Christine Lisetti
Skip Abstract Section
Abstract
We discuss our approach to developing a novel modality for the computer-delivery of Brief Motivational Interventions (BMIs) for behavior change in the form of a personalized On-Demand VIrtual Counselor (ODVIC), accessed over the internet. ODVIC is a multimodal Embodied Conversational Agent (ECA) that empathically delivers an evidence-based behavior change intervention by adapting, in real-time, its verbal and nonverbal communication messages to those of the user’s during their interaction. We currently focus our work on excessive alcohol consumption as a target behavior, and our approach is adaptable to other target behaviors (e.g., overeating, lack of exercise, narcotic drug use, non-adherence to treatment). We based our current approach on a successful existing patient-centered brief motivational intervention for behavior change---the Drinker’s Check-Up (DCU)---whose computer-delivery with a text-only interface has been found effective in reducing alcohol consumption in problem drinkers. We discuss the results of users’ evaluation of the computer-based DCU intervention delivered with a text-only interface compared to the same intervention delivered with two different ECAs (a neutral one and one with some empathic abilities). Users rate the three systems in terms of acceptance, perceived enjoyment, and intention to use the system, among other dimensions. We conclude with a discussion of how our positive results encourage our long-term goals of on-demand conversations, anytime, anywhere, with virtual agents as personal health and well-being helpers.
- Ambady, N. and Rosenthal, R. 1992. Thin slices of expressive behavior as predictors of interpersonal consequences: A meta-analysis. Psychol. Bull. 111, 2, 256--274.Google Scholar
Cross Ref
- Amini, R. and Lisetti, C. 2013. HapFACS: An open source API / software to generate FACS-based expressions for ECAs animation and for corpus generation. In Proceedings of the 5th Biannual Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII’13). IEEE Computer Society. Google ScholarDigital Library
- Amini, R., Lisetti, C., Yasavur, U., and Rishe, N. 2013. On-demand virtual health counselor for delivering behavior-change health interventions. In Proceedings of the IEEE International Conference on Healthcare Informatics (ICHI’13). IEEE. Google ScholarDigital Library
- Aylett, R., Vala, M., Sequeira, P., and Paiva, A. 2007. FearNot! An emergent narrative approach to virtual dramas for anti-bullying education. In Proceedings of the 4th International Conference on Virtual Storytelling Using Virtual Reality Technologies for Storytelling. Lecture Notes in Computer Science, vol. 4871. Springer-Verlag, Berlin Heidelberg, 202--205. Google ScholarDigital Library
- Babor, T. F. and Grant, M. 1992. Programme on substance abuse: Project on identification and management of alcohol-related problems. Report on Phase II, an randomized clinical trial of brief interventions in primary health care. Tech. rep. World Health Organization.Google Scholar
- Babor, T. F., Higgins-Biddle, J. C., Saunders, J. B., and Monteiro, M. G. 2001. AUDIT: The Alcohol Use Disorders Identification Test. Guidelines for Use in Primary Health Care 2nd Ed. World Health Organization, Department of Mental Health and Substance Dependence.Google Scholar
- Bartneck, C., Kulic, D., and Croft, E. 2008. Measuring the anthropomorphism, animacy, likeability, perceived intelligence and perceived safety of robots. In Proceedings of the Metrics for Human-Robot Interaction Workshop in Affiliation with the 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI’08). Vol. 471, 37--44.Google Scholar
- Bavelas, J. B., Black, A., Lemery, C. R., and Mullett, J. 1986. “I show how you feel”---Motor mimicry as a communicative act. J. Personal. Social Psychol. 50, 2, 322--329.Google ScholarCross Ref
- Bewick, B. M., Trusler, K., Barkham, M., Hill, A. J., Cahill, J., and Mulhern, B. 2008. The effectiveness of Web-based interventions designed to decrease alcohol consumption---A systematic review. Prevent. Med. 47, 1, 17--26.Google ScholarCross Ref
- Bickmore, T. and Giorgino, T. 2006. Methodological review: Health dialog systems for patients and consumers. J. Biomed. Inform. 39, 5, 465--467.Google ScholarDigital Library
- Bickmore, T., Gruber, A., and Picard, R. 2005. Establishing the computer---Patient working alliance in automated health behavior change interventions. Patient Ed. Counsel. 59, 21--30.Google ScholarCross Ref
- Bickmore, T. W. and Picard, R. W. 2005. Establishing and maintaining long-term human-computer relationships. ACM Trans. Comput.-Hum. Interact. (TOCHI) 12, 2, 617--638. Google ScholarDigital Library
- Bickmore, T. W., Pfeifer, L. M., and Jack, B. W. 2009. Taking the time to care: Empowering low health literacy hospital patients with virtual nurse agents. In Proceedings of the 27th International ACM Conference on Human Factors in Computing Systems (CHI’09). ACM, New York, 1265--1274. Google ScholarDigital Library
- Bien, T. H., Miller W. R., and Tonigan, J. S. 1993. Brief interventions for alcohol problems: A review. Addiction 88, 315--336.Google ScholarCross Ref
- Botelho, R. 2004. Motivational Practice: Promoting Healthy Habits And Self-care Of Chronic Diseases. MHH Publications.Google Scholar
- Boukricha, H. and Becker-Asano, C. 2007. Simulating empathy for the virtual human max. In Proceedings of the 2nd Workshop at KI2007 on Emotion and Computing -- Current Research and Future Impact, Dirk Reichardt and P. Levi Eds., 23--28.Google Scholar
- Boukricha, H. and Wachsmuth, I. 2011. Empathy-based emotional alignment for a virtual human: A three-step approach. KI - Künstliche Intelligenz 25, 3, 195--204.Google ScholarCross Ref
- Boukricha, H., Wachsmuth, I., Hofstatter, A., and Grammer, K. 2009. Pleasure-arousal-dominance driven facial expression simulation. In Proceedings of the Interaction and Workshops of the 3rd International Conference on Affective Computing and Intelligent (ACII’09). IEEE, 1--7.Google Scholar
- Brug, J., Steenhuis, I., Van Assema, P., and De Vries, H. 1996. The impact of a computer-tailored nutrition intervention. Prevent. Med. 25, 3, 236--242.Google ScholarCross Ref
- Burke, B. L., Arkowitz, H., and Dunn, C. 2002. The efficacy of motivational interviewing and its adaptation. In Motivational Interviewing: Preparing People for Change 2nd Ed. Guilford Press, New-York, NY, 217--250.Google Scholar
- Cassell, J. and Bickmore, T. 2003. Negotiated collusion: Modeling social language and its relationship effects in intelligent agents. User Model. User Adapt. Interact. 13, 1--2, 89--132. Google ScholarDigital Library
- Cassell, J., Sullivan, J., Prevost, S., and Churchill, E. F. 2000. Embodied conversational agents. Social Psychol. 40, 1, 26--36.Google Scholar
- Catrambone, R., Stasko, J., and Xiao, J. 2004. ECA as User Interface Paradigm: Experimental findings within a framework for research. In From Brows to Trust: Evaluating Embodied Conversational Agents, Z. Ruttkay and C. Pelachaud Eds., Kluwer Academic Publishers, Chapter 9, 239--267. Google ScholarDigital Library
- Chartrand, T. L. and Bargh, J. A. 1999. The chameleon effect: The perception-behavior link and social interaction. J. Personal. Social Psychol. 76, 6, 893--910.Google ScholarCross Ref
- Cunningham, J. A., Humphreys, K., and Koski-Jannes, A. 1999. Providing personalized assessment feedback for problem drinking on the Internet. In Proceedings of the 33rd Annual Convention of the Association for the Advancement of Behavior Therapy.Google Scholar
- Davis, G., Gray, P., Madnick, S., Nunamaker, J., Sprague, R., and Whinston, A. 2010. Ideas for the future of the is field. ACM Trans. Manage. Inform. Syst. 1, 1, 2--15. Google ScholarDigital Library
- Doherty, Y., Hall, D., James, P. T., Roberts, S. H., and Simpson, J. 2000. Change counselling in diabetes: The development of a training programme for the diabetes team. Patient Ed. Counsel. 40, 263--278.Google ScholarCross Ref
- Dunn, C., Deroo, L., and Rivara, F. 2001. The use of brief interventions adapted from motivational interviewing across behavioral domains: A systematic review. Addiction 96, 12, 1725--42.Google ScholarCross Ref
- Dunn, T. L., Casey, L. M., Sheffield, J., Newcombe, P., and Chang, A. B. 2012. Dropout from computer-based interventions for children and adolescents with chronic health conditions. J. Health Psychol. 17, 3, 429--42.Google ScholarCross Ref
- Ehrlich, S., Schiano, D., and Sheridan, K. 2000. Communicating facial affect: It’s not the realism, it’s the motion. In Proceedings of the Extended Abstracts on Human Factors in Computing Systems (CHI’00). ACM Press, NY. Google ScholarDigital Library
- Ekman, P. and Freisen, W. V. 1978. Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press.Google Scholar
- Emmons, K. M. and Rollnick, S. 2001. Motivational interviewing in health care settings. Opportunities and limitations. Am. J. Prevent. Med. 20, 1, 68--74.Google ScholarCross Ref
- Friesen, W. V. and Ekman, P. 1983. EMFACS-7: Emotional Facial Action Coding System. Unpublished manuscript, University of California at San Francisco.Google Scholar
- Goldstein, A. P. and Michaels, G. Y. 1985. Empathy: Development, Training, and Consequences 1st Ed. L. Erlbaum Associates, Hillsdale, NJ.Google Scholar
- Gratch, J. and Marsella, S. C. 2004. A domain-independent framework for modeling emotion. Cognitive Syst. Res. 5, 4, 269--306. Google ScholarDigital Library
- Gratch, J., Okhmatovskaia, A., Lamothe, F., Marsella, S., Morales, M., van der Werf, R. J., and Morency L.-P. 2006. Virtual rapport. In Proceedings of the 6th International Conference on Intelligent Virtual. Lecture Notes in Computer Science, vol. 4133, Springer-Verlag, Berlin Heidelberg, 14--27. Google ScholarDigital Library
- Gratch, J., Wang, N., Gerten, J., Fast, E., and Duffy, R. 2007a. Creating rapport with virtual agents. In Proceedings of the 7th International Conference on Intelligent Virtual Agents. Lecture Notes in Computer Science, vol. 4722, Springer-Verlag, Berlin Heidelberg, 125--138. Google ScholarDigital Library
- Gratch, J., Wang, N., Okhmatovskaia, A., Lamothe, F., Marsella, S., Morales, M., van der Werf, R. J., and Morency, L.-P. 2007b. Can virtual humans be more engaging than real ones? In Proceedings of the 12th International Conference on Human-Computer Interaction: Intelligent Multimodal Interaction Environments (HCI’07). Lecture Notes in Computer Science, vol. 4552. Springer-Verlag, Berlin Heidelberg. 286--297. Google ScholarDigital Library
- Heerink, M., Krose, B., Evers, V., and Wielinga, B. 2009. Measuring acceptance of an assistive social robot: a suggested toolkit. In Proceedings of the 18th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN’09). IEEE, 528--533.Google Scholar
- Hester, R. K. and Delaney, H. 1997. Behavioral self-control program for windows: Results of a controlled clinical trial. J. Consult. Clin. Psychol. 65, 685--693.Google ScholarCross Ref
- Hester, R. K., Squires, D. D., and Delaney, H. D. 2005. The Drinker’s Check-up: 12-month outcomes of a controlled clinical trial of a stand-alone software program for problem drinkers. J. Substance Abuse Treat. 28, 2, 159--169.Google ScholarCross Ref
- Hojat, M. 2007. Empathy in Patient Care: Antecedents, Development, Measurement, and Outcomes. Springer, New York, NY.Google Scholar
- Huang, L., Morency, L.-P., and Gratch, J. 2011. Virtual Rapport 2.0. In Proceedings of the International Conference on Intelligent Virtual Agents, Intelligence. Lecture Notes in Computer Science, vol. 6895. Springer-Verlag, Berlin Heidelberg, 68--79. Google ScholarDigital Library
- Johnson, W. and LaBore, C. 2004. A pedagogical agent for psychosocial intervention on a handheld computer. In Proceedings of the AAAI Fall Symposium on Dialogue Systems for Health Communication. 22--24.Google Scholar
- Kang, S.-H., Gratch, J., Wang, N., and Watt, J. 2008a. Agreeable people like agreeable virtual humans. In Proceedings of the 8th International Conference on Intelligent Virtual Agents. Lecture Notes in Computer Science, vol. 5208. Springer-Verlag, Berlin Heidelberg, 253--261. Google ScholarDigital Library
- Kang, S.-H., Gratch, J., Wang, N., and Watt, J. 2008b. Does the contingency of agents’ nonverbal feedback affect users’ social anxiety? In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems. Vol. 1. Number Aamas. International Foundation for Autonomous Agents and Multiagent Systems, 120--127. Google ScholarDigital Library
- Kluwer, T. 2011. “I like your shirt”---Dialogue acts for enabling social talk in conversational agents. In Proceedings of the 10th International Conference on Intelligent Virtual Agents, H. Vihjalmsson, S. Kopp, S. Marsella, and K. R. Thorisson Eds., Lecture Notes in Computer Science, vol. 6895. Springer-Verlag, Berlin Heidelberg, 14--27. Google ScholarDigital Library
- Lafrance, M. 1979. Nonverbal synchrony panel technique: Analysis by the cross-lag and rapport. Social Psychol. 42, 1, 66--70.Google ScholarCross Ref
- Lafrance, M. and Broadbent, M. 1976. Group rapport: Posture sharing as a nonverbal indicator. Group Org. Manag. 1, 3, 328--333.Google ScholarCross Ref
- Lakin, J. L., Jefferis, V., and Cheng, C. 2003. The chameleon effect as social glue: Evidence for the evolutionary significance of nonconscious mimicry. J. Nonverbal Behav. 27, 3, 145--162.Google ScholarCross Ref
- Lisetti, C. L. 2008. Embodied conversational agents for psychotherapy. In Proceedings of the Conference Workshop on Technology in Mental Health (CHI’08). ACM, 1--12.Google Scholar
- Lisetti, C. L. 2009. Features for culturally appropriate avatars for behavior-change promotion in at-risk populations. Stud. Health Technol. Inform. 144, 22--26.Google Scholar
- Lisetti, C. L. 2012. 10 advantages of using avatars in patient-centered computer-based interventions for behavior change. In Proceedings of the International Health Informatics Symposium (IHI’12).Google ScholarDigital Library
- Lisetti, C. L. and Wagner, E. 2008. Mental health promotion with animated characters: Exploring issues and potential. In Proceedings of the AAAI Spring Symposium on Emotion, Personality and Social Behavior.Google Scholar
- Lisetti, C. L., Yasavur, U., Leon, C. D., Amini, R., and Rishe, N. 2012. Building an on-demand avatar-based health intervention for behavior change. In Proceedings of the Florida Artificial Intelligence Research Society Conference in cooperation with the Association for the Advancement of Artificial Intelligence (FLAIRS’12).Google Scholar
- Magerko, B., Dean, J., Idnani, A., Pantalon, M., and Onofrio, G. D. 2011. Dr. Vicky : A virtual coach for learning brief negotiated interview techniques for treating emergency room patients. In Proceedings of the Spring Symposium on Association for the Advancement of Artificial Intelligence (AAAI). 25--32.Google Scholar
- McQuiggan, S. and Lester, J. 2007. Modeling and evaluating empathy in embodied companion agents. Int. J. Hum.-Comput. Stud. 65, 348--360. Google ScholarDigital Library
- McQuiggan, S. W., Robison, J., and Phillips, R. 2008. Modeling parallel and reactive empathy in virtual agents: An inductive approach. In Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’08). International Foundation for Autonomous Agents and Multiagent Systems. 167--174. Google ScholarDigital Library
- Miller, W. and Sanchez, B. 1994. Motivating young adults for treatment and lifestyle change. In Alcohol Use and Misuse by Young Adults, University of Notre Dame Press, 55--81.Google Scholar
- Miller, W., Sovereign, R., and Krege, B. 1988. Motivational interviewing with problem drinkers: II. The drinker’s check-up as a preventive intervention. Behav. Psychotherapy 16, 251--268.Google ScholarCross Ref
- Miller, W. R. and Rollnick, S. 2002. Motivational Interviewing: Preparing People for Change 2nd Ed. Vol. 2. Guilford Press, New York.Google Scholar
- Miller, W. R. and Rose, G. S. 2009. Toward a theory of motivational interviewing. Am. Psychol. 64, 6, 527--537.Google ScholarCross Ref
- National Center for Chronic Prevention and Health Promotion. 2011. Excessive alcohol use at a glance: Addressing a leading risk for death, chronic disease, and injury. Tech. rep., National Center for Chronic Prevention and Health Promotion.Google Scholar
- Neuhauser, L. and Kreps, G. 2011. Participatory design and artificial intelligence: Strategies to improve health communication for diverse audiences. In Proceedings of the Spring Symposium on AI and Health Communication AAAI.Google Scholar
- Nguyen, H. and Masthoff, J. 2009. Designing empathic computers: The effect of multimodal empathic feedback using animated agent. In Proceedings of the 4th International Conference on Persuasive Technology (Persuasive’09). ACM. Google ScholarDigital Library
- NIAAA. 1998. Matching alcoholism treatments to client heterogeneity: Project MATCH three-year drinking outcomes. Alcohol.: Clin. Exp. Res. 23, 60, National Institute on Alcohol Abuse and Alcoholism, 1300--1311.Google Scholar
- Noar, S. M., Benac, C. N., and Harris, M. S. 2007. Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychol. Bull. 133, 4, 673--693.Google ScholarCross Ref
- Ochs, M., Sadek, D., and Pelachaud, C. 2012. A formal model of emotions for an empathic rational dialog agent. Auton. Agents Multi-Agent Syst. 24, 3, 410--440. Google ScholarDigital Library
- Ortony, A., Clore, G. L., and Collins, A. 1988. The Cognitive Structure of Emotions. Vol. 18. Cambridge University Press.Google Scholar
- Pelachaud, C. 2009. Modelling multimodal expression of emotion in a virtual agent. Philos. Trans. Royal Soc. London. Series B, Biol. Sci. 364, 1535, 3539--48.Google ScholarCross Ref
- Portnoy, D. B., Scott-Sheldon, L. A. J., Johnson, B. T., and Carey, M. P. 2008. Computer-delivered interventions for health promotion and behavioral risk reduction: A meta-analysis of 75 randomized controlled trials, 1988-2007. Preven. Med. 47, 1, 3--16.Google ScholarCross Ref
- Prendinger, H. and Ishizuka, M. 2005. The empathic companion - A character-based interface that addresses users’ affective states. Appl. Artifi. Intell. 19, 3--4, 267--286.Google ScholarCross Ref
- Prochaska, J. O. and Velicer, W. F. 1997. The transtheoretical model of health behavior change. Am. J. Health Promotion 12, 1, 38--48.Google ScholarCross Ref
- Reeves, B. and Nass, C. 1996. The Media Equation: How People Treat Computers, Television, and New Media Like Real People and Places. University of Chicago Press. Google ScholarDigital Library
- Resnicow, K., Soler, R., Braithwaite, R. L., Ahluwalia, J. S., and Butler, J. 2000. Cultural sensitivity in substance use prevention. J. Commun. Psychol. 28, 271--290.Google ScholarCross Ref
- Rogers, C. R. 1959. A Theory of Therapy, Personality and Interpersonal Relationships as Developed in the Client-Centered Framework.Google Scholar
- Schulman, D., Bickmore, T., and Sidner, C. 2011. An intelligent conversational agent for promoting long-term health behavior change using motivational interviewing. In Proceedings of the AAAI 2011 Spring Symposium. 61--64.Google Scholar
- Servan-Schreiber, D. 1986. Artificial intelligence and psychiatry. J. Nervous Mental Disease 174, 191--202.Google ScholarCross Ref
- Silverman, B. G., Holmes, J., Kimmel, S., Branas, C., Ivins, D., Weaver, R., and Chen, Y. 2001. Modeling emotion and behavior in animated personas to facilitate human behavior change: The case of the HEART-SENSE game. Healthcare Manag. Sci. 4, 3, 213--28.Google ScholarCross Ref
- Skinner, H. A. 1994. Computerized Lifestyle Assessment: Background Research. Addition Research Foundation.Google Scholar
- Sonnby-borgström, M., Jonsson, P., and Svensson, O. 2003. Emotional empathy as related to mimicry reactions at different levels of information processing. J. Nonverbal Behav. 27, 1, 3--23.Google ScholarCross Ref
- Squires, D. D. and Hester, R. K. 2004. Using technical innovations in clinical practice: The Drinker’s Check-Up software program. J. Clin. Psychol. 60, 2, 159--69.Google ScholarCross Ref
- Swanson, A. J., Pantalon, M. V., and Cohen, K. R. 1999. Motivational interviewing and treatment adherence among psychiatric and dually diagnosed patients. J. Nervous Mental Disease 187, 630--635.Google ScholarCross Ref
- Taigman, Y. and Wolf, L. 2011. Leveraging billions of faces to overcome performance barriers in unconstrained face recognition. arXiv:1108.1122.Google Scholar
- van Baaren, R. B., Holland, R. W., Kawakami, K., and Knippenberg, A. V. 2004. Mimicry and Prosocial Behavior. Psychol. Sci. 15, 1, 71--74.Google Scholar
- Vernon, M. 2010. A review of computer-based alcohol problem services designed for the general public. J. Substance Abuse Treat. 38, 3, 203--211.Google ScholarCross Ref
- von der Pütten, A. M. V. D., Krämer, N. C., and Gratch, J. 2009. Who’s there? Can a virtual agent really elicit social presence? In Proceedings of the 12th Annual International Workshop on Presence.Google Scholar
- Wang, N. and Gratch, J. 2009. Rapport and facial expression. In Proceedings of the 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops (ACII’09). IEEE, 1--6.Google Scholar
- Wang, N. and Gratch, J. 2010. Don’t just stare at me! In Proceedings of the 28th ACM Conference on Human Factors in Computing Systems (CHI’10). ACM, 1241--1249. Google ScholarDigital Library
- White, A., Kavanagh, D., Stallman, H., Klein, B., Kay-Lambkin, F., Proudfoot, J., Drennan, J., Connor, J., Baker, A., Hines, E., and Young, R. 2010. Online alcohol interventions: A systematic review. J. Med. Internet Res. 12, 5, e62.Google ScholarCross Ref
- WHO. 2011. Obesity and overweight. World Health Organization.Google Scholar
- Wierzbicki, M. and Pekarik, G. 1993. A meta-analysis of psychotherapy dropout. Profess. Psychol. Res. Prac. 24, 2, 190--195.Google ScholarCross Ref
- Wispé, L. 1987. History of the concept of empathy. In Empathy and Its Development, N. Einsenberg and J. Strayer Eds., Cambridge University Press, Chapter 2, 17--37.Google Scholar
- Wolf, L., Hassner, T., and Taigman, Y. 2010. Effective unconstrained face recognition by combining multiple descriptors and learned background statistics. IEEE Trans. Pattern Anal. Machine Intell. 33, 1--13. Google ScholarDigital Library
- Yasavur, U., Lisetti, C., and Rishe, N. 2013. Modeling brief alcohol intervention dialogue with MDPs for delivery by ECAs. In Proceedings of the 13th International Conference on Intelligent Virtual Agents (IVA’13). Lecture Notes in Computer Science, vol. 8108. Springer-Verlag, Berlin Heidelberg. 92--105.Google Scholar
Index Terms
- I Can Help You Change! An Empathic Virtual Agent Delivers Behavior Change Health Interventions
Recommendations
Motivating Health Behavior Change with Humorous Virtual Agents
IVA '20: Proceedings of the 20th ACM International Conference on Intelligent Virtual AgentsResearch on the psychology of humor indicates that humor can increase the impact of persuasive messages in certain circumstances, suggesting that virtual agents could use humor to improve the effectiveness of motivational counseling with users. To ...
On-Demand Virtual Health Counselor for Delivering Behavior-Change Health Interventions
ICHI '13: Proceedings of the 2013 IEEE International Conference on Healthcare InformaticsIn this paper, we discuss a novel approach for the computer-delivery of Brief Motivational Interventions (BMIs) for health behavior change. We describe the basic elements of our system architecture, and focus on enabling a multimodal Embodied ...
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 ...
Comments