Americans are more solitary than ever before. Never has been this statement been truer than in post-pandemic 2022. Loneliness and social isolation have been rising for some time (Yanguas et al.,2018). Thirty-six percent of Americans feel lonely much of the time, with younger (aged 18-25) and older adults (aged 50 and older) appearing to be most “at risk” (Weissbourd et al., 2022). Protective measures designed to manage the COVID-19 pandemic further increased loneliness and feelings of isolation. As in-person gatherings became dangerous, those who were able, gratefully turned to technology as a way of staying connected to family and friends (Geirdal et al., 2021). Over time for some, this coping strategy became an addiction. Even before the pandemic, over 10% of young adults already fit the criteria for “problematic internet use” (Pettorruso et al., 2020). Problematic internet use is only one of many forms of technology addiction, others include gaming addiction, social media addiction, smartphone addiction, and more. Technology addiction involves obsessive technology-connected behavior and feelings of stress and anxiety when not connected. Technology addiction is on the rise, although not identified as a clinical addiction in the DSM, it is nevertheless a growing social concern related to problematic technology use or overuse. Such addiction can lead to anxiety about being connected, rumination about online relationships and activities, an over-dependence, and an over-engagement with online platforms (Marciano et al., 2022).
When technology takes the place of in-person relationships, instead of meeting a person’s social and emotional needs, it can reduce well-being. For example, Kuss and Griffiths (2011) found continuous engagement in “Social Networking Sites” to be negatively related to community participation, academic achievement, and relationship quality. Even as various technologies can help connect and sustain social interactions during challenging times like the COVID-19 epidemic (Gioia et al., 2021), addiction to them may ultimately harm users and contribute to their real-life social isolation. Emotional regulation deficits, insecure attachment styles, dissociative experiences, and depressive symptoms have been reported to be related to technology addiction. Technology addiction can also lead to “cyber dissociation,” a subclinical dissociation characterized by the transformation of absolute reality into cyber reality; (Ozturk & Erdogan, 2022), “temporal dissociation,” a part of cognitive absorption characterized by losing track of time; (Mazzoni et al., 2017), and/or “normative dissociation,” over absorption into activities or cognitive processes, (Baughan et al., 2022).
Geirdal et al. (2021) observed that high social media use is related to reduced positive mental health outcomes, especially feelings of well-being and loneliness. On the other hand, Hunt et al. (2018) found cultivating moderation by way of controlling and monitoring social media use is associated with positive mental health outcomes such as reduced anxiety and depression. Educational and intervention strategies to improve emotional regulation while self-monitoring technology consumption may be a fruitful strategy to combat loneliness and help people cope with stress and anxiety related to technology use. Unfortunately, this may be easier said than done because heavy internet users may interpret their addiction as not a critical problem (Kurniasih et al., 2017). It is interesting to note that withdrawal from technology overlaps in symptomology with loneliness, such as feelings of disconnection and isolation. However, more research is needed to understand the direct relationship between feelings of social disconnection in the real world and cyberspace.
Age and Technology Addiction
Historically, older adults have been among the lowest internet users for years. The digital divide had kept many older adults from accessing or feeling comfortable using computers and related technologies. However, in recent years, particularly during the pandemic, older adults have been making increased use of social media (Anderson & Perrin, 2019; Bell, et. al. 2013). During the pandemic, the Internet has helped this age group combat loneliness and isolation. But how much social media use is healthy (Meshi et al., 2020)? In an ongoing project of the first author, exploring the benefits of time spent in natural environments, 12 older participants of diverse backgrounds who walked 3 to 5 times a week for at least 30 minutes were asked to list the top 5 benefits of walking outside. Eleven of the 12 stated disconnecting “for a time” from their technology was one of their top benefits. Clearly, there are both positive and negative outcomes associated with technology use. Smartphone use in later life has been related to lower depression and loneliness. For those with physical challenges, staying in regular contact with family and friends through their tech devices combats loneliness and isolation. Chopik (2016) observed that moderate use of technological devices is beneficial, but its overuse can adversely affect one’s feelings of well-being.
Problematic technology use traditionally has been more of a concern among young adults (Gioia, Rega, & Boursier, 2021). This may reflect their intuitive ease of accessibility to technology and possibly their greater potential to respond to technology’s addictive properties. Studies have used the term “digital native” to describe an individual from a younger generation who grew up during the IT age. Wang et al. (2019) found a link between digital nativity and four different types of IT addiction. Even though age accounted for some of the variance, there were other characteristics of a digital native that were related to addiction, such as having grown up with technology, being comfortable multitasking, relying on graphics for communication, and thriving on instant gratifications and rewards. It is important to take a nuanced approach to understanding technological addiction for younger and older adults.
Considering the “digital divide” in the ability to access and use technologies among older adults compared to younger generations, it is vital to offer individual technology training for everyone in need (Volkom et al., 2014). The age-related cognitive and physical decline may affect access and usability of digital tools. Current software and hardware development rarely consider age-related difficulties in their designs. Additionally, internalized ageism, where older adults are perceived as less capable of understanding and dealing with emerging technologies, may result in older adults internalizing such cultural messages (McDonough, 2016, Tahmaseb McConatha, Kumar, & Magnarelli, 2022).
We live in a technology-infused world; all age groups use the internet for many activities, and most people in western societies have a “digital identity.” While technology may greatly help lonely people who seek connection with close friends, family, or colleagues, it can become a detrimental coping strategy when overused. Total absorption in technologies may help escape negative emotions, leading to further isolation. This dissociated state is rarely realized as an IT addiction, making it even more challenging to change the habit. In the future, it is crucial to understand how we can help people avoid excessive internet use such as by training people to use self-monitoring strategies. Also, addressing such issues as the digital divide and ageism is essential to help different generations benefit from social connections through the internet. Further research on developing strategies to mitigate some of the adverse effects of addictive tech use on loneliness and isolation has become a necessity that seemed to start to grow much before the COVID-19 pandemic.
Anderson, M., & Perrin, A. (2019, December 31). Tech adoption climbs among older adults. Pew Research Center: Internet, Science & Tech. Retrieved September 29, 2022, from https://www.pewresearch.org/internet/2017/05/17/technology-use-among-seniors/
Baughan, A., Zhang, M. R., Rao, R., Lukoff, K., Schaadhardt, A., Butler, L. D. & Hiniker, A. (2022). “I don’t even remember what I read”: How design influences dissociation on social media. CHI Conference on Human Factors in Computing Systems (CHI `22), 18, 1–13. https://doi.org/10.1145/3491102.3501899
Bell, C., Fausset, C.B., Farmer, S., Nguyen, J., Harley, L., & Fain, W.B. (2013, May). Examining social media use among older adults. Proceedings of the 24th ACM Conference on Hypertext and Social Media, 158–163. https://doi.org/10.1145/2481492.2481509
Chopik W. J. (2016). The benefits of social technology use among older adults are mediated by reduced loneliness. Cyberpsychology, behavior and social networking, 19(9), 551–556. https://doi.org/10.1089/cyber.2016.0151
Geirdal, A. Ø., Ruffolo, M., Leung, J., Thygesen, H., Price, D., Bonsaksen, T., & Schoultz, M. (2021). Mental health, quality of life, well-being, loneliness and use of social media in a time of social distancing during the COVID-19 outbreak. A cross-country comparative study. Journal of mental health, 30(2), 148–155. https://doi.org/10.1080/09638237.2021.1875413
Gioia, F., Rega, V., & Boursier, V. (2021). Problematic internet use and emotional dysregulation among young people: A literature review. Clinical neuropsychiatry, 18(1), 41–54. https://doi.org/10.36131/cnfioritieditore20210104
Hunt, M. G., Marx, R., Lipson, C., & Young, J. (2018). No more FOMO: Limiting social media decreases loneliness and depression. Journal of Social and Clinical Psychology, 37(10), 751–768. https://doi.org/10.1521/jscp.2018.37.10.751
Kuss, D. J., & Griffiths, M. D. (2011). Online social networking and addiction – a review of the psychological literature. International journal of environmental research and public health, 8(9), 3528–3552. https://doi.org/10.3390/ijerph8093528
Marciano, L., Ostroumova, M., Schulz, P. J., & Camerini, A. L. (2022). Digital media use and adolescents’ mental health during the Covid-19 Pandemic: A systematic review and meta-analysis. Frontiers in public health, 9, 793868. https://doi.org/10.3389/fpubh.2021.793868
Mazzoni, E., Cannata, D., & Baiocco, L. (2017). Focused, not lost: The mediating role of temporal dissociation and focused immersion on problematic internet use. Behaviour & Information Technology, 36(1), 11–20. https://doi.org/10.1080/0144929X.2016.1159249
McDonough, C. C. (2016). The effect of ageism on the digital divide among older adults. Journal of Gerontology & Geriatric Medicine, 2(008), 1–7. https://doi.org/10.24966/GGM-8662%2F100008
Meshi, D., Cotten, S. R., & Bender, A. R. (2020). Problematic social media use and perceived social isolation in older Adults: A cross-sectional study. Gerontology, 66(2), 160–168. https://doi.org/10.1159/000502577
Musetti, A., Terrone, G., & Schimmenti, A. (2018). An exploratory study on problematic Internet use predictors: Which role for attachment and dissociation? Clinical Neuropsychiatry: Journal of Treatment Evaluation, 15(1), 35–41.
Ozturk, E. & Erdogan, B. (2022). On the psychodigital components of cyber traumatization and dissociation: A psychosocial depiction of cyber societies as dissociogenic. Medicine Science, 11(1), 422–428. http://doi.org/10.5455/medscience.2021.12.411
Pettorruso, M., Valle, S., Cavic, E., Martinotti, G., di Giannantonio, M., & Grant, J. E. (2020). Problematic internet use (PIU), personality profiles and emotion dysregulation in a cohort of young adults: trajectories from risky behaviors to addiction. Psychiatry research, 289, 113036. https://doi.org/10.1016/j.psychres.2020.113036
Remondi, C., Compare, A., Tasca, G. A., Greco, A., Pievani, L., Poletti, B., & Brugnera, A. (2020). Insecure attachment and technology addiction among young adults: The mediating role of impulsivity, alexithymia, and general psychological distress. Cyberpsychology, Behavior, and Social Networking, 23(11), 761–767. https://doi.org/10.1089/cyber.2019.0747
Tahmaseb McConatha, J.; Kumar, V.K., & Magnarelli, J. (2022) Ageism, job engagement, negative stereotypes, intergenerational climate, and life satisfaction among middle-aged and older employees in a university setting. International Journal of Environmental research and Public Health, 19, (13) 7443. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266066/
Volkom, M. V., Stapley, J. C., & Amaturo, V. (2014). Revisiting the digital divide: Generational differences in technology use in everyday life. North American Journal of Psychology, 16(3), 557–574.
Weissbourd, R., Batanova, M., Lovison, V., & Torres, E. (2022, August 2). Loneliness in America: How the pandemic has deepened an epidemic of loneliness. Making Caring Common Project. Harvard Graduate School of Education Retrieved September 28, 2022, from https://mcc.gse.harvard.edu/reports/loneliness-in-america
Wang, H. Y., Sigerson, L., & Cheng, C. (2019). Digital nativity and information technology addiction: Age cohort versus individual difference approaches. Computers in Human Behavior, 90, 1-9. https://doi.org/10.1016/j.chb.2018.08.031
Yanguas, J., Pinazo-Henandis, S., & Tarazona-Santabalbina, F. J. (2018). The complexity of loneliness.Acta bio-medica: Atenei Parmensis, 89(2), 302–314. https://doi.org/10.23750/abm.v89i2.7404