Vital-affective symptom connectivity during electroconvulsive therapy distinguishes depression remission outcomes: A cross-lagged panel network study
Abstract
BACKGROUND: Electroconvulsive therapy (ECT) is effective for depression, but symptom dynamics during treatment remain unclear. Network approaches may clarify symptom relations and identify patterns linked to remission. OBJECTIVE: Examining symptom dynamics during ECT using temporal network modeling and comparing baseline and temporal symptom networks between remitters and non-remitters. METHODS: Using the Dutch ECT Consortium (N = 857, unipolar/bipolar depression), we examined seven harmonized symptoms from the 17-item Hamilton Depression Rating Scale (HDRS-17) and Montgomery-Åsberg Depression Rating Scale (MADRS) over the first five weeks of treatment. We estimated baseline networks using partial correlations and temporal networks using Cross-Lagged Panel Network analysis, which quantified each symptom's in-prediction and out-prediction. Between remitters (N = 413) and non-remitters (N = 379), baseline networks were compared using the Network Comparison Test, while temporal networks were compared via network density, Jaccard overlap, and edge correlations. RESULTS: = 8.20, p < 0.01), with low overlap in edges (Jaccard = 0.25), and non-significant edge-weight correlations (r = 0.16; p = 0.46) between groups. Remitters displayed integrated affective-vital symptom connections, while non-remitters showed fragmented subnetworks. CONCLUSIONS: Reductions in suicidal thoughts preceded broader symptom improvements, suggesting this symptom warrants monitoring. Remitters showed coordinated symptom reduction where affective and vital symptoms reinforced each other, while non-remitters showed independent reduction. These findings provide insights into symptom dynamics during ECT.
Fields of Study & Subjects
Mental Health Research Topics
Treatment of Major Depression
Electroconvulsive Therapy Studies
Publication details
- Journal / source
- Brain stimulation
- Publisher
- Elsevier BV
- Volume
- 19
- Issue
- 2
- Pages
- 103058–103058
- Publication date
- 17 February 2026
- Language
- EN