Why Reviewing Apps Is Not Enough: Transparency for Trust (T4T) Principles of Responsible Health App Marketplaces

Abstract

The overselling of health apps that may provide little benefit and even harm needs the health community’s immediate attention. With little formal regulation, a light-touch approach to consumer protection is now warranted to give customers a modicum of information to help them choose from the vast array of so-called health apps. We suggest 4 guiding principles that should be adopted to provide the consumer with information that can guide their choice at the point of download. We call these the Transparency for Trust (T4T) principles, which are derived from experimental studies, systematic reviews, and reports of patient concerns. The T4T principles are (1) privacy and data security, (2) development characteristics, (3) feasibility data, and (4) benefits. All our questions are in a simple form so that all consumers can understand them. We suggest that app stores should take responsibility for providing this information and store it with any app marketed as a health app. Even the absence of information would provide consumers with some understanding and fuel their choice. This would also provide some commercial impetus for app developers to consider this requested information from the outset.

Responsible AI—Two Frameworks for Ethical Design Practice

“…A number of quality frameworks and guidelines have been developed by multidisciplinary groups of researchers and these can be applied as a basic foundation for more responsible design. For example, the transparency for trust principles [68] includes questions around privacy and data security, development characteristics, feasibility, and health benefits, and their creators advocate that all apps should be required to provide information relating to these four principles at minimum. More specific to mental health, the Psyberguide, developed by mental health professionals, bases its ratings on criteria for credibility, user experience, and transparency [46] while the American Psychiatric Association has an app evaluation model for psychiatrists [69].…”

“…1) Practical Strategies for Explicability: Quality frameworks for digital health provide a valuable starting point for applying principles of transparency and accountability. For example, The Transparency for Trust Principles [68] require standard information to be communicated to users in understandable ways, including information around privacy, data security, development characteristics, feasibility, and health benefits. The Psyberguide [46] bases ratings on transparency as well, so examples of technologies that meet the transparency criteria provide models for practical approaches to implementation.…”

Towards the Design of Ethical Standards Related to Digital Mental Health and all Its Applications

“…Other digital technologies may be blended with traditional care and, if so, clinicians need to be trained to integrate technology effectively into their work. 4. Regulators and governments.…”

Security and Privacy of mHealth Applications: A Scoping Review

“…7 Some of the papers are included in multiple categories due to an overlap in contributions 8 4 of those papers (4/37) were defined as models Next, we discuss the health conditions covered in the included papers, followed by the privacy and security regulations that they refer to. [6], [8], [17], [22], [23], [27], [41], [51]- [68] General focus (n=18) [2], [21], [24] [3], [4], [12], [76], [80], [81], [92], [96]- [110] S/P focused design features and recommendations (n=16) [7], [25], [28], [51], [54], [57], [59], [66], [93]- [95], [111]- [114] 1) Target health conditions…”

“…Furthermore, the generation of large amounts of new personal patient data increases the significance and severity of security and privacy risks. Vulnerabilities regarding privacy and security may result in breaching the confidentiality of consumers' data [6], which can lead to financial losses, discrimination, stress, dissatisfaction [23], or even delays in seeking effective treatment due to perceived privacy risks [24], [25]. The current situation is alarming, as recent studies report on privacy violations being a common occurrence with health and wellbeing (HWB) applications [26], [27].…”