Prevalence of Internet Addiction during the COVID-19 Outbreak and Its Psycho-Demographic Risk Factors in a Sample of Iranian People

Document Type : Original Article


1 Department of Psychology, Islamic Azad University, Tehran Electronic Branch, Tehran, Iran

2 Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran


Background: During the COVID-19 pandemic and unprecedented increase in the use of online services has provided a fertile ground for Internet addiction in the community. Given the negative effects of Internet addiction on individuals and the community, addressing this issue and its consequences seem to be of high importance.
Objectives: This study aimed to examine the prevalence of Internet addiction and Psycho-demographic risk factors during the COVID-19 outbreak in a sample of Iranian people.
Methods: It was a cross-sectional descriptive correlational study, conducted from February to June 2021. Researcher-made demographic information questionnaire, Depression, Anxiety, Stress Scales (DASS-21), Young’s Diagnostic Questionnaire (YDQ), Corona Disease Anxiety scale (CDAS), Social and Emotional Loneliness Scale for Adults (SELSA-S), and Petersburg Sleep Disorder Questionnaire (PSQI) were applied on 404 people (213 men and 191 women) of internet users living in Hamadan province. In order to prevent the spread of COVID-19, the available sampling and online methods were used. Data were analyzed by Chi-square, independent t-test, and logistic regression using SPSS-24 software.
Results: According to the results, the rate of Internet addiction prevalence was 28.5. Internet addiction was occurred more in single people compared to married ones (χ2=7, p<0.000). There was no significant relationship between age, gender, educational status, and Internet addiction. There was a significant direct relationship between Internet addiction and the severity of sleep disorders (1 χ2=14.14, p<0.00), depression (χ2=24.74, p<0.000) and COVID-19 anxiety (1 χ2=19.99, p0.0). There was no significant relationship between feelings of loneliness and internet addiction. The results of Logistic regression revealed that both variables of depression and sleep disorder were significant predictors of Internet addiction with probability ratios of 1.07 and 1.06, indicating that increasing the depression score increases the risk of Internet addiction by 1.07 times (OR=1.07) and increases the sleep disorder score increases the risk of Internet addiction by 1.06 times (OR=1.06).
Conclusion: Considering the high prevalence of Internet addiction in the present study and identifying the role of depression and sleep disorders in predicting Internet addiction, it is of high importance to inform the public about the dangers of excessive use of the Internet and reduce the risk factors during the COVID-19 pandemic. Also, considering the prevalence of Internet addiction in post-COVID-19, it is critically recommended to reduce social constraints.