Collins Kelly M, Armenta Richard F, Cuevas-Mota Jazmine, Liu Lin, Strathdee Steffanie A, Garfein Richard S
a Division of Global Public Health, School of Medicine, University of California San Diego , San Diego , California , USA.
b Division of Family Medicine and Public Health, School of Medicine, University of California San Diego , San Diego , California , USA.
Subst Abus. 2016 Oct-Dec;37(4):606-612. doi: 10.1080/08897077.2016.1176980. Epub 2016 Apr 19.
New and innovative methods of delivering interventions are needed to further reduce risky behaviors and increase overall health among persons who inject drugs (PWID). Mobile health (mHealth) interventions have potential for reaching PWID; however, little is known about mobile technology use (MTU) in this population. In this study, the authors identify patterns of MTU and identified factors associated with MTU among a cohort of PWID.
Data were collected through a longitudinal cohort study examining drug use, risk behaviors, and health status among PWID in San Diego, California. Latent class analysis (LCA) was used to define patterns of MTU (i.e., making voice calls, text messaging, and mobile Internet access). Multinomial logistic regression was then used to identify demographic characteristics, risk behaviors, and health indicators associated with mobile technology use class.
In LCA, a 4-class solution fit the data best. Class 1 was defined by low MTU (22%, n = 100); class 2, by PWID who accessed the Internet using a mobile device but did not use voice or text messaging (20%, n = 95); class 3, by primarily voice, text, and connected Internet use (17%, n = 91); and class 4, by high MTU (41%, n = 175). Compared with low MTU, high MTU class members were more likely to be younger, have higher socioeconomic status, sell drugs, and inject methamphetamine daily.
The majority of PWID in San Diego use mobile technology for voice, text, and/or Internet access, indicating that rapid uptake of mHealth interventions may be possible in this population. However, low ownership and use of mobile technology among older and/or homeless individuals will need to be considered when implementing mHealth interventions among PWID.
需要新的创新干预措施交付方法，以进一步减少注射吸毒者（PWID）的危险行为并改善其整体健康状况。移动健康（mHealth）干预措施有接触到PWID的潜力；然而，对于该人群的移动技术使用（MTU）情况知之甚少。在本研究中，作者确定了MTU模式，并在一组PWID中识别了与MTU相关的因素。
通过一项纵向队列研究收集数据，该研究调查了加利福尼亚州圣地亚哥PWID的吸毒情况、危险行为和健康状况。潜在类别分析（LCA）用于定义MTU模式（即进行语音通话、发送短信和访问移动互联网）。然后使用多项逻辑回归来识别与移动技术使用类别相关的人口统计学特征、危险行为和健康指标。
在LCA中，四类别解决方案最适合数据。类别1由低MTU定义（22%，n = 100）；类别2由使用移动设备访问互联网但不使用语音或短信的PWID组成（20%，n = 95）；类别3主要由语音、短信和联网使用组成（17%，n = 91）；类别4由高MTU组成（41%，n = 175）。与低MTU相比，高MTU类别的成员更可能较年轻、社会经济地位较高、贩卖毒品且每天注射甲基苯丙胺。
圣地亚哥的大多数PWID使用移动技术进行语音、短信和/或互联网访问，这表明在该人群中可能迅速采用mHealth干预措施。然而，在对PWID实施mHealth干预措施时，需要考虑老年和/或无家可归者中移动技术拥有率和使用率较低的情况。
