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Record W2732778325 · doi:10.1093/geroni/igx004.3480

VALIDATION OF PRIMARY CARE QUESTIONNAIRES ON KNOWLEDGE, ATTITUDES, AND PRACTICES TOWARD DEMENTIA

2017· article· en· W2732778325 on OpenAlexaffabout
Nadia Sourial, Geneviève Arsenault‐Lapierre, Marine Hardouin, Isabelle Vedel

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsDementiaExploratory factor analysisConstruct (python library)PsychologyCognitionConstruct validityDiseaseChristian ministryClinical psychologyMedicineFamily medicinePsychometricsPsychiatry

Abstract

fetched live from OpenAlex

In 2013, the Quebec Ministry of Health implemented a reform called the ‘Alzheimer Plan’ in 42 family medicine groups (FMG) to better manage dementia patients in primary care. We created and validated two questionnaires to measure the clinicians’ knowledge, attitudes, and practices regarding dementia care in each FMG. Based on the literature and content validation with experts, one 72-item questionnaire for family physicians and another 70-item questionnaire for nurses and other health professionals were created. The questionnaires were distributed to 865 clinicians after the beginning of the AD plan. Exploratory factor analysis (EFA) was performed to examine the construct validation of each questionnaire and determine the underlying subscales. Prior to the EFA, a clinically-relevant structure of subscales was elaborated. Five subscales were identified within the physicians’ questionnaire: 1) perceived competency and knowledge, 2) attitudes toward the AD Plan, 3) practices for cognitive evaluation, 4) attitudes toward the disease, and 5) collaboration with nurses and other professionals. Four subscales were identified within nurses and other professionals’ questionnaire: 1) perceived competency and knowledge, 2) attitudes toward the AD Plan, 3) attitudes toward the dementia patients and their care-givers, and 4) perceived support from external resources. These subscales were consistent with the a priori clinically-derived structure. Items within the subscales correlated well together and differentiated well across subscales.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.414
Teacher spread0.352 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2017
Admission routes2
Has abstractyes

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