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

Instruments for measuring psychological dimensions in human-robot interaction: systematic review of psychometric properties
Instruments for measuring psychological dimensions in human-robot interaction: systematic review of psychometric properties
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).
1438-8871
Vagnetti, Roberto
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Camp, Nicola
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Story, Matthew
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Ait-Belaid, Khaoula
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Mitra, Suvobrata
298e975b-0138-4876-8d1d-e1f1de78bb34
Zecca, Massimiliano
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Nuovo, Alessandro Di
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Magistro, Daniele
ab9296bc-fda6-469e-a3f8-3a574faa1b7e
Vagnetti, Roberto
769db927-be78-4c31-84c5-5ed4379c6fea
Camp, Nicola
9dcf59fe-47c4-43db-bb6a-333721427eb9
Story, Matthew
7539ce11-f6ce-4d80-b3c6-51a3024903b1
Ait-Belaid, Khaoula
7e2e669d-349c-406d-be65-839f55b1fd64
Mitra, Suvobrata
298e975b-0138-4876-8d1d-e1f1de78bb34
Zecca, Massimiliano
870c8b27-684b-42b3-baed-40dd996c2800
Nuovo, Alessandro Di
09c7ba20-f9a1-484f-ab3a-337d83737c46
Magistro, Daniele
ab9296bc-fda6-469e-a3f8-3a574faa1b7e

Vagnetti, Roberto, Camp, Nicola, Story, Matthew, Ait-Belaid, Khaoula, Mitra, Suvobrata, Zecca, Massimiliano, Nuovo, Alessandro Di and Magistro, Daniele (2024) Instruments for measuring psychological dimensions in human-robot interaction: systematic review of psychometric properties. Journal of Medical Internet Research, 26, [e55597]. (doi:10.2196/preprints.55597).

Record type: Article

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).

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Accepted/In Press date: 25 April 2024
Published date: 5 June 2024

Identifiers

Local EPrints ID: 506018
URI: http://eprints.soton.ac.uk/id/eprint/506018
ISSN: 1438-8871
PURE UUID: 9bdec28f-9fd8-4cdf-a21e-30ff353362a4
ORCID for Daniele Magistro: ORCID iD orcid.org/0000-0002-2554-3701

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Date deposited: 27 Oct 2025 17:57
Last modified: 18 Nov 2025 18:23

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Contributors

Author: Roberto Vagnetti
Author: Nicola Camp
Author: Matthew Story
Author: Khaoula Ait-Belaid
Author: Suvobrata Mitra
Author: Massimiliano Zecca
Author: Alessandro Di Nuovo
Author: Daniele Magistro ORCID iD

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