Revisiting the effect of incentivization on cognitive reflection: A meta-analysis

The effect of performance-based incentives on judgment biases is a controversial issue. A recent extensive meta-analysis of Brañas-Garza et al. (2019, https://doi.org/10.1016/j.socec.2019.101455 ) found no effect of incentives on performance in the cognitive reflection test (CRT), a test commonly used for assessing heuristic versus deliberative judgments. We conducted a meta-analysis of studies that directly compared an incentive versus no-incentive conditions (n = 2836) and found a small positive effect of incentivization (Cohen's d = .21) on CRT performance. In addition, we re-examined the Brañas-Garza et al. (2019) dataset (n = 39,385), taking into consideration not only whether incentivization was used but also the nominal and fiscal size of the incentive. The results show that surprisingly when including only studies that used monetary incentives, the effect of incentivization and incentive size are significant, even when taking into consideration other aspects of the studies. The results thus suggest a small but robust effect of incentives on judgment biases.     

跨期选择单维占优模型的过程检验

跨期选择需要决策者在眼前与未来的损益之间做出权衡与取舍。主流跨期选择理论认为, 跨期选择是把未来价值折扣到现在, 根据折扣后的价值进行选择的过程; 而单维占优模型则认为决策者把“结果”维度上的差异和“延迟”维度上的差异进行比较(维度间差异比较), 然后根据差异更大的维度(即占优势的维度)进行决策。跨期选择众理论之争无果的原因之一或是研究者未能找到揭示其心理过程的令人信服的证据。为此, 本研究采用过程检验而非结果拟合的方法, 首创了“直观模拟天平”任务, 对维度间差异比较的大小进行测量, 从而为验证单维占优模型提供了支持性的证据。实验1A证明了维度间差异大小中介了选择结果, 被试认为“结果”维度上的差异相对于“延迟”维度上的差异越大, 越倾向于选择延迟长、结果大的选项; 反之, 被试认为“延迟”维度上的差异相对于“结果”维度上的差异越大, 越倾向于选择延迟短、结果小的选项。实验1B证明了维度间差异比较是在选择时实时(而不是在选择后)进行的。实验1C通过调整实验程序消减了共同方法偏差对结果的影响。实验2进一步证明维度间差异比较可以解释众多的跨期选择异象。通过4个实验, 本研究揭示了维度间差异比较构成了跨期选择的重要(尽管可能不是唯一)决策过程, 为支持单维占优模型提供了重要的过程验证证据。     

应激对风险和社会决策的影响

应激是有机体在受到真实或者潜在的威胁刺激时所表现出来的全身性非特异性反应, 伴随着紧张和焦虑的心理体验, 交感神经系统的兴奋, 糖皮质激素分泌的增多以及脑干−边缘系统−前额叶神经环路的改变。应激对个体在风险决策行为中的风险寻求和风险回避倾向, 社会决策行为中的利己和利他倾向都会产生重要影响。策略使用异常、习惯化和自动化反应增强、反馈学习过程以及奖惩敏感性的改变是应激影响决策行为的认知基础; 应激激素的分泌, 及杏仁核、前额叶等在决策过程发挥重要作用的脑区活动的改变则为应激作用于决策行为的神经基础。未来研究应重点关注：应激的个体差异与应激对决策影响效应多样性的关系; 综合多种指标对应激进行测量; 考察应激的时序效应; 揭示个体的最佳应激水平; 加强对慢性应激影响决策以及应激对决策影响效应可逆性的研究; 揭示应激影响决策的神经机制。     

辛苦所得与意外所得的非理性消费偏差：基于IAT检测和ERP证据

不同来源的财富因其在人们心理的权重差异会导致对其消费态度与方式的不同。前人运用一系列行为实验已发现意外所得更容易消费、辛苦所得则不容易消费。基于心理账户和内隐社会认知等理论, 运用IAT和ERP考察财富的意外所得与辛苦所得在人们心理引起的内在消费偏差, 进而对内隐消费态度和脑加工机制进行间接检测。IAT研究结果表明, 意外所得与容易消费的联结更加紧密, 辛苦所得与不易消费的联结更加紧密, 从内隐层面验证了前人的行为研究结论; ERP研究结果发现辛苦所得与意外所得这两个不同收入来源可能建立了不同脑加工机制, 且在P3和LPC成分得到反映, P3成分可能是反映辛苦所得组偏好难消费型消费方式的ERP成分, LPC反映了意外所得收入条件下个体偏好易消费型消费方式的特点。     

Psychometric Investigation of the Santa Clara Strength of Religious Faith Questionnaire—Short-Form

This study investigated the psychometric properties of the Santa Clara Strength of Religious Faith Questionnaire—Short Form (SCSRFQ-SF). Participants were 226 undergraduate students (168 female) at a large public university enrolled in randomly selected undergraduate courses. A principal components analysis of the SCSRFQ-SF supported the hypothesized one-factor structure. In addition, the internal consistency was high and the convergent validity of the SCSRFQ-SF was supported with significantly positive relations with the Duke Religion Index. These findings provide initial support for the reliability and construct validity of the SCSRFQ-SF.     

A client‐generated psychometric instrument: The development of ‘PSYCHLOPS’

PSYCHLOPS (Psychological Outcome Profiles) is a recently developed, client‐generated, psychometric instrument that can be used as an outcome measure. Based on a similar instrument developed primarily for use in physical illnesses (MYMOP — ‘Measure Your Medical Outcome Profile’), it seeks the client's perspective on their psychological distress. It asks them to describe and then score the problem that troubles them the most at the start of counselling. We describe the development of PSYCHLOPS, including the involvement of the Plain English Campaign and two national mental health organisations: the mental health charity and support group, Depression Alliance (DA) and Primary Care Mental Health Education (PRIMHE). We review the literature and suggest that PSYCHLOPS, by focusing on the problems of greatest priority to the client, might prove a sensitive measure of improvement after counselling.     

Rank‐based permutation approaches for non‐parametric factorial designs

Inference methods for null hypotheses formulated in terms of distribution functions in general non‐parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set‐up Wald‐type statistics and ANOVA‐type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal–Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability.     

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares

Data in psychology are often collected using Likert‐type scales, and it has been shown that factor analysis of Likert‐type data is better performed on the polychoric correlation matrix than on the product‐moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real‐data example indicates that estimates by ridge GLS are 9–20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich‐type standard errors following the ridge GLS methods also perform reasonably well.     

Evaluation of Multi-parameter Test Statistics for Multiple Imputation

In Ordinary Least Square regression, researchers often are interested in knowing whether a set of parameters is different from zero. With complete data, this could be achieved using the gain in prediction test, hierarchical multiple regression, or an omnibus F test. However, in substantive research scenarios, missing data often exist. In the context of multiple imputation, one of the current state-of-art missing data strategies, there are several different analogous multi-parameter tests of the joint significance of a set of parameters, and these multi-parameter test statistics can be referenced to various distributions to make statistical inferences. However, little is known about the performance of these tests, and virtually no research study has compared the Type 1 error rates and statistical power of these tests in scenarios that are typical of behavioral science data (e.g., small to moderate samples, etc.). This paper uses Monte Carlo simulation techniques to examine the performance of these multi-parameter test statistics for multiple imputation under a variety of realistic conditions. We provide a number of practical recommendations for substantive researchers based on the simulation results, and illustrate the calculation of these test statistics with an empirical example.