Tacheva Zhasmina, Ivanov Anton
School of Information Studies, Syracuse University, Syracuse, NY, United States.
Department of Business Administration, Gies College of Business, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, United States.
JMIR Ment Health. 2021 Mar 8;8(3):e24939. doi: 10.2196/24939.
Opioid-related deaths constitute a problem of pandemic proportions in the United States, with no clear solution in sight. Although addressing addiction-the heart of this problem-ought to remain a priority for health practitioners, examining the community-level psychological factors with a known impact on health behaviors may provide valuable insights for attenuating this health crisis by curbing risky behaviors before they evolve into addiction.
The goal of this study is twofold: to demonstrate the relationship between community-level psychological traits and fatal opioid overdose both theoretically and empirically, and to provide a blueprint for using social media data to glean these psychological factors in a real-time, reliable, and scalable manner.
We collected annual panel data from Twitter for 2891 counties in the United States between 2014-2016 and used a novel data mining technique to obtain average county-level "Big Five" psychological trait scores. We then performed interval regression, using a control function to alleviate omitted variable bias, to empirically test the relationship between county-level psychological traits and the prevalence of fatal opioid overdoses in each county.
After controlling for a wide range of community-level biopsychosocial factors related to health outcomes, we found that three of the operationalizations of the five psychological traits examined at the community level in the study were significantly associated with fatal opioid overdoses: extraversion (β=.308, P<.001), neuroticism (β=.248, P<.001), and conscientiousness (β=.229, P<.001).
Analyzing the psychological characteristics of a community can be a valuable tool in the local, state, and national fight against the opioid pandemic. Health providers and community health organizations can benefit from this research by evaluating the psychological profile of the communities they serve and assessing the projected risk of fatal opioid overdose based on the relationships our study predict when making decisions for the allocation of overdose-reversal medication and other vital resources.
在美国,与阿片类药物相关的死亡构成了一个具有大流行规模的问题,目前尚无明确的解决方案。尽管解决成瘾问题——这一问题的核心——应该仍然是健康从业者的首要任务,但研究对健康行为有已知影响的社区层面心理因素,可能会通过在危险行为演变成成瘾之前加以遏制,为缓解这一健康危机提供有价值的见解。
本研究的目标有两个:从理论和实证两方面证明社区层面心理特征与致命阿片类药物过量之间的关系,并提供一个利用社交媒体数据以实时、可靠且可扩展的方式收集这些心理因素的蓝图。
我们收集了2014年至2016年期间美国2891个县的推特年度面板数据,并使用一种新颖的数据挖掘技术来获取县级平均“大五”心理特征分数。然后,我们进行区间回归,使用控制函数来减轻遗漏变量偏差,以实证检验县级心理特征与各县致命阿片类药物过量流行率之间的关系。
在控制了一系列与健康结果相关的社区层面生物心理社会因素后,我们发现,在研究中于社区层面考察的五个心理特征的三个操作化指标与致命阿片类药物过量显著相关:外向性(β = 0.308,P < 0.001)、神经质(β = 0.248,P < 0.001)和尽责性(β = 0.229,P < 0.001)。
分析社区的心理特征可以成为地方、州和国家抗击阿片类药物流行的一项有价值的工具。健康提供者和社区卫生组织可以从这项研究中受益,通过评估他们所服务社区的心理概况,并根据我们的研究预测的关系,在做出关于过量逆转药物和其他重要资源分配的决策时,评估致命阿片类药物过量的预计风险。