Passive and Active Social Media Use and Depressive Symptoms Among United States Adults

置信区间 优势比 逻辑回归 心理干预 萧条(经济学) 焦虑 抑郁症状 行为危险因素监测系统 医学 可能性 重性抑郁发作 心理学 老年学 临床心理学 人口学 精神科 公共卫生 认知 内科学 宏观经济学 社会学 护理部 经济
作者
César G. Escobar-Viera,Ariel Shensa,Nicholas David Bowman,Jaime E. Sidani,Jennifer M. Knight,A. Everette James,Brian A. Primack
出处
期刊:Cyberpsychology, Behavior, and Social Networking [Mary Ann Liebert]
卷期号:21 (7): 437-443 被引量:269
标识
DOI:10.1089/cyber.2017.0668
摘要

Social media allows users to explore self-identity and express emotions or thoughts. Research looking into the association between social media use (SMU) and mental health outcomes, such as anxiety or depressive symptoms, have produced mixed findings. These contradictions may best be addressed by examining different patterns of SMU as they relate to depressive symptomatology. We sought to assess the independent associations between active versus passive SMU and depressive symptoms. For this, we conducted an online survey of adults 18-49 of age. Depressive symptoms were measured using the Patient-Reported Outcomes Measurement Information System brief depression scale. We measured active and passive SMU with previously developed items. Factor analysis was used to explore the underlying factor structure. Then, we used ordered logistic regression to assess associations between both passive and active SMU and depressive symptoms while controlling for sociodemographic covariates. Complete data were received from 702 participants. Active and passive SMU items loaded on separate factors. In multivariable analyses that controlled for all covariates, each one-point increase in passive SMU was associated with a 33 percent increase in depressive symptoms (adjusted odds ratio [AOR] = 1.33, 95 percent confidence interval [CI] = 1.17-1.51). However, in the same multivariable model, each one-point increase in active SMU was associated with a 15 percent decrease in depressive symptoms (AOR = 0.85, 95 percent CI = 0.75-0.96). To inform interventions, future research should determine directionality of these associations and investigate related factors.
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