Work-Life Balance of Collaborative Statisticians and Methodologists in Multidisciplinary Settings

Importance: Collaborative statisticians and methodologists are essential members of multidisciplinary teams, yet little is known about how their diverse responsibilities, including technical analysis, project leadership, and domain-specific consultation across multiple concurrent projects, affect their work-life balance and professional well-being. Objective: To assess perceptions of work-life balance and identify individual, job-related, and organizational factors associated with work-life balance among collaborative statisticians and methodologists working in multidisciplinary settings. Design, Setting, and Participants: This cross-sectional survey study collected data from November 2022 to May 2024, with analysis conducted in December 2024. Anonymous electronic surveys were distributed through international professional statistical societies, including organizations in North America, Europe, Africa, South America, and Asia. Participants were recruited via a convenience sample through society email listservs and newsletters. Eligible respondents were statisticians, data scientists, or methodologists working in multidisciplinary collaborative settings who had been continuously employed full-time during the previous year. Main Outcomes and Measures: Work-life balance was assessed using the 15-item Work-Life Balance Self-Assessment Scale, which consists of 3 subscales: Work Interference With Personal Life, Personal Life Interference With Work, and Work/Personal Life Enhancement. Regression analyses were used to identify the demographic, organizational, and discipline-specific factors associated with respondents' perception of work-life balance. Results: Of 627 individuals who accessed the survey, 450 (71.8%) met eligibility criteria and completed the survey. Of the 450 respondents who completed the survey, the mean (SD) age was x (y) years, 240 (53.7%) were female, and 270 (60.0%) worked in academia; 143 (31.8%) reported dissatisfaction with their work-life balance, and an additional 47 (10.4%) reported neutral satisfaction. Factors associated with higher work interference scores included unmanageable workload (mean difference, 0.70; 95% CI, 0.48 to 0.92), work-related health issues (mean difference, 0.58; 95% CI, 0.33 to 0.83), inability to complete work during regular hours (mean difference, 0.56; 95% CI, 0.34 to 0.78), and lack of organizational support for work-life balance (mean difference, 0.48; 95% CI, 0.24 to 0.73). Organizational flexibility to attend to personal matters (mean difference, -0.33; 95% CI, -0.64 to -0.01) and adequate compensation (mean difference, -0.29; 95% CI, -0.49 to -0.09) were associated with lower interference scores. Conclusions and Relevance: These findings suggest that targeted educational initiatives, effective mentorship, and wellness-focused organizational policies can foster sustainable work-life balance among statisticians and methodologists in multidisciplinary settings.