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.     

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.     

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.     

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.     

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。     

“自爱”指标与维度的初探——《四库全书》中“自爱”的心理学研究

从《四库全书》中检索到1700部涉及“自爱”的古籍,形成包含2370条句段的语料库并逐条进行内容分析。结果发现,自爱包含自我珍重、自我接纳与自我约束三个主要指标以及个我自爱、小我自爱与大我自爱三个主要维度。未来研究将依据我国社会文化和历史的脉络,结合新时代人们对自爱的理解,编制相应的测量工具,从而为健全人格养成服务。     

中文版无手机恐惧量表的修订

该研究以国外学者Caglar Yildirim和Ana-Paula Correia于2015年编制的Nomophobia量表为基础,修订出了适用于国内的中文版无手机恐惧量表。研究首先使用探索性结构方程模型对量表结构进行初探; 其次使用项目反应模型进行项目分析并根据其分析结果对项目进行修改和筛选,最终形成正式版量表; 最后对正式版量表其进行信效度检验,并再次对量表题目进行项目分析。最终量表共16道题目,包括害怕无法获得信息、害怕失去便利、害怕失去联系和害怕失去网络连接4个维度; 总量表的Cronbach α系数为0.931,四维度的α系数分别为:0.789,0.816,0.887和0.896。CFA验证性结果显示量表结构较好(χ2/df=3.91,RMSEA=0.067,TLI=0.941,CFI=0.952,SRMR=0.04); 使用手机成瘾倾向量表作为校标的结果显示二者之间相关为0.626,效度良好。最终量表项目区分度在[1.734,4.806]之间,四维度区分度均值为2.1765,2.72,3.2925和3.883,项目难度参数在[-1.830,4.806]之间。综上结果显示该研究编制的无手机恐惧量表各项指标均达到了心理测量学要求,可供后续研究使用     

低阶层大学生的炫耀性消费:自尊补偿与地位追求

近年来低阶层大学生炫耀性消费负性事件频发,研究以补偿性消费理论为基础,考察低阶层大学生炫耀性消费的内因与外因。实验一通过比较高、低状态自尊条件下不同阶层被试的炫耀性消费倾向来考察自尊的作用,结果表明低阶层大学生的炫耀性消费倾向受到其状态自尊的调节; 实验二通过比较不同阶层被试对地位及非地位符号商品的支付意愿来考察商品符号价值的作用,结果表明低阶层大学生只有在商品具有地位符号价值时,才会表现出比高阶层大学生更强烈的炫耀性消费倾向。     

二胎环境下小学高年级“脱独”儿童父母教养方式与同胞关系:心理理论的中介作用

研究采用问卷集体施测,收集了788名小学高年级“脱独”儿童的父母教养方式、同胞关系以及心理理论的状况,探讨小学高年级“脱独”儿童父母教养方式对同胞关系的影响及心理理论作为中介变量的影响。结果表明:心理理论在父母教养方式中的父亲过分干涉、母亲情感温暖理解、母亲惩罚严厉、母亲过分干涉与同胞关系之间起完全中介作用; 心理理论在父亲情感温暖理解、父亲偏爱与同胞关系之间起部分中介作用。研究认为,良好的父母教养方式,有助于个体提高心理理论,并可能在一定程度上改善同胞关系。     

Moderating Loss Aversion: Loss Aversion Has Moderators,But Reports of its Death are Greatly Exaggerated

Loss aversion, the principle that losses impact decision making more than equivalent gains, is a fundamental idea in consumer behavior and decision making, though its existence has recently been called into question. Across five unique samples (N_total = 17,720), we tested several moderators of loss aversion, which supported a preference construction account. Across studies, more domain knowledge and experience were associated with lower loss aversion, though people of all knowledge and experience levels were loss averse. Among car buyers, those who knew more about a particular car attribute (e.g., fuel economy) were less loss averse for that attribute but not other attributes (e.g., comfort), consistent with the idea that people with less attribute knowledge are more likely to construct preferences, thereby increasing loss aversion. Additionally, older consumers were more loss averse across different loss aversion measures and studies. We discuss implications for several accounts of loss aversion, including accounts rooted in status quo bias, emotion, or ownership. In addition to discovering loss aversion moderators, we cast doubt on recent claims that loss aversion is a fallacy or is fully explained by status quo bias, risk aversion, or the educated laboratory samples often used to study loss aversion.