Person-centred, occupation-based intervention program supported with problem-solving therapy for type 2 diabetes: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Individuals with diabetes mellitus have difficulty solving problems in meaningful occupations and have similar difficulties with self-care regimens. We examined the effects of an occupation-based intervention supported with problem-solving therapy in individuals with type 2 diabetes mellitus on participation in and satisfaction with meaningful occupations, diabetes-related psychosocial self-efficacy, preferred coping strategies and individual well-being. METHODS: This study was planned as a single-blind, randomised controlled study with a 3-month follow-up involving 67 adults with type 2 diabetes. The Canadian Occupational Performance Measure, Diabetes Empowerment Scale, Brief COPE and five-item World Health Organisation Well-Being Index were used. This programme included evaluations, diabetes education, and problem-solving therapy. The intervention was conducted for 6 weeks, and each weekly session lasted approximately 60 min. Differences between groups were analysed using the Mann-Whitney U test, and the Friedman test was used to calculate group-time interaction differences (i.e., baseline, after 6 weeks and after 3 months). RESULTS: All participants identified the most significant occupational performance problems in self-care as personal care. Significant improvement was reported in the intervention group compared to the control group regarding participation in meaningful occupation, satisfaction with performance, psychosocial self-efficacy, and well-being results (p < 0.001) after the programme and 3 months of follow-up. Participant use of effective coping strategies, active coping and acceptance strategies, and self-efficacy, as revealed by the results, suggested improvement in favour of the intervention group (p < 0.05). CONCLUSIONS: Occupation-based problem-solving therapy encourages participation in meaningful occupations and improves psychosocial self-efficacy, effective coping styles, and well-being in patients with type 2 diabetes mellitus. Problem-solving therapies that incorporate individuals' priorities via meaningful occupation can be used to lead to a meaningful and quality life for individuals with type 2 diabetes mellitus. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03783598 . Retrospectively Registered. First Posted-December 21, 2018, Last Update Posted-February 18, 2020.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".