mental health model of iranian veterans with network analysis approach

Aims: the present study aimed to provide a model of the mental health of veterans and identify its determining factors.information & methods: the study method is based on correlational network data analysis. the data of 9244 veterans, including demographic characteristics and data related to mental health, were extracted in the second 6 months of 2020, and then the network indexes were calculated.findings: age, number of children, percentage of veterans, percentage of neurological and mental disorders, physical functioning, bodily pain, and mental health were the variables that had the most strength. age, number of children, pension, percentage of neurological and mental disorders, physical functioning, depression, anxiety, general health, physical role, physical functioning, social functioning, and vitality were the closeness factors in the mental health network of veterans. the benit value for the variables of depression, age, mental health, physical role, physical functioning, and the number of children in the mental health network of veterans was non-zero. the variables of number of children, percentage of mental disorders, psychiatric diagnoses, especially depression, employment standby, physical problems, and vitality had the highest eigenvector values in the mental health network of veterans. the variables of the number of children, the percentage of mental disorders, depression, vitality, history of hospitalization, and the type of hospitalization had higher leverage (positive) with the mental health network.conclusion: the variables related to quality of life, along with age, number of children, percentage of neurological and mental disorders, and depression, are the main determinants of mental health.