Ariel Shensa1, César G Escobar-Viera2, Jaime E Sidani3, Nicholas D Bowman4, Michael P Marshal5, Brian A Primack3. 1. Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; Center for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, PA, United States. Electronic address: shensaa@upmc.edu. 2. Center for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, PA, United States; Health Policy Institute, University of Pittsburgh, Pittsburgh, PA, United States. 3. Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; Center for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, PA, United States. 4. Department of Communication Studies, West Virginia University, Morgantown, WV, United States. 5. Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States.
Abstract
RATIONALE: Depression is the leading cause of disability worldwide. The suggested association between social media use (SMU) and depression may be explained by the emerging maladaptive use pattern known as problematic social media use (PSMU), characterized by addictive components. OBJECTIVE: We aimed to assess the association between PSMU and depressive symptoms-controlling for overall time and frequency of SMU-among a large sample of U.S. young adults. METHODS: In October 2014, participants aged 19-32 (N = 1749) were randomly selected from a nationally-representative U.S. probability-based panel and subsequently invited to participate in an online survey. We assessed depressive symptoms using the validated Patient-Reported Outcomes Measurement Information System (PROMIS) brief depression scale. We measured PSMU using an adapted version of the Bergen Facebook Addiction Scale to encompass broader SMU. Using logistic regression models, we tested the association between PSMU and depressive symptoms, controlling for time and frequency of SMU as well as a comprehensive set of socio-demographic covariates. RESULTS: In the multivariable model, PSMU was significantly associated with a 9% increase in odds of depressive symptoms (AOR [adjusted odds ratio] = 1.09; 95% CI [confidence interval]: 1.05, 1.13; p < 0.001.) Increased frequency of SMU was also significantly associated with increased depressive symptoms, whereas SMU time was not (AOR = 1.01; 95% CI: 1.00, 1.01; p = 0.001 and AOR = 1.00; 95% CI: 0.999-1.001; p = 0.43, respectively). CONCLUSION: PSMU was strongly and independently associated with increased depressive symptoms in this nationally-representative sample of young adults. PSMU largely explained the association between SMU and depressive symptom, suggesting that it may be how we use social media, not how much, that poses a risk. Intervention efforts aimed at reducing depressive symptoms, such as screenings for maladaptive SMU, may be most successful if they address addictive components and frequency-rather than time-of SMU.
RATIONALE: Depression is the leading cause of disability worldwide. The suggested association between social media use (SMU) and depression may be explained by the emerging maladaptive use pattern known as problematic social media use (PSMU), characterized by addictive components. OBJECTIVE: We aimed to assess the association between PSMU and depressive symptoms-controlling for overall time and frequency of SMU-among a large sample of U.S. young adults. METHODS: In October 2014, participants aged 19-32 (N = 1749) were randomly selected from a nationally-representative U.S. probability-based panel and subsequently invited to participate in an online survey. We assessed depressive symptoms using the validated Patient-Reported Outcomes Measurement Information System (PROMIS) brief depression scale. We measured PSMU using an adapted version of the Bergen Facebook Addiction Scale to encompass broader SMU. Using logistic regression models, we tested the association between PSMU and depressive symptoms, controlling for time and frequency of SMU as well as a comprehensive set of socio-demographic covariates. RESULTS: In the multivariable model, PSMU was significantly associated with a 9% increase in odds of depressive symptoms (AOR [adjusted odds ratio] = 1.09; 95% CI [confidence interval]: 1.05, 1.13; p < 0.001.) Increased frequency of SMU was also significantly associated with increased depressive symptoms, whereas SMU time was not (AOR = 1.01; 95% CI: 1.00, 1.01; p = 0.001 and AOR = 1.00; 95% CI: 0.999-1.001; p = 0.43, respectively). CONCLUSION: PSMU was strongly and independently associated with increased depressive symptoms in this nationally-representative sample of young adults. PSMU largely explained the association between SMU and depressive symptom, suggesting that it may be how we use social media, not how much, that poses a risk. Intervention efforts aimed at reducing depressive symptoms, such as screenings for maladaptive SMU, may be most successful if they address addictive components and frequency-rather than time-of SMU.
Keywords:
Depression; Nationally-representative; PROMIS (patient reported outcomes measurement information system); Problematic social media use; Social media; Social media addiction; Young adults
Authors: Liu Yi Lin; Jaime E Sidani; Ariel Shensa; Ana Radovic; Elizabeth Miller; Jason B Colditz; Beth L Hoffman; Leila M Giles; Brian A Primack Journal: Depress Anxiety Date: 2016-01-19 Impact factor: 6.505
Authors: Katherine M Keyes; Dahsan Gary; Patrick M O'Malley; Ava Hamilton; John Schulenberg Journal: Soc Psychiatry Psychiatr Epidemiol Date: 2019-03-30 Impact factor: 4.328