Social media addiction in romantic relationships: Does user's age influence vulnerability to social media infidelity?

Running head: SOCIAL MEDIA ADDICTION IN ROMANTIC RELATIONSHIPS Social Media Addiction in Romantic Relationships: Does User’s Age Influence Vulnerability to Social Media Infidelity? Irum Saeed Abbasi San Jose State University For inquiries regarding this research, please email at Irum.abbasi@gmail.com Abstract Compulsive social media use has repercussions on the users' social, psychological, professional, and personal lives. The availability of online romantic alternatives disguised as ‘friends’ provide a ripe environment that can facilitate an emotional and/or sexual affair. Online interactions with virtual friends consume users' attention and distract them from spending time with their significant other, which leads to adverse relationship outcomes. In this study, we examined the relationship between social media addiction and infidelity related behaviors in a sample of 365 partners (242 females, 123 males). We also explored if age influences this connection. The findings suggest that SNSs addiction predicts SNSs infidelity related behaviors and age moderates this relationship. The study also finds that a age is negatively related with SNSs addiction and SNSs related infidelity. Implications and limitations of the study are discussed. Keywords: social media addiction, infidelity, Facebook, emotional affair, Internet communication Social Media Addiction in Romantic Relationships: Does User’s Age Influence Vulnerability to Social Media Infidelity? Internet provides many platforms that connect users with known and unknown virtual connections in the cyberspace. Currently, one of the most ubiquitous platforms used for online interactions is social media. It offers a popular way of initiating, developing, and maintaining existing as well as new relationships including illicit relation- ships. Many social networking sites (SNSs) have spawned due to users' demands such as Facebook, Snapchat, Tumblr, and Instagram. The popularity of SNSs is rooted in the online features that allow users to share photos, interests, opinions, and even intimate thoughts and expressions. Interactions on SNSs can be beneficial (Shaw & Gant, 2002). However, these interactions can potentially turn into a habitual compulsion (behavioral addiction), which is referred to as “Facebook intrusion” (Elphinston & Noller, 2011) or “SNSs addiction” (Andreassen, Torsheim, Brunborg, & Pallesen, 2012; Ryan, Chester, Reece, & Xenos, 2014). SNSs addiction can cause social overload (Maier, Laumer, Eckhardt, & Weitzel, 2012), envy (Mukesh, Mayo, & Goncalves, 2016; Tandoc, Ferrucci, & Du y, 2014), and anxiety (Labrague, 2014). Moreover, SNSs addiction can exhibit symptoms of substance abuse including deficient self-regulation, neglect of personal life, cognitive preoccupation, mood modifying experiences, tolerance, concealment of addictive behaviors, and escapism (Kuss & Grifiths, 2011; Kuss & Grifiths, 2017). SNSs addiction manifests itself as a functional impairment and shares some characteristic features of substance abuse addictions such as euphoria, withdrawal, relapse, and reinstatement (Elphinston & Noller, 2011; Karaiskos, Tzavellas, Balta, & Paparrigopoulos, 2010). Relationships formed on SNSs are also addictive and can negatively influence the primary romantic relationship (Marshall, 2012). Re- searchers have coined a term ‘Technoference’ for the everyday technological intrusions in couple interactions or time spent together (McDaniel & Coyne, 2016). Research on partner phubbing (snubbing the partner when one is using phone) also points to the deleterious effect of using cell phone when in the company of the significant other (Chotpitayasunondh & Douglas, 2016). SNSs addiction is also linked with a decreased in the quality of the primary romantic relationship, physical and emotional infidelity, relationship dissatisfaction, romantic disengagement, and a higher risk of divorce (Abbasi & Alghamdi, 2017a, b; Abbasi, 2018a; Kerkhof, Finkenauer, & Muusses, 2011; Utz & Beukeboom, 2011; Valenzuela, Halpern, & Katz, 2014). Social media offers features that enable users to publicly or privately flirt with other users (Clayton, Nagurney, & Smith, 2013). Flirting in the virtual world elicits stronger physical and sexual reactions than experienced in a face-to-face interaction (Alapack, Blichfeldt, & Elden, 2005). The lack of physical presence makes cyberspace interactions uninhibited and users aggressively share their most intimate thoughts and desires (Abbasi & AlGhamdi, 2017b; Carter, 2015; Cravens & Whiting, 2014; Helsper & Whitty, 2010). This lack of self-inhibition online can lead to an emotional affair, which is the hallmark of Internet infidelity (Hertlein & Piercy, 2006). Infidelity is constituted of “inter- actions in a relationship in which at least one of the people engaging in it understands there to be a violation of agreed or implicit sexual and/or emotional boundaries within their couple relationship” (Daines, 2006, p. 48). When such interactions occur on the internet, they constitute Internet infidelity, which can be both, sexual and emotional (Henline, Lamke, & Howard, 2007). Researchers have found that maladaptive Facebook use is linked with feelings of jealousy, suspicion, and loss of trust (Muise, Christofides, & Desmarais, 2009). Suspecting partners engage in partner's surveillance and retaliatory behaviors that leads to conflict, loss of trust, and breakup (Cravens & Whiting, 2014; Muise et al., 2009). The problematic SNSs behaviors include viewing pornography, emotional disclosure, cybersex, emotional involvement, hot chatting, and online dating (Dijkstra, Barelds, & Groothof, 2013; Henline et al., 2007). The prevalence of addictive Facebook use is higher in the young population (Abbasi, 2018b; Kuss & Griffiths, 2011). The peer pressure to engage in popular technologies may be at the root of this addiction (Orchard & Fullwood, 2010). Among millennials (18 to 34-year-olds), Facebook, Instagram and Snapchat are the three most commonly used SNSs (Perez, 2014). Even otherwise, young people are generally prone to developing an Internet addiction (Kuss, Griffiths, & Binder, 2013). Furthermore, previous research has found an inverse relationship be- tween age and Facebook activity intensity, which was seen across an age range of 16 to 56 years (Ozimek & Bierhoff, 2016). This relationship was mediated by social comparison (McAndrew & Jeong, 2012; Ozimek & Bierhoff, 2016). Researchers argue that as people grow older, they tend to use Facebook less often because the need for comparison with significant others declines with age (McAndrew & Jeong, 2012). This is probably because the personal and professional goals (partnership, work, family) are more likely to have been met at an older age than at a younger age. Hypotheses As previously mentioned, SNSs interactions can be addictive and could potentially lead to specific behaviors (flirting, infidelity) that have been shown to adversely impact romantic relationships. Younger population may be prone to developing infidelity because they tend to take risk and disclose freely in an online versus face-to-face environment (Gray, 2016). Building on this, the author hypothesized that there is a positive relationship between SNSs addiction and SNSs infidelity behaviors (H1) and age will moderate this relationship (H2). Ad- ditionally, age is positively related to SNSs addiction and SNSs infidelity (H3). Methods Participants The sample included 365 participants (242 females, 123 males) between the ages of 18–73 years (M = 27.94, SD = 11.67). 35.1% of the participants reported to be married, 14.2% reported to be in a committed relationship, and 50.7% reported to be casually dating. Our sample was from diverse ethnic backgrounds and included Whites (47.4%), Asian (20.8%), Hispanic (24.4%), African American (6.3%), Native American (0.8%), and miscellaneous others (0.3%). The participants spanned a spectrum of occupations, and all participants resided in the US and more than half resided in California (52.2%). Procedure An institutional review board (IRB) at a public university in the United States approved the present study. Snowball sampling was used to recruit participants in the study. A survey link was shared on the approving university's research website, Facebook, Linkedin, Amazon Turk, Whatsapp, etc. The inclusionary criteria included being at least 18 years of age, having a heterosexual romantic relationship, and re- siding in the USA. We excluded cases where participants self-reported to have been diagnosed with a mental illness or failed the attention check questions. The participants who agreed to the terms of the research were directed to the main survey, which included a battery of questionnaires described below. Measures Demographic questionnaire. The demographic questionnaire included self-report items that assessed age, gender, ethnicity, diagnosis of mental illness, sexual orientation, country and state of residence, etc. Social Media Infidelity-Related Behaviors scale (SMIRB). To measure infidelity-related behaviors on social media, we used SMIRB, which is a 7-items scale developed by McDaniel, Drouin, and Cravens (2017). An example item is ‘I sometimes like to chat or message old romantic partners online or on social networking sites’. Participants rated their agreement on a 6-point response scale (1 = strongly disagree, 6 = strongly agree). Items were averaged for analyses where high scores represented greater tendency to engage in infidelity related behaviors. Reliability of the SMIRB-7 for this study was 0.85. Modified Facebook intrusion questionnaire. An eight-item scale developed by Elphinston and Noller (2011) was used to assess the behavioral addiction component among SNSs users. We modified the Facebook intrusion scale to cover all social media (rather than just Facebook) by replacing Facebook in each item with social media. The eight items measured the link between the tendency towards SNSs involvement and eight aspects of behavioral addiction. Responses were rated on a seven-point Likert scale (1 = strongly disagree and 7 = strongly agree). An example item is ‘I feel connected to others when I use social media’. Reliability of this modified scale for the present study was 0.81. Results To test the hypotheses, SPSS PROCESS Macro (Model 1) developed by Hayes (2013) was used with 5000 bootstrap resamples (p < .05). For analyses, SNSs addiction was added as the predictor variable (X), SNSs infidelity was added as the outcome variable (Y), and age was added as the moderator (M). Gender and romantic relationship status were added as control variables. The overall model was significant [F (5, 359) = 21.69, p < .001, R = 0.48]. In line with H1, we found that SNSs addiction is a significant predictor of SNSs infidelity (b = 0.04, t(359) = 8.21 p < .001). Essentially, individuals who reported higher SNSs addiction also reported greater SNSs related infidelity behaviors. We also found support for H2; the relationship between SNSs addiction and SNSs infidelity related behaviors was moderated by age (b = 0.00, t(359)= 2.15, p < .05). In younger people, the relationship between SNSs addiction and SNSs infidelity is strong and as the age increases, this relationship becomes weak. Additionally, we found that age is negatively related to both, SNSs addiction and SNSs infidelity. Table 1 shows the Pearson's bivariate correlation between the variables and controls along with their means and standard deviations. The table also shows mean differences between males and females on the variables and controls. There was no significant gender difference in the variables except SNSs infidelity. Men had significantly higher scores on SNSs infidelity than women. Table 1 shows the Pearson’s bivariate correlations and descriptives of variables and controls. 1 2 3 4 5 1. SNSs Addiction -- .39** -.29** .27** .06 2. SNSs Infidelity -.13* .21** -.20** 3. Age -.76** .06 4. Relationship Status -.05 5. Gender Mean (SD) 27.27 (8.70) 2.09 (.88) 27.94 (11.67) 2.82 (1.36) Women Mean 27.67 1.96 28.48 2.77 SD 8.25 .85 12.43 1.38 Men Mean 26.49 2.34*** 26.89 2.91 SD 9.52 .87 9.97 1.31 Note. N=365. Correlation is significant at the ***p < .001, **p<.01, *p<.05. Correlations for females are presented above the diagonal, whereas those for males are below the diagonal. ***p < .001, **p < .01, *p < .05. Discussion SNSs addiction can lead to a variety of psychological, social (Amichai-Hamburger & Vinitzky, 2010; Wilson, Fornasier, & White, 2010), and interpersonal problems including reduced relationship commitment (Abbasi, 2018c; Clayton et al., 2013; Cravens, Leckie, & Whiting, 2013; Kerkhof et al., 2011). Investment model (Rusbult, 1980) holds that, in addition to relationship satisfaction and absence of alternatives, steady investments (e.g., time, emotional, financial) ad-vanced in the primary relationship are essential for strengthening commitment. Time spent with online friends is traded off with the time that could have been spent with the significant other. It is noteworthy that a crucial underlying factor linked with infidelity is the shared time spent with an extra-dyadic partner (Hertlein & Piercy, 2006). Moreover, research supports that individuals committed to their partners derogate alternatives (Rusbult, Agnew, & Ximena, 2011), while those who ex-perience low commitment are prone to developing interest in alter-natives (Drouin, Miller, & Dibble, 2014). In this study, we found that SNSs addiction is positively linked with SNSs infidelity and this relationship is moderated by age. In other words, the relationship between SNSs addiction and SNSs infidelity changes in strength with age and becomes weak as age progresses. We also found that age is negatively linked with SNSs addiction and SNSs infidelity. Younger individuals reported significantly higher SNSs ad-diction and SNSs infidelity scores as compared to older individuals. This is consistent with previous research that indicated that age is a significant predictor of social media addiction (Abbasi, 2018b; Błachnio, Przepiórka, & Pantic, 2015) and that young people are prone to taking more risks online and/or tend to engage in behaviors that they would not engage in when in an offline environment (Gray, 2016). 5. Limitations and future directions The results from the present study are limited in scope and inter-pretation should be done considering the limitations of the study. We employed a single method (cross-sectional) design; therefore, causality cannot be inferred from these findings. Moreover, the direction of the relationship between the two variables (SNSs addiction and SNSs in-fidelity related behaviors) is not clear. It is plausible that those who are prone to infidelity engage in excessive SNSs use or vice versa. This study also employed self-report scales, which are more subjective than objective. Furthermore, we did not match our participants with their partners. Therefore, the results reported in this study are based on the actor effect (the effect of self on relationship) and not the partner effect. We call for future research including mixed method design studies to address the limitations of the present study. Qualitative design study inclusive of both partners can take into account, both, the actor and partner effect and can also shed light on how certain behaviors ex-acerbate SNSs addiction and SNSs infidelity. Albeit the limitations mentioned above, this study has implications for researchers, SNSs developers, therapists, school counselors, and educators. These findings are especially beneficial to the relationship therapists who could customize their interventions based on the client's age and focus on curbing the risky SNSs behaviors that are detrimental to the SNSs users' social, professional, psychological and interpersonal lives. References Abbasi, I. S. (2018a). The link between romantic disengagement and Facebook addiction: Where does relationship commitment fit in? American Journal of Family Therapy (online first). Abbasi, I. S. (2018b). Social media and committed relationships: What factors make our romantic relationship vulnerable? Social Science Computer Review, 1–10. https://doi. org/10.1177/0894439318770609. Abbasi, I. S. (2018c). Falling prey to online romantic alternatives: Evaluating social media alternative partners in committed versus dating relationships. Social Science Computer Review, 1–11. https://doi.org/10.1177/0894439318793947. Abbasi, I. S., & Alghamdi, N. G. (2017a). The pursuit of romantic alternatives online: Social media friends as potential alternatives. Journal of Sex & Marital Therapy. https://doi.org/10.1080/0092623X.2017.1308450. Abbasi, I. S., & AlGhamdi, N. (2017b). When flirting turns into infidelity: The Facebook dilemma. The American Journal of Family Therapy. https://doi.org/10.1080/ 01926187.2016.1277804. Alapack, R., Blichfeldt, M. F., & Elden, A. (2005). Flirting on the internet and the hickey: A hermeneutic. Cyberpsychology & Behavior, 8, 52–61. Amichai-Hamburger, Y., & Vinitzky, G. (2010). Social network use and personality. Computers in Human Behavior, 26, 1289–1295. Andreassen, C. S., Torsheim, T., Brunborg, G. S., & Pallesen, S. (2012). Development of a Facebook addiction scale. Psychological Reports, 110(2), 501–517. https://doi.org/10. 2466/02.09.18. PR0.110.2.501-517. Błachnio, A., Przepiórka, A., & Pantic, I. (2015). Internet use, Facebook intrusion, and depression: Results of a cross-sectional study. European Psychiatry, 30(6), 681–684. https://doi.org/10.1016/j.eurpsy.2015.04.002. Carter, Z. A. (2015). Married and previously married men and women perceptions of com-munication on Facebook with the opposite sex: How communicating through facebook can be damaging to marriages (Doctoral dissertation) Retrieved from http://gradworks. umi.com/37/00/3700817.html. (3700817). Chotpitayasunondh, V., & Douglas, K. M. (2016). How “phubbing” becomes the norm: The antecedents and consequences of snubbing via smartphone. Computers in Human Behavior, 63, 9–18. https://doi.org/10.1016/j.chb.2016.05.018. Clayton, R. B., Nagurney, A., & Smith, J. R. (2013). Cheating, breakup, and divorce: Is Facebook use to blame? Cyberpsychology, Behavior, and Social Networking, 16, 717–720. Cravens, J. D., Leckie, K. R., & Whiting, J. B. (2013). Facebook in delity: When poking becomes problematic. Contem- porary Family Therapy, 35(1), 74–90. https://doi.org/ 10.1007/s10591-012-9231-5. Cravens, J. D., & Whiting, J. B. (2014). Clinical implications of internet infidelity: Where Facebook fits in. American Journal of Family Therapy, 42(4), 325–339. https://doi. org/10.1080/01926187.2013.874211. Daines, B. (2006). Violations of agreed and implicit sexual and emotional boundaries in couple relationships - Some thoughts arising from Levine's “A clinical perspective on couple infidelity”. Sexual and Relationship Therapy, 21, 45–53. https://doi.org/10. 1080/14681990500430011. Dijkstra, P., Barelds, D. P. H., & Groothof, H. A. K. (2013). Jealousy in response to online and offline in- fidelity: The role of sex and sexual orientation. Scandinavian Journal of Psychology, 54, 328–336. https://doi.org/10.1111/sjop.12055. Drouin, M., Miller, D. A., & Dibble, J. L. (2014). Ignore your partners' current Facebook friends; beware the ones they add!. Computers in Human Behavior, 35, 483–488. https://doi.org/10.1016/j.chb.2014.02.032. Elphinston, R. A., & Noller, P. (2011). Time to Face It! Facebook intrusion and theim-plications for romantic jealousy and relationship satisfaction. Cyber Psychology, Behavior, & Social Networking, 14(11), 631–635. https://doi.org/10.1089/cyber. 2010.0318. Gray, L. (2016). Exploring how and why young people use social networking sites. Doctorate in Applied Educational Psychology. Newcastle University (Newcastle University e-theses). Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press. Helsper, E. J., & Whitty, M. T. (2010). Netiquette within married couples: Agreement about acceptable online behavior and surveillance between partners. Computers in Human Behavior, 26, 916–926. https://doi.org/10.1016/j.chb.2010.02.006. Henline, B. H., Lamke, L. K., & Howard, M. D. (2007). Exploring perceptions of online infidelity. Personal Relationships, 14, 113–128. https://doi.org/10.1111/j.1475-6811. 2006.00144.x. Hertlein, K. M., & Piercy, F. P. (2006). Internet infidelity: A critical review of the lit-erature. The Family Journal, 14(4), 366–371. https://doi.org/10.1177/ 1066480706290508. Karaiskos, D., Tzavellas, E., Balta, G., & Paparrigopoulos, T. (2010). Social network ad-diction: A new clinical disorder? European Psychiatry, 25, 855. Kerkhof, P., Finkenauer, C., & Muusses, L. D. (2011). Relational consequences of com-pulsive Internet use: A longitudinal study among newlyweds. Human Communication Research, 37(2), 147–173. https://doi.org/10.1111/j.1468-2958.2010.01397.x. Kuss, D. J., & Griffiths, M. D. (2011). Excessive online social networking: Can adolescents become addicted to Facebook. Education and Health, 29(4), 68–71. Kuss, D. J., & Griffiths, M. D. (2017). Social networking sites and addiction: Ten lessons learned. International Journal of Environmental Research Public Health, 14, 311. https://doi.org/10.3390/ijerph14030311. Kuss, D. J., Griffiths, M. D., & Binder, J. F. (2013). Internet addiction in students: Prevalence and risk factors. Computers in Human Behavior, 29(3), https://doi.org/10. 1016/j.chb.2012.12.024 959e966.
 Labrague, L. J. (2014). Facebook use and adolescents’ emotional states of depression, anxiety, and stress. Health Science Journal, 8(1), 80–89. Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2012). When social networking turns to social overload: Explaining the stress, emotional exhaustion, and quitting behavior from social network sites' users (2012) (Paper 71). ECIS 2012 Proceedings. Retrieved from https://pdfs.semanticscholar.org/6615/ b961b4f2ff0e114bb9232b0e3db4f9817b69.pdf. Marshall, T. (2012). Facebook surveillance of former romantic partners: Associations with post breakup recovery and personal growth. Cyberpsychology, Behavior, and Social Networking, 15, 521–526. https://doi.org/10.1089/cyber.2012.0125. McAndrew, F. T., & Jeong, H. S. (2012). Who does what on Facebook. Age, sex, and relationship status as predictors of Facebook use. Computers in Human Behavior, 28, 2359–2365. McDaniel, B. T., & Coyne, S. M. (2016). “Technoference”: The interference of technology in couple relationships and implications for women's personal and relational well-being. Psychology of Popular Media Culture, 5, 85–98. https://doi.org/10.1037/ ppm0000065. McDaniel, B. T., Drouin, M., & Cravens, J. (2017). Do you have anything to hide? Infidelity-related behaviors on social media sites and marital satisfaction. Computers in Human Behavior, 66, 88–95. https://doi.org/10.1016/j.chb. 2016.09.031. Muise, A., Christofides, E., & Desmarais, S. (2009). More information than you ever wanted: Does Facebook bring out the green-eyed monster of jealousy? Cyberpsychology & Behavior, 12, 441–444. https://doi.org/10.1089/cpb. 2008.0263. Mukesh, M., Mayo, M., & Goncalves, D. (2016). When friends show off: Facebook and well-being. Proceedings of the Winter Marketing Academic Conference (AMA), February 26-28 Las Vegas, NV. Orchard, L. J., & Fullwood, C. (2010). Current perspectives on personality and Internet use. Social Science Computer Review, 28(2), 155–169. Ozimek, P.m., & Bierhoff, H. W. (2016). Facebook use depending on age: The influence of social comparisons. Computers in Human Behavior, 61, 271–279. Perez, S. (2014). Snapchat is now the #3 social app among millennials. Retrieved from http://techcrunch.com/2014/08/11/snapchat-is-now-the-3-social-app-among-millennials. Rusbult, C. E. (1980). Commitment and satisfaction in romantic associations: A test of the investment model. Journal of Experimental Social Psychology, 16, 172–186. https:// doi.org/10.1016/0022-1031(80)90007-4. Rusbult, C. E., Agnew, C., & Ximena, A. (2011). The investment model of commitment processes. Department of Psychological Sciences Faculty Publications. Paper 26http:// docs.lib.purdue.edu/psychpubs/26. Ryan, T., Chester, A., Reece, J., & Xenos, S. (2014). The uses and abuses of Facebook: A review of Facebook addiction. Journal of Behavior Addiction, 3, 133–148. https://doi. org/10.1556/JBA.3.2014.016. Shaw, L., & Gant, L. (2002). In defense of the Internet: The relationship between Internet communication and depression, loneliness, self-esteem, and perceived social support. Cyber Psychology & Behavior, 5, 157–171. https://doi.org/10.1089/ 109493102753770552. Tandoc, E. C., Ferrucci, P., & Duffy, M. (2014). Facebook use, envy, and depression among college students: Is Facebooking depressing? Computers in Human Behavior, 43139–43146. https://doi.org/10.1016/j.chb.2014.10.053. Utz, S., & Beukeboom, C. J. (2011). The role of social network sites in romantic re-lationships: Effects on jealousy and relationship happiness. Journal of Computer-Mediated Communication, 16(4), 511–527. https://doi.org/10.1111/j.1083-6101. 2011.01552.x. Valenzuela, S., Halpern, D., & Katz, J. E. (2014). Social network sites, marriage well-being and divorce: Survey and state-level evidence from the United States. Computers in Human Behavior, 36, 94–101. https://doi.org/10.1016/j. chb.2014.03.034. Wilson, K., Fornasier, S., & White, K. M. (2010). Psychological predictors of young adults' use of social networking sites. Cyberpsychology, Behavior, and Social Networking, 13(2), 173–177. https://doi.org/10.1089/cyber.2009.0094. SOCIAL MEDIA ADDICTION IN ROMANTIC RELATIONSHIPS