Physical activity and exercise experiences among people with Parkinson’s disease or multiple sclerosis during the COVID-19 pandemic in Canada
Bibliographic record
Abstract
Using interpretive phenomenological analysis, this study examined perceptions and experiences of physical activity (PA) and exercise during and following the COVID-19 pandemic among individuals with mild-to-moderate multiple sclerosis (MS) or Parkinson’s disease (PD) in Canada. Eleven participants (4 males, 7 females; 4 people with MS and 7 with PD) each completed two interviews online between May and July of 2022. Interview 1 focused on PA and exercise behaviours across the pandemic while interview 2 discussed perceived outcomes of PA and exercise changes related to physical health/functioning, psychological/emotional health, social functioning, and overall well-being. Two themes were generated using reflexive thematic analysis: 1) “It truly was a COVID-19 bubble:” The influence of isolation and restrictions in Canada; and 2) Managing MS or PD during COVID-19: “Exercising was essential.” For most participants, PA declined due to COVID-19 restrictions, which in turn was associated with an increase in symptoms. Three participants described little change to their frequency of PA, although often the mode changed and intensity decreased. Two participants described how COVID-19 restrictions lifted exercise barriers, leading to more frequent PA during lockdowns specifically. Participants also described how COVID-19 and its restrictions impacted their daily routines and psychological motivation. Findings highlight the need to provide accessible, motivating, and sociable exercise for individuals with MS or PD in situations where in-person exercise is not feasible. In particular, developing technology to allow for exercise closer to in-person experiences, aiming to increase stamina, full-body movement, and balance.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".