ArticleEuropean psychiatry : the journal of the Association of European Psychiatrists2024
Understanding symptom profiles of depression with the PHQ-9 in a community sample using network analysis.
Article in European psychiatry : the journal of the Association of European Psychiatrists, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Depressive Symptom Patterns and Digital Screen Exposure Among Adults in Qatar: A Cross-Sectional Study With Implications for Psychiatric and Mental Health Nursing Practice.Journal of psychiatric and mental health nursing · 2026Article
- Childhood experience profiles and their impact on depression-burnout networks among nurses: a latent class and network analysis.BMC nursing · 2025Article
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4 authors.
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Abstract
backgroundDepression is one of the most prevalent mental health conditions in the world. However, the heterogeneity of depression has presented obstacles for research concerning disease mechanisms, treatment indication, and personalization. The current study used network analysis to analyze and compare profiles of depressive symptoms present in community samples, considering the relationship between symptoms.
methodsCross-sectional measures of depression using the Patient Health Questionnaire - 9 items (PHQ-9) were collected from community samples using data from participants scoring above a clinical threshold of ≥10 points (N = 2,023; 73.9% female; mean age 49.87, SD = 17.40). Data analysis followed three steps. First, a profiling algorithm was implemented to identify all possible symptom profiles by dichotomizing each PHQ-9 item. Second, the most prevalent symptom profiles were identified in the sample. Third, network analysis for the most prevalent symptom profiles was carried out to identify the centrality and covariance of symptoms.
resultsOf 382 theoretically possible depression profiles, only 167 were present in the sample. Furthermore, 55.6% of the symptom profiles present in the sample were represented by only eight profiles. Network analysis showed that the network and symptoms' relationship varied across the profiles.
conclusionsFindings indicate that the vast number of theoretical possible ways to meet the criteria for major depressive disorder (MDD) is significantly reduced in empirical samples and that the most common profiles of symptoms have different networks and connectivity patterns. Scientific and clinical consequences of these findings are discussed in the context of the limitations of this study.
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