TY - JOUR
T1 - Data sharing practices in randomized trials of addiction interventions
AU - Vassar, Matt
AU - Jellison, Sam
AU - Wendelbo, Hannah
AU - Wayant, Cole
N1 - Funding Information:
The cultural push for transparent — or “open” — scientific practices aims to improve the validity and reproducibility of research ( Munafò, Nosek, & Bishop, 2017 ). Open science is a means to reduce the incidence and effect of bias, which has historically been detected in high volume. Examples of such bias include selective reporting of results ( Wayant, Scheckel, & Hicks, 2017 ), p-hacking — defined as the collection or analysis of data until nonsignificant results become significant ( Head, Holman, Lanfear, Kahn, & Jennions, 2015 ), and hypothesizing after the results are known (HARK-ing) ( Kerr, 1998 ). It is argued that adherence to open scientific practices, which includes publishing an a priori protocol and depositing raw data and metadata (e.g., data assumptions or transformations) in a public repository, benefits both the individual scientist and science as a whole( Dijkers, 2019 ). Science as a whole may benefit from open science through increased rigor and validity of study findings (through independent replication) ( Vickers, 2011 ) or the ability to reconstruct analyses in a manner that tailors findings to unique clinical settings ( Krumholz, 2015 ). Individual scientists are said to benefit from open science practices through increased citations and media attention to their articles ( McKiernan, Bourne, & Titus Brown, 2016 ). Additionally, open science practices may benefit patient health ( Aitken, de St, Pagliari, Jepson, & Cunningham-Burley, 2016 ). Because the benefits to society and science are widely believed to outweigh harms, such as increased time for authors ( Dijkers, 2019 ), numerous initiatives to require data sharing have appeared. For example, the National Institutes of Health (2003a), National Science Foundation (2018) , and the Wellcome Trust (2017) — all major US- and UK-based funding agencies — now require full data sharing in some form. In this study, we investigated whether RCTs of interventions for drug, alcohol, or tobacco addictions published in highly ranked addiction journals used data sharing procedures and whether trialists made their data publicly available. 2
Funding Information:
The research results discussed in this publication were made possible in total or in part by funding through the award for project number HR18-119 , from the Oklahoma Center for the Advancement of Science and Technology .
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/3
Y1 - 2020/3
N2 - Introduction: Transparent, open scientific research practices aim to improve the validity and reproducibility of research findings. A key component of open science is the public sharing of data and metadata that constitute the basis for research findings. Methods: We conducted a 6 year cross-sectional investigation of the rates and methods of data sharing in 15 high-impact addiction journals that publish clinical trials. We extracted trial characteristics and whether the trial data were shared publicly in any form. We conducted a sensitivity analysis of only trials with public funding sources. Results: In the included journals, zero (0/394, 0.0%) RCTs shared their data publicly. The large majority (315/394, 79.9%) of included trials received funding from public sources. Eight journals had data sharing policies and published 299 of the included trials (75.9%). Conclusion: Our finding has significant implications for the addiction research community. These implications are broad, ranging from possibly slowed scientific advancement to noncompliance with obligations to the public whose tax dollars funded a large majority of the included RCTs. To improve the rates of data sharing, we recommend studying incentive systems, while simultaneously working to cultivate a data sharing system that emphasizes scientific, rather than author, accuracy.
AB - Introduction: Transparent, open scientific research practices aim to improve the validity and reproducibility of research findings. A key component of open science is the public sharing of data and metadata that constitute the basis for research findings. Methods: We conducted a 6 year cross-sectional investigation of the rates and methods of data sharing in 15 high-impact addiction journals that publish clinical trials. We extracted trial characteristics and whether the trial data were shared publicly in any form. We conducted a sensitivity analysis of only trials with public funding sources. Results: In the included journals, zero (0/394, 0.0%) RCTs shared their data publicly. The large majority (315/394, 79.9%) of included trials received funding from public sources. Eight journals had data sharing policies and published 299 of the included trials (75.9%). Conclusion: Our finding has significant implications for the addiction research community. These implications are broad, ranging from possibly slowed scientific advancement to noncompliance with obligations to the public whose tax dollars funded a large majority of the included RCTs. To improve the rates of data sharing, we recommend studying incentive systems, while simultaneously working to cultivate a data sharing system that emphasizes scientific, rather than author, accuracy.
KW - Data sharing
KW - Randomized controlled trials
KW - Research methodology
UR - http://www.scopus.com/inward/record.url?scp=85075278779&partnerID=8YFLogxK
U2 - 10.1016/j.addbeh.2019.106193
DO - 10.1016/j.addbeh.2019.106193
M3 - Article
C2 - 31770694
AN - SCOPUS:85075278779
VL - 102
JO - Addictive Behaviors
JF - Addictive Behaviors
SN - 0306-4603
M1 - 106193
ER -