No abstract

Replication studies in psychological science sometimes fail to reproduce prior findings. If these studies use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data-collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replication studies from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) for which the original authors had expressed concerns about the replication designs before data collection; only one of these studies had yielded a statistically significant effect ( p < .05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate the original effects. We revised the replication protocols and received formal peer review prior to conducting new replication studies. We administered the RP:P and revised protocols in multiple laboratories (median number of laboratories per original study = 6.5, range = 3–9; median total sample = 1,279.5, range = 276–3,512) for high-powered tests of each original finding with both protocols. Overall, following the preregistered analysis plan, we found that the revised protocols produced effect sizes similar to those of the RP:P protocols (Δ r = .002 or .014, depending on analytic approach). The median effect size for the revised protocols ( r = .05) was similar to that of the RP:P protocols ( r = .04) and the original RP:P replications ( r = .11), and smaller than that of the original studies ( r = .37). Analysis of the cumulative evidence across the original studies and the corresponding three replication attempts provided very precise estimates of the 10 tested effects and indicated that their effect sizes (median r = .07, range = .00–.15) were 78% smaller, on average, than the original effect sizes (median r = .37, range = .19–.50).

Replication efforts in psychological science sometimes fail to replicate prior findings. If replications use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the replication protocol rather than a challenge to the original finding. Formal pre-data collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replications from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) in which the original authors had expressed concerns about the replication designs before data collection and only one of which was “statistically significant” (p &lt; .05). Commenters on RP:P suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these failed to replicate (Gilbert et al., 2016). We revised the replication protocols and received formal peer review prior to conducting new replications. We administered the RP:P and Revised replication protocols in multiple laboratories (Median number of laboratories per original study = XX; Range XX to YY; Median total sample = XX; Range XX to YY) for high-powered tests of each original finding with both protocols. Overall, XX of 10 RP:P protocols and XX of 10 Revised protocols showed significant evidence in the same direction as the original finding (p &lt; .05), compared to an expected XX. The median effect size was [larger/smaller/similar] for Revised protocols (ES = .XX) compared to RP:P protocols (ES = .XX), and [larger/smaller/similar] compared to the original studies (ES = .XX) and [larger/smaller/similar] compared to the original RP:P replications (ES = .XX). Overall, Revised protocols produced [much larger/somewhat larger/similar] effect sizes compared to RP:P protocols (ES = .XX). We also elicited peer beliefs about the replications through prediction markets and surveys of a group of researchers in psychology. The peer researchers predicted that the Revised protocols would [decrease/not affect/increase] the replication rate, [consistent with/not consistent with] the observed replication results. The results suggest that the lack of replicability of these findings observed in RP:P was [partly/completely/not] due to discrepancies in the RP:P protocols that could be resolved with expert peer review.

Risen and Gilovich (2008) found that subjects believed that “tempting fate” would be punished with ironic bad outcomes (a main effect), and that this effect was magnified when subjects were under cognitive load (an interaction). A previous replication study (Frank & Mathur, 2016) that used an online implementation of the protocol on Amazon Mechanical Turk failed to replicate both the main effect and the interaction. Before this replication was run, the authors of the original study expressed concern that the cognitive-load manipulation may be less effective when implemented online than when implemented in the lab and that subjects recruited online may also respond differently to the specific experimental scenario chosen for the replication. A later, large replication project, Many Labs 2 (Klein et al. 2018), replicated the main effect (though the effect size was smaller than in the original study), but the interaction was not assessed. Attempting to replicate the interaction while addressing the original authors’ concerns regarding the protocol for the first replication study, we developed a new protocol in collaboration with the original authors. We used four university sites ( N = 754) chosen for similarity to the site of the original study to conduct a high-powered, preregistered replication focused primarily on the interaction effect. Results from these sites did not support the interaction or the main effect and were comparable to results obtained at six additional universities that were less similar to the original site. Post hoc analyses did not provide strong evidence for statistical inconsistency between the original study’s estimates and our estimates; that is, the original study’s results would not have been extremely unlikely in the estimated distribution of population effects in our sites. We also collected data from a new Mechanical Turk sample under the first replication study’s protocol, and results were not meaningfully different from those obtained with the new protocol at universities similar to the original site. Secondary analyses failed to support proposed substantive mechanisms for the failure to replicate.

Members of many socially stigmatized and historically exploited groups are more likely to be ill, to be injured, and to die prematurely relative to members of socially privileged and historically advantaged groups. This is true in the United States and elsewhere. These disparities are often large, pervasive, and persistent, and constitute a public health crisis. Although pervasive, such large and pervasive disparities along lines of stigma are not obligatory. In the present chapter, we examine how stigma operates at the individual, interpersonal, and structural level to produce broad patterns of mental and physical health disparities. We then suggest some initial steps at the individual, interpersonal, and structural levels to reduce health disparities along the lines of stigma.