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Record W4396643858 · doi:10.29309/tpmj/2024.31.05.8116

Which practice is best to manage the Hidden curriculum for the best use of mobile devices in clinical practice? A systematic review.REVIEW

2024· article· en· W4396643858 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Professional Medical Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsBest practiceClinical PracticeCurriculumComputer scienceEngineering ethicsMedicineMedical educationData sciencePsychologyEngineeringPedagogyNursingPolitical science

Abstract

fetched live from OpenAlex

Objective: To evaluate the literature regarding the practices to manage the hidden curriculum for the best use of mobile devices in clinical practice. Study Design: Systematic Review. Setting: Articles selected for review from Canada, United Kingdom, Japan, Ireland and Saudi Arabia. Period: July to Dec 2023. Methods: Following databases were searched: PubMed (12,579), the Cochrane Library (348), scopus (84), PsycInfo (21), CINAHL (220), Google Scholar (1,414). Primary variable (Evaluation of the development of clinical skills made possible by mobile devices) and secondary variable (to determine how satisfied students are with their mobile learning experience). The quality of study was critically appraised according the Critical Appraisal Skills Programme (CASP) scale. Results: The research findings indicate that using mobile devices into medical education has a variety of effects. Positive instructor perspectives, more student involvement, and higher learning outcomes were frequently reported by participants. Medical students' growth of technological competency and readiness for the changing healthcare landscape have been found to be accelerated by mobile devices. The integration of virtual simulations and applications that are interactive has had a positive impact on the development of clinical abilities. Positive effects included themes of individualization, collaborative learning communities, and a better understanding of patient-centered care. On the other hand, issues including the digital divide, diversions, and security threats were recognized as obstacles that called for a careful strategy to reduce any negative effects. When everything is considered, the findings confirm the revolutionary potential of mobile device incorporation in medical education and highlight how it helps to create a dynamic, technologically advanced learning environment for prospective medical professionals. Conclusion: This study provides insight on how adding mobile devices into medical education has a revolutionary effect. The research indicates enhanced learning outcomes, increased student involvement, and altering faculty perspectives through insightful stories and compelling arguments.

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.

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)0.045
metaresearch head score (Gemma)0.073
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0450.073
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0010.001

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 head0.107
GPT teacher head0.572
Teacher spread0.465 · 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