Do scores on the new psychological, social and biological foundations of behavior (PSBB) section of MCAT 2015 predict medical students' academic performance in behavioral and social sciences (BSS) courses
Bibliographic record
Abstract
Purpose:The Medical College Admissions Test (MCAT) changed in 2015 to reflect 21st century medical education, and one change was the addition of the new Psychological, Social and Biological Foundations of Behavior (PSBB) section which assesses knowledge that provides a foundation for learning in medical school about the behavioral and socio-cultural determinants of health and health outcomes.Memorial University in 2013-2014 participated in the PSBB validity study to learn how well PSBB scores predict students' academic performance in behavioral and social sciences (BSS) courses and clerkships.Methods: All first and second year medical students at Memorial University of Newfoundland were invited to take a prototype PSBB exam and short post-exam survey in fall 2013 and to give permission for their grades in courses that were conceptually related to PSBB content to be included in the study.Results: Eighty-one percent of first and 91% of second year medical students participated in the study.We compared prototype PSBB scores to performance in coursework related to BSS.Grades in psychiatry, and neuroscience blocks as well as a course on community health were predicted by prototype PSBB scores (corrected correlations equal .41,.33,and .40,respectively).Conclusions: Performance on the PSBB prototype predicted performance in coursework with BSS content.Prediction was stronger for psychiatry and community health than neuroscience coursework, potentially due to the greater alignment of concepts between the PSBB section and related medical school coursework.Future research will evaluate the predictive validity of prototype PSBB scores with performance in psychiatry clerkships.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".