Evidence map›Paper›PMID 30262927›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2019

Sharing data for future research-engaging participants' views about data governance beyond the original project: a DIRECT Study.

Nisha Shah, Victoria Coathup, Harriet Teare, Ian Forgie, Giuseppe Nicola Giordano, Tue Haldor Hansen, Lenka Groeneveld, Michelle Hudson, Ewan Pearson, Hartmut Ruetten and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
–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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

11 authors.

Nisha ShahHeLEX Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK. Nisha.shah@dph.ox.ac.uk.
Victoria CoathupHeLEX Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Harriet TeareHeLEX Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Ian ForgieDivision of Molecular and Clinical Medicine, University of Dundee, Dundee, UK.
Giuseppe Nicola GiordanoDepartment of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
Tue Haldor HansenThe Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Lenka GroeneveldDepartment of Epidemiology and Biostatistics, Vrije Universiteit Medical centre, Amsterdam, The Netherlands.
Michelle HudsonNIHR Exeter Clinical Research Facility, University of Exeter Medical School, Exeter, UK.
Ewan PearsonDivision of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
Hartmut RuettenTranslational Medicine & Early Development, Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany.
Jane KayeHeLEX Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeBiomedical data governance strategies should ensure that data are collected, stored, and used ethically and lawfully. However, research participants' preferences for how data should be governed is least studied. The Diabetes Research on Patient Stratification (DIRECT) project collected substantial amounts of health and genetic information from patients at risk of, and with type II diabetes. We conducted a survey to understand participants' future data governance preferences. Results will inform the postproject data governance strategy.

methodsA survey was distributed in Denmark, Sweden, The Netherlands, and the United Kingdom.

resultsIn total 855 surveys were returned. Ninety-seven percent were supportive of sharing data postproject, and 90% were happy to share data with universities, and 56% with commercial companies. The top three priorities for data sharing were highly secure database, DIRECT researchers to monitor data used by other researchers, and researchers cannot identify participants. Respondents frequently suggested that a postproject Data Access Committee should involve a DIRECT researcher, diabetes clinician, patient representative, and a DIRECT participant.

conclusionPreferences of how data should be governed, and what data could be shared and with whom varied between countries. Researchers are considered as key custodians of participant data. Engaging participants aids in designing governance to support their choices.

Indexed as

AdultAgedAged, 80 and overBiomedical ResearchDatabases, FactualDenmarkDiabetes Mellitus, Type 2Ethics, ResearchFemaleHumansInformation DisseminationMaleMiddle AgedNetherlandsPatient ParticipationResearch Personneldata governancedata sharingethicspatient involvementtype II diabetes

Identifiers

What OpenQuestion 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 OpenQuestion graph.