Social development is the sub area of developmental psychology that concerns the description of children’s development of relationships with others, their understanding of the meaning of their relationships with others, and their understanding of others’ behaviors, attitudes, and intentions. The examination of the social, emotional, biological, and cognitive processes that account for these developmental changes in social development are of interest as well. The historical shifts in the understanding of social development from Darwin to the present can be traced by an examination of the major theoretical and methodological advances that have characterized this area of inquiry. The history of social development is divided into five time periods—the beginning years (1880–1915), a period of conceptual clashes (1915–1940), a period of expansion (1940–1960), an era that saw the rise of contemporary themes (1960–1985), and the current period (from 1985 to 2019). Finally, future directions and unresolved issues are noted.
Ross D. Parke
Kendall Cotton Bronk, Elyse Postlewaite, Betsy Blackard, Jordan Boeder, and Hannah Lucas
Social development refers to the process through which individuals learn to get along with others. It encompasses the formation of friendships and romantic relationships as well as experiences of bullying and loneliness. Across the life span, cognitive development enables increasingly complex social interactions, and the most important contexts for social development expand. Early in life, family is the primary context for social development, but in adulthood the social world grows to include peers, colleagues, and others. Social development is critical for well-being. Research finds that the lasting social bonds that individuals form are perhaps the most important ingredient in a life well lived.
Cornelia Wrzus and Jenny Wagner
Over the entire life span, social relationships are essential ingredients of human life. Social relationships describe regular interactions with other people over a certain period and generally include a mental representation of the relationship and the relationship partner. Social relationships cover diverse types, such as those with family members, romantic partners, friends, colleagues, as well as with other unrelated people. In general, most of these relationships change in number, contact frequency, and relationship quality during adulthood and old age. For example, both the number of and contact with friends and other unrelated people generally decrease with advancing age, whereas the number of and contact with family members remain rather stable. Relatively little is known about longitudinal changes in the quality of relationships, apart from romantic relationships, because few longitudinal studies have tracked specific relationships. Some explanatory factors, which are discussed in the literature, are (a) motivational changes, (b) reduced time due to work and family demands during adulthood, and (c) resource constraints in older age. Future work on social relationships would benefit from increasingly applying dyadic and network approaches to include the perspective of relationship partners as well as from examining online and offline contact in social relationships, which has already proved important among younger adults.
Gizem Hülür and Elisa Weber
Lifespan development is embedded in multiple social systems and social relationships. Lifespan developmental and relationship researchers study individual codevelopment in various dyadic social relationships, such as dyads of parents and children or romantic partners. Dyadic data refers to types of data for which observations from both members of a dyad are available. The analysis of dyadic data requires the use of appropriate data-analytic methods that account for such interdependencies. The standard actor-partner interdependence model, the dyadic growth curve model, and the dyadic dual change score model can be used to analyze data from dyads. These models allow examination of questions related to dyadic associations such as whether individual differences in an outcome can be predicted by one’s own (actor effects) and the other dyad member’s (partner effects) level in another variable, correlated change between dyad members, and cross-lagged dyadic associations, that is, whether one dyad member’s change can be predicted by the previous levels of the other dyad member. The choice of a specific model should be guided by theoretical and conceptual considerations as well as by features of the data, such as the type of dyad, the number and spacing of observations, or distributional properties of variables.