Support for rural practice: female physicians and the life–career interface
Bibliographic record
Abstract
INTRODUCTION: The need for family physicians in rural areas across the USA and Canada is a longstanding issue that has been well documented. Since family physicians constitute the largest population of rural practitioners, the problem has been exacerbated by a sharp decline in medical students' interest in the field of family medicine and the aging of the current rural workforce. Previous research has shown that female physicians in rural areas need strong support networks to maintain a healthy work-life balance. The purpose of this study was to better understand the types of support they need and how they find it, as well as how their needs change over time. METHODS: Twenty physicians from the same rurally focused family medicine residency were interviewed over a 3-month period using a semi-structured format. Physicians ranged in experience from 1 year out of residency to 25 years out of residency. Using a phenomenological approach, interviews were transcribed and then coded and analyzed by three members of the research team, one of them an experienced qualitative researcher, who met periodically to reflect on the process of coding. Emergent subthemes and themes were discussed by the multidisciplinary team. RESULTS: The participants discussed in detail the types of support they relied on and the continuing challenges of maintaining a healthy work-life interface. Main themes included the need to select carefully one's life partner and practice partners and the difficulties in setting up practice in an area without family, friends or professional mentors nearby. Although forming boundaries was important, so was developing close relationships with patients and their families. The one thing that sustained all of the physicians was a meaningful relationship with their patients. The doctor-patient connection is what brings joy and helps every one of them cope with the harder aspects of life in rural areas. CONCLUSION: The general consensus of respondents was that the career-life interface varies across individuals, changes over time and is always a work in progress. Rural female physicians think of their work in relational terms, and it involves a great deal of emotional labor. Support systems mitigate the psychological effects of this labor and help physicians develop resilience in managing both career and life. Educators can better prepare female physicians by discussing the costs and benefits of emotional labor and the necessity of support networks, as well as how to negotiate a contract that is consistent with one's values, practice style and family life.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".