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.

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 (p > .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.

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.

Assessing Mood With the Identifying Depression Early in Adolescence Chatbot (IDEABot): Development and Implementation Study.

BACKGROUND: Mental health status assessment is mostly limited to clinical or research settings, but recent technological advances provide new opportunities for measurement using more ecological approaches. Leveraging apps already in use by individuals on their smartphones, such as chatbots, could be a useful approach to capture subjective reports of mood in the moment. OBJECTIVE: This study aimed to describe the development and implementation of the Identifying Depression Early in Adolescence Chatbot (IDEABot), a WhatsApp-based tool designed for collecting intensive longitudinal data on adolescents' mood. METHODS: The IDEABot was developed to collect data from Brazilian adolescents via WhatsApp as part of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo) study. It supports the administration and collection of self-reported structured items or questionnaires and audio responses. The development explored WhatsApp's default features, such as emojis and recorded audio messages, and focused on scripting relevant and acceptable conversations. The IDEABot supports 5 types of interactions: textual and audio questions, administration of a version of the Short Mood and Feelings Questionnaire, unprompted interactions, and a snooze function. Six adolescents (n=4, 67% male participants and n=2, 33% female participants) aged 16 to 18 years tested the initial version of the IDEABot and were engaged to codevelop the final version of the app. The IDEABot was subsequently used for data collection in the second- and third-year follow-ups of the IDEA-RiSCo study. RESULTS: The adolescents assessed the initial version of the IDEABot as enjoyable and made suggestions for improvements that were subsequently implemented. The IDEABot's final version follows a structured script with the choice of answer based on exact text matches throughout 15 days. The implementation of the IDEABot in 2 waves of the IDEA-RiSCo sample (140 and 132 eligible adolescents in the second- and third-year follow-ups, respectively) evidenced adequate engagement indicators, with good acceptance for using the tool (113/140, 80.7% and 122/132, 92.4% for second- and third-year follow-up use, respectively), low attrition (only 1/113, 0.9% and 1/122, 0.8%, respectively, failed to engage in the protocol after initial interaction), and high compliance in terms of the proportion of responses in relation to the total number of elicited prompts (12.8, SD 3.5; 91% out of 14 possible interactions and 10.57, SD 3.4; 76% out of 14 possible interactions, respectively). CONCLUSIONS: The IDEABot is a frugal app that leverages an existing app already in daily use by our target population. It follows a simple rule-based approach that can be easily tested and implemented in diverse settings and possibly diminishes the burden of intensive data collection for participants by repurposing WhatsApp. In this context, the IDEABot appears as an acceptable and potentially scalable tool for gathering momentary information that can enhance our understanding of mood fluctuations and development.

Sex-specific inflammatory markers of risk and presence of depression in adolescents.

BACKGROUND: Associations between inflammatory markers and depression are reported among adults; however, less is known in adolescent depression in particular whether these associations are sex-specific. We aimed to identify inflammatory markers of increased risk and presence of depression in adolescence and their association with severity of depressive symptoms in the entire cohort and separately in boys and girls. METHODS: We measured serum cytokines using a Meso Scale Discovery electrochemiluminescence V-PLEX assay in a cohort of 150 adolescents stratified for risk/presence of depression. Risk group and sex-specific differences in inflammatory markers were assessed with 2-way mixed ANOVA, and sex-moderated associations between inflammatory markers and the severity of depressive symptoms were assessed with moderated multiple hierarchical regression analyses. RESULTS: We found a significant interaction between biological sex and the risk group, where boys showed higher interleukin (IL)-2 levels among the depressed group compared with the low-risk group. The severity of depressive symptoms was associated with elevated levels of IL-2 in boys, and of IL-6 in girls. There was a significant moderating effect of sex on the relationship between IL-2 and the severity of depressive symptoms but not for IL-6. LIMITATIONS: The cross-sectional design means that we cannot be certain about the direction of the associations. CONCLUSIONS: Our findings suggest sex-specific associations between inflammatory markers and the development of adolescent depression, where IL-2 may increase risk for depression and severity of depressive symptoms in boys, but not in girls. However, IL-6 may increase risk for more severe depressive symptoms in girls.

Identifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample.

OBJECTIVE: The Identifying Depression Early in Adolescence Risk Score (IDEA-RS) was recently developed in Brazil using data from the Pelotas 1993 Birth Cohort to estimate the individualized probability of developing depression in adolescence. This model includes 11 sociodemographic variables and has been assessed in longitudinal studies from four other countries. We aimed to test the performance of IDEA-RS in an independent, community-based, school-attending sample within the same country: the Brazilian High-Risk Cohort. METHODS: Standard external validation, refitted, and case mix-corrected models were used to predict depression among 1442 youth followed from a mean age of 13.5 years at baseline to 17.7 years at follow-up, using probabilities calculated with IDEA-RS coefficients. RESULTS: The area under the curve was 0.65 for standard external validation, 0.70 for the case mix-corrected model, and 0.69 for the refitted model, with discrimination consistently above chance for predicting depression in the new dataset. There was some degree of miscalibration, corrected by model refitting (calibration-in-the-large reduced from 0.77 to 0). CONCLUSION: IDEA-RS was able to parse individuals with higher or lower probability of developing depression beyond chance in an independent Brazilian sample. Further steps should include model improvements and additional studies in populations with high levels of subclinical symptoms to improve clinical decision making.

Adolescent depression beyond DSM definition: a network analysis.

Calls for refining the understanding of depression beyond diagnostic criteria have been growing in recent years. We examined the prevalence and relevance of DSM and non-DSM depressive symptoms in two Brazilian school-based adolescent samples with two commonly used scales, the Patient Health Questionnaire (PHQ-A) and the Mood and Feelings Questionnaire (MFQ). We analyzed cross-sectional data from two similarly recruited samples of adolescents aged 14-16 years, as part of the Identifying Depression Early in Adolescence (IDEA) study in Brazil. We assessed dimensional depressive symptomatology using the PHQ-A in the first sample (n = 7720) and the MFQ in the second sample (n = 1070). We conducted network analyses to study symptom structure and centrality estimates of the two scales. Additionally, we compared centrality of items included (e.g., low mood, anhedonia) and not included in the DSM (e.g., low self-esteem, loneliness) in the MFQ. Sad mood and worthlessness items were the most central items in the network structure of the PHQ-A. In the MFQ sample, self-hatred and loneliness, two non-DSM features, were the most central items and DSM and non-DSM items in this scale formed a highly interconnected network of symptoms. Furthermore, analysis of the MFQ sample revealed DSM items not to be more frequent, severe or interconnected than non-DSM items, but rather part of a larger network of symptoms. A focus on symptoms might advance research on adolescent depression by enhancing our understanding of the disorder.

Identifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample

Objective: The Identifying Depression Early in Adolescence Risk Score (IDEA-RS) was recently developed in Brazil using data from the Pelotas 1993 Birth Cohort to estimate the individualized probability of developing depression in adolescence. This model includes 11 sociodemographic variables and has been assessed in longitudinal studies from four other countries. We aimed to test the performance of IDEA-RS in an independent, community-based, school-attending sample within the same country: the Brazilian High-Risk Cohort. Methods: Standard external validation, refitted, and case mix-corrected models were used to predict depression among 1442 youth followed from a mean age of 13.5 years at baseline to 17.7 years at follow-up, using probabilities calculated with IDEA-RS coefficients. Results: The area under the curve was 0.65 for standard external validation, 0.70 for the case mix-corrected model, and 0.69 for the refitted model, with discrimination consistently above chance for predicting depression in the new dataset. There was some degree of miscalibration, corrected by model refitting (calibration-in-the-large reduced from 0.77 to 0). Conclusion: IDEA-RS was able to parse individuals with higher or lower probability of developing depression beyond chance in an independent Brazilian sample. Further steps should include model improvements and additional studies in populations with high levels of subclinical symptoms to improve clinical decision making.

Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study.

The Identifying Depression Early in Adolescence Risk Score (IDEA-RS) has been externally assessed in samples from four continents, but North America is lacking. Our aim here was to evaluate the performance of the IDEA-RS in predicting future onset of Major Depressive Disorder (MDD) in an adolescent population-based sample in the United States of America - the Great Smoky Mountains Study (GSMS). We applied the intercept and weights of the original IDEA-RS model developed in Brazil to generate individual probabilities for each participant of the GSMS at age 15 (N = 1029). We then evaluated the performance of such predictions against the diagnosis of MDD at age 19 using simple, case-mix corrected and refitted models. Furthermore, we compared how prioritizing the information provided by parents or by adolescents affected performance. The IDEA-RS exhibited a C-statistic of 0.63 (95% CI 0.53-0.74) to predict MDD in the GSMS when applying uncorrected weights. Case-mix corrected and refitted models enhanced performance to 0.69 and 0.67, respectively. No significant difference was found in performance by prioritizing the reports of adolescents or their parents. The IDEA-RS was able to parse out adolescents at risk for a later onset of depression in the GSMS cohort with above chance discrimination. The IDEA-RS has now showed above-chance performance in five continents.

Physical activity and depressive symptoms among adolescents in a school-based sample

Objective: To explore associations between self-reported weekly physical activity and depressive symptomatology among adolescents in a school-based sample from Brazil. Methods: We surveyed 7,405 adolescents aged 14 to 16 years in 101 public schools in Porto Alegre, Brazil. We assessed physical activity using an adapted version of the Patient-Centered Assessment and Counseling for Exercise Plus Nutrition - Adolescent Physical Activity Measure (PACE+), and depressive symptoms using the Brazilian Portuguese version of the Patient Health Questionnaire - Adolescent Version. We compared the depressive symptom scores among adolescents with varying levels of physical activity. Results: Of the overall sample, 84.4% exercised less than the recommended frequency of 60 minutes/day, at least 5 days/week, of moderate to intense physical activity (PACE+ score ≥ 5). Adolescents whose physical activity levels fell below that threshold had higher median depression scores (8 [IQR = 10] vs. 7 [IQR = 9], W = 4060461, p < 0.001). A similar pattern was observed for depression scores in those with PACE+ < 1 (median of 10 [IQR = 11]) and ≥ 1 (7 [IQR = 9], W = 7457608, p < 0.001). Conclusion: In this large sample of Brazilian adolescents, those who exercised less frequently and vigorously than their peers reported more depressive symptoms.

Sleep disturbances, circadian activity, and nocturnal light exposure characterize high risk for and current depression in adolescence.

STUDY OBJECTIVES: Major depressive disorder (MDD) in adolescence is associated with irregularities in circadian rhythms and sleep. The characterization of such impairment may be critical to design effective interventions to prevent development of depression among adolescents. This study aimed to examine self-reported and actimetry-based circadian rhythms and sleep-wake behavior associated with current MDD and high risk (HR) for MDD among adolescents. METHODS: Ninety-six adolescents who took part in the IDEA-RiSCo study were recruited using an empirically developed depression-risk stratification method: 26 classified as low risk (LR), 31 as HR, and 39 as a current depressive episode (MDD). We collected self-report data on insomnia, chronotype, sleep schedule, sleep hygiene as well as objective data on sleep, rest-activity, and light exposure rhythms using actimetry for 10 days. RESULTS: Adolescents with MDD exhibited more severe insomnia, shorter sleep duration, higher social jetlag (SJL), lower relative amplitude (RA) of activity, and higher exposure to artificial light at night (ALAN) compared with the other groups. They also presented poorer sleep hygiene compared with the LR group. The HR group also showed higher insomnia, lower RA, higher exposure to ALAN, and higher SJL compared with the LR group. CONCLUSIONS: HR adolescents shared sleep and rhythm alterations with the MDD group, which may constitute early signs of depression, suggesting that preventive strategies targeting sleep should be examined in future studies. Furthermore, we highlight that actimetry-based parameters of motor activity (particularly RA) and light exposure are promising constructs to be explored as tools for assessment of depression in adolescence.

Physical activity and depressive symptoms among adolescents in a school-based sample.

OBJECTIVE: To explore associations between self-reported weekly physical activity and depressive symptomatology among adolescents in a school-based sample from Brazil. METHODS: We surveyed 7,405 adolescents aged 14 to 16 years in 101 public schools in Porto Alegre, Brazil. We assessed physical activity using an adapted version of the Patient-Centered Assessment and Counseling for Exercise Plus Nutrition - Adolescent Physical Activity Measure (PACE+), and depressive symptoms using the Brazilian Portuguese version of the Patient Health Questionnaire - Adolescent Version. We compared the depressive symptom scores among adolescents with varying levels of physical activity. RESULTS: Of the overall sample, 84.4% exercised less than the recommended frequency of 60 minutes/day, at least 5 days/week, of moderate to intense physical activity (PACE+ score ≥ 5). Adolescents whose physical activity levels fell below that threshold had higher median depression scores (8 [IQR = 10] vs. 7 [IQR = 9], W = 4060461, p < 0.001). A similar pattern was observed for depression scores in those with PACE+ < 1 (median of 10 [IQR = 11]) and ≥ 1 (7 [IQR = 9], W = 7457608, p < 0.001). CONCLUSION: In this large sample of Brazilian adolescents, those who exercised less frequently and vigorously than their peers reported more depressive symptoms.

Self-Reported Social Media Use by Adolescents in Brazil: A School-Based Survey.

INTRODUCTION: Although there is a general perception that adolescent social media use is a global phenomenon, there is a scarcity of data on patterns and preferences of social media use among youth in low- and middle-income countries. We here describe self-reported prevalences and perceived effects of social media use in a school-based sample of Brazilian adolescents. METHODS: We analyzed cross-sectional data on 7,113 adolescents aged 14 to 16 years-old enrolled in 101 public state schools between 2018 and 2019 in Porto Alegre, Brazil. RESULTS: Among the 7,113 with complete data for analyses, 54.9% were female, and 60.6% reported their skin color as white. At least one social media platform was used by 97.7% of adolescents everyday, and 64.7% reported being online "almost constantly". YouTube and WhatsApp were the most popular platforms. Most participants perceived the effect of social media use on their lives as neutral. DISCUSSION: The pattern of social media use by adolescents in Porto Alegre, Brazil, is similar to that reported for samples from high income countries. Also, we found that those who reported being constantly online were also more likely to report socializing with their friends offline.

The Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo): Rationale, Methods, and Baseline Characteristics.

Background: The characterization of adolescents at high risk for developing depression has traditionally relied on the presence or absence of single risk factors. More recently, the use of composite risk scores combining information from multiple variables has gained attention in prognostic research in the field of mental health. We previously developed a sociodemographic composite score to estimate the individual level probability of depression occurrence in adolescence, the Identifying Depression Early in Adolescence Risk Score (IDEA-RS). Objectives: In this report, we present the rationale, methods, and baseline characteristics of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo), a study designed for in-depth examination of multiple neurobiological, psychological, and environmental measures associated with the risk of developing and with the presence of depression in adolescence, with a focus on immune/inflammatory and neuroimaging markers. Methods: Using the IDEA-RS as a tool for risk stratification, we recruited a new sample of adolescents enriched for low (LR) and high (HR) depression risk, as well as a group of adolescents with a currently untreated major depressive episode (MDD). Methods for phenotypic, peripheral biological samples, and neuroimaging assessments are described, as well as baseline clinical characteristics of the IDEA-RiSCo sample. Results: A total of 7,720 adolescents aged 14-16 years were screened in public state schools in Porto Alegre, Brazil. We were able to identify individuals at low and high risk for developing depression in adolescence: in each group, 50 participants (25 boys, 25 girls) were included and successfully completed the detailed phenotypic assessment with ascertainment of risk/MDD status, blood and saliva collections, and magnetic resonance imaging (MRI) scans. Across a variety of measures of psychopathology and exposure to negative events, there was a clear pattern in which either the MDD group or both the HR and the MDD groups exhibited worse indicators in comparison to the LR group. Conclusion: The use of an empirically-derived composite score to stratify risk for developing depression represents a promising strategy to establish a risk-enriched cohort that will contribute to the understanding of the neurobiological correlates of risk and onset of depression in adolescence.