Computer Automation of Mental Health Measurement, Diagnosis and Therapy

心理健康测量、诊断和治疗的计算机自动化

• 批准号: RGPIN-2019-04395
• 负责人: Rose, Jonathan
• 金额: $ 4.01万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714796
• 关键词: Computer; Automation; Mental; Health; Measurement

We have entered an era in which the knowledge and expertise of medical professionals can begin to be automated through innovations in computer software and hardware. The long-term vision of this research is the creation of an all-software replacement for medical diagnosis and treatment. Such technology would contribute to a significant reduction in suffering and the effects of poverty in the world. In the proposed research, we attempt to take the first steps of research and development on tools and interventions that aid in the solution of existing medical problems. Our strategy is to collaborate with like-minded medical professionals who are also researchers, and find ways to automate aspects of measurement, diagnosis and therapy with their expert assistance. One of the most under-served areas of medicine that could benefit the most from the helping hand' of computer automation is mental health diagnosis and therapy. This is motivated by the grossly insufficient number of Psychiatrists in this country available to deal with the high incidence of mental health disorders. This proposal describes several projects on monitoring, diagnosis and therapy for mental health conditions. The first project explores a method of tracking a patient's mental health state, using data generated from their smartphone. The goal is to infer, from that data, the severity of a mental health disorder such as social anxiety, generalized anxiety, depression or bipolar disorder. Such tracking could enable the prevention of such episodes from worsening, and to help determine, much more quickly, the efficacy of drug or psychotherapy treatments. This project has begun, with a collaborator who is both a clinician and research Psychiatrist. We have developed a mobile application that provides many streams of data from the patient-owner of the smartphone. This work has already raised many questions on the algorithmic and clinical side, as well as issues in data privacy, that must be answered or solved to be able to infer mental health state from smartphone data. A second major project concerns addiction, which often goes hand-in-hand with mental health issues. One common addiction is tobacco smoking, and we collaborate with a nicotine addiction clinician/researcher. We propose the development of a chatbot' (a computer that speaks to humans) that uses known-good clinical techniques to help a smoker make the decision to quit. This is motivated by the fact that 94% of all current smokers are ambivalent about quitting, and need to make this decision before they will be in any way motivated to try to quit. The full proposed research program has several other projects, including one to measure a psychometric through game play, another to help children on the autism spectrum plan structured playdates, another to help people quit smoking once they've taken the decision to do so, and a final one to automate a measurement of cognition.

我们已经进入了一个时代，在这个时代里，医疗专业人员的知识和专长可以开始通过计算机软件和硬件的创新而自动化。 这项研究的长期愿景是为医疗诊断和治疗创造一个全软件替代品。 这种技术将有助于大大减少世界上的痛苦和贫穷的影响。 在拟议的研究中，我们试图采取研究和开发工具和干预措施的第一步，以帮助解决现有的医疗问题。 我们的策略是与志同道合的医学专业人士合作，他们也是研究人员，并在他们的专家帮助下找到自动化测量，诊断和治疗的方法。 其中一个服务最少的医学领域，可以受益最大的帮助之手“的计算机自动化是心理健康诊断和治疗。 这是由于该国精神科医生人数严重不足，无法处理精神健康障碍的高发率。 该提案介绍了关于监测、诊断和治疗精神健康状况的几个项目。 第一个项目探索了一种使用智能手机生成的数据跟踪患者心理健康状态的方法。 目标是从这些数据中推断出心理健康障碍的严重程度，如社交焦虑、广泛性焦虑、抑郁或双相情感障碍。 这种跟踪可以防止此类事件恶化，并有助于更快地确定药物或心理治疗的疗效。 这个项目已经开始，与一位既是临床医生又是研究精神病学家的合作者。我们开发了一个移动的应用程序，可提供来自智能手机患者所有者的许多数据流。 这项工作已经在算法和临床方面提出了许多问题，以及数据隐私方面的问题，这些问题必须得到回答或解决，才能从智能手机数据中推断出心理健康状态。 第二个主要项目涉及成瘾，这往往与心理健康问题密切相关。 一种常见的成瘾是吸烟，我们与尼古丁成瘾临床医生/研究人员合作。 我们建议开发一种聊天机器人（一种与人类交谈的计算机），它使用已知的良好临床技术来帮助吸烟者做出戒烟的决定。 这是因为94%的吸烟者对戒烟的态度是矛盾的，他们需要在戒烟之前做出决定。 完整的拟议研究计划还有其他几个项目，包括一个通过游戏来测量心理测量，另一个帮助自闭症谱系障碍儿童计划结构化的游戏日期，另一个帮助人们戒烟，一旦他们决定这样做，最后一个是自动测量认知。