Alcohol-induced retrograde facilitation? Mixed evidence in a preregistered replication and encoding-maintenance-retrieval analysis

Somewhat counterintuitively, alcohol consumption following learning of new information has been shown to enhance performance on a delayed subsequent memory test. This phenomenon has become known as the retrograde facilitation effect (Parker et al., 1981). Although conceptually replicated repeatedly, serious methodological problems are associated with most previous demonstrations of retrograde facilitation. Moreover, two potential explanations have been proposed, the interference and the consolidation hypothesis. So far, empirical evidence for and against both hypotheses is inconclusive (Wixted, 2004). To scrutinize the existence of the effect, we conducted a pre-registered replication that avoided common methodological pitfalls. In addition, we used Küpper-Tetzel and Erdfelder’s (2012) multinomial processing tree (MPT) model to disentangle encoding, maintenance, and retrieval contributions to memory performance. With a total sample size of N = 93, we found no evidence for retrograde facilitation in overall cued or free recall of previously presented word pairs. In line with this, MPT analyses also showed no reliable difference in maintenance probabilities. However, MPT analyses revealed a robust alcohol advantage in retrieval. We conclude that alcohol-induced retrograde facilitation might exist and be driven by an underlying retrieval benefit. Future research is needed to investigate potential moderators and mediators of the effect explicitly

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

A Many-analysts Approach to the Relation Between Religiosity and Well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates