JMIR Human Factors

(Re-)designing health care and making health care interventions and technologies usable, safe, and effective

Editor-in-Chief:

Andre Kushniruk BA, MSc, PhD, FACMI, School of Health Information Science, University of Victoria, Canada


JMIR Human Factors (JHF, ISSN 2292-9495; Editor-in-Chief: Prof. Andre Kushniruk) is a multidisciplinary journal with contributions from design experts, medical researchers, engineers, and social scientists.

JMIR Human Factors focuses on understanding how the behaviour and thinking of humans can influence and shape the design of health care interventions and technologies, and how the design can be evaluated and improved to make health care interventions and technologies usable, safe, and effective. This includes usability studies and heuristic evaluations, studies concerning ergonomics and error prevention, design studies for medical devices and healthcare systems/workflows, enhancing teamwork through Human Factors based teamwork training, measuring non-technical skills in staff like leadership, communication, situational awareness and teamwork, and healthcare policies and procedures to reduce errors and increase safety.

JHF aspires to lead health care towards a culture of "usability by design", as well as to a culture of testing, error-prevention and safety, by promoting and publishing reports rigorously evaluating the usability and human factors aspects in health care, as well as encouraging the development and debate on new methods in this emerging field. Possible contributions include usability studies and heuristic evaluations, studies concerning ergonomics and error prevention, design studies for medical devices and healthcare systems/workflows, enhancing teamwork through human factors-based teamwork training, measuring non-technical skills in staff like leadership, communication, situational awareness and teamwork, and healthcare policies and procedures to reduce errors and increase safety. Reviews, viewpoint papers and tutorials are as welcome as original research.

All articles are professionally copyedited and typeset. JMIR Human Factors is indexed in PubMed, PubMed Central, DOAJ, Scopus, and Psychinfo.

Recent Articles

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Participatory Design and Participatory Research

Advances in digital technology and the use of multimedia platforms to deliver information provide clinicians with a unique opportunity to develop innovative ways to consistently provide high-quality, accessible, and evidence-based information to support patient participation. Introducing new technologies into everyday acute care clinical practice can be difficult.

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General Articles on Human Factors

Mobile health (mHealth) apps have become part of the infrastructure for access to health care in hospitals, especially during the COVID-19 pandemic. However, little is known about the effects of sociodemographic characteristics on the digital divide regarding the use of hospital-based mHealth apps and their benefits to patients and caregivers.

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Focus Groups and Qualitative Research with Users

TourHeart, a web-based stratified stepped care mental health platform, is a one-stop solution that integrates psychoeducation and other well-being promotional tools for mental health promotion and mental illness prevention and evidence-based, low-intensity psychological interventions for the treatment of people with anxiety and depressive symptoms. Instead of focusing only on symptom reduction, the platform aims to be person-centered and recovery-oriented, and continual feedback from stakeholders is sought. Understanding the perspectives of users and service providers enables platform developers to fine-tune both the design and content of the services for enhanced service personalization and personal recovery.

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Focus Groups and Qualitative Research with Users

Clinician trust in machine learning–based clinical decision support systems (CDSSs) for predicting in-hospital deterioration (a type of predictive CDSS) is essential for adoption. Evidence shows that clinician trust in predictive CDSSs is influenced by perceived understandability and perceived accuracy.

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Design and Usability of Consumer Health Tech and Home Monitoring Devices

Patients’ spontaneous speech can act as a biomarker for identifying pathological entities, such as mental illness. Despite this potential, audio recording patients’ spontaneous speech is not part of clinical workflows, and health care organizations often do not have dedicated policies regarding the audio recording of clinical encounters. No previous studies have investigated the best practical approach for integrating audio recording of patient-clinician encounters into clinical workflows, particularly in the home health care (HHC) setting.

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Heuristic Usability Evaluations

Poor usability is a primary cause of unintended consequences related to the use of electronic health record (EHR) systems, which negatively impacts patient safety. Due to the cost and time needed to carry out iterative evaluations, many EHR components, such as clinical decision support systems (CDSSs), have not undergone rigorous usability testing prior to their deployment in clinical practice. Usability testing in the predeployment phase is crucial to eliminating usability issues and preventing costly fixes that will be needed if these issues are found after the system’s implementation.

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Design and Usability of Consumer Health Tech and Home Monitoring Devices

Cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are posing a huge burden on health care systems worldwide. Mobile apps can deliver behavior change interventions for chronic disease prevention on a large scale, but current evidence for their effectiveness is limited.

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Design and Usability of Clinical Software and EHRs

People with Parkinson disease (PD) have a variety of complex medical problems that require detailed review at each clinical encounter for appropriate management. Care of other complex conditions has benefited from digital health solutions that efficiently integrate disparate clinical information. Although various digital approaches have been developed for research and care in PD, no digital solution to personalize and improve communication in a clinical encounter is readily available.

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User-centred Design Case Studies

When caring for patients with chronic conditions such as chronic obstructive pulmonary disease (COPD), health care professionals (HCPs) rely on multiple data sources to make decisions. Collating and visualizing these data, for example, on clinical dashboards, holds the potential to support timely and informed decision-making. Most studies on data-supported decision-making (DSDM) technologies for health care have focused on their technical feasibility or quantitative effectiveness. Although these studies are an important contribution to the literature, they do not further our limited understanding of how HCPs engage with these technologies and how they can be designed to support specific contexts of use. To advance our knowledge in this area, we must work with HCPs to explore this space and the real-world complexities of health care work and service structures.

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Theme Issue: Human Factors of the COVID-19 Outbreak

During the COVID-19 pandemic, patient portals and their message platforms allowed remote access to health care. Utilization patterns in patient messaging during the COVID-19 crisis have not been studied thoroughly. In this work, we propose characterizing patients and their use of asynchronous virtual care for COVID-19 via a retrospective analysis of patient portal messages.

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Design and Usability of Research Instruments

Digital innovations in medicine are disruptive technologies that can change the way diagnostic procedures and treatments are delivered. Such innovations are typically designed in teams with different disciplinary backgrounds. This paper concentrates on 2 interdisciplinary research teams with 20 members from the medicine and engineering sciences working jointly on digital health solutions.

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Design and Usability of Consumer Health Tech and Home Monitoring Devices

Symptom checker apps are patient-facing decision support systems aimed at providing advice to laypersons on whether, where, and how to seek health care (disposition advice). Such advice can improve laypersons’ self-assessment and ultimately improve medical outcomes. Past research has mainly focused on the accuracy of symptom checker apps’ suggestions. To support decision-making, such apps need to provide not only accurate but also trustworthy advice. To date, only few studies have addressed the question of the extent to which laypersons trust symptom checker app advice or the factors that moderate their trust. Studies on general decision support systems have shown that framing automated systems (anthropomorphic or emphasizing expertise), for example, by using icons symbolizing artificial intelligence (AI), affects users’ trust.

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