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Record W4412465484 · doi:10.2196/68481

Effects of the Hidden Curriculum in Medical Education: Scoping Review

2025· review· en· W4412465484 on OpenAlexvenueno aff
Sebastian Parra Larrotta, Erwin Hernando Hernández Rincón, Daniela Niño Correa, Claudia Peñuela, Álvaro Enrique Romero-Tapia

Bibliographic record

VenueJMIR Medical Education · 2025
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintCurriculumHidden curriculumMedical educationPsychologyPedagogyMedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Medical education now focuses on developing skilled and dependable professionals, with particular attention to the hidden curriculum and its influence on professionalism and humanism. OBJECTIVE: This scoping review aimed to analyze the available evidence on the benefits and adverse effects of the hidden curriculum in medical education. METHODS: A scoping review of the literature available in the indexed databases PubMed, Scopus, ScienceDirect, and Latin American and Caribbean Health Sciences Literature (LILACS) with MeSH (Medical Subject Headings) descriptors was conducted on the effects of the hidden curriculum in medical education between January 2000 and April 2024. A total of 29 papers were selected for the review. RESULTS: Our review included studies from 10 countries, most of which were descriptive and cross-sectional, revealing both positive and negative impacts of the hidden curriculum in medical education. These include the transmission of implicit values and the influence on forming skills and professional identity. It was found that some elements contributed to the integral development of students, and others generated challenges that affected the quality of medical education. Likewise, the need for further research to design implementation strategies in different medical schools was described. CONCLUSIONS: The hidden curriculum proves to have both a positive and negative impact on the attitudes and values of medical students. The findings highlight the need to generate greater awareness and proactive strategies in educational institutions to improve the quality of training and promote the holistic development of future health professionals.

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)0.053
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.053
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.013
GPT teacher head0.449
Teacher spread0.436 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations10
Published2025
Admission routes1
Has abstractyes

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