Digital behavior patterns and ADHD symptoms in late adolescents and young adults
Shu Chen1, Guangying He2, Jingbo Zhao3
1Office of Student Affairs, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.
Background:
Digital media use has become deeply embedded in the daily lives of late adolescents and young adults, yet less is known about how specific digital behavior patterns are associated with ADHD symptom dimensions. This study focused on three emerging digital behaviors-speed watching, fragmented information consumption, and media multitasking-and examined their associations with inattention and hyperactivity-impulsivity within an ecologically informed multidomain framework encompassing demographic, perceived environmental, and family correlates.
Methods:
A total of 3,418 high school and university students aged 15-25 years (M_age = 18.60, SD = 1.05; 60.56% female) participated in the study, including 1,929 high school students (56.44%) and 1,489 university students (43.56%). They completed self-report measures of ADHD symptoms, digital behavior patterns, perceived physical environment, family environment, and demographic characteristics. ADHD symptoms were assessed in two dimensions: inattention and hyperactivity-impulsivity. Digital behavior patterns included speed watching, fragmented information consumption, and media multitasking. Pearson correlation analyses and hierarchical regression models were conducted to examine bivariate associations and the incremental explanatory value of digital behavior patterns after accounting for demographic, perceived environmental, and family variables.
Results:
Fragmented information consumption showed the strongest bivariate correlations with both inattention (r = 0.588) and hyperactivity-impulsivity (r = 0.488). In the hierarchical regression models, entering the digital behavior variables after the demographic, perceived environmental, and family variables accounted for an additional 22.3% of the variance in inattention and 14.5% of the variance in hyperactivity-impulsivity. Fragmented information consumption remained the strongest statistical correlate of both inattention (β = 0.379, p < 0.001) and hyperactivity-impulsivity (β = 0.256, p < 0.001), followed by media multitasking. The final models explained 44.0% and 34.9% of the variance in inattention and hyperactivity-impulsivity, respectively.
Conclusion:
Among the examined ecological correlates, digital behavior patterns-particularly fragmented information consumption and media multitasking-showed the most pronounced associations with ADHD symptoms in late adolescents and young adults. These findings suggest that distinguishing among specific forms of digital engagement may provide useful behavior-specific information about ADHD symptom variation. Because total screen time was not assessed, the findings do not establish that these behaviors are more informative than overall screen exposure. Given the cross-sectional and self-report design, the findings should be interpreted as associations rather than evidence of causal effects.
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