By Lt. Col. Dan Cassidy, Ph.D., ABPP, U.S. Air Force
Oct. 24, 2024

U.S. Air Force photo by Airman 1st Class Rhea Beil

We’ve made plenty of progress as a species these past 500 years. Life expectancy is up,¹ poverty is down,² and the internet is ubiquitous.³ And yet, all is not well. Nearly one in 10 Americans met criteria for a past-year major depressive episode in 2020. Among people 18-25 years of age, that number crested nearly one in five.⁴ That’s a 9.8% absolute increase since 2005.⁵

Recent data suggest that excessive screen time may be partly to blame.⁶ That’s worth a deeper dive, since over half of military service members classify as ‘high screen users’ (>2hrs/day, not for work or school).⁷

Genes, Technology, and Behavior – An Analogous Case

There’s evidence that the symptoms and health consequences of heart disease were known for thousands of years. Yet, we saw invention of the modern computer hard drive before arriving, in 1957, at a real understanding of its causes and prevention.⁸ That’s when Framingham Heart Study data demonstrated that heart health is modifiable by individual behavior, and not merely a product of genetic misfortune. Good work and excellent news followed as coordination across the clinical and public health communities brought the prevalence of heart disease to heel beginning in the 1970s.⁹

Challenge and Opportunity are a Package Deal

An abundance of delicious food is, as it turns out, problematic for human health¹⁰; so, too, a sedentary lifestyle.¹¹ But the same innovations that spawned these heart health challenges also helped solve for undernutrition and set the economic conditions for improvements in human health and well-being. Now as before, emerging technologies expand the domain of the possible, pairing promise with preventable peril. Our civilization invests an estimated 352 billion hours each month on social media platforms.¹² We spend some of this time meeting interesting people and learning new things, and some ignoring our children and skipping a dinner out with friends. Empirical work over the last decade suggests that this shift in how each of us spends our time feeds a corresponding, population-wide decline in mood and perceived well-being.

Research in this domain has focused on adolescents, among whom Kim and colleagues observed heavy (i.e., >4hrs/day) screen time to more than triple the odds of a major depressive episode relative to light use (i.e., <2hrs/day).¹³ A systematic review of the relationship between screen time and mental health summarizing data from nearly two million adolescents across 50 separate studies demonstrated a direct relationship between volume of recreational screen use and symptoms of anxiety and depression.⁶ More compellingly, a series of experimental studies has intervened on young adults’ screen time exposure, establishing among those with baseline emotional distress a causal relationship between social media exposure and mental health symptoms.^{14, 15} Benefits of deliberately reduced social media use are variously attributed to improvements in sleep quality and duration,^{16, 17, 18} increased physical activity,¹⁹ and a reduction in unrealistic social comparison.²⁰

Practical Implications for Health Care Providers

Today’s digital media landscape is qualitatively distinct from that of the early 2000s. New analytic methods such as matrix factorization reveal the preferences and interests of individual users, while age-old concepts like variable interval reinforcement combine with ‘infinite scroll’ interfaces to maximize time on site.²¹ Motor vehicle accidents and rapid transit to the hospital both were enabled by the combustion engine, and our experience with social media and related technologies also will bring benefits and challenges to each of us and the patients we serve.

Let’s say, for example, you’re helping a patient resolve symptoms of posttraumatic stress and identify sleep health as a likely moderator of change in the context of an exposure-based treatment. Your patient has no difficulty falling or staying asleep, but they’re struggling to get to bed at a reasonable hour and believe the tractor beam of social media is partly to blame. Or maybe together, you’ve agreed to implement behavioral activation for depression, but they’re struggling with adherence to the plan – technology is displacing real-world experiences. How to proceed?

Grocery stores position well-lit candy in the ‘impulse purchase’ area near the register. We live in a digital environment that’s similarly engineered to form and sustain specific patterns of habit, some of which we may wish to shake. The good news is that a habit is a habit; good or undesirable, each follows a classic three-term contingency model comprising a cue, an action, and a consequence.²² Helping patients fine-tune their digital habits involves a familiar set of behavior design principles:

• Self-Monitoring. Merely tracking behavior (e.g., when, what, and for how long) yields impressive benefit.²³ Tracking begets awareness, which inspires action and enables refinement of self-designed behavior change tactics. Paper-and-pencil diaries and a variety of apps are available for this purpose.
• Cue Avoidance. Opting out of automatic notifications via mobile device settings prevents the ‘lead domino’ from falling, forestalling a behavioral chain reaction that’s tough to abort once activated.²⁴ Leaving devices beyond reach or out of sight extends this principle yet further.
• Implementation Intention. Nature abhors a vacuum! The wisdom is ancient, but the scientific evidence is fresh: anticipating challenging situations (“When I…”) and ‘preloading’ a highly specific desired behavior (“...then I will…”) increases our ability to follow-through in the moments that matter most.²⁵ “When I feel the urge to check my phone during the morning meeting, then I will flip the phone face down and make two seconds of deliberate eye contact with whomever is speaking.”

The Tip Sheet on Social Media Use and Mental Health | Youth Engaged 4 Change summarizes recommendations for healthy social media use originally developed for youth, but from which we all can benefit.

We’re afforded only so much time during a human life. The quality of attention we bring to each moment dictates the cumulative quality of our experience. May each of us learn to use technology wisely and for maximum benefit.

References

1. Deaton, A. (2013). The great escape: Health, wealth, and the origins of inequality. Princeton University Press.
2. World Bank. (2020). Poverty and Shared Prosperity 2020: Reversals of Fortune. Washington, DC: World Bank. doi:10.1596/978-1-4648-1602-4.
3. International Telecommunication Union (ITU). (2023). Global and regional ICT data. ITU. https://www.itu.int/en/ITU-D/Statistics/pages/stat/default.aspx
4. Goodwin, R. D., Dierker, L., Wu, M., Galea, S., Hoven, C., & Weinberger, A. H. (2022). Trends in U.S. depression prevalence from 2015 to 2020: The widening treatment gap. American Journal of Preventive Medicine, 63, 275-282.
5. Substance Abuse and Mental Health Services Administration. (2006). Results from the 2005 National Survey on Drug Use and Health: National findings (NSDUH Series H-30, DHHS Publication No. SMA 06-4194). Rockville, MD: Office of Applied Studies.
6. Santos, R. M. S., Mendes, C. G., Sen Bressani, G. Y., de Alcantara Ventura, S., de Almeida Noguiera, Y. J., de Miranda, D. M., & Romano-Silva, M. A. (2023). The associations between screen time and mental health in adolescents: a systematic review. BMC psychology, 11, 127.
7. Olapeju, B., Hendrickson, Z. M., Shanahan, P., Mushtaq, O., & Ahmed, A. E. (2024). Health behavior profiles and association with mental health status among US active-duty service members. Frontiers in Public Health, 12, 1324663.
8. Dawber, T. R., Kannel, W. B., Revotskie, N., Stokes, J., Kagan, A., & Gordon, T. (1959). Some factors associated with the development of coronary heart disease: Six years' follow-up experience in the Framingham Study. American Journal of Public Health and the Nation’s Health, 49, 1349-1356.
9. Mensah, G. A., & Brown, D. W. (2007). An overview of cardiovascular disease burden in the United States. Health Affairs, 26, 38-48.
10. Temple, J. L. (2020). Behavioral sensitization of the reinforcing value of food: What food and drugs have in common. Preventive Medicine, 92, 90-99.
11. Jingjie, W., Yang, L., Jing, Y., Ran, L., Yiqing, X., & Zhou, N. (2022). Sedentary time and its association with risk of cardiovascular diseases in adults: an updated systematic review and meta-analysis of observational studies. BMC Public Health, 22, 286.
12. We Are Social. (2023). Digital 2023: Global overview report. DataReportal. https://datareportal.com/reports/digital-2023-global-overview-report
13. Kim, S., Favotto, L., Halladay, J., Wang, L., Boyole, M. H., & Georgiades, K. (2020). Differential associations between passive and active forms of screen time and adolescent mood and anxiety disorders. Social psychiatry and psychiatric epidemiology, 55, 1469-1478.
14. Davis, C. G., & Goldfield, G. S. (2024). Limiting social media use decreases depression, anxiety, and fear of missing out in youth with emotional distress: A randomized controlled trial. Psychology of Popular Media. Psychology of Popular Media. Advance online publication. https://psycnet.apa.org/doi/10.1037/ppm0000536
15. Tromholt, M. (2016). The Facebook experiment: Quitting Facebook leads to higher levels of well-being. Cyberpsychology, Behavior, and Social networking, 19, 661-666.
16. Alonzo, R. Hussain, J., Stranges, S., & Anderson, K. K. (2021). Interplay between social media use, sleep quality, and mental health in youth: A systematic review. Sleep Medicine Reviews, 56, 101414.
17. Schrempft, S., Baysson, H., Chessa, A., Lorthe, E., Zaballa, Maria-Eugenia, Stringhini, S., Guessous, I., & Nehme, M. (2024). Associations between bedtime media use and sleep outcomes in an adult population-based cohort. Sleep Medicine, 121, 226-235.
18. Brautsch, L. A., Lund, L., Andersen, M. M., Jennum, P. J., Folker, A. P., & Andersen, S. (2023). Digital media use and sleep in late adolescence and young adulthood: a systematic review. Sleep Medicine Reviews, 68, 101742.
19. Neville, R. D., Hopkins, W. G., McArthur, B. A., Draper, C. E., & Madigan, S. (2024). Associations between changes in 24-hour movement behaviors in children and adolescents during the COVID-19 Pandemic: A systematic review and mediation-based meta-analysis. J Phys Act Health, 8, 323-332.
20. Midgley, C., Thai, S., Lockwood, P. Kovacheff, C., & Page-Gould, E. (2021). When every day is a high school reunion: social media comparisons and self-esteem. Journal of Personality and Social Psychology, 121, 285-307.
21. Mejias, U. A., & Couldry, N. (2019). Datafication. Internet Policy Review, 8, 1-10.
22. Skinner, B. F. (1953). Science and Human Behavior. New York: Macmillan.
23. Faulhaber, M. E. (2023). The effect of self-monitoring limited social media use on psychological well-being. Technology, Mind, and Behavior, 4, DOI: 10.1037/tmb0000111
24. Li, M., Duan, J., Liu, Y., Zou, J., Yang, X., & Zeng, H. (2023). The habitual characteristic of smart phone use under relevant cues among Chinese college students. Frontiers in Psychology, 14, 1218886.
25. Elliott, M. A., Paterson, A., Orr, S., Marshall, C., Wood, C., Toye, M., & Wilson, C. (2021). Evidence that implementation intentions reduce drivers’ use of mobile phones while driving. Transportation Research Part F: Traffic Psychology and Behaviour, 78, 381-397.

U.S. Air Force Lt. Col. Dan Cassidy, Ph.D., ABPP, is a board-certified clinical health psychologist at the PHCoE with research and applied interests in population science and health behavior change.