Recent books like Richard Seymour’s “The Twittering Machine” and Shoshana Zuboff’s “The Age of Surveillance Capitalism” offer sobering accounts of the impact of over two decades of life in the internet age- they also offer paths forward. Recent events in the news point to an apparent erosion of global trust in many established institutions, with many well-known tech companies joining the ranks. Breaches in data use or misuse have only fueled this more. Clandestine data operations between tech and health care, as evidenced by “Project Knightingale,” offer strong headwinds for digital health to advanace. We are at a pivot point if health systems and consumers are to use these apps or sensors to optimize health, new rules of engagement need to emerge, so value on all sides can be realized.
A new paper by Afua van Haasteran and colleagues from the Department of Health Sciences in Zurich, published in Digital Health, proposes an mHealth (which I use as interchangeably with digital health) trustworthiness checklist. There are hundreds of thousands of health-related apps a download away from most consumers- how are they meant to know a “good” app from a “bad” app? Most free apps will sell your data onto third parties, and you may not even know it. As I have mentioned in prior posts, the Net Promotor Score (NPS) yields little value in the context of health outcomes. Professional societies like the American Psychiatric Association have developed some high-level guidance for their members to follow. Still, little consensus exists, and digital mental health apps comprise one-third of all health-related apps.
The current study focuses on end-users delving into features they deem to be a barometer of trust. The literature the authors reviewed included the following concepts: data use agreements, cost, feedback on user experience, reputation, tracking, content, and sources of said content. They used these concepts in focus group testing with twenty adults. Trustworthiness factors spanned five dimensions and included:
– Informational content- how robust is the material in the app, and is it informed by research?
– Organizational attributes – do I know the brand already? is it for-profit or not-for-profit?
– Societal influence- everyone is using it, so I feel like I need to too. Is it free?
– Technology-related features- app is user-friendly and intuitive.
– User control – I have control over how much data I share.
Factors that lead to mistrust in digital health relate to over monitoring and using geolocation. Apps that have lengthy privacy policies in obscure language or those that sought permission for access to camera and microphone features on smartphones as part of onboarding also raised red flags with consumers.
The authors prose a checklist that ideally will be applied to digital health apps. This checklist serves several needs, one the consumer would have a yardstick to base their choices on, and two app developers would have some standards to consider in their prototyping. I think the mHAT checklist is a welcome addition to the digital health app development toolbox, and I hope it will be widely applied as we move forward.
Thanks for reading – Trina
(Opinions are my own)
References
Development of a mHealth App Trustworthiness checklist.
https://journals.sagepub.com/doi/full/10.1177/2055207619886463
