This week, Mad in America examines three studies around technology and mental health. The first finds that preoccupation with smartphones is linked to reduced psychological well-being among Turkish adolescents. The second reports that high and increasing screen use is linked to suicidal behavior and increased mental health symptoms in US youths. The third finds that more than one-third of US adults consults AI chatbots about their mental health at least once per week. Taken together, these studies find that people with mental health concerns are increasingly looking to technology that is itself implicated in poor mental health to help solve their mental health issues.
Preoccupation with Smartphones Linked to Reduced Psychological Well-Being in Adolescents
A new Turkish study published in BMC Psychology finds that being distracted and alienated from the environment due to smartphone use (smombie) and being preoccupied with a smartphone during face-to-face interactions with others (phubbing) are linked to reduced psychological well being. This research, led by Ramazan Inci from Batman University in Turkey, reports that while both smombie and phubbing levels are associated with reduced psychological well-being, phubbing is the stronger predictor.
The goal of this study was to examine the link between smombie and phubbing levels to psychological well-being in adolescents. The authors recruited 626 Turkish adolescents between the ages of 10 to 19 through social media invitations shared in school, youth, and community groups. Participants were asked to complete three self-report surveys: the Smombie Scale for Adolescents, the General Phubbing Scale, and the Psychological Well-Being Scale.
Increases in both smombie and phubbing levels were linked to a decrease in psychological well-being. These behaviors were also linked to one another, meaning that as smombie levels increased, so did phubbing. According to the authors, smombie and phubbing levels together explain about 24% of the observed differences in psychological well-being. Phubbing was the factor most linked to decreased psychological well-being. The authors report that phubbing levels were associated with an additional 5 point reduction in psychological well-being (on a scale from eight to 56) compared to all other variables including smombie levels.
This study had several notable limitations. The authors recruited participants using a convenience sample design. This could limit the validity of the findings compared to a random sample. The surveys relied on self-report measures. The results could have been biased by participants misremembering or providing socially acceptable rather than true responses. The participants were all Turkish adolescents, limiting generalizability to other populations. Smombie and phubbing levels may have a significantly different relationship to psychological well-being in collectivist cultures like Turkey compared to more individualistic cultures such as the US.
High and Increasing Addictive Screen Use Patterns Linked to Suicidal Behavior in US Youths
A new longitudinal study published in JAMA finds that high and increasing screen use patterns are linked to increased risk of suicidal behaviors in youths. This study, led by Yunyu Xiao of Weill Cornell Medicine Medical School in New York, also finds that high video game use was associated with increased internalizing symptoms (such as depression and anxiety) while increasing social media use was linked to more severe externalizing symptoms (such as aggression and impulsivity).
The goal of this research was to examine addictive patterns associated with smartphone use and their influence on suicidal behaviors and adverse mental health outcomes. The authors recruited 4,285 children between the ages of nine and 10 from 21 US cities to participate in this study. Researchers measured suicidal behaviors, mental health symptoms, and addictive screen use patterns related to smartphones, social media, and video games at baseline and at two, three, and four year follow-ups.
The authors identified three addictive use trajectories for social media and smartphone use: high, increasing, and low. They also found two addictive trajectories (high and low) for video game use. For social media use, 40.9% of participants were classified as having high or increasing addictive use patterns. High (2.39 times increased odds) and increasing (2.14) social media addictive use trajectories were linked to greater risk of suicidal behavior compared to low use. The high social media use trajectory was also linked to a 79% increased risk of externalizing symptoms such as aggression and impulsivity.
For smartphone use, nearly three-quarters of participants were classified as having a high or increasing addictive use trajectory. High (2.17 times increased odds) and increasing (22% increased odds) addictive smartphone use trajectories were linked to greater risk of suicidal behaviors compared to low use.
For video game use, 41.1% of participants showed a high use trajectory. The high addictive use trajectory was associated with a 54% increased odds of suicidal behaviors compared to low use. The high addictive video game use trajectory was also linked to doubled odds of internalizing symptoms such as anxiety and depression.
This study had 3 main limitations. This research was observational, meaning the data cannot conclusively say that addictive screen use trajectories cause suicidal behavior and increased mental health symptoms. For example, it could be the case that mental health symptoms drove participants towards more social media and video game use. The self-report nature of the surveys means the data could have been biased by misremembering or participants providing socially acceptable rather than accurate information. This research was conducted using a sample from the US, limiting generalizability to other populations.
More than One-Third of US Adults Routinely Consult AI Chatbots About Their Mental Health
A new study published in the Journal of Medical Internet Research finds that more than one-third of US adults consults an AI chatbot at least once per week about mental health concerns. This research, led by Michiko Ueda from Syracuse University, also reports that participants with moderate to severe depression and anxiety are more likely to consult AI chatbots about their mental health while heavy AI users are more likely to report suicidal ideation.
The goal of the current work was to examine patterns of AI chatbot use related to mental health among adults in the US. The authors also wanted to assess preferences for AI chatbots compared to human mental health professionals. They recruited 1,805 participants between the ages of 18 to 49 and had them take an anonymous online survey about AI use related to mental health, preference for AI chatbots relative to human mental health professionals, and mental health symptoms.
Six-hundred-thirty-eight participants (35.2%) said they consulted an AI chatbot at least once per week about mental health concerns. This included 99 participants (5.5%) that were classified as “heavy users.” These participants reported regularly spending hours discussing their mental health with an AI chatbot. Participants with moderate to severe symptoms of depression or anxiety were 71% more likely to discuss their mental health with an AI chatbot. Heavy AI users were nearly 2.5 times more likely to report suicidal thoughts.
Sixty percent of participants said they would discuss their mental health with family and friends before using an AI chatbot. While 28.4% of participants that had seen a human mental health professional before reported fewer visits after starting AI chatbot use, the majority of participants expressed more positive views of human mental health professionals compared to AI chatbots. Heavy AI users were the exception, reporting similar positive ratings for both AI chatbots and human mental health professionals.
This research had four main limitations. The observational design means that this data cannot speak to causes. The self-report nature of the surveys means that data may be biased by misremembering or socially acceptable rather than accurate responses. The low number of heavy AI users means the findings related to this group may not be an accurate representation of the larger population of heavy users. These results are likely not generalizable to populations outside the US.
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Inci, R., Sağlam, M., Köroğlu, S., Oluç, T., Gül, N., & Yıldız, M. (2026). The effect of Smombie and phubbing levels on psychological well-being in adolescents. BMC Psychology, 14(1). (Link)
Ueda M, Birnbaum ML, Liu Y, Yu Q, Tian X, Mirer A, Ramanathan S, Sinyor M. (2026). Help-Seeking in the Age of AI: Cross-Sectional Survey of the Use and Perceptions of AI-Based Mental Health Support Among US Adults. JMIR Ment Health 2026;13:e88196 (Link)
Xiao, Y., Meng, Y., Brown, T. T., Keyes, K. M., & Mann, J. J. (2025). Addictive screen use trajectories and suicidal behaviors, suicidal ideation, and mental health in US youths. JAMA, 334(3), 219. (Link)