The Workshop Program

Academia Keynote Speakers

Dr. Timothy Bickmore is a Professor and Associate Dean for Research in the Khoury College of Computer Sciences at Northeastern University in Boston. The focus of his research is on the development and evaluation of relational agents, virtual and robotic, that emulate face-to-face interactions between health providers and patients. These agents have been used in automated health education and long-term health behavior change interventions, spanning preventive medicine and wellness promotion, chronic disease management, inpatient care, substance misuse screening and treatment, mental health treatment, and palliative care. His systems have been evaluated in multiple clinical trials with results published in medical journals including JAMA and The Lancet. Prior to Northeastern, Dr. Bickmore served as an Assistant Professor of Medicine at the Boston University School of Medicine. Dr. Bickmore received his Ph.D. from MIT, doing his dissertation work in the Media Lab studying interactions between people and embodied conversational agents in task contexts, such as healthcare, in which social-emotional behavior can be used to improve outcomes.

Abstract:

Relational agents are computer agents designed to build and maintain long-term, social-emotional relationships with people, and are particularly effective for tasks in which long-term interactions and trust relationships are known to be important, such as in health counseling. When deployed on mobile devices, relational agents have the potential to not only develop strong therapeutic relationships with users, but to provide a ubiquitous channel for health education and behavior change for a variety of health conditions. In this talk I will focus on the challenges in deploying relational agents on mobile devices for health interventions, along with the unique affordances this combination of platform and medium provide. I will describe several mobile agent-based interventions my lab has developed and currently have in clinical trial, spanning chronic disease management for patients with atrial fibrillation, preconception care promotion for women in Lesotho, wellness promotion for members of predominately African American churches, and COVID vaccination promotion. I will also discuss design studies we have conducted that contrast agent-based interfaces with conventional GUI-based interfaces on smartphones for a variety of healthcare tasks.

Industry Keynote Speaker

Steve Downs is co-founder at Building H, a project to build health into everyday life by harnessing innovation to reimagine how we eat, sleep, get around, socialize and entertain ourselves — to be healthy by design. Previously, Steve was chief technology and strategy officer at Robert Wood Johnson Foundation (RWJF), where he led a transformation of the Foundation’s practice of program strategy. Steve held a variety of management roles at RWJF — including chief technology and information officer and leader of the foundation’s innovation portfolio — while funding and working directly with innovators at the intersection of tech and health.

Abstract:

The U.S. is in the midst of a chronic disease epidemic that’s been growing steadily over several decades. The epidemic is driven by gradual changes in lifestyles, which have been strongly influenced by gradual changes in our environments — and specifically in the environments created by consumer products and services — the cars, televisions, smartphones, packaged foods and restaurants — that shape our daily lives. Each generation of technology creates new products and services that maximize convenience and efficiency, and by doing so, makes it hard for people to live healthy lives. As new technologies emerge, there is plenty of innovation focused on applying them to address the consequences of the situation, but an important and largely untapped opportunity exists to harness new technologies to tackle the problem at its roots — to reimagine how everyday life could be healthy by design.

Schedule

This is the schedule of the workshop on March 21, 2022 (all times in EDT (New York)):

9:30 - 9:45 Opening Remarks

9:45 - 10:45 Paper session I:

Andy Alorwu et al. Initial Experiences with Longitudinal Self-Tracking of Sleep and Low Back Pain
Hyeseong Park et al. ReSmart-15 : An Information Gain based Questionnaire for Early Dementia Detection
Ravi Shankar. Challenges for Automation of Public Health Data Analysis

10:45 - 11:00 Coffee break

11:00 - 12:00 Industry Keynote: Steve Downs

12:00 - 13:00 Social lunch break

13:00 - 13:45 Paper session II

Joonas Moilanen et al. Designing Personalities for Mental Health Conversational Agents
Hye Sun Yun et al. Techno-spiritual Engagement: Mechanisms for Improving Uptake of mHealth Apps Designed for Church Members

13:45 - 14:00 Coffee break

14:00 - 15:00 Academic Keynote: Timothy Bickmore

15:00 - 16:00 Brainstorming session and closing remarks

Recordings of our keynote speakers have been published here.

Accepted Papers

The proceedings are published as part of the IUI workshop proceedings.

Full Paper:

Andy Alorwu, Aku Visuri, Simo Hosio. Initial Experiences with Longitudinal Self-Tracking of Sleep and Low Back Pain

Low Back Pain (LBP) is a leading cause of disability globally, making it a serious public health concern. In this paper we present the initial results and analysis of a longitudinal self-tracking study on sleep and LBP using a custom built mobile application. We designed and deployed a mobile app for a period of 7 months to collect daily and monthly sleep and low back pain data using custom and standardized questionnaires. We discuss the feasibility of our approach for longitudinal data collection. Our data analysis reveals heterogeneity in user perceptions of factors that affect their sleep and LBP. Combining our quantitative and qualitative analyses, we contribute to literature on sleep and LBP.

Joonas Moilanen, Aku Visuri, Elina Kuosmanen, Andy Alorwu and Simo Hosio. Designing Personalities for Mental Health Conversational Agents

In recent years, the use of conversational agents (CA) has been increasing at a rapid pace. Efforts have been made to leverage CAs for tackling mental health challenges. Our goal is to improve mental well-being by enabling self-help ideas through chat-based CAs. To enhance the effectiveness and user reception of CAs, we designed different conversational personalities with low and high variants of extroversion and conscientiousness. We used various language cues and example conversation scripts as the basis of our design process. This paper presents the design and validation process of such CA personalities. Our results indicate that the final personality characteristics presented in the scripts are recognizable

Hye Sun Yun, Shuo Zhou, Everlyne Kimani, Stefan Olafsson, Teresa K. O’LearyDhaval Parmar, Jessica Hoffman, Stephen Intille, Michael Paasche-Orlow and Timothy Bickmore. Techno-spiritual Engagement: Mechanisms for Improving Uptake of mHealth Apps Designed for Church Member

Keeping users engaged with mHealth applications is important but difficult to achieve. We describe the development of a smartphone-based application designed to promote health and wellness in church communities, along with mechanisms explicitly designed to maintain engagement. We evaluated religiously tailored techno-spiritual engagement mechanisms, including a prayer posting wall, pastor announcements, an embodied conversational agent for dialogue-based scriptural reflections and health coaching, and tailored push notifications. We conducted a four-week pilot study with 25 participants from two churches, measuring high levels of participant acceptance and satisfaction with all features of the application. Engagement with the app was higher for users considered to be more religious and correlated with the number of notifications received. Our findings demonstrate that our tailored mechanisms can increase engagement with an mHealth app.

Position Paper:

Hyeseong Park, Myung Won Raymond Jung, Ji-Hye Kim and Uran Oh. ReSmart-15 : An Information Gain based Questionnaire for Early Dementia Detection

To build an effective questionnaire for detecting early dementia, we propose ReSmart-15 which is a dementia detection questionnaire that includes daily behavior-based questions in five categories (i.e., attention (3Q), spatial ability (3Q), spatiotemporal ability (3Q), memory (3Q), and thinking ability (3Q)). As for the evaluation, we first collected responses from two different screening tests with 87 participants. Then we used a machine learning method called "information gain" ranking to show the effectiveness of ReSmart-15 compared to another representative screening test. As a result, we found that the top 2 questions were from ReSmart-15, and 60 percent of ReSmart-15 questions were in the top 10.

Ravi Shankar. Challenges for Automation of Public Health Data Analysis

Advancements in Machine Learning and Data Science are not adequately reflected in how public health data is handled today. There is a visible gap between the advances in computing and medical sciences. In this position paper, we present an example of data science applied to the automation of a repetitive process within a cervical cancer screening program. We discuss the challenges for automating public health data and share our insights to elevate artificial intelligence (AI) in public healthcare.

Page updated

Report abuse