Consensus Statement on Public Involvement and Engagement with Data-Intensive Health Research

This consensus statement reflects the deliberations of an international group of stakeholders with a range of expertise in public involvement and engagement (PI&E) relating to data-intensive health research. It sets out eight key principles to establish a secure role for PI&E in and with the...

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Vydáno v:International journal of population data science Ročník 4; číslo 1; s. 586
Hlavní autoři: Aitken, Mhairi, Tully, Mary P, Porteous, Carol, Denegri, Simon, Cunningham-Burley, Sarah, Banner, Natalie, Black, Corri, Burgess, Michael, Cross, Lynsey, Van Delden, Johannes, Ford, Elizabeth, Fox, Sarah, Fitzpatrick, Natalie, Gallacher, Kay, Goddard, Catharine, Hassan, Lamiece, Jamieson, Ron, Jones, Kerina H, Kaarakainen, Minna, Lugg-Widger, Fiona, McGrail, Kimberlyn, McKenzie, Anne, Moran, Rosalyn, Murtagh, Madeleine J, Oswald, Malcolm, Paprica, Alison, Perrin, Nicola, Richards, Emma Victoria, Rouse, John, Webb, Joanne, Willison, Donald J
Médium: Journal Article
Jazyk:angličtina
Vydáno: Wales Swansea University 12.02.2019
Témata:
Population Data Science
ISSN:2399-4908, 2399-4908
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Abstract This consensus statement reflects the deliberations of an international group of stakeholders with a range of expertise in public involvement and engagement (PI&E) relating to data-intensive health research. It sets out eight key principles to establish a secure role for PI&E in and with the research community internationally and ensure best practice in its execution. Our aim is to promote culture change and societal benefits through ensuring a socially responsible trajectory for innovations in this field. Our key premise is that the public should not be characterised as a problem to be overcome but a key part of the solution to establish socially beneficial data-intensive health research for all.
AbstractList This consensus statement reflects the deliberations of an international group of stakeholders with a range of expertise in public involvement and engagement (PI&E) relating to data-intensive health research. It sets out eight key principles to establish a secure role for PI&E in and with the research community internationally and ensure best practice in its execution. Our aim is to promote culture change and societal benefits through ensuring a socially responsible trajectory for innovations in this field. Our key premise is that the public should not be characterised as a problem to be overcome but a key part of the solution to establish socially beneficial data-intensive health research for all.
This consensus statement reflects the deliberations of an international group of stakeholders with a range of expertise in public involvement and engagement (PI&E) relating to data-intensive health research. It sets out eight key principles to establish a secure role for PI&E in and with the research community internationally and ensure best practice in its execution. Our aim is to promote culture change and societal benefits through ensuring a socially responsible trajectory for innovations in this field. Our key premise is that the public should not be characterised as a problem to be overcome but a key part of the solution to establish socially beneficial data-intensive health research for all.
Author Gallacher, Kay
Hassan, Lamiece
Ford, Elizabeth
Porteous, Carol
Cunningham-Burley, Sarah
Fox, Sarah
Banner, Natalie
Fitzpatrick, Natalie
Kaarakainen, Minna
Richards, Emma Victoria
Goddard, Catharine
Webb, Joanne
Denegri, Simon
Van Delden, Johannes
Oswald, Malcolm
Jones, Kerina H
Jamieson, Ron
Willison, Donald J
Black, Corri
Paprica, Alison
Cross, Lynsey
McGrail, Kimberlyn
McKenzie, Anne
Perrin, Nicola
Lugg-Widger, Fiona
Moran, Rosalyn
Burgess, Michael
Murtagh, Madeleine J
Rouse, John
Aitken, Mhairi
Tully, Mary P
AuthorAffiliation 8 University Medical Centre Utrecht, Julius Centre for Health Sciences, Uniwersiteitsweg 100, 3584 CG Utrecht, Netherlands
22 Public Panel, Farr Institute of Health Informatics Research, London, UK
5 University of Aberdeen, Institute of Applied Health Sciences, Aberdeen Centre for Health Data Science, School of Medicine, Medical Science and Nutrition, Foresterhill, Aberdeen AB25 2ZD
16 University of Western Australia, Faculty of Health and Medical Sciences, School of Population and Global Health, 35 Stirling Highway, 6009 Perth Australia
18 Newcastle University, The School of Geography, Politics and Sociology, Windsor Terrace, Newcastle upon Tyne NE2 4HE , UK
13 Public Panel, Farr Institute of Health Informatics Research, Scotland, UK
7 Swansea University. Population Data Science, Medical School, Singleton Campus, Swansea SA2 8PP, UK
6 University of British Columbia, Faculty of Medicine, School of Population and Public Health, 2206 East Mall Vancouver, BC Canada V6T 1Z3
1 University of Edinbur
AuthorAffiliation_xml – name: 5 University of Aberdeen, Institute of Applied Health Sciences, Aberdeen Centre for Health Data Science, School of Medicine, Medical Science and Nutrition, Foresterhill, Aberdeen AB25 2ZD
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– name: 19 University of Toronto, Dalla Lana School of Public Health, Institute of Health Policy, Management and Evaluation, Health Sciences Building,155 College Street, Toronto, ON M5T 3M6, Canada
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Conflicts of interest: Dr. Aitken reports grants from The Farr Institute at The University of Manchester is supported by a 10-funder consortium led by the MRC (Grant No: MR/M501633/2), during the conduct of the study; Dr. Black reports grants from Farr Institute UK (MRC collaboration), grants from ESRC (ADRC-Scotland), during the conduct of the study; Dr Cunningham-Burley reports grants from Farr Institute UK (MRC collaboration (Grant No: MR/M501633/2), grants from ESRC (ADRC-Scotland), during the conduct of the study; Dr. Denegri reports non-financial support and other from National Institute for Health Research (NIHR), personal fees and non-financial support from University College London, personal fees from Google DeepMind Health, grants from Wellcome Trust, other from a wide range of engagements, speaking invitations and requests for advice consistent with my expertise some of which relates to the submitted work, outside the submitted work; Dr. Goddard reports grants from MRC, during the conduct of the study; Dr. Tully reports grants from The Farr Institute at The University of Manchester which is supported by a 10-funder consortium led by the MRC (Grant No: MR/M501633/2), during the conduct of the study; non-financial support from EuroRec Institute, non-financial support from BioData World Congress, outside the submitted work.
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Snippet This consensus statement reflects the deliberations of an international group of stakeholders with a range of expertise in public involvement and engagement...
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SubjectTerms Population Data Science
Title Consensus Statement on Public Involvement and Engagement with Data-Intensive Health Research
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