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
Year: 2023
Type: article
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 14-16, 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 (p > 0.05). 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, 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.
Source: JAACAP Open
Authors: Jader Piccin, Anna Viduani, Claudia Buchweitz, Rivka B. Pereira, Aline Zimerman, Guilherme R. Amando, Victor Cosenza, Leonardo Z. Ferreira, Natália A.G. McMahon, Ramásio F. Melo, Danyella Richter, Frederico D.S. Reckziegel, Fernanda Rohrsetzer, Laila Souza, André C. Tonon, Marina Tuerlinckx Costa-Valle, Zuzanna Zajkowska, Ricardo Matsumura Araújo, Tobias U. Hauser, Alastair van Heerden, Maria Paz Hidalgo, Brandon A. Kohrt, Valeria Mondelli, Johnna R. Swartz, Helen L. Fisher, Christian Kieling
Institutions: Universidade Federal do Rio Grande do Sul, Hospital de Clínicas de Porto Alegre, Universidade Federal de Pelotas, King's College London, Wellcome Centre for Human Neuroimaging, University College London, University of Tübingen, Human Sciences Research Council, South African Medical Research Council, University of the Witwatersrand, George Washington University, South London and Maudsley NHS Foundation Trust, National Institute for Health and Care Research, University of California, Davis
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,600
Funders: Wellcome Trust, MQ: Transforming Mental Health, National Institute for Health and Care Research, Royal Academy of Engineering, Academy of Medical Sciences, King's College London, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul, National Institutes of Health, NIHR Maudsley Biomedical Research Centre, Medical Research Council, Economic and Social Research Council, National Institute of Mental Health
Awards: G1233865316, G1590373245, Brazilian-American Initiative on Neuroimaging for Identifying Depression Early in Adolescence (BRAIN-IDEA), G429285467, G4694713930, G508911896, G5375860973, G579898549, G5921580337, G6242089139, G6671708061, G7418193128, Centre for Society and Mental Health, G771299261
OpenAlex ID: W4389704613