Preventing Translational Scientists From Extinction: The Long-Term Impact of a Personalized Training Program in Translational Medicine on the Careers of Translational Scientists
Bibliographic record
Abstract
Far too much biomedical research is wasted and ends in the so called ‘Valley of Death’: the gap that exists between biomedical research and its clinical application. While the translational process requires collaboration between many disciplines, current translational medicine focuses on single disciplines. Therefore, educational pathways that integrate clinical and research skills in interdisciplinary and interprofessional contexts are needed. The Eureka institute (http://www.eurekainstitute.org/) was founded to address these issues. The institute organizes an annual one-week international certificate course to educate professionals in the domains of translational medicine. Study design: This study set out to investigate the impact of the Eureka certificate course on the alumni, focusing on their ability to engage in translational activities and thus become more proficient translational professionals. An explanatory, mixed-methods study was executed. Data collection: A questionnaire was distributed to collect quantitative data on the number of alumni whothat were able to apply what they learned during the Eureka course and engage in translational activities. Questionnaire data were also used to inform the semi-structured interviews that were conducted subsequently. Results: 51% of the alumni reported that participating in the Eureka course had played a role in their decision to change to a different job or in the way they were accomplishing their everyday work. Ten conditions for change that either hampered or supported the Eureka alumni’s engagement in translational research activities were identified. Further, the learning outcomes of the Eureka course that impacted the alumni’s professional activities were explored using Personal Professional Theory (PPT). The insight that alumni gained in the full translational spectrum and stakeholders involved stimulated reflection on alumni’s their own role within that pathway. Further, according to the alumni, the course provided them with the skills and confidence to pursue a career as translational professional. These learning outcomes, in combination with conditions that supported alumni’s engagement in translational activities, such as supportive professional partners, opportunities to network or collaborate, and a translational work environment, contributed to the large number of alumni that were able to engage in translational activities.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".