{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T14:05:50Z","timestamp":1787580350963,"version":"build-2736575974"},"reference-count":119,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T00:00:00Z","timestamp":1719964800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Research on the mental health and quality of life (hereafter QOL) among fire service recruits after the end of the COVID-19 restrictions is lacking. This study explored the network structure of depression, anxiety and insomnia, and their interconnections with QOL among fire service recruits in the post-COVID-19 era.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This cross-sectional study used a consecutive sampling of fire service recruits across China. We measured the severity of depression, anxiety and insomnia symptoms, and overall QOL using the nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder scale (GAD-7), Insomnia Severity Index (ISI) questionnaire, and World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. We estimated the most central symptoms using the centrality index of expected influence (EI), and the symptoms connecting depression, anxiety and insomnia symptoms using bridge EI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In total, 1,560 fire service recruits participated in the study. The prevalence of depression (PHQ-9\u2009\u2265\u20095) was 15.2% (95% CI: 13.5\u201317.1%), while the prevalence of anxiety (GAD-7\u2009\u2265\u20095) was 11.2% (95% CI: 9.6\u201312.8%). GAD4 (\u201cTrouble relaxing\u201d) had the highest EI in the whole network model, followed by ISI5 (\u201cInterference with daytime functioning\u201d) and GAD6 (\u201cIrritability\u201d). In contrast, PHQ4 (\u201cFatigue\u201d) had the highest bridge EI values in the network, followed by GAD4 (\u201cTrouble relaxing\u201d) and ISI5 (\u201cInterference with daytime functioning\u201d). Additionally, ISI4 \u201cSleep dissatisfaction\u201d (average edge weight\u2009=\u2009\u22121.335), which was the central symptom with the highest intensity value, had the strongest negative correlation with QOL.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Depression and anxiety were important mental health issues to address among fire service recruits in the post-COVID-19 era in China. Targeting central and bridge symptoms identified in network analysis could help address depression and anxiety among fire service recruits in the post-COVID-19 era.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2024.1348870","type":"journal-article","created":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T05:16:45Z","timestamp":1719983805000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["A network analysis of the interrelationships between depression, anxiety, insomnia and quality of life among fire service 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