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Objective: Untreated mental disorders are important among low- and middle-income country (LMIC) university students in Latin America, where barriers to treatment are high. Scalable interventions are needed. This study compared transdiagnostic self-guided and guided internet-delivered cognitive behavioral therapy (i-CBT) with treatment as usual (TAU) for clinically significant anxiety and depression among undergraduates in Colombia and Mexico. Method: 1,319 anxious, as determined by the Generalized Anxiety Disorder–7 (GAD-7) = 10+ and/or depressed, as determined by the Patient Health Questionnaire–9 (PHQ-9) = 10+, undergraduates (mean [SD] age = 21.4 [3.2]); 78.7% female; 55.9% first-generation university student) from seven universities in Colombia and Mexico were randomized to culturally adapted versions of self-guided i-CBT (n = 439), guided i-CBT (n = 445), or treatment as usual (TAU; n = 435). All randomized participants were reassessed 3 months after randomization. The primary outcome was remission of both anxiety (GAD-7 = 0–4) and depression (PHQ-9 = 0–4). We hypothesized that remission would be higher with guided i-CBT than with the other interventions. Results: Intent-to-treat analysis found significantly higher adjusted (for university and loss to follow-up) remission rates (ARD) among participants randomized to guided i-CBT than either self-guided i-CBT (ARD = 13.1%, χ12 = 10.4, p =.001) or TAU (ARD = 11.2%, χ12 = 8.4, p =.004), but no significant difference between self-guided i-CBT and TAU (ARD = −1.9%, χ12 = 0.2, p =.63). Per-protocol sensitivity analyses and analyses of dimensional outcomes yielded similar results. Conclusions: Significant reductions in anxiety and depression among LMIC university students could be achieved with guided i-CBT, although further research is needed to determine which students would most likely benefit from this intervention. What is the public health significance of this article?: Anxiety and depression are significant public health problems in LMIC universities. A culturally adapted transdiagnostic-guided i-CBT could help alleviate these problems as a low-threshold intervention component of a stepped-care treatment delivery model. [ABSTRACT FROM AUTHOR]

Purpose: Parental psychological control and autonomy support, abuse, and neglect influence adolescents' mental health. Analyzing the direct and indirect associations between childrearing characteristics, maltreatment, and mental health is important, especially in understudied and diverse cultural contexts. First, we examine the associations of parental psychological control and autonomy support with adolescent internalizing and externalizing problems directly and indirectly, through maltreatment. Second, we evaluate the extent to which parental psychological control and autonomy support may discriminate self-reported maltreatment in adolescents. Methods: Eight-hundred-and-nine-adolescents (Mage = 13.5) from six urban public middle schools in Mexico City participated and responded to the self-administered Perceived Parental Autonomy Support Scale and the ISPCAN Child Abuse Screening Tool for each parental figure and the Youth Self Report for evaluation of internalizing and externalizing problems. Results: Maternal models obtained the best fit [R2 =.380, for internalizing, and R2 =.229, for externalizing problems], with strongest indirect effects through maternal negligence for internalizing problems [x2(2) = 1.729, ρ =.4212, RMSEA =.000 (.000,.067), CFI =.999, TLI =.999] and through maternal psychological abuse for externalizing problems [x2(2) = 1.666, ρ =.4347, RMSEA =.000 (.000,.066), CFI =.999, TLI =.999]. Parental psychological control and autonomy support discriminate self-reported maltreatment with an area under the curve between.68 and.99. Conclusions: Maternal models showed an association of parental childrearing characteristics with adolescent mental health problems directly and indirectly through maltreatment, and preliminary evidence suggests that parental childrearing characteristics may discriminate self-reported maltreatment in adolescents. [ABSTRACT FROM AUTHOR]

Key Points: Question: Can an individualized treatment rule identify patients who benefit as much or more from self-guided internet-delivered cognitive behavioral therapy (i-CBT) as from guided i-CBT? Findings: In this secondary analysis of a randomized clinical trial of 1319 university students with anxiety and/or depression, guided i-CBT optimized the probability of (1) joint remission of anxiety and depression for 91.7% of participants, (2) remission of anxiety for 100% of participants, and (3) remission of depression for 71.5% of participants. Self-guided i-CBT, in comparison, optimized the probability of remission of depression for the remaining 28.5% of participants. Meaning: Self-guided i-CBT is sometimes equally or more effective than guided i-CBT for depression but not anxiety. Importance: Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT. Objective: To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors. Design, Setting, and Participants: This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022. Interventions: Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435). Main Outcomes and Measures: Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline. Results: The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P =.003) or treatment as usual (40.0% [2.7%]; P =.001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P =.007; self-guided i-CBT: 25.4% [8.8%]; P =.004; treatment as usual: 31.0% [9.4%]; P =.001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P =.14; treatment as usual: 53.0% [6.0%]; P =.25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P =.001; treatment as usual: 41.8% [3.2%]; P <.001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P =.07). Conclusions and Relevance: Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings. Trial Registration: ClinicalTrials.gov Identifier: NCT04780542 This prespecified secondary analysis of a randomized clinical trial discusses the development of an individualized treatment rule using machine learning methods for guided vs self-guided internet-delivered cognitive behavioral therapy based on a rich set of baseline predictors. [ABSTRACT FROM AUTHOR]