Shensa Ariel, Escobar-Viera César G, Sidani Jaime E, Bowman Nicholas D, Marshal Michael P, Primack Brian A
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.
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.
Soc Sci Med. 2017 Jun;182:150-157. doi: 10.1016/j.socscimed.2017.03.061. Epub 2017 Apr 24.
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.
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.
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.
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).
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.
抑郁症是全球致残的主要原因。社交媒体使用(SMU)与抑郁症之间的假定关联可能由一种新出现的适应不良使用模式来解释,这种模式被称为问题性社交媒体使用(PSMU),其特征是具有成瘾性成分。
我们旨在评估在美国大量年轻成年人样本中,PSMU与抑郁症状之间的关联,并控制SMU的总体时间和频率。
2014年10月,从美国一个具有全国代表性的基于概率的样本中随机选取19 - 32岁的参与者(N = 1749),随后邀请他们参与一项在线调查。我们使用经过验证的患者报告结局测量信息系统(PROMIS)简短抑郁量表来评估抑郁症状。我们使用改编后的卑尔根Facebook成瘾量表来测量PSMU,以涵盖更广泛的SMU。使用逻辑回归模型,我们测试了PSMU与抑郁症状之间的关联,同时控制SMU的时间和频率以及一系列全面的社会人口统计学协变量。
在多变量模型中,PSMU与抑郁症状的几率显著增加9%相关(调整后的优势比[AOR] = 1.09;95%置信区间[CI]:1.05,1.13;p < 0.001)。SMU频率增加也与抑郁症状增加显著相关,而SMU时间则不然(AOR = 1.01;95% CI:1.00,1.01;p = 0.001和AOR = 1.00;95% CI:0.999 - 1.001;p = 0.43)。
在这个具有全国代表性的年轻成年人样本中,PSMU与抑郁症状增加密切且独立相关。PSMU在很大程度上解释了SMU与抑郁症状之间的关联,这表明可能是我们使用社交媒体的方式,而非使用量,构成了风险。旨在减轻抑郁症状的干预措施,如对适应不良的SMU进行筛查,如果针对成瘾成分和频率而非SMU的时间进行干预,可能最为成功。