A toolbox to evaluate the trustworthiness of published findings

During the past few years, researchers have criticized their professions for providing an entry point for false-positive results arising from publication bias and questionable research practices such as p-hacking (i.e., selectively reporting analyses that yield a p-value below 5 %). Researchers are advocating replication studies and the implementation of open-science practices, like preregistration, in order to identify trustworthy effects. Nevertheless, because such consumer research developments are still emerging, most prior research findings have not been replicated, leaving researchers in the dark as to whether a line of research or a particular effect is trustworthy. We tackle this problem by providing a toolbox containing multiple heuristics to identify data patterns that might, from the information provided in published articles, indicate publication bias and p-hacking. Our toolbox is an easy-to-use instrument with which to initially assess a given set of findings.