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Record W2035344290 · doi:10.1159/000113415

Functional Disability in Early Alzheimer’s Disease – A Validation Study of the Italian Version of the Disability Assessment for Dementia Scale

2008· article· en· W2035344290 on OpenAlexfundno aff
Luc Pieter De Vreese, Paolo Caffarra, Rita Savarè, Renata Cerutti, M. Franceschi, Enzo Grossi

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2008
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersMcGill University
KeywordsCronbach's alphaDementiaPsychologyMini–Mental State ExaminationAlzheimer's diseaseConstruct validityActivities of daily livingPopulationGerontologyPsychometricsDiseaseMedicineClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

AIM: To determine the applicability and psychometric properties of the Italian version of the Disability Assessment of Dementia scale (DAD-I) in a community-residing population with early-stage Alzheimer's disease (AD). METHODS: The DAD-I was administered to the primary caregivers of 159 patients (mean age +/- SD 77.1 +/- 5.2) with mild AD (mean Mini Mental State Examination, MMSE, +/- SD 23.1 +/- 2.2). RESULTS: The DAD-I showed excellent internal consistency reliability (Cronbach's alpha = 0.92) and good construct validity. The DAD-I score was not significantly associated with gender, education and presumed duration of the illness, and had a low negative correlation with age. The DAD-I score correlated moderately with the traditional Instrumental Activities of Daily Living and Activities of Daily Living scales, respectively, with r = 0.53 and r = 0.54 (p < 0.0001). Relatively low, but statistically significant correlations (r ranging between 0.21 and 0.31) with the MMSE were also found. CONCLUSION: The DAD-I was found to be a reliable and valid instrument to assess functional disability in community-dwelling Italian subjects with early-stage AD.

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)0.001
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 score0.006
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
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 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

Citations29
Published2008
Admission routes1
Has abstractyes

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