Game-Based Assessment of Cognitive Abilities and Personality Characteristics for Surgical Resident Selection: A Preliminary Validation Study
Bibliographic record
Abstract
Background: Assessment of nontechnical attributes is important in selecting candidates for surgical training. Currently, these assessments are typically made based on ineffective methods, which have been shown to be poorly correlated with later performance. Objective: The study aimed to examine preliminary evidence regarding the use of game-based assessment (GBA) for assessing cognitive abilities and personality characteristics in candidates for surgical residencies. Methods: The study had 2 phases. In the first phase, a gamified test was developed to assess competencies relevant for surgical residents. Three games were chosen, assessing 14 competencies: planning, problem-solving, ingenuity, goal orientation, self-reflection, endurance, analytical thinking, learning ability, flexibility, concentration, conformity, multitasking, working memory, and precision. In the second phase, we collected data from 152 medical interns and 30 expert surgeons to evaluate the test's feasibility, acceptability, and validity for candidate selection. Results: Feedback from the interns and surgeons supported the relevance of the test for selection of surgical residents. In addition, analyses of the interns' performance data supported the appropriateness of the score calculation process and the internal structure of the test. Based on this data, the test showed good psychometric properties, including reliability (α=0.76) and discrimination (mean discrimination 0.39, SD 0.18). Correlations between test scores and background variables indicated significant correlations with gender, video game experience, and technical aptitude test scores (all P<.001). Conclusions: This study presents an innovative GBA testing cognitive abilities and personality characteristics. Preliminary evidence supports the validity, feasibility, and acceptability of the test for the selection of surgical residents. However, evidence for test-criterion relationships, particularly the GBA's ability to predict future surgical performance, remains to be established. Future longitudinal studies are necessary to confirm its utility as a selection tool.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".