Feasibility and acceptability of an adapted peer-based walking intervention for adults with moderate-to-severe traumatic brain injury
Bibliographic record
Abstract
Purpose To examine the feasibility and acceptability of a 6-week peer-based walking intervention for adults with moderate-to-severe TBI with telehealth supports.Materials and methods Pre-post feasibility trial with 18 community-dwelling adults (10 men; 8 women) with moderate-to-severe TBI aged 21–61 years (M = 40.6, SD = 11.3). Feasibility outcomes included participation, attrition, safety across 12 90-minute sessions, and telehealth platform quality. Acceptability outcomes included program satisfaction. Exploratory outcomes included daily step count with activity trackers and pre-post intervention questionnaires (mood, leisure satisfaction, exercise self-efficacy, quality of life) through video conferencing.Results 15/18 (83%) participants completed ≥ 9 sessions (75%). Three participants were lost to attrition. No major adverse events reported. Minor events included fatigue and muscle soreness. Participants reported high satisfaction (M = 9.2/10, SD = 0.9). Average weekly steps per day rose from 10,011 to 11,177 steps (12%). Three participants’ step count data were not included due to tremors or forgetting to wear the device (≥ 9 days). One major and several minor connectivity problems occurred. Wilcoxon Signed Ranks tests identified a significant change in negative affect (p < 0.002).Conclusions Findings support the feasibility and acceptability of a 6-week peer-based walking intervention with telehealth supports for our sample.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".