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Original research
Robot for health data acquisition among older adults: a pilot randomised controlled cross-over trial
  1. Roel Boumans1,2,
  2. Fokke van Meulen1,
  3. Koen Hindriks2,
  4. Mark Neerincx2,
  5. Marcel G M Olde Rikkert1
  1. 1 Department of Geriatrics, Radboud University Medical Center, Nijmegen, The Netherlands
  2. 2 Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
  1. Correspondence to Roel Boumans, Department of Geriatrics, Radboudumc, Nijmegen, The Netherlands; roel.boumans{at}radboudumc.nl

Abstract

Background /Objectives Healthcare professionals (HCP) are confronted with an increased demand for assessments of important health status measures, such as patient-reported outcome measurements (PROM), and the time this requires. The aim of this study was to investigate the effectiveness and acceptability of using an HCP robot assistant, and to test the hypothesis that a robot can autonomously acquire PROM data from older adults.

Design A pilot randomised controlled cross-over study where a social robot and a nurse administered three PROM questionnaires with a total of 52 questions.

Setting A clinical outpatient setting with community-dwelling older adults.

Participants Forty-two community-dwelling older adults (mean age: 77.1 years, SD: 5.7 years, 45% female).

Measurements The primary outcome was the task time required for robot–patient and nurse–patient interactions. Secondary outcomes were the similarity of the data and the percentage of robot interactions completed autonomously. The questionnaires resulted in two values (robot and nurse) for three indexes of frailty, well-being and resilience. The data similarity was determined by comparing these index values using Bland-Altman plots, Cohen’s kappa (κ) and intraclass correlation coefficients (ICC). Acceptability was assessed using questionnaires.

Results The mean robot interview duration was 16.57 min (SD=1.53 min), which was not significantly longer than the nurse interviews (14.92 min, SD=8.47 min; p=0.19). The three Bland-Altman plots showed moderate to substantial agreement between the frailty, well-being and resilience scores (κ=0.61, 0.50 and 0.45, and ICC=0.79, 0.86 and 0.66, respectively). The robot autonomously completed 39 of 42 interviews (92.8%).

Conclusion Social robots may effectively and acceptably assist HCPs by interviewing older adults.

  • social robot
  • older adults
  • questionnaires
  • patient-reported outcome measurement

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

http://dx.doi.org/10.1136/bmjqs-2018-008977

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    Footnotes

    • Funding This study was funded by the Radboud Universitair Medisch Centrum (Grant No: 4TU Human&Technology).

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval This study was approved by the Institutional Review Board of the Radboudumc.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Data are available upon request.

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