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
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...
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creator | Piccin, Jader Viduani, Anna Buchweitz, Claudia Pereira, Rivka B. Zimerman, Aline Amando, Guilherme R. Cosenza, Victor Ferreira, Leonardo Z. McMahon, Natália A.G. Melo, Ramásio F. Richter, Danyella Reckziegel, Frederico D.S. 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. Kieling, Christian |
description | 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.
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 (p > .05). Participants highlighted their familiarity with the research team and assessment process as a motivator for sustained engagement.
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.
This article details the study protocol and methods used in the longitudinal assessment of 150 Brazilian teenagers with depression and at risk for depression as part of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo). Over 3 years, the authors collected clinical and digital data using innovative mobile technology, including a WhatsApp bot. Most adolescents participated in all the study phases, showing feasibility of prospective follow-up in a middle-income country. This approach allowed for a deeper understanding of depression in young populations, particularly in areas where mental health research is sca |
doi_str_mv | 10.1016/j.jaacop.2023.11.002 |
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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 (p > .05). Participants highlighted their familiarity with the research team and assessment process as a motivator for sustained engagement.
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.
This article details the study protocol and methods used in the longitudinal assessment of 150 Brazilian teenagers with depression and at risk for depression as part of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo). Over 3 years, the authors collected clinical and digital data using innovative mobile technology, including a WhatsApp bot. Most adolescents participated in all the study phases, showing feasibility of prospective follow-up in a middle-income country. This approach allowed for a deeper understanding of depression in young populations, particularly in areas where mental health research is scarce.</description><identifier>ISSN: 2949-7329</identifier><identifier>EISSN: 2949-7329</identifier><identifier>DOI: 10.1016/j.jaacop.2023.11.002</identifier><identifier>PMID: 38863682</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>adolescence ; cohort ; depression ; digital phenotyping ; risk score ; Study Protocol and Methods Advancement</subject><ispartof>JAACAP open, 2024-06, Vol.2 (2), p.145-159</ispartof><rights>2023 The Authors</rights><rights>2023 The Authors.</rights><rights>2023 The Authors 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3092-f1886342db7228b249f875ea09cbfeac8bc75b4c78b7691361cf371ff28fcac23</citedby><cites>FETCH-LOGICAL-c3092-f1886342db7228b249f875ea09cbfeac8bc75b4c78b7691361cf371ff28fcac23</cites><orcidid>0000-0002-7347-0527 ; 0000-0002-3829-4820 ; 0000-0002-3260-8948 ; 0000-0003-0514-8883 ; 0000-0001-7691-4149 ; 0000-0002-5214-305X ; 0000-0003-2530-6885 ; 0000-0002-4332-6938 ; 0000-0002-7997-8137 ; 0000-0002-6171-917X ; 0000-0002-6289-6397 ; 0000-0002-3670-198X ; 0000-0001-8690-6839 ; 0000-0001-7843-9345 ; 0000-0002-6213-9724 ; 0000-0003-4818-3144 ; 0000-0001-6981-0835 ; 0000-0003-4191-6966 ; 0000-0001-9847-3460 ; 0000-0003-2718-5829 ; 0000-0003-4174-2126</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11163476/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11163476/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,865,886,27929,27930,53796,53798</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38863682$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Piccin, Jader</creatorcontrib><creatorcontrib>Viduani, Anna</creatorcontrib><creatorcontrib>Buchweitz, Claudia</creatorcontrib><creatorcontrib>Pereira, Rivka B.</creatorcontrib><creatorcontrib>Zimerman, Aline</creatorcontrib><creatorcontrib>Amando, Guilherme R.</creatorcontrib><creatorcontrib>Cosenza, Victor</creatorcontrib><creatorcontrib>Ferreira, Leonardo Z.</creatorcontrib><creatorcontrib>McMahon, Natália A.G.</creatorcontrib><creatorcontrib>Melo, Ramásio F.</creatorcontrib><creatorcontrib>Richter, Danyella</creatorcontrib><creatorcontrib>Reckziegel, Frederico D.S.</creatorcontrib><creatorcontrib>Rohrsetzer, Fernanda</creatorcontrib><creatorcontrib>Souza, Laila</creatorcontrib><creatorcontrib>Tonon, André C.</creatorcontrib><creatorcontrib>Costa-Valle, Marina Tuerlinckx</creatorcontrib><creatorcontrib>Zajkowska, Zuzanna</creatorcontrib><creatorcontrib>Araújo, Ricardo Matsumura</creatorcontrib><creatorcontrib>Hauser, Tobias U.</creatorcontrib><creatorcontrib>van Heerden, Alastair</creatorcontrib><creatorcontrib>Hidalgo, Maria Paz</creatorcontrib><creatorcontrib>Kohrt, Brandon A.</creatorcontrib><creatorcontrib>Mondelli, Valeria</creatorcontrib><creatorcontrib>Swartz, Johnna R.</creatorcontrib><creatorcontrib>Fisher, Helen L.</creatorcontrib><creatorcontrib>Kieling, Christian</creatorcontrib><title>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</title><title>JAACAP open</title><addtitle>JAACAP Open</addtitle><description>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.
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 (p > .05). Participants highlighted their familiarity with the research team and assessment process as a motivator for sustained engagement.
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.
This article details the study protocol and methods used in the longitudinal assessment of 150 Brazilian teenagers with depression and at risk for depression as part of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo). Over 3 years, the authors collected clinical and digital data using innovative mobile technology, including a WhatsApp bot. Most adolescents participated in all the study phases, showing feasibility of prospective follow-up in a middle-income country. 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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 (p > .05). Participants highlighted their familiarity with the research team and assessment process as a motivator for sustained engagement.
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.
This article details the study protocol and methods used in the longitudinal assessment of 150 Brazilian teenagers with depression and at risk for depression as part of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo). Over 3 years, the authors collected clinical and digital data using innovative mobile technology, including a WhatsApp bot. Most adolescents participated in all the study phases, showing feasibility of prospective follow-up in a middle-income country. This approach allowed for a deeper understanding of depression in young populations, particularly in areas where mental health research is scarce.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>38863682</pmid><doi>10.1016/j.jaacop.2023.11.002</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-7347-0527</orcidid><orcidid>https://orcid.org/0000-0002-3829-4820</orcidid><orcidid>https://orcid.org/0000-0002-3260-8948</orcidid><orcidid>https://orcid.org/0000-0003-0514-8883</orcidid><orcidid>https://orcid.org/0000-0001-7691-4149</orcidid><orcidid>https://orcid.org/0000-0002-5214-305X</orcidid><orcidid>https://orcid.org/0000-0003-2530-6885</orcidid><orcidid>https://orcid.org/0000-0002-4332-6938</orcidid><orcidid>https://orcid.org/0000-0002-7997-8137</orcidid><orcidid>https://orcid.org/0000-0002-6171-917X</orcidid><orcidid>https://orcid.org/0000-0002-6289-6397</orcidid><orcidid>https://orcid.org/0000-0002-3670-198X</orcidid><orcidid>https://orcid.org/0000-0001-8690-6839</orcidid><orcidid>https://orcid.org/0000-0001-7843-9345</orcidid><orcidid>https://orcid.org/0000-0002-6213-9724</orcidid><orcidid>https://orcid.org/0000-0003-4818-3144</orcidid><orcidid>https://orcid.org/0000-0001-6981-0835</orcidid><orcidid>https://orcid.org/0000-0003-4191-6966</orcidid><orcidid>https://orcid.org/0000-0001-9847-3460</orcidid><orcidid>https://orcid.org/0000-0003-2718-5829</orcidid><orcidid>https://orcid.org/0000-0003-4174-2126</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2949-7329 |
ispartof | JAACAP open, 2024-06, Vol.2 (2), p.145-159 |
issn | 2949-7329 2949-7329 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11163476 |
source | DOAJ Directory of Open Access Journals; PubMed Central; Alma/SFX Local Collection |
subjects | adolescence cohort depression digital phenotyping risk score Study Protocol and Methods Advancement |
title | 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 |
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