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采用离群值响应模式检查提高阳性和阴性综合征量表(PANSS)的测量效果。

Outlier-response pattern checks to improve measurement with the Positive and Negative Syndrome Scale (PANSS).

机构信息

Bar Ilan University, Ramat Gan, Israel.

Bar Ilan University, Ramat Gan, Israel.

出版信息

Psychiatry Res. 2021 Sep;303:114114. doi: 10.1016/j.psychres.2021.114114. Epub 2021 Jul 15.

Abstract

We derived outlier-response pattern checks to flag possible careless PANSS (Positive and Negative Syndrome Scale) administrations based on analysis of 122,000 administrations from 29 registration trials of antipsychotics from NEWMEDS data repository. Flags identify outlier administrations based on frequency of endorsing a given response value, use of even or odd values, consecutive use of same value, variability of values, responses per specific item, and values on multiple items. Outlier flags were compared to published expert derived scoring inconsistency flags and tested in Monte Carlo simulated data, with known inconsistency, and appear to be useful at identifying administrations that require review.

摘要

我们根据来自 NEWMEDS 数据存储库的 29 项抗精神病药物注册试验中 122,000 次的分析,得出了异常反应模式检查,以标记可能存在的粗心 PANSS(阳性和阴性综合征量表)管理。根据给定响应值的频率、使用偶数或奇数值、连续使用相同值、值的变化性、特定项目的响应数以及多个项目的值,标志可以识别异常管理。异常标志与已发表的专家推导的评分不一致标志进行了比较,并在具有已知不一致性的蒙特卡罗模拟数据中进行了测试,似乎可用于识别需要审查的管理。

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