SCH: Multidimensional Data Science Approach: Measuring and Characterizing Craving and Affective Profiles in Substance Use Disorders

SCH：多维数据科学方法：测量和表征药物使用障碍中的渴望和情感特征

• 批准号: 10816923
• 负责人: Nidal Moukaddam
• 金额: $ 30万
• 依托单位: RICE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10816923
• 关键词: Affect; Affective; Alcohols; Behavioral; Brain; Cellular Phone; Characteristics; Clinical; Clinical assessments; Cocaine; Cognitive; Coupled; Cues; Data; Data Science; Databases; Detection; Development; Dimensions; Emotional; Evidence based intervention; Functional Magnetic Resonance Imaging; Impairment; Intervention; Knowledge; Label; Laboratories; Life; Measurement; Measures; Methamphetamine; Methods; Modality; Modeling; Monitor; Neurons; Occupational; Opioid; Patients; Pattern; Persons; Pharmaceutical Preparations; Phenotype; Physiological; Pilot Projects; Psyche structure; Public Health; Relapse; Research; Running; Source; Stimulus; Substance Use Disorder; Testing; Withdrawal Symptom; addiction; behavior measurement; behavioral response; biobehavior; craving; design; digital; insight; intervention effect; machine learning model; mindfulness; multidimensional data; multidisciplinary; multimodal data; multimodality; novel; novel strategies; pharmacologic; predictive modeling; prevent; response; sensor; social; substance use; substance use treatment; wearable sensor technology

Substance use, e.g. of opioid, cocaine, methamphetamine, and alcohol, has skyrocketed in the US, and has been declared a public health crisis. Substance use disorder (SUD) leads to a significant impairment in physical, mental, social, and occupational functioning, coupled with an inability to reduce or control use and the development of tolerance and withdrawal symptoms. Like any other addiction, the precursor to substance use episodes are cravings moments, and hence, they will be opportune moments to intervene if it is possible to detect them. We have the potential to characterize patients’ conditions by combining multimodal sensor measurement in the laboratory like fMRI and clinical assessment, and field measurement via wearable and ubiquitous sensing. However, there are still many challenges to be solved to leverage these multimodal data to extract clinically useful and actionable insights. The proposed research will be executed via two aims: Aim 1) Develop a multidimensional database from patients with SUD, via laboratory brain and physiological measurements and field physiological and behavioral measurements. We will use fMRI to measure ground truth of craving responses, while recording physiological signature during craving inducing or emotional cues. We will also collect physiological and behavioral responses using mobile phones and wearable sensors in the field. We will analyze the relationships among brain-biobehavioral responses and craving and affective profiles in laboratory and field settings. Aim 2) Develop robust multimodal data science methods for craving and affective profile detection and characterization: We will design 1) new approaches that positively transfer knowledge from multiple modalities to fewer modalities: we will combine data from different sensor sources while guaranteeing the model can be run with fewer sensors during testing, 2) craving and affect profile detection using regular/irregular characteristics and sparse weak labels, 3) craving and affect detection models with unlabeled data and a limited number of noisy labels, and 4) personalized craving and affect detection models with unlabeled data. We will evaluate our proposed data science approach using the data collected previously and in non-patient and patient pilot studies.

在美国，阿片类药物、可卡因、甲基苯丙胺和酒精等物质的使用激增， 已被宣布为公共卫生危机。物质使用障碍(SUD)会导致严重的损害 在身体、精神、社交和职业功能方面，加上无法减少或控制使用 以及耐受性和戒断症状的发展。就像其他上瘾的人一样， 物质使用发作是渴望的时刻，因此，它们将是介入的时机 如果有可能检测到它们的话。我们有潜力通过结合实验室中的多模式传感器测量(如功能磁共振成像和临床评估)以及通过可穿戴和无处不在的传感进行现场测量来表征患者的病情。然而，要利用这些多模式数据提取临床上有用和可操作的见解，仍有许多挑战需要解决。拟议的研究将通过两个目标进行： 目的1)通过实验室脑和生理测量以及现场生理和行为测量，建立一个多维数据库。我们将使用功能磁共振成像来测量渴望反应的基本事实，同时记录渴望诱导或情绪暗示的生理特征。我们还将在现场使用移动电话和可穿戴传感器收集生理和行为反应。我们将在实验室和现场环境中分析大脑生物行为反应与渴望和情感特征之间的关系。 目的2)开发稳健的多模式数据科学方法，用于渴望和情感轮廓检测 我们将设计一种新的方法，将知识从多个通道积极地传递到更少的通道：我们将结合来自不同传感器来源的数据，同时保证模型在测试过程中可以用更少的传感器运行；2)使用规则/不规则特征和稀疏弱标签来渴望和影响轮廓检测；3)使用未标记数据和有限数量的噪声标签来渴望和影响检测模型；以及4)使用未标记数据来个性化渴望和影响检测模型。我们将使用之前收集的数据以及非患者和患者试点研究中的数据来评估我们建议的数据科学方法。