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Record W1824574040 · doi:10.3233/wor-2011-1201

Identity cues and dementia in nursing home intervention

2011· article· en· W1824574040 on OpenAlexafffund
Aline Vézina, Line Robichaud, Philippe Voyer, Daniel Pelletier

Bibliographic record

VenueWork · 2011
Typearticle
Languageen
FieldPsychology
TopicEducation, Healthcare and Sociology Research
Canadian institutionsHôpital du Saint-SacrementUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsIdentity (music)DementiaPsychologyPsychological interventionIntervention (counseling)Health careCategorizationQualitative researchFamily caregiversNursingMedicineSociologyPsychiatryDiseaseComputer science

Abstract

fetched live from OpenAlex

This study examines the identity cues that family caregivers and healthcare personnel use with seniors living with dementia and living in nursing homes. The identity cues represent biographical knowledge used to stimulate the dementia sufferer, trigger signals and incite interaction. Our grounded approach hinges on three objectives: to identify and categorize identity cues; to document their uses; and to gain a better understanding of their effectiveness. We interviewed nine family caregivers and 12 healthcare workers. Qualitative data indicates that the participants use identity cues that evoke seniors' sociological, relational and individual characteristics. These identity cues play a central role in communication and constitute important information that the family caregivers can share with healthcare personnel. They sustain memory, facilitate care and reinforce seniors' self-value. These results help to define identity, foster a greater role for family caregivers, and constitute a sound basis for the implementation of personalized interventions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.118
GPT teacher head0.490
Teacher spread0.372 · 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.

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
Published2011
Admission routes2
Has abstractyes

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