This revised proposal from James P. McHale seeks an Independent Scientist Award (KO2) from the NICHD. The overall aim of the proposed RCA is to free the candidate from teaching and administrative duties to devote nearly full time to continue and develop further his programmatic research on early coparenting and infant development. This work has reflected an important shift in socialization theory, which prior to the mid 1990s neglected family group level organization. However, recent work documents that coparenting processes take shape during early family formation, show marked stability over time, and show prospective relations with children's social and emotional adjustment. Yet little is known about determinants of coparenting and family level dynamics, including infant effects on the developing coparental system. And despite replicated research documenting that coparental antagonism and lack of mutuality lead to child problems with impulse control, aggression, and anxiety, intervention studies capitalizing on this knowledge are not yet on the horizon. This RCA would provide a context for 5 years of programmatic work nested within an ongoing research agenda on the evolution and role of coparenting alliances in promoting infant and child adjustment and mental health. Work includes a currently active RO1 study of the transition to coparenthood and a second recently completed study of coparenting from infancy to toddlerhood.The RCA would enhance pursuit of a comprehensive model documenting when coparental dissonance is growth promoting and when it is growth stultifying for children. It would also permit the candidate to develop new evaluation and analytic skills to address data in promising new ways that expand conceptualizations of infant contributions to early family dynamics. Institutional environment is strongly supportive. Career development activities, outlined in greater detail in this resubmission, include: intensive learning about microanalysis and about translational research with leading experts, and coursework in longitudinal analysis and advanced statistical modeling.
