State work engagement and state affect: Similar yet distinct concepts

State work engagement (SWE), a multidimensional construct of work-related well-being, was originally conceptualized as a trait, but diary studies have revealed substantial within-person fluctuations. Given that SWE is conceptualized as a work-related affective-motivational construct, the question arises as to whether SWE can be differentiated from other affective constructs. Thus, the goal of the present study was to compare SWE and state affect with respect to their degree of within-person variability and to examine their distinct relationships with health and performance variables (i.e., sleep quality and job performance). Fifty-two employees (44% female) participated in the study, which included 3 assessments per day over the course of 2 weeks. Our results revealed that energetic arousal and tense arousal fluctuated more strongly within days than vigor and absorption. Multilevel analyses demonstrated that high sleep quality predicted higher state affect but not higher SWE. In addition, vigor exhibited an inverted U-shaped relation with performance. In sum, SWE as a time-varying construct showed some overlap with state affect but also demonstrated discriminant validity.     

Do people reason rationally about causally related events? Markov violations,weak inferences,and failures of explaining away

Making judgments by relying on beliefs about the causal relationships between events is a fundamental capacity of everyday cognition. In the last decade, Causal Bayesian Networks have been proposed as a framework for modeling causal reasoning. Two experiments were conducted to provide comprehensive data sets with which to evaluate a variety of different types of judgments in comparison to the standard Bayesian networks calculations. Participants were introduced to a fictional system of three events and observed a set of learning trials that instantiated the multivariate distribution relating the three variables. We tested inferences on chains X₁ → Y → X₂, common cause structures X₁ ← Y → X₂, and common effect structures X₁ → Y ← X₂, on binary and numerical variables, and with high and intermediate causal strengths. We tested transitive inferences, inferences when one variable is irrelevant because it is blocked by an intervening variable (Markov Assumption), inferences from two variables to a middle variable, and inferences about the presence of one cause when the alternative cause was known to have occurred (the normative “explaining away” pattern). Compared to the normative account, in general, when the judgments should change, they change in the normative direction. However, we also discuss a few persistent violations of the standard normative model. In addition, we evaluate the relative success of 12 theoretical explanations for these deviations.     

“You’re on ten,where can you go from there?” Tufnel problems in repeated experiential judgments

We describe a set of Tufnel problems that arise when repeated use of a fixed-point scale precipitates failures to assess a full range of subjective experiences. As empirical evidence, participants in Study 1 periodically reported their depth of mind wandering on either 5- or 7-point Likert scales during a sustained attention task. The proportion of participants providing maximum scale ratings increased quickly over time-on-task and did so more quickly for the 5-point than for the 7-point group. Participants in Study 2 completed the same task using a 10-point scale before indicating whether and where they could have used a scale extended to “11” during the task. Slightly more than 20% of participants reported needing a scale extension. This Need for 11 was associated with differences in both reports of mind wandering depth and task performance. We conclude that Tufnel problems warrant methodological consideration and reflect interesting constraints on human judgment.     

Leaping to Conclusions: Why Premise Relevance Affects Argument Strength

Everyday reasoning requires more evidence than raw data alone can provide. We explore the idea that people can go beyond this data by reasoning about how the data was sampled. This idea is investigated through an examination of premise non‐monotonicity, in which adding premises to a category‐based argument weakens rather than strengthens it. Relevance theories explain this phenomenon in terms of people's sensitivity to the relationships among premise items. We show that a Bayesian model of category‐based induction taking premise sampling assumptions and category similarity into account complements such theories and yields two important predictions: First, that sensitivity to premise relationships can be violated by inducing a weak sampling assumption; and second, that premise monotonicity should be restored as a result. We test these predictions with an experiment that manipulates people's assumptions in this regard, showing that people draw qualitatively different conclusions in each case.     

From crisis of evidence to a “crisis” of relevance? Incentive-based answers for social psychology’s perennial relevance worries

Current controversies in social psychology have sparked the promotion of new rules for evidence in the field. This “crisis of evidence” echoes prior concerns from the 1970s about a so-called “crisis of social psychology”, with such issues as replication and statistical significance once more under examination. I argue that parallel concerns about the relevance of our research, raised but not completely resolved in the 1970s crisis, also deserve a fresh look. In particular, the advances made in the current crisis of evidence came about because of changes in academic career incentives, particularly publishing. Today, many voices in psychology urge greater respect for relevance in topics, methods and communication, but the lack of clear and concrete incentives to do so has stood in the way of answers. I diagnose the current incentive structures, propose partial solutions that are within the reach of journal editors and professional societies, and conclude by discussing the links between relevance and evidence, as well as special challenges to the relevance of social psychology post-2016.     

神经质对青少年情绪化饮食的影响：一个有调节的中介效应模型

摘 要 为探讨神经质、青少年情绪化饮食、体验回避及自尊之间的关系,选取1000名青少年为被试,采用简式大五人格问卷、荷兰饮食行为问卷、接纳行动量表及自尊量表进行测试。结果表明：（1）神经质对青少年情绪化饮食有显著的正向影响,并间接地通过体验回避对青少年情绪化饮食产生作用;（2）自尊在体验回避对青少年情绪化饮食的影响中起显著的调节作用,具体而言,在低自尊水平下,体验回避能显著地正向预测青少年情绪化饮食,而在高自尊水平下,体验回避对青少年情绪化饮食的预测作用不显著。     

The Experience in Personal Social Systems Questionnaire (EXIS.pers): Development and Psychometric Properties

This study presents the theoretical background, development, and psychometric properties of the German and English versions of the Experience in Personal Social Systems Questionnaire (EXIS.pers). It assesses how the members of a personal social system experience their situation within that system. It is designed as a research tool for interventions in which only one member of the system participates (e.g., Family Constellation Seminars). The EXIS.pers was created to measure change on the individual level relating to one's own important personal social system. In Study 1, we used exploratory factor analysis (EFA) for latent variable identification of the original German EXIS.pers (n = 179). In Studies 2 and 3, we used confirmatory factor analysis (CFA) to examine the dimensionality of the German (n = 634) and English (n = 310) EXIS.pers. Internal consistencies and cross‐cultural structural equivalence were assessed. EFA indicated that a four‐factor model provided best fit for the German EXIS.pers. For both the German and English EXIS.pers, CFA provided the best fit for a five‐factor bi‐level model that included a general factor (Experience In Personal Social Systems) and four dimensions (Belonging, Autonomy, Accord, Confidence). Good internal consistencies, external associations, and cross‐cultural structural equivalence were demonstrated. This study provides first evidence for the German and English EXIS.pers as an economical and reliable measure of an individual's experience within his or her personal social systems.