Primary care case management of culturally diverse dementia patients and caregivers, a pilot cross-sectional study in a Montreal Family Medicine Group
Bibliographic record
Abstract
Background: Pending the arrival of definitive treatment for dementia -an increasingly common neurodegenerative illness, clinicians look to better utilize available resources to improve patients' and their informal caregivers' quality of life.Case management is an innovative model of care and has been implemented in Quebec in select primary care clinics called Family Medicine Groups (FMG).Often nurses or social workers (also called "infirmiers-pivot" in French), case managers assess and follow dementia patients, coordinating their care and collaborating closely with other members of the healthcare team.However, little evidence exists on how this model of dementia care navigates culturally sensitive contexts, especially given the rich and diverse cultural landscape of Quebec and Montreal.Objectives: To determine the ethnocultural diversity of dementia patients and their informal caregivers of the Herzl Family Practice Centre, a FMG using case management; to determine whether Canadian born and foreign born service users had different needs and problems.Methods: 15 community-dwelling dementia patients and their 15 informal caregivers were recruited.We report descriptive statistics of their sociodemographic, ethnocultural, memory and health characteristics, in addition to (a) patient needs using the Camberwell Assessment of Need for Elderly (CANE) and (b) caregiver problems and needs using the Carers' Needs Assessment for Dementia (CNA-D).Dementia severity was measured using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA).We describe differences between Canadian born and foreign born study participants (hypothesis generating).Results: The 15 patients were on average 76.5 years old (sd: 9.2, range: 61-91), of which 10 were men, still in the early stages of cognitive decline with a mean MoCA of 22.7 (3.4,15-27).Patients reported "memory", "physical health", "money/budgeting" as common needs, and received both informal and formal help to meet most needs.The 15 caregivers were aged 72.3 years old (12.5, 41-90), with 12 women.They reported "physical or psychiatric illness" and "lack of information about dementia", "about treatment" and "about services" as common problems.They received adequate "diagnosis or treatment" from the family physician, but their needs for "support from a social worker", "printed information material" and other services were not met.Compared to their 5 Canadian born counterparts, the 10 foreign born patients had more needs (and different needs) and a lower quality of life.This may be explained by their older age, longer onset of memory symptoms, worse cognition and more behavioral symptoms.The 9 foreign born caregivers were younger than their 6 Canadian born peers, but reported more stress associated with their patient's behavioral symptoms, more problems (and different problems) and more needs (and different needs) for services.Conclusion: These findings may be clinically impactful in the care of our patient population, albeit statistically insignificant due to the small sample size.Valuable insight was gained about the conduct of research with this vulnerable population.The role that cultural diversity can play in the complex environment of dementia case management merits further investigation, in order to better serve all members of a population already vulnerable by age and disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| 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".