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Record W2078357997 · doi:10.12968/bjcn.2004.9.8.15359

Assessing cognitive impairment in older people: the Watson clock drawing test

2004· article· en· W2078357997 on OpenAlexaff
Christopher Armstrong Esther, Brad Hagen, Mark L. Sandilands, Christine Smith

Bibliographic record

VenueBritish Journal of Community Nursing · 2004
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsMedicineCognitionTest (biology)Cognitive impairmentCognitive declineGerontologyIntervention (counseling)WatsonCognitive testClinical psychologyPsychiatryDementiaDisease

Abstract

fetched live from OpenAlex

A non-random sample of 331 community-based clients aged 75 years and over, who were being cared for at home, were involved in a longitudinal study to assess cognitive impairment (CI). The clock drawing test (CDT) using the Watson et al (1993) scoring protocol was used to determine its utility as a tool for community nurses to assess CI. In the first phase of the study, 294 CDTs were used in analysis and 58.8% (n = 172) of participants were cognitively impaired. Subsequent assessments at 9 months and 18 months using both the CDT and the Mini-Mental State Examination (MMSE) confirmed the high initial level of cognitive impairment among the sample. Over the course of the study 37 participants who had high CDT scores were admitted to institutional care and their cognitive status continued to decline. Among those who remained in the community, the percentage with some degree of cognitive impairment remained high, and over the course of the study there was a significant linear decline in the mean MMSE score. The CDT takes less time to administer than the MMSE and appears to be a more sensitive tool for detecting early changes in cognition. The CDT could therefore be useful as an initial assessment tool by community mental health nurses to help facilitate early intervention for older clients who are beginning to experience cognitive changes.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.027
GPT teacher head0.363
Teacher spread0.336 · 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

Citations5
Published2004
Admission routes1
Has abstractyes

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