What Makes an Effective Chief of Pediatric Cardiology: Insights From Chiefs of North American Pediatric Programs
Bibliographic record
Abstract
BACKGROUND: Although the position of a pediatric cardiology chief is often seen as the apex of one's academic career, its roles, responsibilities, and qualifications are not well defined in the literature. This study was done to gain further insight of the role and attributes of a pediatric cardiology chief by surveying those who are currently serving the position across North American centers. METHODS AND RESULTS: This was a mixed-methods study with a survey given to North American pediatric cardiology chiefs at programs with fellowship training programs. The survey was a semistructured questionnaire that was independently reviewed by 3 cardiologists. Smaller private practice groups and nonacademic programs were excluded. Survey inventory included items rated on a 5-point Likert scale, open-ended prompts, and targeted questions. A total of 40 of 65 (62%) pediatric cardiology chiefs responded to the survey. Respondents identified key chief attributes included communication skills, honesty/transparency, and conflict-resolution skills. Likert scale data demonstrated participants were satisfied with their position, although many reported growing concerns of increased demands from administration, faculty, and pressures of program performance in the current era. There is also a noted paucity of diversity among those serving in leadership positions within pediatric cardiology, which was acknowledged by survey respondents. CONCLUSIONS: We gathered information directly from current North American pediatric cardiology chiefs examining the current era of its role. There are resounding themes on the emphasis for communication, honesty, conflict resolution, and mentorship. Future studies should examine faculty perceptions and a global perspective of the role.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".