Technology access, use, socioeconomic status, and healthcare disparities among African Americans in the US
Bibliographic Data
| ID | 22072075 |
|---|---|
| Authors | Ebenezer Larnyo (0000-0001-5837-0707, University of California, Santa Barbara, corresponding author), Sharon Tettegah (0000-0002-5468-9216, University of California, Santa Barbara), Jonathan Aseye Nutakor (0000-0002-6294-2701, Jiangsu University), Stephen Addai‐Dansoh (0000-0002-4070-6273, Jiangsu University), Stephen Addai-Dansoh, Francisca Arboh (0000-0003-4385-341X, Teesside University) |
| Year | 2025 |
| Volume | 13 |
| Pages | 1547189-1547189 |
| Publication date | 2025-05-28 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2025.1547189 |
| PMID | 40503485 |
| OpenAlex | W4410823388 |
| Language | EN |
| References cited | 62 |
Background Healthcare disparities remain a significant challenge in addressing equitable healthcare access and outcomes for minority populations, including African Americans. Rooted in systemic racism and historical exclusion, these inequities persist as part of broader structural violence. Leveraging health technology holds promise in addressing these disparities by enhancing access to care, improving its quality, and reducing inequities. However, the association between health technology access, use, socioeconomic status (SES), and healthcare disparities among African Americans remains underexplored. This study aims to explore the potential role of technology in mitigating healthcare disparities by investigating the associations between technology access, healthcare technology use, socioeconomic status (SES), and health disparities among African Americans. Methods Using data from the Health Information National Trends Survey (HINTS) Wave 6 dataset, a sample of 815 African Americans was analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). Findings The results of the study showed that technology access had a significant positive effect on healthcare technology use ( β = 0.260, p < 0.000). Technology access ( β = −0.086, p = 0.034) and healthcare technology use ( β = −0.180, p < 0.001) demonstrated a significant negative effect on healthcare disparity, respectively. Results also revealed SES had a significant positive effect on technology access ( β = 0.424, p < 0.001). Additionally, SES was found to significantly moderate the relationship between technology access and healthcare disparities, indicating variability in the impact of technology access based on SES levels among African Americans. Conclusion These findings highlight the potential of technology in mitigating healthcare disparities among African Americans. By promoting enhanced health technology access and utilization, particularly in lower SES populations, the healthcare outcomes for vulnerable communities can be significantly improved. Policymakers, healthcare providers, and technology developers are encouraged to collaborate in providing conducive conditions for the adoption and use of technology to advance healthcare equity
Economic growth · Economics · Environmental health · Geography · Health care · Health equity · Population · Socioeconomic status · Electronic Health Records Systems · Healthcare Policy and Management · Medicine · Telemedicine and Telehealth Implementation · Gerontology
The Health Information National Trends Survey (HINTS)
An empirical comparison of the efficacy of covariance-based and variance-based SEM
Trends in the Use of Telehealth During the Emergence of the Covid-19 Pandemic — United States, January–March 2020
The relation between students’ socioeconomic status and ICT literacy
Cutoff criteria for fit indexes in covariance structure analysis
When to use and how to report the results of PLS-SEM
Understanding uptake in demand-side broadband subsidy programs
Digital health technologies and inequalities
Internet, Phone, Mail, and Mixed‐Mode Surveys
Delayed access to HIV diagnosis and care
Approaches to Improvement of Digital Health Literacy (eHL) in the Context of Person-Centered Care
The impact of health information technology on disparity of process of care
Parental health literacy and health knowledge, behaviours and outcomes in children
The Expanding Digital Divide
Determinants of broadband access and affordability
Do wealth disparities contribute to health disparities within racial/ethnic groups
Role of Health Information Technology in Addressing Health Disparities
Systemic And Structural Racism
Principles and Practice of Structural Equation Modeling
Rethinking Racism
The effects of social adversity, discrimination, and health risk behaviors on the accelerated aging of African Americans
What Is to Be Done
Understanding Racial-ethnic Disparities in Health
| Citation velocity | historical |
|---|---|
| Highly cited | No |