Multiple sclerosis patients need and want information on exercise promotion from healthcare providers: a qualitative study
Bibliographic record
Abstract
BACKGROUND: There is growing recognition of the benefits and safety of exercise and its importance in the comprehensive care of persons with multiple sclerosis (MS), yet uptake is low. OBJECTIVE: We explored the needs and wants of patients with MS regarding exercise promotion through healthcare providers. SETTING AND PARTICIPANTS: Participants were adults with MS who had mild-or-moderate disability and a range of exercise levels. All participants lived in the Midwest of the United States. METHODS: Fifty semi-structured interviews were conducted and analysed using thematic analysis. Two themes emerged, namely interactions between patients and healthcare providers and needs and wants of patients. RESULTS: Analysis of participant accounts illustrate that current exercise promotion by healthcare providers does not meet patient needs and wants. The identified needs and wants of persons with MS involved (i) information and knowledge on the benefits of exercise and exercise prescription, (ii) materials to allow home and community exercise and (iii) tools for initiating and maintaining exercise behaviour. DISCUSSION AND CONCLUSION: Patients with MS frequently interact with healthcare providers and are generally unsatisfied with exercise promotion during interactions. Healthcare providers can address the low uptake of exercise among persons with MS by acting upon the identified unmet needs involving materials, knowledge and behaviour change strategies for exercise.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".