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Record W2127887451

Issues related to medical students' engagement in integrated rural placements: an exploratory factor analysis.

2009· article· en· W2127887451 on OpenAlexaff
Tyrone Donnon, Wayne Woloschuk, Doug Myhre

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsExploratory factor analysisCronbach's alphaDescriptive statisticsMedical educationConstruct validityReliability (semiconductor)PsychologyRural communityFamily medicineMedicinePsychometricsClinical psychologyDemography
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to identify and investigate the factors derived from the rural integrated community clerkship (RICC) questionnaire that influenced the decision of medical students to pursue a 36-week rural community placement option. METHODS: A total of 162 first-year (n = 92) and second-year (n = 70) medical students completed the 35-item RICC questionnaire. We used qualitative interviews to develop questionnaire items, and we used subsequent descriptive statistics and exploratory factor analyses to analyze the data. RESULTS: Students with origins in rural communities were not significantly more likely to consider a RICC than their urban counterparts. However, students who identified family medicine as their discipline of choice were 3 times more likely to consider a RICC. Exploratory factor analysis, based on correlation of questionnaire items, determined 7 factors (themes) for the questionnaire. The questionnaire had strong internal reliability (Cronbach a = 0.94). CONCLUSION: Although generally supportive of the rural clerkship option, students are less concerned about the clinical experience than they are about the practical implications of moving to a rural community. The RICC questionnaire was shown to have strong reliability and construct validity in measuring students' perceptions of a long-term clerkship placement in a rural community.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.447
Teacher spread0.386 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2009
Admission routes1
Has abstractyes

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