Evidence and Research for Action, FHI 360, Durham, NC, USA.
Global Health Institute, Duke University, Durham, NC, USA.
AIDS Behav. 2024 Dec;28(12):4005-4019. doi: 10.1007/s10461-024-04499-5. Epub 2024 Oct 1.
PrEP stigma measurement remains a challenge to the validity of studies and interventions addressing HIV prevention. It may lead to inaccurate assessment of the relationship between PrEP stigma and health outcomes such as PrEP persistence and care retention in groups experiencing HIV-related inequities. The present research explored the psychometric properties of a novel IV pre-exposure prophylaxis (PrEP) stigma scale in a cohort of racially diverse men who have sex with men (MSM). Using item response theory, analyses explored presence of differential item functioning (DIF) among Black and White respondents. Participants completed baseline surveys measuring psychosocial factors, sociodemographic factors, and PrEP stigma items. The primary analysis used a machine learning approach to assess (a) the presence of DIF; and (b) compare latent stigma between Black and White respondents, after correcting for any DIF. The model identified four out of 13 scale items as having a high probability of DIF for Black respondents, which is relatively good given that the original PrEP stigma scale was neither designed nor tested for validation comparing Black and White respondents. The DIF-adjusted latent PrEP stigma measure reveals statistically and substantially significantly higher levels of stigma for Black compared to White respondents (Diff.: 1.05 +/- 0.19). While most items performed well, findings demonstrate the importance of assessing measurement error in populations where stigma is rampant and being studied or intervened upon (and in this case, where multilevel and intersectional stigma may be present).
预防用药(PrEP)污名的衡量仍然是对研究和干预措施有效性的挑战,这些研究和干预措施旨在解决艾滋病毒预防问题。它可能导致对预防用药污名与健康结果之间关系的不准确评估,例如在经历与艾滋病毒相关的不平等的群体中,预防用药的持续使用和护理保留。本研究在一个种族多样化的男男性行为者(MSM)队列中探索了一种新的 IV 暴露前预防(PrEP)污名量表的心理计量学特性。使用项目反应理论,分析探讨了黑人和白人受访者之间是否存在差异项目功能(DIF)。参与者完成了基线调查,测量了心理社会因素、社会人口因素和预防用药污名项目。主要分析使用机器学习方法来评估:(a)是否存在 DIF;(b)在纠正任何 DIF 后,比较黑人和白人受访者之间的潜在污名。该模型确定了 13 个量表项目中的 4 个对黑人受访者有高度 DIF 的可能性,这相对较好,因为原始的预防用药污名量表既不是为了验证黑人和白人受访者之间的差异而设计的,也没有经过验证。经 DIF 调整的潜在预防用药污名测量结果显示,与白人受访者相比,黑人受访者的污名程度在统计学上和实质性上都显著更高(差异:1.05 +/- 0.19)。虽然大多数项目表现良好,但研究结果表明,在污名严重且正在研究或干预的人群中,评估测量误差非常重要(在这种情况下,可能存在多层次和交叉的污名)。