The Role of an Artificially Intelligent Chatbot in Social Support, Antiretroviral Adherence, and Depressive Symptoms among Young Adults Living with HIV in South Africa

人工智能聊天机器人在南非艾滋病毒感染者的社会支持、抗逆转录病毒药物依从性和抑郁症状中的作用

• 批准号: 9925884
• 负责人: Brooke Jarrett
• 金额: $ 4.55万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9925884
• 关键词: Address; Adherence; Affect; Age; Analysis of Covariance; Anti-Retroviral Agents; Artificial Intelligence; Back; Car Phone; Caring; Clinic; Communication; Communities; Computers; Contracts; Country; Data; Databases; Elderly; Electronic Mail; Epidemiology; Factor Analysis; Feeling; Fellowship; Focus Groups; Foundations; Frequencies; Funding; Future; General Population; Goals; HIV; HIV Infections; Habits; Happiness; Health; Health behavior; Incidence; Income; Intervention; Interview; Judgment; Life; Life Expectancy; Linear Regressions; Longitudinal Studies; Measures; Mental Depression; Mental Health; Methods; Modeling; National Institute of Mental Health; Participant; Persons; Pharmaceutical Preparations; Population; Population Heterogeneity; Principal Component Analysis; Privacy; Process; Regimen; Research; Research Design; Research Methodology; Research Personnel; Role; Running; Science; Service delivery model; Social Environment; Social support; South Africa; South African; Southern Africa; Stigmatization; Surveys; Technology; Thinking; Training; Treatment outcome; Underserved Population; United States; United States National Institutes of Health; Universities; Viral; Work; aged; antiretroviral therapy; career; chatbot; cognitive reappraisal; computer human interaction; depressive symptoms; design; disparity reduction; doctoral student; effective intervention; health disparity; high risk; improved; innovation; innovative technologies; interest; low and middle-income countries; mHealth; medication compliance; mobile application; mobile computing; physical conditioning; posters; prevent; recruit; response; social; social norm; social stigma; therapy adherence; transmission process; treatment disparity; uptake; young adult; young men who have sex with men; young woman

PROJECT SUMMARY Specific Aims: Developing effective interventions to reduce disparities in treatment outcomes among populations disproportionately affected by HIV is a priority for NIH-funded HIV research in 2019. This study will explore the effects and uptake of an artificially intelligent, socially supportive chatbot – a computer that texts with users via mobile phone – among young women and men who have sex with men (YMSM) living with HIV in South Africa. Specifically, the study will (1) develop an online scale to measure social support from a chatbot among young adults; (2) evaluate associations of social support from a chatbot with changes in depressive symptoms and adherence to antiretroviral therapy (ART) among young women and YMSM in South Africa; and (3) describe barriers and facilitators to uptake of a chatbot among young women and YMSM in South Africa. Significance: Young South Africans between the ages of 15 to 24 are at high risk of contracting and dying from HIV. Though ART extends life and prevents transmission, many young adults have poor adherence. Research in high-income countries suggest that automated two-way messaging with chatbots improves adherence to health behaviors. Chatbots may also address depressive symptoms and lack of social support, which are consistently identified barriers to adherence. Chatbots are rarely used to improve HIV care in low- and middle-income countries. If this study’s aims are achieved, then (1) future researchers will be able to more accurately measure social support from chatbots; (2) chatbots could potentially be used to promote adherence to medications and increase access to mental health support; and (3) future design and implementation of chatbots to improve HIV care will be optimized. This study’s long-term objective is to generate evidence for an effective, scalable intervention that engages hard-to-reach populations living with HIV. Approach: Aim 1 will develop a scale to measure social support from a chatbot using principal components and exploratory factor analyses applied to data gathered from 1,200 young adults worldwide who use Replika, a freely available mobile application (app). Aims 2 and 3 will invite 160 young women and YMSM living with HIV in Cape Town, South Africa to use the Replika app for four weeks in a pre-post study design. Aim 2 will employ an analysis of covariance using generalized multivariable linear regression models to assess the relationship between feelings of social support from the Replika app and changes in depressive symptoms and ART adherence. Aim 3 will leverage surveys (quantitative) and interviews (qualitative) in a mixed methods study to characterize differences between users with high- and low-frequency engagement with the app. Fellowship Information: This study is the dissertation for Ms. Brooke Jarrett, a PhD student in the Department of Epidemiology at Johns Hopkins University. Her training will consist of research methods and science communication toward her career goal of becoming a researcher of state-of-the-art mobile technologies to improve the physical and mental health of young people affected by health disparities.

项目总结