Mental health states of soldiers with histories of corona virus disease 2019 infection in Taiwan: A comparison study with non-infected soldiers

Abstract

Objectives: According to the most recent studies on the mental health impacts of coronavirus disease 2019 (COVID-19), psychological effects are salient in the community, but they are not obvious in the military population. In the study, we intended to examine mental health state and suicide ideation among soldiers with past histories of COVID-19 and to compare them with non-infected controls. Methods: We recruited 193 active-duty military personnel from northern Taiwan and collected their responses of a series of copies of the questionnaire, i.e., Beck's Depression Inventory for depression, Beck's Anxiety Inventory for anxiety, Davidson Trauma Scale for symptoms of posttramatic stress disorder (PTSD), Pittsburgh Sleep Quality Index for sleep disturbance and sleep dissatisfaction, and Five-item Brief Symptom Rating Scale for suicide ideation. Results: Among our samples, about 58.5% (113/193) reported a past history of COVID-19 infection (infected group) at least once. More than 85% had vaccinated in more than two doses. The infected soldier group presented themselves significantly higher magnitude (1.92 ± 0.54) of impacts on their lives than noninfected control group (1.72 ± 0.66, p < 0.05). The discrepancy in life impact between infected and non-infected groups was significantly more salient in male soldiers (p < 0.05) comparing with female. In male soldiers, most mental health states were higher in the non-infected group than the infected group but nonsignificant. Conclusion: This study shows the common and differences in mental health states and suicide ideation between COVID-19 infected and non-infected soldiers in Taiwan and genders. In line with the findings of current studies, our results showed nonsignificant differences between male and female groups in the military population although significant differences among the community population. Further studies with larger sample sizes and more details are needed to confirm our assumption.