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Record W2106512600 · doi:10.1017/s0144686x01008236

Seniors' experiences of client-centred residential care

2001· article· en· W2106512600 on OpenAlexafffundabout
Jacquie Eales, Norah Keating, Annita Joy. Damsma

Bibliographic record

VenueAgeing and Society · 2001
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Alberta
FundersHealth Canada
KeywordsContentmentStaffingPerspective (graphical)Qualitative researchNursingPsychologySocial psychologySociologyMedicine

Abstract

fetched live from OpenAlex

The philosophy concerning long-term care for frail seniors has shifted from a provider-driven, medical model toward a more client-centred, social model. While this philosophy emphasises the decision-making abilities of clients and respect for their values and preferences, evidence suggests that there are difficulties in understanding and implementing the philosophy. Qualitative in-depth interviews were conducted with residents of adult family living and assisted living programmes in western Canada to better understand the elements that residents themselves felt were integral to client-centred care. Three main themes emerged from the data analysis: (1) the physical setting, people within the setting, and the community were important areas of expression of residents' values and preferences; (2) the decision about where to live influenced whether the residential care environment was congruent with residents' values and preferences; (3) contentment resulted when there was a good fit between preferences and experiences, reflecting the essence of residents' perspective of client-centred care. Choices among models of care, appropriate staffing levels and training, and recognition of family contributions may improve the practice of client-centred 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)0.005
metaresearch head score (Gemma)0.009
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0040.002
Open science0.0010.006
Research integrity0.0020.003
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 head0.026
GPT teacher head0.347
Teacher spread0.321 · 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

Citations42
Published2001
Admission routes3
Has abstractyes

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