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Record W7098170405

Research Family physicians ’ perspectives on care of dementia patients and family caregivers

2015· article· en· W7098170405 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaFocus groupGrounded theoryFamily caregiversQualitative researchAmbulatory careAmbulatoryDisease
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE To identify factors that facilitate or impede family physicians in ambulatory care of patients with dementia and the family caregivers of such patients. DESIGN Explanatory qualitative analyses of focus group discussions. SETTING Large, medium, and small urban; suburban; and rural family practices from various regions of the province of Quebec. PARTICIPANTS Twenty-five family doctors whose practices had at least 75 % ambulatory patients; of these patients, an estimated minimum of 20 % were 65 years old or older and at least 2 % suffered from dementia. METHOD Physicians were recruited by telephone to be paid participants in their regions in focus groups studying aspects of dementia care in ambulatory settings. Grounded theory and constant comparative methods were used to explore data from 3 French-speaking focus groups and 1 English-speaking focus group. MAIN FINDINGS Physicians were 72 % male, had a mean of 21.3 years in practice, and spent about 87 % of their professional time in office practice. An estimated 38.7 % of their patients were 65 years old or older, and 5.6% of these patients had Alzheimer disease or related dementias. Physicians were comfortable caring for these patients and their family caregivers but thought much of this care should come from support services offered

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)0.013
metaresearch head score (Gemma)0.037
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 score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.086
GPT teacher head0.263
Teacher spread0.177 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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