Published in:
Open Access 01-12-2014 | Research article
Barriers to and facilitators of interventions to counter publication bias: thematic analysis of scholarly articles and stakeholder interviews
Published in: BMC Health Services Research | Issue 1/2014
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Background
When the nature and direction of research results affect their chances of publication, a distortion of the evidence base – termed publication bias – results. Despite considerable recent efforts to implement measures to reduce the non-publication of trials, publication bias is still a major problem in medical research. The objective of our study was to identify barriers to and facilitators of interventions to prevent or reduce publication bias.
Methods
We systematically reviewed the scholarly literature and extracted data from articles. Further, we performed semi-structured interviews with stakeholders. We performed an inductive thematic analysis to identify barriers to and facilitators of interventions to counter publication bias.
Results
The systematic review identified 39 articles. Thirty-four of 89 invited interview partners agreed to be interviewed. We clustered interventions into four categories: prospective trial registration, incentives for reporting in peer-reviewed journals or research reports, public availability of individual patient-level data, and peer-review/editorial processes. Barriers we identified included economic and personal interests, lack of financial resources for a global comprehensive trial registry, and different legal systems. Facilitators identified included: raising awareness of the effects of publication bias, providing incentives to make data publically available, and implementing laws to enforce prospective registration and reporting of clinical trial results.
Conclusions
Publication bias is a complex problem that reflects the complex system in which it occurs. The cooperation amongst stakeholders to increase public awareness of the problem, better tailoring of incentives to publish, and ultimately legislative regulations have the greatest potential for reducing publication bias.