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.     

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.     

A model‐based intervention for depressed mothers and their infants

Many studies have reported on the adverse effects of maternal depression on offspring. Infants of depressed mothers are found to be more likely at risk to develop mental and socioemotional problems. In this study, an early intervention program is presented that aims to improve the interaction between depressed mothers and their infants to prevent developmental problems in the children. The program has recently been introduced in the Dutch Community Mental Health Centers as part of a national multicomponent program to reduce the risk of psychiatric and social problems in the offspring of parents with a mental disorder. The intervention for depressed mothers with babies is based on a transactional model in which the mother–child interaction plays a key role in explaining the development of socioemotional problems in the children. The model as discussed in the first part of this article addresses a range of evidenced‐based parental, child, and contextual risk factors that effect the quality of the interactions between depressed mothers and their infants and that contribute to both vulnerability and resilience of the children during later childhood and adolescence. ©2005 Michigan Association for Infant Mental Health.     

Masking misfit in confirmatory factor analysis by increasing unique variances: a cautionary note on the usefulness of cutoff values of fit indices

Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as "golden rules" for establishing the fit or other aspects of structural equation models. The current study shows how differences in unique variances influence the value of the global chi-square model test and the most commonly used fit indices: Root-mean-square error of approximation, standardized root-mean-square residual, and the comparative fit index. Using data simulation, the authors illustrate how the value of the chi-square test, the root-mean-square error of approximation, and the standardized root-mean-square residual are decreased when unique variances are increased although model misspecification is present. For a broader understanding of the phenomenon, the authors used different sample sizes, number of observed variables per factor, and types of misspecification. A theoretical explanation is provided, and implications for the application of structural equation modeling are discussed.     

Connectedness and Self‐Regulation as Constructs of the Student Success Skills Program in Inner‐City African American Elementary School Students

The authors evaluated a small‐group counseling intervention, Student Success Skills, provided to 53 inner‐city, 4th‐ and 5th‐grade African American students. Compared with the control group, students who received the treatment reported significant changes in metacognitive skill and feelings of connectedness to school. Furthermore, treatment‐group students received higher posttest change scores on certain executive functioning subscale items, as reported by their classroom teachers. Implications for counseling practice are presented.     

Introducing a novel method to assess cumulative steroid concentrations: increased hair cortisol concentrations over 6 months in medicated patients with depression

Depression has been linked to increased cortisol concentrations using point measures taken from urine, blood, or saliva samples. However, with regard to hypercortisolism-induced consequences, long-term cumulative cortisol burden is of relevance. Our objective was to use hair analysis as a new method to assess cortisol exposure over 6 months in depressed patients and healthy controls. We examined 23 depressed patients (8 men and 15 women, mean age: 41.6 years (?±?standard deviation (SD), 13.1 years); mean duration of current depressive episode 9 months (?±?SD, 13 months)) and 64 healthy controls, matched for age and gender. Cortisol concentrations in two 3-cm hair segments from near to the scalp were analyzed, representing cortisol secretion during the 6 months prior to sampling. Compared with healthy individuals, depressed patients had higher hair cortisol concentrations in the first (mean?±?SD: 26.7?±?20.8 vs. 18.7?±?11.5?pg/mg, p?相似文献   

The parish clergy as a mental health resource

Summary This paper presents observations on the assets and liabilities of the parish clergy as a mental health resource within the community. These observations are drawn from a ten-year program of continuing education for cleargy in mental health, which focuses on daily pastoral experience. The parish setting is similar in many respects to the service area of a community mental health center. The clergy's assets often include availability, experience, tradition, and the special significance of the religious leader. Inadequate training in mental health skills and the complex demands of parish life are among the problems confronting the clergy in this area. On the whole, the pastoral role offers a unique and highly useful opportunity for positive psychological intervention.The work described in this paper has been supported in part by National Institute of Mental Health grant no. MH-11929-01 and by grants from the Cleveland Foundation and the Grant Foundation, Inc., and the Cuyahoga County Board of Mental Health and Mental Retardation.