Evidence map›Paper›PMID 39266406›Full record

ArticleResearch in social & administrative pharmacy : RSAP2024

Laypersons' understanding of statistical concepts commonly used in prescription drug promotion: A review of the research literature.

Naomi Dyer Yount, Benedicta Osafo-Darko, Willow Burns, Maurice C Johnson, Kevin R Betts, Helen W Sullivan

Abstract read
In one paragraph

Article in Research in social & administrative pharmacy : RSAP, 2024. 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

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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

6 authors.

Naomi Dyer YountWestat, Rockville, MD, USA. Electronic address: naomiyount@westat.com.
Benedicta Osafo-DarkoUniversity of Maryland School of Public Health, College Park, MD, USA. Electronic address: darkoa@umd.edu.
Willow BurnsWestat, Rockville, MD, USA. Electronic address: willowburns@westat.com.
Maurice C JohnsonGeorge Mason University, Fairfax, VA, USA. Electronic address: mjohns38@gmu.edu.
Kevin R BettsU.S. Food and Drug Administration, Silver Spring, MD, USA. Electronic address: kevin.betts@fda.hhs.gov.
Helen W SullivanU.S. Food and Drug Administration, Silver Spring, MD, USA. Electronic address: helen.sullivan@fda.hhs.gov.

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

backgroundThe prevalence of direct-to-consumer (DTC) advertising for prescription drugs has led to concerns about how consumers interpret the medical information conveyed in these ads. One strategy for improving lay understanding of medical information involves incorporating quantitative information about a treatment's potential benefits and risks.

objectiveThis literature review investigates laypersons' interpretations of statistical concepts, expanding on past reviews and including terms that may be used in DTC prescription drug advertising.

methodsWe searched six databases for articles published from January 2000 to October 2021. Articles were included if they were in English and examined general or lay audiences' comprehension of quantitative or statistical concepts, without limiting the context of the studies to medical situations.

resultsWe identified 25 eligible articles. The evidence suggests that likelihood ratios, odds ratios, probabilities, numbers needed to treat/harm, and confidence intervals hinder comprehension of quantitative information. The results are mixed for information presented as frequencies, percentages, absolute risk reduction, and relative risk reduction. The mixed findings could be due to numeracy, framing as risks or benefits, and operationalization of the outcomes. We found no studies examining interpretations of minimum, maximum, central tendency, power, statistical significance, or hazard ratio.

conclusionStudies spanning several decades have examined how laypeople interpret statistical concepts. While a few terms are consistently studied, many questions still remain on how to make risk information more understandable to lay audiences, particularly those with low numeracy.

Indexed as

Prescription DrugsComprehensionDirect-to-Consumer AdvertisingHumansPrescription DrugsLiterature reviewProbabilityRisk communicationRisk comprehensionStatisticsUnderstanding risk

Identifiers

PMID39266406
PMCPMC11578788

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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.