2020 Military Poster Presentations

Jacob Doyle, OMSII, Mackenzie Berry, OMSII, Sun Jin Oh, OMSII, Amanda Sniadach, OMSII, Raul Betancourt-Perez, OMSIII, Isain Zapata, PhD, Anthony LaPorta, MD, Brunson Larry; Rocky Vista University College of Osteopathic Medicine

Objectives: The purpose of this study was to assess the likelihood of providing false answers to questions asking about the level of stress while measuring different demographics.

Methods: 103 medical students (78 male, 25 female; 85 Caucasian, 11 Asian, 6 Mixed; 66 single, 37 married) attending Rocky Vista University from three sessions (2017, N=30; 2018, N=32; 2019, N=41). All student participants were contracted with the U.S. military. Students were put in a hyper-realistic mass-trauma simulation to induce stress. The data was collected using the Veracity TouchScreener® tablet, which records and analyzes involuntary responses to detect dishonesty. All responses were pooled across 2017, 2018, and 2019. Contingency tables were analyzed for Marital status and Gender using a Cochran-Mantel-Haenszel test for Nonzero Correlation.

Results: Results showed single participants were more likely to truthfully admit being stressed as compared to married participants; however, neither group is more likely to be dishonest. Gender showed a significant effect for stress data; however, no specific trends could be detected for different answer types in these studies. This is likely due to small effect size, small sample size or both. A non-significant trend could be observed with females being more likely to admit stress than males and males being more likely to lie than females.

Conclusion: We concluded that single participants were more likely to admit being stressed when compared to married participants. This data will enable us to identify populations that are more susceptible to stress in order to provide them with resources and training to further improve their mental health and readiness. Future studies will include data from another session in 2020; this may solidify the trend shown in Gender demographic by increasing the sample size.