可以使用不同的PROMIS域项目集来测量PROPr
Christoph Paul Klapproth1, Felix Fischer2, Annika Doehmen2
1Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, Berlin 10117, Germany.
不同的项目子集可以估计患者报告结果测量信息系统 (PROMIS) 偏好评分 (PROPr). 将每个域减少到2个项目平均不会显著改变PROPr估计,支持灵活的PROPr计算.
科学领域:
- 健康 结果 研究 研究 结果
- 心理测量 心理测量 心理测量
- 项目响应理论 (IRT)
背景情况:
- 患者报告结果测量信息系统 (PROMIS) 偏好评分 (PROPr) 源自PROMIS框架内的健康评估.
- 项目响应理论 (IRT) 允许使用各种项目子集测量PROMIS健康领域.
- 这项研究调查了PROPr是否也可以使用不同的项目子集准确估计.
研究的目的:
- 通过实证和计算来测试假设,PROPr可以从不同的项目子集中估计.
- 评估使用不同数量的项目对PROPr估计准确性和一致性的影响.
- 为了确定一个减少的项目集 (2项) 是否足够地表示完整的PROPr分数.
主要方法:
- 经验分析:在199名癌症患者中,从3项子集 (4,2项和10项) 中估计的PROMIS疼痛推断 (PI) 评分.
- 统计比较:使用了类内相关系数 (ICC) 和布兰德-阿尔特曼 (B-A) 图表来评估分数估计之间的差异和一致性.
- 模拟:使用IRT模拟项目响应,将模拟项目库的PROPr估计与实证结果进行比较.
主要成果:
- 经验性比较显示,PROPr的偏差较小,一致性较高 (ICC>0.98),估计从4对10项相比,4对2项.
- 模拟结果显示,使用2个项目 (PROPr_sim) 时,与4个项目 (PROPr_4) 相比,PROPr_4的平均PROPr略有增加,一致性很好 (ICC = 0.95).
- 经验和模拟方法都表明,不同的项目子集产生可比的PROPr估计,在使用更少的项目时偏差最小.
结论:
- 该研究证实,不同的项目子集可以有效地估计PROMIS PI用于PROPr计算.
- 将项目设置缩减为每个域的2个项目并不会显著改变平均PROPr估计.
- 虽然平均估计是相似的,但协议是不同的,强调需要考虑个人比较和整个分数的范围.
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