Findings suggest that bedtime procrastination involves both reflective and automatic cognitive processes. Future interventions would benefit from a dual-process approach, using cognitive and behavioural techniques to reduce bedtime procrastination.

Move the night way: how can physical activity facilitate adaptation to shift work?

Shift work, involving night work, leads to impaired sleep, cognition, health and wellbeing, and an increased risk of occupational incidents. Current countermeasures include circadian adaptation to phase shift circadian biomarkers. However, evidence of real-world circadian adaptation is found primarily in occupations where light exposure is readily controlled. Despite this, non-photic adaptation to shift work remains under researched. Other markers of shift work adaptation exist (e.g., improvements in cognition and wellbeing outcomes) but are relatively unexplored. Timeframes for shift work adaptation involve changes which occur over a block of shifts, or over a shift working career. We propose an additional shift work adaptation timeframe exists which encompasses acute within shift changes in markers of adaptation. We also propose that physical activity might be an accessible and cost-effective countermeasure that could influence multiple markers of adaptation across three timeframes (Within Shift, Within Block, Within Work-span). Finally, practical considerations for shift workers, shift work industries and future research are identified.

Calibrated to drive: Measuring self-assessed driving ability and perceived workload after prolonged sitting and sleep restriction.

Self-assessed driving ability may differ from actual driving performance, leading to poor calibration (i.e., differences between self-assessed driving ability and actual performance), increased risk of accidents and unsafe driving behaviour. Factors such as sleep restriction and sedentary behaviour can impact driver workload, which influences driver calibration. This study aims to investigate how sleep restriction and prolonged sitting impact driver workload and driver calibration to identify strategies that can lead to safer and better calibrated drivers. Participants (n = 84, mean age = 23.5 ± 4.8, 49 % female) undertook a 7-day laboratory study and were randomly allocated to a condition: sitting 9-h sleep opportunity (Sit9), breaking up sitting 9-h sleep opportunity (Break9), sitting 5-h sleep opportunity (Sit5) and breaking up sitting 5-h sleep opportunity (Break5). Break9 and Break5 conditions completed 3-min of light-intensity walking on a treadmill every 30 min between 09:00-17:00 h, while participants in Sit9 and Sit5 conditions remained seated. Each participant completed a 20-min simulated commute in the morning and afternoon each day and completed subjective assessments of driving ability and perceived workload before and after each commute. Objective driving performance was assessed using a driving simulator measuring speed and lane performance metrics. Driver calibration was analysed using a single component and 3-component Brier Score. Correlational matrices were conducted as an exploratory analysis to understand the strength and direction of the relationship between subjective and objective driving outcomes. Analyses revealed participants in Sit9 and Break9 were significantly better calibrated for lane variability, lane position and safe zone-lane parameters at both time points (p < 0.0001) compared to Sit5 and Break5. Break5 participants were better calibrated for safe zone-speed and combined safe zone parameters (p < 0.0001) and speed variability at both time points (p = 0.005) compared to all other conditions. Analyses revealed lower perceived workload scores at both time points for Sit9 and Break9 participants compared to Sit5 and Break5 (p = <0.001). Breaking up sitting during the day may reduce calibration errors compared to sitting during the day for speed keeping parameters. Future studies should investigate if different physical activity frequency and intensity can reduce calibration errors, and better align a driver's self-assessment with their actual performance.

Sleep hygiene - What do we mean? A bibliographic review.

There is no consensus on the definition of sleep hygiene and its components. We examined the definition of sleep hygiene based on its use in published studies. Four databases (Medline, EMBASE, PsycINFO and CINAHL) were searched from inception until December 31, 2021 for the phrase 'sleep hygiene' in the title or abstract. We identified 548 relevant studies in adults: 250 observational and 298 intervention studies. A definition of sleep hygiene was provided in only 44% of studies and converged on three themes: behavioural factors, environmental factors, and an aspect of control. Sleep hygiene components were explicitly defined in up to 70% of observational studies, but in only 35% of intervention studies. The most commonly considered components of sleep hygiene were caffeine (in 51% of studies), alcohol (46%), exercise (46%), sleep timing (45%), light (42%), napping (39%), smoking (38%), noise (37%), temperature (34%), wind-down routine (33%), stress (32%), and stimulus control (32%), although the specific details of each component varied. Lack of consistency in definitions of sleep hygiene and its components may hinder communication between researchers, clinicians, and the public, and likely limits the utility of sleep hygiene as an intervention.

The impact of breaking up sitting during simulated nightshifts on musculoskeletal pain: A randomised controlled trial.

OBJECTIVES: Prolonged sitting is associated with an increased risk of musculoskeletal pain, especially in nightshift workers. However, research investigating effects of breaking up sitting on musculoskeletal pain during nightshifts is lacking. This study evaluated effects of prolonged sitting or breaking up sitting with short bouts of light-intensity physical activity on pain in healthy adults during simulated nightshifts. METHODS: An in-laboratory randomised controlled trial was undertaken with 52 healthy adults completing five simulated nightshifts. Participants were randomised to prolonged sitting (Sit9; n = 26) or breaking up prolonged sitting (Break9; n = 26). Break9 group completed 3-min walking every 30 min during nightshifts, while Sit9 group remained seated. Musculoskeletal pain intensity and sensory/affective pain experiences were assessed. Linear mixed models examined pain within nights (pre-to post-shift) and across nights (pre-shift-night-1 to pre-shift-night-5). RESULTS: Musculoskeletal pain intensity increased within nights for both Sit9 (mean change [95%CI] points: 0.14 [0.05, 0.24]) and Break9 (0.09 [0.001, 0.19], but not across nights (Sit9: -0.13 [-0.33, 0.08]; Break9: 0.07 [-0.14, 0.29]). Sensory-pain experience improved across nights for Sit9 (-3.08 [-4.72, -1.45]), but not within nights (0.77 [-0.004, 1.55]). There was no change in affective-pain experience in either group. Between-group difference was observed favouring Sit9 for improving sensory-pain across nights (ß: 3.71 [1.42, 5.99]). No other between-group difference was observed. CONCLUSION: Both prolonged sitting and breaking up sitting were associated with a within-night increase in musculoskeletal pain intensity. Compared to prolonged sitting, breaking up sitting did not induce benefits on pain in healthy adults working simulated nightshifts. TRIAL REGISTRATION: ACTRN12619001516178.

Healthy sleep practices for shift workers: consensus sleep hygiene guidelines using a Delphi methodology.

STUDY OBJECTIVES: The unique requirements of shift work, such as sleeping and working at variable times, mean that current sleep hygiene guidelines may be inappropriate for shift workers. Current guidelines may also contradict fatigue management advice (e.g. advising against daytime napping). The present study utilized a Delphi methodology to determine expert opinion regarding the applicability of current guidelines for shift workers, the appropriateness of the term "sleep hygiene," and develop tailored guidelines for shift workers. METHODS: The research team reviewed current guidelines and existing evidence to draft tailored guidelines. Seventeen individual guidelines, covering sleep scheduling, napping, sleep environment, bedtime routine, substances, light exposure, diet, and exercise were drafted. Experts from sleep, shift work, and occupational health fields (n = 155) were invited to review the draft guidelines using a Delphi methodology. In each round, experts voted on individual guidelines, with 70% agreement considered consensus. Where consensus was not reached, written feedback from experts was discussed and incorporated into subsequent iterations. RESULTS: Of the experts invited, 68 (44%) agreed to participate, with 55 (35%) completing the third (final) round. Most experts (84%) agreed that tailored guidelines were required for shift workers. Consensus was reached on all guidelines after three rounds. One additional guideline (sleep inertia) and an introductory statement were developed, resulting in a final set of 18 individual guidelines, termed "healthy sleep practices for shift workers." CONCLUSIONS: This is the first study to develop tailored sleep hygiene guidelines for shift workers. Future research should investigate the acceptability and effectiveness of these guidelines amongst shift workers.