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AbstractAs 20% of adolescents develop emotion regulation difficulties, it is important to identify important early predictors thereof. Using the machine learning algorithm SEM‐forests, we ranked the importance of (87) candidate variables assessed at age 13 in predicting quadratic latent trajectory models of emotion regulation development from age 14 to 18. Participants were 497 Dutch families. Results indicated that the most important predictors were individual differences (e.g., in personality), aspects of relationship quality and conflict behaviors with parents and peers, and internalizing and externalizing problems. Relatively less important were demographics, bullying, delinquency, substance use, and specific parenting practices—although negative parenting practices ranked higher than positive ones. We discuss implications for theory and interventions, and present an open source risk assessment tool, ERRATA.

AbstractParents' monitoring efforts are thought to be effective in reducing children's future externalizing problems. Empirical evidence for this claim, however, is limited, as only few studies have unraveled the temporal ordering of these constructs. The present six‐wave longitudinal study contributed to the existing literature by examining within‐family linkages between monitoring efforts (behavioral control and solicitation) and adolescents' externalizing behaviors while controlling for between‐family differences. In addition, it was assessed whether these associations differed when using child versus parent reports, differed for less versus more autonomy‐supportive parents, and differed for fathers' versus mothers' monitoring efforts. Longitudinal data (six annual waves) of 497 adolescents (56.9% boys, Mage at T1 = 13.03, SD = 0.46), their mothers (N = 495, Mage at T1 = 44.41, SD = 4.45), and their fathers (N = 446, Mage at T1 = 46.74, SD = 5.10) of the Dutch study Research on Adolescent Development and Relationships (RADAR) were used. Results showed no evidence for the claim that parents' monitoring efforts predict future externalizing problems. In contrast, we found some evidence for the idea that parents' monitoring efforts change in reaction to changes in externalizing problems; when adolescents reported higher levels of externalizing problems than usual in 1 year, this predicted less behavioral control from mothers in the next year. Linkages between monitoring efforts and externalizing problems did not differ between less or more autonomy‐supportive parents. Overall, our findings suggest that monitoring efforts are not effective, but also not damaging, in relation to adolescents' externalizing problems.

In spring 2020, the COVID-19 pandemic was declared. The threat the pandemic poses as well as associated lockdown measures created challenging times for many. This study aimed to investigate the individual and social factors associated with low mental health, particularly perceived threat and lockdown measures, and factors associated with psychological well-being, particularly sense of control. An online survey was completed by participants (N = 8,229) recruited from 79 countries. In line with pre-registered hypotheses, participants showed elevated levels of anxiety and depression worldwide. This poor mental health was predicted by perceived threat. The effect of threat on depression was further moderated by social isolation, but there was no effect of sense of control. Sense of control was low overall, and was predicted negatively by maladaptive coping, but positively by adaptive coping and the perception that the government is dealing with the outbreak. Social isolation increased with quarantine duration, but was mitigated by frequent communication with close ones. Engaging in individual actions to avoid contracting the virus was associated with higher anxiety, except when done professionally. We suggest that early lockdown of the pandemic may have had detrimental psychological effects, which may be alleviated by individual actions such as maintaining frequent social contact and adaptive coping, and by governmental actions which demonstrate support in a public health crisis. Citizens and governments can work together to adapt better to restrictive but necessary measures during the current and future pandemics.

This Teacher's Corner paper introduces Bayesian evaluation of informative hypotheses for structural equation models, using the free open-source R packages bain, for Bayesian informative hypothesis testing, and lavaan, a widely used SEM package. The introduction provides a brief non-technical explanation of informative hypotheses, the statistical underpinnings of Bayesian hypothesis evaluation, and the bain algorithm. Three tutorial examples demonstrate informative hypothesis evaluation in the context of common types of structural equation models: 1) confirmatory factor analysis, 2) latent variable regression, and 3) multiple group analysis. We discuss hypothesis formulation, the interpretation of Bayes factors and posterior model probabilities, and sensitivity analysis.

The present paper examines longitudinally how subjective perceptions about COVID-19, one's community, and the government predict adherence to public health measures to reduce the spread of the virus. Using an international survey (N = 3040), we test how infection risk perception, trust in the governmental response and communications about COVID-19, conspiracy beliefs, social norms on distancing, tightness of culture, and community punishment predict various containment-related attitudes and behavior. Autoregressive analyses indicate that, at the personal level, personal hygiene behavior was predicted by personal infection risk perception. At social level, social distancing behaviors such as abstaining from face-to-face contact were predicted by perceived social norms. Support for behavioral mandates was predicted by confidence in the government and cultural tightness, whereas support for anti-lockdown protests was predicted by (lower) perceived clarity of communication about the virus. Results are discussed in light of policy implications and creating effective interventions.

During the initial phase of the COVID-19 pandemic, U.S. conservative politicians and the media downplayed the risk of both contracting COVID-19 and the effectiveness of recommended health behaviors. Health behavior theories suggest perceived vulnerability to a health threat and perceived effectiveness of recommended health-protective behaviors determine motivation to follow recommendations. Accordingly, we predicted that-as a result of politicization of the pandemic-politically conservative Americans would be less likely to enact recommended health-protective behaviors. In two longitudinal studies of U.S. residents, political conservatism was inversely associated with perceived health risk and adoption of health-protective behaviors over time. The effects of political orientation on health-protective behaviors were mediated by perceived risk of infection, perceived severity of infection, and perceived effectiveness of the health-protective behaviors. In a global cross-national analysis, effects were stronger in the U.S. (N = 10,923) than in an international sample (total N = 51,986), highlighting the increased and overt politicization of health behaviors in the U.S.

Background. The effective implementation of government policies and measures for controlling the coronavirus disease 2019 (COVID-19) pandemic requires compliance from the public. This study aimed to examine cross-sectional and longitudinal associations of trust ingovernment regarding COVID-19 control with the adoption of recommended health behaviours and prosocial behaviours, and potential determinants of trust in government duringthe pandemic.Methods. This study analysed data from the PsyCorona Survey, an international project onCOVID-19 that included 23 733 participants from 23 countries (representative in age andgender distributions by country) at baseline survey and 7785 participants who also completedfollow-up surveys. Specification curve analysis was used to examine concurrent associationsbetween trust in government and self-reported behaviours. We further used structural equation model to explore potential determinants of trust in government. Multilevel linear regressions were used to examine associations between baseline trust and longitudinal behavioural changes.Results. Higher trust in government regarding COVID-19 control was significantly associatedwith higher adoption of health behaviours (handwashing, avoiding crowded space, self-quarantine) and prosocial behaviours in specification curve analyses (median standardised β =0.173 and 0.229, p < 0.001). Government perceived as well organised, disseminating clear messages and knowledge on COVID-19, and perceived fairness were positively associated withtrust in government (standardised β = 0.358, 0.230, 0.056, and 0.249, p < 0.01). Higher trustat baseline survey was significantly associated with lower rate of decline in health behavioursover time ( p for interaction = 0.001).Conclusions. These results highlighted the importance of trust in government in the control of Covid-19.

The present paper examines longitudinally how subjective perceptions about COVID-19, one's community, and the government predict adherence to public health measures to reduce the spread of the virus. Using an international survey (N = 3040), we test how infection risk perception, trust in the governmental response and communications about COVID-19, conspiracy beliefs, social norms on distancing, tightness of culture, and community punishment predict various containment-related attitudes and behavior. Autoregressive analyses indicate that, at the personal level, personal hygiene behavior was predicted by personal infection risk perception. At social level, social distancing behaviors such as abstaining from face-to-face contact were predicted by perceived social norms. Support for behavioral mandates was predicted by confidence in the government and cultural tightness, whereas support for anti-lockdown protests was predicted by (lower) perceived clarity of communication about the virus. Results are discussed in light of policy implications and creating effective interventions.