Predicting Self-Care Behaviors Among Older Adults Coping With Arthritis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this investigation is to examine correlates and predictors of self-care activities for persons diagnosed with arthritis both cross-sectionally and longitudinally. METHOD: Data from telephone surveys conducted with 313 older (M = 68.8, SD = 8.93) individuals, chosen from a larger sample, who reported professionally diagnosed arthritis, were used. RESULTS: A total of 10 of the 11 self-care activities changed significantly during the 1-year interval, with 9 showing increased participation. Results from hierarchical regressions showed that all three blocks of predictors explained significant portions of variance, with gender and perceived importance of general health significantly predicting self-care activities at Time 1, at Time 2, and longitudinally. DISCUSSION: These results highlight the influence of demographic, health status, and health belief variables on self-care both cross-sectionally and longitudinally. Future work should focus on the mediating effects of these and other variables to better understand the processes by which individuals engage in self-care behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".