Age and psychosocial contributors to well-being among older adults living with chronic pain
Bibliographic record
Abstract
Objectives: this study examined the influence of age variables along with psychosocial variables on well-being among older adults living with chronic pain.Methods: Using a cross-sectional survey design, older adults living with chronic pain in canada (N = 220) completed an online survey assessing age variables (ie age at onset of chronic pain, current age), psychosocial variables (ie pain catastrophizing, pain disability, physical functioning, psychological inflexibility), and well-being variables (ie autonomy, environmental mastery, self-acceptance, overall eudaimonic well-being).Results: current age, but not age of onset of chronic pain, significantly predicted eudaimonic well-being and self-acceptance.Physical functioning, pain catastrophizing, and pain disability significantly predicted eudaimonic well-being, autonomy, and environmental mastery.Pain catastrophizing also significantly predicted self-acceptance.With regards to the relative importance of effect sizes, physical functioning followed by pain catastrophizing were the most important factors contributing to autonomy, environmental mastery, and self-acceptance.these psychosocial factors were more important for self-acceptance than they were for autonomy or environmental mastery.Conclusion: When living with chronic pain, the psychosocial variables of most importance to older adults' well-being may be physical functioning and pain catastrophizing, and the development of psychological interventions for older chronic pain populations should account for these psychosocial factors.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".