Experiential Avoidance and Emotion Regulation in Borderline Personality Disorder

Many of the severe behavioral difficulties observed among persons with BPD (e.g., self-harm, suicidal behaviors) have been conceptualized as attempts to avoid or escape unwanted emotional experiences. As such, experiential avoidance likely plays a prominent role in the difficulties faced by persons with BPD. Individuals with BPD have demonstrated heightened levels of experiential avoidance in several studies. Several key features of BPD may contribute to experiential avoidance among persons with BPD, including a vulnerability to negative or distressing emotions, difficulty regulating emotions, and distress intolerance. Some research also suggests that a vulnerability to negative emotions among persons with BPD may be partly due to the use of experiential avoidance strategies to cope with emotional experiences. Within this paper, we review the literature on experiential avoidance and possible mechanisms underlying experiential avoidance among persons with BPD, and discuss the research and clinical implications of this literature.     

Using Big Data and Machine Learning in Personality Measurement: Opportunities and Challenges

This conceptual paper examines the promises and critical challenges posed by contemporary personality measurement using big data. More specifically, the paper provides (i) an introduction to the type of technologies that give rise to big data, (ii) an overview of how big data is used in personality research and how it might be used in the future, (iii) a framework for approaching big data in personality science, (iv) an exploration of ideas that connect psychometric reliability and validity, as well as principles of fairness and privacy, to measures of personality that use big data, (v) a discussion emphasizing the importance of collaboration with other disciplines for personality psychologists seeking to adopt big data methods, and finally, (vi) a list of practical considerations for researchers seeking to move forward with big data personality measurement and research. It is expected that this paper will provide insights, guidance, and inspiration that helps personality researchers navigate the challenges and opportunities posed by using big data methods in personality measurement. © 2020 European Association of Personality Psychology     

Construct Measurement Quality Improves Predictive Accuracy in Violence Risk Assessment: an Illustration Using the Personality Assessment Inventory

Much of the risk assessment literature has focused on the predictive validity of risk assessment tools. However, these tools often comprise a list of risk factors that are themselves complex constructs, and focusing on the quality of measurement of individual risk factors may improve the predictive validity of the tools. The present study illustrates this concern using the Antisocial Features and Aggression scales of the Personality Assessment Inventory (Morey, 1991). In a sample of 1,545 prison inmates and offenders undergoing treatment for substance abuse (85% male), we evaluated (a) the factorial validity of the ANT and AGG scales, (b) the utility of original ANT and AGG scales and newly derived ANT and AGG scales for predicting antisocial outcomes (recidivism and institutional infractions), and (c) whether items with a stronger relationship to the underlying constructs (higher factor loadings) were in turn more strongly related to antisocial outcomes. Confirmatory factor analyses (CFAs) indicated that ANT and AGG items were not structured optimally in these data in terms of correspondence to the subscale structure identified in the PAI manual. Exploratory factor analyses were conducted on a random split‐half of the sample to derive optimized alternative factor structures, and cross‐validated in the second split‐half using CFA. Four‐factor models emerged for both the ANT and AGG scales, and, as predicted, the size of item factor loadings was associated with the strength with which items were associated with institutional infractions and community recidivism. This suggests that the quality by which a construct is measured is associated with its predictive strength. Implications for risk assessment are discussed. Copyright © 2013 John Wiley & Sons, Ltd.     

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     

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.     

Compiling Measurement Invariant Short Scales in Cross-Cultural Personality Assessment Using Ant Colony Optimization

Examining the influence of culture on personality and its unbiased assessment is the main subject of cross-cultural personality research. Recent large-scale studies exploring personality differences across cultures share substantial methodological and psychometric shortcomings that render it difficult to differentiate between method and trait variance. One prominent example is the implicit assumption of cross-cultural measurement invariance in personality questionnaires. In the rare instances where measurement invariance across cultures was tested, scalar measurement invariance—which is required for unbiased mean-level comparisons of personality traits—did not hold. In this article, we present an item sampling procedure, ant colony optimization, which can be used to select item sets that satisfy multiple psychometric requirements including model fit, reliability, and measurement invariance. We constructed short scales of the IPIP-NEO-300 for a group of countries that are culturally similar (USA, Australia, Canada, and UK) as well as a group of countries with distinct cultures (USA, India, Singapore, and Sweden). In addition to examining factor mean differences across countries, we provide recommendations for cross-cultural research in general. From a methodological perspective, we demonstrate ant colony optimization's versatility and flexibility as an item sampling procedure to derive measurement invariant scales for cross-cultural research. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

On Pedagogy of Personality Assessment: Application of Bloom's Taxonomy of Educational Objectives

In this article, Bloom's (1956 Bloom, B. (Ed.), Englehart, M. D., Furst, E. J., Hill, W. H., &; Krathwohl, D. R. (1956). Taxonomy of educational objectives: Handbook 1. Cognitive domain. White Plains, NY: Longman. [Google Scholar]) Taxonomy of Educational Objectives, a pedagogical tool that can help instructors of personality assessment to develop effective and student-centered instructional design, is discussed. Bloom's taxonomy provides a progressive sequence of educational objectives used for lesson planning, needs assessment, and measurement of learning outcomes. The taxonomy comprises 6 categories of objectives that are ordered hierarchically, from the simplest to the most advanced. The levels are knowledge, comprehension, application, analysis, synthesis, and evaluation. I explain how the taxonomy can be applied to the teaching of personality assessment and discuss the implications for assessment pedagogy. I provide examples of effective instructional activities, overview the signs of learners at each level, and highlight typical errors that students make in their oral and written work. Strategies to help learners progress to higher order thinking are also addressed.     

On the Comparison of TAT and Free Speech Techniques in Personality Assessment

Schnurr, Rosenberg, and Oxman (1992) recently compared the free speech samples and Thematic Apperception Test (TAT) responses of 95 normal adults. They concluded that the two techniques are not interchangeable, and that the TAT, which proved superior in the prediction of individual differences, may be preferable to free speech instructions for eliciting data in content analytic studies. We disagree with both conclusions. Various forms of narrative speech samples may be highly correlated, so long as psychologically meaningful, well-validated, and higher order content categories are used. The use of first-order content categories is less likely to contribute to the study of personality.     

Developments in Research in Personality Assessment

Progress in personality research requires an adequate data analysis link between concepts of what people are like and observations of how they are likely to behave. Advances in computer technology have strengthened this link but also have made it necessary for investigators to be wary of lack of selectivity and trivialization in their research designs.     

Clinician-Guided Assessment of Personality Using the Structural Interview and the Structured Interview of Personality Organization (STIPO)

This article demonstrates the utility of a theory-guided psychodynamic approach to the assessment of personality and personality pathology based on the object relations model developed by Kernberg (1984). We describe a clinical interview, the Structural Interview (SI; Kernberg, 1984), and also a semistructured approach, the Structured Interview of Personality Organization (STIPO; Clarkin, Caligor, Stern, & Kernberg, 2004) based on this theoretical model. Both interviews focus on the assessment of consolidated identity versus identity disturbance, the use of adaptive versus lower level defensive operations, and intact versus loss of reality testing. In the context of a more clinically oriented assessment, the SI makes use of tactful confrontation of discrepancies and contradictions in the patient's narrative, and also takes into account transference and countertransference phenomena, whereas the more structured approach of the STIPO incorporates clinical judgment informed by clinical theory into a well-guided interaction with the patient. Both interviews have good interrater reliability and are coherent with the alternative model for personality disorder diagnosis proposed by the Diagnostic and Statistical Manual of Mental Disorders (5th ed.), Section III. Finally, they provide the clinician with specific implications for prognosis and treatment planning and can rationally guide clinical decision making.     

数据权属与规制探讨

数据可分为原生数据与衍生数据。原生数据视来源不同分属国家、集体或个人。数据处理而形成的衍生数据往往涉及多方利益,形成“利益光谱”,对应多方权利主体。基于价值优先次序、权利位阶规则等,数据利益的“两头强化,多方平衡”,是我国法律数据确权和规制的指导思想。“两头强化”是指法律强化对位于“利益光谱”两端的国家利益与个人权益的保护,“多方平衡”指的是多方主体数据权益的平衡。数据规制的“硬法”进路为：明确法律概念,分析“利益光谱”,确定利益归属,权衡优先次序,平衡多方利益,搭建规制框架,制定具体规则。