Evidence map›Paper›PMID 26938633›Full record

ReviewPloS one2016

Improving Decision Making about Genetic Testing in the Clinic: An Overview of Effective Knowledge Translation Interventions.

France Légaré, Hubert Robitaille, Claire Gane, Jessica Hébert, Michel Labrecque, François Rousseau

Open access · goldAbstract readReview
In one paragraph

Review in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
2.7field-weighted citation impact, top 10% 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Perspectives on Consumer and Clinical Genetic Testing Education among Medical Students in West Texas.Journal of community hospital internal medicine perspectives · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Clinical genetic testing in medical education.Proceedings (Baylor University. Medical Center) · 2019
    Article
  13. Article
  14. Article
  15. Article
  16. An Applied Framework in Support of Shared Decision Making aboutAMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    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 at 2 institutions in 1 country.

France LégaréPopulation Health and Practice-Changing Research Group, Centre hospitalier universitaire de Québec Research Centre, Quebec, Canada.
Hubert RobitaillePopulation Health and Practice-Changing Research Group, Centre hospitalier universitaire de Québec Research Centre, Quebec, Canada.
Claire GanePopulation Health and Practice-Changing Research Group, Centre hospitalier universitaire de Québec Research Centre, Quebec, Canada.
Jessica HébertPopulation Health and Practice-Changing Research Group, Centre hospitalier universitaire de Québec Research Centre, Quebec, Canada.
Michel LabrecquePopulation Health and Practice-Changing Research Group, Centre hospitalier universitaire de Québec Research Centre, Quebec, Canada.
François RousseauPopulation Health and Practice-Changing Research Group, Centre hospitalier universitaire de Québec Research Centre, Quebec, Canada.
Centre hospitalier universitaire de Québec · CAUniversité Laval · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnowledge translation (KT) interventions are attempts to change behavior in keeping with scientific evidence. While genetic tests are increasingly available to healthcare consumers in the clinic, evidence about their benefits is unclear and decisions about genetic testing are thus difficult for all parties.

objectiveWe sought to identify KT interventions that involved decisions about genetic testing in the clinical context and to assess their effectiveness for improving decision making in terms of behavior change, increased knowledge and wellbeing.

methodsWe searched for trials assessing KT interventions in the context of genetic testing up to March 2014 in all systematic reviews (n = 153) published by two Cochrane review groups: Effective Practice and Organisation of Care (EPOC) and Consumers and Communication.

resultsWe retrieved 2473 unique trials of which we retained only 28 (1%). Two EPOC reviews yielded two trials of KT interventions: audit and feedback (n = 1) and educational outreach (n = 1). Both targeted health professionals and the KT intervention they assessed was found to be effective. Four Consumers and Communication reviews yielded 26 trials: decision aids (n = 15), communication of DNA-based disease risk estimates (n = 7), personalized risk communication (n = 3) and mobile phone messaging (n = 1). Among these, 25 trials targeted only health consumers or patients and the KT interventions were found to be effective in four trials, partly effective in seven, and ineffective in four. Lastly, only one trial targeted both physicians and patients and was found to be effective.

conclusionsMore research on the effectiveness of KT interventions regarding genetic testing in the clinical context may contribute to patients making informed value-based decisions and drawing the maximum benefit from clinical applications of genetic and genomic innovations.

Indexed as

Decision MakingDecision Support Systems, ClinicalTranslational Research, BiomedicalCommunicationDecision Support TechniquesGenetic Predisposition to DiseaseGenetic TestingHumansOutcome Assessment, Health CarePatient Education as TopicProfessional-Patient RelationsResearch Design

Identifiers

PMID26938633
PMCPMC4777394
OpenAlexW2295146385

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.