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Record W4379229557 · doi:10.5334/pme.838

Evaluation of Continuing Professional Development for Physicians – Time for Change: A Scoping Review

2023· review· en· W4379229557 on OpenAlexaff
Shera Hosseini, Louise Allen, Faran Khalid, Donny Li, Elizabeth Stellrecht, Michelle Howard, Teresa M. Chan

Bibliographic record

VenuePerspectives on Medical Education · 2023
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWilliam Osler Health SystemHumber River Regional HospitalHamilton Health SciencesMcMaster University
Fundersnot available
KeywordsChecklistPsychological interventionMedical educationIntervention (counseling)Quality (philosophy)MEDLINEProgram evaluationMedicineQuality managementHealth careProfessional developmentPsychologyNursing

Abstract

fetched live from OpenAlex

Introduction: Evaluation of education interventions is essential for continuous improvement as it provides insights into how and why outcomes occur. Specifically, for physicians' continuing professional development (CPD) programs, which aim to upskill physicians in a range of practice-essential domains, evaluations are crucial to assure physicians' continuous development, enhanced patient care and safety. However, evaluations of health professions education (HPE) interventions tend to be outcomes focused, failing to capture how and why outcomes occur. This scoping review aimed to identify evaluation techniques used to evaluate CPD programs for physicians, and to determine how these techniques are being implemented as well as the their quality. Methods: We searched PubMed, Embase, Web of Science, among others for English publications on evaluation of CPD programs for physicians, in the past decade. We used a data charting template to extract study details regarding the evaluation techniques and produced a checklist to assess the quality of the evaluations. Results: 101 studies were included; of which 91 studies did not use an evaluation framework. Our findings revealed shortcomings in the evaluations of CPD programs including lack of attention to: intervention processes; unintended outcomes and contextual factors; use of theory; evaluation framework use; and rationale for chosen evaluation method. Discussion: Our findings highlighted major gaps in the evaluation techniques employed in physicians' CPD. Attention needs to be paid to evaluating both program processes and outcomes to illuminate how and why impacts are or are not occurring.

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)0.007
metaresearch head score (Gemma)0.037
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.158
GPT teacher head0.544
Teacher spread0.386 · 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

Citations13
Published2023
Admission routes1
Has abstractyes

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