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Record W158328767

The dining experience of residents with dementia in long-term care facilities

2008· dissertation· en· W158328767 on OpenAlexaboutno aff
Mei Lillian kuen Hung

Bibliographic record

VenueSummit (Simon Fraser University) · 2008
Typedissertation
Languageen
FieldNursing
TopicNutrition, Health and Food Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsLong-term careDementiaTerm (time)GerontologyMedicinePsychologyNursingPathology
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study aimed to explore the dining experience of residents with dementia in long-term care facilities, with a focus on the psychosocial aspect of their experiences. Data were collected by multiple methods, including participant observation and conversational interviews with residents with dementia, focus groups with staff, and examination of documents at two urban facilities in British Columbia, Canada. Data analysis revealed eight themes: (1) Outpacing/ Relaxed pace, (2) Withholding/ Holding, (3) Stimulation, (4) Disrespect/ Respect, (5) Invalidation/ Validation, (6) Distancing/ Connecting, (7) Disempowerment/ Empowerment, and (8) Ignoring/ Inclusion. These themes provide a clear set of factors that affect the quality of residents' experiences and offer insights into the processes of how multiple factors influence the residents' experiences in complex ways. The results suggest that although staff approaches significantly impact residents' experiences, the physical environment and organizational milieu are also responsible for hindering and facilitating staff to provide care.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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