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Record W3206881111 · doi:10.22605/rrh6883

Comparison of educational environments in different sized rural hospitals during a longitudinal integrated clerkship in Thailand

2021· article· en· W3206881111 on OpenAlexaboutno aff
Boonluksiri, Thongmak, Warachit

Bibliographic record

VenueRural and Remote Health · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMedicineClinical clerkshipFamily medicinePopulationMultidisciplinary approachRural areaMedical educationNursingPsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: The longitudinal integrated clerkship (LIC) curriculum model focuses on patient-centered care and continuity of clinical and cultural learning between medical students, patients, clinicians, and a system of care. In rural settings, participating medical students are expected to have an interest in rural medicine and an involvement in the community. Many schools in the USA, Canada, and Australia have implemented LICs in undergraduate programs in different ways. However, a few published reports in Asia are available. This is the first report of a modified rural LIC in Thailand. The objective was to assess the educational environment of a rural LIC using the Dundee Ready Education Environment Measure (DREEM) questionnaire and to compare students' response on the basis of year of study and different sizes of hospitals. METHODS: A cross-sectional study was conducted. The study population comprised 75 clinical-year students in 2020. The modified LIC was implemented as part of integrated multidisciplinary rural clerkships for fourth-year students, and for fifth-year students undertaking clinical placements. Clinical clerkships in rural settings took place over 12 weeks for fourth-year students and over 14 weeks for fifth-year students. Practical exposure included the clinical areas of internal medicine, psychiatry, surgery, pediatrics, obstetrics and gynecology, emergency medicine, and family medicine, in outpatient and inpatient settings. The DREEM questionnaire was used to evaluate students' perceptions of learning climate. Data analysis was performed to determine the different size of hospitals and other factors associated with a favorable educational environment. RESULTS: The response rate to the questionnaire was 96%. The overall DREEM score average was 137.7/200. Students' perceptions of learning and of teaching had mean scores of 30.1/48 and 35.7/44, respectively. Students' academic self-perceptions scored 18.7/32. Students' perceptions of atmosphere scored 30.4 of 48, and social self-perceptions scored 18.3/28. The academic subscale had the lowest percentage of scores regarded as confidence in knowledge gain. The factors associated with positive educational environment were staff as principal preceptors and large hospitals. CONCLUSIONS: LIC implementation in a community health system is a model for expanding clinical clerkships. Good infrastructure of the host hospital and enthusiastic preceptors are the key success factors. Staff supervision is essential to encourage student learning, especially in academic environments. Large hospitals have better infrastructure to support learning processes than small hospitals.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.352
Teacher spread0.331 · 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.

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
Published2021
Admission routes1
Has abstractyes

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