Managing arthritis through activity: Do pain acceptance and negative disease outcome expectations reflect motivational differences among the active and inactive?
Bibliographic record
Abstract
Although physical activity (PA) is a proven arthritis-management strategy, many individuals with arthritis are inactive. Motivating the inactive requires an understanding of whether social cognitions linked to PA differ between active and inactive individuals. According to social cognitive theory, individuals’ negative outcome expectations (OE-likelihood; OE-distress) about the impact of PA on their arthritis may differ (e.g., PA causes joint stiffness). However, PA-negative OE research is limited as the focus tends to be on positive OEs. Further, individuals who are active at differing levels also differ in arthritis pain acceptance (i.e., willingness to engage in valued activities). To date, pain acceptance differences between the active and inactive have not been investigated. Our purpose was to examine whether adults with medically-diagnosed arthritis (Mage=49.91 years) who were active (n=156) or inactive (n=97) differed in negative disease-related OEs (OE-likelihood; OE-distress) and pain acceptance. A between groups MANCOVA controlling for body mass index and arthritis pain was significant (p<.01). Follow-up ANOVAs revealed that actives reported significantly less negative OE-likelihood (partial eta squared=.08), less OE-distress (partial eta squared=.13), and more pain acceptance (partial eta squared=.06) versus their inactive counterparts (p’s<.01). Findings support theory and are the first to illustrate that disease- and activity-related social cognitions differ among active and inactive adults with arthritis. Continued investigation of differences may lead to knowing which social cognitions should be targeted for motivational improvement among the inactive, and whether tailoring of improvement strategies would vary as a function of pain acceptance. Funding: CIHR; Saskatchewan Health Research FoundationAcknowledgments: CIHR;Saskatchewan Health Research Foundation
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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 | 0.002 | 0.006 |
| 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) | 0.002 | 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".