Heterogeneity in direct replications in psychology and Its association with effect size

We examined the evidence for heterogeneity (of effect sizes) when only minor changes to sample population and settings were made between studies and explored the association between heterogeneity and average effect size in a sample of 68 meta-analyses from 13 preregistered multilab direct replication projects in social and cognitive psychology. Among the many examined effects, examples include the Stroop effect, the "verbal overshadowing" effect, and various priming effects such as "anchoring" effects. We found limited heterogeneity; 48/68 (71%) meta-analyses had nonsignificant heterogeneity, and most (49/68; 72%) were most likely to have zero to small heterogeneity. Power to detect small heterogeneity (as defined by Higgins, Thompson, Deeks, & Altman, 2003) was low for all projects (mean 43%), but good to excellent for medium and large heterogeneity. Our findings thus show little evidence of widespread heterogeneity in direct replication studies in social and cognitive psychology, suggesting that minor changes in sample population and settings are unlikely to affect research outcomes in these fields of psychology. We also found strong correlations between observed average effect sizes (standardized mean differences and log odds ratios) and heterogeneity in our sample. Our results suggest that heterogeneity and moderation of effects is unlikely for a 0 average true effect size, but increasingly likely for larger average true effect size

Associations between lifestyle factors and multidimensional frailty: a cross-sectional study among community-dwelling older people

Background: Multidimensional frailty, including physical, psychological, and social components, is associated to disability, lower quality of life, increased healthcare utilization, and mortality. In order to prevent or delay frailty, more knowledge of its determinants is necessary; one of these determinants is lifestyle. The aim of this study is to determine the association between lifestyle factors smoking, alcohol use, nutrition, physical activity, and multidimensional frailty. Methods: This cross-sectional study was conducted in two samples comprising in total 45,336 Dutch community-dwelling individuals aged 65 years or older. These samples completed a questionnaire including questions about smoking, alcohol use, physical activity, sociodemographic factors (both samples), and nutrition (one sample). Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Results: Higher alcohol consumption, physical activity, healthy nutrition, and less smoking were associated with less total, physical, psychological and social frailty after controlling for effects of other lifestyle factors and sociodemographic characteristics of the participants (age, gender, marital status, education, income). Effects of physical activity on total and physical frailty were up to considerable, whereas the effects of other lifestyle factors on frailty were small. Conclusions: The four lifestyle factors were not only associated with physical frailty but also with psychological and social frailty. The different associations of frailty domains with lifestyle factors emphasize the importance of assessing frailty broadly and thus to pay attention to the multidimensional nature of this concept. The findings offer healthcare professionals starting points for interventions with the purpose to prevent or delay the onset of frailty, so community-dwelling older people have the possibility to aging in place accompanied by a good quality of life

Associations of individual chronic diseases and multimorbidity with multidimensional frailty

Objective: To examine the associations between individual chronic diseases and multidimensional frailty comprising physical, psychological, and social frailty. Methods: Dutch individuals (N = 47,768) age ≥ 65 years completed a general health questionnaire sent by the Public Health Services (response rate of 58.5 %), including data concerning self-reported chronic diseases, multidimensional frailty, and sociodemographic characteristics. Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Total frailty and each frailty domain were regressed onto background characteristics and the six most prevalent chronic diseases: diabetes mellitus, cancer, hypertension, arthrosis, urinary incontinence, and severe back disorder. Multimorbidity was defined as the presence of combinations of these six diseases. Results: The six chronic diseases had medium and strong associations with total ((f2 = 0.122) and physical frailty (f2 = 0.170), respectively, and weak associations with psychological (f2 = 0.023) and social frailty (f2 = 0.008). The effects of the six diseases on the frailty variables differed strongly across diseases, with urinary incontinence and severe back disorder impairing frailty most. No synergetic effects were found; the effects of a disease on frailty did not get noteworthy stronger in the presence of another disease. Conclusions: Chronic diseases, in particular urinary incontinence and severe back disorder, were associated with frailty. We thus recommend assigning different weights to individual chronic diseases in a measure of multimorbidity that aims to examine effects of multimorbidity on multidimensional frailty. Because there were no synergetic effects of chronic diseases, the measure does not need to include interactions between diseases

Group autonomy enhancing treatment versus cognitive behavioral therapy for anxiety disorders: A cluster-randomized clinical trial

Background: Although cognitive behavioral therapy (CBT) is effective in the treatment of anxiety disorders, few evidence-based alternatives exist. Autonomy enhancing treatment (AET) aims to decrease the vulnerability for anxiety disorders by targeting underlying autonomy deficits and may therefore have similar effects on anxiety as CBT, but yield broader effects. Methods: A multicenter cluster-randomized clinical trial was conducted including 129 patients with DSM-5 anxiety disorders, on average 33.66 years of age (SD = 12.57), 91 (70.5%) female, and most (92.2%) born in the Netherlands. Participants were randomized over 15-week groupwise AET or groupwise CBT and completed questionnaires on anxiety, general psychopathology, depression, quality of life, autonomy-connectedness and self-esteem, pre-, mid-, and posttreatment, and after 3, 6, and 12 months (six measurements). Results: Contrary to the hypotheses, effects on the broader outcome measures did not differ between AET and CBT (d =.16 or smaller at post-test). Anxiety reduction was similar across conditions (d =.059 at post-test) and neither therapy was superior on long term. Conclusion: This was the first clinical randomized trial comparing AET to CBT. The added value of AET does not seem to lie in enhanced effectiveness on broader outcome measures or on long term compared to CBT. However, the study supports the effectiveness of AET and thereby contributes to extended treatment options for anxiety disorders

Same Data, Different Conclusions: Radical Dispersion in Empirical Results When Independent Analysts Operationalize and Test the Same Hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Selective Hypothesis Reporting in Psychology:Comparing Preregistrations and Corresponding Publications

In this study, we assessed the extent of selective hypothesis reporting in psychological research by comparing the hypotheses found in a set of 459 preregistrations with the hypotheses found in the corresponding articles. We found that more than half of the preregistered studies we assessed contained omitted hypotheses (N = 224; 52%) or added hypotheses (N = 227; 57%), and about one-fifth of studies contained hypotheses with a direction change (N = 79; 18%). We found only a small number of studies with hypotheses that were demoted from primary to secondary importance (N = 2; 1%) and no studies with hypotheses that were promoted from secondary to primary importance. In all, 60% of studies included at least one hypothesis in one or more of these categories, indicating a substantial bias in presenting and selecting hypotheses by researchers and/or reviewers/editors. Contrary to our expectations, we did not find sufficient evidence that added hypotheses and changed hypotheses were more likely to be statistically significant than nonselectively reported hypotheses. For the other types of selective hypothesis reporting, we likely did not have sufficient statistical power to test for a relationship with statistical significance. Finally, we found that replication studies were less likely to include selectively reported hypotheses than original studies. In all, selective hypothesis reporting is problematically common in psychological research. We urge researchers, reviewers, and editors to ensure that hypotheses outlined in preregistrations are clearly formulated and accurately presented in the corresponding articles.</p

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

The Meta-Plot: A Graphical Tool for Interpreting the Results of a Meta-Analysis

The meta-plot is a descriptive visual tool for meta-analysis that provides information on the primary studies in the meta-analysis and the results of the meta-analysis. More precisely, the meta-plot portrays (1) the precision and statistical power of the primary studies in themetaanalysis, (2) the estimate and confidence interval of a random-effects meta-analysis, (3) the results of a cumulative random-effects metaanalysis yielding a robustness check of the meta-analytic effect size with respect to primary studies' precision, and (4) evidence of publication bias. After explaining the underlying logic and theory, the meta-plot is applied to two cherry-picked meta-analyses that appear to be biased and to 10 randomly selected meta-analyses from the psychological literature. We recommend accompanying any meta-analysis of common effect size measures with the meta-plot

Selective Hypothesis Reporting in Psychology: Comparing Preregistrations and Corresponding Publications

In this study, we assessed the extent of selective hypothesis reporting in psychological research by comparing the hypotheses found in a set of 459 preregistrations with the hypotheses found in the corresponding articles. We found that more than half of the preregistered studies we assessed contained omitted hypotheses (N = 224; 52%) or added hypotheses (N = 227; 57%), and about one-fifth of studies contained hypotheses with a direction change (N = 79; 18%). We found only a small number of studies with hypotheses that were demoted from primary to secondary importance (N = 2; 1%) and no studies with hypotheses that were promoted from secondary to primary importance. In all, 60% of studies included at least one hypothesis in one or more of these categories, indicating a substantial bias in presenting and selecting hypotheses by researchers and/or reviewers/editors. Contrary to our expectations, we did not find sufficient evidence that added hypotheses and changed hypotheses were more likely to be statistically significant than nonselectively reported hypotheses. For the other types of selective hypothesis reporting, we likely did not have sufficient statistical power to test for a relationship with statistical significance. Finally, we found that replication studies were less likely to include selectively reported hypotheses than original studies. In all, selective hypothesis reporting is problematically common in psychological research. We urge researchers, reviewers, and editors to ensure that hypotheses outlined in preregistrations are clearly formulated and accurately presented in the corresponding articles