Success4life Youth Empowerment for Promoting Well-being and Boosting Mental Health: Protocol for an Experimental Study
Bibliographic record
Abstract
BACKGROUND: There is an increasingly alarming worsening of mental health among the youth. There remain significant unmet needs for developing innovative, evidence-based technology-enhanced, positive psychology interventions (PPIs) all-inclusive in targeting psychological distress and risk factors related to high-risk behavior commonly encountered in adolescents. OBJECTIVE: We aim to assess the effectiveness of a hybrid (incorporating both synchronous and asynchronous learning) and holistic (targeting social and emotional learning and tackling risk factors unique for this age group) PPI, "success4life youth empowerment," in improving well-being in the youth. METHODS: Students' well-being will be assessed by the 5-item World Health Organization Well-Being Index, and hope will be assessed by the 6-item Children's Hope Scale at week 0, week 8, and week 10, month 6, and month 12. Any improvement in well-being and hope will be measured, estimating the difference in postintervention (week 8 and week 10) and preintervention (week 0) scores by determining the P value and effect size using appropriate statistical tests. RESULTS: This study includes 2 phases: pilot phase 1, delivered by the creators of the succcess4life youth empowerment modules and platform, and phase 2, which will consist of the estimation of scalability through the recruitment of trainers. We hope to start student recruitment by 2022 and aim to complete the results for phase 1 pilot testing by 2023. CONCLUSIONS: We anticipate that a primarily web-based, 10-week holistic PPI can support improvement in the mental wellness of the youth and has the potential for effective scalability. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/38463.
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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 | 0.029 | 0.023 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.093 | 0.015 |
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".