Voice-based conversational agents for sensing and support: Examples from academia and industry

Bérubé, Caterina; Fleisch, Elgar

doi:10.1016/b978-0-323-90045-4.00017-4

Cited by 3 publications

(1 citation statement)

References 105 publications

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“…Indeed, vocal interactions have been observed to be the least cognitively demanding while driving compared with visual and haptic interactions [28,29]. Moreover, voice assistants are increasingly being implemented to deliver digital health interventions [30][31][32][33]. Although research is still in its infancy, efforts have been made to develop voice-based conversational agents to monitor and support individuals with chronic diseases such as cancer, cardiovascular diseases, cognitive disorders, or diabetes [30].…”

Section: Introductionmentioning

confidence: 99%

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial

Bérubé,

Lehmann,

Maritsch

et al. 2024

JMIR Hum Factors

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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 or continuous glucose monitoring devices, which require manual and visual interaction, thereby removing the focus of attention from the driving task. Hypoglycemia causes a decrease in attention, thereby challenging the safety of using such devices behind the wheel. Here, we present an investigation of a hands-free technology—a voice warning that can potentially be delivered via an in-vehicle voice assistant. Objective This study aims to investigate the feasibility of an in-vehicle voice warning for hypoglycemia, evaluating both its effectiveness and user perception. Methods We designed a voice warning and evaluated it in 3 studies. In all studies, participants received a voice warning while driving. Study 0 (n=10) assessed the feasibility of using a voice warning with healthy participants driving in a simulator. Study 1 (n=18) assessed the voice warning in participants with T1DM. Study 2 (n=20) assessed the voice warning in participants with T1DM undergoing hypoglycemia while driving in a real car. We measured participants’ self-reported perception of the voice warning (with a user experience scale in study 0 and with acceptance, alliance, and trust scales in studies 1 and 2) and compliance behavior (whether they stopped the car and reaction time). In addition, we assessed technology affinity and collected the participants’ verbal feedback. Results Technology affinity was similar across studies and approximately 70% of the maximal value. Perception measure of the voice warning was approximately 62% to 78% in the simulated driving and 34% to 56% in real-world driving. Perception correlated with technology affinity on specific constructs (eg, Affinity for Technology Interaction score and intention to use, optimism and performance expectancy, behavioral intention, Session Alliance Inventory score, innovativeness and hedonic motivation, and negative correlations between discomfort and behavioral intention and discomfort and competence trust; all P<.05). Compliance was 100% in all studies, whereas reaction time was higher in study 1 (mean 23, SD 5.2 seconds) than in study 0 (mean 12.6, SD 5.7 seconds) and study 2 (mean 14.6, SD 4.3 seconds). Finally, verbal feedback showed that the participants preferred the voice warning to be less verbose and interactive. Conclusions This is the first study to investigate the feasibility of an in-vehicle voice warning for hypoglycemia. Drivers find such an implementation useful and effective in a simulated environment, but improvements are needed in the real-world driving context. This study is a kickoff for the use of in-vehicle voice assistants for digital health interventions.

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Section: Introductionmentioning

confidence: 99%

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial

Bérubé,

Lehmann,

Maritsch

et al. 2024

JMIR Hum Factors

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Let’s Chat to Negotiate: Designing a Conversational Agent for Learning Negotiation Skills

Zahn,

Schöbel

2024

Lecture Notes in Computer Science

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Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial (Preprint)

Bérubé¹,

Lehmann²,

Maritsch³

et al. 2022

Preprint

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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

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Voice-based conversational agents for sensing and support: Examples from academia and industry

Cited by 3 publications

References 105 publications

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial

Let’s Chat to Negotiate: Designing a Conversational Agent for Learning Negotiation Skills

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial (Preprint)

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