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1- University of Isfahan
Abstract:   (52 Views)
Introduction: In late 2019, a specific disease called Covid-19 was identified in Wuhan, China, and then spread worldwide. The coronavirus pandemic has had different psychological effects on individuals; One of these effects has been an increase in the level of coronavirus anxiety. Because coronavirus anxiety has a detrimental effect on peoplechr('39')s live, identifying and targeting its predictors can be effective in managing coronavirus anxiety. Therefore, the purpose of this study was to predict coronavirus anxiety based on resilience, cognitive emotion regulation and cyberchondria.
Methods: ­The research method was descriptive and the statistical population included all Isfahan’s residents aged 18 to 60 years (The mean age of participants was 33.74±8.15) in 2020 year. Among this population, the sample were selected by convenience sampling method. Due to the specific conditions of the pandemic, the questionnaires was prepared online and published on social networks. Then, those who were interested, completed the questionnaires. After removing incomplete and distorted questionnaires, the sample size reached 409 people (342 women and 67 men).  Data were collected by Lee’s Coronavirus Anxiety Scale, Connor and Davidsonchr('39')s Resilience Scale, Garnefski and Kraaij’s Cognitive Emotion Regulation Questionnaire and McElroy et al.’s Cyberchondria Severity Scale. Then, data were analyzed using SPSS19 software through Pearson correlation coefficient and enter linear regression analysis.
Results: Based on the obtained value of adjusted R2 (0/155), the results of the enter linear regression analysis showed that in general, about 15.5% of the total changes of the dependent variable (coronavirus anxiety) can be explained by independent variables of the study including resilience, nine subscales of cognitive emotion regulation including self-blame, acceptance, rumination, positive refocusing, planning, positive reappraisal, putting into perspective, catastrophizing and other-blame as well as cyberchondria; But after a more detailed analysis of the model by  separation of independent variables and considering the value of T and its significance, the results showed that in more detail only the variables of resilience, subscales of self-blame and acceptance in the variable of cognitive emotion regulation and cyberchondria were able to predict coronavirus anxiety (P <0.05).
Conclusion: Regarding the research results, several important points can be mentioned; Resilient people are highly adaptable to difficult situations such as the Covid-19 pandemic and do not easily become severely anxious. In addition to resilience, the quality of cognitive emotion regulation (adaptive or maladaptive) can play a key role in managing coronavirus anxiety. Cyberchondria can also increase the coronavirus anxiety. Based on the findings, it can be implicitly concluded that by designing interventions based on promoting resilience and modifying cognitive emotion regulation strategies and manipulating cyberchondria-related actions, it is possible to manage coronavirus anxiety. This study, like other studies, faced limitations; For example, the lack of cooperation of some people in completing the questionnaires, the sample limitation to people living in Isfahan, the lack of random sampling and not limiting the age range of participants in the study. By considering these limitations, the generalization of results should be done with sufficient caution.
     
Type of Study: Research |
Received: 2021/03/12 | Accepted: 2021/10/12 | Published: 2021/11/16

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