Predicting User Engagement in Longitudinal Interventions with Virtual Agents

Trinh, Ha; Shamekhi, Ameneh; Kimani, Everlyne; Bickmore, Timothy

doi:10.1145/3267851.3267909

Cited by 20 publications

(13 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, engagement is also being investigated within the context of long-term human-agent interaction. In such a context (Trinh et al, 2018 ) separate between three user categories: Those who “dropout,” those who are “moderately engaged” and those who are “highly engaged.”…”

Section: Definition Of Engagementmentioning

confidence: 99%

Engagement in Human-Agent Interaction: An Overview

et al. 2020

View full text Add to dashboard Cite

Engagement is a concept of the utmost importance in human-computer interaction, not only for informing the design and implementation of interfaces, but also for enabling more sophisticated interfaces capable of adapting to users. While the notion of engagement is actively being studied in a diverse set of domains, the term has been used to refer to a number of related, but different concepts. In fact it has been referred to across different disciplines under different names and with different connotations in mind. Therefore, it can be quite difficult to understand what the meaning of engagement is and how one study relates to another one accordingly. Engagement has been studied not only in human-human, but also in human-agent interactions i.e., interactions with physical robots and embodied virtual agents. In this overview article we focus on different factors involved in engagement studies, distinguishing especially between those studies that address task and social engagement, involve children and adults, are conducted in a lab or aimed for long term interaction. We also present models for detecting engagement and for generating multimodal behaviors to show engagement.

show abstract

Section: Definition Of Engagementmentioning

confidence: 99%

Engagement in Human-Agent Interaction: An Overview

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Current work on virtual agents mirrors the gender stereotypes, where female-looking agents are mostly used in roles associated with communion traits. Female agents have been dominantly used in applications such as personal companions [24,38], assistants [54], health counsellors [9,10,44,53], and mental health counsellors [40]. Male agents seem to be dominantly used in applications that require agency or competence traits such as mentors [5,6], educational applications [27,33,57] or motivators [5].…”

Section: Virtual Agents and Gender Stereotypesmentioning

confidence: 99%

Gender Stereotypes in Virtual Agents

Nag

Yalçın

2020

Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents

View full text Add to dashboard Cite

Visual, behavioral and verbal cues for gender are often used in designing virtual agents to take advantage of their stereotypical effects on the users. However, recent studies point towards a more gender-balanced view of stereotypical traits and roles in our society. This paper is intended as an effort towards a progressive and inclusive approach for gender representations in virtual agents. Our contributions are twofold. First, in an iterative design process, we created representative male, female and androgynous agents with few differences in their visual attributes. Second, we used these agents to evaluate the stereotypical assumptions of gendered traits and roles in virtual agents. Our results showed that, indeed, gender stereotypes are not as effective as previously assumed, and androgynous agents could represent a middle-ground between gendered stereotypes. We present our findings in the hope to foster discussions in virtual agent research and the frequent stereotypical use of gender representations. CCS CONCEPTS • Human-centered computing → User studies; • Computing methodologies → Intelligent agents; • Social and professional topics → Gender.

show abstract

“…The interview guide was developed by the first author (SB) and used exploratory questions and probes, with feedback from other members of the research team (BO, GW, and JS) based on the research question and findings from the current literature [8,9,14,18,[21][22][23]26,27,[35][36][37][38]. The guide explored a variety of topics, including experience at diagnosis; self-care behavior before using the MDC app; users' experiences with the MDC app, including when, where, and how it was used; changes to self-management practices as a result of using the MDC app; initial impression of the ECA Laura and changes over time; perceptions of her role in self-management, and her perceived personality characteristics.…”

Section: Acceptability: Qualitative Datamentioning

confidence: 99%

“…Some of the characteristics of ECAs that may affect their acceptability include users being deterred by a monotonous voice and repetitive messages [13,18,20]. Although ECAs are more engaging if they have human-like characteristics and engage in social dialog, this effect is mitigated if there is an unnatural dissonance between a character's speech and the expected facial expressions and body movements of the ECA [17,[21][22][23]. This phenomenon, coined the uncanny valley by Masahiro Mori in 1970, was supported by research suggesting that people have unpleasant impressions of artificial characters, such as ECAs that have an almost, but not perfectly, realistic human appearance [24,25].…”

Section: Introductionmentioning

confidence: 99%

Acceptability of an Embodied Conversational Agent for Type 2 Diabetes Self-Management Education and Support via a Smartphone App: Mixed Methods Study (Preprint)

Baptista¹,

Wadley²,

Bird³

et al. 2019

Preprint

View full text Add to dashboard Cite

BACKGROUND Embodied conversational agents (ECAs) are increasingly used in health care apps; however, their acceptability in type 2 diabetes (T2D) self-management apps has not yet been investigated. OBJECTIVE This study aimed to evaluate the acceptability of the ECA (Laura) used to deliver diabetes self-management education and support in the My Diabetes Coach (MDC) app. METHODS A sequential mixed methods design was applied. Adults with T2D allocated to the intervention arm of the MDC trial used the MDC app over a period of 12 months. At 6 months, they completed questions assessing their interaction with, and attitudes toward, the ECA. In-depth qualitative interviews were conducted with a subsample of the participants from the intervention arm to explore their experiences of using the ECA. The interview questions included the participants’ perceptions of Laura, including their initial impression of her (and how this changed over time), her personality, and human character. The quantitative and qualitative data were interpreted using integrated synthesis. RESULTS Of the 93 intervention participants, 44 (47%) were women; the mean (SD) age of the participants was 55 (SD 10) years and the baseline glycated hemoglobin A1c level was 7.3% (SD 1.5%). Overall, 66 of the 93 participants (71%) provided survey responses. Of these, most described Laura as being helpful (57/66, 86%), friendly (57/66, 86%), competent (56/66, 85%), trustworthy (48/66, 73%), and likable (40/66, 61%). Some described Laura as not real (18/66, 27%), boring (26/66, 39%), and annoying (20/66, 30%). Participants reported that interacting with Laura made them feel more motivated (29/66, 44%), comfortable (24/66, 36%), confident (14/66, 21%), happy (11/66, 17%), and hopeful (8/66, 12%). Furthermore, 20% (13/66) of the participants were frustrated by their interaction with Laura, and 17% (11/66) of the participants reported that interacting with Laura made them feel guilty. A total of 4 themes emerged from the qualitative data (N=19): (1) perceived role: a friendly coach rather than a health professional; (2) perceived support: emotional and motivational support; (3) embodiment preference acceptability of a human-like character; and (4) room for improvement: need for greater congruence between Laura’s words and actions. CONCLUSIONS These findings suggest that an ECA is an acceptable means to deliver T2D self-management education and support. A human-like character providing ongoing, friendly, nonjudgmental, emotional, and motivational support is well received. Nevertheless, the ECA can be improved by increasing congruence between its verbal and nonverbal communication and accommodating user preferences. CLINICALTRIAL Australian New Zealand Clinical Trials Registry CTRN12614001229662; https://tinyurl.com/yxshn6pd

show abstract

Predicting User Engagement in Longitudinal Interventions with Virtual Agents

Cited by 20 publications

References 28 publications

Engagement in Human-Agent Interaction: An Overview

Engagement in Human-Agent Interaction: An Overview

Gender Stereotypes in Virtual Agents

Acceptability of an Embodied Conversational Agent for Type 2 Diabetes Self-Management Education and Support via a Smartphone App: Mixed Methods Study (Preprint)

Contact Info

Product

Resources

About