Identifying dementia care needs of family physicians, people living with dementia, and care partners in Canada: Results of a national survey
Bibliographic record
Abstract
Abstract Background There is consensus that timely detection, diagnosis and ongoing care of people with dementia is primarily the responsibility of family physicians in Canada. Yet evidence indicates low to moderate diagnosis rates and significant challenges in management of dementia. With the growing number of Canadians living with dementia, there is an increasing need to develop effective practice tools for family physicians and to understand the needs of people living with dementia and their caregivers. This nationwide study was conducted to identify the gaps in tools currently being used, and to identify the domains of care that people with lived experience of dementia and their caregivers feel are being done well, and those that require improvement by their family physician. Method Three nationwide surveys were distributed to target audiences: the 39‐item Dementia Care Needs Assessment Survey for family physicians, the 35‐item Dementia Journey Survey: Caregiver Experience for caregivers, and the 33‐item Dementia Journey Survey: Living with Dementia Experience for persons living with dementia. Survey questions were both multiple choice and open‐ended. Descriptive analyses were conducted on closed‐ended survey questions. Qualitative analyses of open‐ended questions were both inductive, based on observed patterns, and deductive, based on the study objectives. Result The surveys received 288 physician, 78 people with dementia, and 485 care partner responses. Preliminary analysis indicates consensus between physicians, people with dementia, and care partners on 15 of 22 barriers to diagnosis and care. Barriers highlighted included gaps in education and support, community resources, and access to specialists, as well as the need for improved communication around care and diagnosis. A further 4 themes were highlighted by physicians and 3 themes by people with dementia that did not overlap, indicating divergent needs. 24.7% of physicians reported using practice tools for dementia care, 10% of whom use only 1 tool for all aspects. Conclusion Optimal primary care is a cornerstone of a comprehensive approach to supporting people with dementia and their care partners. Identifying gaps in knowledge and tools to support practice and developing new educational programs that are aligned with the needs of people with dementia are vital to improve primary dementia care.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".