Exploring benefits and ethical challenges in the rise of mHealth (mobile healthcare) technology for the common good: An analysis of mobile applications for health specialists

Panagiota Galetsi, Korina Katsaliaki and Sameer Kumar

Technovation, 2023, vol. 121, issue C

Abstract: This study reflects on proliferating ethical initiatives, with an eye on social good in the healthcare industry context while leveraging innovative digital technological infrastructures such as the use of mobile technology for health professionals. A content analysis has been conducted of the descriptions, functions, and user reviews for 168 smartphone apps addressed to health professionals which were classified based on their type regarding diagnosis and features. We used an expanded version of the Communication Privacy Management (CPM) theory to explain the ethical considerations of mHealth apps' selection based on the existing privacy and trustworthiness features, emphasizing apps that utilize smart technologies, such as artificial intelligence (AI). A future agenda is provided for the development of technologically advanced and responsible mHealth apps and their contribution to society. Disease handbook/manual and differential diagnosis are the two most frequently appearing types of mHealth apps. Privacy policy declarations are included in most apps, but a credible source is identified in less than half of the mHealth apps for medical professionals. Apps utilizing AI methods are still few, but users' comments indicate expectations for apps with more smart capabilities. This study is one of the few that offers a multi-layered analysis of the usefulness of health-diagnosis mobile apps for professionals, the ethical challenges that accompany them, and the requirements IT developers must address to increase apps’ use in everyday medical practice for better healthcare and social outcomes.

Keywords: Mobile applications; Health diagnosis; Medical professionals; Artificial intelligence (AI); Classification; Features; Data privacy; Trustworthiness; Machine learning mHealth apps (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:121:y:2023:i:c:s0166497222001456

DOI: 10.1016/j.technovation.2022.102598

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