Evidence map›Paper›PMID 28527373›Full record

ArticleSocial science & medicine (1982)2017

"I don't believe it." Acceptance and skepticism of genetic health information among African-American and White smokers.

Erika A Waters, Linda Ball, Sarah Gehlert

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 3% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Testing Explanations for Skepticism of Personalized Risk Information.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
    Article
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  10. Translating Cancer Risk Prediction Models into Personalized Cancer Risk Assessment Tools: Stumbling Blocks and Strategies for Success.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
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  14. Review
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

3 authors at 1 institution in 2 countries.

Erika A WatersWashington University in St. Louis, USA. Electronic address: waterse@wudosis.wustl.edu.
Linda BallWashington University in St. Louis, USA.
Sarah GehlertWashington University in St. Louis, USA.
Washington University in St. Louis · US

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Infectious Diseases/Basic Microbial Pathogenic MechanismsT32AI007172 · NIAID · WASHINGTON UNIVERSITY · PI Daniel E. Goldberg, JENNIFER A PHILIPS · 1985 to 2026
$13.0M
NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1 TR002345NIAID NIH HHS T32 AI007172NIMHD NIH HHS L60 MD006280
6 · The paper itself

Abstract

rationaleEffective translation of genomics research into practice depends on public acceptance of genomics-related health information.

objectiveTo explore how smokers come to accept or reject information about the relationship between genetics and nicotine addiction.

methodsThirteen focus groups (N = 84) were stratified by education (seven < Bachelor's degree, six ≥ Bachelor's degree) and race (eight black, five white). Participants viewed a 1-min video describing the discovery of a genetic variant associated with increased risk of nicotine addiction and lung cancer. Next, they provided their opinions about the information. Two coders analyzed the data using grounded theory.

resultsPre-video knowledge about why people smoke cigarettes and what genetic risk means informed beliefs about the relationship between genes and addiction. These beliefs were not always consistent with biomedical explanations, but formed the context through which participants processed the video's information. This, in turn, led to information acceptance or skepticism. Participants explained their reactions in terms of the scientific merits of the research and used their existing knowledge and beliefs to explain their acceptance of or skepticism about the information.

conclusionLaypeople hold complex understandings of genetics and addiction. However, when lay and biomedical explanations diverge, genetics-related health information may be rejected.

Indexed as

Educational StatusPatient Acceptance of Health CareRacial GroupsSmokersAdultBlack or African AmericanFemaleFocus GroupsGrounded TheoryHealth Knowledge, Attitudes, PracticeHumansLung NeoplasmsMaleMiddle AgedQualitative ResearchSmokingGene-environment interactionHealth communicationInformation processingMessage rejectionTobacco use

Identifiers

PMID28527373
PMCPMC5535773
OpenAlexW2610454920

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.