Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31532
PYTHEIA: A Scale for Assessing Rehabilitation and Assistive Robotics

Authors: Yiannis Koumpouros, Effie Papageorgiou, Alexandra Karavasili, Foteini Koureta


The objective of the present study was to develop a scale called PYTHEIA. The PYTHEIA is a self-reported measure for the assessment of rehabilitation and assistive robotics and other assistive technology devices. The development of PYTHEIA faced the absence of a valid instrument that can be used to evaluate the assistive robotic devices both as a whole, as well as any of their individual components or functionalities implemented. According to the results presented, PYTHEIA is a valid and reliable scale able to be applied to different target groups for the subjective evaluation of various assistive technology devices.

Keywords: Rehabilitation, assistive technology, assistive robots, rehabilitation robots, scale, psychometric test, assessment, validation, user satisfaction.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1327


[1] H. P. Parette, J. J. Hourcade, A. van Biervliet, “Selection of appropriate technology for children with disabilities”, Teaching Exceptional Children, vol. 25, no. 3, pp. 18-22, 1993.
[2], "Choosing the appropriate assistive device: A card sorting activity | POGOe - Portal of Geriatrics Online Education", 2009. (Online). Available: (Accessed: 10- Jan- 2016).
[3] S. Isabelle, S. Bessey, K. Dragas, P. Blease, J. Shepherd and S. Lane, "Assistive Technology for Children with Disabilities", Occup Ther Health, vol. 16, no. 4, pp. 29-51, 2003.
[4] M. Scherer and J. Galvin, "An outcomes perspective of quality pathways to the most appropriate technology", in Evaluating, Selecting and Using Appropriate Assistive Technology, M. Scherer and J. Galvin, Ed. Gaithersburg, MD: Aspen, 1996, pp. 1-26.
[5] S. Winkler, B. Vogel, H. Hoenig, D. Ripley, S. Wu, S. Fitzgerald, W. Mann and D. Reker, "Cost, Utilization, and Policy of Provision of Assistive Technology Devices to Veterans Poststroke by Medicare and VA", Medical Care, vol. 48, no. 6, pp. 558-562, 2010.
[6] G. Dejong, S. Palsbo and P. Beatty, "1. The Organization and Financing of Health Services for Persons with Disabilities", The Milbank Quarterly, vol. 80, no. 2, pp. 261-301, 2002.
[7] WHO. “Joint position paper on the provision of mobility devices in less-resourced settings.”. (Online). Available: (Accessed: 12- Jan- 2016).
[8] I. Ebner. “Abandonment of assistive technology”. (online). Available: (Accessed: 08- Jan- 2016).
[9] S. S. Johnston, and J. Evans, “Considering response efficiency as a strategy to prevent assistive technology abandonment”, Journal of Special Education technology, vol. 20, no. 3, pp. 45-50, 2005.
[10] M. Scherer, "Outcomes of assistive technology use on quality of life", Disability and Rehabilitation, vol. 18, no. 9, pp. 439-448, 1996.
[11] J. Jutai, “Quality of life impact of assistive technology”, Rehabilitation Engineering, vol. 14, pp: 2-7, 1999.
[12] M. Scherer and L. Cushman, "Predicting satisfaction with assistive technology for a sample of adults with new spinal cord injuries", Psychological Reports, vol. 87, no. 3, pp. 981-987, 2000.
[13] G. Craddock, A. Stankovic, T. MacKeogh and M. Scherer, “Online advocacy: user experience and evaluation”, in Challenges for assistive technology: AAATE07, Eizmendi G, et al., Ed. Netherlands: IOS Press; 2007, pp. 748-752.
[14] M. Scherer, J. Jutai, M. Fuhrer, L. Demers and F. Deruyter, "A framework for modelling the selection of assistive technology devices (ATDs)", Disabil Rehabil Assist Technol, vol. 2, no. 1, pp. 1-8, 2007.
[15] M. Scherer, Matching Person and Technology Process and Accompanying Assessment Instruments. Webster, NY: The Institute for Matching Person & Technology, Inc., 1998.
[16] L. Demers, R. Weiss-Lambrou and B. Ska, Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST Version 2.0) An Outcome Measure for Assistive Technology Devices. Webster, NY: The Institute for Matching Person & Technology.
[17] M. J. Scherer, Laura A. Cushman, "Measuring subjective quality of life following spinal cord injury: a validation study of the assistive technology device predisposition assessment", Disability and Rehabilitation, vol. 23, no. 9, pp. 387-393, 2001.
[18] M. J. Scherer and G. Craddock, “Matching Person & Technology (MPT) assessment process”, Technology & Disability, Special Issue: The assessment of Assistive Technology Outcomes, Effects and Costs, vol. 14, no. 3, pp. 125-131, 2002.
[19] L. Demers, M. Monette, Y. Lapierre, D. Arnold and C. Wolfson, "Reliability, validity, and applicability of the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST 2.0) for adults with multiple sclerosis", Disability and Rehabilitation, vol. 24, no. 1-3, pp. 21-30, 2002.
[20] G. Brancato, S. Macchia, M. Murgia, M. Signore, G. Simeoni, K. Blanke, T. Körner, A. Nimmergut, P. Lima, R. Paulino and J. Hoffmeyer-Zlotnik, Handbook of Recommended Practices for Questionnaire Development and Testing in the European Statistical System. European Commission, 2006.
[21] A. Burns, C. Brayne and M. Folstein, "Key Papers in Geriatric Psychiatry: mini-mental state: a practical method for grading the cognitive state of patients for the clinician. M. Folstein, S. Folstein and P. McHugh, Journal of Psychiatric Research, 1975, 12, 189-198.", Int. J. Geriat. Psychiatry, vol. 13, no. 5, pp. 285-294, 1998.
[22] R. Henson, "Use of Exploratory Factor Analysis in Published Research: Common Errors and Some Comment on Improved Practice", Educational and Psychological Measurement, vol. 66, no. 3, pp. 393-416, 2006.
[23] J. C. Nunally and I. R. Berstein, Psychometric Theory, 3rd ed., New York: McGraw-Hill, 1994.