arXiv subjects

Timothy Bickmore

Publications and source records attributed to Timothy Bickmore.

8 recordsLinked to original sources

arXiv2026

Designing for Adolescent Voice in Health Decisions: Embodied Conversational Agents for HPV Vaccination

Adolescents are directly affected by preventive health decisions such as vaccination, yet their perspectives are rarely solicited or supported. Most digital interventions for Human Papillomavirus (HPV) vaccination are designed exclusively for parents, implicitly treating adolescents as passive recipients rather than stakeholders with agency. We present the design and evaluation of a mobile intervention that gives adolescents a voice in HPV vaccination decisions alongside their parents. The system uses embodied conversational agents tailored to each audience: parents interact with an animated physician using education and motivational interviewing techniques, while adolescents can choose between an age-appropriate doctor or a narrative fantasy game that conveys HPV facts through play. We report findings from a clinic-based pilot study with 21 parent-adolescent dyads. Results indicate high satisfaction across both audiences, improved HPV knowledge, and increased intent to vaccinate. We discuss design implications for supporting adolescent participation, choice, and agency in decisions about their health.

cs.HC↗

arXiv2026

Relational Appliances: A Robot in the Refrigerator for Home-Based Health Promotion

Kitchen appliances are frequently used domestic artifacts situated at the point of everyday dietary decision making, making them a promising but underexplored site for health promotion. We explore the concept of relational appliances: everyday household devices designed as embodied social actors that engage users through ongoing, personalized interaction. We focus on the refrigerator, whose unique affordances, including a fixed, sensor-rich environment, private interaction space, and close coupling to food items, support contextualized, conversational engagement during snack choices. We present an initial exploration of this concept through a pilot study deploying an anthropomorphic robotic head inside a household refrigerator. In a home-lab apartment, participants repeatedly retrieved snacks during simulated TV "commercial breaks" while interacting with a human-sized robotic head. Participants were randomized to either a health-promotion condition, in which the robot made healthy snack recommendations, or a social-chat control condition. Outcomes included compliance with recommendations, nutritional quality of selected snacks, and psychosocial measures related to acceptance of the robot. Results suggest that participants found the robot persuasive, socially engaging, and increasingly natural over time, often describing it as helpful, aware, and companionable. Most participants reported greater awareness of their snack decisions and expressed interest in having such a robot in their own home. We discuss implications for designing relational appliances that leverage anthropomorphism, trust, and long-term human-technology relationships for home-based health promotion.

cs.HC↗

arXiv2025

HealthDial: A No-Code LLM-Assisted Dialogue Authoring Tool for Healthcare Virtual Agents

We introduce HealthDial, a dialogue authoring tool that helps healthcare providers and educators create virtual agents that deliver health education and counseling to patients over multiple conversations. HealthDial leverages large language models (LLMs) to automatically create an initial session-based plan and conversations for each session using text-based patient health education materials as input. Authored dialogue is output in the form of finite state machines for virtual agent delivery so that all content can be validated and no unsafe advice is provided resulting from LLM hallucinations. LLM-drafted dialogue structure and language can be edited by the author in a no-code user interface to ensure validity and optimize clarity and impact. We conducted a feasibility and usability study with counselors and students to test our approach with an authoring task for cancer screening education. Participants used HealthDial and then tested their resulting dialogue by interacting with a 3D-animated virtual agent delivering the dialogue. Through participants' evaluations of the task experience and final dialogues, we show that HealthDial provides a promising first step for counselors to ensure full coverage of their health education materials, while creating understandable and actionable virtual agent dialogue with patients.

cs.HC↗

arXiv2025

Balancing Efficiency and Empathy: Healthcare Providers' Perspectives on AI-Supported Workflows for Serious Illness Conversations in the Emergency Department

Serious Illness Conversations (SICs), discussions about values and care preferences for patients with life-threatening illness, rarely occur in Emergency Departments (EDs), despite evidence that early conversations improve care alignment and reduce unnecessary interventions. We interviewed 11 ED providers to identify challenges in SICs and opportunities for technology support, with a focus on AI. Our analysis revealed a four-stage SIC workflow (identification, preparation, conduction, documentation) and barriers at each stage, including fragmented patient information, limited time and space, lack of conversational guidance, and burdensome documentation. Providers expressed interest in AI systems for synthesizing information, supporting real-time conversations, and automating documentation, but emphasized concerns about preserving human connection and clinical autonomy. This tension highlights the need for technologies that enhance efficiency without undermining the interpersonal nature of SICs. We propose design guidelines for ambient and peripheral AI systems to support providers while preserving the essential humanity of these conversations.

cs.HC↗

arXiv2024

Virtual Agent-Based Communication Skills Training to Facilitate Health Persuasion Among Peers

Many laypeople are motivated to improve the health behavior of their family or friends but do not know where to start, especially if the health behavior is potentially stigmatizing or controversial. We present an approach that uses virtual agents to coach community-based volunteers in health counseling techniques, such as motivational interviewing, and allows them to practice these skills in role-playing scenarios. We use this approach in a virtual agent-based system to increase COVID-19 vaccination by empowering users to influence their social network. In a between-subjects comparative design study, we test the effects of agent system interactivity and role-playing functionality on counseling outcomes, with participants evaluated by standardized patients and objective judges. We find that all versions are effective at producing peer counselors who score adequately on a standardized measure of counseling competence, and that participants were significantly more satisfied with interactive virtual agents compared to passive viewing of the training material. We discuss design implications for interpersonal skills training systems based on our findings.

cs.HC↗

arXiv2024

Investigating User Perceptions of Collaborative Agenda Setting in Virtual Health Counseling Session

Virtual health counselors offer the potential to provide users with information and counseling in complex areas such as disease management and health education. However, ensuring user engagement is challenging, particularly when the volume of information and length of counseling sessions increase. Agenda setting a clinical counseling technique where a patient and clinician collaboratively decide on session topics is an effective approach to tailoring discussions for individual patient needs and sustaining engagement. We explore the effectiveness of agenda setting in a virtual counselor system designed to counsel women for breast cancer genetic testing. In a between subjects study, we assessed three versions of the system with varying levels of user control in the system's agenda setting approach. We found that participants' knowledge improved across all conditions. Although our results showed that any type of agenda setting was perceived as useful, regardless of user control, interviews revealed a preference for more collaboration and user involvement in the agenda setting process. Our study highlights the importance of using patient-centered approaches, such as tailored discussions, when using virtual counselors in healthcare.

cs.HC↗

arXiv2024

Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents

We introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion includes listener empathy for the speaker's affective state. Empathic grounding is generally required whenever the speaker's emotions are foregrounded and can make the grounding process more efficient and reliable by communicating both propositional and affective understanding. Both speaker expressions of affect and listener empathic grounding can be multimodal, including facial expressions and other nonverbal displays. Thus, models of empathic grounding for embodied agents should be multimodal to facilitate natural and efficient communication. We describe a multimodal model that takes as input user speech and facial expression to generate multimodal grounding moves for a listening agent using a large language model. We also describe a testbed to evaluate approaches to empathic grounding, in which a humanoid robot interviews a user about a past episode of pain and then has the user rate their perception of the robot's empathy. We compare our proposed model to one that only generates non-affective grounding cues in a between-subjects experiment. Findings demonstrate that empathic grounding increases user perceptions of empathy, understanding, emotional intelligence, and trust. Our work highlights the role of emotion awareness and multimodality in generating appropriate grounding moves for conversational agents.

cs.HC↗

arXiv2023

Keeping Users Engaged During Repeated Administration of the Same Questionnaire: Using Large Language Models to Reliably Diversify Questions

Standardized, validated questionnaires are vital tools in research and healthcare, offering dependable self-report data. Prior work has revealed that virtual agent-administered questionnaires are almost equivalent to self-administered ones in an electronic form. Despite being an engaging method, repeated use of virtual agent-administered questionnaires in longitudinal or pre-post studies can induce respondent fatigue, impacting data quality via response biases and decreased response rates. We propose using large language models (LLMs) to generate diverse questionnaire versions while retaining good psychometric properties. In a longitudinal study, participants interacted with our agent system and responded daily for two weeks to one of the following questionnaires: a standardized depression questionnaire, question variants generated by LLMs, or question variants accompanied by LLM-generated small talk. The responses were compared to a validated depression questionnaire. Psychometric testing revealed consistent covariation between the external criterion and focal measure administered across the three conditions, demonstrating the reliability and validity of the LLM-generated variants. Participants found that the variants were significantly less repetitive than repeated administrations of the same standardized questionnaire. Our findings highlight the potential of LLM-generated variants to invigorate agent-administered questionnaires and foster engagement and interest, without compromising their validity.

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