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Record W1890198070 · doi:10.1017/s0144686x15000276

A qualitative study of nursing assistants' awareness of person-centred approaches to dementia care

2015· article· en· W1890198070 on OpenAlexaff
Paulette V. Hunter, Thomas Hadjistavropoulos, Sharon Kaasalainen

Bibliographic record

VenueAgeing and Society · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsMcMaster UniversityUniversity of ReginaUniversity of Saskatchewan
Fundersnot available
KeywordsDementiaNursingPsychologyAged careQualitative researchPerson-centered careWork (physics)MedicineHealth careSociologyPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Recently, the number of education programmes addressing person-centred approaches to long-term residential dementia care has increased, and nursing assistants (NAs) are often the target audience. The effectiveness of employee education programmes is actively debated, and our objective is to contribute to this discussion by exploring the knowledge NAs acquire through practice. We examined approaches to person-centred care generated during a series of interviews with NAs, and compared these to the content of five frameworks for person-centred dementia care. Our results suggest that although NAs acquire significant knowledge about person-centred dementia care during the course of their work, application of person-centred care strategies varies across NAs. We propose ways of enhancing NA education in order to address gaps in knowledge. We also recommend sustained attention to organisational factors that contribute to variability in practice.

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)0.020
metaresearch head score (Gemma)0.032
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.032
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.408
GPT teacher head0.463
Teacher spread0.055 · 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

Citations23
Published2015
Admission routes1
Has abstractyes

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