Team Composition Revisited: A Team Member Attribute Alignment Approach

Research methods for studying team composition tend to employ either a variable-centered or person-centered approach. The variable-centered approach allows scholars to consider how patterns of attributes between team members influence teams, while the person-centered approach allows scholars to consider how variation in multiple attributes within team members influences subgroup formation and its effects. Team composition theory, however, is becoming increasingly sophisticated, assuming variation on multiple attributes both within and between team members—for example, in predicting how a team functions differently when its most assertive members are also optimistic rather than pessimistic. To support this new theory, we propose an attribute alignment approach, which complements the variable-centered and person-centered approaches by modeling teams as matrices of their members and their members’ attributes. We first demonstrate how to calculate attribute alignment by determining the vector norm and vector angle between team members’ attributes. Then, we demonstrate how the alignment of team member personality attributes (neuroticism and agreeableness) affects team relationship conflict. Finally, we discuss the potential of using the attribute alignment approach to enrich broader team research

Team composition revisited: expanding the team member attribute alignment approach to consider patterns of more than two attributes

The attribute alignment approach to team composition allows researchers to assess variation in team member attributes that occurs simultaneously within and across individual team members. This approach facilitates the development of theory testing the proposition that individual members are themselves complex systems comprised of multiple attributes, and that the configuration of those attributes affects team-level processes and outcomes. Here, we expand this approach, originally developed for two attributes, by describing three ways researchers may capture the alignment of three or more team member attributes: 1) a geometric approach, 2) a physical approach accentuating ideal alignment, and 3) an algebraic approach accentuating the direction (as opposed to magnitude) of alignment. We also provide examples of the research questions each could answer and compare the methods empirically using a synthetic dataset assessing 100 teams of 3-7 members across four attributes. Then, we provide a practical guide to selecting an appropriate method when considering team-member attribute patterns by answering several common questions regarding applying attribute alignment. Finally, we provide code (https://github.com/kjem514/Attribute-Alignment-Code) and apply this approach to a field data set in our appendices

The TT genotype of methylenetetrahydrofolate reductase 677C>T polymorphism increases the susceptibility to pediatric ischemic stroke: meta-analysis of the 822 cases and 1,552 controls

The 677C>T polymorphism within methylenetetrahydrofolate reductase (MTHFR) gene is related to an elevated level of homocysteine. Thus it may be considered as a genetic risk factor in ischemic stroke. Apparently studies of this type of polymorphism in childhood stroke have shown conflicting results. We performed meta-analysis of all the data that are available in relation with MTHFR polymorphism and the risk of ischemic stroke in children. We searched PubMed (last search dated December 2010) using “MTHFR polymorphism”, “ischemic stroke” “child”, “children”, “pediatric stroke” as keywords and reference lists of studies and reviews on the topic. Finally, 15 case–control studies corresponded to the inclusion criteria for meta-analysis. These studies involved the total number of 822 children and adolescents after ischemic stroke and 1,552 control subjects. Fixed or random effects models were used depending on the heterogeneity between the studies. The association between ischemic stroke and 677C>T polymorphism within MTHFR gene was observed in three of the studies. The pooled analysis showed that TT genotype of MTHFR gene is more common in stroke patients than in controls (p = 0.0402, odds ratio = 1.57, 95 % confidence interval 1.02–2.41). The Egger’s test did not reveal presence of a publication bias. The results based on a sizeable group of cases and controls have proved that the 677C>T polymorphism in MTHFR gene is associated with the development of ischemic stroke in children

Better together: member proactivity is better for team performance when aligned with conscientiousness

Proactivity, the tendency to create change in the work environment, typically improves team performance. This relationship is far from perfect, however. We explore inconsistencies in the team proactivity literature to shed light on an important question – when is member proactivity beneficial or dysfunctional for teams? First, we consider the composition of member proactivity at the team level and whether a simple ‘more is better’ heuristic neglects a more complex relationship linking member proactivity to team coordination and performance. Second, we explore whether proactivity is better when aligned with another individual difference focused on the propensity to plan and coordinate with others (i.e., conscientiousness). In two studies, we compare traditional additive and configurational compositional approaches to these two attributes with a new attribute alignment approach, allowing us to examine the co-occurrence of proactivity and conscientiousness within some team members relative to others. First, we find that team member proactivity-conscientiousness alignment (P-C alignment) predicts the performance of MBA consulting teams better than the other team composition models we considered. Then, we replicate this finding in a laboratory simulation, finding that it occurs because P-C alignment improves team coordination. Our results demonstrate that member proactivity is most effective for the team when it aligns with conscientiousness