Perceptions of community-based online exercise programming for persons with multiple sclerosis during COVID-19: A qualitative case study
Bibliographic record
Abstract
Exercise can preserve physical, cognitive, and physiological functioning in adults living with relapsing remitting multiple sclerosis (RRMS), making it critical to understand exercise programming options, such as online programming, that may reduce exercise related barriers in this population. Using an exploratory case study design, we qualitatively examined the perceptions and experiences of online exercise programming among persons with multiple sclerosis (PwMS). Seven individuals recruited from the Brock Functional Inclusive Training Centre (Bfit) completed semi-structured interviews which were audio recorded and transcribed verbatim. Data were analysed using thematic analysis. Three major themes were generated from the data: (1) Give and take: Accessibility to exercise, (2) It’s just not real: Experiences and perceptions of technology, and (3) It’s so much more than exercise: The importance of connecting with others. Participants described increased accessibility to exercise, however, barriers to accessibility were also articulated. Previous experiences and attitudes towards using online platforms strongly impacted perceptions of technology positively and negatively. Perceptions of community in the online exercise programming impacted participants’ experiences and motivation to engage in exercise. In comparison to facility-based programs, social experiences were hindered; however online exercise programming offered more social opportunities than having no online options. Our findings highlight the complex perceptions of online exercise programming for PwMS. Practitioners should attempt to address challenges of online exercise offerings to create a better experience for this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".