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Psychometric Data Linking Across HIV and Substance Use Cohorts.
AIDS and Behavior ( IF 2.7 ) Pub Date : 2020-05-19 , DOI: 10.1007/s10461-020-02883-5
Benjamin D Schalet 1 , Patrick Janulis 1, 2 , Michele D Kipke 3 , Brian Mustanski 1, 2 , Steven Shoptaw 4 , Richard Moore 5 , Marianna Baum 6 , Soyeon Kim 7 , Suzanne Siminski 7 , Amy Ragsdale 8 , Pamina M Gorbach 8, 9
Affiliation  

Psychometric data linking of psychological and behavioral questionnaires can facilitate the harmonization of data across HIV and substance use cohorts. Using data from the Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO), we demonstrate how to capitalize on previous linking work with a common linked depression metric across multiple questionnaires. Cohorts were young men who have sex with men (MSM), substance-using MSM, HIV/HCV cocaine users, and HIV-positive patients. We tested for differential item functioning (DIF) by comparing C3PNO cohort data with general population data. We also fit a mixed-effects model for depression, entering HIV-status and recent opioid/heroin use as fixed effects and cohort as a random intercept. Our results suggest a minimal level of DIF between the C3PNO cohorts and general population samples. After linking, descriptive statistics show a wide range of depression score means across cohorts. Our model confirmed an expected positive relationship between substance use and depression, though contrary to expectations, no significant association with HIV status. The study reveals the likely role of cohort differences, associated patient characteristics, study designs, and administration settings.



中文翻译:


HIV 和药物使用群体之间的心理测量数据关联。



将心理和行为问卷链接起来的心理测量数据可以促进艾滋病毒和药物滥用群体数据的协调。使用来自 NIDA 机会合作联盟 (C3PNO) 的数据,我们演示了如何利用之前的关联工作与跨多个问卷的通用关联抑郁指标。队列包括男男性行为者 (MSM)、吸毒 MSM、HIV/HCV 可卡因使用者和 HIV 阳性患者。我们通过将 C3PNO 队列数据与一般人群数据进行比较来测试差异项目功能 (DIF)。我们还拟合了抑郁症的混合效应模型,进入艾滋病毒状态和最近使用阿片类药物/海洛因作为固定效应,队列作为随机拦截。我们的结果表明 C3PNO 队列和一般人群样本之间存在最低水平的 DIF。关联后,描述性统计数据显示各个队列的抑郁评分平均值存在很大差异。我们的模型证实了物质使用和抑郁之间存在预期的正相关关系,尽管与预期相反,但与艾滋病毒状况没有显着相关性。该研究揭示了队列差异、相关患者特征、研究设计和管理设置的可能作用。

更新日期:2020-05-19
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