Apathy in Older Adults With and Without Dementia: An Integrative Review of Barriers and Facilitators to Care
Bibliographic record
Abstract
Despite the detrimental impact of apathy on the cognition, functional abilities, and quality of life of older people, it is often under-rated and under-managed. This integrative review provides a comprehensive overview of the barriers as well as potential facilitators to optimal care for older adults with apathy. A systematic search for relevant literature using Whittemore and Knafl’s framework was conducted to identify factors that inhibit or facilitate optimal detection and intervention for apathy in older people with and without dementia. Four key barriers were identified including lack of standardized definition of apathy, lack of awareness, overlap with other disorders, and methodological limitations of clinical trials. Key facilitators included involvement of the dyad (persons with apathy and their families/formal caregivers), education, training and experience, and adoption of new and innovative method of screening and intervention. To provide optimal care for older people with apathy, there is need to adopt a multifaceted approach, including the development of precise definition of apathy, consideration of person-centered approach, caregiver training, and best practice guidelines for management of apathy. Future research and practice into effective interventions for management of apathy in older adults, and enhanced education and training for healthcare professionals, are needed to ensure quality of care for older adults with apathy.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".