Characteristics, Outcomes, Sex and Gender Considerations of Community-Based Physical Activity Interventions after Moderate-to-Severe Traumatic Brain Injury: Scoping Review
Bibliographic record
Abstract
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. 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). 19 studies were identified. Seven PA intervention types were included. CERT scores varied (M = 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. 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 | 0.023 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.014 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| 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".