Social Media and Resilience in the COVID-19 Crisis

Rita Mano

Department of Human Services, University of Haifa, Haifa, Israel.

DOI: 10.4236/aasoci.2020.1011026                

Abstract

Social media have affected everyday life for many individuals for many years. Social media is now a major route for networking and increased support due to the limitations imposed to alleviate the quick and problematic spread of the pandemic. Considering the emergence of a crisis followed by the pandemic, here we present a general framework to unravel the impact of social media on resilience during the pandemic. More specifically, we present and discuss the possibility of both positive and negative outcomes of social media use on resilience during the crisis of COVID-19.

Keywords

Social Media Use, Social Media Effects, Resilience, COVID-19

1. Introduction

A crisis is experienced when members of a society face an event or set of unexpected events that rose suddenly and are caused by natural, technological, or human causes. A particular case of crisis is the present pandemic of COVID-19, which can be defined as a social phenomenon that triggered substantial loss of social and economic resources. When such conditions exist then resilience is attainable including physical and mental health deterioration (Norris et al., 2008). Technology can become a valuable resource for coping with uncertainly and restore or replace lost or unavailable resources (Masten, 2018; Vindevogel, 2017). The role of social media in this process cannot be underestimated (Whittaker, McLennan, & Handmer, 2015) because accessing social media during and following disasters (Pawar et al., 2012; Southwick et al., 2016) shape the process of resilience that within the complexity of a crisis such as COVID-19 (Reghezza-Zitt & Rufat, 2019). Here we consider the positive and negative aspects of social media among individuals who experience a crisis during COVID-19 and discuss how differences in the extent of use of social media and socioeconomic differences affect resilience.

Social media use increases constantly in the 21st century. In 2019, 72% of U.S. adults used at least one social media site. Sixty-eight percent of teen social media users say that they have had people support them through difficult times through social media platforms (Lenhart et al., 2015). In the United States, about seven of 10 individuals use social media to connect with others, receive news content, share information, and entertain themselves (Pew Research Center, 2018). Young individuals use social media for a variety of reasons including entertainment, identity formation, and social enhancement and maintaining interpersonal connections (Ifinedo, 2016).

The online platforms of connectivity provide individuals with a platform that overcomes barriers of distance and time to connect and reconnect with others and thereby expand and strengthen their offline networks and interactions (Antoci et al., 2015; Hall, Kearney, & Xing, 2018; Subrahmanyam, Reich, Waechter, & Espinoza, 2008). Social media use protects therefore against the detrimental effects of stress and threat commonly experienced by individuals during crises and enhances experiences of well-being (Barasa et al., 2018). For all these reasons, social media can increase significantly the level of resilience among individuals who experience crises (Mano et al., 2019). While studies provide ample evidence of the impact of online networks and interactions as effective means to compensate for the less frequent offline interaction and the economic, social, and health outcomes resulting from it (Antoci, Sabatini, & Sodini, 2015) yet, we know little of the impact of social media on resilience during a crisis.

2. Defining Resilience

Resilience is defined as the process of effectively negotiating, adapting to, or managing significant sources of stress or trauma. Individuals seeking to regain control of the situation are likely to use the resources not affected by the crisis to install stability (Masten, 2018; Vindevogel, 2017).

Resilience studies focus on positive recovery and adaptation processes and the analysis of a system’s strengths, resilience has been gradually associated with social-ecological factors important in developing the sense of well-being under stress. Resilience in the COVID-19 crisis is the process of adequate adaptation to significant stressors and the potential for quick and decisive recovery, especially in times of crises when individuals need social support (Sippel et al., 2015). In order for resilience to rake place rapidly and completely resources should be available and accessible immediately. These resources should be also abundant in the senses that no competition between individuals would take place and they are not destroyed by excessive use.

An influential model addressing resilience is that of Norris and Colleagues (2008). The model addresses resilience in community as the outcome of networked resources including economic development, social capital, and information communication. Indeed, Chan maintains that “by harnessing the characteristics of the social media tools, organizational capacity to demonstrate resilience in response to crises can be significantly enhanced by creating new avenues for collaboration to help build more resilient communities over time” (Chan, 2013: p. 5; Whittaker, McLennan, & Handmer, 2015). the potential of online networks to connect individuals and groups and expand the depth and extent of connectivity (Jurgens & Helsloot, 2018) has become noticed in disaster-induced communities (Whittaker, McLennan, & Handmer, 2015) affecting and even strengthening offline networks and interactions (Antoci et al., 2015; Hall et al., 2018) . All these are of immense importance in relieving stress that often follows crises (Pawar & Rathod, 2007; Sippel et al., 2015).

3. Social Media and Resilience

Originally, social media has been regarded as an important source of information especially when individuals are in a state of uncertainty and possible dissatisfaction with existing sources of information (Jung & Moro, 2014; Chan, 2013). However, with time social media and online channels are identified with the involvement of individuals in the virtual social space (Kreijns et al., 2004) . This involvement provides social support and hence lower discomfort (Wixom and Todd, 2005; Wang et al., 2012; Rosenberg, 2019) that is especially important in times of crisis (Chan, 2013).

IIa: Positive effects of social media use on resilience

The positive effects of social media on individual wellbeing are widely known by now. First, social media decreases the likelihood of social isolation since the increase in connectivity increases a sense of belonging and decreases loneliness (Burke et al., 2010; Stepanikova et al., 2010). Second, social media lowers discomfort because it increases the potential of expression that is often limited in day-to-day interactions (Wixom and Todd, 2005; Wang et al., 2012; Rosenberg, 2019) that is especially important in times of crisis (Chan, 2013). Third, social media increases the likelihood for positive social support from social groups, family, friendships and community that are especially important when we are disconnected from the external environment (Davis, 2012; Dolev-Cohen and Barak, 2013; Diener, 2009) . The notion of social support is especially noticed because it mediates the effects of life stress on health and well-being (Pawar & Rathod, 2007; Sippel et al., 2015). Positive social support can provide protection against stress and facilitate in development of individual resilience among individuals who face significant adversity (Zautra, Hall, & Murray, 2010). Fourth, social media use has been associated with a decrease in depression and loneliness and an increase in self-esteem and social support among this population. Finally, online activity can increase resilience as well. Social media includes a variety of online activities involving the use of profiles, comments, photos, or video sharing. These expand the depth and extent of connectivity (Jurgens & Helsloot, 2018) and enable individuals to expand their network (Smith and Anderson, 2018) thus improving that chances for more extensive social support once the crisis is over. While social media use has been linked to psychological well-being, the findings have not been unanimous.

IIb: Negative effects of social media use on resilience

The fact that social media use is considered to have become popular across all age groups (Smith & Anderson, 2018) is still debated especially because most studies have focused on adolescent and young adults in college settings (e.g., Booker, Kelly, & Sacker, 2018; Ellison et al., 2007; Kross et al., 2013). The specific of these samples in terms of age led to a growing body of research asking how social media use is associated with some health-related outcomes. For example, a recent longitudinal study found that Facebook use is generally negatively associated with mental well-being (Shakya & Christakis, 2017). Another study examining the influence of Facebook use on subjective well-being over time among young adults found that Facebook, rather than enhancing well-being, might undermine it (Kross et al., 2013). Several recent studies have also found negative associations of social media use with a variety of indicators of mental health among adolescents and young adults. For example, in a study drawing data from a sample of adolescents and their parents throughout the United States, Barry, Sidoti, Briggs, Reiter, and Lindsey (2017) found that social media use is moderately and positively related to adolescent-reported fear of missing out and loneliness as well as with parent-reported hyperactivity/impulsivity, anxiety, and depression.

Similarly, Berryman et al. (2018) found that while overall social media use was not predictive of impaired mental health functioning, one particular activity, that is, “vaguebooking” (posting unclear but alarming posts to get attention), was found to be predictive of suicidal ideation among young adults. Another study that assessed the impact of overall social media use, nighttime-specific social media use, and emotional investment in social media on adolescent sleep and well-being also found that nighttime-specific use and emotional investment are more important than overall use in determining adolescent sleep and well-being (Woods & Scott, 2016).

Social media and online networks make it easier for individuals to create a mass circulation of their message transmitted via different online means, such as instant messaging, blogs, group lists and forums, and chat rooms (Leavitt et al., 2009). When people go through the process of “social exchange”, they talk to each more frequently to exchange information or opinions. These networks prompt spontaneous and intentional or accidental increase of influence on others seeking to increase and maintain high personal involvement. However, according to the social contagion theory individual’s behaviors are subject to those of the people who are important to that individual (Christakis & Fowler, 2013; Heath & Porter, 2017).

The positive and negative effects of social media use have been the center of studies seeking to find a set of variables that moderate their impact. Clearly, the positive effects are more evident among users who are familiar with online networks and can use them for various purposes. These individuals are aware of the differences between the different media and use them so they can facilitate the formation of new connections that transforms originally “weak” social ties into stronger social ties (Boyd, 2008; Choi, 2006; Lee & Ma, 2012) . The negative effects are more evident among individuals, often younger adults that make excessive use of these networks and get exposed to “misinformation” or “misbehaviors”. Lower resilience can be then expected steaming from lack of awareness (Woods & Scott, 2016).

4. Social Media Variations

Specific features of online platform may create variations in outcomes. Some platforms are based on written interaction (Twitter, Tumblr) are shown to affect negatively resilience whereas other platforms such as Instagram, focusing on photo-sharing, was rather positively associated with positive mental health variables (Zakour, 2019). Recent studies predict various aspects of users behavior in the context of social media use (Wixom and Todd, 2005; Wang et al., 2012; Rosenberg, 2019) and conclude that social media have become popular because it can fulfill users’ various needs related to social connections through the perspective of uses and gratification theory (Katz et al., 1973). Brailovskaia and Margraf (2016) for example comparing Facebook users and non-users show that while Facebook users had higher values of life satisfaction, happiness and social support, non-users showed higher depression symptoms. Other studies indicate how social media use can decrease real-life social interactions decreasing mental health and well-being (Berryman et al., 2018; Hall et al., 2018). evidence also indicates that social media increases adolescents’ depression symptoms (Rosen et al., 2013; Ra et al., 2018; Choate, 2017) causing high dissatisfaction and anxiety (Booker et al., 2018) and subjective well-being (Kim and Kim, 2017) to the point that for some individuals social media use appears to be meaningless (Sagioglu and Greitemeyer, 2014). This is why we need to assess how routine versus occasional use of social media use may have differential effects on resilience.

Indeed, in a national survey of U.S. young adults, Primack et al. (2017) found that compared with individuals who use 0 to 2 social media platforms, individuals who use 7 to 11 social media platforms have substantially higher odds of having increased levels of depression and anxiety symptoms. In a recent study among U.S. adolescents, Ra et al. (2018) have also found a statistically significant but modest association between higher frequency of digital media use and subsequent symptoms of attention-deficit/hyperactivity disorder. This is why Frison and Eggermont (2015) suggested a distinction between Facebook users and revealed that adolescents’ well-being depending on type of use—whether it was “active” or “passive” use. According to this study, active Facebook use were more likely to report positive outcomes, relatively to the passive users who reported they did not actively engaged in exchanges and merely viewed others’ posts.

Variations in technology use Internet access are frequently related to socioeconomic status differences. According to the Social Diversification Hypothesis socio-economic attributes, knowledge, skills, power, and agency are strong predictors of individual behaviors and attitudes especially those referring to the centrality of social networks (Mesch et al., 2012).

5. Socioeconomic Variations

Experiencing a crisis uncovers the multiple factors associated with one’s personal backgrounds and lifestyle. According to the lifestyle exposure theory, socio-demographic differences reflect variations in personal lifestyle that may determine behavior. Since space is a major element of the theory, social media are considered a new space for various lifestyle related activity (Rosenberg, 2019). Such activity is social, since individuals carry it out in a social space, where they expose themselves to similar others and perhaps to those who are not similar to them (Clemensen, Danbjørg, Syse, & Coxon, 2016: p. 2).

One critical factor is older age. Elderly people are less likely to use the Internet unless concerns such as health are considered (Bundorf et al., 2006). Education is important too because it increases the skills necessary for using the internet for information retrieval, shopping (Lu & Su, 2009), participating in social forums and more. Variations in social media use indicate that socioeconomic status and motivation differ across socio-demographic characteristics as well. Higher education has positive effects on sharing news related to entertainment and job-related content information (Mesch et al., 2012). As regards gender, men’s engagement in social media is task-and-achievement oriented, whereas women are likely to spend more time on Facebook (Smock et al., 2011), mainly to maintain interpersonal relationships (Guadagno et al., 2011) and avoid loneliness (Stepanikova et al., 2010). First, in accordance with the gender socialization process, women tend to be more socially oriented (Merchant, 2012) than men. Second, female users are more likely to disclose personal information online than male users, due to their tendency toward an expressive and open style of communication. Third, women value cooperation form relationships that are more intimate and are more motivated to maintain existing relationships than men (Merchant, 2012).

6. Conclusion

The global crisis caused by COVID has placed individuals into a new reality that in many ways. Individuals face now conditions of financial and social ambiguity and the need to protect and be protected from the outcomes of the new way of handling life and its adversities. Individuals experienced a substantial loss of social and economic resources, which increased affected resilience. This is where the role of technology comes into the fore because it increases opportunities for connectivity as well as accessing, producing and disseminating new information (Lee et al., 2012) and hence enables individuals to use the necessary resources and tools they need to overcome hardship in adverse situations such as those eminent in physical and personal crises.

The online networks assist us to maintain the sense of belonging and our ability to express opinions that otherwise would have been restricted by time or space limitations and in many cases, they can provide information and resources that we need to in order to cope with the perceived threat. However, to some extent or the other we have not considered the importance of the context of online connectivity deriving from the variations of social media use and socioeconomic variations.

Users may have different motivations and views regarding the best way to satisfy their online needs. While they remain aware that the possibility of being engaged in social media raises their potential to increase their social connections and resilience they may still prefer not to do so. We therefore need more in depth analysis of the profiles of users and their needs to assess the extent to which the virtual space is the best way to pursue a sense of stability and empowerment that will help us cope with the adversities of the COVID-19 crisis and increase our resilience. We can postulate therefore that the use of social media can have no effect, and either positive or negative effects or even a mix of both depending on the context of use.

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.

References

[1]	Antoci, A., Sabatini, F., & Sodini, M. (2015). Online and Offline Social Participation and Social Poverty Traps: Can Social Networks Save Human Relations? Journal of Mathematical Sociology, 39, 229-256. https://doi.org/10.1080/0022250X.2015.1022278
[2]	Barasa, E., Mbau, R., & Gilson, L. (2018). What Is Resilience and How Can It Be Nurtured? A Systematic Review of Empirical Literature on Organizational Resilience. International Journal of Health Policy and Management, 7, 491. https://doi.org/10.15171/ijhpm.2018.06
[3]	Barry, C. T., Sidoti, C. L., Briggs, S. M., Reiter, S. R., & Lindsey, R. A. (2017). Adolescent Social Media Use and Mental Health from Adolescent and Parent Perspectives. Journal of Adolescence, 61, 1-11. https://doi.org/10.1016/j.adolescence.2017.08.005
[4]	Berryman, C., Ferguson, C. J., & Negy, C. (2018). Social Media Use and Mental Health among Young Adults. Psychiatric Quarterly, 89, 307-314. https://doi.org/10.1007/s11126-017-9535-6
[5]	Booker, C. L., Kelly, Y. J., & Sacker, A. (2018). Gender Differences in the Associations between Age Trends of Social Media Interaction and Well-Being among 10-15 Year Olds in the UK. BMC Public Health, 18, 321. https://doi.org/10.1186/s12889-018-5220-4
[6]	Boyd, D. M. (2008). Taken Out of Context: American Teen’s Sociality in Networked Publics. Berkeley, CA: ProQuest.
[7]	Brailovskaia, J., & Margraf, J. (2016). Comparing Facebook Users and Facebook Non-Users: Relationship between Personality Traits and Mental Health Variables—An Exploratory Study. PLoS ONE, 11, e0166999. https://doi.org/10.1371/journal.pone.0166999
[8]	Bundorf, M. K., Wagner, T. H., Singer, S. J., & Baker, L. C. (2006). Who Searches the Internet for Health Information? Health Services Research, 41, 819-836. https://doi.org/10.1111/j.1475-6773.2006.00510.x
[9]	Burke, M., Marlow, C., & Lento, T. (2010). Social Network Activity and Social Well-Being. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1909-1912). New York: ACM. https://doi.org/10.1145/1753326.1753613
[10]	Chan, J. C. (2013). The Role of Social Media in Crisis Preparedness, Response and Recovery. http://www.oecd.org.ezproxy.haifa.ac.il/governance/risk/The%20role%20of%20S ocial%20media%20in%20crisis%20preparedness,%20response%20and%20recov ery.pdf
[11]	Choate, L. H. (2017). “Never Enough”: Bridging the Chasm Between College Women’s Achievements and Their Anguish. About Campus, 22, 21-27. https://doi.org/10.1002/abc.21284
[12]	Choi, J. H. J. (2006). Living in Cyworld: Contextualising Cities in South Korea. In A. Bruns, & J. Jacobs (Eds.), Uses of Blogs (pp. 173-186). Bern: Peter Lang.
[13]	Christakis, N. A., & Fowler, J. H. (2013). Social Contagion Theory: Examining Dynamic Social Networks and Human Behavior. Statistics in Medicine, 32, 556-577. https://doi.org/10.1002/sim.5408
[14]	Clemensen, J., Danbjørg, D. B., Syse, M. D., & Coxon, I. R. (2016). The Rise of Patient 3.0: The Impact of Social Media. Proceedings of the 8th International Conference on E-Health.
[15]	Davis, K. (2012). Friendship 2.0: Adolescents’ Experiences of Belonging and Self-Disclosure Online. Journal of Adolescence, 35, 1527-1536. https://doi.org/10.1016/j.adolescence.2012.02.013
[16]	Diener, E. (2009). Assessing Well-Being: The Collected Works of Ed Diener. Social Indicators Research Series, 39. https://doi.org/10.1007/978-90-481-2354-4_1
[17]	Dolev-Cohen, M., & Barak, A. (2013). Adolescents’ Use of Instant Messaging as a Means of Emotional Relief. Computers in Human Behavior, 29, 58-63. https://doi.org/10.1016/j.chb.2012.07.016
[18]	Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The Benefits of Facebook “Friends:” Social Capital and College Students’ Use of Online Social Network Sites. Journal of Computer-Mediated Communication, 12, 1143-1168. https://doi.org/10.1111/j.1083-6101.2007.00367.x
[19]	Frison, E., & Eggermont, S. (2015). Toward an Integrated and Differential Approach to the Relationships between Loneliness, Different Types of Facebook Use, and Adolescents’ Depressed Mood. Communication Research, 47, 701-728. https://doi.org/10.1177/0093650215617506
[20]	Hall, J. A., Kearney, M. W., & Xing, C. (2018). Two Tests of Social Displacement through Social Media Use. Information Communication and Society, 22, 1-18. https://doi.org/10.1080/1369118X.2018.1430162
[21]	Heath, M., & Porter, T. H. (2017). Patient Health Records: An Exploratory Study of Patient Satisfaction. Health Policy and Technology, 6, 401-409. https://doi.org/10.1016/j.hlpt.2017.10.002
[22]	Ifinedo, P. (2016). Applying Uses and Gratifications Theory and Social Influence Processes to Understand Students’ Pervasive Adoption of Social Networking Sites: Perspectives from the Americas. International Journal of Information Management, 36, 192-206. https://doi.org/10.1016/j.ijinfomgt.2015.11.007
[23]	Jung, J. Y., & Moro, M. (2014). Multi-Level Functionality of Social Media in the Aftermath of the Great East Japan Earthquake. Disasters, 38, s123-s143. https://doi.org/10.1111/disa.12071
[24]	Jurgens, M., & Helsloot, I. (2018). The Effect of Social Media on the Dynamics of (Self) Resilience during Disasters: A Literature Review. Journal of Contingencies and Crisis Management, 26, 79-88. https://doi.org/10.1111/1468-5973.12212
[25]	Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and Gratifications Research. The Public Opinion Quarterly, 37, 509-523. https://doi.org/10.1086/268109
[26]	Kim, B., & Kim, Y. (2017). College Students’ Social Media Use and Communication Network Heterogeneity: Implications for Social Capital and Subjective Well-Being. Computers in Human Behavior, 73, 620-628. https://doi.org/10.1016/j.chb.2017.03.033
[27]	Kreijns, K., Kirschner, P. A., Jochems, W., & Van Buuren, H. (2004). Determining Sociability, Social Space, and Social Presence in a Synchronous Collaborative Groups. CyberPsychology& Behavior, 7, 155-172. https://doi.org/10.1089/109493104323024429
[28]	Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N. et al. (2013). Facebook Use Predicts Declines in Subjective Well-Being in Young Adults. PLoS ONE, 8, e69841. https://doi.org/10.1371/journal.pone.0069841
[29]	Leavitt, A., Burchard, E., Fisher, D., & Gilbert, S. (2009). The Influentials: New Approaches for Analyzing Influence on Twitter. Web Ecology Project. http://tinyurl.com/lzjlzq
[30]	Lee, C. S., & Ma, L. (2012). News Sharing in Social Media: The Effect of Gratifications and Prior Experience. Computers in Human Behavior, 28, 331-339. https://doi.org/10.1016/j.chb.2011.10.002
[31]	Lee, K. M., Kim, J. Y., Cho, W. K., Goh, K. I., & Kim, I. M. (2012). Correlated Multiplexity and Connectivity of Multiplex Random Networks. New Journal of Physics, 14, Article ID: 033027. https://doi.org/10.1088/1367-2630/14/3/033027
[32]	Lenhart, A., Smith, A., Anderson, M., Duggan, M., & Perrin, A. (2015). Teens, Technology & Friendship (Vol. 10). Washington DC: Pew Research Center.
[33]	Lu, H. P., & Su, P. Y. J. (2009). Factors Affecting Purchase Intention on Mobile Shopping Web Sites. Internet Research, 19, 442-458. https://doi.org/10.1108/10662240910981399
[34]	Mano, R. M., Kirshcenbaum, A., & Rapaport, C. (2019). Earthquake Preparedness: A Social Media Fit Perspective to Accessing and Disseminating Earthquake Information. International Journal of Disaster Risk Management, 1, 19-31. https://doi.org/10.18485/ijdrm.2019.1.2.2
[35]	Masten, A. S. (2018). Resilience Theory and Research on Children and Families: Past, Present, and Promise. Journal of Family Theory & Review, 10, 12-31. https://doi.org/10.1111/jftr.12255
[36]	Merchant, K. (2012). How Men and Women Differ: Gender Differences in Communication Styles, Influence Tactics, and Leadership Styles.
[37]	Mesch, G., Mano, R., & Tsamir, J. (2012). Minority Status and Health Information Search: A Test of the Social Diversification Hypothesis. Social Science & Medicine, 75, 854-858. https://doi.org/10.1016/j.socscimed.2012.03.024
[38]	Norris, S. L., High, K., Gill, T. M., Hennessy, S., Kutner, J. S., Reuben, D. B., Landefeld, C. S. et al. (2008). Health Care for Older Americans with Multiple Chronic Conditions: A Research Agenda. Journal of the American Geriatrics Society, 56, 149-159. https://doi.org/10.1111/j.1532-5415.2007.01530.x
[39]	Pawar, A. A., & Rathod, J. (2007). Occupational Stress in Naval Personnel. Medical Journal Armed Forces India, 63, 154-156. https://doi.org/10.1016/S0377-1237(07)80062-1
[40]	Pawar, A. A., Chikkanna, C. B., Rote, M. S. et al. (2012). Occupational Stress and Social Support in Naval Personnel. Medical Journal Armed Forces India, 68, 360-365. https://doi.org/10.1016/j.mjafi.2012.04.026
[41]	Pew Research Center (2018). Social Media Fact Sheet. https://www.pewresearch.org/internet/fact-sheet/social-media/
[42]	Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of Multiple Social Media Platforms and Symptoms of Depression and Anxiety: A Nationally-Representative Study among U.S. Young Adults. Computers in Human Behavior, 69, 1-9. https://doi.org/10.1016/j.chb.2016.11.013
[43]	Ra, C. K., Cho, J., Stone, M. D., De La Cerda, J., Goldenson, N. I., Moroney, E., Leventhal, A. M. et al. (2018). Association of Digital Media Use with Subsequent Symptoms of Attention-Deficit/Hyperactivity Disorder among Adolescents. JAMA Journal of the American Medical Association, 320, 255-263. https://doi.org/10.1001/jama.2018.8931
[44]	Reghezza-Zitt, M., & Rufat, S. (2019). Disentangling the Range of Responses to Threats, Hazards and Disasters. Vulnerability, Resilience and Adaptation in Question. Cybergeo: European Journal of Geography. https://doi.org/10.4000/cybergeo.32917
[45]	Rosen, L. D., Whaling, K., Rab, S., Carrier, L. M., & Cheever, N. A. (2013). Is Facebook Creating “iDisorders”? The Link between Clinical Symptoms of Psychiatric Disorders and Technology Use, Attitudes, and Anxiety. Computers in Human Behavior, 29, 1243-1254. https://doi.org/10.1016/j.chb.2012.11.012
[46]	Rosenberg, D. (2019). Use of e-Government Services in a Deeply Divided Society: A Test and an Extension of the Social Inequality Hypotheses. New Media & Society, 21, 464-482. https://doi.org/10.1177/1461444818799632
[47]	Sagioglu, C., & Greitemeyer, T. (2014). Facebook’s Emotional Consequences: Why Facebook Causes a Decrease in Mood and Why People Still Use It. Computers in Human Behavior, 35, 359-363. https://doi.org/10.1016/j.chb.2014.03.003
[48]	Shakya, H. B., & Christakis, N. A. (2017). Association of Facebook Use with Compromised Well-Being: A Longitudinal Study. American Journal of Epidemiology, 185, 203-211. https://doi.org/10.1093/aje/kww189
[49]	Sippel, L. M., Pietrzak, R. H., Charney, D. S., Mayes, L. C., & Southwick, S. M. (2015). How Does Social Support Enhance Resilience in the Trauma-Exposed Individual? Ecology and Society, 20, 10-20. https://doi.org/10.5751/ES-07832-200410
[50]	Smith, A., & Anderson, M. (2018). Social Media Use 2018: Demographics and Statistics. Washington DC: Pew Research Center. https://www.pewresearch.org/internet/2018/03/01/social-media-use-in-2018/
[51]	Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011). Facebook as a Toolkit: A Uses and Gratification Approach to Unbundling Feature Use. Computers in Human Behavior, 27, 2322-2329. https://doi.org/10.1016/j.chb.2011.07.011
[52]	Southwick, S. M., Sippel, L., Krystal, J., Charney, D., Mayes, L., & Pietrzak, R. (2016). Why Are Some Individuals More Resilient than Others: The Role of Social Support. World Psychiatry, 15, 77-79. https://doi.org/10.1002/wps.20282
[53]	Stepanikova, I., Nie, N. H., & He, X. (2010). Time on the Internet at Home, Loneliness and Life Satisfaction: Evidence from Panel Time-Diary Data. Computers in Human Behavior, 26, 329-338. https://doi.org/10.1016/j.chb.2009.11.002
[54]	Subrahmanyam, K., Reich, S. M., Waechter, N., & Espinoza, G. (2008). Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults. Journal of Applied Developmental Psychology, 29, 420-433. https://doi.org/10.1016/j.appdev.2008.07.003
[55]	Vindevogel, S. (2017). Resilience in the Context of War: A Critical Analysis of Contemporary Conceptions and Interventions to Promote Resilience among War-Affected Children and Their Surroundings. Peace & Conflict: Journal of Peace Psychology, 23, 76-84. https://doi.org/10.1037/pac0000214
[56]	Wang, Z., Tchernev, J. M., & Solloway, T. (2012). A Dynamic Longitudinal Examination of Social Media Use, Needs, and Gratifications among College Students. Computers in Human Behavior, 28, 1829-1839. https://doi.org/10.1016/j.chb.2012.05.001
[57]	Whittaker, J., McLennan, B., & Handmer, J. (2015). A Review of Informal Volunteerism in Emergencies and Disasters: Definition, Opportunities and Challenges. International Journal of Disaster Risk Reduction, 13, 358-368. https://doi.org/10.1016/j.ijdrr.2015.07.010
[58]	Wixom, B. H., & Todd, P. A. (2005). A Theoretical Integration of User Satisfaction and Technology Acceptance. Information Systems Research, 16, 85-102. https://doi.org/10.1287/isre.1050.0042
[59]	Woods, H. C., & Scott, H. (2016). #Sleepyteens: Social Media Use in Adolescence Is Associated with Poor Sleep Quality, Anxiety, Depression and Low Self-Esteem. Journal of Adolescence, 51, 41-49. https://doi.org/10.1016/j.adolescence.2016.05.008
[60]	Zakour, M. J. (2019). Macro-Level Interventions in Disasters: Theoretical Foundations for Improving Mental Health Outcomes. Best Practice in Mental Health, 15, 16-28.
[61]	Zautra, A. J., Hall, J. S., & Murray, K. E. (2010). Resilience: A New Definition of Health for People and Communities.
[62]	Guadagno, R. E., Muscanell, N. L., Okdie, B. M., Burk, N. M., & Ward, T. B. (2011). Even in Virtual Environments Women Shop and Men Build: A Social Role Perspective on Second Life. Computers in Human Behavior, 27, 304-308. https://doi.org/10.1016/j.chb.2010.08.008