MatricS—A novel tool for monitoring professional role development in surgical disciplines
Bibliographic record
Abstract
Introduction Mentoring is an effective method for human resource development. Monitoring the process is important for individual mentee/mentor pairs as well as for program directors. Due to individual personality differences of both mentees and mentors and their respective interactions, it is challenging to monitor the individual development process of mentees in a structured manner. This study investigates to what extent a novel instrument, the mentee-based assessment tool for role development of interpersonal competencies in surgical professions (MatricS) can adequately monitor the professional role development process of residents during an established mentoring program. Material and methods In a prospective longitudinal study, the competence development of 31 mentees in two subsequent cohorts was assessed by a modified role matrix based on Canadian Medical Education Directives for Specialists. The evaluation focused on three defined roles (D, developer; N, networker; M, multiplicator) at three levels (private, employer-related, national/international) with four stages of development. For validation of mentee self-assessments, the assessments of the respective mentors were recorded alongside. For correlation analyses, Pearson coefficients were calculated, pre-post-comparisons were done by paired t-tests; significance was assumed at p < 0.05, respectively. Results Mentee self-assessments overall correlated well with the objective mentor assessments (Pearson's r 0.8, p < 0.001). Significant correlations of this magnitude were found for both individual cohorts as well as for all individual roles. The mentees acquired competencies in all roles indicated by significant increases of corresponding MatricS scores. The largest competency gains (mean ± SD) were found in the role D (start: 1.30 ± 0.77, end: 2.13 ± 0.83, p < 0.001). The majority of mentees achieved the prespecified target competency level in >75% of all roles and levels. Conclusion The role development process during mentoring can be reliably monitored by using MatricS. MatricS scores highly correlate between mentees and mentors, indicating that mentee self-assessments are suitable and sufficient for monitoring. These findings help to lessen the work burden on senior surgeons and thus can help to increase the acceptance of mentoring programs in surgical disciplines.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".