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Citation
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Tao Y, Hou W, Niu H, Ma Z, Zheng Z, Wang S, Liu X, Zhang L. J. Affect. Disord. 2022; ePub(ePub): ePub. |
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Abstract
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INTRODUCTION: Recently, in the view of network analysis, depression has been conceptualized as a complex and dynamic network model combining individual symptoms. To date, no studies have systematically examined and compared depressive symptom networks across different populations.
METHODS: A total of 36,105 participants were recruited and asked to complete the Patient Health Questionnaire-9 among junior high school students, senior high school students, college students, and elderly adults who were more susceptible to depression during the COVID-19 lockdown in China. In the analysis, we applied the optimal cutoff score ≥ 8 for students and a score ≥ 6 for elderly adults to identify 5830 participants who were likely to be depressed. The index of "strength" was used to identify central symptoms in the network structure.
RESULTS: The results showed that Sad Mood was the most central symptom among junior high school students, senior high school students, and college students, but the most central symptom in the elderly was Guilt. Among the top three central symptoms, Suicide Ideation was unique to senior high school students, while Anhedonia was most prevalent among college students. Guilt - Suicide Ideation, Anhedonia - Energy, Anhedonia - Sad Mood, and Sleep - Energy showed the strongest association among junior and senior high school students, college students, and elderly adults, respectively. NCT (i.e., Network Comparison Test) suggested that the network's global connectivity was ultimately inconsistent, but the network structure remained roughly intact.
CONCLUSION: In treatment, targeting central symptoms may be critical to alleviating depression.
Language: en |