Formulating recommendations to improve care for persons living with dementia: deliberative dialogues with multiple stakeholders in the province of Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: Persons living with dementia and their care partners encounter many challenges within the health and social care system, including lack of information, support, counselling, and access to community services, as well as significant staff turnover in home care services. The objective of this study was to work with multiple stakeholders to formulate relevant and feasible recommendations to improve care for persons living with dementia and their care partners in Quebec, Canada. METHODS: We conducted deliberative dialogues in the context of a large mixed methods study on the care of persons living with dementia and care partners. First, we organized two deliberative dialogues with care partners to formulate recommendations informed by the quantitative and qualitative results of the large study. These recommendations were further discussed in a third deliberative dialogue focused on the prioritization of relevant and feasible recommendations by clinicians, health project managers, and decision-makers. We performed a thematic analysis of the data using a multi-level framework: structural, organizational, provider, and patient perspectives. RESULTS: Participants formulated 14 recommendations. Two structural-level recommendations included fighting ageism and ensuring the same access to services in the whole province. Three organizational-level recommendations involved improving interdisciplinarity collaboration, improving access and follow-up in primary care, and adapting emergency departments. Additionally, two organizational-level recommendations were specific to healthcare crisis management (such as the COVID-19 pandemic): ensuring both the regular communication and the flexibility of implemented rules. Four provider-level recommendations encompassed providing more training on dementia, offering more training on levels of care, reviewing the relationship-based approach in training programs, and revising and optimizing medications. There were three patient-level recommendations including strengthening partnerships with persons living with dementia and care partners, guaranteeing personalized services and care, and reinforcing support for care partners. CONCLUSION: The deliberative dialogues enabled us to formulate relevant recommendations based on research evidence, the lived experience of care partners, and the expertise of clinicians, health project managers and decision-makers. The results revealed several recommendations that will help mitigate the challenges faced by persons living with dementia and care partners in the health and social care system by informing policies and practices.
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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 | 0.027 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.041 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".