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BACKGROUND Hypoglycemia is a serious complication in diabetes, it impairs cognitive and psychomotor function, and is linked to driving mishaps. In-vehicle voice assistants (VAs) have been designed to proactively deliver a warning of hypoglycemia while driving. However, proactive VAs can cause driving impairments through startling. Hence, we complement the voice warning from the VA with ambient light-emitting diodes (LED) and investigate the effect of this addition on emotional reaction. OBJECTIVE Designing an in-vehicle voice warning for hypoglycemia and assessing its effect on the emotional reaction and technology acceptance. METHODS We present two studies investigating the emotional reactions of drivers with diabetes to different hypoglycemia warning modalities. The same procedure was replicated in two settings: simulated and real driving. A quasi-experimental design, with two independent variables (blood glucose phase and warning modality) and one main dependent variable (emotional reaction), was implemented. The material and apparatus included intravenous catheters to manipulate blood glucose and a tablet with an app to simulate hypoglycemia warnings. The warnings had three possible modalities: Standard, Voice, and Voice + LED. Objective emotional reaction (arousal) was measured physiologically via skin conductance response (SCR). Subjective emotional reaction was measured with the Affective Slider (valence and arousal). Both emotional reaction measures were tested with a mixed-effect linear model. Secondary outcomes included self-reported measures of technology acceptance. RESULTS Our results showed that in the simulated-driving setting, the Voice + LED warning modality was preferred over other modalities. However, this advantage decreased in real-world driving because the LED was less visible outdoors. The Voice modality was more effective than the Standard warning modality in both simulated and real-world driving studies. The mixed model on self-reported emotional reaction yielded significant results. Self-reported arousal was higher during Decreasing blood glucose and Hypoglycemia for Voice and Voice + LED in the real-world driving study. In contrast, self-reported valence was influenced by blood glucose manipulation rather than the warning modality. The mixed model on SCR did not yield significant results. Participants consistently ranked the Voice and Voice + LED warning modalities superior to the Standard modality. CONCLUSIONS This paper proposes using the in-vehicle VA and ambient lighting system installed in a car to deliver a warning of hypoglycemia. It investigated how the warning modality affects emotional response and acceptance in virtual and real-world environments. The study provides insight into the potential of implementing VA-based health warnings in cars and contributes to a better understanding of the challenges and opportunities of in-vehicle VA-based health interventions.

BACKGROUND Hypoglycemia is a frequent and acute complication in type-1 diabetes mellitus (T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be detected and signaled through flash glucose monitoring (FGM) or continuous glucose monitoring (CGM) devices. These devices, however, require manual and visual interaction, removing the focus of attention from the driving task. Hypoglycemia is known to cause a decrease in attention, challenging the safety of using such devices behind the wheel. Here, we present an investigation of hands- and distraction-free technology: an in–vehicle voice–assistant–based warning. OBJECTIVE Designing and assessing a voice–assistant–based health warning for hypoglycemia while driving and addressing the limitations of the current warning solutions. METHODS We developed and assessed the warning in three studies, where participants received the warning while driving. In all studies, we measured participants’ self-reported technology readiness, perception of the warning, and compliance behavior (whether they stopped the car and their reaction time), and assessed any room for improvement through participants’ feedback. In Study 0, 10 healthy participants drove in a simulator and assessed the feasibility of using a voice assistant to deliver a warning. In Study 1, 18 participants with T1DM drove in a simulator and assessed the revised version of the warning. In Study 2, 20 participants with T1DM undergoing hypoglycemia assessed a further revised version of the warning while driving in a real car on a test track. In all studies, we also measured self-reported technology readiness, and acceptance of the warning, and assessed compliance behavior and reaction time in response to the warning. RESULTS In all studies, 100% of participants complied with the warning. In Study 0, healthy participants perceived the warning as usable and useful, and their feedback suggested reducing speech rate and increasing driver-assistant interaction. In Study 1, participants with T1DM reported good perception and their feedback suggested the warning to be less instructive. In Study 2, we observed moderate perception (lower than in Study 1), and participants’ feedback revealed the warning was too overloading. CONCLUSIONS To the best of the authors’ knowledge, this is the first study investigating the feasibility of an in–vehicle voice–assistant–based warning for hypoglycemia while driving. Drivers find such an implementation useful and effective, although individuals with T1DM preferred a simple and direct voice warning, rather than a conversational one. This may reflect the utility and unfamiliarity of proactive behavior in voice assistants. We anticipate this research to be a starting point for the combination of driver-state warnings and for voice–assistant–based health support, and to be a guide for the design of such a combination. CLINICALTRIAL ClinicalTrials.gov NCT04035993, NCT04569630

BACKGROUND Mental health interventions delivered through mobile health (mHealth) technologies can increase the access to mental health services, especially among university students. The development of mHealth intervention is complex and needs to be context sensitive. There is currently limited evidence on the perceptions, needs, and barriers related to these interventions in the Southeast Asian context. OBJECTIVE This qualitative study aimed to explore the perception of university students and mental health supporters in Singapore about mental health services, campaigns, and mHealth interventions with a focus on conversational agent interventions for the prevention of common mental disorders such as anxiety and depression. METHODS We conducted 6 web-based focus group discussions with 30 university students and one-to-one web-based interviews with 11 mental health supporters consisting of faculty members tasked with student pastoral care, a mental health first aider, counselors, psychologists, a clinical psychologist, and a psychiatrist. The qualitative analysis followed a reflexive thematic analysis framework. RESULTS The following 6 main themes were identified: a healthy lifestyle as students, access to mental health services, the role of mental health promotion campaigns, preferred mHealth engagement features, factors that influence the adoption of mHealth interventions, and cultural relevance of mHealth interventions. The interpretation of our findings shows that students were reluctant to use mental health services because of the fear of stigma and a possible lack of confidentiality. CONCLUSIONS Study participants viewed mHealth interventions for mental health as part of a blended intervention. They also felt that future mental health mHealth interventions should be more personalized and capable of managing adverse events such as suicidal ideation.

Background Health care and well-being are 2 main interconnected application areas of conversational agents (CAs). There is a significant increase in research, development, and commercial implementations in this area. In parallel to the increasing interest, new challenges in designing and evaluating CAs have emerged. Objective This study aims to identify key design, development, and evaluation challenges of CAs in health care and well-being research. The focus is on the very recent projects with their emerging challenges. Methods A review study was conducted with 17 invited studies, most of which were presented at the ACM (Association for Computing Machinery) CHI 2020 conference workshop on CAs for health and well-being. Eligibility criteria required the studies to involve a CA applied to a health or well-being project (ongoing or recently finished). The participating studies were asked to report on their projects’ design and evaluation challenges. We used thematic analysis to review the studies. Results The findings include a range of topics from primary care to caring for older adults to health coaching. We identified 4 major themes: (1) Domain Information and Integration, (2) User-System Interaction and Partnership, (3) Evaluation, and (4) Conversational Competence. Conclusions CAs proved their worth during the pandemic as health screening tools, and are expected to stay to further support various health care domains, especially personal health care. Growth in investment in CAs also shows the value as a personal assistant. Our study shows that while some challenges are shared with other CA application areas, safety and privacy remain the major challenges in the health care and well-being domains. An increased level of collaboration across different institutions and entities may be a promising direction to address some of the major challenges that otherwise would be too complex to be addressed by the projects with their limited scope and budget.