A Method to Explore the Best Mixed-Effects Model in a Data-Driven Manner with Multiprocessing: Applications in Public Health Research.

In the present study, I developed and tested an R module to explore the best models within the context of multilevel modeling in research in public health. The module that I developed, explore.models, compares all possible candidate models generated from a set of candidate predictors with information criteria, Akaike information criterion (AIC), and Bayesian information criterion (BIC), with multiprocessing. For testing, I ran explore.models with datasets analyzed in three previous studies in public health, which assumed candidate models with different degrees of model complexity. These three studies examined the predictors of psychological well-being, compliance with preventive measures, and vaccine intent during the COVID-19 pandemic. After conducting model exploration with explore.models, I cross-validated the nomination results with calculated model Bayes Factors to examine whether the model exploration was performed accurately. The results suggest that explore.models using AIC and BIC can nominate best candidate models and such nomination outcomes are supported by the calculated model Bayes Factors. In particular, all the identified models are superior to the full models in terms of model Bayes Factors. Also, by employing AIC and BIC with multiprocessing, explore.models requires a shorter processing time than model Bayes Factor calculations. These results indicate that explore.models is a reliable, valid, and feasible tool to conduct data-driven model exploration with datasets collected from multiple groups in research on health psychology and education.

Using measurement alignment in research on adolescence involving multiple groups: A brief tutorial with R.

Measurement alignment adjusts factor loadings and intercepts across different groups to achieve measurement invariance, which assumes the equal measurement model is validated across different groups. It should be achieved for validly conducting analysis and comparison in studies involving multiple groups, such as cross-cultural or cross-national studies. In this paper, I presented how to conduct measurement alignment with R. In addition to measurement alignment, I explained how to perform the Monte Carlo simulation to test the consistency and validity of alignment results and factor score calculation to facilitate further statistical analysis. A tutorial R code that implements all described procedures is freely shared via GitHub to inform readers who intend to use the alignment technique in their research projects.

Cross-language validation of COVID-19 Compliance Scale in 28 languages.

Although compliance scales have been used to assess compliance with health guidelines to reduce the spread of COVID-19, no scale known to us has shown content validity regarding global guidelines and reliability across an international sample. We assessed the validity and reliability of a Compliance Scale developed by a group of over 150 international researchers. Exploratory factor analysis determined reliable items on the English version. Confirmatory factor analysis confirmed the reliability of the six-item scale and convergent validity was found. After invariance testing and alignment, we employed a novel R code to run a Monte Carlo simulation for alignment validation. This scale can be employed to measure compliance across multiple languages, and our alignment validation method can be conducted with future cross-language surveys.

The effects of secondary stressors, social identity, and social support on perceived stress and resilience: Findings from the COVID-19 pandemic.

Primary stressors are direct outcomes of extreme events (e.g., viruses, floodwater) whereas secondary stressors stem from pre-disaster life circumstances and societal arrangements (e.g., illness, problematic pre-disaster policies) or from inefficient responses to the extreme event. Secondary stressors can cause significant long-term damage to people affected but are also tractable and amenable to change. In this study we explored the association between secondary stressors, social identity processes, social support, and perceived stress and resilience. Pre-registered analyses of data from the COVIDiSTRESS Global Survey Round II (N = 14,600; 43 countries) show that secondary stressors are positively associated with perceived stress and negatively associated with resilience, even when controlling for the effects of primary stressors. Being a woman or having lower socioeconomic status (SES) is associated with higher exposure to secondary stressors, higher perceived stress, and lower resilience. Importantly, social identification is positively associated with expected support and with increased resilience and lower perceived stress. However, neither gender, SES, or social identification moderated the relationship between secondary stressors and perceived stress and resilience. In conclusion, systemic reforms and the availability of social support are paramount to reducing the effects of secondary stressors.

Mediation analysis of conspiratorial thinking and anti-expert sentiments on vaccine willingness.

OBJECTIVE: Vaccines are an effective means to reduce the spread of diseases, but they are sometimes met with hesitancy that needs to be understood. METHOD: In this study, we analyzed data from a large, cross-country survey conducted between June and August 2021 in 43 countries (N = 15,740) to investigate the roles of trust in government and science in shaping vaccine attitudes and willingness to be vaccinated. RESULTS: Despite significant variability between countries, we found that both forms of institutional trust were associated with a higher willingness to receive a COVID-19 vaccine. Furthermore, we found that conspiratorial thinking and anti-expert sentiments predicted reduced trust in government and science, respectively, and that trust mediated the relationship between these two constructs and ultimate vaccine attitudes. Although most countries displayed similar relationships between conspiratorial thinking and anti-expert sentiments, trust in government and science, and vaccine attitudes, we identified three countries (Brazil, Honduras, and Russia) that demonstrated significantly altered associations between the examined variables in terms of significant random slopes. CONCLUSIONS: Cross-country differences suggest that local governments' support for COVID-19 prevention policies can influence populations' vaccine attitudes. These findings provide insight for policymakers to develop interventions aiming to increase trust in the institutions involved in the vaccination process. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Moral reasoning and moral competence as predictors of cooperative behavior in a social dilemma.

The level of moral development may be crucial to understand behavior when people have to choose between prioritizing individual gains or pursuing general social benefits. This study evaluated whether two different psychological constructs, moral reasoning and moral competence, are associated with cooperative behavior in the context of the prisoner's dilemma game, a two-person social dilemma where individuals choose between cooperation or defection. One hundred and eighty-nine Mexican university students completed the Defining Issues Test (DIT-2; measuring moral reasoning) and the Moral Competence Test (MCT) and played an online version of the prisoner's dilemma game, once against each participant in a group of 6-10 players. Our results indicate that cooperative behavior is strongly affected by the outcomes in previous rounds: Except when both participants cooperated, the probability of cooperation with other participants in subsequent rounds decreased. Both the DIT-2 and MCT independently moderated this effect of previous experiences, particularly in the case of sucker-outcomes. Individuals with high scores on both tests were not affected when in previous rounds the other player defected while they cooperated. Our findings suggest that more sophisticated moral reasoning and moral competence promote the maintenance of cooperative behaviors despite facing adverse situations.

How are moral foundations associated with empathic traits and moral identity?

We examined the relationship between moral foundations, empathic traits, and moral identity using an online survey via Mechanical Turk. In order to determine how moral foundations contribute to empathic traits and moral identity, we performed classical correlation analysis as well as Bayesian correlation analysis, Bayesian ANCOVA, and Bayesian regression analysis. Results showed that individualizing foundations (harm/care, fairness/reciprocity) and binding foundations (ingroup/loyalty, authority/respect, purity/sanctity) had various different relationships with empathic traits. In addition, the individualizing versus binding foundations showed somewhat reverse relationships with internalization and symbolization of moral identity. This suggests that moral foundations can contribute to further understanding of empathic traits and moral identity and how they relate to moral behavior in reality. We discuss the implications of these results for moral educators when starting to teach students about moral issues. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-021-02372-5.

Which moral exemplars inspire prosociality?

Some stories of moral exemplars motivate us to emulate their admirable attitudes and behaviors, but why do some exemplars motivate us more than others? We systematically studied how motivation to emulate is influenced by the similarity between a reader and an exemplar in social or cultural background (Relatability) and how personally costly or demanding the exemplar's actions are (Attainability). Study 1 found that university students reported more inspiration and related feelings after reading true stories about the good deeds of a recent fellow alum, compared to a famous moral exemplar from decades past. Study 2A developed a battery of short moral exemplar stories that more systematically varied Relatability and Attainability, along with a set of non-moral exemplar stories for comparison. Studies 2B and 2C examined the path from the story type to relatively low stakes altruism (donating to charity and intentions to volunteer) through perceived attainability and relatability, as well as elevation and pleasantness. Together, our studies suggest that it is primarily the relatability of the moral exemplars, not the attainability of their actions, that inspires more prosocial motivation, at least regarding acts that help others at a relatively low cost to oneself.

Validity testing of the conspiratorial thinking and anti-expert sentiment scales during the COVID-19 pandemic across 24 languages from a large-scale global dataset.

In this study, we tested the validity across two scales addressing conspiratorial thinking that may influence behaviours related to public health and the COVID-19 pandemic. Using the COVIDiSTRESSII Global Survey data from 12 261 participants, we validated the 4-item Conspiratorial Thinking Scale and 3-item Anti-Expert Sentiment Scale across 24 languages and dialects that were used by at least 100 participants per language. We employed confirmatory factor analysis, measurement invariance test and measurement alignment for internal consistency testing. To test convergent validity of the two scales, we assessed correlations with trust in seven agents related to government, science and public health. Although scalar invariance was not achieved when measurement invariance test was conducted initially, we found that both scales can be employed in further international studies with measurement alignment. Moreover, both conspiratorial thinking and anti-expert sentiments were significantly and negatively correlated with trust in all agents. Findings from this study provide supporting evidence for the validity of both scales across 24 languages for future large-scale international research.

Cerebellum and Emotion in Morality.

In this chapter, I examined the relationship between the cerebellum, emotion, and morality with evidence from large-scale neuroimaging data analysis. Although the aforementioned relationship has not been well studied in neuroscience, recent studies have shown that the cerebellum is closely associated with emotional and social processes at the neural level. Also, debates in the field of moral philosophy, psychology, and neuroscience have supported the importance of emotion in moral functioning. Thus, I explored the potentially important but less-studied topic with NeuroSynth, a tool for large-scale brain image analysis, while addressing issues associated with reverse inference. The result from analysis demonstrated that brain regions in the cerebellum, the right Crus I and Crus II in particular, were specifically associated with morality in general. I discussed the potential implications of the finding based on clinical and functional neuroimaging studies of the cerebellum, emotional functioning, and neural networks for diverse psychological processes.

Testing the validity of the modified vaccine attitude question battery across 22 languages with a large-scale international survey dataset: within the context of COVID-19 vaccination.

In this study, we tested the validity of the modified version of the Vaccine Attitude Question Battery (VAQB) across 22 different languages. Validity test was conducted with a large-scale international survey dataset, COVIDiSTRESSII Global Survey, collected from 20,601 participants from 62 countries. We employed exploratory and confirmatory factor analysis, measurement invariance test, and measurement alignment for internal validity test. Moreover, we examined correlation between the VAQB score, vaccination intent, compliance with preventive measures, and trust in public health-related agents. The results reported that the modified VAQB, which included five items, showed good validity across 22 languages with measurement alignment. Furthermore, the VAQB score showed negative association with vaccination intent, compliance, and trust as expected. The findings from this study provide additional evidence supporting the validity of the modified VAQB in 22 languages for future large-scale international research on COVID-19 and vaccination.

Trust in the scientific research community predicts intent to comply with COVID-19 prevention measures: An analysis of a large-scale international survey dataset.

In the present study, I explored the relationship between people's trust in different agents related to the prevention of the spread of coronavirus disease 2019 (COVID-19) and their compliance with pharmaceutical and non-pharmaceutical preventive measures. The COVIDiSTRESSII Global Survey dataset, which was collected from international samples, was analysed to examine the aforementioned relationship across different countries. For data-driven exploration, network analysis and Bayesian generalised linear model (GLM) analysis were performed. The result from network analysis demonstrated that trust in the scientific research community was most central in the network of trust and compliance. In addition, the outcome from Bayesian GLM analysis indicated that the same factor, trust in the scientific research community, was most fundamental in predicting participants' intent to comply with both pharmaceutical and non-pharmaceutical preventive measures. I briefly discussed the implications of the findings, the importance of trust in the scientific research community in explaining people's compliance with a measure to prevent the spread of COVID-19.

Representative Sampling of the Via Assessment Suite for Adults.

Character strengths have become a popular topic in personality research. A set of questionnaires has recently been developed as measures of character strengths: the VIA Inventory of Strengths-Revised, two 96-item short forms of that instrument, and two new measures called the Global Assessment of Character Strengths and Signature Strengths Survey. Collectively, these are referred to as the VIA Assessment Suite for Adults. Prior research has supported the reliability and validity of these measures. The current study extended those findings through a demographically stratified sample of 1,765 U.S. resident adults. Results indicated the scores were interchangeable across all three versions of the VIA-IS, irrespective of whether the items are all positively keyed or a mix of positive and negative items. In addition, the VIA-IS-R factor structure is also consistent with a previously identified three-factor model for the strengths. By freeing residual covariances, a model was developed for which adequate fit was replicable. This provided the foundation for demonstrating measurement invariance. The present study also explored differences in strengths across demographic categories and evaluated various approaches to identifying key (signature) strengths for the respondents. Recommendations on the use of the different instruments are provided.

Applying elastic-net regression to identify the best models predicting changes in civic purpose during the emerging adulthood.

INTRODUCTION: Changes in civic purpose during the emerging adulthood has been a significant research topic since it is closely associated with active civic engagement later in human lives. While standard regression methods have been used in previous studies to predict civic purpose development, they have limitations that may not always lead to best prediction models. We aimed to address these limitations by utilizing elastic-net multinomial logistic regression, which favors models with the least number of necessary predictors, in exploration of predictors for civic purpose development in a data-driven manner. METHODS: We analyzed data from the longitudinal Civic Purpose Project while focusing on the model that best predicted civic purpose from Wave 1 (12th grade before high school graduation) to Wave 2 (two years after Wave 1). The reanalyzed data included responses from 476 participants (60.29% females, 39.08% males) who were recruited from Californian high schools in the United States and completed the survey at both Waves. The elastic-net regression was performed 5000 times for predicting three dependent variables, Wave 2 political purpose, community service purpose, and expressive activity purpose, with Wave 1 predictors. We identified which predictors were selected as the constituents of the best regression models during the elastic-net regression process. RESULTS: Results showed that civic purpose, moral and political identity, and external supports (e.g., parental and peer involvement, school civic opportunities, etc.) in Wave 1 significantly predicted civic purpose in Wave 2. Several predictors were excluded from the regression models during the elastic-net regression process. CONCLUSION: We found that the elastic-net regression was able to present the more regularized model for prediction. Implications for promoting civic purpose are discussed as well as utilizing the elastic-net regression method.

Replicating the Disease framing problem during the 2020 COVID-19 pandemic: A study of stress, worry, trust, and choice under risk.

In the risky-choice framing effect, different wording of the same options leads to predictably different choices. In a large-scale survey conducted from March to May 2020 and including 88,181 participants from 47 countries, we investigated how stress, concerns, and trust moderated the effect in the Disease problem, a prominent framing problem highly evocative of the COVID-19 pandemic. As predicted by the appraisal-tendency framework, risk aversion and the framing effect in our study were larger than under typical circumstances. Furthermore, perceived stress and concerns over coronavirus were positively associated with the framing effect. Contrary to predictions, however, they were not related to risk aversion. Trust in the government's efforts to handle the coronavirus was associated with neither risk aversion nor the framing effect. The proportion of risky choices and the framing effect varied substantially across nations. Additional exploratory analyses showed that the framing effect was unrelated to reported compliance with safety measures, suggesting, along with similar findings during the pandemic and beyond, that the effectiveness of framing manipulations in public messages might be limited. Theoretical and practical implications of these findings are discussed, along with directions for further investigations.

Do Histories of Painful Life Experiences Affect the Expression of Empathy Among Young Adults? An Electroencephalography Study.

Previous research suggests that prior experience of pain affects the expression of empathy. However, most of these studies attended to physical pain despite evidence indicating that other forms of pain may also affect brain activity and emotional states in similar ways. To address this limitation, we compared empathic responses of 33 participants, some of whom had experienced a personal loss, across three conditions: observing strangers in physical pain, psychological pain, and a non-painful condition. We also examined the effect of presence of prior painful experience on empathic reactions. In addition, we examined the stimulation type, prior experience, and ERPs in the early Late Positive Potential (300-550 ms), late Late Positive Potential (550-800 ms), and very late Late Positive Potential (VLLPP; 800-1,050 ms) time windows. Behavioral data indicated that participants who had personally experienced a loss scored significantly higher on perspective taking in the psychological-pain condition. ERP results also indicated significantly lower intensity in Fp2, an electrode in the prefrontal region, within VLLPP time window for participants experiencing a loss in the psychological-pain condition. The results of both behavioral and ERP analysis indicated that prior experience of psychological pain is related to cognitive empathy, but not affective empathy. The implication of these findings for research on empathy, for the study of psychological pain, and the moderating influence of prior painful experiences are discussed.

Stress and worry in the 2020 coronavirus pandemic: relationships to trust and compliance with preventive measures across 48 countries in the COVIDiSTRESS global survey.

The COVIDiSTRESS global survey collects data on early human responses to the 2020 COVID-19 pandemic from 173 429 respondents in 48 countries. The open science study was co-designed by an international consortium of researchers to investigate how psychological responses differ across countries and cultures, and how this has impacted behaviour, coping and trust in government efforts to slow the spread of the virus. Starting in March 2020, COVIDiSTRESS leveraged the convenience of unpaid online recruitment to generate public data. The objective of the present analysis is to understand relationships between psychological responses in the early months of global coronavirus restrictions and help understand how different government measures succeed or fail in changing public behaviour. There were variations between and within countries. Although Western Europeans registered as more concerned over COVID-19, more stressed, and having slightly more trust in the governments' efforts, there was no clear geographical pattern in compliance with behavioural measures. Detailed plots illustrating between-countries differences are provided. Using both traditional and Bayesian analyses, we found that individuals who worried about getting sick worked harder to protect themselves and others. However, concern about the coronavirus itself did not account for all of the variances in experienced stress during the early months of COVID-19 restrictions. More alarmingly, such stress was associated with less compliance. Further, those most concerned over the coronavirus trusted in government measures primarily where policies were strict. While concern over a disease is a source of mental distress, other factors including strictness of protective measures, social support and personal lockdown conditions must also be taken into consideration to fully appreciate the psychological impact of COVID-19 and to understand why some people fail to follow behavioural guidelines intended to protect themselves and others from infection. The Stage 1 manuscript associated with this submission received in-principle acceptance (IPA) on 18 May 2020. Following IPA, the accepted Stage 1 version of the manuscript was preregistered on the Open Science Framework at https://osf.io/g2t3b. This preregistration was performed prior to data analysis.

Exploring the association between compliance with measures to prevent the spread of COVID-19 and big five traits with Bayesian generalized linear model.

Research has examined the association between people's compliance with measures to prevent the spread of COVID-19 and personality traits. However, previous studies were conducted with relatively small-size datasets and employed frequentist analysis that does not allow data-driven model exploration. To address the limitations, a large-scale international dataset, COVIDiSTRESS Global Survey dataset, was explored with Bayesian generalized linear model that enables identification of the best regression model. The best regression models predicting participants' compliance with Big Five traits were explored. The findings demonstrated first, all Big Five traits, except extroversion, were positively associated with compliance with general measures and distancing. Second, neuroticism, extroversion, and agreeableness were positively associated with the perceived cost of complying with the measures while conscientiousness showed negative association. The findings and the implications of the present study were discussed.

A method to adjust a prior distribution in Bayesian second-level fMRI analysis.

Previous research has shown the potential value of Bayesian methods in fMRI (functional magnetic resonance imaging) analysis. For instance, the results from Bayes factor-applied second-level fMRI analysis showed a higher hit rate compared with frequentist second-level fMRI analysis, suggesting greater sensitivity. Although the method reported more positives as a result of the higher sensitivity, it was able to maintain a reasonable level of selectivity in term of the false positive rate. Moreover, employment of the multiple comparison correction method to update the default prior distribution significantly improved the performance of Bayesian second-level fMRI analysis. However, previous studies have utilized the default prior distribution and did not consider the nature of each individual study. Thus, in the present study, a method to adjust the Cauchy prior distribution based on a priori information, which can be acquired from the results of relevant previous studies, was proposed and tested. A Cauchy prior distribution was adjusted based on the contrast, noise strength, and proportion of true positives that were estimated from a meta-analysis of relevant previous studies. In the present study, both the simulated images and real contrast images from two previous studies were used to evaluate the performance of the proposed method. The results showed that the employment of the prior adjustment method resulted in improved performance of Bayesian second-level fMRI analysis.

COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak.

This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey - an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available.