Occupational therapy for caregiver burden in adult palliative care: randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: This study aimed to eliminate activity limitations and improve activity performance in caregivers of patients hospitalised in palliative care units through occupational therapy intervention, enhance their coping skills with insomnia and depression, and thereby improve the activity performance and psychosocial health of caregivers. METHODS: It was carried out between 1 July 2024 and 31 September 2024, in palliative care. This cross-sectional study collected data using the Patient Demographic Form, Zarit Caregiver Burden Scale (ZCBS), Beck Depression Inventory (BDI), Pittsburgh Sleep Quality Index (PSQI) and Canadian Occupational Performance Measure (COPM). RESULTS: A total of 56 individuals (mean age 50.42±13.04 years; 18 females, 10 males) participated in our study. Before the intervention, the participants' mean total scores were 31.32±16.69 for ZCBS, 15.32±11.01 for BDI, 8.25±3.49 for PSQI and 6.75±2.74 for COPM performance scores, with satisfaction scores averaging 6.52±2.92. The preintervention total mean score on the ZCBS was 31.32±16.69, while postintervention mean score was 30.82±17.83 (p<0.05).After intervention, a statistically significant difference was found in the caregivers' ZCBS, BDI, PSQI and COPM scores compared to preintervention measurements (p<0.05). CONCLUSION: It is believed that person-centred and holistic occupational therapy interventions planned for caregivers can reduce their depression levels and improve sleep quality and activity performance. Regular assessment of caregivers' depression levels, sleep quality and activity performance, along with providing advance information on potential challenges and coping strategies, is crucial.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.003 | 0.002 |
| 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".