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Record W3164161487 · doi:10.1136/bmjoq-2021-001385

Development and evaluation of an online medication safety module for medical students at a rural teaching hospital: the Winchester District Memorial Hospital

2021· article· en· W3164161487 on OpenAlexaff
Ali Elbeddini, Yasamin Tayefehchamani

Bibliographic record

VenueBMJ Open Quality · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsTest (biology)Intervention (counseling)MedicinePatient safetyMedical educationOnline learningControl (management)Significant differenceNursingMultimediaComputer scienceHealth careInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To design, implement and assess an online learning module for third-year and fourth-year medical students addressing medication safety. DESIGN: This study was a prospective, parallel, open-label, randomised controlled trial with two arms: (1) a control arm in which students were given five articles to read about medication safety, and (2) an intervention arm in which students were given access to an interactive web-based learning module on medication safety. Pretesting and post-testing were done online to evaluate change in medication safety knowledge. RESULTS: Ten students completed the study in the intervention group (online module) and six students completed the study in the control group. The increase in score obtained on the post-test, relative to the pretest, was 15.4% in the group who completed the online module and 2.0% in the control group (difference=13.4%, 95% CI 0.5% to 26.2%, p=0.04). CONCLUSION: Students who completed an online educational tool about medication safety demonstrated a significantly greater increase in knowledge than those who completed a few readings. Online learning modules can be a convenient and effective means of teaching safe prescribing concepts to medical trainees.

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)0.022
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.226
GPT teacher head0.561
Teacher spread0.335 · 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 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

Citations5
Published2021
Admission routes1
Has abstractyes

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