‘It’s not just the word care, it’s the meaning of the word…(they) actually care': caregivers’ perceptions of home-based primary care in Toronto, Ontario
Bibliographic record
Abstract
ABSTRACT The frail and homebound older adult populations currently experience difficulties accessing primary care in the medical office. Given this fundamental access to care problem, and the questionable care quality that arises when navigating a labyrinthine health-care system, these populations have typically been subject to inadequate primary care. To meet their needs better, growing research stresses the importance of providing comprehensive home-based primary care (HBPC), delivered by an inter-professional team of health-care providers. Family care-givers typically provide the majority of care within the home, yet their perceptions of HBPC remain under-researched. The purpose of this study was to explore unpaid care-givers' perceptions of and experiences with HBPC programmes in Toronto, Canada. We conducted qualitative inductive content analysis, using analytic procedures informed by grounded theory, to discover a number of themes regarding unpaid care-givers' understandings of HBPC. Findings suggest that, compared to the standard office-based care model, HBPC may better support unpaid care-givers, providing them assistance with system navigation and offering them the peace of mind that they are not alone, but have someone to call should the need arise. The implications of this research suggest that HBPC could be a model to help mitigate the discontinuities in care that patients with comorbid chronic conditions and their attendant unpaid care-givers experience when accessing fragmented health, home and social care systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".