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Record W2104524677 · doi:10.1080/13607860600963422

Measurement and analysis of behavioural disturbance among community-dwelling and institutionalized persons with dementia

2007· article· en· W2104524677 on OpenAlexaffabout
Norm O’Rourke, Michel Bédard, Yaacov G. Bachner

Bibliographic record

VenueAging & Mental Health · 2007
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsLakehead UniversitySimon Fraser University
Fundersnot available
KeywordsDementiaGerontologyPsychologyScale (ratio)DiseaseMedicineDemographyGeography

Abstract

fetched live from OpenAlex

Census data suggest that persons over 84 years of age represent the fastest growing segment of populations in most western nations. As advancing age remains the single strongest risk factor for dementia, prevalence rates are expected to increase substantially in coming years. This awareness underscores the need to more fully understand the clinical presentation of Alzheimer disease and other neurodegenerative disorders. The present study examines responses to the 28-item Dementia Behaviour Disturbance Scale (DBD; Baumgarten, Becker, & Gauthier, 1990) among a national sample of persons with dementia (PWD) in Canada. A 3-factor solution appears to best reflect DBD responses for both institutionalized and community-dwelling PWD. This finding is notable given that the former was significantly more impaired and presented with significantly greater levels of behavioural disturbance. Support for the factorial validity of these constructs is provided relative to caregiver burden and depressive symptomatology. Of note, only 14 of 28 DBD items were retained in our analyses; on this basis, we propose the use of an abridged version of the scale. These findings can be generalized with greater confidence given the random and representative nature of the PWD and caregiver samples.

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)0.002
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 score0.005
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.056
GPT teacher head0.345
Teacher spread0.289 · 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

Citations10
Published2007
Admission routes2
Has abstractyes

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