Evidence map›Paper›PMID 36125098›Full record

ArticleTranslational behavioral medicine2023

Returning complex genetic risk information to promote better health-related behaviors: a commentary of the literature and suggested next steps.

Morgan N Driver, Sally I-Chun Kuo, Danielle M Dick

Abstract read
In one paragraph

Article in Translational behavioral medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

3 authors.

Morgan N DriverDepartment of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA.ORCID 0000-0001-6738-0667
Sally I-Chun KuoDepartment of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
Danielle M DickDepartment of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA.

Funding

Development of a Novel Personalized Risk Assessment for College Alcohol PreventionR34AA027347 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI WILLIAMS, CHELSEA DERLAN · 2019 to 2021
$610k
NIAAA NIH HHS R34 AA027347
6 · The paper itself

Abstract

Genome-wide association studies aim to identify genetic variants that are associated with a disease phenotype in order to enhance precision medicine efforts. Despite the excitement surrounding the promise of precision medicine and interest among the public in accessing personalized genetic information, there has been little effort dedicated to understanding how complex genetic risk information could be incorporated into clinical practice to inform prevention, screening, and treatment. In this article, we briefly summarize the literature on the impact of receiving genetic risk information on health-related behavior, discuss the limitations of these studies, and outline the challenges that will need to be overcome, along with suggested next steps for future studies, to understand the true promise of precision medicine. The current literature demonstrates that there is no consistent or strong evidence that receiving complex genetic risk information, such as polygenic risk scores, has an impact on behavior; however, there are a number of limitations that may impact the failure to find significant effects associated with receiving genetic feedback. Behavior change is a complex process and simply providing genetic risk information without incorporating a theoretical perspective on behavior change diminishes the potential impact of receiving genetic risk information on actual behavior change. Future studies and interventions which return genetic feedback should be designed using theoretical frameworks of behavior change models to improve the impact of receiving personalized genetic information.

Indexed as

Genome-Wide Association StudyHealth BehaviorHumansRisk Factorsbehavior change theoryhealth behaviorhealth belief modelpersonalized genetic feedbackpolygenic risk scoresprecision medicineprevention

Identifiers

PMID36125098
PMCPMC9972341

What Socratic holds

Textmetadata
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.