Does partisan media make a pawn of mistrust? Institutional trust and preventive COVID-19 health behaviors in a polarized pandemic

In a rapidly developing crisis such as the COVID-19 pandemic, people are often faced with contradictory or changing information and must determine what sources to trust. Across five time points (N = 5902) we examine how trust in various sources predicts COVID-19 health behaviors. Trust in experts and national news predicted more engagement with most health behaviors from April 2020 to March 2022 and trust in Fox news, which often positioned itself as counter to the mainstream on COVID-19, predicted less engagement. However, we also examined a particular public health behavior (masking) before and after the CDC announcement recommending masks on 3 April 2020 (which reversed earlier expert advice discouraging masks for the general public). Prior to the announcement, trust in experts predicted less mask-wearing while trust in Fox News predicted more. These relationships disappeared in the next 4 days following the announcement and reversed in the 2 years that follow, and emerged for vaccination in the later time points. We also examine how the media trusted by Democrats and Republicans predicts trust in experts and in turn health behaviors. Broadly we consider how the increasingly fragmented epistemic environment has implications for polarization on matters of public health.     

Subtask analysis of process data through a predictive model

Response process data collected from human–computer interactive items contain detailed information about respondents' behavioural patterns and cognitive processes. Such data are valuable sources for analysing respondents' problem-solving strategies. However, the irregular data format and the complex structure make standard statistical tools difficult to apply. This article develops a computationally efficient method for exploratory analysis of such process data. The new approach segments a lengthy individual process into a sequence of short subprocesses to achieve complexity reduction, easy clustering and meaningful interpretation. Each subprocess is considered a subtask. The segmentation is based on sequential action predictability using a parsimonious predictive model combined with the Shannon entropy. Simulation studies are conducted to assess the performance of the new method. We use a case study of PIAAC 2012 to demonstrate how exploratory analysis for process data can be carried out with the new approach.     

Blunted reward responsiveness prospectively predicts emotional distress when exposed to a naturalistic stressor

Both stress and blunted reward responsiveness have been identified as core risk factors of depression. Whether blunted reward responsiveness increases psychological vulnerability to real-life stress from a dynamic perspective (from stress reactivity to recovery) has not been investigated. By utilizing a real-world stressful event (i.e. the final examination), this study aimed to explore the role of reward responsiveness in the stress-emotional distress relationship during stress reactivity and recovery phases. We followed 57 undergraduates with three assessments, from six weeks before examination weeks (T1, baseline), one day before the examinations (T2) to two weeks after the examinations (T3), therefore, covering stress reactivity (T1 to T2) and recovery (T2 to T3) phases. At baseline, reward responsiveness was measured as the Reward Positivity (RewP) in the doors task. Stress and emotional distress (anxiety and depression) were reported at T1, T2 and T3 to capture their dynamic changes. Results showed that self-report stress levels significantly increased from T1 to T2 (stress reactivity phase) and decreased from T2 to T3 (stress recovery phase). Furthermore, blunted reward responsiveness at baseline prospectively predicted emotional distress during the stress reactivity phase but not the recovery phase. Specifically, during the stress reactivity phase, higher perceived stress was associated with greater anxiety and depression only in participants with relatively smaller residual RewP amplitudes but not in participants with relatively larger residual RewP amplitudes. Our study demonstrated that a blunted reward responsiveness is a vulnerable factor of depression, especially when exposed to stress. Our findings provide insights into prevention and intervention for stress-related disturbance.     

开放的正义域、否定性标准与个人自由——哈耶克的正义观析论

哈耶克主张规则正义,反对结果正义,反对假“社会正义”之名行“分配正义”之实,进而导向平均分配的泥沼。正义的作用仅在于它为个人行动提供了否定性价值标准。正义只能告诉人们不能做什么,而不能指示人们必须做什么,特别是它不能成为人类认识未知领域的行动准则,这就在逻辑上为个人自由行动提供了一个开放的正义域。他反对把正义作为行为的价值观念,因为对个体行为的正义性施以道德判断会束缚人的自由。     

Standardization and decomposition of rates: Useful analytic techniques for behavior and health studies

Standardization and decomposition are widely used analytic techniques in population studies for adjusting the impact of compositional factors on rates. This study demonstrates the application of these methods to behavior and health studies. Bootstrapping is used to estimate standard errors of the component effects and to conduct significance tests for them. The authors have developed a Windows-based computer program that is demonstrated in the study for standardization and decomposition analysis by using empirical data on HIV seropositivity rates in two injection-drug-using populations in the northeastern United States.     

西方心育教学模式评介

本文探讨了心育与心育教学模式的意义 ;着重介绍了西方几种有代表性的心育教学模式 ,即布鲁纳的发现教学法、威廉姆斯的创造与情意教学模式、开放教室的教学模式与勒温的敏感性训练等 ;并与传统教学模式相比较 ,分析了西方心育教学模式的主要特征     

启发式在警觉任务中的交叉复合作用

通过对个体和团队和警觉任务的阶段性研究,本研究发现了启发式对个体警觉任务的交叉复合作用,个体在警觉任务关键信号出现时绩效不一定下降。关键信号出现时成绩的升降取决于关键信号与背景信号的可取性。另外,团队结构克服了个体决策中出现的信息不全和信息加工资源不足的缺陷,使警觉任务在关键事件发生时、发生前和发生后的成绩波动不大。