Ingram School of Nursing, McGill University, Montreal, Canada.
St. Mary's Research Centre, Montreal, Canada.
Qual Life Res. 2021 May;30(5):1503-1512. doi: 10.1007/s11136-020-02750-9. Epub 2021 Jan 25.
The PACIC assesses key components of the Chronic Care Model. The purpose of this study is to examine the dimensionality and psychometric properties of the PACIC.
A convenience sample of 221 adults in Canada who self-identified as living with one or more physical and/or mental chronic diseases was invited to participate via an online survey link. Rasch analysis was performed, including item and person misfit, reliability, response format, targeting, unidimensionality of subscales, and differential item functioning (DIF). Also, Confirmatory Factor Analysis (CFA) was conducted and model fit of alternative factor structures proposed for the PACIC in the literature and those suggested by the Rasch analysis were explored.
The patient activation, delivery system, and problem-solving subscales fit the Rasch model expectations; no modifications were required. The goal setting item 10 had a disordered threshold and was recoded. Four of the five follow-up subscale items had a disordered threshold and were recoded. All subscales were unidimensional and no local dependency was detected. DIF was only detected for some items in the follow-up subscale. The CFA revealed that none of the published factor structures fit the data; the fit statistics were appropriate when item 10 was removed and the follow-up subscale was removed.
Improving chronic disease care relies upon having validated measures to evaluate the extent to which care goals are met. With some modifications, four of the five PACIC subscales were found to be psychometrically robust.
PACIC 评估慢性护理模型的关键组成部分。本研究的目的是检验 PACIC 的维度和心理测量特性。
通过在线调查链接邀请了 221 名加拿大成年人参与,这些成年人自我认定患有一种或多种身体和/或精神慢性病。进行了 Rasch 分析,包括项目和人员不匹配、可靠性、响应格式、目标、子量表的单维性和差异项目功能(DIF)。此外,还进行了验证性因素分析(CFA),并探讨了文献中提出的 PACIC 的替代因素结构以及 Rasch 分析建议的因素结构的模型拟合。
患者激活、传递系统和解决问题子量表符合 Rasch 模型的预期;不需要进行修改。目标设定项目 10 的阈值存在紊乱,需要重新编码。五个随访子量表中的四个项目的阈值存在紊乱,需要重新编码。所有子量表均为单维,未检测到局部依赖。仅在随访子量表的某些项目中检测到 DIF。CFA 显示,没有一种已发表的因素结构适合数据;当删除项目 10 和随访子量表时,拟合统计数据是合适的。
改善慢性病护理依赖于具有验证性的衡量标准,以评估护理目标的实现程度。经过一些修改,PACIC 的五个子量表中有四个具有良好的心理测量学特性。