The impact of interpersonal relationships on rural doctorsâ clinical courage
Bibliographic record
Abstract
INTRODUCTION: Clinical courage occurs when rural doctors push themselves to the limits of their scope of practice to provide the medical care needed by patients in their community. This mental strength to venture, persevere and act out of concern for one's patient, despite a lack of formally recognised expertise, becomes necessary for doctors who work in relative professional isolation. Previous research by the authors suggested that the clinical courage of rural doctors relies on the relationships around them. This article explores in more depth how relationships with others can impact on clinical courage. METHODS: At an international rural medicine conference in 2017, doctors who practised rural/remote medicine were invited to participate in the study. Twenty-seven semistructured interviews were conducted exploring experiences of clinical courage. Initial analysis of the material, using a hermeneutic phenomenological frame, sought to understand the meaning of clinical courage. In the original analysis, an emic question arose: 'How do interpersonal relationships impact on clinical courage'. The material was re-analysed to explore this question, using Wenger's community of practice as a theoretical framework. RESULTS: This study found that clinical courage was affected by the relationships rural doctors had with their communities and patients, with each other, with the local members of their healthcare team and with other colleagues and health leaders outside their immediate community of practice. CONCLUSION: As a collective, rural doctors can learn, use and strengthen clinical courage and support its development in new members of the discipline. Relationships with rural communities, rural patients and urban colleagues can support the clinical courage of rural doctors. When detractors challenge the value of clinical courage, it requires individual rural doctors and their community of practice to champion rural doctors' way of working.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".