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Examining early-phase symptom trajectories in interpersonal psychotherapy versus antidepressant medication for adults with depression: A dynamic time warp network analysis.

Abstract

BACKGROUND: Depression is characterized by substantial symptom heterogeneity, which is often concealed when examining total severity scores. Analyzing symptom-level change can improve our understanding of treatment effects and recovery processes. This study, therefore, examined dynamic symptom networks during early-phase interpersonal psychotherapy (IPT) and selective serotonin reuptake inhibitor (SSRI) antidepressant treatment, assessing patterns of symptom change across as well as differences between treatments. METHODS: Using weekly item-level Hamilton Depression Rating Scale (HAM-D) data from a randomized clinical trial comparing IPT and SSRIs for adults with depression, this preregistered study examined symptom trajectories in the first six weeks of treatment with Dynamic Time Warping (DTW). RESULTS: Depressive symptom trajectories and DTW-based symptom networks were largely similar for IPT and SSRI. In both conditions, changes in somatic symptoms of anxiety and middle insomnia tended to precede improvements in depressed mood. CONCLUSIONS: Early symptom change may occur outside the core affective domain, underscoring the importance of monitoring symptoms broadly. Symptom-level patterns may reflect patients' stage of recovery and provide clinically relevant information beyond total severity scores. The absence of differences in improvement patterns between IPT and SSRI suggest few indications for treatment selection based on baseline symptom profiles. Future research should replicate and extend these findings to subsequent treatment phases using more frequent assessments and a broader range of interventions.

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BibTeXRIS

Anika Noort, Wessel A van Eeden, Paola Rucci, Carolina Corda, Erik J Giltay, Ellen Driessen. 2026-07-16. Examining early-phase symptom trajectories in interpersonal psychotherapy versus antidepressant medication for adults with depression: A dynamic time warp network analysis.. https://doi.org/10.1016/j.jad.2026.122279

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