Reading the Mind in the Eyes Test Scores Demonstrate Poor Structural Properties in Nine Large Non-Clinical Samples

The Reading the Mind in the Eyes Test (RMET) is widely used in clinical and non-clinical research. However, the structural properties of RMET scores have yet to be rigorously examined. We analyzed the structural properties of RMET scores in nine existing datasets comprising non-clinical samples ranging from 558 to 9,267 (median = 1,112) participants each. We used confirmatory factor analysis to assess two theoretically derived factor models, exploratory factor analysis to identify possible alternative factor models, and reliability estimates to assess internal consistency. Neither of the theoretically derived models was a good fit for any of the nine datasets, and we were unable to identify any better fitting multidimensional models. Internal consistency metrics were acceptable in six of the nine datasets, but these metrics are difficult to interpret given the uncertain factor structures. Our findings contribute to a growing body of evidence questioning the reliability and validity of RMET scores.

Authors

Institutions

Publication Details

Journal
Assessment
Published
2025-03-29
DOI
https://doi.org/10.1177/10731911251328604
Citations
3
Primary Topic
Behavioral Health and Interventions
Type
article
Field-Weighted Citation Impact
4.63

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reading the Mind in the Eyes Test Scores Demonstrate Poor Structural Properties in Nine Large Non-Clinical Samples

Vince Polito, Victoria Savalei, Wendy C. Higgins, Robert M. Ross
3 citations
Assessment
Behavioral Health and Interventions
4.63
article

Reading the Mind in the Eyes Test Scores Demonstrate Poor Structural Properties in Nine Large Non-Clinical Samples

Vince Polito, Victoria Savalei, Wendy C. Higgins, Robert M. Ross
article en
3 citations

Abstract

The Reading the Mind in the Eyes Test (RMET) is widely used in clinical and non-clinical research. However, the structural properties of RMET scores have yet to be rigorously examined. We analyzed the structural properties of RMET scores in nine existing datasets comprising non-clinical samples ranging from 558 to 9,267 (median = 1,112) participants each. We used confirmatory factor analysis to assess two theoretically derived factor models, exploratory factor analysis to identify possible alternative factor models, and reliability estimates to assess internal consistency. Neither of the theoretically derived models was a good fit for any of the nine datasets, and we were unable to identify any better fitting multidimensional models. Internal consistency metrics were acceptable in six of the nine datasets, but these metrics are difficult to interpret given the uncertain factor structures. Our findings contribute to a growing body of evidence questioning the reliability and validity of RMET scores.

AssessmentVol. 33(2)
University of British Columbia (CA), The University of Melbourne (AU), Macquarie University (AU)
John Templeton Foundation, Australian Government, Macquarie University, Australian Research Council
No poverty
Openalex Percentile: Top 6%
Behavioral Health and Interventions
4.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Reading the Mind in the Eyes Test Scores Demonstrate Poor Structural Properties in Nine Large Non-Clinical Samples — Vince Polito, Victoria Savalei, et al. · Assessment (2025) | TGRS Research Map | TGRS