Participatory co-creation of an adapted physical activity program for adults with moderate-to-severe traumatic brain injury
Bibliographic record
Abstract
Background: Research about using physical activity (PA) to improve health, quality of life, and participation after moderate-to-severe traumatic brain injury (TBI) is receiving growing attention. However, best-practices for maintaining PA participation after TBI have yet to be defined. In this context, a team of researchers and stakeholders with a moderate-to-severe TBI (including program participants and peer mentors) participated in a co-creation process to optimize a 9-month, 3-phased, community-based, adapted PA program named TBI-Health. Purpose: The study aimed to provide a detailed account of the participation in and co-creation of a new TBI-Health Program to enhance sport and exercise participation for adults with moderate-to-severe TBI. Specifically, we carried out an in-depth exploration of the perceived experiences and outcomes of users over one cycle of the program to assist the co-creation process. Methods: = 4) were involved in audio-recorded focus groups after each program phase. Reflexive thematic analyses within and across the phases identified three higher-order themes. Results: Program Participation included barriers, facilitators, sources of motivation and suggested modifications to optimize the program; Biopsychosocial Changes highlighted perceived physical, psychological, and social outcomes, by self and others, that resulted from program participation; PA Autonomy emphasized transitions in knowledge, sex- and gender-related beliefs, and abilities related to exercise and sport participation. Conclusions: Study findings suggest the TBI-Health program can increase autonomy for and reduce barriers to PA for adults with moderate-to-severe TBI, which results in increased PA participation and important physical, psychological, and social benefits. More research is needed about the TBI-Health program with larger samples.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".