IntroductionResearch indicates that stressors introduced by the COVID-19 pandemic have negatively impacted mental health, particularly among young people.1 Time spent on digital technology (e.g., social media, smartphones) has also increased2 as schools, workplaces, and social gathering sites have closed, thus intensifying pre-pandemic concerns regarding the putative effects of digital technology use (DTU) on mental health. Indeed, recent academic and newspaper articles have both directly and indirectly asserted that increased DTU is a source of the heightened psychological distress observed during the pandemic.3–5 However, these claims are dubious for two primary reasons. First, these articles rely on self-report measures of DTU, which are inaccurate6 and prone to systematic bias.7 Second, since the pandemic has impacted both mental health and DTU for many, the observed association between the two may be attributable to a shared common cause, rather than causality. Thus, we investigated the longitudinal associations between objectively measured DTU and mental health while accounting for important COVID-19-related effects.MethodsThis study was approved by the University of Pittsburgh and followed Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. In this four-wave panel study, participants were recruited from Prolific (https://www.prolific.co/), an online participant-recruitment platform. Waves of data collection were launched on August 14, September 12, October 14, and November 9 of 2020. Eligible participants were U.S. residents, 18-35 years old, iPhone users, and had ≥ 10 previous submissions on Prolific with approval rating ≥95%. At each wave, participants uploaded screenshots of their “Screen Time” application (which passively tracks device usage) and completed self-reports of mental health (depression, anxiety, suicidal ideation [SI]), COVID-19-related stressors, and perceived COVID-19-related impact on well-being and DTU (Table 1). We extracted three elements from the “Screen Time” screenshots: (1) total screen time, (2) total time spent on social media, and (3) total number of pickups. We estimated separate random-intercept multilevel models for each mental health outcome using Mplus. Predictors were entered hierarchically in blocks (see eTable 3 in Supplement) to assess ΔR2 at the within- and between-person levels. See Supplement for methodological details. ResultsA total of 384 young adults participated in this study (Mage = 24.5, SDage = 5.1; 57% female; 54% white; 48% Bachelor’s degree education or above). Overall, participants averaged 47.5 hours of Screen Time, 677 pickups, and 15.5 hours of social media over the past week. On average, participants reported experiencing between 4 and 5 pandemic-related stressors per wave. Mean depression and anxiety t-scores were 54.6 and 56.7, respectively, and nearly 29% of participants reported past-week SI at least once. See eTable 1 for summary statistics of sample demographics and primary variables.Results of the multilevel analyses revealed that objectively-measured total screen time and social media use were unrelated to within- or between-person differences in mental health, while between-person difference in pickups was negatively associated with depression (see Figure 1). Together, the objective DTU variables explained, at most, 2.8% of the within- or between-person variance in any of the mental health outcomes (eTable 3 in Supplement). COVID-related impacts on well-being had the largest effects across models—accounting for about 45% and 10%, respectively, of the between- and within-person variance in depression and anxiety, and 21%/28% of the between/within variance in SI. DiscussionAmong a sample of young adults, a population with particularly high rates of DTU8 and COVID-19-related distress,1 we found that objectively-measured DTU did not contribute to increases in depression, anxiety, or SI—refuting the popular notion that increases in DTU may be contributing to young peoples’ psychological distress during the pandemic. Rather, depression, anxiety, and SI were driven mostly by young peoples’ reports of the pandemic’s impact on their well-being. The convenience-based sample, retrospective (past week) assessments of mental health outcomes, and single-item measures of COVID-19-related impacts are limitations of the study. Nevertheless, results indicate that current speculations about the direct harms of DTU on mental health may be unfounded and risk diverting attention from a more likely cause: pandemic-related stressors.
Fuzzy Constructs: The Overlap between Mental Health and Technology ‘Use’
