Explanation in personality psychology: "Verbal magic" and the five-factor model

The social evolution of individual differences: Future directions for a comparative science of personality in social behavior

Personality is essential for understanding the evolution of cooperation and conflict in behavior. However, personality science remains disconnected from the field of social evolution, limiting our ability to explain how personality and plasticity shape phenotypic adaptation in social behavior. Researchers also lack an integrative framework for comparing personality in the contextualized and multifaceted behaviors central to social interactions among humans and other animals. Here we address these challenges by developing a social evolutionary approach to personality, synthesizing theory, methods, and organizing questions in the study of individuality and sociality in behavior. We critically review current measurement practices and introduce social reaction norm models for comparative research on the evolution of personality in social environments. These models demonstrate that social plasticity affects the heritable variance of personality, and that individual differences in social plasticity can further modify the rate and direction of adaptive social evolution. Future empirical studies of frequency- and density-dependent social selection on personality are crucial for further developing this framework and testing adaptive theory of social niche specialization.

Logical fallacies and misinterpretations that hinder progress in translational addiction neuroscience

Substance use disorders (SUDs) are heterogeneous and complex, making the development of translationally predictive rodent and nonhuman primate models to uncover their neurobehavioral underpinnings difficult. Neuroscience-focused outcomes have become highly prevalent, and with this, the notion that SUDs are disorders of the brain embraced as a dominant theoretical orientation to understand SUD etiology and treatment. These efforts, however, have led to few efficacious pharmacotherapies, and in some cases (as with cocaine or methamphetamine), no pharmacotherapies have translated from preclinical models for clinical use. In this theoretical commentary, we first describe the development of animal models of substance use behaviors from a historical perspective. We then define and discuss three logical fallacies including 1) circular explanation, 2) affirming the consequent, and 3) reification that can apply to developed models. We then provide three case examples in which conceptual or logical issues exist in common methods (i.e., behavioral economic demand, escalation, and reinstatement). Alternative strategies to refocus behavioral models are suggested for the field to better bridge the translational divide between animal models, the clinical condition of SUDs, and current and future regulatory pathways for intervention development.

Network models of driver behavior

The way people behave in traffic is not always optimal from the road safety perspective: drivers exceed speed limits, misjudge speeds or distances, tailgate other road users or fail to perceive them. Such behaviors are commonly investigated using self-report-based latent variable models, and conceptualized as reflections of violation- and error-proneness. However, attributing dangerous behavior to stable properties of individuals may not be the optimal way of improving traffic safety, whereas investigating direct relationships between traffic behaviors offers a fruitful way forward. Network models of driver behavior and background factors influencing behavior were constructed using a large UK sample of novice drivers. The models show how individual violations, such as speeding, are related to and may contribute to individual errors such as tailgating and braking to avoid an accident. In addition, a network model of the background factors and driver behaviors was constructed. Finally, a model predicting crashes based on prior behavior was built and tested in separate datasets. This contribution helps to bridge a gap between experimental/theoretical studies and self-report-based studies in traffic research: the former have recognized the importance of focusing on relationships between individual driver behaviors, while network analysis offers a way to do so for self-report studies.

Personality Dynamics, Motivation, and the Logic of Explanation

Dynamic personality approaches provide an important step forward for twenty-first century personality theories because they promise greater explanatory power compared with latent trait approaches. Nevertheless, whether dynamic personality theories satisfactorily address motivated action remains unclear. To address this, this article discusses the logic of explanation and problems with latent trait approaches in terms of circularity and reification. The article then assesses explanation within dynamic personality accounts and the putative role of motivation. While dynamic personality approaches avoid many of the problems associated with latent trait accounts, a satisfactory account of motivational systems and “human nature” is currently missing. Suggestions for addressing the dynamics of human nature in terms of criteria for motivational systems are discussed. Attachment theory is offered as one possible foundation for addressing the motivational dynamics of personality.

On Dreams and Motivation: Comparison of Freud's and Hobson's Views

The merits of Freudian dream theory continue to be debated and both supporters and critics appeal to empirical evidence to support their respective positions. What receives much less attention is the theoretical coherency of either Freudian dream theory or alternative perspectives. This paper examines Freudian dream theory and J. Allan Hobson's alternative position by addressing the role of motivation in dreams. This paper first discusses motivation in Freudian theory and its relation to dreams and disguise-censorship. The role of motivation in Hobson's theory is then considered. Hobson's claim that dream plot and content selection is random and based on design error and functional imbalance is then discussed in relation to the protoconsciousness theory proposal that dreams serve an adaptive function. While there are apparent inconsistencies in Hobson's position, his appeal to emotions and instincts provides a preliminary platform for understanding the role of motivation in dreams that is consonant with the Freudian position.

Using network analysis to study behavioural phenotypes: an example using domestic dogs

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs (Canis lupus familiaris). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

Using network analysis to study behavioural phenotypes: an example using domestic dogs

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs (Canis lupus familiaris). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

Ego, drives, and the dynamics of internal objects

This paper addresses the relationship between the ego, id, and internal objects. While ego psychology views the ego as autonomous of the drives, a less well-known alternative position views the ego as constituted by the drives. Based on Freud's ego-instinct account, this position has developed into a school of thought which postulates that the drives act as knowers. Given that there are multiple drives, this position proposes that personality is constituted by multiple knowers. Following on from Freud, the ego is viewed as a composite sub-set of the instinctual drives (ego-drives), whereas those drives cut off from expression form the id. The nature of the "self" is developed in terms of identification and the possibility of multiple personalities is also established. This account is then extended to object-relations and the explanatory value of the ego-drive account is discussed in terms of the addressing the nature of ego-structures and the dynamic nature of internal objects. Finally, the impact of psychological conflict and the significance of repression for understanding the nature of splits within the psyche are also discussed.

Evolutionary and differential psychology: conceptual conflicts and the path to integration

Evolutionary psychology has seen the majority of its success exploring adaptive features of the mind believed to be ubiquitous across our species. This has given rise to the belief that the adaptationist approach has little to offer the field of differential psychology, which concerns itself exclusively with the ways in which individuals systematically differ. By framing the historical origins of both disciplines, and exploring the means through which they each address the unique challenges of psychological description and explanation, the present article identifies the conceptual and theoretical problems that have kept differential psychology isolated not only from evolutionary psychology, but from explanatory approaches in general. Paying special attention to these conceptual problems, the authors review how these difficulties are being overcome by contemporary evolutionary research, and offer instructive suggestions concerning how differential researchers (and others) can best build upon these innovations.

Fundamental Questions in Personality

The network perspective represents a novel contribution to personality theory by conceptualising personality traits as emerging from the mutual dependencies between fundamental and causal affective, behavioural, and cognitive components. We argue that incorporating a more nuanced biological and developmental perspective to causality and a more precise approach to affective, behavioural, cognitive and motivational components may serve to enrich the network perspective. Although the graphical approach to modelling personality is aesthetically pleasing, analytic techniques are not yet available to put network models to the (quantitative) test. Copyright © 2012 John Wiley & Sons, Ltd.