Chronically Ill Canadians' Experiences of Being Unattached To a Family Doctor: A Qualitative Study of Marginalized Patients in British Columbia
Bibliographic record
Abstract
Background: Unattached patients do not have a regular primary care provider.Initiatives are being developed to increase attachment rates across Canada.Most existing attention paid to patient unattachment has focused on quantifying the problem and health system costs.Our purpose is to qualitatively identify the implications of chronically ill patients' experiences of unattachment for health policy and planning to provide policy-relevant insights for Canadian attachment initiatives.Methods: Three focus groups were conducted with marginalized chronically ill individuals residing in a mid-sized city in British Columbia who are unattached to a family doctor.We use the term marginalized as a descriptor to acknowledge that by virtue of their low socio-economic status and lack of attachment the participants are marginalized in Canada's health care system Focus groups were structured as an open conversation organized around a series of probing questions.They were digitally recorded and transcribed verbatim.Thematic analysis was employed.Results: Twenty-six individuals participated in the focus groups.The most common chronic illnesses reported were active drug addiction or recovery (and their associated symptoms), depression, arthritis, and hepatitis C. Participants identified life transitions as being the root cause for not having a family doctor.There was a strong sense that unsuccessful attempts to get a family doctor reflected that they were undesirable patients.Participants wanted to experience having a trusting relationship with a regular family doctor as they believed it would encourage greater honesty and transparency.One of the main health concerns regarding lack of access to a regular family doctor is that participants lacked access to preventative care.Participants were also concerned about having a discontinuous medical record due to unattachment.Conclusions: Participants perceived that there are many benefits to be had by having attachment to a regular family doctor and that experiencing unattachment challenged their health and access to health care.We encourage more research to be done on the lived experience of unattachment in order to provide on-the-ground insights that policy-makers require in order to develop responsive, patient-centred supports and programs.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.055 | 0.017 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".