BACKGROUND: Selective reporting is wasteful, leads to bias in the published record and harms the credibility of science. Studies on potential determinants of selective reporting currently lack a shared taxonomy and a causal framework.
OBJECTIVE: To develop a taxonomy of determinants of selective reporting in science.
DESIGN: Inductive qualitative content analysis of a random selection of the pertinent literature including empirical research and theoretical reflections.
METHODS: Using search terms for bias and selection combined with terms for reporting and publication, we systematically searched the PubMed, Embase, PsycINFO and Web of Science databases up to January 8, 2015. Of the 918 articles identified, we screened a 25 percent random selection. From eligible articles, we extracted phrases that mentioned putative or possible determinants of selective reporting, which we used to create meaningful categories. We stopped when no new categories emerged in the most recently analyzed articles (saturation).
RESULTS: Saturation was reached after analyzing 64 articles. We identified 497 putative determinants, of which 145 (29%) were supported by empirical findings. The determinants represented 12 categories (leaving 3% unspecified): focus on preferred findings (36%), poor or overly flexible research design (22%), high-risk area and its development (8%), dependence upon sponsors (8%), prejudice (7%), lack of resources including time (3%), doubts about reporting being worth the effort (3%), limitations in reporting and editorial practices (3%), academic publication system hurdles (3%), unfavorable geographical and regulatory environment (2%), relationship and collaboration issues (2%), and potential harm (0.4%).
CONCLUSIONS: We designed a taxonomy of putative determinants of selective reporting consisting of 12 categories. The taxonomy may help develop theory about causes of selection bias and guide policies to prevent selective reporting.