Network analysis of depressive symptoms, cognitive functioning, and life satisfaction among healthcare workers
BackgroundDepression and cognitive impairment among healthcare workers significantly affect their life satisfaction (LS). This study used network analysis to explore the associations between depression, cognitive symptoms, and LS in healthcare workers.MethodsA total of 655 healthcare workers were as...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Psychiatry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1586086/full |
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| Summary: | BackgroundDepression and cognitive impairment among healthcare workers significantly affect their life satisfaction (LS). This study used network analysis to explore the associations between depression, cognitive symptoms, and LS in healthcare workers.MethodsA total of 655 healthcare workers were assessed using the Patient Health Questionnaire (PHQ-9), the Perceived Deficits Questionnaire-Depression (PDQ-D), and the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF). Regularized partial correlation network analysis was conducted, focusing on the strength values and predictability of each item in the network. The R software was used for statistical analysis and visualization of the network.ResultsThe average PHQ-9 depression score was 4.79, while the mean cognitive symptoms score was 15.38 (Our score range for all participants: PDQ-D 0 - 70; PHQ-9 0 - 27). Network analysis revealed that PDQ12 (“Trouble getting started”), PDQ13 (“Drifting”), and PDQ17 (“Remembering numbers”) were the central symptoms of the entire depression-cognition network. PHQ1 (“Anhedonia”), PHQ7 (“Concentration”), and PDQ 13 (“Drifting”) were the most critical bridge symptoms connecting depression and cognition. The three symptoms of PHQ2 (“Sad Mood”), PHQ4 (“Fatigue”), and PDQ 13 (“Drifting”) had the strongest negative correlations with LS. Gender showed no significant relationship with global network strength, edge weight distribution, or individual edge weights.ConclusionThis network analysis identified several central symptoms, including “Trouble getting started”, “Drifting”, and “Remembering numbers”. It also identified bridge symptoms such as “Anhedonia”, “Concentration”, and “Drifting”. These findings provide important evidence for the development of targeted interventions. Furthermore, measures such as improving emotional management, increasing rest periods, and providing psychological support may help alleviate fatigue and low mood, enhance attentional functioning, and ultimately improve life satisfaction among healthcare workers. |
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| ISSN: | 1664-0640 |