A Controlled Investigation of a Cognitive Behavioural Pain Management Program for Older Adults
Bibliographic record
Abstract
BACKGROUND: Although psychosocial treatments for pain have been found to be effective in reducing self-reported pain, physician visits, and in improving mood, the research has largely focused on younger persons. As such, there is a paucity of related studies involving older adults. METHOD: We implemented and evaluated a 10-session psychosocial (i.e. cognitive behavioural orientation) pain management program that was specifically designed for older adults. The intervention was delivered either in the participants' homes or in bookable rooms in seniors' residence buildings. Ninety-five community dwelling seniors with at least one chronic pain condition were assigned to either a treatment or a wait-list control condition. An assessment battery was administered to treatment participants immediately before the program started, immediately post-treatment, and 3-months post-treatment. Comparable data were obtained from control group participants, although 3-month follow-up data were not available for the control group. Outcome variables included pain intensity, coping strategy usage, pain beliefs/appraisals, and perceived life stressors. RESULTS: Although decreases in pain intensity were observed in both the treatment and wait-list control groups, the intervention was found to result in fewer maladaptive beliefs about pain and greater use of relaxation, which is considered to be an adaptive coping strategy. CONCLUSIONS: Although some treatment benefits were identified (e.g. change in pain-related beliefs), future research should test the effectiveness of a cognitive behavioural treatment program tailored for seniors with participants who are experiencing higher pain intensities than those reported by our sample (i.e. those who experience a higher level of pain at baseline may represent a more suitable sample for assessing the effectiveness of our intervention in reducing pain intensity).
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".