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Subject Selection Bias in Intervention Experiments with Socially Assistive Robots and the Impact on the Representativeness of the Population

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Social Robotics (ICSR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11876))

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Abstract

The subjects of all studies have their own personalities and characteristics. For example, the characteristics of elderly individuals being assisted by Socially Assistive Robots (SARs) needs to be investigated. However, the attributes of subjects’ personalities that affect the outcome of intervention experiments involving SARs have been analyzed mainly by gender so far. The purpose of this study is to clarify the selection criteria of the subjects in intervention experiments with SARs and their influence on subjects’ attributes. Semi-structured interviews were conducted to clarify the criteria by which subjects were selected and the relationship between the subjects and the facility personnel. We interviewed 13 staff members who were involved in the selection of subjects for SAR intervention experiments in six facilities. According to the subject selection criteria discovered in these interviews, we did follow-up research to clarify the influence on the attributes of the selected subjects. In conclusion, the subject selection criteria reported by the staff were analyzed according to four categories based on the interview surveys. It was verified that the selection criteria affected the selection attributes of subjects’ degree of involvement, relationship, and character. Going forward, it is necessary to link this research to not only the personality of the elderly person being assisted but also to their family structure and hobbies, friendship characteristics, and the function of the SARs.

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Acknowledgments

This work was supported by the “Strategic Promotion of Innovative Research and Development” of the Japan Science and Technology Agency (JST), Grant Number JPMJSV1011. We would also like to thank the faculty staff of Seikatsu Kagaku Un-Ei Co., Ltd. Without their participation and contribution, this research could not have been conducted.

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Authors and Affiliations

  1. Department of Human and Engineered Environmental Studies, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, Japan

    Toshiharu Igarashi, Misato Nihei & Minoru Kamata

  2. Institute of Gerontology, The University of Tokyo, Faculty of Engineering Bldg.8., 7F, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan

    Misato Nihei & Minoru Kamata

  3. Research Institute of National Rehabilitation Center for Persons with Disabilities, 1 Namiki 4-chome, Tokorozawa, Saitama Prefecture, 359-8555, Japan

    Jumpei Mizuno & Takenobu Inoue

Authors
  1. Toshiharu Igarashi
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  2. Misato Nihei
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  3. Jumpei Mizuno
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  4. Takenobu Inoue
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  5. Minoru Kamata
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Corresponding author

Correspondence to Misato Nihei .

Editor information

Editors and Affiliations

  1. Robotics Lab, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Miguel A. Salichs

  2. The National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

  3. Faculty of Industrial Design, Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Emilia Ivanova Barakova

  4. Mechanical & Industrial, Qatar University, Doha, Qatar

    John-John Cabibihan

  5. Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA, USA

    Alan R. Wagner

  6. Robotics Lab - Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Álvaro Castro-González

  7. Wichita State University, Wichita, KS, USA

    Hongsheng He

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Igarashi, T., Nihei, M., Mizuno, J., Inoue, T., Kamata, M. (2019). Subject Selection Bias in Intervention Experiments with Socially Assistive Robots and the Impact on the Representativeness of the Population. In: Salichs, M., et al. Social Robotics. ICSR 2019. Lecture Notes in Computer Science(), vol 11876. Springer, Cham. https://doi.org/10.1007/978-3-030-35888-4_5

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  • DOI: https://doi.org/10.1007/978-3-030-35888-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35887-7

  • Online ISBN: 978-3-030-35888-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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