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Developing and Evaluating Complex Interventions: The Case of Robotic Systems in Cognitive Rehabilitation Therapy

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Towards Trustworthy Artificial Intelligent Systems

Abstract

The use of robots in cognitive rehabilitation has been going on, at an experimental level, in the last decades, comprehending a broad scope of applications ranging from those aiming at the stimulation of patients with dementia to others addressing children in the autism spectrum. Though the results provided by the multiple projects developed in this domain apparently point to the eventual beneficial character of this intervention, its validation and formal recognition in clinical terms still lacks, keeping these experiments punctual and inconsequent in medical terms, being the impact of its developments limited to the robotics R&D. In the present paper, we briefly address this issue claiming that the formal clinical recognition of the possible beneficial role of artificial intelligent systems in cognitive rehabilitation therapy is only possible if/when the robotic projects dedicated to this theme are designed and developed as Complex Interventions, i.e., interventions that stand on a lattice of interdependencies and co-effects. According to the Medical Research Council, Complex Interventions are widely used in the health service, in public health practice, and in areas of social policy such as education, transport and housing that have important health consequences. The present paper reviews the guidelines and recommendations defined both by the “Framework for Development and Evaluation of Randomized Control Trials (RCTs) for Complex Interventions to Improve Health”, April 2000, and its updated 2019 version “Developing and evaluating complex interventions”. Both are intended to help researchers with the design of the intervention, choosing the appropriate methods, identifying the constraints on evaluation, presenting the evidence in the light of methodological and practical constraints. The present paper adopts an end-user centered stance in which the physical and psychological well-being of the patients that are targeted by these interventions, namely those that volunteer to participate in the trials, as well as that of their families, is viewed as ethically prior. According to this assumption, a fundamental role is given to the monitoring of this well-being and its assessment throughout the intervention process and the monitoring and assessment of the evolution of their health condition before, during the trials and after the experiment, in a long-run mode.

This was the theme of a communication presented by the author at the International Conference on Robot Ethics and Standards-ICRES 2020, 27–28th September 2020, Taiwan (online participation).

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Notes

  1. 1.

    https://mrc.ukri.org/documents/pdf/complex-interventions-guidance/.

  2. 2.

    https://mrc.ukri.org/documents/pdf/rcts-for-complex-interventions-to-improve-health/.

  3. 3.

    https://mrc.ukri.org/documents/pdf/complex-interventions-guidance/.

  4. 4.

    According to Johanna [1], the patients’ trust in their health care professionals is central to clinical practice and has been identified as the foundation for effective treatments and fundamental for patient-centered care.

  5. 5.

    https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders.

  6. 6.

    AuRoRA Project http://aurora.herts.ac.uk/.

  7. 7.

    SoftBank Robotics. Accessed on: Mar. 20, 2019. [Online]. Available: https://www.softbankrobotics.com/emea/en/nao.

  8. 8.

    When Dinosaurs Ruled the Earth, a short film about autism, robots and dinosaurs. J Autism Dev Disord. 2000 Jun;30(3):205–223.

  9. 9.

    https://alea-research.com/clinical-research-vs-medical-treatment/#:~:text=While%20there%20are%20a%20lot,help%20patients%20in%20the%20future.

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Correspondence to Maria Isabel Aldinhas Ferreira .

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Ferreira, M.I.A. (2022). Developing and Evaluating Complex Interventions: The Case of Robotic Systems in Cognitive Rehabilitation Therapy. In: Ferreira, M.I.A., Tokhi, M.O. (eds) Towards Trustworthy Artificial Intelligent Systems. Intelligent Systems, Control and Automation: Science and Engineering, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-031-09823-9_7

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