The Relationship of Previous Training and Experience of Journal Peer Reviewers to Subsequent Review Quality

Background Peer review is considered crucial to the selection and publication of quality science, but very little is known about the previous experiences and training that might identify high-quality peer reviewers. The reviewer selection processes of most journals, and thus the qualifications of their reviewers, are ill defined. More objective selection of peer reviewers might improve the journal peer review process and thus the quality of published science. Methods and Findings 306 experienced reviewers (71% of all those associated with a specialty journal) completed a survey of past training and experiences postulated to improve peer review skills. Reviewers performed 2,856 reviews of 1,484 separate manuscripts during a four-year study period, all prospectively rated on a standardized quality scale by editors. Multivariable analysis revealed that most variables, including academic rank, formal training in critical appraisal or statistics, or status as principal investigator of a grant, failed to predict performance of higher-quality reviews. The only significant predictors of quality were working in a university-operated hospital versus other teaching environment and relative youth (under ten years of experience after finishing training). Being on an editorial board and doing formal grant (study section) review were each predictors for only one of our two comparisons. However, the predictive power of all variables was weak. Conclusions Our study confirms that there are no easily identifiable types of formal training or experience that predict reviewer performance. Skill in scientific peer review may be as ill defined and hard to impart as is “common sense.” Without a better understanding of those skills, it seems unlikely journals and editors will be successful in systematically improving their selection of reviewers. This inability to predict performance makes it imperative that all but the smallest journals implement routine review ratings systems to routinely monitor the quality of their reviews (and thus the quality of the science they publish).