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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2019-09-01
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Series: | Cognitive Research |
Online Access: | http://link.springer.com/article/10.1186/s41235-019-0183-2 |
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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 |
work_keys_str_mv |
AT nicholaburton bestworstscalingimprovesmeasurementoffirstimpressions AT michaelburton bestworstscalingimprovesmeasurementoffirstimpressions AT danrigby bestworstscalingimprovesmeasurementoffirstimpressions AT clareamsutherland bestworstscalingimprovesmeasurementoffirstimpressions AT gillianrhodes bestworstscalingimprovesmeasurementoffirstimpressions |
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