The Digital Transformation of Mental Health Care and Psychotherapy – A Market and Research Maturity Analysis

Digital technology trends for mental health, instantiated with only emerging use cases or already established applications, offer significant potential to improve clinical therapy and care. In this paper, we identify five major trends, mHealth/eHealth, telehealth, artificial intelligence (AI), big data, and biosensors/wearables; describe seven specific technology use cases for mental health care and psychotherapy; and provide an overview of their maturity in practice

Mechatronics & the cloud

Conventionally, the engineering design process has assumed that the design team is able to exercise control over all elements of the design, either directly or indirectly in the case of sub-systems through their specifications. The introduction of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) means that a design team’s ability to have control over all elements of a system is no longer the case, particularly as the actual system configuration may well be being dynamically reconfigured in real-time according to user (and vendor) context and need. Additionally, the integration of the Internet of Things with elements of Big Data means that information becomes a commodity to be autonomously traded by and between systems, again according to context and need, all of which has implications for the privacy of system users. The paper therefore considers the relationship between mechatronics and cloud-basedtechnologies in relation to issues such as the distribution of functionality and user privacy

Linking recorded data with emotive and adaptive computing in an eHealth environment

Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development

Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice

Objectives Sexual and reproductive health (SRH) services are undergoing a digital transformation. This study explored the acceptability of three digital services, (i) video consultations via Skype, (ii) live webchats with a health advisor and (iii) artificial intelligence (AI)-enabled chatbots, as potential platforms for SRH advice. Methods A pencil-and-paper 33-item survey was distributed in three clinics in Hampshire, UK for patients attending SRH services. Logistic regressions were performed to identify the correlates of acceptability. Results In total, 257 patients (57% women, 50% aged <25 years) completed the survey. As the first point of contact, 70% preferred face-to-face consultations, 17% telephone consultation, 10% webchats and 3% video consultations. Most would be willing to use video consultations (58%) and webchat facilities (73%) for ongoing care, but only 40% found AI chatbots acceptable. Younger age (<25 years) (OR 2.43, 95% CI 1.35 to 4.38), White ethnicity (OR 2.87, 95% CI 1.30 to 6.34), past sexually transmitted infection (STI) diagnosis (OR 2.05, 95% CI 1.07 to 3.95), self-reported STI symptoms (OR 0.58, 95% CI 0.34 to 0.97), smartphone ownership (OR 16.0, 95% CI 3.64 to 70.5) and the preference for a SRH smartphone application (OR 1.95, 95% CI 1.13 to 3.35) were associated with video consultations, webchats or chatbots acceptability. Conclusions Although video consultations and webchat services appear acceptable, there is currently little support for SRH chatbots. The findings demonstrate a preference for human interaction in SRH services. Policymakers and intervention developers need to ensure that digital transformation is not only cost-effective but also acceptable to users, easily accessible and equitable to all populations using SRH services

Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare

Managing the Ethical Dimensions of Brain-Computer Interfaces in eHealth: An SDLC-based Approach

A growing range of brain-computer interface (BCI) technologies is being employed for purposes of therapy and human augmentation. While much thought has been given to the ethical implications of such technologies at the ‘macro’ level of social policy and ‘micro’ level of individual users, little attention has been given to the unique ethical issues that arise during the process of incorporating BCIs into eHealth ecosystems. In this text a conceptual framework is developed that enables the operators of eHealth ecosystems to manage the ethical components of such processes in a more comprehensive and systematic way than has previously been possible. The framework’s first axis defines five ethical dimensions that must be successfully addressed by eHealth ecosystems: 1) beneficence; 2) consent; 3) privacy; 4) equity; and 5) liability. The second axis describes five stages of the systems development life cycle (SDLC) process whereby new technology is incorporated into an eHealth ecosystem: 1) analysis and planning; 2) design, development, and acquisition; 3) integration and activation; 4) operation and maintenance; and 5) disposal. Known ethical issues relating to the deployment of BCIs are mapped onto this matrix in order to demonstrate how it can be employed by the managers of eHealth ecosystems as a tool for fulfilling ethical requirements established by regulatory standards or stakeholders’ expectations. Beyond its immediate application in the case of BCIs, we suggest that this framework may also be utilized beneficially when incorporating other innovative forms of information and communications technology (ICT) into eHealth ecosystems