[Latar belakang: Kelelahan penerbang sipil termasuk pada penerbangan jarakdekat dapat mempengaruhi fungsi kognisi penerbang sehingga membahayakankeselamatan penerbangan. Tujuan penelitian ini untuk mengidentifikasi faktorfaktoryang mempengaruhi kelelahan penerbang sipil pada penerbangan jarakdekat di Indonesia.Metode: Desain penelitian potong lintang dengan purposive sampling dilakukandi antara penerbang jarak dekat dengan rating Boeing 737 series yangmelaksanakan pengujian kesehatan di Balai Kesehatan Penerbangan selamaperiode 5-26 Mei 2014. Kelelahan diukur dengan Self-Reporting Questionnaire,Fatigue Severity Scale (FSS). Data dikumpulkan dengan pengisian kuesioner olehsubyek, meliputi demografi, pekerjaan, kehilangan waktu tidur (EpworthSleepiness Scale - ESS), faktor personal, dukungan manajemen, dan FSS. Analisisregresi linear dipakai untuk menganalisis faktor-faktor berkaitan kelelahan.Hasil: Di antara 785 penerbang yang melaksanakan pengujian kesehatan, 382bersedia berpartisipasi, dan 239 subyek memiliki rating Boeing 737 series. Ratarataskala kelelahan adalah 4,66 (standar deviasi 1,202). Faktor-faktor dominanyang mempertinggi skala kelelahan adalah jumlah sektor 24 jam terakhir, jamterbang penugasan di luar jadwal, dan kehilangan waku tidur. Setiap penambahan1 sektor dalam 24 jam terakhir meningkatkan 0,371 skala kelelahan [koefisienregresi (β) = 0,371; P = 0,000]. Selanjutnya setiap penambahan 1 jam terbangpenugasan di luar jadwal memepertinggi 0,033 skala kelelahan (β = 0,033; P =0,000). Sedangkan setiap penambahan 1 nilai ESS mempertinggi 0,043 skalakelelahan (β = 0,043; P = 0,008).Simpulan: Jumlah sektor 24 jam terakhir, kehilangan waktu tidur, dan jamterbang penugasan di luar jadwal mempertinggi risiko kelelahan di antarapenerbang sipil pada penerbangan jarak dekat di Indonesia.;Background: Fatigue could impair pilots’ cognitive function which may lead toaccidents in short-haul flight. The aims of this study were to investigate the riskfactors of short-haul commercial pilots fatigue in IndonesiaMethods: Cross-sectional study with purposive sampling was directed to Boeing737 series typed-rating pilots who were taking medical examination at the CivilAviation Medical Center, Jakarta from May 5-26th 2014. Fatigue was measuredwith Self-Reporting Questionnaire, Fatigue Severity Scale (FSS). Data werecollected by completing an anonymous questionnaire on demographics, workload,sleep restriction (Epworth Sleepiness Scale-ESS), personal factors, andmanagerial support. Risk factors and fatigue were analyzed using linearregression.Results: During data collection, 785 pilots were taking medical examination, 382pilots were willing to participate and 239 Boeing 737 series typed-rating pilotswere chosen as subjects. Mean of FSS was 4.66 ± 1.202. Dominant factors offatigue were number of sectors in 24 consecutive hours, flight times of unplannedflights in 30 consecutive days, and sleep restriction. Each additional sectorcorrelated significantly to a 0.371 increase on the FSS [regression coefficient (β)= 0,371; p=0,000] and each additional value of ESS correlated significantly to a0,043 on the FSS (β = 0,043; p = 0,008), while each additional flight times ofunplanned flights correlated significantly to a 0,033 on the FSS (β = 0,033; p =0,000).Conclusions: Number of sectors in 24 consecutive hours, flight times ofunplanned flights in 30 consecutive days, and sleep restriction correlatedsignificantly to higher FSS., Background: Fatigue could impair pilots’ cognitive function which may lead toaccidents in short-haul flight. The aims of this study were to investigate the riskfactors of short-haul commercial pilots fatigue in IndonesiaMethods: Cross-sectional study with purposive sampling was directed to Boeing737 series typed-rating pilots who were taking medical examination at the CivilAviation Medical Center, Jakarta from May 5-26th 2014. Fatigue was measuredwith Self-Reporting Questionnaire, Fatigue Severity Scale (FSS). Data werecollected by completing an anonymous questionnaire on demographics, workload,sleep restriction (Epworth Sleepiness Scale-ESS), personal factors, andmanagerial support. Risk factors and fatigue were analyzed using linearregression.Results: During data collection, 785 pilots were taking medical examination, 382pilots were willing to participate and 239 Boeing 737 series typed-rating pilotswere chosen as subjects. Mean of FSS was 4.66 ± 1.202. Dominant factors offatigue were number of sectors in 24 consecutive hours, flight times of unplannedflights in 30 consecutive days, and sleep restriction. Each additional sectorcorrelated significantly to a 0.371 increase on the FSS [regression coefficient (β)= 0,371; p=0,000] and each additional value of ESS correlated significantly to a0,043 on the FSS (β = 0,043; p = 0,008), while each additional flight times ofunplanned flights correlated significantly to a 0,033 on the FSS (β = 0,033; p =0,000).Conclusions: Number of sectors in 24 consecutive hours, flight times ofunplanned flights in 30 consecutive days, and sleep restriction correlatedsignificantly to higher FSS.] |