Best-worst scaling improves measurement of first impressions

Abstract A common goal in psychological research is the measurement of subjective impressions, such as first impressions of faces. These impressions are commonly measured using Likert ratings. Although these ratings are simple to administer, they are associated with response issues that can limit re...

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Main Authors: Nichola Burton, Michael Burton, Dan Rigby, Clare A. M. Sutherland, Gillian Rhodes
Format: Article
Language:English
Published: SpringerOpen 2019-09-01
Series:Cognitive Research
Online Access:http://link.springer.com/article/10.1186/s41235-019-0183-2
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spelling doaj-633d7c8d1486421a8d55b3480ebafe492020-11-25T02:44:22ZengSpringerOpenCognitive Research2365-74642019-09-014111010.1186/s41235-019-0183-2Best-worst scaling improves measurement of first impressionsNichola Burton0Michael Burton1Dan Rigby2Clare A. M. Sutherland3Gillian Rhodes4ARC Centre of Excellence in Cognition and its Disorders, School of Psychological Science, The University of Western AustraliaSchool of Agriculture and Environment, The University of Western AustraliaEconomics, School of Social Sciences, University of ManchesterARC Centre of Excellence in Cognition and its Disorders, School of Psychological Science, The University of Western AustraliaARC Centre of Excellence in Cognition and its Disorders, School of Psychological Science, The University of Western AustraliaAbstract A common goal in psychological research is the measurement of subjective impressions, such as first impressions of faces. These impressions are commonly measured using Likert ratings. Although these ratings are simple to administer, they are associated with response issues that can limit reliability. Here we examine best-worst scaling (BWS), a forced-choice method, as a potential alternative to Likert ratings for measuring participants’ facial first impressions. We find that at the group level, BWS scores correlated almost perfectly with Likert scores, indicating that the two methods measure the same impressions. However, at the individual participant level BWS outperforms Likert ratings, both in terms of ability to predict preferences in a third task, and in terms of test-retest reliability. These benefits highlight the power of BWS, particularly for use in individual differences research.http://link.springer.com/article/10.1186/s41235-019-0183-2
collection DOAJ
language English
format Article
sources DOAJ
author Nichola Burton
Michael Burton
Dan Rigby
Clare A. M. Sutherland
Gillian Rhodes
spellingShingle Nichola Burton
Michael Burton
Dan Rigby
Clare A. M. Sutherland
Gillian Rhodes
Best-worst scaling improves measurement of first impressions
Cognitive Research
author_facet Nichola Burton
Michael Burton
Dan Rigby
Clare A. M. Sutherland
Gillian Rhodes
author_sort Nichola Burton
title Best-worst scaling improves measurement of first impressions
title_short Best-worst scaling improves measurement of first impressions
title_full Best-worst scaling improves measurement of first impressions
title_fullStr Best-worst scaling improves measurement of first impressions
title_full_unstemmed Best-worst scaling improves measurement of first impressions
title_sort best-worst scaling improves measurement of first impressions
publisher SpringerOpen
series Cognitive Research
issn 2365-7464
publishDate 2019-09-01
description Abstract A common goal in psychological research is the measurement of subjective impressions, such as first impressions of faces. These impressions are commonly measured using Likert ratings. Although these ratings are simple to administer, they are associated with response issues that can limit reliability. Here we examine best-worst scaling (BWS), a forced-choice method, as a potential alternative to Likert ratings for measuring participants’ facial first impressions. We find that at the group level, BWS scores correlated almost perfectly with Likert scores, indicating that the two methods measure the same impressions. However, at the individual participant level BWS outperforms Likert ratings, both in terms of ability to predict preferences in a third task, and in terms of test-retest reliability. These benefits highlight the power of BWS, particularly for use in individual differences research.
url http://link.springer.com/article/10.1186/s41235-019-0183-2
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