Evidence map›Paper›PMID 38903012›Full record

Trial reportMedical decision making : an international journal of the Society for Medical Decision Making2024

Using Separate Single-Outcome Risk Presentations Instead of Integrated Multioutcome Formats Improves Comprehension in Discrete Choice Experiments.

Matthew J Wallace, E Hope Weissler, Jui-Chen Yang, Laura Brotzman, Matthew A Corriere, Eric A Secemsky, Jessie Sutphin, F Reed Johnson, Juan Marcos Gonzalez, Michelle E Tarver and 9 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Medical decision making : an international journal of the Society for Medical Decision Making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

19 authors.

Matthew J WallaceDuke Clinical Research Institute, Durham, NC, USA.ORCID 0000-0002-6250-4998
E Hope WeisslerDuke University School of Medicine, Durham, NC, USA.
Jui-Chen YangDuke Clinical Research Institute, Durham, NC, USA.ORCID 0000-0001-8229-6578
Laura BrotzmanUniversity of Michigan School of Public Health, Ann Arbor, MI, USA.ORCID 0000-0003-3243-0913
Matthew A CorriereUniversity of Michigan Medical School, Ann Arbor, MI, USA.ORCID 0000-0002-7415-0322
Eric A SecemskyBeth Israel Deaconess Medical Center, Boston, MA, USA.
Jessie SutphinDuke Clinical Research Institute, Durham, NC, USA.ORCID 0000-0002-2000-3677
F Reed JohnsonDuke Clinical Research Institute, Durham, NC, USA.ORCID 0000-0002-7572-2150
Juan Marcos GonzalezDuke Clinical Research Institute, Durham, NC, USA.ORCID 0000-0002-5386-0907
Michelle E TarverUS Food and Drug Administration, Silver Spring, MD, USA.
Anindita SahaUS Food and Drug Administration, Silver Spring, MD, USA.ORCID 0000-0003-0306-4264
Allen L ChenUS Food and Drug Administration, Silver Spring, MD, USA.ORCID 0000-0001-9348-0143
David J GebbenUS Food and Drug Administration, Silver Spring, MD, USA.
Misti MaloneUS Food and Drug Administration, Silver Spring, MD, USA.
Andrew FarbUS Food and Drug Administration, Silver Spring, MD, USA.
Olufemi BabalolaUS Food and Drug Administration, Silver Spring, MD, USA.
Eva M RorerUS Food and Drug Administration, Silver Spring, MD, USA.
Brian J Zikmund-FisherUniversity of Michigan School of Public Health, Ann Arbor, MI, USA.ORCID 0000-0002-1637-4176
Shelby D ReedDuke Clinical Research Institute, Durham, NC, USA.ORCID 0000-0002-7654-4464

Funding

Shared Decision-Making to Improve the Health Status of Patients with Claudication: Developing and Implementing Strategies to Individualize Treatment DecisionsK23HL150290 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SECEMSKY, ERIC ALEXANDER · 2020 to 2024
$851k
Addressing variability in peripheral arterial disease outcomes using machine learning techniquesF32HL151181 · NHLBI · DUKE UNIVERSITY · PI WEISSLER, ELIZABETH HOPE · 2020 to 2021
$130k
FDA HHS 75F40120C00157NHLBI NIH HHS F32 HL151181NHLBI NIH HHS K23 HL150290
6 · The paper itself

Abstract

introductionDespite decades of research on risk-communication approaches, questions remain about the optimal methods for conveying risks for different outcomes across multiple time points, which can be necessary in applications such as discrete choice experiments (DCEs). We sought to compare the effects of 3 design factors: 1) separated versus integrated presentations of the risks for different outcomes, 2) use or omission of icon arrays, and 3) vertical versus horizontal orientation of the time dimension.

methodsWe conducted a randomized study among a demographically diverse sample of 2,242 US adults recruited from an online panel (mean age 59.8 y,

resultsMean comprehension varied significantly across versions (

conclusionsIn presentations of multiple risks over multiple time points, presenting risk information separately for each health outcome appears to increase understanding. HIGHLIGHTS: When conveying information about risks of different outcomes at multiple time points, separate presentations of single-outcome risks resulted in higher comprehension than presentations that combined risk information for different outcomes.We also observed benefits of presenting single-outcome risks separately among respondents with lower numeracy and graph literacy.Study participants who scored higher on risk understanding were more internally consistent in their responses to a discrete choice experiment.

Indexed as

Choice BehaviorComprehensionAdultAgedCommunicationFemaleHealth LiteracyHumansMaleMiddle AgedRisk AssessmentSurveys and Questionnairesdiscrete choice experimentliteracynumeracyrisk-communication

Identifiers

PMID38903012
PMCPMC12635851

What Socratic holds

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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 Socratic graph.