Research Topic

Human Factors in Data-driven Connected Health Technologies

About this Research Topic

Population growth, increased longevity, more complex health conditions, shortage of physicians, and the high cost of healthcare delivery are some of the current healthcare challenges. Connected health technologies, including telehealth, telemedicine, mHealth, digital health, and eHealth services are gaining more and more attention, both from providers and patients. They are seen as an integral part of the solution to many of the challenges facing healthcare, enabling more effective integration of care, improving clinical outcomes, and driving patient and physician satisfaction. Health applications, mobile diagnostics, remote monitoring devices, and wearables are just a few examples. Big data, artificial intelligence, machine learning, and data integration are at the forefront of connected health technologies, with great potential for better prevention, detection, diagnosis, and treatment of disease. However, connected health solutions have been often technology-driven, without the involvement of the people they are aimed at. Healthcare professionals are often reluctant to engage with this technology and patients and carers are looking for usable, safe, and effective solutions.

Human factors (HF) and human-centered design research aim to investigate and design novel user experiences and interactions with data-driven connected health technologies for both patients and health care professionals. Explainability, transparency, ergonomics, usability, inclusivity, fairness, data interpretation, and interaction are only a few of the human factor problems that modern big data and AI research still needs to address in the context of medicine and public health. Thus, understanding how people think and behave, their needs and wants can influence and shape the development of solutions that are acceptable by users, usable, safe, and effective. This Research Topic - ‘Human Factors in Data-driven Connected Health Technologies’ aims to present and discuss the latest advancements in the design, development, and evaluation of data-driven connected health technologies from the human factors' perspective.

We welcome contributions from researchers, focusing on connected health technologies from the human factors perspective. Contributions should address behavioral, cognitive, and socio-technical problems related to the design and implementation of these types of technologies in data/AI-driven medicine and public health. Submissions should report new knowledge of empirical work that has not been published before. Potential topics include, but are not limited, to people, methods, and technologies in big data and AI for:

• Self-management technologies for chronic conditions
• Audit and feedback systems
• Clinical decision support tools
• Wearable sensors
• Medical devices for disease diagnosis
• The virtual clinic (Virtual reality/augmented reality)
• Connected health cities
• Mind-machine interaction (Brain-computer / neural interfaces)
• Enabling and assistive technologies and personal digital assistants
• Big data technologies for COVID-19:
- Symptom tracking apps/systems
- Contact tracing apps/systems
- Immunity passports apps/systems (digital or hybrid services)
• Complex sociotechnical systems (addressing the interaction between people, services, technologies, procedures, products, and cultures)
• Patient portals, Electronic Health Records and medication order systems


Keywords: connected health, human factors, big data, digital health, public health informatics


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Population growth, increased longevity, more complex health conditions, shortage of physicians, and the high cost of healthcare delivery are some of the current healthcare challenges. Connected health technologies, including telehealth, telemedicine, mHealth, digital health, and eHealth services are gaining more and more attention, both from providers and patients. They are seen as an integral part of the solution to many of the challenges facing healthcare, enabling more effective integration of care, improving clinical outcomes, and driving patient and physician satisfaction. Health applications, mobile diagnostics, remote monitoring devices, and wearables are just a few examples. Big data, artificial intelligence, machine learning, and data integration are at the forefront of connected health technologies, with great potential for better prevention, detection, diagnosis, and treatment of disease. However, connected health solutions have been often technology-driven, without the involvement of the people they are aimed at. Healthcare professionals are often reluctant to engage with this technology and patients and carers are looking for usable, safe, and effective solutions.

Human factors (HF) and human-centered design research aim to investigate and design novel user experiences and interactions with data-driven connected health technologies for both patients and health care professionals. Explainability, transparency, ergonomics, usability, inclusivity, fairness, data interpretation, and interaction are only a few of the human factor problems that modern big data and AI research still needs to address in the context of medicine and public health. Thus, understanding how people think and behave, their needs and wants can influence and shape the development of solutions that are acceptable by users, usable, safe, and effective. This Research Topic - ‘Human Factors in Data-driven Connected Health Technologies’ aims to present and discuss the latest advancements in the design, development, and evaluation of data-driven connected health technologies from the human factors' perspective.

We welcome contributions from researchers, focusing on connected health technologies from the human factors perspective. Contributions should address behavioral, cognitive, and socio-technical problems related to the design and implementation of these types of technologies in data/AI-driven medicine and public health. Submissions should report new knowledge of empirical work that has not been published before. Potential topics include, but are not limited, to people, methods, and technologies in big data and AI for:

• Self-management technologies for chronic conditions
• Audit and feedback systems
• Clinical decision support tools
• Wearable sensors
• Medical devices for disease diagnosis
• The virtual clinic (Virtual reality/augmented reality)
• Connected health cities
• Mind-machine interaction (Brain-computer / neural interfaces)
• Enabling and assistive technologies and personal digital assistants
• Big data technologies for COVID-19:
- Symptom tracking apps/systems
- Contact tracing apps/systems
- Immunity passports apps/systems (digital or hybrid services)
• Complex sociotechnical systems (addressing the interaction between people, services, technologies, procedures, products, and cultures)
• Patient portals, Electronic Health Records and medication order systems


Keywords: connected health, human factors, big data, digital health, public health informatics


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 May 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 May 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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