Game-Based Human-Robot Interaction Promotes Self-disclosure in People with Visual Impairments and Intellectual Disabilities
The willingness to share personal information about negative social experiences is of great importance for the effectiveness of robot-mediated social therapies. This paper reports the results of a pilot test on the effectiveness of using a game or a conversation on achieving a higher self-disclosure in people with visual and intellectual disabilities. The participants interacted with a humanoid robot NAO. Comparable game-based and conversation-based interaction were implemented. We measured the length of the self-disclosing sentences during the two interactions. The majority of the participants said that they preferred the conversation-based over the game-based interaction. The results indicate that during the game-based interaction the participants used much longer self-disclosing sentences in comparison with the to be conversation-based interaction. The outcomes of this pilot will help to improve the human-robot interactions for promoting self-disclosure as the first step in a research project that aims to alleviate worrying behavior in this user group.
We thank the six participants in this study for participating and contributing to this research. We also thank Bartiméus expertise center for facilitating the research and Bartiméus Sonneheerdt Foundation for the Grant nr 2017075B.
- 2.Sprecher, S., Treger, S., Wondra, J.D., Hilaire, N., Wallpe, K.: Taking turns: reciprocal self-disclosure promotes liking in initial interactions. J. Soc. Clin. Psychol. 49(5), 860–866 (2013)Google Scholar
- 5.Zimmerman, J., Forlizzi, J., Evenson, S.: Research through design as a method for interaction design research in HCI. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 493–502. ACM (2007)Google Scholar
- 7.World Health Organization, et al.: International classification of impairments, disabilities, and handicaps: a manual of classification relating to the consequences of disease, published in accordance with resolution wha29. 35 of the twenty-ninth world health assembly, May 1976 (1980)Google Scholar
- 8.Ferreira, B., Silva, W., Oliveira Jr, E.A., Conte, T.: Designing personas with empathy map. In: SEKE, vol. 152 (2015)Google Scholar
- 10.Kearsley, G., Shneiderman, B.: Engagement theory: a framework for technology-based teaching and learning. Educ. Technol. 38(5), 20–23 (1998)Google Scholar
- 11.Cooper, G., Hoffman, K., Powell, B., Marvin, R.: The Circle of Security Intervention. Disorganized Attachment and Caregiving, p. 318 (2011)Google Scholar
- 12.Lourens, T., Barakova, E.: User-friendly robot environment for creation of social scenarios. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds.) IWINAC 2011. LNCS, vol. 6686, pp. 212–221. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21344-1_23CrossRefGoogle Scholar
- 13.Kim, M.-G., et al.: Designing robot-assisted pivotal response training in game activity for children with autism. In: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1101–1106. IEEE (2014)Google Scholar
- 14.Buchina, N., Kamel, S., Barakova, E.: Design and evaluation of an end-user friendly tool for robot programming. In: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 185–191. IEEE (2016)Google Scholar
- 17.Marchi, E., Ringeval, F., Schuller, B., Neustein, A.: Voice-enabled assistive robots for handling autism spectrum conditions: an examination of the role of prosody. In: Neustein, A. (ed.) Speech and Automata in the Health Care, pp. 207–236. Walter de Gruyter GmbH & Co KG, Berlin (2014)Google Scholar