Anesthesiologists With Advanced Degrees in Education: Qualitative Study of a Changing Paradigm
Bibliographic record
Abstract
BACKGROUND: Anesthesiology education has undergone profound changes over the past century, from a pure clinical apprenticeship to novel comprehensive curricula based on andragogic learning theories. Combined with institutional and regulatory requirements, these new curricula have propagated professionalization of the clinician-educator role. A significant number of clinician-educator anesthesiologists, often with support from department chairs, pursue formal health professions education (HPE) training, yet there are no published data demonstrating the benefits or costs of these degrees to educational leaders. OBJECTIVE: This study aims to collect the experiences of anesthesiologists who have pursued HPE degrees to understand the advantages and costs of HPE degrees to anesthesiologists. METHODS: Investigators performed a qualitative study of anesthesiologists with HPE degrees working at academic medical centers. Interviews were thematically analyzed via an iterative process. They were coded using a team-based approach, and representative themes and exemplary quotations were identified. RESULTS: Seven anesthesiologists were interviewed, representing diverse geographic regions, subspecialties, and medical institutions. Analyses of interview transcripts resulted in the following 6 core themes: outcomes, extrinsic motivators, intrinsic motivators, investment, experience, and recommendations. The interviewees noted the advantages of HPE training for those wishing to pursue leadership or scholarship in medical education; however, they also noted the costs and investment of time in addition to preexisting commitments. The interviewees also highlighted the issues faculty and chairs might consider for the optimal timing of HPE training. CONCLUSIONS: There are numerous professional and personal benefits to pursuing HPE degrees for faculty interested in education leadership or scholarship. Making an informed decision to pursue HPE training can be challenging when considering the competing pressures of clinical work and personal obligations. The experiences of the interviewed anesthesiologists offer direction to future anesthesiologists and chairs in their decision-making process of whether and when to pursue HPE training.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".