在一般人群中使用在线筛查来发现处于精神病临床高风险的参与者。
Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis.
机构信息
Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
出版信息
Schizophr Bull. 2019 Apr 25;45(3):600-609. doi: 10.1093/schbul/sby069.
INTRODUCTION
Identification of participants at clinical high-risk (CHR) for the development of psychosis is an important objective of current preventive efforts in mental health research. However, the utility of using web-based screening approaches to detect CHR participants at the population level has not been investigated.
METHODS
We tested a web-based screening approach to identify CHR individuals. Potential participants were invited to a website via e-mail invitations, flyers, and invitation letters involving both the general population and mental health services. Two thousand two hundred seventy-nine participants completed the 16-item version of the prodromal questionnaire (PQ-16) and a 9-item questionnaire of perceptual and cognitive aberrations (PCA) for the assessment of basic symptoms (BS) online. 52.3% of participants met a priori cut-off criteria for the PQ and 73.6% for PCA items online. One thousand seven hundred eighty-seven participants were invited for a clinical interview and n = 356 interviews were conducted (response rate: 19.9%) using the Comprehensive Assessment of At-Risk Mental State (CAARMS) and the Schizophrenia Proneness Interview, Adult Version (SPI-A). n = 101 CHR participants and n = 8 first-episode psychosis (FEP) were detected. ROC curve analysis revealed good to moderate sensitivity and specificity for predicting CHR status based on online results for both UHR and BS criteria (sensitivity/specificity: PQ-16 = 82%/46%; PCA = 94%/12%). Selection of a subset of 10 items from both PQ-16 and PCA lead to an improved of specificity of 57% while only marginally affecting sensitivity (81%). CHR participants were characterized by similar levels of functioning and neurocognitive deficits as clinically identified CHR groups.
CONCLUSION
These data provide evidence for the possibility to identify CHR participants through population-based web screening. This could be an important strategy for early intervention and diagnosis of psychotic disorders.
简介
识别有发展为精神病风险的临床高风险（CHR）参与者是当前精神卫生研究中预防工作的重要目标。然而，尚未研究使用基于网络的筛查方法在人群水平上检测 CHR 参与者的效用。
方法
我们测试了一种基于网络的筛查方法来识别 CHR 个体。通过电子邮件邀请、传单和包括一般人群和精神卫生服务在内的邀请信，邀请潜在参与者访问网站。2279 名参与者在线完成了 16 项前驱症状问卷（PQ-16）和 9 项感知和认知异常问卷（PCA），以评估基本症状（BS）。52.3%的参与者在线符合 PQ 的先验截止标准，73.6%的参与者在线符合 PCA 项目标准。1787 名参与者被邀请进行临床访谈，n=356 次访谈（应答率：19.9%）使用了风险精神状态全面评估（CAARMS）和成人版精神分裂症倾向访谈（SPI-A）。n=101 名 CHR 参与者和 n=8 名首发精神病（FEP）被发现。基于在线 UHR 和 BS 标准的结果，ROC 曲线分析显示出预测 CHR 状态的良好到中等敏感性和特异性（敏感性/特异性：PQ-16=82%/46%；PCA=94%/12%）。从 PQ-16 和 PCA 中选择 10 项组成的子集可将特异性提高到 57%，而仅略微影响敏感性（81%）。CHR 参与者的功能和神经认知缺陷水平与临床确定的 CHR 组相似。
结论
这些数据为通过基于人群的网络筛查识别 CHR 参与者提供了证据。这可能是早期干预和诊断精神病障碍的重要策略。
Zotero 插件