Co-creating and Implementing a Community-Based Peer-Assisted Physical Activity Program to Promote Exercise and Sport Participation after Moderate-to-Severe Traumatic Brain Injury
Bibliographic record
Abstract
Traumatic brain injury (TBI) is a leading cause of death and disability around the world, and moderate-to-severe TBI may result in long-term or lifelong sequelae that prevent individuals from returning to a pre-injury way of functioning. Physical activity (PA; e.g., exercise and sport) demonstrates the potential to alleviate some of this burden through meaningful health-improving activities that are positive for mood, community participation, and quality of life after moderate-to-severe TBI. However, adults with moderate-to-severe TBI do not participate in recommended amounts of PA. Therefore, establishing best-practice methods to support PA participation in the community after moderate-to-severe TBI is warranted for the purpose of improving long-term outcomes. This doctoral dissertation addresses that gap with (1) a scoping review of the current literature about community-based PA interventions after moderate-to-severe TBI, (2) an exploratory case study of an existing peer-based PA program being piloted in a YMCA fitness centre, (3) an interpretive case study of co-creating a tailored peer-based PA program with key stakeholders, and (4) an interpretative phenomenological analysis of COVID-19’s impact on program participants and their PA. Results showed (1) community-based PA interventions can lead to significant improvements in health-related outcomes after moderate-to-severe TBI, but further research is needed with sex and gender considerations, telehealth applications, and better intervention reporting; (2) the inner mechanisms of a peer-based PA program from the perspective of multiple stakeholders and the autonomy-supportive approaches needed to tailor the intervention for future users; (3) how the participation in and co-creation of a new optimized community-based peer-assisted program can increase PA autonomy, reduce PA barriers, and lead to important biopsychosocial benefits; and (4) the profound impact of COVID-19 and necessary considerations to support PA in a pandemic after moderate-to-severe TBI. Findings of this dissertation include implications for the rehabilitation sciences and literature. Integrated knowledge transfer approaches to co-creating a peer-based PA program in the community can lead to the co-production of knowledge between researchers and users, who benefit from health promotion opportunities that further their participation in society. Peer-based PA programs can transcend rehabilitation to the community context with positive health behaviours that extend beyond a formal intervention.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".