Seth M. Spain

Development of identity clarity and content in adulthood.

The current research examines self-concept clarity over 2 assessment points with the aims of establishing patterns of stability and change in self-concept clarity across adulthood, modeling corollary changes in traits and health-related role limitations, and demonstrating the ways in which gender and age moderate these patterns. Within this sample of 461 adults age 19–86 years of age, self-concept clarity had robust rank-order stability and no significant mean-level change during a 3-year assessment window. However, significant interindividual variability was present in the developmental patterns of self-concept clarity over time. These individual differences in development of self-concept clarity corresponded to developmental patterns in Big Five personality traits and health-related role limitations. Results of this 2 wave longitudinal study suggest 3 primary conclusions: (a) self-concept clarity predicts and corresponds to trait maturation over time, (b) decreasing self-concept clarity corresponds to increasing role limitations, and (c) these effects are somewhat contingent on gender and age. Results are discussed in reference to the maturation of identity content and metacognitive identity evaluation over the life span.

Count-Based Research in Management Suggestions for Improvement

We review 11 years (2001-2011) of management research using count-based dependent variables in 10 leading management journals. We find that approximately one out of four papers use the most basic Poisson regression model in their studies. However, due to potential concerns of overdispersion, alternative regression models may have been more appropriate. Furthermore, in many of these papers the overdispersion may have been caused by excess zeros in the data, suggesting that an alternative zero-inflated model may have been a better fit for the data. To illustrate the potential differences among the model specifications, we provide a comparison of the different models using previously published data. Additionally, we simulate data using different parameters. Finally, we offer a simplified decision tree guideline to improve future count-based research.

Separating the why from the what: Reply to Jonas and Markon(2015).

In this response to the commentary offered by Jonas and Markon (2015) on our earlier work, we address points of agreement and disagreement on the nature and utility of functionalist and descriptivist accounts of personality. Specifically, we argue that explanatory and conceptual parsimony is more appropriate than statistical parsimony for evaluating the proposed models, discuss ways in which functionalist and descriptivist approaches can complement one another, and provide some cautions about interpreting latent traits.

A sociogenomic perspective on neuroscience in organizational behavior

We critically examine the current biological models of individual organizational behavior, with particular emphasis on the roles of genetics and the brain. We demonstrate how approaches to biology in the organizational sciences assume that biological systems are simultaneously causal and essentially static; that genotypes exert constant effects. In contrast, we present a sociogenomic approach to organizational research, which could provide a meta-theoretical framework for understanding organizational behavior. Sociogenomics is an interactionist approach that derives power from its ability to explain how genes and environment operate. The key insight is that both genes and the environment operate by modifying gene expression. This leads to a conception of genetic and environmental effects that is fundamentally dynamic, rather than the static view of classical biometric approaches. We review biometric research within organizational behavior, and contrast these interpretations with a sociogenomic view. We provide a review of gene expression mechanisms that help explain the dynamism observed in individual organizational behavior, particularly factors associated with gene expression in the brain. Finally, we discuss the ethics of genomic and neuroscientific findings for practicing managers and discuss whether it is possible to practically apply these findings in management.

Children’s Stories as a Foundation for Leadership Schemas: More than Meets the Eye

Abstract This chapter examines how the stories can shape the leadership and followership schemas of children. We explore how television programs can shape attitudes toward leaders as well as providing role models for effective or desirable leadership and followership behaviors. In particular, we use personality assessments of characters from the popular children’s television show The Transformers to demonstrate how fictional stories can inform children of what characteristics are associated with leadership. Moreover, we demonstrate how the television program provided examples of both positive and negative styles of leadership and followership as well as providing normative information of what constitutes appropriate interpersonal behavior within organizations. These findings help illustrate the power of storytelling as a tool for leadership development, particularly in children.

Brief Report: Personality Mediates the Relationship between Autism Quotient and Well-Being: A Conceptual Replication using Self-Report

Autism spectrum disorder (ASD) impacts well-being across the lifespan. Individuals with ASD evidence differences in personality traits and self-concept clarity that are predictors of well-being in typically-developing individuals. The current research replicates a growing body of evidence demonstrating differences in well-being and personality between individuals low in ASD characteristics (n = 207) and individuals high in ASD characteristics (n = 46) collected from the general population using an online survey. Results were consistent in a subsample of demographically matched pairs (n = 39 per group) and relative to norms. Further, the current research provides the first evidence that openness, conscientiousness, emotional stability, and self-concept clarity mediate the relationship between ASD characteristics and well-being.

Toward a Sociogenomic Model of Leadership: A Theoretical Overview

In this article, we address biological models of individual organizational behavior, giving special attention to biological models of leadership. We believe that current approaches to biology in the organizational sciences assume that biological systems are simultaneously causal and essentially static. In contrast, we present a sociogenomic approach to leadership research. Sociogenomics is an interactionist approach, but its great strength derives from its power to explain how genes and environment operate, and so how they interact. The key insight is that both genes and the environment operate by modifying gene expression. This leads to a conception of genetic and environmental effects in leadership that is fundamentally dynamic, rather than the comparatively static interpretations of classical biometric approaches. We briefly review the behavioral genetics research within the leadership field, and then we interpret results of the behavioral genetics studies from the standpoint of sociogenomics. We then contrast these interpretations with existing approaches to genetics in leadership research. Finally, we outline some broad avenues of research that the sociogenomic approach indicates may be fruitful for a greater understanding of the biological substrates of leadership, the nature of leadership constructs, and the design of leadership interventions. We emphasize the utility of the sociogenomic perspective for leadership as a meta-theoretic framework, even for researchers who do not take an explicitly biological approach.

Testing the Form of Theoretical Models by Relaxing Assumptions: Comparing Parametric and Nonparametric Models

One of the most fundamental assumptions in parametric statistical analysis is that the parametric model correctly captures the form of relationships being modeled. A key example is traditional multiple linear regression, where each partial regression function is assumed to be linear. This assumption is rarely explicitly tested in organizational research, partially because statistical approaches for testing the assumption are not widely known. We present methods to test this assumption by relaxing it. We discuss both fully nonparametric techniques and the more restrictive additive model, which relaxes only the assumption of linearity, compared to linear regression. We demonstrate how to fit both hypothesized linear models and equivalent additive models. We illustrate how to compare these models to determine whether the regression functions are truly linear. We discuss the strengths and limitations of nonparametric regression and additive models and advocate for more general use of these techniques in analysis of organizational data.

Three-Mode Principal Components Analysis of Daily Affect at Work

Affect was largely ignored in the organizational sciences until very recently. However, the impact of affect on dynamic process influencing workplace behavior is increasingly critical. This study employs the multi-way analytic techniques PARAFAC and the Tucker model in an attempt to clarify the three sources of variance in daily mood ratings. The 2 x 2 x 2 structure found here is largely consistent with work by Zevon and Tellegen (1982) and Tellegen, Watson, and Clark (1999), and bears on research into the nature of affective processes in workplace behavior.