MétaCan
Menu
Back to cohort
Record W4392287376 · doi:10.1177/10497323241231425

How Community-Based Health and Social Care Professionals Support Unpaid Caregivers: Experiences From One Health Authority in Ontario, Canada

2024· article· en· W4392287376 on OpenAlexaffabout
Jodi Webber, Marcia Finlayson, Kathleen E. Norman, Tracy J. Trothen

Bibliographic record

VenueQualitative Health Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsQueen's UniversityAlgoma University
Fundersnot available
KeywordsOperationalizationThematic analysisNursingHealth carePublic relationsPsychologyPopulationQualitative researchSociologyMedicinePolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

In Ontario, Canada, rising rates of caregiver distress have been the 'canary in the coal mine' for a health system out of balance with the needs of an ageing population. Community-based health and social care professionals are well placed to play an important role in the caregiver support process; however, a gap has remained in the understanding of if and how caregiver support strategies are operationalized or experienced by community service providers (CSPs). The goal of this study was to describe how CSPs interpreted policy and how those interpretations may enable their work in supporting unpaid caregivers. Using a qualitative constructionist design, we interviewed 24 participants and reviewed 92 publicly available documents. Braun and Clarke's method of thematic analysis was used for analysis strategy. Four overarching themes were identified: (1) community care as a priority, (2) sidewalk accountability, (3) creative care planning through partnerships, and (4) challenges to care delivery. We found that the importance of caregivers to the health system was reflected in organizational policy and strategy. There is an opportunity to improve health outcome for caregivers and the population alike through strong leadership and a clear shared vision. Our findings also suggested that social capital was a significant factor in enabling providers in their work, leveraging long-standing relationships, and accumulated local knowledge to implement highly creative care plans.

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)0.043
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.474
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.007
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 head0.883
GPT teacher head0.750
Teacher spread0.133 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueQualitative Health ResearchSame topicHealth Policy Implementation ScienceFrench-language works237,207