Digital engagement and its association with adverse psychiatric symptoms: A longitudinal cohort study utilizing latent class analysis

Objectives: To assess the impact of digital media usage on psychiatric symptoms in an adolescent population utilizing a longitudinal cohort design. Methods: Using two waves of the GUI child cohort, age 13 (N = 7527) and age 17/18 (N = 6126), we used latent class analysis (LCA) to create latent groups centred around self-reported time spent online, and the self-reported behaviours children engaged with online. At both waves, the 4 class latent model suited best. We used the different symptoms scales of the Strengths and Difficulties Questionnaires (SDQ), self-reported, at age 17 as our outcome variable. Using linear regression analysis, we then examined the associations between our latent class model and psychiatric symptoms, using moderate usage as our reference group, with adjustments being made for baseline psychiatric symptoms, maternal education and pre-diagnosed mental disorder. Results: For females, placement in the high usage group at 13 was associated with increased internalizing symptoms, whereas placement in the high usage group at 17 was associated with an increase in all symptoms. For males, placement in the high usage group at 17 was associated with increased emotional symptoms, and placement in the “low usage & behaviour engagement”group, a group showing low reported time online and low engagement in our measured online behaviours at 17, was associated with an increase in all symptoms. Finally for both sexes, placement in the “moderate usage, entertainment only” group at age 13, (a group reporting no school-based online engagement), was associated with increases in all symptoms except emotional symptoms. Conclusion: High digital media usage is associated with increased psychiatric symptoms in both males and females, with moderate usage associated with positive effects on symptoms compared to both our high usage, and low usage groups.