The role of data sharing in survey dropout: a study among scientists as respondents
| Date | 18 November 2022 |
| Pages | 864-879 |
| DOI | https://doi.org/10.1108/JD-06-2022-0135 |
| Published date | 18 November 2022 |
| Subject Matter | Library & information science,Records management & preservation,Document management,Classification & cataloguing,Information behaviour & retrieval,Collection building & management,Scholarly communications/publishing,Information & knowledge management,Information management & governance,Information management,Information & communications technology,Internet |
| Author | Urs Alexander Fichtner,Lukas Maximilian Horstmeier,Boris Alexander Brühmann,Manuel Watter,Harald Binder,Jochen Knaus |
The role of data sharing in survey
dropout: a study among scientists
as respondents
Urs Alexander Fichtner
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –University of Freiburg,
Freiburg im Breisgau, Germany
Lukas Maximilian Horstmeier and Boris Alexander Br€
uhmann
Section of Health Care Research and Rehabilitation Research,
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –University of Freiburg,
Freiburg im Breisgau, Germany, and
Manuel Watter, Harald Binder and Jochen Knaus
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –University of Freiburg,
Freiburg im Breisgau, Germany
Abstract
Purpose –One of the currently debated changes in scientific practice is the implementation of data sharing
requirements for peer-reviewed publication to increase transparency and intersubjective verifiability of
results. However, it seems that data sharing is a not fully adopted behavior among researchers. The theory
of planned behavior was repeatedly applied to explain drivers of data sharing from the perspective of data
donors (researchers). However, data sharing can be viewed from another perspective as well: survey
participants. The research questions (RQs) for this study were as follows: 1 Does data sharing increase
participant’s nonresponse? 2 Does data sharing influence participant’s response behavior? The purpose of
this paper is to address these issues.
Design/methodology/approach–To answer the RQs, a mixed methods approach was applied, consisting
of a qualitative prestudy and a quantitative survey including an experimental component. The latter was a
two-group setup with an intervention group (A) and a control group (B). A list-based recruiting of members
of the Medical Faculty of the University of Freiburg was applied for 15 days. For exploratory data analysis
of dropouts and nonresponse, we used Fisher’s exact tests and binary logistic regressions.
Findings –In sum, we recorded197 cases for Group A and 198 cases for Group B. We found no systematic
group differences regarding response bias or dropout. Furthermore, we gained insight s into the
experiences our sample made with data sharing: half of our sample already requested data of other
researchers or shared data on request of other researchers. Data repositories, however, were used less
frequently: 28% of our respondents used data from repositories and 19% stored data in a repository.
JD
79,4
864
Ethics approval: This study was performed in line with the principles of the Declaration of Helsinki. The
study has been granted by the Ethics Committee of the Albert-Ludwigs-Universit€
at Freiburg.
Furthermore, it was reviewed and approved by the data security officer of the Medical Center of the
University of Freiburg. Data collection was based on written informed consent. In case of missing
informed consent, we excluded those cases from analysis.
Funding: This project was funded by the Medical Faculty of the University Hospital and Medical
Center of the University of Freiburg.
Conflicts of interests: All authors certify that there is no actual or potential conflict of interest in
relation to this article.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0022-0418.htm
Received 23 June 2022
Revised 17 October 2022
Accepted 23 October 2022
Journal of Documentation
Vol. 79 No. 4, 2023
pp. 864-879
© Emerald Publishing Limited
0022-0418
DOI 10.1108/JD-06-2022-0135
Originality/value –To the authors’knowledge, their study is the first study that includes researchers as
survey subjects investigating the effect of data sharing on their response patterns.
Keywords Data sharing, Data publication, Attitudes toward data sharing, Dropout rate, Researcher behavior,
Survey response bias
Paper type Research paper
Introduction
Discussion on the implementation of rules for good scientific practice represents a
fundamental and ongoing aspect of the scientific method and within its community.
Amplified in recent years by the replication crisis of published results within the social
sciences (Callaway, 2011), a new debate on additional measures of quality control and
transparency within the scientific process has emerged (e.g. (Craig et al., 2020)). One of the
currently debated changes in scientific practice is the implementation of data sharing
requirements for peer-reviewed publication to increase transparency and intersubjective
verifiability of results. In 2009 and 2021, e.g. the German Research Society (Deutsche
Forschungsgemeinschaft (DFG)) continuously pushed this topic by updating a guideline
emphasizing the necessity of clearly documented and available research data to enable
replication of scientific outcomes (DFG–Deutsche Forschungsgemeinschaft, 2009,2021).
Despite these initiatives toward data sharing, these principles are, however, not well
established within the broader scientific practiceand face several criticisms (Brase et al., 2015;
Rauber et al., 2016;Zenk-M€
oltgen et al., 2018). Focusing on the subjective aspects among data
sharing–the behavior of data don or and researcher, potential drivers or barriers for researchers
sharing their data might be occupational experience (Zenk-M€
oltgen et al., 2018), a lack of
incentives (Devriendt et al.,2021) or potential fear of data misuse (Abele-Brehm et al., 2019).
Whilea body of research emphasizesthe role of theresearcher in relationto data sharing(Bailey,
2022;Devriendtet al., 2021;Federer et al., 2015;Houtkoop et al., 2018;Joo et al.,2017;Perrieret al.,
2020;Tenopir et al., 2011;Zenk-M€
oltgen et al., 2018), we could not find correspondingresearch
specifically on the implications of datasharing for the behaviorof research participants, e.g.due
to concerns of data protection, trust and confidentiality. Two systematic reviews address
individuals’perspectives on data sharing in the context of biobanking (Garrison et al., 2016;
Shabaniet al., 2014). Garrison et al. found that ind ividual consent for shar ing research data was
preferred to broad consent indicating that perceived control over the data flow plays a rolein
data sharing. This is supported by the conclusions made by Shabani et al. stating that
individuals are concerned about the breadth of data access. However,Garrison et al. point out
that there are gapsin knowledge about individualdecision factors.
The theory of planned behavior(TPB) was therefore applied to conceptualize behavior for
the subjective aspectsamong data sharing (Ajzen, 1991;Kim and Stanton, 2016;Zenk-M€
oltgen
et al., 2018), both in relation to study-participants’survey response as well as for researchers
sharing data. Introducing the role of beliefs, attitudes, norms and resources as factors
influencing behavior (Ajzen, 1991;Kim and Zhang, 2015), an individual decidesto participatein
a survey(behavioralintention) or notand, as consequence,executesthe correspondentbehavior.
As nextsteps, this paperwill (1) integratesurvey responsebehavior into thestate of research
on data sharing pointing out the double role of researchers as respondents in our study,
(2) present theapplied methodology of the small experimental explorative study,(3) show the
results and (4)discuss the implicationsof our research findings within the scientific context.
Data sharing in practice
Some authors argue that the lack of data sharing is a scientific disservice to society and
requires a top-down action that unites all initiatives to improve the research cycle (Peat et al.,
2014;Van Calster et al., 2021). Data sharing is expected to not only increase transparency of
research results by enabling intersubjective verifiability, but also to offer the chance of
The role of data
sharing in
survey dropout
865
Get this document and AI-powered insights with a free trial of vLex and Vincent AI
Get Started for FreeStart Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting