Zadafshar S., Kheradmand M., Kazemian H., Akrami, N.
Publication Date: 2022/11/22
Journal of Applied Psychological Research (22518126)13(3)pp. 327-341
The aim of the present study was to predict COVID-19 traumatic stress and posttraumatic growth in nurses of coronavirus patient care unit based on perceived social support considering the mediating role of self-compassion and cognitive emotion regulation. The present study is a descriptive correlation with the structural equation model and in terms of purpose is applied. The statistical population includes all nurses who worked in hospitals in Isfahan in 2021, of which 230 (143 female and 87 male) were selected through an available sample. Research instruments included the multidimensional perceived social support (MSPSS), self-compassion (SCS), cognitive emotion regulation questionnaire (CERQ), posttraumatic growth inventory (PGI), and COVID-19 traumatic stress scale (CTSS). Descriptive statistics and structural equation modeling as well as SPSS-23 and Amos-23 were used to analyze the data. Results showed that perceived social support directly and indirectly through matched cognitive emotion regulation strategies and self-compassion had a positive effect on posttraumatic growth (β = 0.228, P < 0.01) and a negative effect on COVID-19 traumatic stress (β = -0.316, P < 0.01), whereas the relationship between non-matched cognitive emotion regulation strategies and posttraumatic growth was not significant (P < 0.05). The research findings not only have practical and theoretical implications, but also can be used as a useful model to provide nurses with adequate services to pave the way for growth and development after trauma and prevent covid-19 traumatic stress.
Journal of Mazandaran University of Medical Sciences (17359260)23(102)pp. 45-57
Background and purpose: Individuals treat the Internet phenomenon differently based on their personalities. Also, personality can predispose individuals for some psychological disorders. Some psychologists state that personality comes from nervous system functions, therefore, this study investigated the personality characteristics caused by brain-behavioral systems and gender on Internet addiction. Materials and methods: This casual-comparison research was performed in 225 people selected through cluster sampling from Internet cafes, libraries and gyms' clients in Isfahan. The data was collected using Young's Internet addiction scale and Gray-Wilson Personality Questionnaire. Results: Multivariate Variance Analysis (MANOVA) showed significant differences in brain-behavioral systems of addicted and non-addicted groups. Paired-test showed that these differences were due to differences in passive avoidance, and fight and flight subscales. Independent sample t-test also showed significant differences in Internet addiction between male and female. Moreover, multiple regression analysis confirmed the predicting role of passive avoidance and gender in Internet addiction. Conclusion: Behavioral inhibition system sensitivity could influence the risk factors of internet addiction. This is probably caused by enjoying the nature of Internet activities and delay in the negative outcomes at the same time. These are pleasant for individuals with high behavioral inhibition system sensitivity. Furthermore, males are more prone to Internet addiction; that is due to more tendencies to develop social relations and gaining less family support than females.
