Evidence map›Paper›PMID 31549257›Full record

ArticleCognitive research: principles and implications2019

Best-worst scaling improves measurement of first impressions.

Nichola Burton, Michael Burton, Dan Rigby, Clare A M Sutherland, Gillian Rhodes

Abstract read
In one paragraph

Article in Cognitive research: principles and implications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Assessing patient information needs for new antidiabetic medications to inform shared decision-making: A best-worst scaling experiment in China.Health expectations : an international journal of public participation in health care and health policy · 2024
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  4. Article
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  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nichola BurtonARC Centre of Excellence in Cognition and its Disorders, School of Psychological Science, The University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia. nichola.burton@uwa.edu.au.ORCID http://orcid.org/0000-0003-4470-4846
Michael BurtonSchool of Agriculture and Environment, The University of Western Australia, Crawley, WA, Australia.
Dan RigbyEconomics, School of Social Sciences, University of Manchester, Manchester, UK.
Clare A M SutherlandARC Centre of Excellence in Cognition and its Disorders, School of Psychological Science, The University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia.
Gillian RhodesARC Centre of Excellence in Cognition and its Disorders, School of Psychological Science, The University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia.

Funding

Australian Research Council CE110001021Australian Research Council DP130102300Australian Research Council DP170104602
6 · The paper itself

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.

Identifiers

PMID31549257
PMCPMC6757072

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.