Comparison of spiral versus block curriculum styles in preparing medical students to diagnose and manage concussions
Bibliographic record
Abstract
Objective Examine differences between the recently implemented integrated spiral (year 1) and conventional block (years 2-4) MD curriculum at University of British Columbia (UBC) with respect to knowledge of concussion diagnosis and management. Design Cross-sectional survey Setting UBC undergraduate MD program Participants An online survey was distributed to all 1152 students currently enrolled in UBC medical school. To date, 123 surveys have been returned (10.7% response rate) with 58 first year students (integrated spiral curriculum) and 65 students in years 2-4 (conventional block curriculum). Females made up 60% of responses. Interventions Online survey, hosted by FluidSurveys (Fluidware, Ottawa, ON), distributed through email. Outcome measures Questions focused on demographic data, knowledge of concussion definitions, and management considerations. Main results Majority of responses revealed both curriculums have promoted a strong understanding of concussion definition and related symptoms (84% correct response rate). Only 8.1% of participants believed that functional imaging (MRI or CT) is a mandatory assessment tool for concussions. Differences between the conventional and integrated curriculums included: understanding concussions can occur without direct impact to the head (91.4% integrated vs. 69.2% conventional: χ2(1)=43.325, p<0.001) and identifying long-term consequences of repetitive concussive injuries (dementia: 91.4% integrated vs. 66.2% conventional; death or severe disability with second impact syndrome: 77.6% integrated vs. 55.4% conventional). Conclusions The findings from this study reveal a number of positive signs regarding the evolution of medical education in terms of concussion diagnosis and management. The integrated curriculum is taking further steps in advancing concussion knowledge in medical education. Competing interests None.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".