Using Digital Media to Improve Adolescent Resilience and Prevent Mental Health Problems: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Global databases show a high prevalence of mental health problems among adolescents (13.5% among those aged 10-14 years and 14.65% for those aged 15-19 years). Successful coping depends on risk and protective factors and how their interaction influences resilience. Higher resilience has been shown to correlate with fewer mental health problems. Digital mental health interventions may help address these problems. OBJECTIVE: This protocol serves as a framework for planning a scoping review to map the types of digital communication media and their effectiveness in increasing resilience in youths. METHODS: The Joanna Briggs Institute guidelines will be used: defining the research questions; identifying relevant studies; study selection (we will select articles based on titles and abstracts); charting the data; collating, summarizing, and reporting the results; and consultation. The synthesis will focus on the type of digital media used to increase adolescent resilience skills and the impact they have on adolescent resilience skills. Quantitative and qualitative analyses will be conducted. RESULTS: The study selection based on keywords was completed in December 2023, the study screening and review were completed in February 2024, and the results manuscript is currently being prepared. This scoping review protocol was funded by the Center for Higher Education Funding and the Indonesia Endowment Fund for Education. CONCLUSIONS: The results of the study will provide a comprehensive overview of commonly used digital media types and their effectiveness in increasing youth resilience. Thus, the results of this scoping review protocol can serve as foundational evidence in deciding further research or interventions. This study may also be used as a guideline for mapping and identifying the type and impact of communication media used to increase adolescents' resilience skills. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58681.
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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 | 0.107 | 0.107 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.096 | 0.020 |
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".