지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.8
- 수록면
- 38 - 44 (7page)
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초록· 키워드
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Purpose: This study aimed to identify the prevalence of fatigue and its associated factors leading to the fatigue among Korean commercial airline pilots.
Methods: An anonymous, web-based questionnaire collecting data on sleep related characteristics was completed by airline pilots. The final 1,029 samples of completed questionnaires were analyzed. The association of the risk factors with fatigue was determined using logistic regression analysis.
Results: The prevalence of fatigue was 60% (Fatigue Severity Scale index≥3.2), disturbed sleep 28% (Pittsburgh Sleep Quality Index≥9), daytime sleepiness 17% (Epworth Sleepiness Scale≥10), and sleep apnea (Berlin Questionnaire≥2) 11%. The fully adjusted logistic regression showed that quality of life (odds ratio [OR]=0.16, confidence interval [CI]=0.11–0.24), daytime sleepiness (OR=1.26, CI=1.18–1.34), sleep quality (OR=1.44, CI=1.29–1.61), mental workload (OR=1.10, CI=1.05–1.14), vigorous physical activity (OR=0.82, CI=0.72–0.92), late starts (OR=1.25, CI=1.06–1.46) and average weekly flying hours (OR=1.02, CI=1.00–1.03) were associated with higher levels of fatigue.
Conclusion: Lower quality of life, disturbed sleep, more subjective sleepiness, shorter sleep duration, higher mental workload, less vigorous physical activity, frequent late starts, and longer flying hour were shown to be risk factors for fatigue in airline pilots. These findings should be taken into account in the development of sleep and fatigue countermeasures for airline pilots.
Methods: An anonymous, web-based questionnaire collecting data on sleep related characteristics was completed by airline pilots. The final 1,029 samples of completed questionnaires were analyzed. The association of the risk factors with fatigue was determined using logistic regression analysis.
Results: The prevalence of fatigue was 60% (Fatigue Severity Scale index≥3.2), disturbed sleep 28% (Pittsburgh Sleep Quality Index≥9), daytime sleepiness 17% (Epworth Sleepiness Scale≥10), and sleep apnea (Berlin Questionnaire≥2) 11%. The fully adjusted logistic regression showed that quality of life (odds ratio [OR]=0.16, confidence interval [CI]=0.11–0.24), daytime sleepiness (OR=1.26, CI=1.18–1.34), sleep quality (OR=1.44, CI=1.29–1.61), mental workload (OR=1.10, CI=1.05–1.14), vigorous physical activity (OR=0.82, CI=0.72–0.92), late starts (OR=1.25, CI=1.06–1.46) and average weekly flying hours (OR=1.02, CI=1.00–1.03) were associated with higher levels of fatigue.
Conclusion: Lower quality of life, disturbed sleep, more subjective sleepiness, shorter sleep duration, higher mental workload, less vigorous physical activity, frequent late starts, and longer flying hour were shown to be risk factors for fatigue in airline pilots. These findings should be taken into account in the development of sleep and fatigue countermeasures for airline pilots.
목차
I. INTRODUCTION
II. MATERIALS AND METHODS
III. RESULTS
IV. DISCUSSION
V. CONCLUSION
REFERENCES
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