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Record W2499333236 · doi:10.5116/ijme.5780.bdba

Bedside teaching: an underutilized tool in medical education

2016· article· en· W2499333236 on OpenAlexaboutno aff
Mohammed Garout, Abdulelah Nuqali, Ahmad Alhazmi, Hani Almoallim

Bibliographic record

VenueInternational Journal of Medical Education · 2016
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
FundersVanderbilt University
KeywordsMedical educationMEDLINEMedicinePsychologyData scienceComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Bedside teaching (BST) is a fundamental component of clinical training and an essential tool in the creation of a competent physician.1-15 Sir William Osler (1849-1919), one of Canada’s most renowned physicians, was the first to introduce BST to medical education in 1892. He described modern medical education as something that needed to be taught at the bedside: “Medicine is learned by the bedside and not in the classroom.”9 BST allows the physician and patient to interact at the bedside; through this physician-patient interaction process, medical students and residents are simultaneously afforded the opportunity to learn clinical skills, clinical reasoning, physician-patient communication, empathy, and professionalism.6,12,15 In real practice, comprehensive history taking can help the physician diagnose up to 56% of patient problems, which may rise to 73% if a physical examination is added.8 Much information can be gained and a proper diagnosis reached by obtaining a good medical history and performing an efficient clinical examination.8 Clinical teaching in which the patient is involved is enriched by these visual, auditory, and tactile experiences. Senior medical students and medical residents believe that BST is a valuable but underutilized tool.15 Time spent on BST has been on the decline since 1978, as highlighted by Ahmed, who reported that the proportion of teaching time taken up by BST had declined from 75% 30 years ago to only 16% today.8 The learning triad The BST learning triad comprises patients, students, and tutors.6 All three must be present for BST to occur and it must occur within a clinical environment. Each individual member brings his or her own value to the learning triad. For example, the student brings medical knowledge and the eagerness to learn; the tutor brings depth of knowledge, mentorship, and willingness to help the student learn and make connections; and finally, the patient brings relevant clinical issues to the forefront that allow the student to learn. An effective learning environment requires all three groups to work together in the learning triad.6 The obstacles that may reduce the effectiveness of BST can be categorized by each group in the learning triad.

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)0.004
metaresearch head score (Gemma)0.036
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.433
Teacher spread0.415 · 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 designOther design
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

Citations43
Published2016
Admission routes1
Has abstractyes

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