Noah Kreski1, Jonathan Platt1, Caroline Rutherford1, Mark Olfson2, Candice Odgers3, John Schulenberg4, Katherine M Keyes5. 1. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York. 2. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York; Department of Psychiatry, Columbia University Medical Center, Columbia University, New York, New York. 3. Department of Psychological Science, University of California Irvine, Social and Behavioral Sciences Gateway, Irvine, California. 4. Institute for Social Research, University of Michigan, Ann Arbor, Michigan; Department of Psychology and Center for Growth and Human Development, University of Michigan, Ann Arbor, Michigan. 5. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York. Electronic address: kmk2104@columbia.edu.
Abstract
PURPOSE: Depression is increasingly common among US adolescents; the extent to which social media exposure contributes to this increase remains controversial. METHODS: We used Monitoring the Future data from 8th and 10th grade students (n = 74,472), 2009-2017, to assess the relationship between daily social media use and depressive symptoms. Self-reported depressive symptom score (range: 4-20) was assessed continuously using a log-transformed outcome and at varying cut scores with logistic regression analyses. First, these outcomes were examined overall, comparing adolescents using social media daily to adolescents who were not. We then estimated predicted depressive symptom scores using 26 predictors in order to establish underlying depression risk. We partitioned students into depression risk quintiles to control for confounding due to underlying depression risk and examine heterogeneity in the association between social media use and depressive symptoms. Sensitivity analyses were used to test the robustness of results with different configurations of the predicted score model, and overall associations were examined in two-year groups to identify differences in effects. RESULTS: For girls, in adjusted risk-stratified analysis, daily social media use was not associated with high (vs. low) depressive symptoms. For boys, results were inconsistent, suggesting a protective effect of daily social media use at some cut scores. Results were consistent across sensitivity analyses, and any potential harmful effects appear to be limited to 2009-2010, limiting the evidence supporting social media as a current risk factor for depressive symptoms. CONCLUSIONS: Among US adolescents, daily social media use is not a strong or consistent risk factor for depressive symptoms.
PURPOSE: Depression is increasingly common among US adolescents; the extent to which social media exposure contributes to this increase remains controversial. METHODS: We used Monitoring the Future data from 8th and 10th grade students (n = 74,472), 2009-2017, to assess the relationship between daily social media use and depressive symptoms. Self-reported depressive symptom score (range: 4-20) was assessed continuously using a log-transformed outcome and at varying cut scores with logistic regression analyses. First, these outcomes were examined overall, comparing adolescents using social media daily to adolescents who were not. We then estimated predicted depressive symptom scores using 26 predictors in order to establish underlying depression risk. We partitioned students into depression risk quintiles to control for confounding due to underlying depression risk and examine heterogeneity in the association between social media use and depressive symptoms. Sensitivity analyses were used to test the robustness of results with different configurations of the predicted score model, and overall associations were examined in two-year groups to identify differences in effects. RESULTS: For girls, in adjusted risk-stratified analysis, daily social media use was not associated with high (vs. low) depressive symptoms. For boys, results were inconsistent, suggesting a protective effect of daily social media use at some cut scores. Results were consistent across sensitivity analyses, and any potential harmful effects appear to be limited to 2009-2010, limiting the evidence supporting social media as a current risk factor for depressive symptoms. CONCLUSIONS: Among US adolescents, daily social media use is not a strong or consistent risk factor for depressive symptoms.
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