Are Psychology Journals Anti-replication? A Snapshot of Editorial Practices

Although replication is a central tenet of science, direct replications are rare in psychology. This research tested variation in the replicability of 13 classic and contemporary effects across 36 independent samples totaling 6,344 participants. In the aggregate, 10 effects replicated consistently. One effect – imagined contact reducing prejudice – showed weak support for replicability. And two effects – flag priming influencing conservatism and currency priming influencing system justification – did not replicate. We compared whether the conditions such as lab versus online or US versus international sample predicted effect magnitudes. By and large they did not. The results of this small sample of effects suggest that replicability is more dependent on the effect itself than on the sample and setting used to investigate the effect.

The hypothesis of a Hierarchy of the Sciences with physical sciences at the top, social sciences at the bottom, and biological sciences in-between is nearly 200 years old. This order is intuitive and reflected in many features of academic life, but whether it reflects the “hardness” of scientific research—i.e., the extent to which research questions and results are determined by data and theories as opposed to non-cognitive factors—is controversial. This study analysed 2434 papers published in all disciplines and that declared to have tested a hypothesis. It was determined how many papers reported a “positive” (full or partial) or “negative” support for the tested hypothesis. If the hierarchy hypothesis is correct, then researchers in “softer” sciences should have fewer constraints to their conscious and unconscious biases, and therefore report more positive outcomes. Results confirmed the predictions at all levels considered: discipline, domain and methodology broadly defined. Controlling for observed differences between pure and applied disciplines, and between papers testing one or several hypotheses, the odds of reporting a positive result were around 5 times higher among papers in the disciplines of Psychology and Psychiatry and Economics and Business compared to Space Science, 2.3 times higher in the domain of social sciences compared to the physical sciences, and 3.4 times higher in studies applying behavioural and social methodologies on people compared to physical and chemical studies on non-biological material. In all comparisons, biological studies had intermediate values. These results suggest that the nature of hypotheses tested and the logical and methodological rigour employed to test them vary systematically across disciplines and fields, depending on the complexity of the subject matter and possibly other factors (e.g., a field's level of historical and/or intellectual development). On the other hand, these results support the scientific status of the social sciences against claims that they are completely subjective, by showing that, when they adopt a scientific approach to discovery, they differ from the natural sciences only by a matter of degree.

We discuss three arguments voiced by scientists who view the current outpouring of concern about replicability as overblown. The first idea is that the adoption of a low alpha level (e.g., 5%) puts reasonable bounds on the rate at which errors can enter the published literature, making false-positive effects rare enough to be considered a minor issue. This, we point out, rests on statistical misunderstanding: The alpha level imposes no limit on the rate at which errors may arise in the literature (Ioannidis, 2005b). Second, some argue that whereas direct replication attempts are uncommon, conceptual replication attempts are common-providing an even better test of the validity of a phenomenon. We contend that performing conceptual rather than direct replication attempts interacts insidiously with publication bias, opening the door to literatures that appear to confirm the reality of phenomena that in fact do not exist. Finally, we discuss the argument that errors will eventually be pruned out of the literature if the field would just show a bit of patience. We contend that there are no plausible concrete scenarios to back up such forecasts and that what is needed is not patience, but rather systematic reforms in scientific practice.