Survey on academic medicine culture, enablers & barriers in a newly formed academic department in Singapore
Bibliographic record
Abstract
Objective: A positive culture of academic medicine is important for improving healthcare, research and medical education. This study seeks to assess academic medicine culture, enablers and barriers with a multi-dimensional structured survey, in a newly formed academic department from the perspectives of faculty and staff.Methods: Thirteen dimensions relating to academic medicine culture were identified after focused group discussions. Each dimension contains four relevant questions with answers on a 5-point Likert scale. This web-based questionnaire survey was conducted for senior and junior physicians within SingHealth Duke-NUS Obstetrics & Gynecology (OBGYN) academic department in 2011. This unit was started within the academic medical centre formed by SingHealth, and Duke-NUS which is a medical school jointly established by Duke University and National University of Singapore (NUS). Gaps were identified and addressed with various initiatives. A second survey in 2012 and a third survey in 2013 were conducted to assess the change in culture.Results: In the first survey, the top three favorable dimensions (highest percentage of composite positive response) were: Supervisor and Departmental Support for Academic Medicine (64.0%); Academic Faculty Development (57.9%); and Communications & Feedbacks on Academic Medicine (57.3%). The bottom three dimensions which were areas for improvements were: Academic Clinical Staffing Issue (23.8%); Relating Clinical Service to Research & Education (33.2%); and Academic Teamwork across Institutions (36.3%). In the second survey, there was overall improvement for 12 of the 13 dimensions. In the third survey, there was overall improvement for all the 13 dimensions compared to the first survey.Conclusions: There were positive changes, likely contributed by initiatives within the department to engage staff and to address gaps in various aspects of academic medicine culture.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".