Evidence map›Paper›PMID 35067067›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2022

A Procedure for Eliciting Women's Preferences for Breast Cancer Screening Frequency.

Emily Grayek, Yanran Yang, Baruch Fischhoff, Karen E Schifferdecker, Steven Woloshin, Karla Kerlikowske, Diana L Miglioretti, Anna N A Tosteson

Open access · hybridAbstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Risk-Adapted Breast Screening for Women at Low Predicted Risk of Breast Cancer: An Online Discrete Choice Experiment.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    Article
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

8 authors at 4 institutions in 1 country.

Emily GrayekDepartment of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0003-4158-3866
Yanran YangDepartment of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA.
Baruch FischhoffDepartment of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA.
Karen E SchifferdeckerThe Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Steven WoloshinThe Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Karla KerlikowskeDepartments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Diana L MigliorettiDivision of Biostatistics, Department of Public Health Sciences, University of California, Davis, Davis, CA, USA.
Anna N A TostesonThe Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Carnegie Mellon University · USDartmouth Institute for Health Policy and Clinical Practice · USSan Francisco VA Medical Center · USUniversity of California, Davis · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KARLA M KERLIKOWSKE · 2011 to 2026
$52.9M
NCI NIH HHS P01 CA154292NCI NIH HHS P30 CA023108
6 · The paper itself

Abstract

backgroundWe evaluate the construct validity of a proposed procedure for eliciting lay preferences among health care policy options, suited for structured surveys. It is illustrated with breast cancer screening, a domain in which people may have heterogeneous preferences.

methodsOur procedure applies behavioral decision research principles to eliciting preferences among policy options expressed in quantitative terms. Three-hundred women older than 18 y without a history of breast cancer were recruited through Amazon MTurk. Participants evaluated 4 screening options for each of 4 groups of women, with varying risk of breast cancer. Each option was characterized by estimates of 3 primary outcomes: breast cancer deaths, false alarms, and overdiagnosis resulting in unnecessary treatment of cancers that would not progress. These estimates were based on those currently being developed by the Breast Cancer Surveillance Consortium. For each risk group, participants stated how frequently they would wish to receive screening, if the predicted outcomes applied to them.

resultsA preregistered test found that preferences were robust enough to be unaffected by the order of introducing and displaying the outcomes. Other tests of construct validity also suggested that respondents generally understood the task and expressed consistent preferences. Those preferences were related to participants' age and mammography history but not to measures of their numeracy, subjective numeracy, or demographics. There was considerable heterogeneity in their preferences.

conclusionsMembers of the public can be engaged more fully in informing future screening guidelines if they evaluate the screening options characterized by the expected health outcomes expressed in quantitative terms. We offer and evaluate such a procedure, in terms of its construct validity with a diverse sample of women. HIGHLIGHTS: A novel survey method for eliciting lay preferences for breast cancer screening is proposed and evaluated in terms of its construct validity.Participants were generally insensitive to irrelevant task features (e.g., order of presentation) and sensitive to relevant ones (e.g., quantitative estimates of breast cancer risk, harms from screening).The proposed method elicits lay preferences in terms that can inform future screening guidelines, potentially improving communication between the public and policy makers.

Indexed as

Breast NeoplasmsEarly Detection of CancerFemaleHumansMammographyMass ScreeningRisk Factorsbreast cancer screeningclinical guidelinesmammographypreference elicitationrisk communicationsurvey methodology

Identifiers

PMID35067067
PMCPMC9277327
OpenAlexW4206950060

What OpenQuestion holds

Textmetadata
LicenceTDM
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.