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Record W3197300969 · doi:10.5770/cgj.24.490

The Cultural Diversity of Dementia Patients and Caregivers in Primary Care Case Management: a Pilot Mixed Methods Study

2021· article· en· W3197300969 on OpenAlexafffundvenueabout
Xin Qiang Yang, Isabelle Vedel, Vladimir Khanassov

Bibliographic record

VenueCanadian Geriatrics Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsJewish General HospitalJewish Rehabilitation HospitalMcGill University Health CentreMcGill University
FundersFonds de Recherche du Québec - SantéFaculty of Medicine, McGill UniversityMcGill University
KeywordsMedicineDementiaDiversity (politics)Primary careCultural diversityGerontologyNursingFamily medicineDiseaseInternal medicineAnthropology

Abstract

fetched live from OpenAlex

CONTEXT: The Canadian reality of dementia care may be complicated by the cultural diversity of patients and their informal caregivers. OBJECTIVES: To what extent do needs differ between Canadian- and foreign-born patients and caregivers? What are their experiences with the illness in primary care case management? METHODS: Mixed methods, sequential explanatory design (a cross-sectional study, followed by a qualitative descriptive study), involving 15 pairs of patients and caregivers. RESULTS: Foreign-born patients had more needs compared to their Canadian-born counterparts. Foreign-born caregivers reported more stress, more problems, and increased need for services. However, the reported experiences of Canadian- vs. foreign-born individuals were similar. CONCLUSION: The results remain hypothesis-generating. The present pilot illustrated the suitability of mixed methods to this area of study, which deserves further investigation to better serve all members of a population already vulnerable by age and disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.305
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2021
Admission routes4
Has abstractyes

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Same venueCanadian Geriatrics JournalSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207