The Role of Personality Profiles in the Longitudinal Relationship Between Work-related Well-being and Life Satisfaction Among Working Adults in Switzerland

Drawing on the concept of spillover between work and life domains and using a person-centred approach, the present study examined the role of Big Five personality trait profiles in moderating the relationship between work-related well-being and life satisfaction over a 1-year period in a sample of working adults in Switzerland (N = 1204). Latent profile analysis was first carried out to derive and compare alternative latent personality profile models. Subsequently, a two-wave cross-lagged structural equation model using three personality profiles (resilient, average, and oversensitive) as moderators was tested. Work stress and job satisfaction were used as negative and positive indicators of work-related well-being. The results showed that in the overall sample, only Time 1 life satisfaction predicted Time 2 job satisfaction. We found a moderating role for the personality profiles, where the effect of Time 1 work stress on Time 2 life satisfaction became salient in the oversensitive profile, while a significant effect of Time 1 life satisfaction on Time 2 work stress was found in the resilient profile. The current study showed that different combinations of personality traits may determine the way in which work-related well-being and general well-being relate to each other. © 2019 European Association of Personality Psychology     

Longitudinal Experience-Wide Association Studies—A Framework for Studying Personality Change

The importance of personality for predicting life outcomes in the domains of love, work, and health is well established, as is evidence that personality traits, while relatively stable, can change. However, little is known about the sources and processes that drive changes in personality traits and how such changes might impact important life outcomes. In this paper, we make the case that the research paradigms and methodological approaches commonly used in personality psychology need to be revised to advance our understanding of the sources and processes of personality change. We propose Longitudinal Experience-Wide Association Studies as a framework for studying personality change that can address the limitations of current methods, and we discuss strategies for overcoming some of the challenges associated with Longitudinal Experience-Wide Association Studies. © 2020 European Association of Personality Psychology     

A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires

This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology     

Assessing Personality States: What to Consider when Constructing Personality State Measures

Repeated assessments of personality states in daily diary or experience sampling studies have become a more and more common tool in the psychologist's toolbox. However, and contrary to the widely available literature on personality traits, no best practices for the development of personality state measures exist, and personality state measures have been developed in many different ways. To address this, we first define what a personality state is and discuss important components. On the basis of this, we define what a personality state measure is and suggest a general guideline for the development of such measures. Following the ABC of test construction can then guide the strategy for obtaining validity and reliability evidence: (A) What is the construct being measured? (B) What is the intended purpose of the measure? And (C) What is the targeted population of persons and situations? We then conclude with an example by developing an initial item pool for the assessment of conscientiousness personality states. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

Bringing Back the Person into Behavioural Personality Science Using Big Data

Behaviour and the individual person are important but widely neglected topics of personality psychology. We argue that new technologies to collect and new methods to analyse Big (Behavioural) Data have the potential to bring back both more behaviour and the individual person into personality science. The call for studying the individual person in the history of personality science, the related idiographic/nomothetic divide, as well as attempts to reconcile these two approaches are briefly reviewed. Furthermore, different meanings of the term idiographic and some unique selling points that emphasize the importance of idiographic research are highlighted. A nonexhaustive literature review shows that a wealth of behaviours are considered in extant personality studies using such Big Data but only in a nomothetic way. Against this background, we demonstrate the potential of Big Data collection and analysis with regard to four idiographic research topics: (i) unique manifestations of common traits and the resurgence of personal dispositions, (ii) idiographic prediction, (iii) intraindividual consistency versus variability of behaviour and (iv) intraindividual personality trait change through intervention. Methodological, ethical and legal pitfalls of doing Big Data research with individual persons as well as potential countermeasures are considered.     

Understanding Personality through Patterns of Daily Socializing: Applying Recurrence Quantification Analysis to Naturalistically Observed Intensive Longitudinal Social Interaction Data

Ambulatory assessment methods provide a rich approach for studying daily behaviour. Too often, however, these data are analysed in terms of averages, neglecting patterning of this behaviour over time. This paper describes recurrence quantification analysis (RQA), a non-linear time series technique for analysing dynamic systems, as a method for analysing patterns of categorical, intensive longitudinal ambulatory assessment data. We apply RQA to objectively assessed social behaviour (e.g. talking to another person) coded from the Electronically Activated Recorder. Conceptual interpretations of RQA parameters, and an analysis of Electronically Activated Recorder data in adults going through a marital separation, are provided. Using machine learning techniques to avoid model overfitting, we find that adding RQA parameters to models that include just average amount of time spent talking (a static measure) improves prediction of four Big Five personality traits: extraversion, neuroticism, conscientiousness, and openness. Our strongest results suggest that a combination of average amount of time spent talking and four RQA parameters yield an R² = .09 for neuroticism. Neuroticism is shown to be associated with shorter periods of extended conversation (periods of at least 12 minutes), demonstrating the utility of RQA to identify new relationships between personality and patterns of daily behaviour. Materials: https://osf.io/5nkr9/ . © 2020 European Association of Personality Psychology     

Daily Responsiveness,Expectations, and Self-disclosure: How the Average Levels and Within-person Variability of Three Relationship Components Mediate Personality–Relationship Transactions in Romantic Couples

The associations between couple members' personality and their relationship satisfaction can be conceptualized as reciprocal transactions. To better understand these transactions, we focused on both partners' interpersonal vulnerabilities (i.e. neuroticism, low self-esteem, and insecure attachment); daily emotional, cognitive, and behavioural relationship components (i.e. perceived responsiveness, positive expectations, and self-disclosure); and relationship satisfaction. Specifically, we examined whether the average levels and within-person variability of the relationship components mediated the transactions between interpersonal vulnerabilities and relationship satisfaction. Data came from 689 female–male couples aged 18 to 81 years who participated in three measurement occasions across 12 months, including a 14-day diary phase. We used mediated dyadic bivariate latent change score models to test the level–change and change–change transactions and mediations. The findings partly supported our hypotheses: Couple members with interpersonal vulnerabilities had lower average levels (but not higher within-person variability) of the relationship components, and less satisfied couple members had lower average levels and higher within-person variability of these components. The lower average levels but not the variability mediated between a lower level of relationship satisfaction and an increase in avoidant attachment. No other mediations were observed. We discuss the importance of studying daily relationship components for better understanding reciprocal transactions in couples. © 2020 European Association of Personality Psychology     

An extension of commonly used toilet-training procedures to children with autism spectrum disorder

The current study evaluated a toilet-training treatment package described by Greer et al. (2016) with children diagnosed with autism spectrum disorder (ASD). Most of the current research on toilet-training interventions for children with ASD are replications and modifications of Azrin and Foxx (1971) or (more recently) LeBlanc et al. (2005). However, these procedures are composed of components that are not included in studies with typically developing (TD) children. For example, Greer et al. evaluated the effectiveness of three typical components within a toilet-training package, mostly with TD participants: a 30-min sit schedule, placing participants in underwear, and differential reinforcement. The primary purpose of the current study was to replicate and extend the treatment package described by Greer et al. to children with ASD. A secondary purpose was to evaluate modifications necessary for individualized toilet training when the commonly used components were ineffective. The results of Greer et al. were replicated for 11 participants with ASD in the current study, suggesting that intensive toileting interventions (e.g., interventions requiring overcorrection, reprimands, and dense sit schedules) may only be necessary for a subset of individuals with ASD.