Predicting Cyberchondria and COVID-19 Anxiety based on Internet addiction in COVID-19 pandemic

The current research aimed to predict the Cyberchondria and anxiety of COVID-19 based on internet addiction in the COVID-19 pandemic in the households of Marvdasht city. According to the purpose of this research, it was a basic research type, and with a descriptive research design. The statistical population of households in Marvdasht city was 100 people, who were selected by the convenience sampling method. The research tools were Alipour et al.'s Corona Virus Anxiety Scale (2019), Mehdi Reza Sarafaraz et al.'s Cyberchondria Severity Scale (2020), and Young's Internet Addiction Test (1998) by Kimberly Young. The data were analyzed using SPSS software. After collecting and extracting the data, the scores of the participants were analyzed using Pearson's correlation coefficient and regression. The results of Pearson's correlation coefficient show that there is a positive and significant relationship between Cyberchondria and Internet addiction, and no significant relationship was found between the anxiety of COVID-19 and Internet addiction. Also, the regression results showed that Internet addiction was a significant predictor of Cyberchondria. As a result, people who deal with the Internet more than others, such as people who suffer from Internet addiction disorder and spend many hours on the Internet. More than other people, seek to solve their problems, including medical problems, through the information available on the Internet, which increases their risk of Cyberchondria and a positive and meaningful correlation between Internet addiction and Cyberchondria.