Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL, USA.
Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL, USA.
Drug Alcohol Depend. 2023 Mar 1;244:109782. doi: 10.1016/j.drugalcdep.2023.109782. Epub 2023 Jan 20.
Opioid use has been increasing at alarming rates over the past 15 years, yet uptake of medication for opioid use disorder (MOUD) remains low. Much of the research on individual characteristics predicting MOUD uptake is equivocal, and there is a dearth of research on setting-level and network-level characteristics that predict MOUD uptake. Towards a more holistic, multilevel understanding, we explore individual-level, network-level, and community-level characteristics associated with MOUD uptake.
Baseline data from a longitudinal study of young people who inject drugs and their injection and support network members living in Chicago (N = 165) was used to conduct cross-sectional multilevel logistic regression analyses to examine associations between MOUD uptake and a set of potential predictors at the individual-, network-, and community-levels that were chosen based on theoretical relevance or support from previous empirical studies.
Stigma at both the individual and community levels was significantly associated with MOUD uptake (though in different directions). Greater individual-level stigma was associated with a higher likelihood of MOUD uptake, while having a more normatively stigmatizing community environment was associated with a lower likelihood of MOUD uptake. Using heroin and cocaine simultaneously and having a larger support network were associated with a greater likelihood of MOUD uptake.
The present study's holistic, multilevel approach identified three individual-level characteristics, one network-level characteristic, and one community-level characteristic associated with MOUD uptake. However, more research is needed examining multilevel predictors, to help with developing interventions addressing barriers to MOUD use at multiple levels of influence.
在过去的 15 年中,阿片类药物的使用呈惊人的速度增长,但阿片类药物使用障碍(MOUD)的药物治疗使用率仍然很低。大量关于预测 MOUD 使用率的个体特征的研究结果存在争议,而且关于预测 MOUD 使用率的设置水平和网络水平特征的研究也很少。为了更全面、多层次地了解这一问题,我们探讨了与 MOUD 使用率相关的个体水平、网络水平和社区水平特征。
利用一项针对居住在芝加哥的注射毒品的年轻人及其注射和支持网络成员的纵向研究的基线数据(N=165),进行横断面多层次逻辑回归分析,以检验 MOUD 使用率与个体、网络和社区层面的一组潜在预测因素之间的关联,这些因素是根据理论相关性或以往实证研究的支持而选择的。
个体和社区层面的污名与 MOUD 使用率显著相关(尽管方向不同)。个体层面的污名程度越高,接受 MOUD 治疗的可能性就越大,而社区环境的规范污名化程度越高,接受 MOUD 治疗的可能性就越小。同时使用海洛因和可卡因以及拥有更大的支持网络与接受 MOUD 治疗的可能性更大相关。
本研究的整体、多层次方法确定了三个个体特征、一个网络特征和一个社区特征与 MOUD 使用率相关。然而,需要更多的研究来检验多层次的预测因素,以帮助开发针对多个影响层面的 MOUD 使用障碍的干预措施。