Evidence map›Paper›PMID 42681191›Full record

ArticleBehavior research methods2026

Time after time, the best-worst scaling method is more reliable than ranking.

Garston Liang, Mackenzie Glover, Guy E Hawkins

Abstract read
In one paragraph

Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Garston LiangDiscipline of Psychology, University of Technology Sydney, Building 20, 100 Broadway, Ultimo, New South Wales, 2008, Australia. garston.liang@uts.edu.au.ORCID http://orcid.org/0000-0002-9230-7258
Mackenzie GloverDiscipline of Psychology, University of Newcastle, Callaghan, Australia.
Guy E HawkinsDiscipline of Psychology, University of Newcastle, Callaghan, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two popular methods of preference elicitation are rankings and best-worst scaling (BWS). Rankings, while simple and widely adopted, can be burdensome with larger item sets and fail to capture indifference between options that are neither loved nor hated. Best-worst scaling is a survey method that sidesteps the set size problem by capitalizing on people's natural capacity to identify preferences at the extremes. Across three experiments, our primary finding is that elicited preferences for ranking and BWS methods align, and that BWS methods provide additional resolution to resolve the indifference between middling options where rankings can struggle as well as the relative importance of each option. Moreover, we show that BWS methods exhibit greater test-retest reliability compared to rankings, even over time frames as short as minutes. Taken together, our results privilege BWS as a reliable and readily accessible alternative to ranking methods for preference elicitation.

Indexed as

Choice BehaviorHumansReproducibility of ResultsBest–worst scalingPreference elicitationRankingReliability

Identifiers

PMID42681191
PMCPMC13534160

What OpenQuestion holds

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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.