Changes to coping and its relationship to improved wellbeing in the optimal health program for chronic disease
Bibliographic record
Abstract
Adaptive-style coping strategies are associated with favourable mental health and quality of life outcomes among individuals with chronic disease. The Optimal Health Program (OHP) is a psychosocial self-efficacy program that empowers individuals to be active leaders in their health and wellness management. This study aimed to evaluate the impact of the OHP on coping styles. Adults with Type 1 or Type 2 diabetes, chronic kidney disease, stroke survivors, and stroke carers were recruited from St. Vincent's Hospital, Australia, to participate in one of three trials evaluating the efficacy of the OHP compared to usual care for the management of these chronic conditions. Coping was assessed at baseline, then at 3, 6- and 12-months post baseline. To examine changes in coping in association with OHP participation, we conducted a linear mixed-effects model, using the repeated measures approach. The sample was comprised of 411 participants, with 76 (18.5%) stroke survivors, 69 (16.8%) stroke carers, 151 (36.7%) chronic kidney disease patients, and 115 (28.0%) diabetes mellitus patients. There were significant group by time interactions for problem-focused coping, instrumental support, positive reframing, and self-blame, indicating that participants in the OHP arm improved significantly more than those in the control group with regard to coping styles. Many interactions were significant at 3 and 6 months, but not 12 months. The OHP was successful in improving adaptive coping behaviours and decreasing maladaptive coping behaviours in the short-term, but the effects were not maintained at 12 months. Additional booster sessions may be helpful in sustaining intervention effects. This study serves as support for the importance of interventions targeting the psychosocial and physical health aspects of chronic disease to improve individuals’ overall wellbeing.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".