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Record W2136034542 · doi:10.1017/s0714980814000014

Structure factorielle d’une version française du Nursing Home Behavior Problem Scale

2014· article· en· W2136034542 on OpenAlexaff
July Fraser, Philippe Landreville, Philippe Voyer, Pierre‐Hugues Carmichael

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2014
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCentre hospitalier universitaire de QuébecUniversité Laval
Fundersnot available
KeywordsDementiaFrenchNursing homesScale (ratio)PsychologyFactorial analysisGerontologyFactorialNursingMinimum Data SetClinical psychologyMedicineHumanitiesStatisticsMathematicsGeographyCartographyDisease

Abstract

fetched live from OpenAlex

Several measuring devices are available to assess specific behavioural problems of dementia patients residing in nursing homes but only a few have been translated and validated in French. This study's main objective was to determine the factorial structure of the French version of the Nursing Home Behavior Problem Scale (NHBPS) with people suffering from dementia. A secondary objective was to document the variables associated with the global score of the NHBPS and the underlying dimensions of the instrument. Participants (n = 155) were diagnosed with dementia and resided in three nursing homes and a hospital's long-term care unit. The presence of behavioural problems and other characteristics were assessed by two nurses. A factor analysis revealed five key dimensions in the francophone version of the questionnaire. Several variables were associated with the total score of the NHBPS and its five underlying dimensions. Although the factorial solution of the French version of the NHBPS is similar to the English versions, our results also show differences that may depend on methodological characteristics.

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)0.011
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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 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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissement→Same topicDementia and Cognitive Impairment Research→French-language works237,207→