Using social–cognitive constructs to predict preoperative exercise before total joint replacement.
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to apply Bandura's (1998) social-cognitive theory to understand preoperative exercise and walking behavior in a sample of individuals waiting for total joint replacement (TJR) surgery. METHOD: Participants (N = 78) were individuals waiting for TJR who completed measures of the social-cognitive theory, e.g., barrier efficacy, task efficacy, outcome expectancy, self-regulation, neighborhood walking environment, WOMAC-pain, WOMAC-physical function (Western Ontario and McMaster Universities Arthritis Index; In N. Bellamy, W. W. Buchanan, C. H. Goldsmith, J. Campbell, & L. W. Stitt, Validation study of WOMAC: A health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee, The Journal of Rheumatology, 1988, 15, pp. 1833-1840) framed for exercise and walking. RESULTS: Independent t tests suggested no differences (p > .05) between type of surgery (hip vs. knee), gender, or age for exercise and over half of the sample was considered inactive (55%; American Geriatrics Society, 2001). Overall, social-cognitive theory failed to explain exercise in this sample; only pain (β = -.31) explained exercise behavior. When walking behavior was considered specifically, however, task efficacy for walking (β = .55) and self-regulation (β = .24) explained 32% of behavior. social cognitive theory showed limited capability in predicting exercise in this sample but strong capability for explaining walking. CONCLUSION: When considering exercise before TJR surgery, our findings reflect the significance of the pain associated with advanced osteoarthritis and the negative impact on preoperative exercise behaviors. As walking was the most commonly reported type of exercise, results from this study suggest that task efficacy for walking and self-regulation may play an important role when considering interventions aimed to increase walking behavior before TJR.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".