A survey of the members of the American Society of Pediatric Neurosurgeons and factors associated with well-being
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to survey the members of the American Society of Pediatric Neurosurgeons (ASPN) to assess the prevalence and associated risks of burnout among pediatric neurosurgeons. The authors aimed to identify the factors that most significantly contributed to this risk to provide a baseline group of characteristics to improve physician well-being. METHODS: Institutional Review Board approval from the University of Arizona was obtained, and the 7-question and 9-question Mayo Physician Well-Being Index (WBI) was distributed to members of the ASPN (n = 275). This index screens for many different aspects of distress for physicians, including burnout risk, stress, depression, fatigue, suicidal ideation, and low career satisfaction. RESULTS: An analysis of 111 pediatric neurosurgeons (111/275 [40% response rate]) was completed. Respondent ages were distributed, with those aged 56-60 years representing the highest proportion (20%). University practice represented a majority (72%). One-third (32%) of respondents reported practicing greater than 25 years, and most physicians in the survey were married (76%). One-third of surgeons spend 61-70 hours working per week (33%), and a plurality are on call between 6 and 10 days per month (42%). Most surgeons reported treating fewer than 200 cases per year (37% reported 100-150 cases; 23%, 151-200). Most pediatric neurosurgeons (63%) stated their annual salary was sufficient. Analysis of each WBI question was performed to identify which factors specifically contributed to the risk of burnout. An overwhelming majority of respondents reported that they make significant efforts to do at least one thing each week that brings them joy (97%), and they either agree or strongly agree that they perform meaningful work (98% of all participants, 97% of females, and 98% of men, p = 0.010). Nearly half of all respondents (49%) reported feelings of burnout and a majority of them were female (67% of women and 42% of men, p = 0.021). Time, environment, case volumes, and quality-of-life concerns are all factors that significantly contribute to the overall risk of burnout and well-being. CONCLUSIONS: This survey study of the ASPN membership revealed a 49% rate of burnout with females at higher risk (67%). Factors associated with burnout were salary, more than 10 days on call per month, electronic medical record stressors, and work-life incongruity. The aforementioned notwithstanding, respondents believe pediatric neurosurgery is a meaningful career. This study provides evidence supporting a moral imperative toward recognition of burnout symptoms and a pivot point toward implementing change.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".