Interventions on children’s and adolescents’ physical activity and sedentary behaviour: protocol for a systematic review from a sex/gender perspective
Bibliographic record
Abstract
BACKGROUND: Low levels of physical activity (PA) and high levels of sedentary behaviour (SB) have been observed in young people. Both behaviours are detrimental for health with patterns tending to continue into adulthood. There is sustained value in establishing health habits in early years. Even though levels of SB and participation in PA differ among boys and girls, and the effectiveness of interventions to promote PA and/or prevent sedentary behaviours varies by sex/gender to date, sex/gender in systematic reviews is not yet widely considered. Additionally, while tools have been proposed, there is no consensus on the criteria to assess sex/gender in systematic reviews in the context of health promotion. The main objectives of this systematic review are to evaluate the effects of interventions on girls' and boys' PA and SB and to appraise the extent to which the studies have taken sex/gender into account. METHODS: Eleven electronic databases will be searched to identify all relevant (randomized) controlled trials. Two independent reviewers will screen studies, extract data and appraise the quality of studies. The main outcome of the studies will be a quantified measure of PA and/or SB. Risk of bias of individual studies will be assessed using the Cochrane Risk of Bias Tool for RCTs. Meta-analyses will be conducted when possible among studies with sufficient homogeneity. To evaluate sex/gender considerations in primary studies, we will use a sex/gender checklist that builds on existing tools and was developed during a 2-day, iterative process among a multidisciplinary panel of 16 experts. The GRADE framework will be used to evaluate evidence across studies for each main efficacy outcome. DISCUSSION: To our knowledge, our systematic review will be the first to analyse how sex/gender is considered in interventions promoting PA and/or reducing SB in children and adolescents in detail. The review will provide information on how sex/gender aspects have been considered in recent research and the extent to which sex/gender might impact study outcomes. Our findings will be of interest to stakeholders, health promoters, researchers and policy makers who wish to support more equal outcomes from interventions promoting PA and/or reducing SB. TRIAL REGISTRATION: PROSPERO CRD42018109528 .
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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 | 0.085 | 0.092 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.018 | 0.019 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.085 | 0.014 |
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".