Maternal Sensitivity: a Resilience Factor against Internalizing Symptoms in Early Adolescents Born Very Preterm?

Compared with full-terms, preterm individuals are more at risk from infancy to adulthood for developing internalizing symptoms. Early maternal interactive behavior, especially maternal sensitivity, has been found to be a resilience factor in the developmental outcome of preterm children. The present longitudinal study aimed at examining whether early interactive parenting behaviors have a long term impact on the internalizing symptoms of preterm-born young adolescents. A total sample of 36 very preterm and 22 full-term children participated in an 11-year follow-up study. Maternal interactive behavior was assessed during a mother–infant interaction when the infant was 18 months old. At 11 years, internalizing symptoms were assessed with the Child Behavior Checklist (CBCL). Hierarchical regression analyses revealed that the interaction between groups (preterm/full-term) and maternal sensitivity at 18 months significantly explained CBCL internalizing symptoms at 11 years (β = ?0.526; p < 0.05). Specifically, although prematurity was related to internalizing problems, preterm children with higher maternal sensitivity did not differ from their full-term-born peers on the CBCL internalizing problems domain. These results suggest that maternal sensitivity is a long-term resilience factor preventing the development of internalizing problems at early adolescence in very preterm individuals.     

The roles of fatalism, self-confidence, and intellectual resources in the disablement process in older adults

In this study, the authors examined the relations between 3 psychological variables-fatalism, self-confidence, and intellectual resources-and the subsequent development of illness and disability 20 years later in an adult sample. Results indicated that greater fatalism, assessed in 1974, predicted greater difficulty in everyday cognitive tasks as well as illness in 1994. Higher self-confidence in 1974 was associated with lesser degrees of cognitive and fine motor difficulty in 1994. Greater intellectual resources in 1974 (a combination of intellectual flexibility and education) predicted less cognitive and gross motor difficulty as well as lesser degrees of illness in 1994. Some of these relations were stronger for older than for middle-aged individuals. Results are discussed in the context of models of the disablement process.     

Psychological effects of complex environments during the life span: A review and theory

This paper reviews evidence supporting a theory about the psychological effects of complex environments suggested by research on the causal relationships between occupational conditions and psychological functioning. The review indicates that environmental complexity leads to effective cognitive functioning across all stages of the life span. This effect has been found in both sexes, in several nations, and in species other than man. Although the evidence is not as extensive, environmental complexity also appears to lead to a self-directed rather than conformist orientation.     

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.     

Investigating the Relationships Between Mobility Behaviours and Indicators of Subjective Well-Being Using Smartphone-Based Experience Sampling and GPS Tracking

People interact with their physical environments every day by visiting different places and moving between them. Such mobility behaviours likely influence and are influenced by people's subjective well-being. However, past research examining the links between mobility behaviours and well-being has been inconclusive. Here, we provide a comprehensive investigation of these relationships by examining individual differences in two types of mobility behaviours (movement patterns and places visited) and their relationship to six indicators of subjective well-being (depression, loneliness, anxiety, stress, affect, and energy) at two different temporal levels of analysis (two-week tendencies and daily level). Using data from a large smartphone-based longitudinal study (N = 1765), we show that (i) movement patterns assessed via GPS data (distance travelled, entropy, and irregularity) and (ii) places visited assessed via experience sampling reports (home, work, and social places) are associated with subjective well-being at the between and within person levels. Our findings suggest that distance travelled is related to anxiety, affect, and stress, irregularity is related to depression and loneliness, and spending time in social places is negatively associated with loneliness. We discuss the implications of our work and highlight directions for future research on the generalizability to other populations as well as the characteristics of places. © 2020 European Association of Personality Psychology     

Problem solving by reference to rules or previous episodes: The effects of organized training,analogical models,and subsequent complexity of experience

Subjects learned a microcomputer drawing package under different conditions of training organization and practice complexity. Training instructions were presented in either a random or an organized order, and with or without an analogical model of the software package. Practice trials varied in visual and logical complexity. Performance on paper-arid-pencil and problem-solving tests was better following the model than following the no-model condition when practice trials were logically complex; the reverse was true when they were logically simple. Performance on the test of problem solving was also better following organized training than following randomly ordered training when practice trials were visually complex; the reverse was true following visually simple practice. We propose that the subjects performed the tasks by engaging in either episodebased or rule-based processing, and that performance was optimized when the processing used at encoding and retrieval was the same. The acquisition of skill in solving real problems is explained as procedural compilation.