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Record W4401079165 · doi:10.1186/s12909-024-05737-z

Factors associated with satisfaction of the australian rural resident medical officer cadetship program: results from a cross-sectional study

2024· article· en· W4401079165 on OpenAlexaff
Phillipa Kensit, Md Irteja Islam, Robyn Ramsden, Louise Geddes, Yann Guisard, Chris Russell, Alexandra Martiniuk

Bibliographic record

VenueBMC Medical Education · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLogistic regressionOfficerAttendanceCross-sectional studyWorkforceMedicineMentorshipGraduation (instrument)Family medicineTest (biology)Rural areaMedical educationPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Australian Rural Resident Medical Officer Cadetships are awarded to medical students interested in a rural medical career. The Rural Residential Medical Officer Cadetship Program (Cadetship Program) is administered by the Rural Doctors Network on behalf of the NSW Ministry of Health. This study aimed to assess the overall experience of medical students and key factors that contributed to their satisfaction with the Cadetship Program. METHODS: A quantitative cross-sectional study was conducted among 107 former cadets who had completed the Cadetship Program. Data on medical students' experience with the Cadetship Program (outcome variable) and potential explanatory variables were collected using a structured self-administered questionnaire. Explanatory variables included gender, geographical location, rural health club membership, rural clinical school attendance, financial support, mentorship benefits, networking opportunities, influence on career decisions, opportunity for preferential placements, and relocation. Both bivariate (Pearson's chi-squared test) and multiple logistic regression analysis were employed to identify the factors associated with medical students' overall experience with the Cadetship Program. The non-linear analysis was weighted to represent the rural/remote health workforce, in Stata/SE 14.1. RESULTS: Our results indicate that 91% of medical students were satisfied with the Cadetship Program. The logistic regression model identified two significant predictors of a positive experience with the Cadetship Program. Medical students who perceived financial support as beneficial were significantly more likely to report a satisfactory program experience (aOR = 6.22, 95% CI: 1.36-28.44, p = 0.019) than those who perceived financial support as not beneficial. Similarly, those who valued networking opportunities were more likely to have a positive view of their cadetship experience (aOR = 10.06, 95% CI: 1.11-91.06, p = 0.040) than their counterparts. CONCLUSION: Our study found that students who valued financial support and networking opportunities had the most positive views of the Cadetship Program. These findings demonstrate that the Cadetship Program may be most helpful for those who need financial support and for students who seek networking opportunities. These findings increase our knowledge about the characteristics of medical students who have the most positive experiences with the Cadetship Program. They help us to understand the mechanisms of influence of such programs on individuals' decisions to be part of the future rural health workforce.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.122
GPT teacher head0.505
Teacher spread0.383 · 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 teacher head, not a consensus.

Study designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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