African American and Hispanic populations are less likely to access health and medical information through common sources/channels compared to their White counterparts. Although this information can help prevent high-prevalence diseases such as heart disease and diabetes, factors such as trust in certain sources (e.g. doctors), health literacy levels, or cultural and language preferences are known barriers to African Americans? and Hispanics? active health information seeking. Because smartphones are a ubiquitous consumer device among all races and ethnicities, the project goal is to refine and test how HealthyMe/MiSalud, an English/Spanish smartphone application (app) can support personal health libraries that bridge the gap between available but under-used health information and the people who need it. The project aims to identify how smartphone apps, data science methods, and health literacy techniques can motivate English-speaking African Americans and bilingual/Spanish-speaking Hispanics to assemble and use prevention-focused personal health libraries. Using a prototype app based on healthfinder.gov, the team will use participatory design methods to expand and refine the prototype with additional information sources, functions, and an algorithm that continually personalizes information. The app will allow users to assemble digital personal health libraries that match their health information preferences and needs. This project has three specific aims to achieve the goal of refining and testing an English and Spanish smartphone app for personalized preventive health libraries.
Aim 1 : Understand the intended users of a prevention-focused app and involve them in participatory design to refine the prototype app.
Aim 2 : Refine the prototype app so it is testable with intended users and consistent with published app requirements.
Aim 3 : Develop and assess the effectiveness of the application?s inference engine (personalized recommendation algorithms), using user interactions. A participatory design approach and select principles of community-based participatory research (CBPR) will provide direct, continuous engagement with community members during the process to develop, design, implement, and evaluate the proposed app. This project creates significant public health benefit because the app will provide new knowledge about how to use technology and data science techniques to engage African American and Hispanic populations in increased information seeking for reliable, actionable prevention information they would be unlikely to find and use otherwise. After final refinements, the app will be available in online stores for free downloads.

Public Health Relevance

African American and Hispanic populations are less likely to access health and medical information through common sources/channels compared to their White counterparts. Although this information can help prevent high-prevalence diseases such as heart disease and diabetes, factors such as trust in certain sources (e.g. doctors), health literacy levels, or cultural and language preferences are known barriers to African Americans? and Hispanics? information seeking. The proposed project aims to develop and test a smartphone application using participatory design, data science methods and health literacy techniques so that English-speaking African Americans and bilingual/Spanish-speaking Hispanics are motivated to assemble and use prevention- focused personal health libraries.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
5R01LM013039-03
Application #
9929637
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Vanbiervliet, Alan
Project Start
2018-09-18
Project End
2022-05-31
Budget Start
2020-06-01
Budget End
2021-05-31
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Maryland College Park
Department
Administration
Type
Schools of Public Health
DUNS #
790934285
City
College Park
State
MD
Country
United States
Zip Code
20742