To Challenge the Morning Lark and the Night Owl: Using Smartphone Sensing Data to Investigate Day–Night Behaviour Patterns

For decades, day–night patterns in behaviour have been investigated by asking people about their sleep–wake timing, their diurnal activity patterns, and their sleep duration. We demonstrate that the increasing digitalization of lifestyle offers new possibilities for research to investigate day–night patterns and related traits with the help of behavioural data. Using smartphone sensing, we collected in vivo data from 597 participants across several weeks and extracted behavioural day–night pattern indicators. Using this data, we explored three popular research topics. First, we focused on individual differences in day–night patterns by investigating whether ‘morning larks’ and ‘night owls’ manifest in smartphone-sensed behavioural indicators. Second, we examined whether personality traits are related to day–night patterns. Finally, exploring social jetlag, we investigated whether traits and work weekly day–night behaviours influence day–night patterns on weekends. Our findings highlight that behavioural data play an essential role in understanding daily routines and their relations to personality traits. We discuss how psychological research can integrate new behavioural approaches to study personality.     

How Are Personality States Associated with Smartphone Data?

Smartphones promise great potential for personality science to study people's everyday life behaviours. Even though personality psychologists have become increasingly interested in the study of personality states, associations between smartphone data and personality states have not yet been investigated. This study provides a first step towards understanding how smartphones may be used for behavioural assessment of personality states. We explored the relationships between Big Five personality states and data from smartphone sensors and usage logs. On the basis of the existing literature, we first compiled a set of behavioural and situational indicators, which are potentially related to personality states. We then applied them on an experience sampling data set containing 5748 personality state responses that are self-assessments of 30 minutes timeframes and corresponding smartphone data. We used machine learning analyses to investigate the predictability of personality states from the set of indicators. The results showed that only for extraversion, smartphone data (specifically, ambient noise level) were informative beyond what could be predicted based on time and day of the week alone. The results point to continuing challenges in realizing the potential of smartphone data for psychological research. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

The Personality Panorama: Conceptualizing Personality Through Big Behavioural Data

Personality psychology has long been grounded in data typologies, particularly in the delineation of behavioural, life outcome, informant-report, and self-report sources of data from one another. Such data typologies are becoming obsolete in the face of new methods, technologies, and data philosophies. In this article, we discuss personality psychology's historical thinking about data, modern data theory's place in personality psychology, and several qualities of big data that urge a rethinking of personality itself. We call for a move away from self-report questionnaires and a reprioritization of the study of behaviour within personality science. With big data and behavioural assessment, we have the potential to witness the confluence of situated, seamlessly interacting psychological processes, forming an inclusive, dynamic, multiangle view of personality. However, big behavioural data come hand in hand with important ethical considerations, and our emerging ability to create a ‘personality panopticon’ requires careful and thoughtful navigation. For our research to improve and thrive in partnership with new technologies, we must not only wield our new tools thoughtfully, but humanely. Through discourse and collaboration with other disciplines and the general public, we can foster mutual growth and ensure that humanity's burgeoning technological capabilities serve, rather than control, the public interest. © 2020 European Association of Personality Psychology     

Subjectifying the Personality State: Theoretical Underpinnings and an Empirical Example

Recent developments in personality research highlight the value of modelling dynamic state-like manifestations of personality. The present work integrates these developments with prominent clinical models addressing within-person multiplicity and promotes the exploration of models centred on state-like manifestations of personality that function as cohesive organizational units. Such units possess distinct subjective qualities and are characterized by specific affects, behaviours, cognitions, and desires that tend to be co-activated. As background, we review both theory and research from the fields of social cognition, psychotherapy, and psychopathology that serve as the foundation for such models. We then illustrate our ideas in greater detail with one well-supported clinical model—the schema therapy mode model, chosen because it provides a finite and definite set of modes (i.e. cohesive personality states). We assessed these modes using a newly developed experience-sampling measure administered to 52 individuals (four times daily for 15 days). We estimated intraindividual and group-level temporal and contemporaneous networks based on the within-person variance as well as between-person network. We discuss findings from exemplar participants and from group-level networks and address cross-model particularities and consistencies. In conclusion, we consider potential idiographic and nomothetic applications of subjective states dynamic personality research based on intensive longitudinal methods. © 2020 European Association of Personality Psychology     

How do people respond to health news? The role of personality traits

When a patient receives a health diagnosis, their response (e.g. changes in behaviour, seeking support) can have significant consequences for long-term health and well-being. Characteristics of health news are known to influence these responses, but personality traits have been omitted from this line of research. The current study examines the role of personality traits in predicting response to health news. Participants (N = 298) read scenarios in which they received health news that was manipulated to vary in severity, controllability and likelihood of outcomes. Participants then rated how likely they were to engage in a number of response behaviours. We examined the main effects and interaction of situational manipulations and personality traits on ratings of these behaviours. Both situations and personality traits influenced behavioural responses to health events. In particular, conscientiousness predicted taking action and seeking social support. Neuroticism predicted both maladaptive and adaptive behavioural responses, providing support for the ‘healthy neurotic’ hypothesis. Moreover, personality traits predicted best in weak (unlikely, controllable) situations. Both personality traits and situational characteristics contribute to behavioural responses to health news.     

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     

Vocational interests and Big Five traits as predictors of job instability

Although empirical research on this topic is scarce, personality traits and vocational interests have repeatedly been named as potential individual level predictors of job change. Using a long-term cohort study (N = 291), we examined RIASEC interest profiles and Big Five personality scores at the beginning of the professional career as predictors of subsequent job changes, both internal as well as external, over the next 15 years. Overall, results provide additional evidence for an individual difference perspective on job instability, although our findings vary across instability variables. Consistent with previous research, external job changes in particular related to individual differences. Specifically, scores on Investigative, Artistic, Enterprising and Conventional scales showed to be the most important interest related predictors. With regard to Big Five personality traits, strongest associations were found with Agreeableness and Openness. In addition, facet level analyses proved to be useful to further clarify linkages between personality and job instability.     

Testing the bi‐dimensional effects of attitudes on behavioural intentions and subsequent behaviour

Attitudes are typically treated as unidimensional predictors of both behavioural intentions and subsequent behaviour. On the basis of previous research showing that attitudes comprise two independent, positive and negative dimensions, we hypothesized that attitudes would be bi‐dimensional predictors of both behavioural intentions and subsequent behaviour. We focused on health‐risk behaviours. We therefore also hypothesized that the positive dimension of attitude (evaluations of positive behavioural outcomes) would better predict both behavioural intentions and subsequent behaviour than would the negative dimension, consistent with the positivity bias/offset principle. In Study 1 (cross sectional design), N = 109 university students completed questionnaire measures of their intentions to binge‐drink and the positive and negative dimensions of attitude. Consistent with the hypotheses, both attitude dimensions independently predicted behavioural intentions and the positive dimension was a significantly better predictor than was the negative dimension. The same pattern of findings emerged in Study 2 (cross sectional design; N = 186 university students) when we predicted intentions to binge‐drink, smoke and consume a high‐fat diet. Similarly, in Study 3 (prospective design; N = 1,232 speed limit offenders), both the positive and negative dimensions of attitude predicted subsequent (6‐month post‐baseline) speeding behaviour on two different road types and the positive dimension was the better predictor. The implications for understanding the motivation of behaviour and the development of behaviour‐change interventions are discussed.     

Linking property crime using offender crime scene behaviour: A comparison of methods

This study compared the ability of seven statistical models to distinguish between linked and unlinked crimes. The seven models utilised geographical, temporal, and modus operandi information relating to residential burglaries (n = 180), commercial robberies, (n = 118), and car thefts (n = 376). Model performance was assessed using receiver operating characteristic analysis and by examining the success with which the seven models could successfully prioritise linked over unlinked crimes. The regression‐based and probabilistic models achieved comparable accuracy and were generally more accurate than the tree‐based models tested in this study. The Logistic algorithm achieved the highest area under the curve (AUC) for residential burglary (AUC = 0.903) and commercial robbery (AUC = 0.830) and the SimpleLogistic algorithm achieving the highest for car theft (AUC = 0.820). The findings also indicated that discrimination accuracy is maximised (in some situations) if behavioural domains are utilised rather than individual crime scene behaviours and that the AUC should not be used as the sole measure of accuracy in behavioural crime linkage research.     

Ant Colony Optimization and Local Weighted Structural Equation Modeling. A Tutorial on Novel Item and Person Sampling Procedures for Personality Research

Measurement in personality development faces many psychometric problems. First, theory‐based measurement models do not fit the empirical data in terms of traditional confirmatory factor analysis. Second, measurement invariance across age, which is necessary for a meaningful interpretation of age‐associated personality differences, is rarely accomplished. Finally, continuous moderator variables, such as age, are often artificially categorized. This categorization leads to bias when interpreting differences in personality across age. In this tutorial, we introduce methods to remedy these problems. We illustrate how Ant Colony Optimization can be used to sample indicators that meet prespecified demands such as model fit. Further, we use Local Structural Equation Modeling to resample and weight subjects to study differences in the measurement model across age as a continuous moderator variable. We also provide a detailed illustration for both tools with the Neuroticism scale of the openly available International Personality Item Pool – NEO inventory using data from the UK sample (N = 15 827). Combined, both tools can remedy persistent problems in research on personality and its development. In addition to a step‐by‐step illustration, we provide commented syntax for both tools. © 2019 European Association of Personality Psychology     

Trait personality and state variability: Predicting individual differences in within- and cross-context fluctuations in affect,self-evaluations,and behavior in everyday life

Prior research on the effects of personality on the variability of states has either not assessed states in real-life contexts or not incorporated meaningful contextual information when analyzing state variability. Providing an integrated contextualized approach, we introduce the Within and Across Context (WAC) Variability framework that disentangles real-life within-person fluctuations occurring within and across real-life contexts. To illustrate the utility of this framework, we investigated effects of Big Five personality traits on the level and the within- and cross-context variability of experience-sampled states (affect, self-esteem, behavior) of psychology freshmen (N = 118). Results provide initial empirical support for the meaningful separation of within- and cross-context variability and their distinct relations to personality.     

Health performance of individuals within the Campbell paradigm

In this paper, we developed a comprehensive health performance measure that formally links individual health attitudes with the likelihood of engaging in a wide variety of health‐related behaviours from various domains such as sustenance, hygiene, and physical exercise. Within what Kaiser, Byrka, and Hartig (2010) call the Campbell paradigm, we equated general health attitude with what a person does to retain or promote his or her health. Thus, health behaviours, on one hand, were expected to form a homogeneous, transitively ordered class of behaviours. On the other hand, the very behavioural class was in turn thought to be the basis from which an individual's health attitude could be directly assessed. A sample of 391 adults provided us with survey data containing different sets of health behaviours as well as variables and personality measures that had been corroborated as health‐behaviour relevant in previous research. We found that self‐reports of 50 behaviours and expressions of appreciation for 20 of these behaviours from various domains formed a transitively ordered class of activities. In contrast to the conventional view in health psychology, in which attitudes are regarded as a psychological cause behind individual behaviour, and in contrast to conventional findings in health psychology, where behaviours appear to fall into numerous sets of more or less distinct domains of health‐enhancing activities (e.g., exercising or avoiding risks), our findings speak of the psychological and formal unity of health behaviour. Inevitably, attitude measures grounded in the Campbell paradigm gauge individual attitudes, and just as much, they measure the health performance of individuals.     

The relationship between cognitive ability and personality scores in selection situations: A meta‐analysis

Several faking theories have identified applicants’ cognitive ability (CA) as a determinant of faking—the intentional distortion of answers by candidates—but the corresponding empirical findings in the area of personality tests are often ambiguous. Following the assumption that CA is important for faking, we expected applicants with high CA to show higher personality scores in selection situations, leading in this case to significant correlations between CA and personality scores, but not in nonselection situations. This meta‐analysis (66 studies, k = 115 individual samples, N = 46,265) showed this pattern of results as well as moderation effects for the study design (laboratory vs. field), the response format of the personality test, and the type of CA test.     

Personality and daily experience revisited

In this introduction to the Journal of Personality special issue devoted to "Advances in Personality and Daily Experience" we attempt to trace recent progress in the study of personality and daily life. We begin by comparing and contrasting the methods of daily experience research adopted by investigators who authored empirical articles in the 1991 and current special issues according to the mode, schedule, and sampling frame for data collection. We then compare data analytic strategies across the 14 years between the two special issues and conclude that although the nature of the questions addressed has not changed dramatically, newer analytic methods and associated software have enhanced our ability to answer these questions more precisely. Finally, we provide an overview of the special issue contributions organized around three broad themes: personal vulnerabilities and resources that predict reactions to everyday events, interpersonal manifestations of personality in daily experience, and how personality in daily life affects physical and mental health and relates to disease risk.     

Seeing is Knowing: On the Predictive Accuracy of Self‐ and Informant Reports for Prosocial and Moral Behaviours

Under certain circumstances, well‐known others (so‐called informants) may possess unique insights into targets' personality traits beyond the targets' self‐views. Specifically, as proposed by the self–other knowledge asymmetry model, an incremental predictive ability of informants is most likely for traits and corresponding behaviours that are clearly visible to others and highly evaluative in nature. In two studies, we provide an empirical test of this proposition and extend prior research to one of the most important domains of interpersonal interaction: prosocial and moral behaviours. Specifically, we investigate the unique predictive power of informant reports in trait Honesty–Humility for fairness in the dictator game and dishonesty in a cheating paradigm. Importantly, while both these classes of behaviour are highly evaluative in nature, only fairness is clearly visible to others. Correspondingly, in line with the self–other knowledge asymmetry model, our results reveal unique predictive accuracy of informant reports for fairness. For dishonesty, by contrast, there was no conclusive evidence for incremental predictive power of informant reports. This implies that informants may indeed provide valuable information beyond targets' self‐reports on trait aspects driving fair behaviour, but that targets themselves are their own best experts when it comes to judging trait aspects driving dishonest behaviour. Copyright © 2017 European Association of Personality Psychology     

The Center for Lifespan Psychology at the Max Planck Institute for Human Development: Overview of conceptual agenda and illustration of research activities

Founded in 1981 by the late Paul B. Baltes, the Center for Lifespan Psychology at the Max Planck Institute for Human Development has helped to establish lifespan psychology as a distinct conceptual approach within developmental psychology. Recently, the Center has extended its research programme into developmental behavioural neuroscience. Here, we provide an overview of the Center's conceptual agenda, and present two of its seven research projects in greater detail. Work at the Center is guided by three propositions: (1) to study lifespan changes in behaviour as interactions among maturation, learning, and senescence; (2) to develop theories and methods that integrate empirical evidence across domains of functioning, timescales, as well as behavioural and neuronal levels of analysis; (3) to identify mechanisms of development by exploring age-graded differences in plasticity. The Intra-Person Dynamics Project studies the organization of cognitive abilities within individuals of different ages, and investigates lifespan age differences in the plasticity and components of episodic memory performance. The Sensorimotor–Cognitive Couplings Project examines lifespan differences in dynamic dependencies between sensorimotor and cognitive performance. Both projects combine behavioural assessments with methods from developmental neuroscience to delineate age-graded changes in brain–behaviour mappings. Current research in other projects includes: (1) behavioural development in very old age, as assessed in the Berlin Aging Study; (2) the interplay of motivation, affect, and cognition in developmental regulation; (3) behavioural and electrophysiological mechanisms of social interaction from infancy to adulthood; and (4) formal and statistical issues in structural equation modelling, with an emphasis on latent growth curve modelling. Graduate education and research at the Center profit greatly from cooperation with other institutions in Berlin and Potsdam as well as from national and international collaboration.     

Personality in Action: Assessing Personality to Identify an ‘Ideal’ Conscientious Response Type with Two Different Behavioural Tasks

Performance on achievement tests is characterized by an interplay of different individual attributes such as personality traits, motivation or cognitive styles. However, the prediction of individuals' performance from classical self-report personality measures obtained during large and comprehensive aptitude assessments is biased by, for example, subjective response tendencies. This study goes beyond by using behavioural data based on two different types of tasks, requiring different conscientious-related response behaviours. Moreover, a typological approach is proposed, which includes different behavioural indicators to obtain information on complex personality characteristics. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

Individual differences in the acceptance of stereotyping

Previous research has documented individual differences in a range of constructs relating to social stereotyping, prejudice, and intergroup attitudes. However, research has not sought specifically to measure a general acceptance of social stereotyping. In the present research, we explored attitudinal, cognitive, emotional, and personality correlates of a person’s self-reported willingness to rely on stereotypical information when interacting with people of different social and cultural groups. In six studies (N = 1080) we found that more acceptance of stereotyping was associated with more explicit and implicit stereotyping of particular groups, less liberal gender-role values, more authoritarian attitudes, preference for hierarchies, higher social dominance orientation, less universal outlook, less complexity in describing others’ emotions, less utilization of emotional information, and more utilization of social categories (gender and race) when rating the similarity of faces, less agreeable and more agentic personality, and more rigid and simplistic cognitive style (all independent of one’s gender). Female and African-American participants were less accepting of stereotyping than male and Caucasian participants. The general tendency to accept stereotyping in daily life is a measurable individual difference that may prove useful in social-personality research.