Project Overview
The increasing presence of digital media in adolescents’ leisure activities has raised concerns about the potential negative impact of excessive digital media use on their mental health. Over the past decade, an array of research endeavors have been pursued with the intent to explore and elucidate this evolving concern. However, the existing empirical evidence presents a somewhat inconsistent narrative. Some investigations have reported negative correlations between prolonged digital media usage and mental health, while others have reported either positive or no significant associations [1,2,3,4].
These divergent findings underscore the need to move beyond simplistic measures of “total screen time” and instead consider the type, purpose, and/or social context of digital media use. Emerging evidence indicates that what adolescents do online—and how they interact with others—may be more consequential than the sheer quantity of time spent on screens [see 5,6 & 7]
Objectives
This study sought to:
- Examine the association between time spent online (outside school) and adolescents’ well-being (i.e.,life satisfaction, positive affect, and negative affect).
- Investigate how specific digital activities—such as solo gaming, collaborative gaming, browsing, and social networking—relate to well-being outcomes.
Methods
This study utilized data from the 2018 Programme for International Student Assessment (PISA). The sample comprised 260,711 15-year-old students across 45 countries/economies.
Key Measures
- Well-Being: Assessed through self-reported life satisfaction, positive affect (e.g., happiness), and negative affect (e.g., sadness).
- Media Use: Measured through total screen time outside school and frequency of specific activities like gaming, browsing for fun, and social media engagement.
Data Preparation
- Excluded schools with fewer than five participating students to minimize data sparsity.
- Recoded internet usage variables (for school use, weekday use, and weekend use) to enhance clarity and consistency.
- Prepared a clean, structured dataset suitable for multilevel modeling.
The map below shows the number of schools in each country. Please hover to view country-level data.
Results
To account for the nested structure of the data (students within schools within countries) a three-level multilevel model was used for each outcome.The unconditional models( modesl with. o predictors) revealed the proportion of variance attributable to differences at the country and school levels for each outcome as follows:
- Life satisfaction: 2.7% country, 6.6% school
- Positive affect: 2% country, 4.7% school
- Negative affect: 3% country, 8% school
Estimating effect of screen time on the three outcomes
Screen Time and Subjective Well-Being
The analysis revealed significant associations between the amount of time spent on the internet and subjective well-being:
Adolescents who spent five or more hours per day online outside of school reported:
- Lower life satisfaction.
- Lower positive affect
- Higher negative affect
These effects remained consistent even after controlling for SES, indicating that heavy internet use may independently contribute to declines in subjective well-being.
The plot below displays country-level estimates of the relationship between screen time and life satisfaction.
Each point represents a country’s estimated effect of screen time on adolescents’ life satisfaction, with horizontal lines indicating confidence intervals. In most countries increased screen time is associated with lower life satisfaction. The countries are sorted from the strongest negative associations at the bottom (e.g., Iceland) to the weakest or near-zero associations at the top (e.g., Brunei Darussalam).
The vertical dashed line at zero represents no effect. Since the majority of confidence intervals lie to the left of this line, the plot provides visual evidence of a generally negative association between screen time and life satisfaction across countries. However, the variation in effect sizes and confidence intervals suggests the strength of this relationship differs significantly across national contexts.
This plot illustrates the estimated impact of different screen time durations and socioeconomic status (SES) on well-being. Compared to the reference group (2 or less hours), all screen time durations from three hours to seven or more hours are associated with negative well-being estimates. The effect becomes more negative as screen time increases, suggesting a dose-response relationship where more screen time is linked with lower well-being
This plot compares the estimated effects of different screen time durations on two dimensions of emotional well-being: Positive Affect and Negative Affect.
Screen Time and Positive Affect (blue circles):
As screen time increases from three to seven+ hours, estimates of positive affect decline slightly, suggesting that longer screen time may be associated with lower levels of positive emotions such as joy, interest, and enthusiasm.
Screen Time and Negative Affect (orange squares):
In contrast, negative affect estimates increase with longer screen time durations. This means adolescents who spend more time on screens report higher levels of negative emotions like anxiety, sadness, or irritation.
Differential Effects of Activity Types
The findings also highlighted that the type of digital activity plays a critical role in adolescent on well-being:
Negative Associations
Solo gaming and browsing the internet for fun were consistently associated with lower life satisfaction and higher negative affect.
Positive Associations
Collaborative gaming, social networking, and using the internet for communication and information were positively associated with life satisfaction and positive affect. These activities likely foster social connections, engagement, and a sense of purpose, which may explain their more positive impact.
Conclusion and Insights
The findings underscore the potential mental health implications associated with excessive screen time in adolescents. The results emphasize that protracted screen time can negatively impact the mental well-being of adolescents irrespective of their socioeconomic background, highlighting the universality of this concern.
The findings also highlight the need to move beyond viewing digital media use as a monolithic activity when assessing its impact on adolescent well-being. The results indicate the importance of differentiating between the types of digital activities adolescents engage in and understanding the specific effects each can have on their mental health.
These insights equip policymakers, educators, and parents to design targeted strategies that promote healthier digital engagement and safeguard adolescent mental health. Future research should prioritize uncovering causal pathways and examining how individual and cultural factors may shape these dynamics.
References
Twenge, J. M., & Campbell, W. K. (2019). Media Use Is Linked to Lower Psychological Well-Being: Evidence from Three Datasets. The Psychiatric Quarterly, 90(2), 311–331. https://doi.org/10.1007/s11126-019-09630-7
Twenge, J. M., & Campbell, W. K. (2018). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive Medicine Reports, 12, 271–283. https://doi.org/10.1016/j.pmedr.2018.10.003
Odgers, C. L., & Jensen, M. R. (2020). Annual Research Review: Adolescent mental health in the digital age: facts, fears, and future directions. Journal of Child Psychology and Psychiatry, and allied disciplines, 61(3), 336–348. https://doi.org/10.1111/jcpp.13190
Orben A. (2020). Teenagers, screens and social media: a narrative review of reviews and key studies. Social Psychiatry and Psychiatric Epidemiology, 55(4), 407–414. https://doi.org/10.1007/s00127-019-01825-4
OECD (2019), PISA 2018 Results (Volume I): What Students Know and Can Do, PISA, OECD Publishing, Paris, https://doi.org/10.1787/5f07c754-en.
Keles, B., McCrae, N., & Grealish, A. (2020). A systematic review: The influence of social media on depression, anxiety and psychological distress in adolescents. International Journal of Adolescence and Youth, 25(1), 79–93. https://doi.org/10.1080/02673843.2019.1590851
Valkenburg, P. M., Beyens, I., & Pouwels, J. L. (2021). Adolescents’ well-being as a function of digital media use: A latent profile analysis. Child Development, 92(5), 1673–1690. https://doi.org/10.1111/cdev.13633