In search of attachment: a qualitative study of chronically ill women transitioning between family physicians in rural Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Most Canadians receive basic health services from a family physician and these physicians are particularly critical in the management of chronic disease. Canada, however, has an endemic shortage of family physicians. Physician shortages and turnover are particularly acute in rural regions, leaving their residents at risk of needing to transition between family physicians. The knowledge base about how patients manage transitioning in a climate of scarcity remains nascent. The purpose of this study is to explore the experience of transitioning for chronically ill, rurally situated Canadian women to provide insight into if and how the system supports transitioning patients and to identify opportunities for enhancing that support. METHODS: Chronically ill women managing rheumatic diseases residing in two rural counties in the province of Ontario were recruited to participate in face-to-face, semi-structured interviews. Interview transcripts were analysed thematically to identify emergent themes associated with the transitioning experience. RESULTS: Seventeen women participated in this study. Ten had experienced transitioning and four with long-standing family physicians anticipated doing so soon. The remaining three expressed concerns about transitioning. Thematic analysis revealed the presence of a transitioning trajectory with three phases. The detachment phase focused on activities related to the termination of a physician-patient relationship, including haphazard notification tactics and the absence of referrals to replacement physicians. For those unable to immediately find a new doctor, there was a phase of unattachment during which patients had to improvise ways to receive care from alternative providers or walk-in clinics. The final phase, attachment, was characterized by acceptance into the practice of a new family physician. CONCLUSIONS: Participants often found transitioning challenging, largely due to perceived gaps in support from the health care system. Barriers to a smooth transition included inadequate notification procedures, lack of formal assistance finding new physicians, and unsatisfactory experiences seeking care during unattachment. The participants' accounts reveal opportunities for a stronger system presence during transition and a need for further research into alternative models of primary care delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".