Skip to main content

ORIGINAL RESEARCH article

Front. Psychiatry, 23 March 2022
Sec. Public Mental Health
This article is part of the Research Topic COVID-19 Pandemic: Mental Health, Life Habit Changes and Social Phenomena View all 70 articles

Investigating Anxiety and Fear of COVID-19 as Predictors of Internet Addiction With the Mediating Role of Self-Compassion and Cognitive Emotion Regulation

\nReihaneh Moniri
&#x;Reihaneh Moniri*Kimia Pahlevani Nezhad&#x;Kimia Pahlevani NezhadFahimeh Fathali LavasaniFahimeh Fathali Lavasani
  • Deputy of Behavioral Sciences and Mental Health, Tehran Psychiatric Institute, Iran University of Medical Sciences, Tehran, Iran

Background: In addition to many deaths due to the Coronavirus pandemic, many psychological issues and problems are affecting people's health. Including the constant anxiety and fear of infecting themselves and their families, COVID-19 has led to excessive spending of time in cyberspace and the Internet.

Methods: In this study, the role of fear and anxiety of COVID-19 in predicting Internet addiction among 1,008 students was investigated. The mediating role of the two components of self-compassion and cognitive emotion regulation has also been measured. Data collection was done online due to the outbreak of the disease and a modeling method was used to analyze the data.

Results: The results shows that anxiety and fear of COVID-19 has a positive and significant relationship with both Internet addiction (r = 0.32) and maladaptive cognitive emotion regulation strategies (r = 0.17), and it has a negative relationship with self-compassion (r = −0.25).

Conclusions: The findings suggest that self-compassion can play a protective role against internet addiction at the time of COVID-19 pandemic while maladaptive strategies for emotion regulation can be risk factors for anxiety and fear of the virus.

Introduction

In December 2019, a virus of unknown origin entangled the world called SARS-CoV-2, or more commonly referred to as the COVID-19 virus. The virus began to spread from China and the city of Wuhan, which spread widely around the world despite China's rapid quarantine efforts (1). According to the World Health Organization (WHO), the coronavirus pandemic has become a global concern and measures such as social distancing, regular hand washing, and in a case of infection, house quarantining for 7 to 14 days is necessary (2). Based on WHO, the number of confirmed cases worldwide is more than 373 million and the number of deaths is about 5.65 million people as of January 2022, and is on an ascending path. In particular, Iran has reported about 6.34 million confirmed cases and more than 132 thousand deaths (3). The pandemic has effected almost every part of human life (4) such as: socializing, working, planning and even shopping. Also the social isolation which is one of the consequences of the pandemic, has not only changed the lifestyles of the people all over the world, such as the quantity of physical activities and sleep patterns, it has also influenced mental health and emotional responses of the people (5). Even it is studied that less physical activity, sleep problems related to the quarantine, and internet usage can be the risk factors for increased anxiety at the time of pandemic (6). Some psychological impacts of the disease have been investigated with the onset of the prevalence but the solutions in order to reduce the damage have been somehow neglected (7). Fear and anxiety caused by little knowledge about the virus (8), fear of disease and death (2), spreading false news (9), reduced social contacts (1), restrictions on the use of public transportations (10), economic problems (11) and excessive use of social media (12) are among the problems of this period of time. Dr. David Murphy (president of the British Psychological Society) introduced fear and anxiety as one of the basic variables that should be investigated during COVID-19 pandemic (13). Besides that, fear and anxiety as consequences of COVID-19 can lead to disorders such as depression and anxiety among adolescents (14).

An unavoidable requirement of the coronavirus pandemic is observing physical and social distancing. Physical distancing means staying 6 feet away from others while social distancing is home-staying and prohibition of outdoor activities, which has encouraged the use of virtual ways of communication. By returning people to the routine of social life, the importance of practicing physical distancing is being more emphasized. People who are infected by the coronavirus need to self-quarantine for at least 14 days and in this period of time they should stay at home, wash their hands regularly, not share items such as towels and utensils, and not having visitors. In severe cases, hospitalization and intensive care may be required. At the end of the illness, when subjects have no symptoms, with doctor's diagnosis, they can return to normal life. Quarantine has many psychological impacts such as PTSD, anxiety and irritability, insomnia, depression and anger. Also due to the fact that people spend most of their time at home, the risk of intimate partner violence (IPV) in multiple domains of abuse has increased (1519), however its benefits typically outweigh these health issues when setting public policy. Another important impact of staying at home is increasing the usage of Internet both for telecommuting and browsing for information on outbreaks and other news related to the disease such as the mortality rate (20); which can also be a trigger to the fear of COVID-19 and obtaining incorrect information (9). Besides the concern of the COVID-19 pandemic, Internet, social media and games have become an integral part of individual's lives; which has added a disorder called Internet addiction into the list of problems and psychiatric disorders (21). Addiction is defined as a high dependency on something and the inability to control the consumption that can involve some kinds of substance, behavior and process (22) such as gambling, excessive sexual behavior, compulsive buying, Internet use, or stealing (23). According to the recent statistics, about 4.66 billion people are active internet users as of February 2021, where 3.96 billion people are also active social media users (24). As of April 2019, Iran ranks first in the Middle East with 62.7 million internet users (25) and according to the report of Internet World Stats, it is the 17th country with the greatest number of internet users worldwide.

Over the last decade, increasing population size and the frequency of internet use has become a concern of the possible negative consequences of overuse (26). This concern has increased during the time of the COVID-19 pandemic due to social contact restrictions and the reduction of non-virtual communications and outdoor activities (12). There are some psychological factors which can predict addiction to the internet; such as loneliness, self-esteem and life satisfaction (27), shyness and locus of control (28), depression (29), emotional regulation (30), and self-compassion (31).

The concept of self-compassion was created in response to criticisms of the concept of self-esteem as a component of psychological health. As self-esteem is based on the performance of others, kind of social judgment and comparison, self-efficacy, true self-esteem, self-respect, and self-compassion have been identified as components that provide a better explanation for mental health. Self-compassion is a concept that consists of three parts: (a) kindness toward oneself rather than self-blaming and being self-judgmental during times of difficulty, (b) having human commonalities instead of a sense of isolation and (c) mindfulness vs. over-identification or avoidance toward painful feelings. Being self-compassionate is being used for one who understands his/her condition in a non-evaluative manner and keeps being empathic instead of over criticizing. The person interprets the situation as an experience which may occur to everyone during their lifetime, acknowledging that suffering and he is not the only person in pain in the world. Furthermore, he can keep thoughts and emotions in balanced awareness instead of attaching to one and avoiding the others (32). The relationship between self-compassion and anxiety, depression and self-criticism are negatively significant, while the positive association between self-compassion and wellbeing, optimism and happiness are proven. There is a negative relationship between internet addiction and depression and lower self-esteem thus self-compassion can play a protective role against this psychopathology (33).

Another factor that can predict internet addiction is cognitive emotion regulation which is a general term that is defined as the human's ability to manage and modulate emotions in every difficult situation of life, consciously or unconsciously (34). According to Gross' model, emotion regulation includes 5 stages: (1) situation selection, (2) situation modification, (3) attention deployment, (4) cognitive change and (5) response modulation (34). Moreover, various studies have introduced different emotion regulation strategies that fall into two categories: adaptive and maladaptive. Maladaptive strategies include repression, avoidance, and mental rumination; which are associated with a variety of disorders such as anxiety and depression. Adaptive strategies include problem solving (ability to change conditions that create undesirable emotions), acceptance (accepting emotions and feelings as they are) and reappraisal (positive interpretation of stressful situations as a way of anxiety reduction) (34, 35). Inability to use healthy strategies to moderate negative emotions may lead to many mental disorders such as affective and anxiety disorders; while adaptive ways of emotion regulation are linked to psychological and physical wellbeing (35). Additionally, some research shows that students with severe internet addiction have greater difficulties in emotion regulation (36) and it may be an important variable in understanding the relationship between mental health problems and improper use of social media (37). Other research suggests that activation of maladaptive coping strategies such as rumination, may increase the likelihood of using the Internet as a means of cognitive-emotional self-regulation. Thus, using the Internet may become a strategy for controlling unwanted negative emotions (38).

In general, the pandemic of COVID-19 has affected every part of our lives, on top our psychological health which can be influenced by some non-mental components and some interpersonal issues. Besides that, people are constantly worried about getting infected, whether themselves or their loved ones, so this fear and anxiety has become an integral part of their lives. People may cope with this pressure in different ways; some by exercising at home, some through learning new skills, and some people may spend most of their time in cyberspace, computer games, and more generally, on the Internet. In order to help with the current situation, this work intends to investigate the relationship between anxiety and fear caused by the COVID-19 disease, and Internet addiction with the mediating role of self-compassion and cognitive emotion regulation.

Methods

Samples

The target sample in this research was students from different academic levels which were selected using the convenience sampling method. They were invited to participate in this research through popular social media pages and groups. Due to the prevalence of the coronavirus and the need to follow health protocols, online methods were used to collect data in this study. Questionnaires were sent to the target population, through programs such as WhatsApp, Telegram and Instagram. The survey was started in January 2020 and the data collection was done after 2 months. Inclusive criteria are students and those who have access to the internet in order to fill out a questionnaire online. If a questionnaire was not completely done, or only one option had been selected in all questions, the person was excluded from the sample. The questuionnaire was sent to more than 1,200 students and 1,008 of them filled the inclucive criterias. Participation or non-participation in the study was not beneficial or harmful for individuals and all of them answered the questionnaires based on personal satisfaction.

In this study, 12 samples for each subscale were collected. This number of samples required is based on the book of multivariate regression in behavioral research written by Kerlinger (39), which indicates the need for 12 or 15 samples per subscale in this method of analysis. With a total of 18 subscales, there was a requirement to collect data from at least 216 students.

Materials

Corona Disease Anxiety Scale

The CDAS has recently been developed and validated to measure anxiety caused by the outbreak of coronavirus in Iran. The final version of this questionnaire has 18 items and 2 components. Items 1 to 9 measure psychological symptoms and items 10 to 18 measure physical symptoms. This tool is scored in a 4-point Likert scale (never = 0, sometimes = 1, most times = 2 and always = 3). High scores in this questionnaire indicate higher levels of anxiety in the individuals. The reliability of this tool was obtained using Cronbach's alpha method for the psychological symptom α = 0.879, the physical symptom α = 0.861, and the whole questionnaire α = 0.919 (40).

Young Internet Addiction Test (IAT)

The IAT is a 20-item questionnaire that assesses the person's performance at work, school and home (3 questions), social behaviors (3 questions), emotional communication and response via the Internet (7 questions), and general patterns of Internet use (7 questions) (41). Respondents answer on a 5-point Likert measure (“does not apply” to “always”), which people score from 0 to 100. Those who get <49 will be in the “average users”' category, participants scoring between 50 and 79 are “problematic internet users,” and those scoring 80 and above be categorized as “severely problematic users.” In the study of Widyanto et al. (42), the internal validity of the questionnaire was higher than 0.92 and the validity of the retest was also reported to be significant. It also shows good to moderate internal consistency and, alpha coefficients of 0.82 (42). In a Persian psychometric survey of the test, the validity of the retest was 0.82 and internal consistency, where the alpha coefficient was 0.88 (43).

Self-Compassion Scale Short-Form

The Self-Compassion Scale (SCS) is a 26-item questionnaire with six subscales consist of self-kindness, self-judgment, common humanity, isolation, mindfulness and over-identification; which is a valid and reliable test (44). The Self-Compassion Scale Short-Form (SCSSF) is a shorter 12-item questionnaire and with a 5-point Likert measure that is a reliable and valid alternative to the full version with a high correlation (r ≥ 0.97). The internal consistencies for the SCS–SF subscales were 0.54 and 0.75 for the English version of SCS–SF. Reliabilities for all but one subscale (self-kindness) were above 0.60, and Cronbach's alphas of 0.60 and above are acceptable (45). In the Persian version of the test, Cronbach's alphas of 0.91 for the whole scale and 0.77 to 0.92 for the six subscales were calculated. Validity coefficient with the general health questionnaire was−0.45 and for the subscales from−0.28 to−0.48 (46).

Cognitive Emotion Regulation Questionnaire

The CERQ is a 36-item multidimensional questionnaire designed to identify cognitive emotion regulation strategies that people use in stressful, threatening or traumatic life events; which is a valuable and reliable tool. This questionnaire examines 9 cognitive strategies for emotion regulation (self-blame, blaming others, acceptance, refocusing on planning, positive refocusing, rumination, positive reappraisal, putting into perspective, and catastrophizing) (47). Moreover, the short-form of cognitive emotional regulation (CERQ-short) is an 18-item questionnaire with high alpha reliabilities. Self-blame has the lowest alpha in this questionnaire between the subscale (0.67) and the rest of the alphas were in a range of 0.73 to 0.81 (48). Based on the standardization done in Iran, this questionnaire with Cronbach's alpha between 0.68 and 0.82 (for 9 subscales) has a good validity in the Iranian society (49).

Result

The research is a cross-sectional and modeling method using SPSS Statistics v22 and AMOS v22 has been applied to analyze the data. Also a description of the demographic information of the participants is given in Table 1.

TABLE 1
www.frontiersin.org

Table 1. Demographic characteristics of study sample (n = 1,008).

Descriptive indicators such as mean, standard deviation, range of values, and correlation matrix of the studied variables are reported in Table 2. As can be seen, anxiety and fear of COVID-19 has a positive and significant relationship with both Internet addiction (r = 0.32) and maladaptive cognitive emotion regulation strategies (r = 0.17) and it has a negative relationship with self-compassion (r = -0.25).

TABLE 2
www.frontiersin.org

Table 2. Descriptive statistics and the correlation matrix (n = 1,008).

Considering the significant relationships between research variables, the results of path analysis are summarized in Table 3 to investigate the mediating role of self-compassion and cognitive emotion regulation strategies as the role of mediators. The results show that the relationship between all pathways in the mediation model except anxiety and fear of COVID-19 pathway with adaptive cognitive emotion regulation strategies were statistically significant (p < 0.0001). Therefore, the findings support the mediating role of self-compassion and maladaptive cognitive emotion regulation strategies in the relationship between anxiety and fear of COVID-19 and Internet addiction. The results are summarized in Figure 1 below. In other words, these findings suggest that people with high anxiety and fear of COVID-19 use maladaptive emotion regulation strategies, which in turn increase their susceptibility to Internet addiction. Also, people with high anxiety and fear of COVID-19 with low levels of self-compassion, are more vulnerable in the path of Internet addiction.

TABLE 3
www.frontiersin.org

Table 3. Summary of mediation analyses on direct and indirect effects of Corona Disease Anxiety on internet addiction (n = 1,008).

FIGURE 1
www.frontiersin.org

Figure 1. Examining the indirect effect of corona disease anxiety on internet addiction through self-compassion and emotion regulation.

Discussion

The aim of this study was to investigate anxiety and fear of COVID-19 as predictors of Internet addiction with the mediating role of self-compassion and cognitive emotion regulation. From the results, it is concluded that in the days when the world is widely affected by COVID-19, there is an association between the fear and anxiety of the virus and the misuse of the Internet. Although the level of anxiety may not indicate that one is suffering from an anxiety disorder, it still requires awareness and, if necessary, intervention. Also, due to the continuing epidemic and its other consequences, people's fear and anxiety may increase in severity to the extent of psychiatric diagnosis. Various factors can be effective in this regard. For example, it seems that limitations related to social distancing, the need to commit to health protocols and high mortality rates, can cause a significant rise in anxiety and fear, which leads to obsessive behaviors such as spending time in cyberspace.

Our findings show that a high level of compassion can be effective in reducing the effect of COVID-19 anxiety on Internet addiction. Since the compassionate person scores higher in the three main indicators of this component, namely self-kindness, human commonalities and mindfulness, it can be inferred as a protective variable, which is congruent with the study of Muris et al. (50, 51). Constantly blaming oneself for the possibility that the individual's actions will put himself or his family members at the risk of infection, as well as feeling responsible for the health of people with whom they are in contact, can cause great anxiety, which is contrary to the constructive effects of self-kindness. Another effect of self-blame is that it leads to the application of maladaptive coping strategies, which is followed by decreased self-esteem, the feeling of helplessness, and social isolation (52). The feeling of common humanity, especially during the coronavirus pandemic, can create this perception that people all around the world are involved in an unavoidable condition, which has imposed many deaths and major limitations in the way of normal life. This factor creates a feeling of closeness to other human beings. Therefore, the less one considers themself a member of human society, the more one will experience anxiety and separation (52, 53). In addition, lack of self-awareness about the present and the constant mental conflict with the issue of coronavirus and fear of death (of themselves and/or their loved ones), and over-identification with these thoughts also increases the level of anxiety. All of these factors explain people turning to virtual networks and the Internet as an inefficient way to deal with this fear and anxiety (12, 54).

Cognitive emotion regulation plays an important role in coping with stressful situations, as it determines the effect of these situations on our mental health. The use of adaptive strategies can help a person cope with stressors such as coronavirus pandemic more efficiently. According to the results, there is a positive relationship between anxiety and fear of coronavirus and the use of maladaptive strategies of cognitive emotion regulation such as avoidance, suppression and rumination, which is consistent with Jungmann and Witthoft (55). Most of people have ruminating thoughts with anxious content such as risk of infection and death of themselves or their loved ones. Moreover, daily exposure to the news of death rates cause people to experience high levels of anxiety. Obsessive use of internet is an avoiding strategy in order to feel less anxious during the pandemic. The negative reinforcing effect of using the Internet turns this behavior into an addiction. Some other reasons for the pathological use of internet could be some dissociative symptoms which are found in their neural pathways (56). It is also proven that social media users have much more social and emotional impairments in comparison with the non-users (57). All these descriptions explain the positive and significant relationship between anxiety and fear of COVID-19 and Internet addiction.

Conclusions

Due to the increase in addictive behaviors during COVID-19 pandemic (58), self-compassion can play a protective role while maladaptive strategies for emotion regulation such as self-blame, blaming others, and rumination can be risk factors for anxiety and fear of the virus which leads to more obsessive use of internet.

Suggestions

Self-compassion can be enhanced with treatments such as Mindful Self Compassion (MSC), Compassion Focused Therapy (CFT), Mindfulness-Based Stress Reduction (MBSR), Acceptance and Commitment Therapy (ACT), Dialectical Behavior Therapy (DBT) and Mindfulness Based Cognitive Therapy (MBCT) (59). Also, training emotional regulation skills in limited sessions can help control the level of experienced anxiety. It can also improve adaptive strategies and reduce the use of maladaptive strategies at the time of stress (60). In addition internet is not only the cause of addiction but also due to the extreme relation between anxiety and stress and the use of it, Internet-based interventions could be used to promote wellbeing and manage psychological distress during Covid-19 pandemic (61).

Limitations

This study was performed on a student population, and precautions should be taken in generalizing the results to other individuals. Also, due to the prevalence of coronavirus, data collection has been done online and by the convenience sampling method, which may bias the results.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author Contributions

All the data collecting, analyzing, and writing the whole research has been done with the efforts of RM and KP, under the supervision of FL. All authors have read and approved the final manuscript.

Funding

This research has been written with the efforts of the authors of the article.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Li QG, Wu X, Wang P, Zhou X, Tong L, Ren Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Eng J Med. (2020) 382:1199–207. doi: 10.1056/NEJMoa2001316

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Mohammadpour M, Ghorbani V, Khoramnia S, Ahmadi SM, Ghvami M, Maleki M. Anxiety, self-compassion, gender differences and COVID-19: predicting self-care behaviors and fear of COVID-19 based on anxiety and self-compassion with an emphasis on gender differences. Iran J Psychiatry. (2020) 15:213–9. doi: 10.18502/ijps.v15i3.3813

PubMed Abstract | CrossRef Full Text | Google Scholar

3. World Health Organization. WHO Coronavirus (COVID-19) Dashboard. (2022). Available online at: https://covid19.who.int/. (accessed January, 2022).

Google Scholar

4. Fountoulakis KN, Karakatsoulis G, Abraham S, Adorjan K, Ahmed HU, Alarcón RD, et al. Results of the COVID-19 mental health international for the general population (COMET-G) study. Eur Neuropsychopharmacol. (2022) 54:21–40. doi: 10.1016/j.euroneuro.2021.10.004

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Caroppo E, Mazza M, Sannella A, Marano G, Carla Avallone AEC, Janiri D, et al. Will nothing be the same again?: changes in lifestyle during COVID-19 pandemic and consequences on mental health. Int J Environ Res Public Health. (2021) 18:8433. doi: 10.3390/ijerph18168433

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Smirnova D, Syunyakov T, Pavlichenko A, Bragin D, Fedotov I, Filatova V, et al. Interactions between anxiety levels and life habits changes in general population during the pandemic lockdown: decreased physical activity, falling asleep late and internet browsing about COVID-19 are risk factors for anxiety, whereas social media use is not. Psychiatr Danub. (2021) 33:119–29.

PubMed Abstract | Google Scholar

7. Lee SA, Mathis AA, Jobe MC, Pappalardo EA. Clinically significant fear and anxiety of COVID-19: a psychometric examination of the coronavirus anxiety scale. Psychiatry Res. (2020) 290:113112. doi: 10.1016/j.psychres.2020.113112

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Shahed-Haghghadam H, Fathi-Ashtiani A, Rahnejat AM, Soltani MAT, Ebrahimi MR, Donyavi V, et al. Psychological Consequences and Interventions during the COVID-19 Pandemic: Narrative Review. (2020). p. 2.

PubMed Abstract | Google Scholar

9. Lin C-Y, Broström A, Griffiths MD, Pakpour AH. Investigating mediated effects of fear of COVID-19 and COVID-19 misunderstanding in the association between problematic social media use, psychological distress, and insomnia. Internet Interv. (2020) 21:100345. doi: 10.1016/j.invent.2020.100345

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Yang Y, Li W, Zhang Q, Zhang L, Cheung T, Xiang Y-T. Mental health services for older adults in China during the COVID-19 outbreak. Lancet Psychiatry. (2020) 7:e19. doi: 10.1016/S2215-0366(20)30079-1

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Atkeson A. What Will Be the Economic Impact of covid-19 in the US? Rough Estimates Of Disease Scenarios. NBER Working Paper (2020). doi: 10.3386/w26867

CrossRef Full Text | Google Scholar

12. Dong H, Yang F, Lu X, Hao W. Internet addiction and related psychological factors among children and adolescents in China during the coronavirus disease 2019 (COVID-19) epidemic. Front Psychiatry. (2020) 11:751. doi: 10.3389/fpsyt.2020.00751

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Harper CA, Satchell LP, Fido D, Latzman RD. Functional fear predicts public health compliance in the COVID-19 pandemic. Int J Ment Health Addict. (2020) 19:1875–88. doi: 10.31234/osf.io/jkfu3

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Secer I, Ulas S. An investigation of the effect of COVID-19 on OCD in youth in the context of emotional reactivity, experiential avoidance, depression and anxiety. Int J Ment Health Addict. (2020) 19:2306–19. doi: 10.1007/s11469-020-00322-z

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Lee SM, Kang WS, Cho A-R, Kim T, Park JK. Psychological impact of the 2015 MERS outbreak on hospital workers and quarantined hemodialysis patients. Compr Psychiatry. (2018) 87:123–7. doi: 10.1016/j.comppsych.2018.10.003

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Taylor MR, Agho KE, Stevens GJ, Raphael B. Factors influencing psychological distress during a disease epidemic: data from Australia's first outbreak of equine influenza. BMC Public Health. (2008) 8:347. doi: 10.1186/1471-2458-8-347

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Liu X, Kakade M, Fuller CJ, Fan B, Fang Y, Kong J, et al. Depression after exposure to stressful events: lessons learned from the severe acute respiratory syndrome epidemic. Compr Psychiatry. (2012) 53:15–23. doi: 10.1016/j.comppsych.2011.02.003

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Marjanovic Z, Greenglass ER, Coffey S. The relevance of psychosocial variables and working conditions in predicting nurses' coping strategies during the SARS crisis: an online questionnaire survey. Int J Nurs Stud. (2007) 44:991–8. doi: 10.1016/j.ijnurstu.2006.02.012

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Mazzaa M, Marano G, Laib C, Janiria L, Sania G. Danger in Danger: Interpersonal Violence During COVID-19 Quarantine (2020).

PubMed Abstract | Google Scholar

20. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health. (2020) 17:1729. doi: 10.3390/ijerph17051729

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Ayatollah Fathi SS, Sharifirahnmo S, Rostami H, Abbasikasani H. Prediction of computer voyeurism and stigma of the first wave of the coronavirus disease-2019 pandemic based on the dimensions of internet addiction among youth. Avicenna J Clin Med. (2020) 27:124–32. doi: 10.29252/ajcm.27.2.124

CrossRef Full Text | Google Scholar

22. Poli R. Internet-addiction-update-diagnostic-criteria-assessment-and-prevalence. Neuropsychiatry. (2017) 7:04–08. doi: 10.4172/Neuropsychiatry.1000171

CrossRef Full Text | Google Scholar

23. Grant JE, Chamberlain SR. Expanding the definition of addiction: DSM-5 vs. ICD-11. CNS Spectr. (2016) 21:300–3. doi: 10.1017/S1092852916000183

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Statista. Internet Users in the Middle East. (2019). Available online at: https://www.statista.com/statistics/603061/number-of-internet-users-in-middle-east-countries/. (accessed January, 2021).

Google Scholar

26. Kuss DJ, Griffiths MD, Karila L, Billieux J. Internet addiction: a systematic review of epidemiological research for the last decade. Curr Pharm Des. (2014) 20:4026–52. doi: 10.2174/13816128113199990617

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Bozoglan B, Demirer V, Sahin I. Loneliness, self-esteem, and life satisfaction as predictors of Internet addiction: a cross-sectional study among Turkish university students. Scand J Psychol. (2013) 54:313–9. doi: 10.1111/sjop.12049

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Chak K, Leung L. Shyness and locus of control as predictors of internet addiction and internet use. Cyberpsychol Behav. (2004) 7:559–70. doi: 10.1089/cpb.2004.7.559

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Lan CM, Lee YH. The predictors of internet addiction behaviours for Taiwanese elementary school students. Sch Psychol Int. (2013) 34:648–57. doi: 10.1177/0143034313479690

CrossRef Full Text | Google Scholar

30. Yõldõz MA. Emotion regulation strategies as predictors of internet addiction and smartphone addiction in adolescents. J Educ Sci Psychol. (2017) 21:66–78.

PubMed Abstract | Google Scholar

31. Boonlue T, Briggs P, Sillence E. Self-Compassion, Psychological Resilience and Social Media Use in Thai Students. (2016). doi: 10.14236/ewic/HCI2016.4

CrossRef Full Text | Google Scholar

32. Neff K. Self-compassion: an alternative conceptualization of a healthy attitude toward oneself. Self Identity. (2003) 2:85–101. doi: 10.1080/15298860309032

CrossRef Full Text | Google Scholar

33. Akin A, Iskender M. Self-compassion and internet addiction. Turkish Online J Educ Technol. (2011) 10:215–21.

Google Scholar

34. Aldao A, Nolen-Hoeksema S, Schweizer S. Emotion-regulation strategies across psychopathology: a meta analytic review. Clin Psychol Rev. (2010) 30:217–37. doi: 10.1016/j.cpr.2009.11.004

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Schafer JO, Naumann E, Holmes EA, Tuschen-caffier B, Samson AC. Emotion regulation strategies in depressive and anxiety symptoms in youth: a meta-analytic review. J Youth Adolesc. (2017) 46:261–76. doi: 10.1007/s10964-016-0585-0

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Mo PKHC, Chan VWY, Chan SW, Lau JTF. The role of social support on emotion dysregulation and Internet addiction among Chinese adolescents: a structural equation model. Addict Behav. (2018) 82:86–93. doi: 10.1016/j.addbeh.2018.01.027

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Elhai JD, Brian JH, Erwin MC. Emotion regulation's relationships with depression, anxiety and stress due to imagined smartphone and social media loss. Psychiatry Res. (2018) 261:28–34. doi: 10.1016/j.psychres.2017.12.045

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Akbari M. Metacognitions or distress intolerance: the mediating role in the relationship between emotional dysregulation and problematic internet use. Addict Behav Rep. (2017) 6:128–33. doi: 10.1016/j.abrep.2017.10.004

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Pedhazur EJ, Kerlinger FN. Multiple Regression In Behavioral Research, Holt: Rinehart and Winston (1982).

Google Scholar

40. Alipour A, Ghadami A, Alipour Z, Abdollahzadeh H. Preliminary Validation of the Corona Disease Anxiety Scale (CDAS) in the Iranian Sample. Quart J Health Psychol. (2020) 8:163–75. doi: 10.30473/HPJ.2020.52023.4756

CrossRef Full Text | Google Scholar

41. Young KS. Caught in the Net: How To Recognize The Signs Of Internet Addiction–And A Winning Strategy For Recovery. (1998). p. 256. doi: 10.1037/t41898-000

CrossRef Full Text | Google Scholar

42. Widyanto L, McMurran M. The psychometric properties of the internet addiction test. Cyberpsychol Behav. (2004) 7:443–50. doi: 10.1089/cpb.2004.7.443

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Alavi SS, Maracy MR, Najafi M, Jannatifard F, Rezapour H. Psychometric properties of Young internet addiction test. J Behav Sci. (2010) 4.

Google Scholar

44. Neff KD. The development and validation of a scale to measure self-compassion. Self Identity. (2003) 2:223–50. doi: 10.1037/t10178-000

CrossRef Full Text | Google Scholar

45. Raes F, Pommier E, Neff KD, Van gucht D. Construction and factorial validation of a short form of the self compassion scale. Clin Psychol Psychother. (2011) 18:250–5. doi: 10.1002/cpp.702

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Shahbazi R, Maghami J. Confirmatory factor analysis of the persian version of the self-compassion rating scale-revised. J Psychol Models Methods. (2015) 19:31–46.

Google Scholar

47. Garnefski N, Kraaij V. The cognitive emotion regulation questionnaire. Eur J Psychol Assess. (2007) 23:141–9. doi: 10.1027/1015-5759.23.3.141

CrossRef Full Text | Google Scholar

48. Garnefski N, Kraaij V. Cognitive emotion regulation questionnaire – development of a short 18-item version (CERQ-short). Pers Individ Dif. (2006) 41:1045–53. doi: 10.1016/j.paid.2006.04.010

CrossRef Full Text | Google Scholar

49. Hasani J. The reliability and validity of the short form of the cognitive emotion regulation questionnaire. Behav Sci Res. (2011) 9:229–40.

PubMed Abstract | Google Scholar

50. Muris P, Petrocchi N. Protection or vulnerability? a meta-analysis of the relations between the positive and negative components of self-compassion and psychopathology. Clin Psychol Psychother. (2017) 24:373–83. doi: 10.1002/cpp.2005

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Liu Q-Q, Xiu-juanhu Y, Yu-Tingzhang H, Chen-Yan Z. Peer victimization, self-compassion, gender and adolescent mobile phone addiction: Unique and interactive effects. Child Youth Serv Rev. (2020) 118. doi: 10.1016/j.childyouth.2020.105397

CrossRef Full Text | Google Scholar

52. Shiri A, Alilou MM. Role of self-blame and other-blame strategies on the symptoms of internet addiction by the mediation of anxiety. Q J New Psychol Res. (2020) 15:11–25.

Google Scholar

53. Yao MZ, Zhi-Jin Z. Loneliness, social contacts and internet addiction: a cross-lagged panel study. Comput Hum Behav. (2014) 30:164–70. doi: 10.1016/j.chb.2013.08.007

CrossRef Full Text | Google Scholar

54. Priego-Parra BA, Romero AT, Pinto-Gálvez SM, Ramos CD, Salas-Nolasco O, et al. Anxiety, depression, attitudes, and internet addiction during the initial phase of the 2019 coronavirus disease (COVID-19) epidemic: a cross-sectional study in México. (2020). doi: 10.1101/2020.05.10.20095844

CrossRef Full Text | Google Scholar

55. Jungmann SM, Witthoft M. Health anxiety, cyberchondria, and coping in the current COVID-19 pandemic: which factors are related to coronavirus anxiety? J Anxiety Disord. (2020) 73:102239. doi: 10.1016/j.janxdis.2020.102239

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Lai C, Altavilla D, Mazza M, Scappaticci S, Tambelli R, Aceto P, et al. Neural correlate of internet use in patients undergoing psychological treatment for Internet addiction. J Mental Health. (2017) 26:276–82. doi: 10.1080/09638237.2017.1294745

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Tonioni F, Mazza M, Autullo G, Pellicano G, Aceto P, Catalano V, et al. Socio-emotional ability, temperament and coping strategies associated with different use of Internet in Internet addiction. Eur Rev Med Pharmacol Sci. (2018) 22:3461–6. doi: 10.26355/eurrev_201806_15171

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Sun YL, Bao Y, Meng Y, Sun S, Schumann Y, Kosten G, et al. Brief report: increased addictive internet and substance use behavior during the COVID-19 pandemic in China. Am J Addict. (2020) 29:268–70. doi: 10.1111/ajad.13066

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Foroughi AAK, Rafiee S, Taheri S, Abbas A. Self-compassion: conceptualization, research, and interventions (brief review). Shenakht J Psychol Psychiatry. (2020) 6:77–87. doi: 10.29252/shenakht.6.6.77

CrossRef Full Text | Google Scholar

60. Ramezanzadeh F, Moradi A, Mohammadkhani SH. Effectiveness of the training of emotion regulation skills in executive functions and emotion regulation strategies in adolescents at risk. J Cogn Psychol. (2014) 2:37–45.

Google Scholar

61. Brog NA, Hegy JK, Berger T, Znoj H. Effects of an internet-based self-help intervention for psychological distress due to COVID-19: results of a randomized controlled trial. Internet Interv. (2021) 27:100492. doi: 10.21203/rs.3.rs-59343/v2

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: anxiety, COVID-19, internet addiction, self-compassion, cognitive emotion regulation

Citation: Moniri R, Pahlevani Nezhad K and Lavasani FF (2022) Investigating Anxiety and Fear of COVID-19 as Predictors of Internet Addiction With the Mediating Role of Self-Compassion and Cognitive Emotion Regulation. Front. Psychiatry 13:841870. doi: 10.3389/fpsyt.2022.841870

Received: 22 December 2021; Accepted: 24 February 2022;
Published: 23 March 2022.

Edited by:

Daria Smirnova, Samara State Medical University, Russia

Reviewed by:

Marianna Mazza, Agostino Gemelli University Polyclinic (IRCCS), Italy
Lucia Romo, Université Paris Nanterre, France

Copyright © 2022 Moniri, Pahlevani Nezhad and Lavasani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Reihaneh Moniri, reihaneh1996@yahoo.com

ORCID: Reihaneh Moniri orcid.org/0000-0002-2725-2174
Kimia Pahlevani Nezhad Orcid.org/0000-0002-7039-0142

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.