PROMOTING PARTICIPATION IN OCCUPATIONS AMONG OLDER ADULTS LIVING WITH NEUROCOGNITIVE DISORDERS AND CAREGIVERS
Bibliographic record
Abstract
Abstract Participation in meaningful occupations promotes self-confidence, self-esteem, overall health, and healthier life transitions. Due to significant life changes brought by neurocognitive disorders older adults living with neurocognitive disorders as well as caregivers may undergo some disruption in their occupational participation. Few interventions have focused on their ability to engage in meaningful occupations independently and together to successfully orchestrate their life to meet their own occupational needs. The goal of this study was to document the priority needs of older adults living with neurocognitive disorders and caregivers to promote occupational participation, to guide us in the development of an intervention. To this end, a rapid literature review was conducted. Three databases (Medline, PsycInfo and CINAHL) were searched. Studies were included if they used qualitative methods, included community-based individuals and were available in English or French. A total of 20 studies met the inclusion criteria. Two needs were prioritized in the literature by both older adults living with neurocognitive disorders and caregivers: 1) to continue participating in daily activities and social roles (e.g., maintain the connection with the community, use everyday technology), 2) to educate the public about the disease (e.g., bring awareness, knowledge, and understanding of dementia among the community at large). In the presentation we will discuss how the results will inform the development of an occupational-based intervention to promote meaningful occupations.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".