article

Assessment of users' acceptability of a mobile-based embodied conversational agent for the prevention and detection of suicidal behaviour

Authors:

Juan Martínez-Miranda,

Ariadna Martínez,

Héctor Aguilar,

Liliana Jiménez,

Giovanni Rosales,

Elizabeth ValenciaAuthors Info & Claims

Journal of Medical Systems, Volume 43, Issue 8

Pages 1 - 18

https://doi.org/10.1007/s10916-019-1387-1

Published: 01 August 2019 Publication History

Abstract

The use of embodied conversational agents in mental health has increased in the last years. Several studies exist describing the benefits and advantages of this technology as a complement to psychotherapeutic interventions for the prevention and treatment of depression, anxiety, or post-traumatic stress disorder, to name a few. A small number of these works implement capabilities in the virtual agent focused on the detection and prevention of suicidality risks. The work presented in this paper describes the development of an embodied conversational agent used as the main interface in HelPath, a mobile-based application addressed to individuals detected with any of the suicidal behaviours: ideation, planning or attempt. The main objective of HelPath is to continuously collect user's information that, complemented with data from the electronic health record, supports the identification of risks associated with suicidality. Through the virtual agent, the users also receive information and suggestions based on cognitive behaviour therapy that would help them to maintain a healthy condition. The paper also presents the execution of an exploratory pilot to assess the acceptability, perception and adherence of users towards the virtual agent. The obtained results are presented and discussed, and some actions for further improvement of the embodied conversational agent are also identified.

References

[1]

Kenny, P., Parsons, T., Gratch, J., Rizzo, A., Virtual humans for assisted health care. In: Proceedings of the 1st International Conference on PErvasive Technologies Related to Assistive Environments. PETRA `08; ACM; pp. 1---4. 2008.

Digital Library

[2]

Bickmore, T., Utami, D., Matsuyama, R., and Paasche-Orlow, M., Improving access to online health information with conversational agents: A randomized controlled experiment. Journal of Medical Internet Research 18(1):e1, 2016.

[3]

Philip, P., Bioulac, S., Sauteraud, A., Chaufton, C., Olive, J., Could a virtual human be used to explore excessive daytime sleepiness in patients? Presence: Teleoperators and Virtual Environments; 234; pp. 369---376, 2014

[4]

Sillice, M., Morokoff, P., Ferszt, G., Bickmore, T., Bock, B., Lantini, R., and Velicer, W., Using relational agents to promote exercise and sun protection: Assessment of participants' experiences with two interventions. Journal of Medical Internet Research 20(2):e48, 2018.

[5]

Shaked, N., Avatars and virtual agents --- relationship interfaces for the elderly. Healthcare Technology Letters 4(3):83---87, 2017.

[6]

Provoost, S., Lau, H., Ruwaard, J., and Riper, H., Embodied conversational agents in clinical psychology: A scoping review. Journal of Medical Internet Research 19(5):e151, 2017.

[7]

Dingli, A., and Seychell, D., The New Digital Natives: Cutting the Chord. Berlin, Heidelberg: Springer, 2015.

[8]

WHO. World health statistics 2017 --- monitoring health for the SDGs. Tech. Rep.; World Health Organization; https://apps.who.int/iris/bitstream/handle/10665/255336/9789241565486-eng.pdf?sequence=1 Accessed 28 February 2019.

[9]

Martínez-Miranda, J., Palacios-Isaac, A., López-Flores, F., Martínez, A., Aguilar, H., Jiménez, L., Ramos, R., Rosales, G., Altamirano, L., Development of a computational platform to support the screening, surveillance, prevention and detection of suicidal behaviours. Proceedings of the 9th EAI International Conference on Pervasive Computing Paradigms for Mental Health, Buenos Aires, Argentina, 2019.

[10]

Christensen, H., Batterham, P. J., and O'Dea, B., E-health interventions for suicide prevention. International Journal of Environmental Research and Public Health 11(8):8193---8212, 2014.

[11]

Melia, R., Francis, K., Duggan, J., Bogue, J., O'Sullivan, M., Chambers, D., Young, K., Mobile Health Technology Interventions for Suicide Prevention: Protocol for a Systematic Review and Meta-Analysis. JMIR Research Protocols; 26;7(1):e28, 2018.

[12]

Lai, M. H., Maniam, T., Chan, L. F., and Ravindran, A. V., Caught in the web: a review of web-based suicide prevention. Journal of Medical Internet Research 16(1):e30, 2014.

[13]

de la Torre, I., Castillo, G., Arambarri, J., López-Coronado, M., and Franco, M. A., Mobile Apps for Suicide Prevention: Review of Virtual Stores and Literature. JMIR Mhealth Uhealth; 10 5(10):e130, 2017.

[14]

Dehn, D. M., and van Mulken, S., The impact of animated interface agents: a review of empirical research. International Journal of Human Computer Studies 52:1---22, 2000.

Digital Library

[15]

Luger, E., Sellen, A., Like Having a Really Bad PA: The Gulf between User Expectation and Experience of Conversational Agents. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16). ACM, New York, NY, USA, pp. 5286---5297, 2016.

Digital Library

[16]

Bickmore, T., and Gruber, A., Relational agents in clinical psychiatry. Harvard review of psychiatry 18(2):119---130, 2010.

[17]

Perry, Y., Calear, A., Mackinnon, A., Batterham, P., Licinio, J., King, C., Thomsen, N., Scott, J., Donker, T., Merry, S., Fleming, T., Stasiak, K., Werner-Seidler, A., and Christensen, H., Trial for the prevention of depression (tripod) in final-year secondary students: study protocol for a cluster randomised controlled trial. Trials 16:451, 2015.

[18]

May, A., and Klonsky, E., Validity of suicidality items from the youth risk behavior survey in a high school sample. Assessment 18(3):379---381, 2001.

[19]

Bresó, A., Martínez-Miranda, J., Botella, C., Baños, R., and García-Gómez, J., Usability and acceptability assessment of an empathic virtual agent to prevent major depression. Expert Systems 33(4):297---312, 2016.

Digital Library

[20]

Kroenke, K., Spitzer, R., and Williams, J., The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine 16(9):606---613, 2001.

[21]

Burton, C., Szentagotai, A., McKinstry, B., Matheson, C., Matu, S., Moldovan, R., Macnab, M., Farrow, E., David, D., Pagliari, C., Serrano-Blanco, A., and Wolters, M., Pilot randomised controlled trial of help4mood, an embodied virtual agent-based system to support treatment of depression. Journal of Telemedicine and Telecare 22(6):348---355, 2016.

[22]

Martínez-Miranda, J., Embodied conversational agents for the detection and prevention of suicidal behaviour: Current applications and open challenges. Journal of Medical Systems 41:135, 2017.

Digital Library

[23]

Roberts, R., and Chen, Y., Depressive symptoms and suicidal ideation among mexican-origin and anglo adolescents. Journal of the American Academy of Child & Adolescent Psychiatry 34(1):81---90, 1995.

[24]

Ring, L., Utami, D., and Bickmore, T., The Right Agent for the Job? In: Bickmore, T., Marsella, S., Sidner, C. (Eds), Intelligent Virtual Agents. IVA 2014. Lecture Notes in Computer Science. Vol. 8637. Cham: Springer, 2014.

[25]

Baylor, A. L., Kim, Y., Pedagogical agent design: the impact of agent realism, gender, ethnicity, and instructional role. In Lecture Notes in Computer Science: Intelligent Tutoring Systems; vol. 3320; pp. 592---603 Berlin/Heidelberg, Germany: Springer, 2004.

[26]

Pratt, J. A., Hauser, K., Ugray, Z., and Patterson, O., Looking at human---computer interface design: effects of ethnicity in computer agents. Interacting with Computers 19:512---523, 2007.

Digital Library

[27]

Plant, E. A., Doerr, C., Rosenberg-Kima, R., and Baylor, A., The influence of computer-based model's race and gender on female students' attitudes and beliefs towards engineering. Journal of Engineering Education 99(1):35---44, 2010.

[28]

Bickmore, T., Trinh, H., Asadi, R., Olafsson, S., Safety first: Conversational agents for health care. In: Moore R, Szymanski M, Arar R, Ren G, editors. Studies in Conversational UX Design. Springer International Publishing; pp. 33---57, 2018.

[29]

Bohart, A., Elliott, R., Greenberg, L., Watson, J., Empathy. In: Norcross J, editor. Psychotherapy Relationships that Work: Evidence-Based Responsiveness; Chap. 6. Oxford University Press; pp. 89---108, 2011.

[30]

Scherer, K., Schorr, A., Johnstone, T., Appraisal Processes in Emotion: Theory, Methods, Research. Oxford University Press, 2001.

[31]

Ortony, A., Clore, G., Collins, A., The Cognitive Structure of Emotions. Cambridge University Press, 1998.

[32]

Gebhard, P., Alma: A layered model of affect. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems. AAMAS'05; ACM; pp. 29---36, 2005.

[33]

Dias, J., and Paiva, A., Feeling and reasoning: A computational model for emotional characters. In: Bento, C., Cardoso, A., Dias, G. (Eds), Progress in Artificial Intelligence. Berlin Heidelberg: Springer, 2005, 127---140.

[34]

Clark, A., Empathy in Counseling and Psychotherapy: Perspectives and Practices. Lawrence Erlbaum Associates, 2007.

[35]

Martínez-Miranda J, Bresó A, García-Gómez J. Modelling two emotion regulation strategies as key features of therapeutic empathy. In: Bosse T, Broekens J, Dias J, van der Zwaan J, editors. Emotion Modeling: Towards Pragmatic Computational Models of Affective Processes. Springer International; pp. 115---133.

[36]

Bresó, A., Martínez-Miranda, J., Fuster-García, E., and García-Gómez, J., A novel approach to improve the planning of adaptive and interactive sessions for the treatment of major depression. International Journal of Human- Computer Studies 87:80---91.

Digital Library

[37]

Mewton, L., and Andrews, G., Cognitive behavioral therapy for suicidal behaviors: improving patient outcomes. Psychology Research and Behavior Management 9:21---29, 2016.

[38]

Tarrier, N., Taylor, K., and Gooding, P., Cognitive-behavioral interventions to reduce suicide behavior: A systematic review and meta-analysis. Behavior Modification 32(1):77---108, 2008.

[39]

Stanley, B., Brown, G., Brent, D., Wells, K., Poling, K., Curry, J., Kennard, B., Wagner, A., Cwik, M., Klomek, A., Goldstein, T., Vitiello, B., Barnett, S., Daniel, S., and Hughes, J., Cognitive- behavioral therapy for suicide prevention (CBT-SP): Treatment model, feasibility, and acceptability. Journal of the American Academy of Child & Adolescent Psychiatry 48(10):1005---1013, 2009.

[40]

Sarracino, D., Dimaggio, G., Ibrahim, R., Popolo, R., Sassaroli, S., and Ruggiero, G., When REBT Goes Difficult: Applying ABC-DEF to Personality Disorders. Journal of Rational-Emotive and Cognitive-Behavior Therapy 35(3):278---295, 2017.

[41]

Bernstein, D. A., Borkovec, T. D., Hazlett-Stevens, H., New directions in progressive relaxation training: A guidebook for helping professionals. Greenwood Publishing Group, 2000.

[42]

Patterson, W. M., Dohn, H. H., Bird, J., and Patterson, G. A., Evaluation of suicidal patients: The SAD PERSONS scale. Psychosomatics 24(4):343---349, 1983.

[43]

Rosales-Pérez, J. C., Córdova-Osnaya, M., and Cortés-Granados, R., Reliability and validity of Roberts' suicidal scale. Journal of Behavior, Health & Social Issues 7(2):31---41, 2016.

[44]

Avradinis, N., Panayiotopoulos, T., and Anastassakis, G., Behavior believability in virtual worlds: agents acting when they need to. SpringerPlus 2(1):246, 2013. https://doi.org/10.1186/2193-1801-2-246.

[45]

Hamilton, M., A rating scale for depression. Journal of Neurology, Neurosurgery & Psychiatry 23(1):56---62, 1960. https://doi.org/10.1016/0022-3956(88)90024-6.

[46]

Ramos-Brieva, J., and Cordero-Villafafila, A., A new validation of the Hamilton rating scale for depression. Journal of Psychiatric Research 22(1):21---28, 1988. https://doi.org/10.1016/0022-3956(88)90024-6.

[47]

Rubio, G., Montero, I., Jáuregui, J., Villanueva, R., Casado, M., Marín, J., and Santo-Domingo, J., Validación de la escala de riesgo suicida de Plutchik en población española. Archivos de Neurobiología 61(2):143---152, 1998.

[48]

Plutchick, R., van Praga, H. M., Conte, H. R., and Picard, S., Correlates of suicide and violence risk: The suicide risk measure. Comprehensive Psychiatry 30(4):296---302, 1989.

[49]

Hamilton, M., The assessment of anxiety states by rating. The British journal of medical psychology 32(1):50---55, 1959.

[50]

Lobo, A., Chamorro, L., Luque, A., Dal-Ré, R., Badia, X., and Baró, E., Validación de las versiones en español de la Montgomery-Asberg depression rating scale y la Hamilton anxiety rating scale para la evaluación de la depresión y de la ansiedad. Medicina Clínica 118:493---499.

[51]

Terada, K., Jing, L., Yamada, S., Effects of Agent Appearance on Customer Buying Motivations on Online Shopping Sites. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '15). ACM, New York, NY, USA, 929---934, 2015.

[52]

Baylor, A., Promoting motivation with virtual agents and avatars: role of visual presence and appearance, 364, Philosophical Transactions of the Royal Society B, 2009.

[53]

Scherer, K. R., Emotion and emotional competence: conceptual and theoretical issues for modelling agents. In: Scherer K R, Bänziger T, Roesch E B, editors. Blueprint for Affective Computing: A Sourcebook; Chap. 1.1. Oxford University Press; pp. 3---20, 2010.

[54]

Gaggioli, A., Mantovani, F., Castelnuovo, G., Wiederhold, B., and Riva, G., Avatars in clinical psychology: A framework for the clinical use of virtual humans. Cyberpsychology & behavior 6(2):117---165.

[55]

Horvath, A. O., and Luborsky, L., The role of the therapeutic alliance in psychotherapy. Journal of Consulting and Clinical Psychology 61(4):561---573, 1993.

[56]

Bickmore, T., Gruber, A., and Picard, R., Establishing the computer---patient working alliance in automated health behavior change interventions. Patient Education and Counseling 59:21---30, 2005.

[57]

Gong, L., and Nass, C., When a talking-face computer agent is half-human and half-humanoid: Human identity and consistency preference. Human Communication Research 33:163---193, 2007.

[58]

Gris, I., Novick, D., Camacho, A., Rivera, D. A., Gutierrez, M., Rayon, A., Recorded speech, virtual environments, and the effectiveness of embodied conversational agents. In: Bickmore T, Marsella S, Sidner C, editors. Intelligent Virtual Agents. Springer International Publishing; pp. 182---185, 2014.

[59]

Burkhardt, F., Campbell, N., Emotional speech synthesis. In: Calvo R, D'Mello S, Gratch J, Kappas A, editors. The Oxford Handbook of Affective Computing; Chap. 20. Oxford University Press; pp. 286---295, 2015.

[60]

Tielman, M., Neerincx, M., van Meggelen, M., Franken, I., and Brinkman, W., How should a virtual agent present psychoeducation? Technology and Health Care 25(6):1081---1096, 2018.

[61]

Payne, J., Szymkowiak, A., Robertson, P., and Johnson, G., Gendering the machine: Preferred virtual assistant gender and realism in self-service. In: Aylett, R., Krenn, B., Pelachaud, C., Shimodaira, H. (Eds), Intelligent Virtual Agents. Berlin Heidelberg: Springer, 2013, 106---115.

[62]

Cowell, A. J., and Stanney, K. M., Manipulation of non-verbal interaction style and demographic embodiment to increase anthropomorphic computer character credibility. International Journal of Human-Computer Studies 62(2):281---306, 2005.

Digital Library

[63]

Qiu, L., and Benbasat, I., A study of demographic embodiments of product recommendation agents in electronic commerce. International Journal of Human-Computer Studies 68(10):669---688, 2010.

Digital Library

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Assessment of users' acceptability of a mobile-based embodied conversational agent for the prevention and detection of suicidal behaviour

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cover image Journal of Medical Systems

Journal of Medical Systems Volume 43, Issue 8

Aug 2019

559 pages

ISSN:0148-5598

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Copyright © Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

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Plenum Press

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Published: 01 August 2019

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