Who Reaps the Benefits of Social Change? Exploration and Its Socioecological Boundaries

We investigated the interplay between the personality trait exploration and objective socioecological conditions in shaping individual differences in the experience of two individual‐level benefits of current social change: new lifestyle options, which arise from the societal trend toward individualization, and new learning opportunities, which accrue from the societal trend toward lifelong learning. We hypothesized that people with higher trait exploration experience a greater increase in lifestyle options and learning opportunities––but more so in social ecologies in which individualization and lifelong learning are stronger, thus offering greater latitude for exploring the benefits of these trends. We employed structural equation modeling in two parallel adult samples from Germany (N = 2,448) and Poland (N = 2,571), using regional divorce rates as a proxy for individualization and Internet domain registration rates as a proxy for lifelong learning. Higher exploration was related to a greater perceived increase in lifestyle options and in learning opportunities over the past 5 years. These associations were stronger in regions in which the trends toward individualization and lifelong learning, respectively, were more prominent. Individuals higher in exploration are better equipped to reap the benefits of current social change––but the effects of exploration are bounded by the conditions in the social ecology.     

Comparative judgments with missing information: a regression and process tracing analysis

We had participants decide which one of two applicants was better qualified for a scholarship. They also judged the difference between them (comparative judgment). The applicants were described by features (grades) in different subjects (dimensions). The grades on some dimensions were missing (unique dimensions) for an alternative while all the grades were available on other dimensions (common dimensions). In a conventional regression analysis, we found that decision makers gave more weight to dimensions when they were common than when they were unique. However, this commensurability effect was limited to medium important dimensions and did not apply to dimensions of high or low importance. We also observed how participants retrieved information for the choice alternatives and analysed how importance and commensurability are reflected in the processing prior to the decision. Features on more important or common dimensions were inspected earlier than features on less important or unique dimensions. Participants preferred dimensional transitions and inspected features on unique dimensions longer than their common counterparts. This finding suggested that participants used inferences when features were missing. We propose an outline of a decision heuristic to describe decision making with missing information.     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.     

Coaching of Insolvent Entrepreneurs and the Change in Coping Resources,Health, and Cognitive Performance

As coaching becomes an established learning and development tool, it expands to new work contexts and relevant populations. Exploring coaching outcomes in insolvent entrepreneurs is a new and promising field. Business failure is a devastating experience for entrepreneurs, associated with negative emotions and adverse psychological and physiological reactions. Our study is the first to examine if coaching can help improve the coping resources, health, and cognitive performance of insolvent entrepreneurs. The results of our pre-post-test-within-subject analyses based on 19 participants show a positive improvement in psychological well-being, vital exhaustion, and vigilance. By contrast, no improvements were found with regard to coping resources and biomarkers such as stress hormones concentrations in hair. Unexpectedly, the working alliance between client and coach did not increase the improvements following coaching. Our findings contribute to the growing literature on the effects of coaching; however, our results should be interpreted cautiously as unfortunately we had no opportunity to include a control group in our research design.     

Examining Cross-Cultural Differences in Academic Faking in 41 Nations

This study examines cross-cultural differences in students’ academic faking (indicated by claiming to have impossible knowledge about mathematical concepts) by relating data from the Programme for International Student Assessment (PISA) to the comprehensive cultural framework of the Global Leadership and Organizational Behavior Effectiveness (GLOBE) project. Data of N = 233,428 students from 41 countries showed a substantial amount of variance in academic faking between cultures. Students’ academic faking was positively related to the cultural dimensions of gender egalitarianism, humane orientation, and in-group collectivism. Additionally, the similarity between female and male students’ academic faking was slightly greater in more gender-egalitarian cultures than in less gender-egalitarian cultures. Thus, educational stakeholders (e.g., teachers, principals, and policy-makers) should be made aware of cross-cultural differences in academic faking because faking gives fakers an unfair advantage.     

Economic Predictors of Differences in Interview Faking Between Countries: Economic Inequality Matters,Not the State of Economy

Many companies recruit employees from different parts of the globe, and faking behavior by potential employees is a ubiquitous phenomenon. It seems that applicants from some countries are more prone to faking compared to others, but the reasons for these differences are largely unexplored. This study relates country-level economic variables to faking behavior in hiring processes. In a cross-national study across 20 countries, participants (N = 3,839) reported their faking behavior in their last job interview. This study used the random response technique (RRT) to ensure participants’ anonymity and to foster honest answers regarding faking behavior. Results indicate that general economic indicators (gross domestic product per capita [GDP] and unemployment rate) show negligible correlations with faking across the countries, whereas economic inequality is positively related to the extent of applicant faking to a substantial extent. These findings imply that people are sensitive to inequality within countries and that inequality relates to faking, because inequality might actuate other psychological processes (e.g., envy) which in turn increase the probability for unethical behavior in many forms.     

Visuospatial Short-Term Memory Explains Deficits in Tower Task Planning in High-Functioning Children with Autism Spectrum Disorder

Previous findings on planning abilities in individuals with high-functioning autism spectrum disorder (HFA) are inconsistent. Exploring possible reasons for these mixed findings, the current study investigated the involvement of memory in planning performance in 15 children with HFA and 17 typically developing controls. In addition to planning abilities (measured with the Tower of London), short-term memory and delayed recall for verbal as well as visuospatial material were assessed. Findings suggest that particularly reduced efficiency in visuospatial short-term memory is associated with Tower task planning deficits in children with HFA.     

Measuring consciousness in dreams: The lucidity and consciousness in dreams scale

In this article, we present results from an interdisciplinary research project aimed at assessing consciousness in dreams. For this purpose, we compared lucid dreams with normal non-lucid dreams from REM sleep. Both lucid and non-lucid dreams are an important contrast condition for theories of waking consciousness, giving valuable insights into the structure of conscious experience and its neural correlates during sleep. However, the precise differences between lucid and non-lucid dreams remain poorly understood. The construction of the Lucidity and Consciousness in Dreams scale (LuCiD) was based on theoretical considerations and empirical observations. Exploratory factor analysis of the data from the first survey identified eight factors that were validated in a second survey using confirmatory factor analysis: INSIGHT, CONTROL, THOUGHT, REALISM, MEMORY, DISSOCIATION, NEGATIVE EMOTION, and POSITIVE EMOTION. While all factors are involved in dream consciousness, realism and negative emotion do not differentiate between lucid and non-lucid dreams, suggesting that lucid insight is separable from both bizarreness in dreams and a change in the subjectively experienced realism of the dream.