PurposeThis study aimed to determine the relationship between demographic diversity and veterinary professionals regarding their psychological distress and suicidal experiences. This study also aimed to determine what demographic factors were associated with psychological distress and suicidal experiences for veterinary professionals.MethodsThis study used a cross-sectional web-based questionnaire to assess the prevalence of diversity, psychological distress, and suicidality in individuals over 18 working in the veterinary field within the United States. The study received 2,482 responses resulting in 2,208 responses that were included in the analysis. Descriptive statistics were performed to identify the categories with the highest rates of psychological distress, suicidal thoughts, and suicidal behaviors. Binomial logistic regressions were conducted to identify the strongest statistical predictors of psychological distress (Kessler-6-K6), suicidal thinking and suicide behaviors.ResultsOf the 2,208 respondents included in the analysis, 888 (41%) were experiencing serious psychological distress and 381 (17.3%) had considered suicide in the past 12 months. Results of the binomial regressions indicate gender, social class, age, and disability status were the strongest predictors of psychological distress. When controlling for psychological distress, the strongest predictors of suicidal thinking were sexual orientation, marital status, and professional role.ImplicationsLimited research has been done to explore the relationship between demographic diversity of veterinary professionals and psychological distress, suicidal thoughts, and suicidal behaviors specifically. These results shed light on multiple demographic factors that promote and attenuate mental health, as well as the importance of asking respondents their demographic identities in veterinary medicine research. This research attempts to identify these mental health factors without collapsing categories with small sample sizes, which does cause a limitation in statistical power, yet also demonstrates how to increase inclusivity in research.