BackgroundInformation and communication technologies have long become prominent components of health systems. Rapid advances in digital technologies and data science over the last few years are predicted to have a vast impact on health care services, configuring a paradigm shift into what is now commonly referred to as digital health. Forecasted to curb rising health costs as well as to improve health system efficiency and safety, digital health success heavily relies on trust from professional end users, administrators, and patients. Yet, what counts as the building blocks of trust in digital health systems has so far remained underexplored.ObjectiveThe objective of this study was to analyze what relevant stakeholders consider as enablers and impediments of trust in digital health.MethodsWe performed a scoping review to map out trust in digital health. To identify relevant digital health studies, we searched 5 electronic databases. Using keywords and Medical Subject Headings, we targeted all relevant studies and set no boundaries for publication year to allow a broad range of studies to be identified. The studies were screened by 2 reviewers after which a predefined data extraction strategy was employed and relevant themes documented.ResultsOverall, 278 qualitative, quantitative, mixed-methods, and intervention studies in English, published between 1998 and 2017 and conducted in 40 countries were included in this review. Patients and health care professionals were the two most prominent stakeholders of trust in digital health; a third—health administrators—was substantially less prominent. Our analysis identified cross-cutting personal, institutional, and technological elements of trust that broadly cluster into 16 enablers (altruism, fair data access, ease of use, self-efficacy, sociodemographic factors, recommendation by other users, usefulness, customizable design features, interoperability, privacy, initial face-to-face contact, guidelines for standardized use, stakeholder engagement, improved communication, decreased workloads, and service provider reputation) and 10 impediments (excessive costs, limited accessibility, sociodemographic factors, fear of data exploitation, insufficient training, defective technology, poor information quality, inadequate publicity, time-consuming, and service provider reputation) to trust in digital health.ConclusionsTrust in digital health technologies and services depends on the interplay of a complex set of enablers and impediments. This study is a contribution to ongoing efforts to understand what determines trust in digital health according to different stakeholders. Therefore, it offers valuable points of reference for the implementation of innovative digital health services. Building on insights from this study, actionable metrics can be developed to assess the trustworthiness of digital technologies in health care.

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Background: Mobile health applications (mHealth apps) currently lack a consensus on substantial quality and safety standards. As such, the number of individuals engaging with untrustworthy mHealth apps continues to grow at a steady pace.Objective: The purpose of this study was to investigate end-users' opinions on the features or actions necessary for trustworthy mHealth apps; and to convey this information to app developers via a succinct but informative checklist: the mHealth app trustworthiness checklist. Methods:The checklist was formulated in three stages: (a) a literature review of studies identified the desirable features of the most prolific mHealth apps (health and fitness apps); (b) four focus group sessions with past or current users of these apps (n ¼ 20); and (c) expert feedback on whether the checklist items are conceivable in a real-life setting (n ¼ 6).Results: Five major themes emerged from the focus group discussions: informational content, organizational attributes, societal influence, technology-related features, and user control factors. The mHealth app trustworthiness checklist was developed to incorporate these five themes and subsequently modified following expert consultation. In addition to the trustworthiness themes, we identified features that lie between trust and mistrust (limited digital literacy and indifference) as well as 10 features and actions that cause end-users to mistrust mHealth apps. Conclusion:This study contributes to the evidence base on the attributes of trustworthy mHealth apps. The mHealth app trustworthiness checklist is a useful tool in advancing continued efforts to ensure that health technologies are trustworthy.

Trust is a ubiquitous term used in emerging technology (e.g., Big Data, precision medicine), innovation policy, and governance literatures in particular. But what exactly is trust? Even though trust is considered a critical requirement for the successful deployment of precision medicine initiatives, nonetheless, there is a need for further conceptualization with regard to what qualifies as trust, and what factors might establish and sustain trust in precision medicine, predictive analytics, and large-scale biology. These new fields of 21st century medicine and health often deal with the “futures” and hence, trust gains a temporal and ever-present quality for both the present and the futures anticipated by new technologies and predictive analytics. We address these conceptual gaps that have important practical implications in the way we govern risk and unknowns associated with emerging technologies in biology, medicine, and health broadly. We provide an in-depth conceptual analysis and an operative definition of trust dynamics in precision medicine. In addition, we identify three main types of “trust facilitators”: (1) technical, (2) ethical, and (3) institutional. This three-dimensional framework on trust is necessary to building and maintaining trust in 21st century knowledge-based innovations that governments and publics invest for progressive societal change, development, and sustainable prosperity. Importantly, we analyze, identify, and deliberate on the dimensions of precision medicine and large-scale biology that have carved out trust as a pertinent tool to its success. Moving forward, we propose a “points to consider” on how best to enhance trust in precision medicine and predictive analytics.

Background The mobile health (mHealth) app trustworthiness (mHAT) checklist was created to identify end users’ opinions on the characteristics of trustworthy mHealth apps and to communicate this information to app developers. To ensure that the checklist is suited for all relevant stakeholders, it is necessary to validate its contents. Objective The purpose of this study was to assess the feasibility of the mHAT checklist by modifying its contents according to ratings and suggestions from stakeholders familiar with the process of developing, managing, or curating mHealth apps. Methods A 44-item online survey was administered to relevant stakeholders. The survey was largely comprised of the mHAT checklist items, which respondents rated on a 5-point Likert scale, ranging from completely disagree (1) to completely agree (5). Results In total, seven professional backgrounds were represented in the survey: administrators (n=6), health professionals (n=7), information technology personnel (n=6), managers (n=2), marketing personnel (n=3), researchers (n=5), and user experience researchers (n=8). Aside from one checklist item—“the app can inform end users about errors in measurements”—the combined positive ratings (ie, completely agree and agree) of the checklist items overwhelmingly exceeded the combined negative ratings (ie, completely disagree and disagree). Meanwhile, two additional items were included in the checklist: (1) business or funding model of the app and (2) details on app uninstallation statistics. Conclusions Our results indicate that the mHAT checklist is a valuable resource for a broad range of stakeholders to develop trustworthy mHealth apps. Future studies should examine if the checklist works best for certain mHealth apps or in specific settings.