What retrospective and dynamic assessments tell us about youth depression: A network analysis perspective.

Clinical Snapshot

Key Findings

• P Value: Not reported

• Effect Size: Not quantified - qualitative network structure differences reported

• Primary Outcome: Both assessment methods identified three symptom communities with different structural compositions

• Nnt Or Sensitivity: Network stability and replicability measures not provided

• Confidence Interval: Not reported

Clinical Application

Requires smartphone technology and participant engagement over 14 days; may be challenging in routine clinical practice Relevant to Australian youth mental health services; aligns with digital health initiatives but requires validation in local populations before implementation Adolescents and young adults undergoing depression assessment, particularly in research settings

Abstract

PURPOSE: Traditional assessments of depressive symptoms often rely on retrospective self-reports, which may be affected by cognitive and memory biases. Few studies have compared retrospective and dynamic (real-time) assessments to examine the consistency and structure of depressive symptom reporting. This study aimed to compare retrospective and dynamic assessments of depressive symptoms in youth using network analysis to explore symptom-level associations and clustering. METHODS: Ninety Brazilian adolescents and young adults (mean age = 18 years), with and without depression, completed the Short Mood and Feelings Questionnaire (SMFQ) every other day for 14 days via a smartphone-based chatbot (dynamic assessment). At the end of the 2-week period, they completed the same questionnaire retrospectively. Network analyses were conducted using Exploratory Graph Analysis (EGA) and Dynamic Exploratory Analysis (DEA) to identify symptom communities and compare network structures across both assessment methods. RESULTS: Both retrospective and dynamic assessments revealed three symptom communities; however, the composition and structure of these communities differed. Retrospective assessments showed stronger connections among cognitive symptoms, while dynamic assessments displayed a more balanced distribution, with stronger associations between somatic and affective symptoms. IMPLICATIONS: Findings highlight significant differences in depressive symptom networks between retrospective and dynamic assessments. Dynamic methods may offer less biased and more ecologically valid insights into youth depression, underscoring the importance of real-time data collection in clinical assessment and research.

References

1. 1.Pereira, R. B., Manfro, P. H., Viduani, A., Cosenza, V., Buchweitz, C., Piccin, J., Araujo, R. M., Kohrt, B. A., Mondelli, V., Swartz, J. R., Fisher, H. L., van Heerden, A., Golino, H., & Kieling, C. (2026). What retrospective and dynamic assessments tell us about youth depression: A network analysis perspective. Journal of Affective Disorders, 121099. https://doi.org/10.1016/j.jad.2025.121099