COVID-19 and Religious Ethics

The editors of the JRE solicited short essays on the COVID-19 pandemic from a group of scholars of religious ethics that reflected on how the field might help them make sense of the complex religious, cultural, ethical, and political implications of the pandemic, and on how the pandemic might shape the future of religious ethics.     

Predictors of Client Attrition in a University-Based Community Counseling Clinic

The purpose of this study was to investigate how symptom distress, social role, interpersonal relationships, gender, age, number of supports, and education level predict client attrition in a community sample. Using binary logistic regression and cross-sectional data, the authors examined the predictive impact of 8 variables on adult client attrition in a university-based community counseling clinic. Results indicated that education level, interpersonal relationships, and number of supports significantly predicted attrition. In this sample, gender, age, symptom distress, social role, and race did not significantly predict attrition. Implications for clinical assessment and counseling practice are discussed.     

Applying prospect theory to pilot weather-related decision-making: The impact of monetary and time considerations on risk taking behaviour

One of the key findings of prospect theory is that people tend to treat potential gains differently to potential losses. Consistent with earlier findings across a range of areas, pilots were risk averse when faced with an uncertain situation involving monetary gains and risk seeking when faced with a monetary loss. Prospect theory has largely been used to explore monetary decision-making; however, “time” is potentially a more important consideration for pilots than money. For example, how much time can be flown with the current fuel onboard. It was found that pilots' decision behaviour changed when faced with a decision involving time, with pilots risk averse for both a time gain and a time loss situation. Pilots appeared to prefer to know precisely the time required for a journey, rather than take a gamble on a potential short cut. Evidence also suggests pilots were more likely to take risks in situations that they perceive they have more control over (e.g. air traffic delays) compared to dynamic weather-related events. There was some evidence to suggest pilots do not consider a decision in terms of an end state, but rather in terms of losses and gains from their current state. The final part of the study found evidence that it may be possible to predict pilot risk taking behaviour using self-report decision frames.     

How representations of number and numeracy predict decision paradoxes: A fuzzy-trace theory approach

Higher numeracy has been associated with decision biases in some numerical judgment-and-decision problems. According to fuzzy-trace theory, understanding such paradoxes involves broadening the concept of numeracy to include processing the gist of numbers—their categorical and ordinal relations—in addition to objective (verbatim) knowledge about numbers. We assess multiple representations of gist, as well as numeracy, and use them to better understand and predict systematic paradoxes in judgment and decision-making. In two samples (Ns = 978 and 957), we assessed categorical (some vs. none) and ordinal gist representations of numbers (higher vs. lower, as in relative magnitude judgment, estimation, approximation, and simple ratio comparison), objective numeracy, and a nonverbal, nonnumeric measure of fluid intelligence in predicting: (a) decision preferences exhibiting the Allais paradox and (b) attractiveness ratings of bets with and without a small loss in which the loss bet is rated higher than the objectively superior no-loss bet. Categorical and ordinal gist tasks predicted unique variance in paradoxical decisions and judgments, beyond objective numeracy and intelligence. Whereas objective numeracy predicted choosing or rating according to literal numerical superiority, appreciating the categorical and ordinal gist of numbers was pivotal in predicting paradoxes. These results bring important paradoxes under the same explanatory umbrella, which assumes three types of representations of numbers—categorical gist, ordinal gist, and objective (verbatim)—that vary in their strength across individuals.     

Searching for Prosociality in Qualitative Data: Comparing Manual,Closed-Vocabulary,and Open-Vocabulary Methods

Although most people present themselves as possessing prosocial traits, people differ in the extent to which they actually act prosocially in everyday life. Qualitative data that were not ostensibly collected to measure prosociality might contain information about prosocial dispositions that is not distorted by self-presentation concerns. This paper seeks to characterise charitable donors from qualitative data. We compared a manual approach of extracting predictors from participants' self-described personal strivings to two automated approaches: A summation of words predefined as prosocial and a support vector machine classifier. Although variables extracted by the support vector machine predicted donation behaviour well in the training sample (N = 984), virtually, no variables from any method significantly predicted donations in a holdout sample (N = 496). Raters' attempts to predict donations to charity based on reading participants' personal strivings were also unsuccessful. However, raters' predictions were associated with past charitable involvement. In sum, predictors derived from personal strivings did not robustly explain variation in charitable behaviour, but personal strivings may nevertheless contain some information about trait prosociality. The sparseness of personal strivings data, rather than the irrelevance of open-ended text or individual differences in goal pursuit, likely explains their limited value in predicting prosocial behaviour. © 2020 European Association of Personality Psychology     

To Challenge the Morning Lark and the Night Owl: Using Smartphone Sensing Data to Investigate Day–Night Behaviour Patterns

For decades, day–night patterns in behaviour have been investigated by asking people about their sleep–wake timing, their diurnal activity patterns, and their sleep duration. We demonstrate that the increasing digitalization of lifestyle offers new possibilities for research to investigate day–night patterns and related traits with the help of behavioural data. Using smartphone sensing, we collected in vivo data from 597 participants across several weeks and extracted behavioural day–night pattern indicators. Using this data, we explored three popular research topics. First, we focused on individual differences in day–night patterns by investigating whether ‘morning larks’ and ‘night owls’ manifest in smartphone-sensed behavioural indicators. Second, we examined whether personality traits are related to day–night patterns. Finally, exploring social jetlag, we investigated whether traits and work weekly day–night behaviours influence day–night patterns on weekends. Our findings highlight that behavioural data play an essential role in understanding daily routines and their relations to personality traits. We discuss how psychological research can integrate new behavioural approaches to study personality.     

高校教师教学水平评价概化理论预算限制下最佳样本量估计

使用“高校教师教学水平评价问卷”,要求566名学生对19名教师进行评价,对收集到的数据作不同的概化设计,包括t×i、（s：t）×i、（s：t）×（i：v）和（s：t）×（i：v）×o四种设计。基于概化理论,结合预算限制,统一LaGrange乘法公式,自行推导不同设计的最佳样本量公式,联合估计的方差分量,计算出不同设计的最佳样本量。结果表明：（1）LaGrange乘法统一公式表现出较强的通用性,能够适用于预算限制下各种概化设计;（2）评价场合是影响高校教师教学水平评价一个相当重要的因素;（3）（s：t）×（i：v）×o是高校教师教学水平评价概化理论预算限制下最优概化设计;（4）高校教师教学水平评价概化理论预算限制下,每位教师最佳评价学生人数为20人,每个维度最佳评价题目数为3题。     

‘Personality in Its Natural Habitat’ Revisited: A Pooled,Multi-sample Examination of the Relationships Between the Big Five Personality Traits and Daily Behaviour and Language Use

Past research using the Electronically Activated Recorder (EAR), an observational ambulatory assessment method for the real-world measurement of daily behaviour, has identified several behavioural manifestations of the Big Five domains in a small college sample (N = 96). With the use of a larger and more diverse sample of pooled data from N = 462 participants from a total of four community samples who wore the EAR from 2 to 6 days, the primary purpose of the present study was to obtain more precise and generalizable effect estimates of the Big Five–behaviour relationships and to re-examine the degree to which these relationships are gender specific. In an extension of the original article, the secondary purpose of the present study was to examine if the Big Five–behaviour relationships differed across two facets of each Big Five domain. Overall, while several of the behavioural manifestations of the Big Five were generally consistent with the trait definitions (replicating some findings from the original article), we found little evidence of gender differences (not replicating a basic finding from the original article). Unique to the present study, the Big Five–behaviour relationships were not always comparable across the two facets of each Big Five domain. © 2020 European Association of Personality Psychology     

Applying theory to the black box: A model for empirically scoring biodata

Despite being an effective predictor of job performance, empirically keyed biodata assessments have been criticized as black box empiricism unlikely to generalize to new contexts. This paper introduces a model that challenges this perspective, explicating how biodata content, job demands, and criterion variables collectively influence the construct validity, and generalizability of empirically scored biodata. Across two field studies, expected changes in scale correlations with external measures were found that coincided with changes in the contextual similarity between calibration and holdout contexts, the criteria used, and the content validity of biodata items. Collectively, this paper offers a framework that helps understand and optimize empirical biodata keying in practice, furthering confidence for their use in applied settings.     

Adding versus averaging: Evaluability theory applied to job choice decisions

While the unique roles of individual job attributes (e.g., salary and benefits) in job and organizational attraction have received extensive research attention, research examining the mechanisms through which an overall evaluation of a job option is made by combining evaluations of individual attributes is scarce. The current study examined the process through which job choice decisions are made under three conditions: when evaluating a single job offer, when comparing two job offers, and when evaluating more than two job offers. In Study 1, it was found that when a single job offer is evaluated, the average of perceived values of attributes in an offer (e.g., the perceived attractiveness of a salary) drives the choice, whereas the difference between jobs is what matters when two jobs are evaluated simultaneously, potentially leading to a preference reversal between conditions when the same two jobs are evaluated. In Study 2, it was found that average values of attributes across options (e.g., average salary in all job offers received) influence job choice when more than two job offers are evaluated simultaneously. These findings indicate that in all three conditions, job choice decisions are influenced by the evaluability of the choice set, which becomes low when a single job offer is evaluated without any context, or when more than two job offers are evaluated simultaneously, and becomes high when two jobs are compared with each other. When evaluability is low, candidates resort to averaging as the decision rule, whereas adding is used when evaluability is high.