Barriers and facilitators to program directors’ use of the medical education literature: a qualitative study
Bibliographic record
Abstract
Abstract Background It is unclear how often frontline clinical teachers are using this literature and its evidence base in teaching and assessment. Our study purpose was to examine postgraduate program director perspectives on the utilization and integration of evidence-based medical education literature in their teaching and assessment practices. Methods The authors conducted semi-structured telephone interviews with a convenience sample of current and former program directors from across Canada. Interviews were transcribed and analyzed inductively to distil pertinent themes. Results In 2017, 11 former and current program directors participated in interviews. Major themes uncovered included the desire for time-efficient and easily adaptable teaching and assessment tools. Participants reported insufficient time to examine the medical education literature, and preferred that it be ‘synthesized for them’. (i.e., Best evidence guidelines). Participants recognised continuing professional development and peer to peer sharing as useful means of education about evidence-based tools. Barriers to the integration of the literature in practice included inadequate time, lack of financial compensation for teaching and assessment, and the perception that teaching and assessment of trainees was not valued in academic promotion. Discussion Faculty development offices should consider the time constraints of clinical teachers when planning programming on teaching and assessment. To enhance uptake, medical education publications need to consider approaches that best meet the needs of a targeted audiences, including frontline clinical teachers. This may involve novel methods and formats that render evidence and findings from their studies more easily ‘digestible’ by clinical teachers to narrow the knowledge to practice gap.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".