Characteristics, Outcomes, Sex and Gender Considerations of Community-Based Physical Activity Interventions after Moderate-to-Severe Traumatic Brain Injury: Scoping Review
Bibliographic record
Abstract
OBJECTIVE: This scoping review mapped the current evidence about community-based physical activity (PA) interventions for individuals with moderate-to-severe traumatic brain injury (TBI) and identified the reported health-related outcomes, measurement tools used, and considerations given to sex and gender. METHODS: Searches were conducted in six academic databases for peer-reviewed articles (MEDLINE, EMBASE, Cochrane CENTRAL, CINAHL, SPORTDiscus, and PEDro). PRISMA Scoping Review guidelines were followed. Two reviewers independently screened articles for inclusion and extracted data for the analysis with a modified Consensus on Exercise Reporting Template (CERT). Health-related outcomes were classified with domains of the International Classification of Function, Disability and Health (ICF). RESULTS: = 12.74, SD = 3.51 items), with limited details for replication. ICF outcomes focused on improving body functions (74%), activities and participation (14%), environmental factors (1%), and other: not covered (11%). Only four studies (21%) stratified their results by sex or gender. CONCLUSIONS: Identified PA interventions from this review revealed common characteristics that led to improved outcomes. Proposed recommendations aim to improve future research and community practice. There is a pressing need for more sex and gender considerations in PA research after moderate-to-severe TBI.
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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 | 0.020 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".