Examination of self-regulatory efficacy and pain among individuals challenged by arthritis flares.
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: Public health guidelines for physical activity (PA) for individuals with arthritis are 150 min/week. Self-regulatory efficacy to plan and schedule activity (SRE-SP) was greater for individuals meeting guidelines in studies when symptoms were usual. Extreme symptoms of a flare presumably challenge or block PA adherence. We found it surprising that the question of whether pain intensity and SRE-SP differ within the same person as a function of symptom severity (i.e., flare vs. no-flare) and PA level has not been addressed. RESEARCH METHOD/DESIGN: Participants (N = 53) reported SRE-SP and SRE to overcome arthritis barriers (SRE-AB) during the following month, average usual and flare-pain intensity, and PA volume in the past 6 months. Mixed-model ANOVAs compared those meeting or not meeting PA guidelines in both flare and no-flare conditions. RESULTS: Main effects for SRE (SP and AB) were significant for within flare/no-flare comparisons (p < .001) and for SRE-SP were significant between PA groups (p < .05). Individuals meeting PA guidelines have the advantage of greater SRE-SP to motivate adherence than those of the less active. All participants' activity was less efficacious during a flare. For pain intensity, a within-subjects flare versus no-flare effect (p < .001) confirmed that flares are perceived as more of an obstacle or challenge for engaging in PA. CONCLUSION/IMPLICATIONS: Regardless of meeting or not meeting PA guidelines, participants reported lower SRE and higher pain intensity during a flare. PA adherence during a flare may require self-regulation of PA to be active, and in particular, to be able to meet recommended guidelines, relative to symptom severity.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".