5/5 CAPER: Computerized Assessment of Psychosis Risk

摘要 研究表明，如果我们能及早识别出这些疾病的高危个体，我们或许就能 改善病程，希望能一起防止疾病发作。第一代研究 建议通过使用专门的方法来识别那些处于临床高危(CHR)的人 采访寻求帮助的人(精神病症状减轻)是一种很有希望的策略 探索与疾病进展相关的机制，了解病因，并确定新的 治疗目标。这项工作有两个主要的局限性：1)访谈方法只有有限的特异性 15-20%的慢性阻塞性肺病患者转化为精神病，以及2)诊断慢性阻塞性肺病所需的专业知识是 只有在少数几个大都市中心才能进入，需要训练有素的工作人员。在这里，我们的目标是 为新的CHR评估方法奠定基础，这将增加可获得性，并具有积极意义 预测性价值。我们建议开发一种新的精神病症状域敏感(PSDS)电池， 确定与定义精神病的症状相关的任务的优先顺序(积极利用 精神障碍-特定的过程，而不是表征脆弱的迹象)和相关的，与 与这些症状有关的神经生物学系统和计算机制。为了促进 可访问性，我们利用可以通过互联网管理的廉价行为任务；这将设置 为以后的研究测试在求助和非求助中进行广泛筛选的阶段 这将确定哪些人最需要进行深入评估。在这之前 然而，有必要确定哪些任务对预测病程是有效的 以及这种策略与第一代预测方法相比有何不同。我们建议招聘500人。 参与者，500名寻求帮助的个人，以及5个地点和目标1中的500名健康对照，制定了 PSDS电池风险计算器，基于对即将发生的转换最敏感的措施。 此外，纳入求助比较小组对于将PSDS计算器转换为 临床实践，其目标是区分那些最有可能发展成精神障碍的人 不同于其他形式的精神病理学。在目标2中，我们将比较PSD的敏感性和特异性 北美前兆研究的风险计算器 (NAPLS)风险计算器(黄金标准的第一代工具)在预测 为期2年。最后，在目标3中，这项研究将确定PSDS是否可以预测 疗程2年。预测诊断很重要，但能够提供早期干预以限制 精神病的残疾特征是优先考虑的。这个项目将回答初步的问题 下一代CHR电池所必需的，与疾病机制捆绑在一起，由尖端技术提供动力 计算方法，可用于促进精神病风险的尽可能早的检测。

Summary Research suggests that if we can identify individuals at-risk for these disorders early, we may be able to improve the course of illness and hopefully prevent illness onset all together. A first generation of studies suggest that the approach of identifying those at clinical high-risk (CHR), through the use of specialized interviews with help-seeking individuals (with attenuated psychosis symptoms) is a promising strategy for exploring mechanisms associated with illness progression, understanding etiology, and identifying new treatment targets. This work has two major limitations: 1) interview methods have limited specificity as only 15-20% of CHR individuals convert to psychosis, and 2) the expertise needed to make CHR diagnosis is only accessible in a handful of metropolitan centers, and requires extensively trained staff. Here, we aim to lay the foundation for a new approach to CHR assessment that will increase accessibility, and positive predictive value. We propose to develop a new psychosis symptom domain sensitive (PSDS) battery, prioritizing tasks that show correlations with the symptoms that define psychosis (actively tapping into psychotic disorder-specific processes, rather than to trait vulnerability signs) and relatedly, that are tied to the neurobiological systems and computational mechanisms implicated in these symptoms. To promote accessibility, we utilize inexpensive behavioral tasks that could be administered over the internet; this will set the stage for later research testing widespread screening in help-seeking as well as non-help seeking populations, that would identify those most in need of in-depth assessment. Before this can be accomplished however, it is necessary to determine which tasks are effective for predicting illness course and how this strategy compares to the first-generation prediction methods. We propose to recruit 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls across 5 sites and in Aim 1, develop a PSDS battery risk calculator based on measures that prove to be most sensitive to imminent conversion. Further, the inclusion of a help-seeking comparison group is critical for translating the PSDS calculator into clinical practice, where the goal is to differentiate those at greatest risk for developing a psychotic disorder from others forms of psychopathology. In Aim 2, we will compare the sensitivity and specificity of the PSDS risk-calculator to the North American Prodromal Study (NAPLS) risk-calculator (a gold-standard first-generation tool) in the prediction of psychosis conversion over a 2 year- period. Last, in Aim 3, the study will determine if the PSDS predicts functional outcomes over the course of 2 years. Predicting diagnosis is important but being able to provide early intervention to limit the disability characteristic of psychosis is a priority. This project will answer the preliminary questions necessary for a next-generation CHR battery, tied to illness mechanisms and powered by cutting-edge computational methods, that can be used to facilitate the earliest possible detection of psychosis risk.