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Description of retained abilities in older persons with dementia

2000· article· en· W1970374753 on OpenAlexaff
Donna L. Wells, P Dawson

Bibliographic record

VenueResearch in Nursing & Health · 2000
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDementiaPsychologyGerontologyCognitionClinical psychologyDevelopmental psychologyPsychiatryMedicineDisease

Abstract

fetched live from OpenAlex

There have been suggestions in the literature that the care of people with dementia must be focused on abilities as opposed to disabilities. However, this approach has not been carefully defined in terms of what constitutes remaining abilities. This article provides a description of the abilities in people with dementia, which is based on a descriptive analysis of data derived from a larger study regarding the psychometric evaluation of an abilities assessment instrument. The sample comprised 112 male veterans with dementia who were living in a long-term care facility. Their mean age was 75 years. Data were collected in the areas of self-care, social, interactional, and interpretive abilities. Abilities were retained in all four areas. Furthermore, abilities were differently affected and varied considerably across subjects, which is consistent with evidence pertaining to cognitive changes in dementia. Our results provide support for an individualized, abilities-focused approach to the care of people with dementia.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.432
Teacher spread0.361 · 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 designQualitative
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

Citations24
Published2000
Admission routes1
Has abstractyes

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