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Data-driven health messaging: A new approach to public relations for health organizations
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Farzaneh Koohi   , Hossein Emami |
| in Communication Sciences, Islamic Azad University, Science and Research Branch Tehran, Iran |
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Abstract: (124 Views) |
Background: Promoting public health requires greater effectiveness of health messages and appropriate communication with audiences. Data-driven health messaging, also known as “content personalization” in the new literature, is a new approach in the field of public relations that, using demographic data, health records, and audience behaviors, allows for the adjustment of messages tailored to the needs and characteristics of each group or individual. The aim of this study is to analyze the models, benefits, challenges, and implementation strategies of data-driven health messaging (or content personalization) in public relations of health organizations in Iran.
Method: This study was conducted with a descriptive-analytical approach based on a review of documentary sources and examined data-driven, interaction-driven, and audience-driven messaging models.
Findings: The findings show that the successful implementation of data-driven health messaging requires the development of technological infrastructure, the development of legal frameworks, and the enhancement of human resource skills. Despite their high potential for effectiveness, data-driven models are mainly in the long term due to infrastructural and legal barriers in Iran. The interaction-driven model is suitable for a medium-term transition, and the audience-driven model is a good starting point due to its simplicity and rapid implementation.
Conclusion: By providing the possibility of sending targeted messages tailored to the needs of the audience, data-driven health messaging (or content personalization) is a practical and forward-looking approach to promoting public health, the realization of which requires coordination between technological development, regulation, and human resource training. |
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| Keywords: Artificial Intelligence, Digital Health, Medical Informatics, Public Health. |
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Full-Text [PDF 601 kb]
(40 Downloads)
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Letter: Original Article |
Subject:
General
Received: 2025/05/25 | Accepted: 2025/06/21 | ePublished ahead of print: 2025/06/21 | Published: 2025/07/23
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