Physical activity among young children with disabilities: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Physical activity in the early years is necessary for setting the foundation for healthy growth and development in later childhood and adolescence. While most published evidence to date focuses on typically developing children, prevalence rates of physical activity among children with disabilities have been less studied. This protocol paper documents the plan of a systematic review, which aims to synthesise the evidence regarding physical activity levels among young children with disabilities. METHODS AND ANALYSIS: Searches are anticipated to commence in May 2022. Empirical quantitative studies will be considered for inclusion if they present intervention or observational data on non-therapeutic (ie, leisure time) physical activity among children <5.99 years with physical, mental, intellectual or sensory impairments. Data sources will be retrieved via electronic database searches (Cumulative Index to Nursing and Allied Health Literature (CINAHL), EBSCO Sports Medicine Database (SPORTDiscus), Medical Literature Analysis and Retrieval System Online (MEDLINE), Elsevier Bibliographic Database (Scopus), Psychological Abstracts (PsycINFO), Education Resources Information Centre (ERIC) and Excerpta Medica Database (EMBASE)). Additional strategies to identify relevant studies will include manual searching and citation tracking of included articles. Titles and abstracts of identified studies will be screened for inclusion, followed by full-text reviews. Three independent reviewers will conduct quality appraisal using the Downs and Black checklist. A summary of included studies will describe the study designs, participant and activity characteristics, and outcomes. ETHICS AND DISSEMINATION: This systematic review involves a secondary analysis of previously published data; therefore, this review does not require ethical approval. The proposed paper will summarise the current evidence base on physical activity levels among young children with a diagnosed disability. The findings from this systematic review will identify gaps to be explored by future research studies and inform future investigations among the paediatric disability population. PROSPERO REGISTRATION NUMBER: CRD42021266585.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.103 | 0.082 |
| Meta-epidemiology (narrow) | 0.006 | 0.009 |
| Meta-epidemiology (broad) | 0.016 | 0.012 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.108 | 0.018 |
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".