Design Features of Embodied Conversational Agents in eHealth: a Literature Review

Stal, Silke ter; Kramer, Lean L; Tabak, Monique; Akker, Harm op den; Hermens, Hermie

doi:10.1016/j.ijhcs.2020.102409

Cited by 120 publications

(84 citation statements)

References 32 publications

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“…Although ECAs have the potential to be used as eHealth apps such as digital frailty assessments, little is known about how these agents should be designed and how the design affects our impressions of the agents, and no design guidelines exist [ 15 ]. In one study, ter Stal et al [ 16 ] identified people’s first impressions of agents varying in age, gender, and role using a zero acquaintance approach: there was no interaction involved, and participants rated static agent images at first glance.…”

Section: Introductionmentioning

confidence: 99%

Embodied Conversational Agent Appearance for Health Assessment of Older Adults: Explorative Study

Stal¹,

Broekhuis²,

Velsen³

et al. 2020

JMIR Hum Factors

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Background Embodied conversational agents (ECAs) have great potential for health apps but are rarely investigated as part of such apps. To promote the uptake of health apps, we need to understand how the design of ECAs can influence the preferences, motivation, and behavior of users. Objective This is one of the first studies that investigates how the appearance of an ECA implemented within a health app affects users’ likeliness of following agent advice, their perception of agent characteristics, and their feeling of rapport. In addition, we assessed usability and intention to use. Methods The ECA was implemented within a frailty assessment app in which three health questionnaires were translated into agent dialogues. In a within-subject experiment, questionnaire dialogues were randomly offered by a young female agent or an older male agent. Participants were asked to think aloud during interaction. Afterward, they rated the likeliness of following the agent’s advice, agent characteristics, rapport, usability, and intention to use and participated in a semistructured interview. Results A total of 20 older adults (72.2 [SD 3.5] years) participated. The older male agent was perceived as more authoritative than the young female agent (P=.03), but no other differences were found. The app scored high on usability (median 6.1) and intention to use (median 6.0). Participants indicated they did not see an added value of the agent to the health app. Conclusions Agent age and gender little influence users’ impressions after short interaction but remain important at first glance to lower the threshold to interact with the agent. Thus, it is important to take the design of ECAs into account when implementing them into health apps.

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Section: Introductionmentioning

confidence: 99%

Embodied Conversational Agent Appearance for Health Assessment of Older Adults: Explorative Study

Stal¹,

Broekhuis²,

Velsen³

et al. 2020

JMIR Hum Factors

Self Cite

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“…Excerpts of the scripts are shown and discussed in the Results section, and the complete scripts can be found in Multimedia Appendix 3 . The intervention was purely text based without any visual or spoken cues to reduce any bias toward visual CA design features, such as gender, age, or visual appearance [ 33 , 46 ]. Hence, we named the CA Robo, a gender-neutral name.…”

Section: Methodsmentioning

confidence: 99%

“…As scalable and ubiquitous digital tools, CAs facilitate personalized disease management outside the traditional health care system. Relevant aspects for developing personalized CAs, such as the required level of anthropomorphic appearance [ 32 ] or necessary design features [ 33 ], have been extensively investigated. However, to date, there has been no investigation of different interaction styles between patients and health care professionals where CAs play the role of medical experts.…”

Section: Introductionmentioning

confidence: 99%

Deliberative and Paternalistic Interaction Styles for Conversational Agents in Digital Health: Procedure and Validation Through a Web-Based Experiment

Schachner¹,

Gross²,

Hasl³

et al. 2021

J Med Internet Res

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Background Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users. Objective The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context. Methods On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style. Results A total of 88 individuals (42/88, 48% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80% of the assessments (X21,88=38.2; P<.001; phi coefficient rφ=0.68). The validation of the procedure was hence successful. Conclusions We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.

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“…These voice-based counselors are different from a variety of prior innovations for virtual counseling. For example, embodied conversational agents (ECA) 10,11 utilized both voice-based and direct manipulation interfaces (e.g., user selection from a list) for clinical and cognitive support in various domains, including marriage counseling 12 , palliative care counseling 13 , and collecting family health history 14 . A more direct comparisons for the voicebased virtual counselors are the text-based "chat bots" that provided text-based emotional support 9 .…”

Section: Introductionmentioning

confidence: 99%

Cognitive plausibility in voice-based AI health counselors

et al. 2020

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Voice-based personal assistants using artificial intelligence (AI) have been widely adopted and used in home-based settings. Their success has created considerable interest for its use in healthcare applications; one area of prolific growth in AI is that of voicebased virtual counselors for mental health and well-being. However, in spite of its promise, building realistic virtual counselors to achieve higher-order maturity levels beyond task-based interactions presents considerable conceptual and pragmatic challenges. We describe one such conceptual challenge-cognitive plausibility, defined as the ability of virtual counselors to emulate the human cognitive system by simulating how a skill or function is accomplished. An important cognitive plausibility consideration for voice-based agents is its ability to engage in meaningful and seamless interactive communication. Drawing on a broad interdisciplinary research literature and based on our experiences with developing two voice-based (voice-only) prototypes that are in the early phases of testing, we articulate two conceptual considerations for their design and use-conceptualizing voice-based virtual counselors as communicative agents and establishing virtual co-presence. We discuss why these conceptual considerations are important and how it can lead to the development of voice-based counselors for real-world use.

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Design Features of Embodied Conversational Agents in eHealth: a Literature Review

Cited by 120 publications

References 32 publications

Embodied Conversational Agent Appearance for Health Assessment of Older Adults: Explorative Study

Embodied Conversational Agent Appearance for Health Assessment of Older Adults: Explorative Study

Deliberative and Paternalistic Interaction Styles for Conversational Agents in Digital Health: Procedure and Validation Through a Web-Based Experiment

Cognitive plausibility in voice-based AI health counselors

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