Initiation of adapted physical activity for military personnel and civilians with acquired disabilities: The role of social support
Bibliographic record
Abstract
Limited research has explored the factors that promote initiation into adapted physical activity (PA). This critical knowledge gap results in a lack of understanding of how to optimally promote PA participation for individuals with acquired disabilities. With the aim of filling this gap, we conducted a secondary analysis of qualitative data relating to the PA experiences of individuals with physical disabilities. Specifically, we sought to examine the role of social support in initiating PA for individuals with acquired physical disabilities. Participants consisted of both civilians (n=15; age:19-73 years) and military personnel (n=18; age:30-68 years) with acquired disabilities (e.g., amputations, spinal cord injuries). Participants engaged in two semi-structured interviews, which explored PA engagement over time, as well as perceptions of PA. An inductive thematic narrative analysis was used to identify patterns relating to social support and PA initiation. Creative non-fiction was employed to present the findings in a way that fully detailed the depth and richness of participant experiences. Four distinct short stories were created, based on the identified social support networks (family, peers, coaches, and community outreach). The results illustrate the complexity and critical value of social support in the early stages of adapted PA participation. Findings also highlight the different roles of each social support network, as well as the nuances that arise in the availability and expression of social support based on whether participants were civilians or military personnel. This study provides the foundation for further exploration of the significance of social support in promoting adapted PA.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".