Attributional retraining: Promoting psychological wellbeing in older adults with compromised health
Bibliographic record
Abstract
Older adults make up the largest portion of the population of physically inactive individuals. Health challenges, and psychological barriers (e.g., maladaptive causal attributions), contribute to reduced activity engagement and low perceived control. This pilot study tested an attributional retraining (AR) intervention designed to increase control-related outcomes in a physical activity context for older adults with compromised health. Using a randomized treatment design, we examined treatment effects on a sample of older adults attending a day hospital (N = 37, Mage = 80). We employed ANCOVAs, controlling for age, sex, and morbidity, to assess differences in post-treatment outcomes between AR and No-AR conditions. AR recipients (vs. No-AR) reported lower post-treatment helplessness and more perceived control over their health. Our study offers evidence for AR to increase control-related outcomes and lays the groundwork for further research into supporting older adult populations with compromised health.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".