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Record W2042296627 · doi:10.1177/0733464807312236

Caregivers' Aspirations, Realities, and Expectations: The CARE Tool

2008· article· en· W2042296627 on OpenAlexaffabout
Janice Keefe, Nancy Guberman, Pamela Fancey, Lucy Barylak, Daphné Nahmiash

Bibliographic record

VenueJournal of Applied Gerontology · 2008
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsCentre de Santé et de Services Sociaux CavendishUniversité du Québec à MontréalMount Saint Vincent University
Fundersnot available
KeywordsNova scotiaFocus groupPsychologyFamily caregiversNursingNeeds assessmentMedical educationGerontologyMedicineSociology

Abstract

fetched live from OpenAlex

Caregivers to family and friends are increasingly recognized as essential players in the continued shift of care of dependent populations to the community. Currently, Canadian provincial home care programs have neither a comprehensive policy nor an assessment regarding caregivers' needs. This article describes an assessment tool that takes into account caregivers' reality and conditions and that situates them as essential partners with the formal system and reports on the validation and reliability testing of this tool. Seven sites in Quebec and Nova Scotia involving 40 assessors tested the tool with 168 caregivers. Results suggest that this comprehensive tool enables practitioners to understand caregivers' needs and situations. Focus groups with assessors and interviews with home care administrators revealed that the tool increased worker understanding and awareness of what it means to be a caregiver, ascertained the key caregiver concerns, and identified these needs in rapid succession.

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)0.011
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0000.001
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 head0.062
GPT teacher head0.354
Teacher spread0.292 · 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 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

Citations40
Published2008
Admission routes2
Has abstractyes

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