Study: Individuals Show Less Confidence in AI-Suggested Preventive Care Interventions

Study: Individuals Show Less Confidence in AI-Suggested Preventive Care Interventions

Researchers led by Nanyang Technological University, Singapore (NTU Singapore) have found that individuals show less trust in preventative care measures suggested by artificial intelligence (AI) than when the same measures are prompted by human health experts.

Preventive care measures are activities aimed at reducing health risks, such as: B. completing a health screening, increasing physical activity and receiving a vaccination.

By studying 15,000 users of a mobile health application in South Korea, researchers found that emphasizing the inclusion of a human health expert in an AI-suggested intervention could improve its acceptability and effectiveness.

These results suggest that the human element remains important even as the healthcare sector increasingly uses AI to screen, diagnose and treat patients more efficiently. The results could also help design more effective AI-powered prevention measures, the researchers said.

Assistant Professor Hyeokkoo Eric Kwon from NTU Nanyang Business School (NBS), who led the study, said: “Despite artificial intelligence's potential to deliver higher quality interventions, we found that people have less trust in health interventions suggested by AI or derived from AI alone, compared to those they believe are human-based “Our study shows that the affective human element associated with emotions and attitudes remains important even as health interventions are increasingly driven by AI, and that this technology works best when it complements rather than replaces humans.”

This study reflects NTU's efforts as part of NTU2025, the university's five-year strategic plan that addresses humanity's grand challenges such as the impact of technology on humanity. The study, conducted by NTU NBS at the intersection of business and health technology, also highlights NTU's strength and focus on interdisciplinary research.

The results were published in an article in the academic journal Production and Operations Management, co-authored with Assistant Professor Nakyung Kyung from the National University of Singapore.

Greater acceptance of human-based health interventions

To study user perceptions of preventative health measures suggested by artificial intelligence (AI) compared to those suggested by humans, the research team recruited 9,000 users of a mobile health app in South Korea.

Through the app, these users received a pop-up notification prompting them to take a certain number of steps, generated for each user via an AI algorithm. The app then measures the number of steps taken by users who have chosen this health intervention.

For 3,000 users in AI's suggested intervention group, their pop-up notification read: "AI recommends that you walk in the next seven days (personalized step goal). Would you like to participate?" Another 3,000 in the human-suggested intervention received a notification that read: "Health expert recommends that you walk in the next seven days (personalized step goal). Would you like to participate?"

A control group of 3,000 users received the neutral intervention, which made no mention of AI or a health professional.

Of the users who received the intervention suggested by the AI, 19% accepted the intervention. About 10% of this group subsequently achieved their personal step goal at the end of the week. More users in the group that received the human-suggested intervention accepted the intervention (22%) and achieved their goal (13%).

Improving the effectiveness of AI-proposed interventions

The research team then expanded their study to include two additional groups of 3,000 users of the same mobile app.

One group received an intervention that exposed the use of AI in collaboration with health experts. The other group received an intervention that explained how AI generated the interventions (see Table 1 below).

Users were more likely to accept the health intervention that showed how AI was used to complement the opinion of a health professional (27%), compared to purely AI-suggested or human-suggested interventions. 19% of this group achieved their personal step goal.

Transparency about how AI was used to generate the personalized step goal also led to a higher adoption rate (21%). Of this group, 13% achieved their goal.

Although the study was conducted in the context of health care, the researchers believe their results could also be applied in other contexts where affective trust plays a significant role, such as: B. Travel, education, legal and insurance services.

Source:

Nanyang University of Technology, Singapore

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