Prediction of Coronavirus Anxiety based on Attachment Styles, Resilience, and Life Expectancy in Drug Users

Abstract

Background: The Coronavirus disease 2019 (COVID-19) has had unsolvable psychosocial effects on human beings. The marginalized community, especially drug users, probably suffer from greater psychosocial burden. Objectives: The current study aimed to predict COVID-19-induced anxiety based on attachment styles, resilience, and life expectancy in drug users. Methods: The present study is correlational descriptive-analytical research. The statistical population of this study included all drug users in 2021 who were in the process of abstaining from substance use and attended narcotics anonymous (NA) sessions in Bojnurd. In total, 134 addicts were selected based on the available sampling method. For data collection, the Corona Disease Anxiety Scale (CDAS) by Alipour et al., Attachment Styles Questionnaire (AAQ) by Hazen and Shaver, Resilience Scale by Davidson, and Miller Hope Scale (MHS) were used. Data were analyzed by descriptive statistics, Pearson correlation coefficient, and stepwise regression using SPSS 18. Results: As hypothesized, COVID-19-induced anxiety was predicted based on attachment styles, resilience, and life expectancy. Multiple correlation coefficient (0.87) was found between independent variables (attachment styles, resilience, and life expectancy) and COVID-19-induced variable, and attachment styles, resilience, and life expectancy could predict 76% (R2) of COVID-19-induced anxiety changes. Conclusions: COVID-19 and addiction are two epidemic and overlapping diseases and cause a serious threat to public health. According to the findings of this study, in order to prevent COVID-19-induced anxiety in drug users, it is necessary to consider their attachment styles, resilience, and life expectancy.