From Symptoms to Structures: A Systematic Review and Meta-Analysis of Major Depressive Symptom Networks

Major depressive disorder (MDD) is a leading condition examined using network analysis. However, meta-analytic evidence is limited for MDD symptom network studies. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines, we searched Embase, MEDLINE, PsycINFO, CINAHL and bibliographies of previous literature for articles that have produced MDD symptom networks. After screening, 104 articles (N = 875,852) were included in this review, consisting of 85 cross-sectional and 19 temporal network analysis studies. A random-effects Meta-analytic Gaussian Network Aggregation (MAGNA) of MDD symptom networks was estimated based on available data. Despite a pronounced variation in MDD measures and sample demographics, findings consistently showed that depressed mood and fatigue emerged as the most central symptoms. Collectively, this systematic review and meta-analysis underscores network analysis as a technique for understanding MDD symptom dynamics and one that has the potential to improve psychological interventions. Ongoing efforts toward intensive longitudinal datasets and improved reporting practices represent two key avenues for MDD network analysis research.