Street Experiences, Affect, and Coping: Harnessing Computational Models for the Development of a Cellphone-Based Intervention to Prevent Drug Use among Youth Experiencing Homelessness

街头经历、影响和应对：利用计算模型开发基于手机的干预措施，以防止无家可归的青少年吸毒

• 批准号: 10684264
• 负责人: KIMBERLY A TYLER
• 金额: $ 67.54万
• 依托单位: UNIVERSITY OF NEBRASKA LINCOLN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684264
• 关键词: Affect; Age Years; Alcohol consumption; Alcohols; Behavior Therapy; Cellular Phone; Collaborations; Computer Models; Coping Behavior; Data; Development; Drug usage; Ecological momentary assessment; Emotions; Face; Focus Groups; Future; General Population; Goals; Growth; HIV; Health Care Costs; Homelessness; Impulsivity; Intervention; Lifestyle-related condition; Machine Learning; Marijuana; Mediating; Mental Depression; Mental Health; National Institute of Drug Abuse; Outcome; Ownership; Personal Satisfaction; Persons; Pilot Projects; Population; Post-Traumatic Stress Disorders; Prevalence; Public Health; Regulation; Reporting; Research; Risk; Risk Factors; Role; Social Network; Stress; Substance Use Disorder; Surveys; Text Messaging; Time; Victimization; Vulnerable Populations; Work; Youth; acceptability and feasibility; adolescent substance use; computerized tools; coping; cost; design; deter alcohol use; diagnostic criteria; drinking behavior; drug abuse prevention; efficacy trial; experience; feasibility testing; intervention delivery; marijuana use; meetings; member; methamphetamine use; negative affect; observational cohort study; peer; predictive modeling; protective factors; public health research; smartphone application; substance use; therapy design; wireless fidelity; young adult

ABSTRACT Youth experiencing homelessness (YEH) face many significant risks that are detrimental to their long-term well- being and survival, including engaging in negative coping behaviors such as alcohol and drug use. 89% of YEH report lifetime alcohol use, 77% marijuana use, and 48% report methamphetamine use. Drug and alcohol use prevalence rates are 2 to 3 times higher among YEH than in their housed peers, leading to poorer mental health and HIV outcomes for this population. Proximal risk factors for substance use in YEH include street victimization: 39% and 94% have been sexually or physically victimized, respectively; poor mental health: 80% and 74% meet diagnostic criteria for PTSD and depression, respectively; and risky social networks: 62% of YEH report drug use with a network member. Another risk factor for substance is affect regulation. Studies of general population youth find that those with greater negative affect have higher rates of substance use. The role of affect regulation has rarely been examined for YEH; thus, mediating mechanisms are unclear. It is possible that proximal risk factors increase negative affect, leading to greater substance use among YEH. Understanding these linkages is key to developing predictive models of coping. This project uses a socio-ecological framework to examine linkages between Proximal risk factors, Affect regulation, and Coping behaviors. Specifically, we will identify factors that influence positive vs. negative coping behavior for YEH to develop a data-driven intervention that: 1) is relevant to this vulnerable population, and provides individualized support, and 2) can be sustainable outside the research setting. Our team has pioneered the use of cellphones for ecological momentary assessment (EMA) in public health research (Khan), and with YEH (Tyler and Olson). Increased cellphone ownership among YEH alongside growth in urban WiFi hotspot coverage together create a public health opportunity leveraged in this project's aims: 1) determine whether affect regulation mediates the relationship between YEHs’ proximal risk factors and coping behaviors, achieved by analyzing survey data and EMA data on Proximal risk factors, Affect regulation, and Coping behaviors collected via app-based responsive EMA (rEMA) in an observational cohort study of N=300 YEH over 60 days; 2) develop a data-driven app-based just-in-time personal support intervention (JIT-PSI) that delivers responsive messaging to mitigate negative coping in favor of positive coping. This aim is achieved by developing predictive models of coping behavior based on machine learning analyses of Aim 1’s survey and rEMA data; and conducting focus groups with N=30 YEH and meetings with N=15 agency staff to design intervention messaging content responsive to a range of coping behaviors; 3) test the feasibility and acceptability of the JIT-PSI, achieved by an observational cohort study of N=300 YEH over 60 days, using surveys, alongside cellphone based rEMA, and JIT intervention delivery. Leveraging growing number of public free WiFi hotspots and shrinking cellphone hardware costs, this project will yield significant public health impacts by developing a sustainable, JIT behavioral intervention for the prevention of drug use among YEH.

摘要 无家可归的青年面临着许多严重的风险，这些风险对他们的长期健康不利。 存在和生存，包括从事消极的应对行为，如酒精和药物的使用。89%的YEH 报告终生使用酒精，77%使用大麻，48%报告使用甲基苯丙胺。吸毒和酗酒 YEH患者的患病率比有住房的同龄人高2 - 3倍，导致心理健康状况较差 和艾滋病的结果。YEH中使用药物的近端风险因素包括街头受害： 分别有39%和94%的人遭受过性侵害或身体伤害;心理健康状况不佳：80%和74%的人遇到过性侵害或身体伤害。 创伤后应激障碍和抑郁症的诊断标准，分别;和危险的社交网络：62%的YEH报告药物 使用网络成员。物质的另一个风险因素是影响调节。一般人口研究 年轻人发现，那些负面情绪更大的人使用药物的比例更高。情感调节的作用 很少被检查为YEH;因此，调解机制尚不清楚。有可能近端风险 这些因素增加了负面影响，导致YEH中更多的物质使用。理解这些联系是 开发应对预测模型的关键。该项目使用社会生态框架来研究 近端风险因素、情绪调节和应对行为之间的联系。具体来说，我们将确定 影响积极与消极应对行为的因素，以便YEH制定数据驱动的干预措施：1） 与这一弱势群体相关，并提供个性化的支持，2）可以在外部持续 研究设置。我们的团队率先使用手机进行生态瞬时评估（EMA） 在公共卫生研究（汗），并与叶（泰勒和奥尔森）。YEH中的手机拥有量增加 随着城市WiFi热点覆盖率的增长， 本研究的目的是：1）确定情绪调节是否在YEH的近端风险之间起中介作用 因素和应对行为，通过分析调查数据和EMA数据的近端危险因素，影响， 在观察队列中通过基于应用程序的响应EMA（rEMA）收集的监管和应对行为 研究N=300 YEH超过60天; 2）开发基于数据驱动应用程序的即时个人支持干预 （JIT-PSI），提供响应消息，以减轻消极应对，支持积极应对。该目的是 通过基于Aim 1的机器学习分析开发应对行为的预测模型来实现 调查和rEMA数据;与N=30名YEH进行焦点小组讨论，并与N=15名机构工作人员举行会议， 设计干预消息传递内容响应一系列应对行为; 3）测试可行性， JIT-PSI的可接受性，通过N=300 YEH 60天的观察性队列研究实现，使用 调查，以及基于手机的rEMA和JIT干预交付。利用越来越多的公众 免费WiFi热点和手机硬件成本的下降，该项目将产生重大的公共卫生影响 通过制定一个可持续的，及时的行为干预，以防止毒品使用之间的青年。