期刊
JOURNAL OF PSYCHIATRIC RESEARCH
卷 138, 期 -, 页码 404-412出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jpsychires.2021.04.020
关键词
Neurological soft signs; Content analysis; Rating scales; Symptom overlap; Schizophrenia
类别
The study revealed a low overlap between different assessment tools for neurological soft signs, which limits reproducibility and hinders the unification of knowledge from existing data. The diversity in NSS assessment tools suggests the need for further research on the non-localizable nature of NSS.
Introduction: Neurological soft signs (NSS) are described as subtle, non-localizable neurological abnormalities that cannot be related to impairment of a specific brain region or are not believed to be typical for any specific neurological disease. Crucial issue concerning research on NSS are the instruments with which they are assessed, since the results and the conclusions of the studies are mediated by the characteristics of such instruments. There is common, silent and unverified assumption that NSS rating scales may be used as interchangeable measure of the same phenomenon.& nbsp; Aim: To investigate the differences in item content and the interchangeability of commonly used NSS scales. Methods: A content analysis was carried out to determine symptom overlap among the chosen seven most often used scales using the Jaccard index (0 = no overlap, 1 = full overlap) according to the methodology of Fried 2017.& nbsp; Results: 71 NSSs were distinguished from 167 items used in 7 above mentioned instruments. Mean overlap among all scales is low (0.27), overlap among specific scales ranges from 0.1 to 0.5.& nbsp; Conclusions: The diversity of NSS in analyzed tools causes the low overlap between scales, leading to uncertainty as to whether they measure the same phenomena. This limits the reproducibility of studies and impedes the possibility of unifying the knowledge stemming from existing data. We argue that the non-localizable nature of NSS is yet to be examined.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据