Development of a short‐form version of the Reading the Mind in the Eyes Test for assessing theory of mind in older adults. (30th July 2020)

• Record Type: Journal Article
• Authors: Chander, Russell J.; Grainger, Sarah A.; Crawford, John D.; Mather, Karen A.; Numbers, Katya; Cleary, Rhiagh; Kochan, Nicole A.; Brodaty, Henry; Henry, Julie D.; Sachdev, Perminder S.
• Is Part Of: International journal of geriatric psychiatry. Volume 35:Number 11(2020)
• Page Start: 1322
• Page End: 1330
• Publication Date: 2020-07-30
• Subjects: neurocognitive disorders -- Reading the Mind in the Eyes Test -- social cognition -- theory of mind; Geriatric psychiatry -- Periodicals; Geriatric Psychiatry -- Periodicals; 618.97689
• DOI: 10.1002/gps.5369
• Languages: English
• ISSNs: 0885-6230

Abstract

Abstract : Background: The Reading the Mind in the Eyes test (RMET) is a 36‐item assessment for theory of mind (ToM) performance. While this measure has been shown to be sensitive to age‐related ToM difficulties, there are no established cutoffs or guidelines currently available that are specific to older adults. This article seeks to validate a short‐form version of the RMET appropriate for use in such populations. Methods: Cross‐sectional data from 295 participants (mean age 86 years) from the Sydney Memory and Ageing Study, a longitudinal community observational cohort. Participants underwent an assessment battery that included the RMET. Individuals who scored >1SD below the RMET scores of cognitively normal participants were deemed to have below average RMET scores. Various model‐building methods were used to generate short‐form solutions of the RMET, which were compared with previously validated versions in their predictive power for below average full RMET performance. Results: Individuals with below average RMET performance tended to be older and have poorer global cognition. Of the eight short‐form solutions, the 21‐item version generated using genetic algorithm exhibited the best classification performance with an area under the receiver operating curve (AUROC) of 0.98 and had 93.2% accuracy in classifying individuals with below average ToM. A shorter 10‐item solution derived by ant colony optimization also had acceptable performance. Conclusion: We recommend the 21‐item version of the RMET for use in older adult populations for identifying individuals with impaired ToM. Where an even shorter version is needed with a trade‐off of slightly reduced performance, the 10‐item version is acceptable.