From ‘screen time’ to the digital level of analysis: protocol for a scoping review of digital media use in children and adolescents
Bibliographic record
Abstract
INTRODUCTION: Research on the relationship between digital media exposure and child development is complex, inconsistent and fraught with debate. A highlighted area of inadequacy surrounds the methodological limitations of measuring digital media use for both researchers and clinicians, alike. This protocol aims to (1) identify core concepts in the area of screen time and digital media use in children and adolescents (2) map existing research paradigms and screening/measurement tools that serve to underpin and operationalise core concepts and (3) provide an initial step in integrating these findings into a consolidated screening toolkit. It is expected this enterprise will help advance research and clinical evaluation in fields concerned with digital media use, namely medicine, child development and the social sciences. METHODS AND ANALYSIS: The planned scoping review will search relevant electronic databases, including Ovid MEDLINE, PsycINFO and Scopus, in addition to grey literature. All empirical investigations and presentation of original research will be considered, and measurement/screening tools for digital media usage in children and adolescents will be identified and reported on. Two reviewers will pilot test the screening criteria, and data extraction forms prior to independently screening all relevant literature and extracting the data. A three-stage synthesis process will be used to map the existent measurement and screening tools for digital media usage in children and adolescents. ETHICS AND DISSEMINATION: There are no ethical considerations for this scoping review. Plans for dissemination include publication in a top-tier, open-access journal, public presentations and conference proceedings. Presentation of the full scoping review has been accepted to the American Academy of Child & Adolescent Psychiatry 66th Annual Meeting.
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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 | 0.128 | 0.151 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.064 | 0.016 |
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".