Evidence map›Paper›PMID 38363501›Full record

ArticleThe patient2024

Pretesting Discrete-Choice Experiments: A Guide for Researchers.

Nicola B Campoamor, Christi J Guerrini, Whitney Bash Brooks, John F P Bridges, Norah L Crossnohere

Open access · hybridAbstract read
In one paragraph

Article in The patient, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
55.3field-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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Nicola B CampoamorDepartment of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Christi J GuerriniCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA.
Whitney Bash BrooksCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA.
John F P BridgesDepartment of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Norah L CrossnohereDivision of General Internal Medicine, Department of Internal Medicine, The Ohio State University College of Medicine, Columbus, OH, USA. Norah.crossnohere@osumc.edu.ORCID 0000-0002-2811-1330
The Ohio State University · USBaylor College of Medicine · US

Funding

IGG on the Internet: Characterizing Public Perspectives on Law Enforcement Use of Genetic Genealogy Data in Social MediaR01HG011268 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GUERRINI, CHRISTI, MCGUIRE, AMY L · 2020 to 2023
$2.4M
NHGRI NIH HHS R01 HG011268NHGRI NIH HHS R01HG011268
6 · The paper itself

Abstract

Discrete-choice experiments (DCEs) are a frequently used method to explore the preferences of patients and other decision-makers in health. Pretesting is an essential stage in the design of a high-quality choice experiment and involves engaging with representatives of the target population to improve the readability, presentation, and structure of the preference instrument. The goal of pretesting in DCEs is to improve the validity, reliability, and relevance of the survey, while decreasing sources of bias, burden, and error associated with preference elicitation, data collection, and interpretation of the data. Despite its value to inform DCE design, pretesting lacks documented good practices or clearly reported applied examples. The purpose of this paper is: (1) to define pretesting and describe the pretesting process specifically in the context of a DCE, (2) to present a practical guide and pretesting interview discussion template for researchers looking to conduct a rigorous pretest of a DCE, and (3) to provide an illustrative example of how these resources were operationalized to inform the design of a complex DCE aimed at eliciting tradeoffs between personal privacy and societal benefit in the context of a police method known as investigative genetic genealogy (IGG).

Indexed as

Choice BehaviorPatient PreferenceHumansReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID38363501
PMCPMC10894089
OpenAlexW4391882309

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.