A Systematic Review of Workplace-Based Employee Health Interventions and Their Impact on Sleep Duration Among Shift Workers

Factors affecting the psychomotor vigilance of nurses working night shift

BACKGROUND

Shifts and long working hours decrease the psychomotor vigilance of healthcare workers especially when working night shifts. Working night shifts adversely affects nurses' health and impacts patient safety.

AIM

The purpose of this study is to identify factors affecting the psychomotor vigilance of nurses working night shift.

METHODS

This descriptive cross-sectional study was carried out with 83 nurses who were working in a private hospital in Istanbul and voluntarily participated in this study between April 25 and May 30, 2022. Data were collected using "Descriptive Characteristics Form," "Psychomotor Vigilance Task," "Pittsburgh Sleep Quality Index," and "Epworth Sleepiness Scale." The "STROBE checklist" for cross-sectional studies was utilized in order to report the findings of the study.

RESULTS

When time-dependent variation of the nurses' psychomotor vigilance task performances on the night shift was examined, it was observed that the nurses' mean reaction time and number of lapses increased at the end of the night shift. Age, smoking, physical activity, daily water consumption, daytime sleepiness, and sleep quality were found as the factors affecting nurses' psychomotor vigilance.

CONCLUSION

The psychomotor vigilance task performances of nurses working night shift are affected by age and a variety of behavioral factors.

IMPLICATIONS FOR NURSING AND HEALTH POLICY

Suggestions for nursing policy include the implementation of workplace health promotion programs in order to increase the attention level of nurses in order to ensure employee and patient health and safety and create a healthy working environment.

Effect of an Internet-Delivered Cognitive Behavioral Therapy-Based Sleep Improvement App for Shift Workers at High Risk of Sleep Disorder: Single-Arm, Nonrandomized Trial

BACKGROUND

Shift workers are at high risk of developing sleep disorders such as shift worker sleep disorder or chronic insomnia. Cognitive behavioral therapy (CBT) is the first-line treatment for insomnia, and emerging evidence shows that internet-based CBT is highly effective with additional features such as continuous tracking and personalization. However, there are limited studies on internet-based CBT for shift workers with sleep disorders.

OBJECTIVE

This study aimed to evaluate the impact of a 4-week, physician-assisted, internet-delivered CBT program incorporating machine learning-based well-being prediction on the sleep duration of shift workers at high risk of sleep disorders. We evaluated these outcomes using an internet-delivered CBT app and fitness trackers in the intensive care unit.

METHODS

A convenience sample of 61 shift workers (mean age 32.9, SD 8.3 years) from the intensive care unit or emergency department participated in the study. Eligible participants were on a 3-shift schedule and had a Pittsburgh Sleep Quality Index score ≥5. The study comprised a 1-week baseline period, followed by a 4-week intervention period. Before the study, the participants completed questionnaires regarding the subjective evaluation of sleep, burnout syndrome, and mental health. Participants were asked to wear a commercial fitness tracker to track their daily activities, heart rate, and sleep for 5 weeks. The internet-delivered CBT program included well-being prediction, activity and sleep chart, and sleep advice. A job-based multitask and multilabel convolutional neural network-based model was used for well-being prediction. Participant-specific sleep advice was provided by sleep physicians based on daily surveys and fitness tracker data. The primary end point of this study was sleep duration. For continuous measurements (sleep duration, steps, etc), the mean baseline and week-4 intervention data were compared. The 2-tailed paired t test or Wilcoxon signed rank test was performed depending on the distribution of the data.

RESULTS

In the fourth week of intervention, the mean daily sleep duration for 7 days (6.06, SD 1.30 hours) showed a statistically significant increase compared with the baseline (5.54, SD 1.36 hours; P=.02). Subjective sleep quality, as measured by the Pittsburgh Sleep Quality Index, also showed statistically significant improvement from baseline (9.10) to after the intervention (7.84; P=.001). However, no significant improvement was found in the subjective well-being scores (all P>.05). Feature importance analysis for all 45 variables in the prediction model showed that sleep duration had the highest importance.

CONCLUSIONS

The physician-assisted internet-delivered CBT program targeting shift workers with a high risk of sleep disorders showed a statistically significant increase in sleep duration as measured by wearable sensors along with subjective sleep quality. This study shows that sleep improvement programs using an app and wearable sensors are feasible and may play an important role in preventing shift work-related sleep disorders.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/24799.

Evidence summary on the non-pharmacological management of sleep disorders in shift workers

PURPOSE

This study aimed to evaluate, and integrate the relevant evidence on the non-pharmacological management of sleep disorders in shift workers to provide a reference for improving sleep of shift workers.

METHODS

According to the "6S" pyramid model of evidence, a comprehensive search was conducted in evidence-based databases, including BMJ-Best Practice, UpToDate, DynaMed, Cochrane Library, and Joanna Briggs Institute (JBI); clinical practice guideline websites, such as the Guidelines International Network; professional association websites, such as the World Sleep Society; and literature databases, including PubMed, Embase, CINAHL, China National Knowledge Infrastructure (CNKI), Wanfang Database, and Chinese Biology Medicine disc (CBM) from inception to November 30, 2022. Two researchers independently evaluated the literature in accordance with the evaluation standards; conducted the extraction, classification, and synthesis of the evidence; and evaluated its grade and recommendation grade.

RESULTS

A total of 18 studies were included, including 2 clinical decisions, 2 guidelines, 3 expert consensuses, and 11 systematic reviews. In total, 25 pieces of evidence were summarized from 6 aspects: sleep assessment, sleep scheduling, sleep hygiene, light therapy, workplace intervention, and other managements.

CONCLUSION

This study summarized the best evidence for the non-pharmacological management of sleep disorders in shift workers. Shift workers should reasonably arrange their sleep time and develop good sleep hygiene. Additionally, work organizations should jointly promote sleep to improve the sleep conditions of shift workers and promote their physical and mental health.

Effectiveness of sleep interventions for rotating night shift workers: a systematic review and meta-analysis

Background

Sleep disturbance is a common issue among rotating night shift workers and is closely related to health risks. The present study aimed to determine the effectiveness of pharmacological and non-pharmacological sleep interventions for the management of sleep disturbance among rotating night shift workers.

Methods

For this systematic review and meta-analysis, we searched six electronic databases-EMBASE, CINAHL, Cochrane Library, PubMed, Scopus, and Web of Science-for randomized controlled trials and clinical trials published from January 1990 to June 2022. The quality of eligible studies was independently assessed by three authors using the Joanna Briggs Institute Critical Appraisal Checklist for randomized controlled trials and quasi-experimental studies. The meta-analysis was performed based on the random effects model using the Comprehensive Meta-Analysis software. The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Results

Of the 1019 studies retrieved, 30 met the inclusion criteria for the systematic review; 25 were selected for the meta-analysis. Sleep interventions were categorized as follows: pharmacological approach (n = 7), light therapy (n = 9), cognitive behavioral approach (n = 7), aroma or alternative therapy (n = 4), and shift schedule modification (n = 3). The overall mean effect size of the interventions was moderate (Hedges' g = 0.59; 95% confidence interval = 0.33-0.84, z = 4.50, p < 0.001).

Conclusion

Sleep interventions were effective in promoting sleep or reducing sleep disturbance among rotating night shift workers. These findings provide evidence of the effectiveness of various pharmacological and non-pharmacological sleep interventions for managing sleep health in the work environment of rotating night shift workers.

Participatory design of a sleep intervention with correctional supervisors using a root causes approach

BACKGROUND

After a Design Team (DT) conducted a workforce health assessment of correctional supervisors, they selected sleep as an intervention priority, given its numerous health and work consequences. Existing workplace sleep interventions are designed with little worker input, but participatory solutions that incorporate workers' lived experiences and root causes of poor sleep may be more relevant, appropriate, and acceptable to end-users, resulting in better uptake.

METHODS

The DT met bi-monthly to complete the Intervention Design and Analysis Scorecard (IDEAS) tool to brainstorm interventions that address root causes of poor sleep, and evaluate, rank, and select interventions for implementation. We conducted a qualitative review of meeting notes and worksheets from each IDEAS step, and present our findings on root causes and prioritized solutions.

RESULTS

The DT consisted of two university researchers and seven members of a correctional supervisors' union, with 5-9 participants attending each meeting. IDEAS Steps 1-5 were completed in eight meetings over six months. Root causes of poor sleep included mind/body and environmental disruptions, and insufficient time. Three solutions were proposed: training on sleep hygiene, meditation, and sleep debt management; a sleep-tracking smartphone app; and a shared overtime policy based on splitting one 8-hour shift between two supervisors.

CONCLUSIONS

This is the first known application of IDEAS to address sleep, and targeting root causes may result in more efficacious interventions for sleep improvement. Moreover, because IDEAS guides DTs in selecting solutions with the greatest perceived health benefits, reach, cost-effectiveness, and feasibility, it may result in more successful implementation.