five

Item refinement using Development Sample n = 216.

收藏
Figshare2025-12-12 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Item_refinement_using_Development_Sample_n_216_/30873885
下载链接
链接失效反馈
官方服务:
资源简介:
Drug use is a highly stigmatized behavior, and drug-related stigma is a key driver of behavioral risk, lower health care utilization, and associated adverse health outcomes among people who inject drugs (PWID). While instruments exist for measuring drug-related stigma, their applicability to community-based PWID across multiple stigma types (enacted, anticipated, internalized) and settings (health care, society, family) is limited, as most were developed using treatment-based samples and all were developed in urban populations. This study sought to develop a Drug Use Stigma Scale (DUSS) that addresses these limitations. We developed an initial list of 39 items based on literature review and qualitative interviews (N = 27) and three focus groups (N = 28) with PWID recruited from syringe services programs and via peer referral in two predominantly rural West Virginia counties. The scale items were administered in a survey to 336 PWID recruited from the same two counties divided into development and validation samples. Responses to the 39-item scale went through a multidimensional refinement process, including examination of internal consistency, Confirmatory Factor Analysis (CFA), and a three-factor CFA based on stigma setting. Next, a set of final measurement CFAs were conducted. Finally, the resulting scale was examined for criterion-related concurrent validation. The final DUSS consisted of 16 items with excellent fit statistics for the development sample: SRMR: 0.03, RMSEA: 0.09, GFI: 0.92, CFI: 0.96, NFI: 0.94. Fit attenuated but remained satisfactory for the validation sample. DUSS scores were significantly associated with increased odds of not seeking healthcare when needed (OR: 1.47, p = 0.001; OR: 1.61, p
创建时间:
2025-12-12
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作