Current approaches to monitoring patients' mental status rely heavily on self-reported symptomatology, clinician observation, and self-rated symptom scales. The limitations inherent in these methodologies have implications for the accuracy of diagnosis, treatment planning, and prognosis. Certain populations are particularly affected by these limitations because of their unique situations, including criminal forensic patients, who have a history of both criminal behavior and mental disorder, and experience increased stigma and restrictions in their access to mental health care. This population may benefit particularly from recent developments in technology and the growing use of mobile devices and sensors to collect behavioral information via passive monitoring. These technologies offer objective parameters that correlate with mental health status and create an opportunity to use Big Data and machine learning to refine diagnosis and predict behavior in a way that represents a marked shift from current practices. This article reviews the approaches to and limitations of psychiatric assessment and contrasts this with the promise of these new technologies. It then discusses the ethics concerns associated with these technologies and explores their potential relevance to criminal forensic psychiatry and the broader implications they carry for health and criminal justice policy.

中文翻译：

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被动监测法医人口的心理健康状况。

当前监测患者心理状态的方法在很大程度上取决于自我报告的症状，临床医生的观察以及自我评估的症状量表。这些方法固有的局限性影响了诊断，治疗计划和预后的准确性。某些人群由于其独特的情况而特别受到这些限制的影响，其中包括既有犯罪行为又有精神疾病史的法医患者，他们在获得精神卫生保健方面受到的耻辱和限制增加。该人群可能特别受益于技术的最新发展以及移动设备和传感器通过被动监视收集行为信息的日益增长的使用。这些技术提供了与心理健康状况相关的客观参数，并提供了使用大数据和机器学习来细化诊断和预测行为的机会，这代表了与当前实践的明显转变。本文回顾了精神病学评估的方法和局限性，并将其与这些新技术的前景进行了对比。然后，讨论了与这些技术相关的伦理问题，并探讨了它们与刑事法医精神病学的潜在相关性以及它们对健康和刑事司法政策的广泛影响。本文回顾了精神病学评估的方法和局限性，并将其与这些新技术的前景进行了对比。然后，讨论了与这些技术相关的伦理问题，并探讨了它们与刑事法医精神病学的潜在相关性以及它们对健康和刑事司法政策的广泛影响。本文回顾了精神病学评估的方法和局限性，并将其与这些新技术的前景进行了对比。然后，讨论了与这些技术相关的道德问题，并探讨了它们与刑事法医精神病学的潜在相关性以及它们对健康和刑事司法政策的广泛影响。