Evidence map›Paper›PMID 30843639›Full record

ArticleJournal of genetic counseling2019

Exploring genetic counselors' perceptions of usefulness and intentions to use refined risk models in clinical care based on the Technology Acceptance Model (TAM).

Christopher Heinlen, Shelly R Hovick, Guy N Brock, Brett G Klamer, Amanda Ewart Toland, Leigha Senter

Abstract read
In one paragraph

Article in Journal of genetic counseling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Review
  3. 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

6 authors.

Christopher HeinlenDivision of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, Ohio.
Shelly R HovickSchool of Communication, The Ohio State University, Columbus, Ohio.
Guy N BrockDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio.
Brett G KlamerCenter for Biostatistics, The Ohio State University, Columbus, Ohio.
Amanda Ewart TolandDivision of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, Ohio.
Leigha SenterDivision of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, Ohio.

Funding

The OSU Center for Clinical and Translational Science: Advancing Today's Discoveries to Improve HealthUL1TR002733 · NCATS · OHIO STATE UNIVERSITY · PI RINGEL, MATTHEW D · 2018 to 2022
$28.9M
The Ohio State University Center for clinical and Translational ScienceUL1TR001070 · NCATS · OHIO STATE UNIVERSITY · PI JACKSON, REBECCA D · 2013 to 2017
$22.6M
NCATS NIH HHS UL1 TR001070NCATS NIH HHS UL1 TR002733
6 · The paper itself

Abstract

Pathogenic germline mutations in the BRCA1 or BRCA2 genes are associated with an elevated lifetime risk for breast (50%-85% risk) and ovarian cancer (20%-40% risk). Genome-wide association studies have identified over 100 genetic variants associated with modified breast and/or ovarian cancer risk in BRCA1 and BRCA2 carriers. Risk models generated based on these variants have shown that these genetic modifiers strongly influence absolute risk of developing breast or ovarian cancer in BRCA mutation carriers. There is a lack of understanding, however, about the clinical applicability and utility of these risk models. To investigate this gap, we collected survey data from 274 cancer genetic counselors (GCs) through the National Society of Genetic Counselors Cancer Special Interest Group. Questions assessed perceptions of usefulness and intentions of genetic counselors to use these refined risk models in clinical care based on the Technology Acceptance Model (TAM). We found that GCs' reactions to the estimates were largely positive, though they thought the possibility of changing management based on results was unlikely. Additionally, we found that more experienced GCs were more likely to consider refined risk estimates in clinic. Support also was provided for core predictions within the TAM, whereby the perceived usefulness (indirect effect est. = 0.08, 95% CI: [0.04, 0.13]) and perceived ease of use (indirect effect est. = 0.078, 95% CI: [0.04, 0.13]) of refined risk estimates were indirectly associated with intentions to use via attitudes.

Indexed as

Attitude of Health PersonnelGenes, BRCA1Genes, BRCA2Genetic CounselingIntentionAdultBreast NeoplasmsCounselorsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGerm-Line MutationHumansMiddle AgedUnited StatesBRCA1BRCA2cancer riskGenetic counselorsgenetic modifiersrisk modelsTechnology Acceptance Model

Identifiers

PMID30843639
PMCPMC6548677

What OpenQuestion holds

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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.