A Bayesian bird's eye view of 'Replications of important results in social psychology'

Intra- and inter-brain synchrony oscillations underlying social adjustment

Humans naturally synchronize their behavior with other people. However, although it happens almost automatically, adjusting behavior and conformity to others is a complex phenomenon whose neural mechanisms are still yet to be understood entirely. The present experiment aimed to study the oscillatory synchronization mechanisms underlying automatic dyadic convergence in an EEG hyperscanning experiment. Thirty-six people performed a cooperative decision-making task where dyads had to guess the correct position of a point on a line. A reinforcement learning algorithm was used to model different aspects of the participants' behavior and their expectations of their peers. Intra- and inter-connectivity among electrode sites were assessed using inter-site phase clustering in three main frequency bands (theta, alpha, beta) using a two-level Bayesian mixed-effects modeling approach. The results showed two oscillatory synchronization dynamics related to attention and executive functions in alpha and reinforcement learning in theta. In addition, inter-brain synchrony was mainly driven by beta oscillations. This study contributes preliminary evidence on the phase-coherence mechanism underlying inter-personal behavioral adjustment.

Effects of preoperative carbohydrate loading on recovery after elective surgery: A systematic review and Bayesian network meta-analysis of randomized controlled trials

Background

Preoperative carbohydrate loading is an important element of the enhanced recovery after surgery (ERAS) paradigm in adult patients undergoing elective surgery. However, preoperative carbohydrate loading remains controversial in terms of improvement in postoperative outcomes and safety. We conducted a Bayesian network meta-analysis to evaluate the effects and safety of different doses of preoperative carbohydrates administrated in adult patients after elective surgery.

Methods

MEDLINE (PubMed), Web of Science, EMBASE, EBSCO, the Cochrane Central Register of Controlled Trials, and China National Knowledge Infrastructure (CNKI) were searched to identify eligible trials until 16 September 2022. Outcomes included postoperative insulin resistance, residual gastric volume (RGV) during the surgery, insulin sensitivity, fasting plasma glucose (FPG), fasting serum insulin (Fin) level, the serum levels of C-reactive protein (CRP), postoperative scores of pain, patients' satisfaction, thirst, hunger, anxiety, nausea and vomit, fatigue, and weakness within the first 24 h after surgery and the occurrences of postoperative infection. The effect sizes were estimated using posterior mean difference (continuous variables) or odds ratios (dichotomous variables) and 95 credible intervals (CrIs) with the change from baseline in a Bayesian network meta-analysis with random effect.

Results

Fifty-eight articles (N = 4936 patients) fulfilled the eligibility criteria and were included in the meta-analysis. Both preoperative oral low-dose carbohydrate loading (MD: -3.25, 95% CrI: -5.27 to -1.24) and oral high-dose carbohydrate loading (MD: -2.57, 95% CrI: -4.33 to -0.78) were associated with postoperative insulin resistance compared to placebo/water. When trials at high risk of bias were excluded, association with insulin resistance was found for oral low-dose carbohydrate loading compared with placebo/water (MD: -1.29, 95%CrI: -2.26 to -0.27) and overnight fasting (MD: -1.17, 95%CrI: -1.88 to -0.43). So, there was large uncertainty for all estimates vs. control groups. In terms of safety, oral low-dose carbohydrate administration was associated with the occurrences of postoperative infection compared with fasting by 0.42 (95%Crl: 0.20-0.81). In the other outcomes, there was no significant difference between the carbohydrate and control groups.

Conclusion

Although preoperative carbohydrate loading was associated with postoperative insulin resistance and the occurrences of postoperative infection, there is no evidence that preoperative carbohydrate administration alleviates patients' discomfort.

Systematic review registration

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022312944].

Recommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size

In this preregistered study, we investigated whether the statistical power of a study is higher when researchers are asked to make a formal power analysis before collecting data. We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences, which both include a recommendation to do a formal power analysis, and (ii) a sample of pre-registrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes. The determined sample size of the PCRs and IRB proposals (Md = 90.50) was not higher than the determined sample size of the SPRs (Md = 126.00; W = 3389.5, p = 0.936). Typically, power analyses in the registrations were conducted with G*power, assuming a medium effect size, α = .05 and a power of .80. Only 20% of the power analyses contained enough information to fully reproduce the results and only 62% of these power analyses pertained to the main hypothesis test in the pre-registration. Therefore, we see ample room for improvements in the quality of the registrations and we offer several recommendations to do so.

Replication Bayes factors from evidence updating

We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (Journal of Experimental Psychology: General, 143(4), 1457-1475 2014) for the common t test. This reconceptualization is computationally simpler and generalizes easily to most common experimental designs for which Bayes factors are available.

Do Readers Integrate Phonological Codes Across Saccades? A Bayesian Meta-Analysis and a Survey of the Unpublished Literature

It is commonly accepted that phonological codes can be activated parafoveally during reading and later used to aid foveal word recognition- a finding known as the phonological preview benefit. However, a closer look at the literature shows that this effect may be less consistent than what is sometimes believed. To determine the extent to which phonology is processed parafoveally, a Bayesian meta-analysis of 27 experiments and a survey of the unpublished literature were conducted. While the results were generally consistent with the phonological preview benefit (>90% probability of a true effect in gaze durations), the size of the effect was small. Readers of alphabetical orthographies obtained a modest benefit of only 4 ms in gaze durations. Interestingly, Chinese readers showed a larger effect (6-14 ms in size). There was no difference in the magnitude of the phonological preview benefit between homophone and pseudo-homophone previews, thus suggesting that the modest processing advantage is indeed related to the activation of phonological codes from the parafoveal word. Simulations revealed that the results are relatively robust to missing studies, although the effects may be 19-22% smaller if all missing studies found a null effect. The results suggest that while phonology can be processed parafoveally, this happens only to a limited extent. Because phonological priming effects in single-word recognition are small (10-13 ms; Rastle & Brysbaert, 2006) and there is a loss of visual acuity in the parafovea, it is argued that large phonological preview benefit effects may be unlikely.

Cognitive Bias Modification for Behavior Change in Alcohol and Smoking Addiction: Bayesian Meta-Analysis of Individual Participant Data

Cognitive Bias Modification (CBM) refers to a family of interventions targeting substance-related cognitive biases, which have been found to play a role in the maintenance of addictive behaviors. In this study, we conducted a Bayesian meta-analysis of individual patient data from studies investigating the effects of CBM as a behavior change intervention for the treatment of alcohol and tobacco use disorders, in individuals aware of the behavior change goal of the studies. Main outcomes included reduction in the targeted cognitive biases after the intervention and in substance use or relapse rate at the short-to-long term follow-up. Additional moderators, both at the study-level (type of addiction and CBM training) and at the participant-level (amount of completed training trials, severity of substance use), were progressively included in a series of hierarchical mixed-effects models. We included 14 studies involving 2435 participants. CBM appeared to have a small effect on cognitive bias (0.23, 95% credible interval = 0.06–0.41) and relapse rate (−0.27, 95% credible interval = −0.68 – 0.22), but not on reduction of substance use. Increased training practice showed a paradoxical moderation effect on relapse, with a relatively lower chance of relapse in the control condition with increased practice, compared to the training condition. All effects were associated with extremely wide 95% credible intervals, which indicate the absence of enough evidence in favor or against a reliable effect of CBM on cognitive bias and relapse rate in alcohol and tobacco use disorders. Besides the need for a larger body of evidence, research on the topic would benefit from a stronger adherence to the current methodological standards in randomized controlled trial design and the systematic investigation of shared protocols of CBM.

"Eavesdropping on Happiness" Revisited: A Pooled, Multisample Replication of the Association Between Life Satisfaction and Observed Daily Conversation Quantity and Quality

In the present study, we aimed to replicate and extend findings by Mehl, Vazire, Holleran, and Clark (2010) that individuals with higher well-being tend to spend less time alone and more time interacting with others (e.g., greater conversation quantity) and engage in less small talk and more substantive conversations (e.g., greater conversation quality). To test the robustness of these effects in a larger and more diverse sample, we used Bayesian integrative data analysis to pool data on subjective life satisfaction and observed daily conversations from three heterogeneous adult samples, in addition to the original sample ( N = 486). We found moderate associations between life satisfaction and amount of alone time, conversation time, and substantive conversations, but no reliable association with small talk. Personality did not substantially moderate these associations. The failure to replicate the original small-talk effect is theoretically and practically important, as it has garnered considerable scientific and lay interest.

Auditory Distraction During Reading: A Bayesian Meta-Analysis of a Continuing Controversy

Everyday reading occurs in different settings, such as on the train to work, in a busy cafeteria, or at home while listening to music. In these situations, readers are exposed to external auditory stimulation from nearby noise, speech, or music that may distract them from their task and reduce their comprehension. Although many studies have investigated auditory-distraction effects during reading, the results have proved to be inconsistent and sometimes even contradictory. In addition, the broader theoretical implications of the findings have not always been explicitly considered. We report a Bayesian meta-analysis of 65 studies on auditory-distraction effects during reading and use metaregression models to test predictions derived from existing theories. The results showed that background noise, speech, and music all have a small but reliably detrimental effect on reading performance. The degree of disruption in reading comprehension did not generally differ between adults and children. Intelligible speech and lyrical music resulted in the biggest distraction. Although this last result is consistent with theories of semantic distraction, there was also reliable distraction by noise. It is argued that new theoretical models are needed that can account for distraction by both background speech and noise.

Power Analysis and Effect Size in Mixed Effects Models: A Tutorial

In psychology, attempts to replicate published findings are less successful than expected. For properly powered studies replication rate should be around 80%, whereas in practice less than 40% of the studies selected from different areas of psychology can be replicated. Researchers in cognitive psychology are hindered in estimating the power of their studies, because the designs they use present a sample of stimulus materials to a sample of participants, a situation not covered by most power formulas. To remedy the situation, we review the literature related to the topic and introduce recent software packages, which we apply to the data of two masked priming studies with high power. We checked how we could estimate the power of each study and how much they could be reduced to remain powerful enough. On the basis of this analysis, we recommend that a properly powered reaction time experiment with repeated measures has at least 1,600 word observations per condition (e.g., 40 participants, 40 stimuli). This is considerably more than current practice. We also show that researchers must include the number of observations in meta-analyses because the effect sizes currently reported depend on the number of stimuli presented to the participants. Our analyses can easily be applied to new datasets gathered.