Prevalence and network analysis of internet addiction, depression and their associations with sleep quality among commercial airline pilots : A national survey in China
Copyright © 2024 Elsevier B.V. All rights reserved..
OBJECTIVE: Airline pilots are members of a unique occupational group that is often confronted with sleep routine disruptions, yet relatively few studies have examined their mental health status. This study assessed the prevalence and network structure of internet addiction, depression and sleep quality problems in commercial airline pilots.
METHOD: A total of 7055 airline pilots were included in analyses. Internet addiction and depression were measured with the Internet Addiction Test (IAT) and 9-item Patient Health Questionnaire (PHQ-9), respectively. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). The network model was constructed based on an Ising model and its association with sleep quality was evaluated using a flow procedure.
RESULTS: Internet addiction, depression and sleep quality were common among airline pilots. The prevalence of internet addiction was 8.0 % (95 % CI: 7.3-8.6 %), while the rates of depression and poor sleep quality were 23.3 % (95 % CI: 22.3-24.2 %) and 33.0 % (95 % CI: 31.9-34.1 %), respectively. In the depression and internet addiction network model, "Fatigue" (PHQ4; Expected Influence (EI): 2.04) and "Depressed/moody/nervous only while being offline" (IAT20; EI: 1.76) were most central symptoms while "Fatigue" (PHQ4; Bridge EI: 1.30) was also the most important bridge symptom. The flow network model of sleep quality with internet addiction and depression showed that "Appetite" (PHQ5) had the strongest positive association with poor sleep quality.
CONCLUSION: Internet addiction, depression and sleep quality were common among airline pilots and warrant regular screening and timely treatment. Strategies to improve sleep hygiene may be useful in preventing onsets or exacerbations in depression and internet addiction among airline pilots.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:356 |
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| Enthalten in: |
Journal of affective disorders - 356(2024) vom: 12. März, Seite 597-603 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sun, He-Li [VerfasserIn] |
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| Links: |
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| Themen: |
Airline pilots |
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| Anmerkungen: |
Date Revised 25.04.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1016/j.jad.2024.03.022 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM369745744 |
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| 100 | 1 | |a Sun, He-Li |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Prevalence and network analysis of internet addiction, depression and their associations with sleep quality among commercial airline pilots |b A national survey in China |
| 264 | 1 | |c 2024 | |
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| 500 | |a published: Print-Electronic | ||
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| 520 | |a Copyright © 2024 Elsevier B.V. All rights reserved. | ||
| 520 | |a OBJECTIVE: Airline pilots are members of a unique occupational group that is often confronted with sleep routine disruptions, yet relatively few studies have examined their mental health status. This study assessed the prevalence and network structure of internet addiction, depression and sleep quality problems in commercial airline pilots | ||
| 520 | |a METHOD: A total of 7055 airline pilots were included in analyses. Internet addiction and depression were measured with the Internet Addiction Test (IAT) and 9-item Patient Health Questionnaire (PHQ-9), respectively. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). The network model was constructed based on an Ising model and its association with sleep quality was evaluated using a flow procedure | ||
| 520 | |a RESULTS: Internet addiction, depression and sleep quality were common among airline pilots. The prevalence of internet addiction was 8.0 % (95 % CI: 7.3-8.6 %), while the rates of depression and poor sleep quality were 23.3 % (95 % CI: 22.3-24.2 %) and 33.0 % (95 % CI: 31.9-34.1 %), respectively. In the depression and internet addiction network model, "Fatigue" (PHQ4; Expected Influence (EI): 2.04) and "Depressed/moody/nervous only while being offline" (IAT20; EI: 1.76) were most central symptoms while "Fatigue" (PHQ4; Bridge EI: 1.30) was also the most important bridge symptom. The flow network model of sleep quality with internet addiction and depression showed that "Appetite" (PHQ5) had the strongest positive association with poor sleep quality | ||
| 520 | |a CONCLUSION: Internet addiction, depression and sleep quality were common among airline pilots and warrant regular screening and timely treatment. Strategies to improve sleep hygiene may be useful in preventing onsets or exacerbations in depression and internet addiction among airline pilots | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Airline pilots | |
| 650 | 4 | |a Depression | |
| 650 | 4 | |a Internet addiction | |
| 650 | 4 | |a Network analysis | |
| 650 | 4 | |a Sleep quality | |
| 700 | 1 | |a Chen, Pan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Qinge |e verfasserin |4 aut | |
| 700 | 1 | |a Si, Tong Leong |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Yan-Zhang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhu, Han-Yu |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Erliang |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Minzhi |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Jie |e verfasserin |4 aut | |
| 700 | 1 | |a Su, Zhaohui |e verfasserin |4 aut | |
| 700 | 1 | |a Cheung, Teris |e verfasserin |4 aut | |
| 700 | 1 | |a Ungvari, Gabor S |e verfasserin |4 aut | |
| 700 | 1 | |a Jackson, Todd |e verfasserin |4 aut | |
| 700 | 1 | |a Xiang, Yu-Tao |e verfasserin |4 aut | |
| 700 | 1 | |a Xiang, Mi |e verfasserin |4 aut | |
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