A Digital Single-Session Intervention Platform for Youth Mental Health: Cultural Adaptation, Evaluation, and Dissemination
Bibliographic record
Abstract
BACKGROUND: Despite the proliferation of evidence-based digital mental health programs for young people, their low uptake and inconsistent implementation preclude them from benefiting youths at scale. Identifying effective implementation strategies for evidence-based supports is especially critical in regions where treatment access is lowest owing to mental health provider shortages. OBJECTIVE: The goal of this academic-community partnership, funded by the City of San Antonio Metropolitan Health District, was to culturally adapt, disseminate, and gauge the acceptability and utility of an evidence-based digital mental health platform-Project Youth Empowerment and Support (YES)-among English- and Spanish-speaking youths living in south Texas. METHODS: Project YES is an open-access, anonymous platform containing 3 evidence-based, self-guided interventions for youth mental health. Project YES was culturally adapted via focus groups and co-design sessions with San Antonio youths with lived experience of depression and anxiety; translated into Spanish; and disseminated throughout San Antonio, Texas, via community and school partnerships. RESULTS: During the project period (April 2021 to December 2021), 1801 San Antonio youths began and 894 (49.64%) of them completed a 30-minute, single-session intervention within Project YES (aged 11-17 years; n=718, 39.87% male; n=961, 53.36% female; and n=3, 0.17% intersex; n=1477, 82.01% Hispanic; n=77, 4.28% non-Hispanic White; n=113, 6.27% Black; n=28, 1.55% Asian; and n=93, 5.16% other). This completion rate (49.64%) surpassed those previously observed for Project YES (eg, 34% when disseminated via social media). San Antonio youths rated Project YES as highly acceptable across all metrics, both in English and Spanish. In addition, the youths who completed Project YES-ENGLISH reported significant improvements in hopelessness (Cohen d=0.33; P<001), self-hate (Cohen d=0.27; P<001), and perceived agency (Cohen d=0.25; P<001) from before to after the intervention, and the youths who completed Project YES-SPANISH reported significant improvements in self-hate (Cohen d=0.37; P=.049) from before to after the intervention. CONCLUSIONS: The results indicate that Project YES-an open-access, free, and anonymous web-based single-session intervention platform-is an acceptable, accessible, and applicable mental health support for English- and Spanish-speaking San Antonio youths.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".