MP91-06 INCREASED RISK OF HYPOGONADAL SYMPTOMS IN SHIFT WORKERS WITH SHIFT WORK SLEEP DISORDER

BACKGROUND Shift work sleep disorders (SWSDs) are associated with the high turnover rates of nurses, and are considered a major medical safety issue. However, initial management can be hampered by insufficient awareness. In recent years, it has become possible to visualize, collect and analyze the work-life balance of healthcare workers with irregular sleeping and working habits by using wearable sensors that can continuously monitor biometric data under real life settings. In addition, internet-based cognitive behavioral therapy for psychiatric disorders has been shown to be effective. Application of wearable sensors and machine learning may potentially enhance the beneficial effects of internet-based cognitive behavioral therapy. OBJECTIVE In this study, we aim to develop and evaluate the effect of a new Internet-based cognitive behavioral therapy for shift work sleep disorder (iCBTS). This system includes current methods, such as medical sleep advice, as well as machine learning wellbeing prediction to improve sleep durations of shift workers and prevent declines in their wellbeing. METHODS This study consists of two phases: (1) preliminary data collection and machine learning for wellbeing prediction; (2) intervention and evaluation of iCBTS for shift work sleep disorder. Shift workers in the ICU at Mie University will wear a wearable sensor that collects biometric data and answer daily questionnaires regarding their wellbeing. Next, they will be provided with an iCBTS app for 4 weeks. Sleep and wellbeing measurements between baseline and the intervention period will then be compared. RESULTS Recruitment for phase 1 ended in October 2019. Recruitment for phase 2 is scheduled to start in October 2020. Preliminary results are expected to be available by summer 2021. CONCLUSIONS iCBTS empowered with wellbeing prediction is expected to improve the sleep durations of shift workers, thereby enhancing their overall well-being. Findings of this study will reveal the potential of this system for improving sleep disorders among shift workers. CLINICALTRIAL UMIN clinical trials registry (phase 1: UMIN 000036122, phase 2: UMIN000040547)

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Excessive sleepiness of Thai night shift workers in medical circumstances indexed by Epworth Sleepiness Scale

Asian Journal of Medical Sciences ◽

10.3126/ajms.v10i5.24987 ◽

2019 ◽

Vol 10 (5) ◽

pp. 43-48

Author(s):

Phuttharaksa Phucharoen ◽

Phakkharawat Sittiprapaporn

Keyword(s):

Sleep Disorder ◽

Shift Work ◽

Epworth Sleepiness Scale ◽

Night Shift ◽

Sleep Wake Disorders ◽

Shift Workers ◽

Excessive Sleepiness ◽

General Terms ◽

Shift Work Sleep Disorder ◽

Cardinal Symptom

Background: Excessive sleepiness is a cardinal symptom of many sleep disorders including shift work sleep disorder. As shift work sleep disorder is one type of the circadian rhythms sleep–wake disorders (CRSDs), it composes of symptoms of insomnia or excessive sleepiness associated with a recurring work schedule that intersections with the usual sleep timetable. Aims and Objective: The objective was to study the sleep propensity (SPs) in Thai medical staffs who are working in the hospital in Thailand. Materials and Methods: Ten participants included night shift workers with excessive sleepiness. Each participant was assessed by standardized measures of excessive sleepiness (Epworth sleepiness scale [ESS] ≥ 11). Exclusions included clinical major medical problem, psychiatric, neurological problem, use of drugs other than alcohol, uncorrected serious vision issue, pregnancy and lactation, use of antibiotics and herbs during this study. The ESS item scores in this study are all assessments of different situational SPs. Results: The results showed that about 70% of the subjects answered slight chance of dozing, while 20% answered moderate chance of dozing for sitting and reading situation. Only 10% of the subjects would never doze. There were 60% of the subjects answered slight chance of dozing, while 10% answered moderate chance of dozing for as a passenger in a car for hour without a break of the ESS. There were 30% mentioned that they would never doze. Conclusion: The situations can be described in general terms but not completely, for they depend on the subject’s perception of them. Although these preliminary findings represent a relatively information, it may not reflect all the SPs in Thai medical staffs who are working in hospital. It need further research to be done in the larger extended way.

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