Feasibility of methods to reduce publication bias_academics/researchers

We conducted a survey to help understand the views of academics/researchers with regards to different methods of the publication and peer-review process to help reduce publication bias. Respondents were asked questions about their views on publication bias and the publication process in general, followed by nine proposals which have been suggested to reduce publication bias. They were asked to choose the proposal they felt to be 'most effective' at reducing publication bias, and were asked to rate each proposal from 1 (not at all effective) to 5 (very effective). Throughout the survey, there was open ended questions (all optional to complete) so that respondents were able to discuss the pros and cons to any of the proposals.

Responses from academics/researchers in the project "The perceived feasibility of methods to reduce publication bias".

Data were collected via Bristol Online Surveys. Using convenience snowball method, we collected opinions from academics and researchers regarding 9 different methods of peer-review/publication that have been proposed to reduce publication bias. Respondents were asked questions regarding their views on the efficacy of the publication process, and then asked to choose the method they felt to be most effective at reducing publication bias, and to rate all the methods from 1 (not at all effective) to 5 (very effective) . Throughout the survey, non-compulsory open ended questions were provided in order for respondents to provide their opinions on the pros and cons of the methods.

Keywords:
publication bias, peer-review, research publication, open science, study reporting
Subjects:
Sociology

Cite this dataset as:
Carroll, H., 2017. Feasibility of methods to reduce publication bias_academics/researchers. Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00348.

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Data

Raw_data_Academics, … clean.xlsx
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet (90kB)
Creative Commons: Attribution 4.0

Creators

Contributors

University of Bath
Rights Holder

Coverage

Collection date(s):

From 1 September 2015 to 7 December 2015

Temporal coverage:

From 1 September 2015 to 7 December 2015

Geographical coverage:

UK

Documentation

Data collection method:

Bristol Online Surveys was used to gain opinions of academics/researchers regarding the different proposed methods to reduce publication bias during the peer-review and publication process. A convenience snowballing method was used, disseminated via email and Twitter.

Data processing and preparation activities:

The ID as used in the manuscript has been included under ‘ID’. The answers to question 15.a. (‘If yes, would you be willing to name the journal(s) you have most recently published in (maximum 5)?’) have been changed to the mean impact factor (to one decimal place) of the journal(s) stated, rather than providing the journal(s) names. Institution names have been replaced with their respective country.

Funders

Economic and Social Research Council
https://doi.org/10.13039/501100000269

South West ESRC Doctoral Training Centre DTG 2011
ES/J50015X/1

Publication details

Publication date: 24 March 2017
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-00348

URL for this record: https://researchdata.bath.ac.uk/id/eprint/348

Related papers and books

Carroll, H. A., Toumpakari, Z., Johnson, L., and Betts, J. A., 2017. The perceived feasibility of methods to reduce publication bias. PLOS ONE, 12(10), e0186472. Available from: https://doi.org/10.1371/journal.pone.0186472.

Related datasets and code

Carroll, H., 2017. Feasibility of methods to reduce publication bias_editors. Version 1. Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00347.

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: Harriet Carroll

Departments:

Faculty of Humanities & Social Sciences
Health