Barriers and Facilitators Related to Participation in Aquafitness Programs for People with Multiple Sclerosis
Bibliographic record
Abstract
Exercise and leisure activities provide physical and psychosocial benefits to people with multiple sclerosis (MS) and can enhance their quality of life. In Winnipeg, Manitoba, Canada, people with MS have reported barriers to their participation in local MS-specific aquafitness (AF) programs. Therefore, a formal exploration of the accessibility of local AF programs for people with MS was undertaken. The purpose of this phenomenological study was to identify factors that facilitate or impede participation in AF programs by individuals with MS living in Winnipeg. Qualitative data were collected from a total of eight participants through one focus group (n = 7) and one in-depth interview (n = 1). The sample consisted of individuals with MS who were currently participating in AF programming as well as those who were not. Data were audio-recorded and transcribed verbatim, and thematic analysis was completed. Seven themes emerged regarding factors affecting participation in local AF programs. Barriers to participation included inadequate transportation, lack of one-on-one support, environmental inaccessibility, and fears associated with participation in the programs. Facilitators of participation included a knowledgeable instructor and experiencing physical and psychosocial benefits from the program. Information from this study was used locally to advocate for people with MS in order to increase participation in local AF programming.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".