Abstract

Objective: Popular medical articles often describe emerging technologies in abstract, feature-driven terms that fail to engage readers personally. This communication gap may contribute to skepticism and slow adoption of innovations such as Remote Patient Monitoring (RPM). The objective of this conceptual study is to present a novel communication framework that integrates Mind Genomics and Artificial Intelligence (AI) to transform technical descriptions into more relatable, human-centered narratives.
Materials and Methods: The study follows the structural logic of the Mind Genomics experimental design, which organizes complex topics into structured combinations of questions and message elements. An AI-driven simulation was used to model potential response combinations related to RPM, generating 256 possible patterns across trust, data sharing, and perceived health outcomes. Following the regression-based segmentation principles of Mind Genomics, the simulation grouped response patterns into psychologically coherent mind-sets. The present work represents a conceptual, AI-simulated application of the methodology rather than a live participant experiment.
Results: Three distinct mind-sets emerged from the AI simulation: Tech Enthusiasts, who express strong acceptance and trust; Cautious Explorers, who seek reassurance and evidence; and Skeptics, who express concern regarding privacy, accuracy, and loss of human interaction. To enhance intuitive understanding, these segments were further illustrated through a “Fly on the Wall” conversational rendering. A sixteen-pattern response mapping model was also developed to translate segmentation into an accessible reader-participation framework.
Discussion: The findings suggest that attitudes toward medical innovation cluster into identifiable psychological orientations rather than forming a uniform response. By applying AI to simulate Mind Genomics segmentation, this approach demonstrates a scalable strategy for anticipating barriers and facilitators of technology communication.
Conclusion: Integrating Mind Genomics with AI offers a structured method for bridging clinical science and human experience. Even in simulated form, this framework provides a practical model for designing medical technology narratives that are psychologically informed, relatable, and potentially more effective in supporting informed adoption.
Keywords: Mind Genomics; Artificial Intelligence; Remote Patient Monitoring; Patient-Centered Communication; Psychological Segmentation; Technology Adoption.

References

1. Kelly, C.J., Karthikesalingam, A., Suleyman, M., Corrado, G. and King, D (2019). Key challenges for delivering clinical impact with artificial intelligence. npj Digit. Med. 2: 162.
2. Street, R.L., Makoul, G., Arora, N.K. and Epstein, R.M (2009). How does communication heal? Pathways linking clinician–patient communication to health outcomes. Patient Educ. Couns. 74: 295-301.
3. Kruse, C.S., Krowski, N., Rodriguez, B., Tran, L., Hyde, J., Zhou, Y. et al (2017). Telehealth and patient satisfaction: a systematic review and narrative analysis. BMJ Open. 7: e016242.
4. Moskowitz, H.R (2012). 'Mind Genomics': The experimental, inductive science of the ordinary. Sens. Stud. 27: 347-374.
5. Moskowitz, H.R (2024). Mind Genomics: Methodology and experimental design. Mind Genomics Institute.
6. Topol, E.J (2019). High-performance medicine: the convergence of human and artificial intelligence. Med. 25: 44-56.
7. Chen, J.H. and Asch, S.M (2017). Machine Learning and Health Systems: The Importance of a Human-In-The-Loop. Gen. Intern. Med. 32: 1233-1241.