Optimizing Engagement in Digital Mental Health Services among Sexual and Gender Minority Consumers

优化性少数群体消费者对数字心理健康服务的参与

基本信息

批准号：
10738476
负责人：
Meghan Romanelli
金额：
$ 13.84万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-21 至 2027-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10738476
关键词：
Address Adult Advocacy Affective Anxiety Behavioral Caring Characteristics Cognitive Communities Data Analyses Data Analytics Development Discrimination Distal Ethnic Origin Evaluation Expectancy Experimental Designs Feedback Focus Groups Funding Future Gender Identity Goals Health Health Resources Health Services Health Services Accessibility Health Services Research Health behavior change Healthcare Heterogeneity Heterosexuals Improve Access Informatics Infrastructure Internet Intervention K-Series Research Career Programs Mental Depression Mental Health Mental Health Services Mental health promotion Metadata Methodology Methods Modeling Names National Institute of Mental Health Outcome Pattern Personal Satisfaction Population Positioning Attribute Principal Investigator Process Public Health Race Reporting Research Research Support Route Safety Sampling Self Direction Services Sex Orientation Sexual and Gender Minorities Sexual and Gender Minority Youth Shapes Social Work Source Strategic Planning Subgroup Support Groups Symptoms Technology Testing Therapeutic Training Universities Washington analytical method barrier to care big data management care preference career cisgender data integration design digital intervention digital mental health evidence base experience feasibility testing gender minority group gender minority health health care availability health disparity health equity health equity promotion health goals help-seeking behavior human centered design improved innovation insight marginalized population member peer preference professor prototype psychoeducation psychoeducational randomized trial screening self reliance service delivery sexual identity supervised learning theories tool trial design

项目摘要

PROJECT SUMMARY Sexual and gender minority (SGM) populations are disproportionately impacted by mental health concerns relative to their heterosexual and cisgender peers. SGM populations, however, continue to report unmet mental health needs because they cannot or do not access mental health services. Digital Mental Health (DMH) has been recognized as a feasible, economical, and effective approach to broaden the availability of mental health care to consumers who face barriers to mental health help-seeking. SGM consumers cite a preference for DMH resources, and this delivery format holds promise to attend to major access barriers experienced by this consumer group. Yet, the availability of DMH content tailored to the needs of SGM consumers is limited, and a dearth of research examines SGM populations' actual engagement with DMH services. A potential solution to fully understand how SGM populations utilize DMH services would be to characterize their engagement within a natural setting. Leveraging an established partnership with Mental Health America (MHA), a non-profit mental health advocacy group offering free, evidence-based screenings and self-guided DMH resources, this study will follow a large, naturalistic sample of SGM DMH consumers with the aims to: 1) characterize consumers' current and predictive patterns of engagement with MHA's DMH resources and examine consumer characteristics associated with these different engagement patterns (Aim 1); 2) employ human-centered design approaches to gain insights related to group-specific processes not captured by MHA's meta-data that impact DMH engagement among SGM consumers and integrate data to design and build prototype engagement strategies for consumer evaluation (Aim 2), and; 3) test the tailored engagement strategies with MHA's SGM consumers using a micro-randomized trial (MRT) design (Aim 3). To accomplish these aims and prepare for a larger R01 trial, the Principal Investigator will receive training in: 1) the theoretical, substantive, and methodological underpinnings of DMH; 2) big data management and analytic methods, specifically supervised machine learning; 3) human-centered design approaches for designing tailored DMH interventions, and; 4) experimental design and data analysis for evaluating adaptive DMH interventions. The candidate is an Assistant Professor of Social Work at the University of Washington whose long-term career goal is to become an expert in the field of mental health services research, specializing in digital interventions to improve service access for SGM consumers through increased availability and enhanced acceptability. The proposed study advances this objective by aligning with the care preferences of SGM consumers, leveraging the infrastructure of an existing DMH platform at minimal burden to consumers, and contributing evidence towards optimized engagement outcomes for SGM consumers through the use of tailored strategies.

项目概要性少数群体 (SGM) 群体受到心理健康问题的影响尤为严重相对于异性恋和顺性别同龄人。然而，SGM 人群继续报告心理未得到满足健康需求，因为他们不能或不获得心理健康服务。数字心理健康 (DMH) 被认为是扩大心理健康服务的可行、经济且有效的方法照顾面临心理健康寻求帮助障碍的消费者。 SGM 消费者表示偏爱 DMH 资源，并且这种交付格式有望解决此过程中遇到的主要访问障碍消费群体。然而，针对 SGM 消费者需求量身定制的 DMH 内容有限，并且缺乏调查 SGM 人群实际参与 DMH 服务的研究。一个潜在的解决方案充分了解 SGM 人群如何利用 DMH 服务来描述他们在自然环境。利用与非盈利性心理健康组织 Mental Health America (MHA) 建立的合作伙伴关系健康倡导团体提供免费、基于证据的筛查和自我指导的 DMH 资源，这项研究将跟踪 SGM DMH 消费者的大量自然样本，目的是：1) 描述消费者当前的特征与 MHA 的 DMH 资源的互动和预测模式，并检查消费者特征与这些不同的参与模式相关（目标 1）； 2）采用以人为本的设计方法获得与影响 DMH 的 MHA 元数据未捕获的特定群体流程相关的见解 SGM消费者参与并整合数据来设计和构建原型参与策略用于消费者评估（目标 2），以及； 3) 与 MHA 的 SGM 消费者测试定制的参与策略使用微随机试验 (MRT) 设计（目标 3）。为了实现这些目标并为更大的 R01 做好准备试验期间，首席研究员将接受以下方面的培训： 1) 理论、实质性和方法论 DMH 的基础； 2）大数据管理和分析方法，特别是监督机器学习； 3) 以人为本的设计方法，用于设计量身定制的 DMH 干预措施； 4）实验设计以及用于评估适应性 DMH 干预措施的数据分析。该候选人是社会学助理教授在华盛顿大学工作，其长期职业目标是成为心理领域的专家健康服务研究，专注于数字干预，以改善 SGM 消费者的服务获取通过增加可用性和增强可接受性。拟议的研究通过以下方式推进了这一目标结合 SGM 消费者的护理偏好，利用现有 DMH 平台的基础设施以最小的消费者负担，为 SGM 优化参与结果提供证据消费者通过使用量身定制的策略。