University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA 15213, USA.
University of Pittsburgh, School of Health and Rehabilitation Sciences, Pittsburgh, PA 15219, USA.
Alcohol Alcohol. 2020 Oct 20;55(6):652-659. doi: 10.1093/alcalc/agaa061.
Given the importance of addressing provider attitudes toward individuals with unhealthy alcohol use and the current emphasis on person-centered language to help decrease stigma and mitigate negative attitudes, the aim of this study was to evaluate the psychometric properties of a contemporary version of the Alcohol and Alcohol Problems Perception Questionnaire (AAPPQ) that uses person-centered language and addresses the spectrum of alcohol use.
The authors created a person-centered version of the AAPPQ (PC-AAPPQ) and conducted a cross-sectional study of its psychometric properties in academic settings in the Northeastern United States. The PC-AAPPQ was administered to 651 nursing students. Reliability analysis of the new instrument was performed using the total sample. Only surveys with complete data (n = 637) were randomly split into two datasets, one used for the exploratory factor analysis (EFA) (n = 310) and the other for confirmatory factor analysis (CFA) (n = 327).
Compared to all the models generated from the EFA, neither the original six-factor structure nor the five-factor structure was superior to any of the other models. The results indicate that a seven-factor structure with all 30 items is the best fit for the PC-AAPPQ.
The PC-AAPPQ represents a positive effort to modernize the four-decade-old AAPPQ. This 30-item instrument, which adds one additional subscale, offers a means to assess providers' attitudes using respectful wording that avoids perpetuating negative biases and reinforces efforts to affirm the worth and dignity of the population being treated.
鉴于解决医疗服务提供者对饮酒不健康者的态度的重要性，以及当前强调使用以患者为中心的语言来帮助减少污名化和减轻负面态度的重要性，本研究旨在评估使用以患者为中心的语言并涵盖酒精使用谱的当代版酒精和酒精问题感知问卷（AAPPQ）的心理测量学特性。
作者创建了 AAPPQ 的以患者为中心的版本（PC-AAPPQ），并在美国东北部的学术环境中对其心理测量学特性进行了横断面研究。向 651 名护理学生施测了 PC-AAPPQ。使用总样本对新工具的可靠性进行了分析。仅对具有完整数据（n=637）的调查进行随机分组，一组用于探索性因素分析（EFA）（n=310），另一组用于验证性因素分析（CFA）（n=327）。
与 EFA 生成的所有模型相比，原始的六因素结构和五因素结构都没有优于任何其他模型。结果表明，具有所有 30 个项目的七因素结构是 PC-AAPPQ 的最佳拟合。
PC-AAPPQ 代表了对具有四十年历史的 AAPPQ 进行现代化的积极努力。这个包含 30 个项目的工具增加了一个额外的子量表，提供了一种使用尊重性措辞评估提供者态度的方法，避免了延续负面偏见，并加强了肯定所治疗人群的价值和尊严的努力。
