Needs, rationale, and outcomes of leadership education in neurosurgery
Bibliographic record
Abstract
BACKGROUND: Surgeons are expected to lead teams/organizations to achieve optimal patient outcomes; however, few receive formal education in leadership. The goals of the study were to: 1) assess the unmet needs and gaps in leadership education for neurosurgeons and residents/fellows; 2) identify factors associated with availability of leadership education, access to leadership positions and the similarities/differences across geographic regions and institutional type; 3) describe the associations between gender and leadership; 4) determine the impact of leadership education. METHODS: International survey of 657 neurosurgeons, residents/fellows. A series of univariate analysis and multivariate were conducted to assess the association between specific variables and leadership outcomes. RESULTS: Almost half (48%) indicated that leadership education did not exist in their organization. This lack was more notable in non-academic centers (p < 0.001), among neurosurgeons with less than 5 years of work experience (p = 0.03), and respondents from South America (p = 0.02). Nearly two-thirds (61.1%) reported never having leadership training. Significantly fewer respondents in the age range 35-44 years old (p = 0.02), those working in the Middle East (p = 0.02), neurosurgeons with work experience less than 5 years (p = 0.004), working in non-academic center (p = 0.02) attended leadership training. In contrast to the differences seen across geographic regions and types of institutions, overall, the proportions of males and females having access to leadership training and being offered leadership positions were similar. Among participants, 87.1% of those with leadership training were offered leadership roles, compared to 65.5% of those without leadership training (p < 0.001). Additionally, participants with leadership training experienced a burnout rate of 29.2%, whereas those without leadership training had a higher rate of burnout of 40.5% (p = 0.02). CONCLUSIONS: There is a pressing need to develop educational opportunities for leadership in neurosurgery, especially for younger neurosurgeons, neurosurgeons working in non-academic centers, in countries and non-academic institutions where leadership education is less accessible. Leadership education is associated with increased numbers of neurosurgical leaders at all levels as well as reduced levels of burnout.
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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 | 0.009 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".