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Record W4223445190 · doi:10.1017/s0714980821000660

Balancing Flexibility and Administrative Burden: Experiences of Family Managers Using Directly Funded Home Care in Manitoba, Canada

2022· article· en· W4223445190 on OpenAlexafffundabout
Lisette Dansereau, Christine Kelly, Katie Aubrecht, Amanda Grenier, Allison Williams

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsMcMaster UniversityUniversity of TorontoSt. Francis Xavier UniversityUniversity of Manitoba
FundersInstitute of Health Services and Policy Research
KeywordsFlexibility (engineering)GerontologyBusinessNursingMedicineManagementEconomics

Abstract

fetched live from OpenAlex

Abstract Directly funded (DF) home care provides funding to home care recipients to coordinate their own care and supports, and is available across all Canadian provinces. Current research on DF home care focuses on the experiences of adults with disabilities self-directing their own care, but less is known about the experiences of family members managing services for adults 55 years of age and older. This article presents findings from a qualitative analysis of 24 semi-structured interviews with older adults and caregivers using the DF program in Manitoba, Canada, focusing on family manager experiences. We identify three themes in the interview data: (1) DF home care enhances choice and flexibility for older people and their caregivers, (2) choice and flexibility reduce caregiver strain , and (3) agency services reduce administrative burden. We discuss the importance of care relationships and the role of family managers. We recommend that traditional home care systems learn from DF, and that increased administrative support would reduce caregiver strain.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.298
Teacher spread0.245 · 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 teacher head, not a consensus.

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

Citations5
Published2022
Admission routes3
Has abstractyes

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