Instruments for measuring psychological dimensions in human-robot interaction: systematic review of psychometric properties

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Vagnetti, R ORCID: https://orcid.org/0000-0001-5192-1756, Camp, N, Story, M, Ait-Belaid, K, Mitra, S ORCID: https://orcid.org/0000-0001-7620-4809, Zecca, M, Di Nuovo, A and Magistro, D ORCID: https://orcid.org/0000-0002-2554-3701, 2024. Instruments for measuring psychological dimensions in human-robot interaction: systematic review of psychometric properties. Journal of Medical Internet Research, 26: e55597. ISSN 1439-4456

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Official URL: https://doi.org/10.2196/55597

Abstract

Background:
Numerous user-related psychological dimensions can significantly influence the dynamics between humans and robots. For developers and researchers, it is crucial to have a comprehensive understanding of the psychometric properties of the available instruments used to assess these dimensions as they indicate the reliability and validity of the assessment.

Objective:
This study aims to provide a systematic review of the instruments available for assessing the psychological aspects of the relationship between people and social and domestic robots, offering a summary of their psychometric properties and the quality of the evidence.

Methods:
A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines across different databases: Scopus, PubMed, and IEEE Xplore. The search strategy encompassed studies meeting the following inclusion criteria: (1) the instrument could assess psychological dimensions related to social and domestic robots, including attitudes, beliefs, opinions, feelings, and perceptions; (2) the study focused on validating the instrument; (3) the study evaluated the psychometric properties of the instrument; (4) the study underwent peer review; and (5) the study was in English. Studies focusing on industrial robots, rescue robots, or robotic arms or those primarily concerned with technology validation or measuring anthropomorphism were excluded. Independent reviewers extracted instrument properties and the methodological quality of their evidence following the Consensus-Based Standards for the Selection of Health Measurement Instruments guidelines.

Results:
From 3828 identified records, the search strategy yielded 34 (0.89%) articles that validated and examined the psychometric properties of 27 instruments designed to assess individuals’ psychological dimensions in relation to social and domestic robots. These instruments encompass a broad spectrum of psychological dimensions. While most studies predominantly focused on structural validity (24/27, 89%) and internal consistency (26/27, 96%), consideration of other psychometric properties was frequently inconsistent or absent. No instrument evaluated measurement error and responsiveness despite their significance in the clinical context. Most of the instruments (17/27, 63%) were targeted at both adults and older adults (aged ≥18 years). There was a limited number of instruments specifically designed for children, older adults, and health care contexts.

Conclusions:
Given the strong interest in assessing psychological dimensions in the human-robot relationship, there is a need to develop new instruments using more rigorous methodologies and consider a broader range of psychometric properties. This is essential to ensure the creation of reliable and valid measures for assessing people’s psychological dimensions regarding social and domestic robots. Among its limitations, this review included instruments applicable to both social and domestic robots while excluding those for other specific types of robots (eg, industrial robots).

Item Type:	Journal article
Publication Title:	Journal of Medical Internet Research
Creators:	Vagnetti, R., Camp, N., Story, M., Ait-Belaid, K., Mitra, S., Zecca, M., Di Nuovo, A. and Magistro, D.
Publisher:	JMIR Publications Inc.
Date:	5 June 2024
Volume:	26
ISSN:	1439-4456
Identifiers:	Number Type 10.2196/55597 DOI 1906812 Other
Rights:	© Roberto Vagnetti, Nicola Camp, Matthew Story, Khaoula Ait-Belaid, Suvobrata Mitra, Massimiliano Zecca, Alessandro Di Nuovo, Daniele Magistro. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.06.2024. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited.
Divisions:	Schools > School of Science and Technology
Record created by:	Melissa Cornwell
Date Added:	25 Jun 2024 10:23
Last Modified:	25 Jun 2024 10:23
URI:	https://irep.ntu.ac.uk/id/eprint/51621