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Record W4406217469 · doi:10.1177/07334648241308726

Identifying Needs and Support Services for Family Caregivers of Older Community-Based Family Members: Mixed-Method Research Findings

2025· article· en· W4406217469 on OpenAlexafffundabout
Donna M. Wilson, Jennifer Heron, Gilbert BANAMWANA

Bibliographic record

VenueJournal of Applied Gerontology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Alberta
FundersGovernment of Alberta
KeywordsFamily caregiversFamily supportCommunity serviceNursingFamily memberWork (physics)BusinessGerontologyMedicinePsychologyFamily medicinePublic relationsPolitical science

Abstract

fetched live from OpenAlex

A recent Canadian study conducted in one province identified family caregiver support needs and essential support services when caring for older community-based family members requiring assistance with activities of daily living. Weekly interviews of 150 volunteer caregivers over 6 months identified 11 support needs and 5 essential support services. Scoping literature reviews of the 11 needs found they had all been identified before. Program logic investigations of the 5 support services identified a patch-work of temporarily available support services in existence across the province. Two governmental policies are recommended: (a) provincial policy assuring access to the five support services, and (b) federal policy for federal-provincial funding transfers to address the provincial cost of assured community-based support services. Family caregivers require this support to maintain their own and their family member's well-being, particularly as this caregiving prevents or delays older family member hospitalizations and nursing home entry.

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)0.062
metaresearch head score (Gemma)0.082
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 score0.155
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.082
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0040.002
Scholarly communication0.0060.002
Open science0.0020.003
Research integrity0.0010.001
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 head0.115
GPT teacher head0.470
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

Citations4
Published2025
Admission routes3
Has abstractyes

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