Laura M. Pfeifer

Taking the time to care: empowering low health literacy hospital patients with virtual nurse agents

Ninety million Americans have inadequate health literacy, resulting in a reduced ability to read and follow directions in the healthcare environment. We describe an animated, empathic virtual nurse interface for educating and counseling hospital patients with inadequate health literacy in their hospital beds at the time of discharge. The development methodology, design rationale, and two iterations of user testing are described. Results indicate that hospital patients with low health literacy found the system easy to use, reported high levels of satisfaction, and most said they preferred receiving the discharge information from the agent over their doctor or nurse. Patients also expressed appreciation for the time and attention provided by the virtual nurse, and felt that it provided an additional authoritative source for their medical information.

Using Computer Agents to Explain Medical Documents to Patients with Low Health Literacy

OBJECTIVE Patients are commonly presented with complex documents that they have difficulty understanding. The objective of this study was to design and evaluate an animated computer agent to explain research consent forms to potential research participants. METHODS Subjects were invited to participate in a simulated consent process for a study involving a genetic repository. Explanation of the research consent form by the computer agent was compared to explanation by a human and a self-study condition in a randomized trial. Responses were compared according to level of health literacy. RESULTS Participants were most satisfied with the consent process and most likely to sign the consent form when it was explained by the computer agent, regardless of health literacy level. Participants with adequate health literacy demonstrated the highest level of comprehension with the computer agent-based explanation compared to the other two conditions. However, participants with limited health literacy showed poor comprehension levels in all three conditions. Participants with limited health literacy reported several reasons, such as lack of time constraints, ability to re-ask questions, and lack of bias, for preferring the computer agent-based explanation over a human-based one. CONCLUSION Animated computer agents can perform as well as or better than humans in the administration of informed consent. PRACTICE IMPLICATIONS Animated computer agents represent a viable method for explaining health documents to patients.

Usability of Conversational Agents by Patients with Inadequate Health Literacy: Evidence from Two Clinical Trials

Embodied Conversational Agents (ECA) are computer-animated characters that simulate face-to-face conversation with patients. These agents can be programmed with best practices in human-human health communication and used for automated health education and behavior change counseling interventions. Evidence is presented from two ongoing clinical trials demonstrating that patients at different levels of health literacy find these agents acceptable and easy to use for automated health communication interventions. Innovative computer interface systems can be used to ensure that inadequate health literacy not serve as a barrier to interventions using health information technology.

Maintaining reality: Relational agents for antipsychotic medication adherence

We describe an animated, conversational computer agent designed to promote antipsychotic medication adherence among patients with schizophrenia. In addition to medication adherence, the agent also promotes physical activity and system usage, and includes verbal and nonverbal behavior designed to foster a therapeutic alliance with patients. We discuss special considerations in designing interventions for this patient population, and challenges in developing and evaluating conversational agents in the mental health domain. Results from a pilot evaluation study of the agent indicate that it is accepted and effective.

Health Document Explanation by Virtual Agents

We describe the design and evaluation of a virtual agent that explains health documents to patients. The prevalence and impact of low health literacy is presented as a motivation for such agents, given that face-to-face interaction with health providers is cited as one of the most effective means of communicating with these patients. We analyze the form and distribution of pointing gestures used by experts in explaining health documents, and use this data to develop a computational model of agent-based document explanation. This model is evaluated in a randomized controlled trial. Preliminary results indicate that patients with low health literacy are more satisfied with health document explanation by a virtual agent compared to a human.

Response to a relational agent by hospital patients with depressive symptoms

Depression affects approximately 15% of the US population, and is recognized as an important risk factor for poor outcomes among patients with various illnesses. Automated health education and behavior change programs have the potential to help address many of the shortcomings in health care. However, the role of these systems in the care of patients with depression has been insufficiently examined. In the current study, we sought to evaluate how hospitalized medical patients would respond to a computer animated conversational agent that has been developed to provide information in an empathic fashion about a patients hospital discharge plan. In particular, we sought to examine how patients who have a high level of depressive symptoms respond to this system. Therapeutic alliance-the trust and belief that a patient and provider have in working together to achieve a desired therapeutic outcome- was used as the primary outcome measure, since it has been shown to be important in predicting outcomes across a wide range of health problems, including depression. In an evaluation of 139 hospital patients who interacted with the agent at the time of discharge, all patients, regardless of depressive symptoms, rated the agent very high on measures of satisfaction and ease of use, and most preferred receiving their discharge information from the agent compared to their doctors or nurses in the hospital. In addition, we found that patients with symptoms indicative of major depression rated the agent significantly higher on therapeutic alliance compared to patients who did not have major depressive symptoms. We conclude that empathic agents represent a promising technology for patient assessment, education and counseling for those most in need of comfort and caring in the inpatient setting.

THE ROLE OF GESTURE IN DOCUMENT EXPLANATION BY EMBODIED CONVERSATIONAL AGENTS

We describe two empirical studies of how professionals explain documents to lay clients who have varying levels of knowledge about the domain under discussion. We find that hand gestures, and in particular deictic gestures by the professional at various parts of the document play a major role in explanations of documents with clients in face-to-face settings. We describe a preliminary computational model of document explanation by an embodied conversational agent, in which appropriate form and location of hand gestures are used by the agent in explaining a document to a user. Results from a pilot evaluation study indicate that individuals with low levels of domain knowledge prefer receiving explanations from such an agent rather than from a human. Examples are drawn from the healthcare domain, in which research consent forms and hospital discharge instruction forms are used as the documents being explained, and health literacy is used as the measure of client domain knowledge.

Public displays of affect: deploying relational agents in public spaces

Design principles for deploying agents designed for social and relational interactions with users in public spaces are discussed. These principles are applied to the development of a virtual science museum guide agent that uses human relationship-building behaviors to engage visitors. The agent appears in the form of a human-sized anthropomorphic robot, and uses nonverbal conversational behavior, empathy, social dialogue, reciprocal self-disclosure and other relational behavior to establish social bonds with users. The agent also uses a biometric identification system so that it can re-identify visitors it has already talked to. Results from a preliminary study indicate that most users enjoy the conversational and relational interaction with the agent.

Should Agents Speak Like, um, Humans? The Use of Conversational Fillers by Virtual Agents

We describe the design and evaluation of an agent that uses the fillers um and uh in its speech. We describe an empirical study of human-human dialogue, analyzing gaze behavior during the production of fillers and use this data to develop a model of agent-based gaze behavior. We find that speakers are significantly more likely to gaze away from their dialogue partner while uttering fillers, especially if the filler occurs at the beginning of a speaking turn. This model is evaluated in a preliminary experiment. Results indicate mixed attitudes towards an agent that uses conversational fillers in its speech.