Can Occupation-Based Interventions for People Living with Dementia and Their Spousal Caregivers Support Positive Aspects of Caregiving? A Scoping Review
Bibliographic record
Abstract
This scoping review aimed to explore the characteristics and outcomes of occupation-based interventions for people living with dementia and their spousal caregivers relating to positive aspects of caregiving. A conceptualization of positive aspects of caregiving was developed based on the existing literature encompassing three domains - quality of the caregiver/care receiver relationship, meaning of the caregiver's role in daily life, and caregiver's feeling of accomplishment. Arksey and O'Malley's guidelines were used and four databases were searched to identify studies discussing occupation-based interventions involving spousal caregivers and persons living with dementia in the community that addressed at least one of three domains of positive aspects of caregiving identified in our conceptualization. After screening 1,560 articles, 18 articles were included for analysis. Three types of interventions were identified (i.e. music therapy, reminiscence therapy and a tailored activity program) involving three components contributing to positive aspects of caregiving: socializing outside the dyad, producing tangible end products, and education for the caregiver or dyad. Findings indicate that occupation-based interventions can support positive experiences for the dyad by improving the quality of the dyadic relationship and caregivers' feelings of accomplishment.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".