The Role of Outcome Expectations and Self-Efficacy in Explaining Physical Activity Behaviors of Individuals with Multiple Sclerosis
Bibliographic record
Abstract
Multiple sclerosis (MS) is a debilitating neurological disease with few successful interventions available for alleviating symptoms. Physical activity (PA) may aid in alleviating symptoms; however, most individuals with MS are inactive. To promote PA within this population, it is important to identify key theoretical correlates of PA specific to them and then target these in PA interventions. The purpose of this study was to examine the role of self-efficacy and outcome expectations in explaining PA. Seventy-six participants completed a baseline questionnaire measuring these variables and a telephone follow-up 1 month later concerning PA behaviors. Regression analyses showed that self-efficacy (beta = .41) and outcome expectations (beta = .27) directly influenced PA, and that self-efficacy directly influenced outcome expectations (beta = .28). Therefore, to promote PA within this population, interventions should target both self-efficacy and outcome expectations. Individuals with MS need to better understand the benefits of PA and how it can alleviate or improve their symptoms.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".