Evidence map›Paper›PMID 32313367›Full record

ArticleJournal of behavioral decision making2013

Development and Testing of an Abbreviated Numeracy Scale: A Rasch Analysis Approach.

Joshua A Weller, Nathan F Dieckmann, Martin Tusler, C K Mertz, William J Burns, Ellen Peters

Open access · bronzeAbstract read
In one paragraph

Article in Journal of behavioral decision making, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed
15.0field-weighted citation impact, top 1% of its field
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

87 citing papers in PubMed, 406 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Shared Medical Decision Making in Lung Cancer Screening: Experienced versus Descriptive Risk Formats.Medical decision making : an international journal of the Society for Medical Decision Making · 2016
    Trial
  4. Presenting Numeric Information with Percentages and Descriptive Risk Labels: A Randomized Trial.Medical decision making : an international journal of the Society for Medical Decision Making · 2015
    Trial
  5. Clear decisions: improved perceptual clarity reduces age-related decision-making deficits.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026
    Article
  6. Article
  7. Question Order Effects in Multidimensional Risk Perception Measurement.Risk analysis : an official publication of the Society for Risk Analysis · 2026
    Article
  8. Lay Understanding of Vaccine Efficacy.Journal of applied research in memory and cognition · 2025
    Article
  9. Article
  10. Cognitive reflection is a distinct and measurable trait.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Age differences in the neural basis of decision-making under uncertainty.Cognitive, affective & behavioral neuroscience · 2023
    Article
  20. Article

27 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Joshua A WellerDecision Research Eugene OR USA.
Nathan F DieckmannDecision Research Eugene OR USA.
Martin TuslerDepartment of Psychology The Ohio State University Columbus OH USA.
C K MertzDecision Research Eugene OR USA.
William J BurnsDecision Research Eugene OR USA.
Ellen PetersDepartment of Psychology The Ohio State University Columbus OH USA.
Decision Research · USThe Ohio State University · US

Funding

Internet Interviewing and the HRSR01AG020717 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KAPTEYN, ARIE · 2002 to 2015
$18.8M
Roybal Center for Health Decision Making and Financial Independence in Old AgeP30AG024962 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KAPTEYN, ARIE · 2004 to 2018
$5.5M
NIA NIH HHS P30 AG024962NIA NIH HHS R01 AG020717
6 · The paper itself

Abstract

Research has demonstrated that individual differences in numeracy may have important consequences for decision making. In the present paper, we develop a shorter, psychometrically improved measure of numeracy-the ability to understand, manipulate, and use numerical information, including probabilities. Across two large independent samples that varied widely in age and educational level, participants completed 18 items from existing numeracy measures. In Study 1, we conducted a Rasch analysis on the item pool and created an eight-item numeracy scale that assesses a broader range of difficulty than previous scales. In Study 2, we replicated this eight-item scale in a separate Rasch analysis using data from an independent sample. We also found that the new Rasch-based numeracy scale, compared with previous measures, could predict decision-making preferences obtained in past studies, supporting its predictive validity. In Study, 3, we further established the predictive validity of the Rasch-based numeracy scale. Specifically, we examined the associations between numeracy and risk judgments, compared with previous scales. Overall, we found that the Rasch-based scale was a better linear predictor of risk judgments than prior measures. Moreover, this study is the first to present the psychometric properties of several popular numeracy measures across a diverse sample of ages and educational level. We discuss the usefulness and the advantages of the new scale, which we feel can be used in a wide range of subject populations, allowing for a more clear understanding of how numeracy is associated with decision processes. Copyright © 2012 John Wiley & Sons, Ltd.

Indexed as

cognitive reflection testdecision makingindividual differencesnumeracyRasch analysis

Identifiers

PMID32313367
PMCPMC7161838
OpenAlexW2163662064

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.