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

Rivka Barros Pereira, Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Prodia, Child & Adolescent Depression Program, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
Pedro H. Manfro, Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Department of Psychiatry, Universidade do Vale do Rio dos Sinos (UNISINOS), Porto Alegre, Brazil.
Anna Viduani, Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Prodia, Child & Adolescent Depression Program, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
Victor Cosenza, Center for Technological Advancement Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Claudia Buchweitz, Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Prodia, Child & Adolescent Depression Program, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
Jader Piccin, Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Prodia, Child & Adolescent Depression Program, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
Ricardo Matsumura Araujo, Center for Technological Advancement Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Brandon A. Kohrt, Division of Global Mental Health, Department of Psychiatry, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States.
Valeria Mondelli, Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; National Institute for Health and Care Research Maudsley Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.
Johnna R. Swartz, Department of Human Ecology, University of California, Davis, Davis, CA, United States.
Helen L. Fisher, Social, Genetic & Developmental Psychiatry Centre, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; ESRC Centre for Society and Mental Health, King's College London, London, United Kingdom.
Alastair van Heerden, Center for Community Based Research, Human Sciences Research Council, Pietermaritzburg, South Africa; Medical Research Council/Wits Developmental Pathways for Health Research Unit, University of the Witwatersrand, Johannesburg, South Africa.
Hudson Golino, Department of Psychology, University of Virginia, United States.
Christian Kieling, Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Prodia, Child & Adolescent Depression Program, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; Instituto de Pesquisa, Hospital Moinhos de Vento, Porto Alegre, RS, Brazil. Electronic address: christian.kieling@hmv.org.br.

Document Type

Journal Article

Publication Date

4-15-2026

Journal

Journal of affective disorders

Volume

399

DOI

10.1016/j.jad.2025.121099

Keywords

Adolescent; Depression; Network analysis; Psychometrics

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.

Department

Psychiatry and Behavioral Sciences

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