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Bayesian p-curve mixture models as a tool to dissociate effect size and effect prevalence
Much research in the behavioral sciences aims to characterize the “typical” person. A statistically significant group-averaged effect size is often interpreted as evidence that the typical person shows an effect, but that is only true under certain distributional assumptions for which explicit evidence is rarely presented. Mean effect size varies with both within-participant effect size and population prevalence (proportion of population showing effect). Few studies consider how prevalence affects mean effect size estimates and existing estimators of prevalence are, conversely, confounded by uncertainty about effect size. We introduce a widely applicable Bayesian method, the p-curve mixture model, that jointly estimates prevalence and effect size by probabilistically clustering participant-level data based on their likelihood under a null distribution. Our approach, for which we provide a software tool, outperforms existing prevalence estimation methods when effect size is uncertain and is sensitive to differences in prevalence or effect size across groups or conditions.
Trust in scientists and their role in society across 68 countries
Science is crucial for evidence-based decision-making. Public trust in scientists can help decision makers act on the basis of the best available evidence, especially during crises. However, in recent years the epistemic authority of science has been challenged, causing concerns about low public trust in scientists. We interrogated these concerns with a preregistered 68-country survey of 71,922 respondents and found that in most countries, most people trust scientists and agree that scientists should engage more in society and policymaking. We found variations between and within countries, which we explain with individual- and country-level variables, including political orientation. While there is no widespread lack of trust in scientists, we cannot discount the concern that lack of trust in scientists by even a small minority may affect considerations of scientific evidence in policymaking. These findings have implications for scientists and policymakers seeking to maintain and increase trust in scientists.
What makes a man unmanly? The global concept of ‘unmanliness’
This paper presents the findings of a multi-national study that led to the development of a new analytical framework in masculinity research—the Global Concept of ‘Unmanliness’ (GCU). Drawing on three key theories—hegemonic masculinity, precarious manhood and masculinity threat, and emasculation—we conducted an innovative study across 15 countries (selected from an initial pool of 62) to examine cultural perceptions of ‘unmanliness.’ Participants provided open-ended responses to identify traits and behaviors considered unmanly within their cultural contexts. By analyzing common themes expressed by young men, we propose the Global Concept of ‘Unmanliness’ as a framework for understanding how societies define and enforce masculinity norms. Furthermore, comparing these findings with the Global Gender Gap Index (GGGI) revealed a key distinction in how ‘unmanliness’ is characterized across different levels of gender emancipation. In countries with high GGGI rankings (e.g., Norway, Ireland, Germany), ‘unmanliness’ is more often associated with physical traits and behaviors linked to femininity (e.g., clothing, makeup). Conversely, in countries with low GGGI rankings (e.g., Pakistan, Morocco, Nigeria), it is more commonly defined by acts such as violence against women. Our study highlights how cultural and structural gender dynamics shape the boundaries of masculinity and offers a new lens for cross-cultural research on gender norms.
Bank lending and environmental quality in Gulf Cooperation Council countries
To achieve economies with net-zero carbon emissions, it is essential to develop a robust green financial intermediary channel. This study seeks empirical evidence on how domestic bank lending to sovereign and private sectors in Gulf Cooperation Council (GCC) countries impacts carbon dioxide and greenhouse gas emissions. We employ PMG-ARDL model to panel data comprising six countries in GCC over twenty years for carbon dioxide emissions and nineteen years for greenhouse gas emissions. Our findings reveal a long-term positive impact of both bank lending variables on carbon dioxide and greenhouse gas emissions. In addition, lending to the government shows a negative short-term effect on greenhouse gas emissions. The cross-country results demonstrate the presence of a long-run effect of explanatory variables on both types of emissions, except for greenhouse gas in Saudi Arabia. The sort-term impact of the explanatory variables on carbon dioxide and greenhouse gas emissions is quite diverse. Not only do these effects differ across countries, but some variables have opposing effects on the two types of emissions within a single country. The findings of this study present a new perspective for GCC economies: neglecting total greenhouse gas emissions and concentrating solely on carbon dioxide emissions means missing critical information for devising effective strategies to combat threats of environmental degradation and achieve net-zero goals.
Group arts interventions for depression and anxiety among older adults: a systematic review and meta-analysis
In this systematic review and meta-analysis, we assessed the efficacy of group arts interventions, where individuals engage together in a shared artistic experience (for example, dance or painting), for reducing depression and anxiety among older adults (> 55 yr without dementia). Fifty controlled studies were identified via electronic databases searched to February 2024 (randomised: 42, non-randomised: 8). Thirty-nine studies were included. Thirty-six studies investigated the impact of group arts interventions on depression (n = 3,360) and ten studies investigated anxiety (n = 949). Subgroup analyses assessed whether participant, contextual, intervention and study characteristics moderated the intervention–outcome relationship. Risk of bias was assessed with appropriate tools (RoB-2, ROBINS-1). Group arts interventions were associated with a moderate reduction in depression (Cohen’s d = 0.70, 95% confidence interval (CI) = 0.54–0.87, P < 0.001) and a moderate reduction in anxiety (d = 0.76, 95% CI = 0.37–1.52, P < 0.001), although there was publication bias in the depression studies. After a trim and fill adjustment, the effect for depression remained (d = 0.42; CI = 0.35–0.50; P < 0.001). Context moderated this effect: There was a greater reduction in depression when group arts interventions were delivered in care homes (d = 1.07, 95% CI = 0.72–1.42, P < 0.001) relative to the community (d = 0.51, 95% CI = 0.32–0.70, P < 0.001). Findings indicate that group arts are an effective intervention for addressing depression and anxiety among older adults.
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