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Record W4304207099 · doi:10.21203/rs.3.rs-1973311/v1

A Continuing Professional Development Imperative? Examining Trends and Characteristics of Health Professions Education Doctoral Programs

2022· preprint· en· W4304207099 on OpenAlexaboutno aff
Violet Kulo, Christina Cestone

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)CurriculumMedical educationHealth professionsProfessional developmentAllied health professionsFaculty developmentContinuing educationHealth carePolitical scienceMedicinePsychologyPedagogyEngineering

Abstract

fetched live from OpenAlex

Abstract Background Despite the long-standing faculty development initiatives for improving teaching skills in the health professions, there is still a growing need for educators who are formally trained in educational theory and practice as health professions experience dramatic demand and growth. Doctoral programs in health professions education (HPE) provide an avenue for health professions’ faculty continuing professional development (CPD) to enhance their knowledge and skills for teaching and curriculum leadership roles. There has been a proliferation of graduate programs in HPE over the last two decades to respond to the growing need for well-prepared faculty educators and program leadership. The purpose of this study was to identify and describe HPE doctoral programs in United States (U.S.) and Canada. Methods This study first examined doctoral programs in HPE identified in earlier studies. Next, we searched the literature and the web to identify new doctoral programs in the U.S. and Canada that had been established between 2014, when the prior study was conducted, and 2022. We then collated and described the characteristics of these programs, highlighting their similarities and differences. Results We identified a total of 20 doctoral programs, 17 in the U.S. and 3 in Canada. Of these, 12 programs in the U.S. and 1 program in Canada were established in the last 8 years. There are many similarities and some notable differences across programs with respect to degree title, admission requirements, duration, delivery format, curriculum, and graduation requirements. Most programs are delivered in a hybrid format and the average time for completion is 4 years. Conclusions The workforce problem facing health professional schools presents an opportunity, or perhaps imperative, for continuing professional development in HPE. With the current exponential growth of new doctoral programs, there is a need to standardize the title, degree requirements, and further develop core competencies that guide the knowledge and skills HPE graduates are expected to have upon graduation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.137
GPT teacher head0.506
Teacher spread0.368 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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