[Latar belakang: Kelelahan penerbang sipil termasuk pada penerbangan jarak
dekat dapat mempengaruhi fungsi kognisi penerbang sehingga membahayakan
keselamatan penerbangan. Tujuan penelitian ini untuk mengidentifikasi faktorfaktor
yang mempengaruhi kelelahan penerbang sipil pada penerbangan jarak
dekat di Indonesia.
Metode: Desain penelitian potong lintang dengan purposive sampling dilakukan
di antara penerbang jarak dekat dengan rating Boeing 737 series yang
melaksanakan pengujian kesehatan di Balai Kesehatan Penerbangan selama
periode 5-26 Mei 2014. Kelelahan diukur dengan Self-Reporting Questionnaire,
Fatigue Severity Scale (FSS). Data dikumpulkan dengan pengisian kuesioner oleh
subyek, meliputi demografi, pekerjaan, kehilangan waktu tidur (Epworth
Sleepiness Scale - ESS), faktor personal, dukungan manajemen, dan FSS. Analisis
regresi linear dipakai untuk menganalisis faktor-faktor berkaitan kelelahan.
Hasil: Di antara 785 penerbang yang melaksanakan pengujian kesehatan, 382
bersedia berpartisipasi, dan 239 subyek memiliki rating Boeing 737 series. Ratarata
skala kelelahan adalah 4,66 (standar deviasi 1,202). Faktor-faktor dominan
yang mempertinggi skala kelelahan adalah jumlah sektor 24 jam terakhir, jam
terbang penugasan di luar jadwal, dan kehilangan waku tidur. Setiap penambahan
1 sektor dalam 24 jam terakhir meningkatkan 0,371 skala kelelahan [koefisien
regresi (β) = 0,371; P = 0,000]. Selanjutnya setiap penambahan 1 jam terbang
penugasan di luar jadwal memepertinggi 0,033 skala kelelahan (β = 0,033; P =
0,000). Sedangkan setiap penambahan 1 nilai ESS mempertinggi 0,043 skala
kelelahan (β = 0,043; P = 0,008).
Simpulan: Jumlah sektor 24 jam terakhir, kehilangan waktu tidur, dan jam
terbang penugasan di luar jadwal mempertinggi risiko kelelahan di antara
penerbang sipil pada penerbangan jarak dekat di Indonesia.;Background: Fatigue could impair pilots’ cognitive function which may lead to
accidents in short-haul flight. The aims of this study were to investigate the risk
factors of short-haul commercial pilots fatigue in Indonesia
Methods: Cross-sectional study with purposive sampling was directed to Boeing
737 series typed-rating pilots who were taking medical examination at the Civil
Aviation Medical Center, Jakarta from May 5-26th 2014. Fatigue was measured
with Self-Reporting Questionnaire, Fatigue Severity Scale (FSS). Data were
collected by completing an anonymous questionnaire on demographics, workload,
sleep restriction (Epworth Sleepiness Scale-ESS), personal factors, and
managerial support. Risk factors and fatigue were analyzed using linear
regression.
Results: During data collection, 785 pilots were taking medical examination, 382
pilots were willing to participate and 239 Boeing 737 series typed-rating pilots
were chosen as subjects. Mean of FSS was 4.66 ± 1.202. Dominant factors of
fatigue were number of sectors in 24 consecutive hours, flight times of unplanned
flights in 30 consecutive days, and sleep restriction. Each additional sector
correlated 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 a
0,043 on the FSS (β = 0,043; p = 0,008), while each additional flight times of
unplanned 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 of
unplanned flights in 30 consecutive days, and sleep restriction correlated
significantly to higher FSS., Background: Fatigue could impair pilots’ cognitive function which may lead to
accidents in short-haul flight. The aims of this study were to investigate the risk
factors of short-haul commercial pilots fatigue in Indonesia
Methods: Cross-sectional study with purposive sampling was directed to Boeing
737 series typed-rating pilots who were taking medical examination at the Civil
Aviation Medical Center, Jakarta from May 5-26th 2014. Fatigue was measured
with Self-Reporting Questionnaire, Fatigue Severity Scale (FSS). Data were
collected by completing an anonymous questionnaire on demographics, workload,
sleep restriction (Epworth Sleepiness Scale-ESS), personal factors, and
managerial support. Risk factors and fatigue were analyzed using linear
regression.
Results: During data collection, 785 pilots were taking medical examination, 382
pilots were willing to participate and 239 Boeing 737 series typed-rating pilots
were chosen as subjects. Mean of FSS was 4.66 ± 1.202. Dominant factors of
fatigue were number of sectors in 24 consecutive hours, flight times of unplanned
flights in 30 consecutive days, and sleep restriction. Each additional sector
correlated 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 a
0,043 on the FSS (β = 0,043; p = 0,008), while each additional flight times of
unplanned 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 of
unplanned flights in 30 consecutive days, and sleep restriction correlated
significantly to higher FSS.]
SP=Inne Yuliawati.pdf :: Unduh