The Relationship Between Response Time and Diagnostic Accuracy
Bibliographic record
Abstract
PURPOSE: Psychologists theorize that cognitive reasoning involves two distinct processes: System 1, which is rapid, unconscious, and contextual, and System 2, which is slow, logical, and rational. According to the literature, diagnostic errors arise primarily from System 1 reasoning, and therefore they are associated with rapid diagnosis. This study tested whether accuracy is associated with shorter or longer times to diagnosis. METHOD: Immediately after the 2010 administration of the Medical Council of Canada Qualifying Examination (MCCQE) Part II at three test centers, the authors recruited participants, who read and diagnosed a series of 25 written cases of varying difficulty. The authors computed accuracy and response time (RT) for each case. RESULTS: Seventy-five Canadian medical graduates (of 95 potential participants) participated. The overall correlation between RT and accuracy was -0.54; accuracy, then, was strongly associated with more rapid RT. This negative relationship with RT held for 23 of 25 cases individually and overall when the authors controlled for participants' knowledge, as judged by their MCCQE Part I and II scores. For 19 of 25 cases, accuracy on each case was positively related to experience with that specific diagnosis. A participant's performance on the test overall was significantly correlated with his or her performance on both the MCCQE Part I and II. CONCLUSIONS: These results are inconsistent with clinical reasoning models that presume that System 1 reasoning is necessarily more error prone than System 2. These results suggest instead that rapid diagnosis is accurate and relates to other measures of competence.
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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 | 0.004 | 0.756 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".