Role Expectations in Dementia Care Among Family Physicians and Specialists
Bibliographic record
Abstract
BACKGROUND: The assessment and ongoing management of dementia falls largely on family physicians. This pilot study explored perceived roles and attitudes towards the provision of dementia care from the perspectives of family physicians and specialists. METHODS: Semi-structured, one-to-one interviews were conducted with six family physicians and six specialists (three geriatric psychiatrists, two geriatricians, and one neurologist) from University of Toronto-affiliated hospitals. Transcripts were subjected to thematic content analysis. RESULTS: Physicians' clinical experience averaged 16 years. Both physician groups acknowledged that family physicians are more confident in diagnosing/treating uncomplicated dementia than a decade ago. They agreed on care management issues that warranted specialist involvement. Driving competency was contentious, and specialists willingly played the "bad cop" to resolve disputes and preserve long-standing therapeutic relationships. While patient/caregiver education and support were deemed essential, most physicians commented that community resources were fragmented and difficult to access. Improving collaboration and communication between physician groups, and clarifying the roles of other multi-disciplinary team members in dementia care were also discussed. CONCLUSIONS: Future research could further explore physicians' and other multi-disciplinary members' perceived roles and responsibilities in dementia care, given that different health-care system-wide dementia care strategies and initiatives are being developed and implemented across Ontario.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".