Prospective Follow-Up of Adolescents With and at Risk for Depression: Protocol and Methods of the Identifying Depression Early in Adolescence Risk Stratified Cohort Longitudinal Assessments

Authors

Jader Piccin, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Anna Viduani, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Claudia Buchweitz, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Rivka B. Pereira, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Aline Zimerman, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Guilherme R. Amando, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Victor Cosenza, Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Leonardo Z. Ferreira, Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Natália A. McMahon, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Ramásio F. Melo, Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Danyella Richter, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Frederico D. Reckziegel, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Fernanda Rohrsetzer, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Laila Souza, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
André C. Tonon, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Marina Tuerlinckx Costa-Valle, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Zuzanna Zajkowska, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.
Ricardo Matsumura Araújo, Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Tobias U. Hauser, Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom, Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom and with Eberhard Karls University of Tübingen, Tübingen, Germany.
Alastair van Heerden, Human and Social Development, Human Sciences Research Council, Pietermaritzburg, South Africa and Medical Research Council/Wits Developmental Pathways for Health Research Unit, University of the Witwatersrand, Johannesburg, South Africa.
Maria Paz Hidalgo, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Brandon A. Kohrt, The George Washington University, Washington, DC, United States.
Valeria Mondelli, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.
Johnna R. Swartz, University of California, Davis, Davis, CA, United States.
Helen L. Fisher, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.
Christian Kieling, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.

Document Type

Journal Article

Publication Date

6-1-2024

Journal

JAACAP open

Volume

2

Issue

2

DOI

10.1016/j.jaacop.2023.11.002

Keywords

adolescence; cohort; depression; digital phenotyping; risk score

Abstract

OBJECTIVE: To present the protocol and methods for the prospective longitudinal assessments-including clinical and digital phenotyping approaches-of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo) study, which comprises Brazilian adolescents stratified at baseline by risk of developing depression or presence of depression. METHOD: Of 7,720 screened adolescents aged 14 to 16 years, we recruited 150 participants (75 boys, 75 girls) based on a composite risk score: 50 with low risk for developing depression (LR), 50 with high risk for developing depression (HR), and 50 with an active untreated major depressive episode (MDD). Three annual follow-up assessments were conducted, involving clinical measures (parent- and adolescent-reported questionnaires and psychiatrist assessments), active and passive data sensing via smartphones, and neurobiological measures (neuroimaging and biological material samples). Retention rates were 96% (Wave 1), 94% (Wave 2), and 88% (Wave 3), with no significant differences by sex or group ( > .05). Participants highlighted their familiarity with the research team and assessment process as a motivator for sustained engagement. DISCUSSION: This protocol relied on novel aspects, such as the use of a WhatsApp bot, which is particularly pertinent for low- to-middle-income countries, and the collection of information from diverse sources in a longitudinal design, encompassing clinical data, self-reports, parental reports, Global Positioning System (GPS) data, and ecological momentary assessments. The study engaged adolescents over an extensive period and demonstrated the feasibility of conducting a prospective follow-up study with a risk-enriched cohort of adolescents in a middle-income country, integrating mobile technology with traditional methodologies to enhance longitudinal data collection.

APA Citation

Piccin, Jader; Viduani, Anna; Buchweitz, Claudia; Pereira, Rivka B.; Zimerman, Aline; Amando, Guilherme R.; Cosenza, Victor; Ferreira, Leonardo Z.; McMahon, Natália A.; Melo, Ramásio F.; Richter, Danyella; Reckziegel, Frederico D.; Rohrsetzer, Fernanda; Souza, Laila; Tonon, André C.; Costa-Valle, Marina Tuerlinckx; Zajkowska, Zuzanna; Araújo, Ricardo Matsumura; Hauser, Tobias U.; van Heerden, Alastair; Hidalgo, Maria Paz; Kohrt, Brandon A.; Mondelli, Valeria; Swartz, Johnna R.; Fisher, Helen L.; and Kieling, Christian, "Prospective Follow-Up of Adolescents With and at Risk for Depression: Protocol and Methods of the Identifying Depression Early in Adolescence Risk Stratified Cohort Longitudinal Assessments" (2024). GW Authored Works. Paper 5175.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/5175

Department

Psychiatry and Behavioral Sciences