Student Research and Practical Clubs as a Factor in Professional Development and Burnout Resistance Among Surgical Physicians

Burnout (QD85)

Burnout, Вurnout in surgeons, Student scientific and practical clubs, Undergraduate education, Prevention

This cross-sectional study included a cross-sectional survey of 100 surgeons who participated in the student research and practice club "Aesculap" while studying at Sechenov University over a 20-year period (from 2005 to 2025). Psychological burnout was assessed using the MBI questionnaire in 96 respondents. Engagement indicators (duration, activity) were combined into an integrated activity index using a principal component analysis. Multiple linear regression analysis and Spearman's rank correlation analysis were used.

This observational, cross-sectional study was conducted by the Department of Pedagogy and Medical Psychology and the Department of Operative Surgery and Topographical Anatomy at Sechenov First Moscow State Medical University from November 2025 to April 2026. A cross-sectional survey of 100 surgeons who had previously participated in the Eskulap student research and practical club was conducted during their 20-year studies at Sechenov University from 2005 to 2025. Adults (23-43 years old) who graduated from Sechenov University, participated in the Student Scientific and Practical Club "Aesculap" during their 2005-2026 graduation years, and who signed voluntary informed consent were eligible to participate in the study. Exclusion criteria included incomplete questionnaires or refusal to participate in the study. The final sample included 100 respondents (after excluding blank questionnaires) - graduates of the Scientific and Practical Club from 2005 to 2025. 96 participants of whom underwent psychological testing for burnout. All participants were informed of the study's aims and objectives and provided voluntary written informed consent. Data collection was anonymous, and confidentiality was guaranteed. To diagnose emotional burnout, we used the Russian-adapted version of the Maslach Burnout Inventory (MBI), validated on a Russian sample \[Vodopyanova, N.E.; Starchenkova, E.S.; Nasledov, A.D. Standartizirovannyi oprosnik "Professional'noe vygoranie" dlya spetsialistov sotsionomicheskikh professii. Vestnik Sankt-Peterburgskogo universiteta. Sotsiologiya 2013, (4). (In Russ.) Available online: https://cyberleninka.ru/article/n/standartizirovannyy-oprosnik-professionalnoe-vygoranie-dlya-spetsialistov-sotsionomicheskih-professiy (accessed on June 21, 2026).\]. The questionnaire included 22 statements, which respondents rated based on the frequency of their experiences, ranging from 0 ("never") to 6 ("every day"). Values were calculated using three scales: "Emotional Exhaustion," "Depersonalization," and "Reduction in Professional Achievement." A specially designed questionnaire was used to collect data. It included sociodemographic questions (gender, age, and total work experience since graduation) and a set of questions characterizing student engagement in research: duration of membership in the SSC (in years), number of surgical competitions and scientific events during their studies (as an indicator of activity), and a subjective assessment of the impact of SSC membership on their professional career on a scale from 1 (no impact at all) to 10 (absolutely true). Additionally, current medical specialty, academic degree, job title, and involvement in research and/or clinical work were specified, allowing us to describe the professional status of graduates. Involvement indicators (duration, activity) were combined into an integral activity index using the principal component analysis. Multiple linear regression analysis and Spearman's rank correlation analysis were used. A priori sample size calculation was performed using GPower 3.1.9.7 for multiple linear regression (Fixed model, R² deviation from zero). Based on a medium effect size f² = 0.15 (Cohen, 1988), α = 0.05, power = 0.80, and 5 predictors (gender, age, work experience, duration and intensity of SSC participation), the required sample size was 92. Allowing for 15% dropout, we aimed to recruit at least 106 participants. The final analysis included 96 respondents who completed the MBI, which exceeds the minimum requirement and ensures adequate statistical power. Statistical analysis included descriptive statistics, multiple linear regression, Spearman's rank correlation, and principal component analysis (PCA). The PCA was used to create an integrated activity index combining duration and intensity of SSC participation. Regression models were built for each MBI subscale. Effect sizes were calculated using Cohen's f².

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