International Journal of Developmental Science

The goal of this paper was to further our understanding of adolescents' adjustment by studying multiple components of siblings' unique family environments using the difference score methodology. Self-report data about marital conflict, parent-child hostility and adolescents' adjustment were obtained from 114 sibling pairs (mean ages = 14 and 16 years) and their parents. Results indicated that adolescents who had higher appraisals of self-blame for marital conflict than their siblings also had more hostile parent-child relationships than their siblings. In addition, siblings' differential experiences of their family environments were associated with differences in siblings' externalizing, but not internalizing, problems. When considered together, differences in parent-child hostility, appraisals of self-blame and exposure to marital conflict predicted independent variance in differences in siblings' externalizing problems. Results are discussed in the context of using difference scores as a method to study siblings' unique experiences.

Including more than one child per family in research enables the identification of nonshared family effects (resulting in sibling differentiation) as well as shared family effects (resulting in sibling similarity). This paper describes a model used to disentangle shared from nonshared processes in links between parenting and children's behavior. The sample consisted of 172 families with two children aged four to eight years. Children and parents provided reports of parenting, and parents also reported on the children's behavior problems. According to mothers, parenting of children within families was largely similar, however the children's reports (via puppet interviews) indicated substantial differential treatment. In addition, links between parenting and behavior problems were largely nonshared—reinforcing the message from behavioral geneticists that parenting functions on a child-by-child rather than family-by-family basis. That is, rather than serving to make their children similar to one another, these findings support the idea that parent-child interactions lead to unique developmental trajectories for children.

The goal of the present study is to demonstrate the ways in which multilevel models can be applied to family research. We emphasize the conceptual issues in family research that this data analytic technique helps us to address. The family represents a nested, hierarchical structure in which multiple children from the same family are not independent from one another. Multilevel models can be used to accommodate the complex structure of families. We draw on two data structures to illustrate the utility of the analytic technique. The first data structure involves children nested within families. With this data structure, it is possible to: 1) differentiate between family-wide and child-specific processes, 2) examine the way in which adverse family environments may exacerbate differences across siblings and 3) examine the way in which individual child characteristics may modify the impact of the family environment. In addition to children nested within families, data structure # 2 involves a cross-classification, as each parent reports on the emotional problems of multiple children. This hierarchical, cross-classified model allows us to examine predictors of children's emotional problems, predictors of informant agreement on children's emotional problems and the extent of children's similarity with their siblings on emotional problems.

Models of sibling effects emphasize the importance of capturing rule breaking behavior in real time. To date, few studies have utilized electronic Ecological Momentary Assessment (e.EMA) as a methodology that allows siblings to record in real time and across everyday settings their patterns of interaction, including rule breaking behavior. Sixty adolescent sibling pairs drawn from a community-based family study completed 2 waves (baseline, 6 month follow-up) of an e.EMA diary. The diary was activated every 30-45 minutes for 6 consecutive days. Data were analyzed using Generalized Estimating Equations (GEE). Both same- and opposite-sex sibling pairs reported rule breaking behavior, particularly when both siblings were at a friends house. Brothers had the highest levels of self-reported rule break. Across all gender compositions, epochs of rule breaking behavior were associated with increases in anger, stress, and sadness. e.EMA is a promising method to study sibling interactions that complement other real time data capture strategies. Rule breaking behavior between adolescent siblings is particularly linked with spending time with mutual friends and with increases in negative emotions; these findings are congruent with current theoretical models of sibling effects on risk behaviors.

Siblings represent an important social influence on alcohol use in adolescence. That said, there is a need for studies that examine potential mechanisms by which siblings exert an influence on the likelihood of drinking in adolescence. This paper illustrates a method that utilizes videotaped interaction between sibling dyads along with a micro social coding system that captures rule break behavior between siblings. Sibling interaction was observed in sibling pairs participating in the Iowa Youth and Families Project (IYFP) at baseline; younger sibling use of alcohol was tracked for 3 additional annual assessments. Exposure to older sibling rule break at baseline was associated with later use of alcohol by younger siblings across the 3 annual assessments. Micro social methods hold promise for uncovering processes that underlie sibling contagion for alcohol use in adolescence.

The purpose of this study was to highlight the role of twin designs in understanding children's conversational interactions. Specifically, we (a) attempted to replicate the findings of genetic effects on children's conversational language use reported in DeThorne et al. (2008), and (b) examined whether the language used by examiners in their conversation with twins reflected differences in the children's genetic similarity. Behavioral genetic analyses included intraclass correlations and model fitting procedures applied to 514 same-sex twins (202 MZ, 294 DZ, 10 unknown zygosity) from the Western Reserve Reading Project (Petrill, Deater-Deckard, Thompson, DeThorne, & Schatschneider, 2006). Analyses focused on child and examiner measures of talkativeness, average utterance length, vocabulary diversity, and grammatical complexity from a fifteen-minute conversational exchange. Substantial genetic effects on children's conversational language measures replicated results from DeThorne et al. (2008) using an expanded sample. However, no familiality was reflected in the examiner language measures. Modest phenotypic correlations between child and examiner language measures suggested that differences in examiner language use may elicit differences in child language use, but evidence of evocative rGE in which genetic differences across children evoke differences in examiner language use, was not found. The discussion focuses on a comparison of findings to previous studies and implications for future research.

The current study used factor analysis to assess the degree to which personality characteristics derived from different theories signify the same latent personality constructs, and biometric modeling to understand the genetic and environmental structure of these constructs. Participants were drawn from the Twin and Offspring Study in Sweden (TOSS), and included 318 male twin pairs (129 Monozygotic, 189 Dizygotic) and 544 female twin pairs (258 Monozygotic, 286 Dizygotic). Personality characteristics were assessed via two self-report measures: the Temperament and Character Inventory and the Karolinksa Scales of Personality. Factor analyses identified three personality factors for male and female twins: anxiety, aggression, and sociability. In addition, self-regulation tendencies were integrated within each factor. Biometric analyses indicated that these latent factors were heritable (h² ranged from .52 to .67). Most personality characteristics that contributed to each latent factor also demonstrated unique genetic influences. Collectively, these findings underscore the complex nature of aggressiveness, anxiousness, and sociability, and indicate that scales that are conceptually similar may assess genetically distinct systems.