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Adult Day Care: Northern Perspectives

2003· article· en· W2006094704 on OpenAlexaffabout
Linda Ritchie

Bibliographic record

VenuePublic Health Nursing · 2003
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsBrock University
Fundersnot available
KeywordsRespite careFocus groupContext (archaeology)Qualitative researchExploratory researchNursingPerceptionPsychologyMedicineGerontologySociologyGeography

Abstract

fetched live from OpenAlex

This qualitative study explores older adults', caregivers', and nurses' perceptions regarding adult day care (ADC). The study took place in two small towns and one small city in the northern interior region of British Columbia, Canada, with the intent to develop ADC programs that reflect the needs of older persons and their caregivers. The 32 participants contributed their perceptions in focus groups and individual interviews. The interviews, in this descriptive/exploratory study, were audiotaped, transcribed verbatim, and analyzed using inductive, qualitative techniques. The participants acknowledged ADC services as essential to the health and well-being of older adults and their caregivers. The major themes that emerged were need for respite; aging in place; ADC programming; program characteristics; staff knowledge, skills, and attitudes; and northern perspectives. The study participants identified a number of possible reasons for underuse of ADC programming in the north. This study provides information that can facilitate the grounding of ADC policy within the clients' perspectives and a northern context. The participants' thoughts also highlight areas of policy that have broad applicability to the provision of services to the elderly in any setting.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.005
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.053
GPT teacher head0.408
Teacher spread0.355 · 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

Citations22
Published2003
Admission routes2
Has abstractyes

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