Scoping review of interventions aimed at promoting healthy screen use among adolescents
Bibliographic record
Abstract
OBJECTIVES: The objective of this scoping review is to map and synthesise existing literature on interventions aimed at promoting healthy screen use among adolescents. This review identifies the types, functions and settings of interventions, explores the diversity of targeted outcomes and highlights equity considerations and research gaps. DESIGN: We conducted a scoping review in accordance with the Arksey and O'Malley framework and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. DATA SOURCES: We systematically searched Medline, PsycINFO and ERIC from January 2013 to June 2024. Reference lists of included studies were also manually screened. ELIGIBILITY CRITERIA: We included peer-reviewed experimental, quasi-experimental, observational and qualitative studies reporting on interventions designed to promote healthy screen use among adolescents aged 10-19 years. DATA EXTRACTION AND SYNTHESIS: One author extracted data using a structured charting form, and a second author verified all entries. Results were synthesised descriptively across key themes including target populations, theoretical frameworks, intervention components and reported outcomes. RESULTS: From 6433 records, we identified 93 articles on 81 interventions, mainly conducted in high school settings in the USA and Australia. Most examined short-term interventions targeting recreational screen time. Outcomes included media literacy, cyberbullying, internet and gaming addiction, safe internet use, social media use and mental and sexual health. Seventy-eight per cent of interventions attempted to educate adolescents, while 34% offered training activities (eg, educational sessions to elevate risk awareness and skill-based training to enhance digital literacy and self-regulation). Interventions targeting external influences were used less frequently. About 20% of studies showed no statistically significant findings, highlighting the need to promote evidence-based interventions. CONCLUSION: This review identifies a need for broader, multilevel strategies that account for contextual factors and social determinants in influencing screen use and its related health issues. Future research should explore long-term effectiveness while examining the potential moderating and mediating effects of social determinants. Equity considerations were not a primary focus of most interventions, underscoring an important gap in this literature. Future interventions could incorporate equity-focused design and evaluation to ensure they respond to the needs of diverse adolescent populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".