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Record W2769344251 · doi:10.22605/rrh4285

Understanding how emergency medicine physicians survive and thrive in rural practice: a theoretical model

2017· article· en· W2769344251 on OpenAlexafffundabout
Ashra Kolhatkar, Andrea Keesey, Bob Bluman, Brenna M. Lynn, Tandi Wilkinson

Bibliographic record

VenueRural and Remote Health · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsInstitute of Health Services and Policy ResearchUniversity of British Columbia Hospital
FundersUniversity of British ColumbiaDoctors of BC
KeywordsMedicineFailure to thriveFamily medicinePsychologyMedical educationNursingPediatrics

Abstract

fetched live from OpenAlex

INTRODUCTION: The challenges facing emergency medicine (EM) services in Canada reflect the limitations of the entire healthcare system. The emergency department (ED) is uniquely situated in the healthcare system such that shortcomings in hospital- and community-based services are often first revealed there. This is especially true in rural settings, where there are additional site-specific barriers to the provision of EM care. Existing studies look at the factors that influence rural EM physicians in isolation. This study uses a qualitative approach and generates a theoretical model that describes the complex interplay between major factors that influence the experience of rural EM physicians. METHODS: Eight focus groups were conducted with 39 physicians from rural British Columbia, Canada. Semi-structured focus group protocols were designed to leverage the diversity of the focus groups, which included rural generalists, full-time EM practitioners, physicians from very small and remote communities, locums, international medical graduates, physicians new to practice, and physicians who no longer practice rural EM. Following the principles of grounded theory, interview probes were adjusted iteratively to reflect emerging findings. Transcripts were analysed to identify codes and major themes, which served as the basis for the theoretical model. RESULTS: The theoretical model reveals how the causal conditions (a lack of medical and human resources, and the isolation of rural communities due to topography, distance, and inclement weather) contribute to physicians' common experience of feeling fearful and under-supported at work. Two core phenomena emerge as important needs: supportive professional relationships, and healthcare system adaptability. Contextual factors such as remuneration and continuing medical education funding, and the intervening conditions of physicians' rural exposure during formative years, also have an effect. Physicians create innovative solutions to address the challenges that arise in the practice of rural EM. Ultimately, the ability to manage the pressures of rural EM leads physicians to either thrive in or leave rural EM practice. CONCLUSIONS: The theoretical model provides a more complex view of the realities of rural EM care than has been previously described. It identifies factors that enable and hinder rural EM physicians in their practice, and provides an understanding of the strategies they employ to navigate challenges. Some elements of the theoretical model have been previously identified. For example, existing work has found that many rural physicians experience fear and anxiety in their practice. The challenges posed by the variation in rural practice environments have also been previously identified as an important influence. Other elements of the theoretical model, and the common need for practitioners to creatively respond to barriers arising from the healthcare system's inability to respond to local needs, have not been previously identified. This work finds these factors to be a common experience for participants, and as such, more widespread recognition of the importance of these factors could lead to system improvements. Future research is needed to test the hypotheses proposed in this study and explore the generalizability of the findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0080.021
Scholarly communication0.0070.009
Open science0.0030.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.136
GPT teacher head0.473
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2017
Admission routes3
Has abstractyes

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