Examining inter-family differences in intra-family (parent–adolescent) dynamics using grid-sequence analysis.
Year: 2017
Type: article
Abstract: Family systems theorists have forwarded a set of theoretical principles meant to guide family scientists and practitioners in their conceptualization of patterns of family interaction-intra-family dynamics-that, over time, give rise to family and individual dysfunction and/or adaptation. In this article, we present an analytic approach that merges state space grid methods adapted from the dynamic systems literature with sequence analysis methods adapted from molecular biology into a "grid-sequence" method for studying inter-family differences in intra-family dynamics. Using dyadic data from 86 parent-adolescent dyads who provided up to 21 daily reports about connectedness, we illustrate how grid-sequence analysis can be used to identify a typology of intrafamily dynamics and to inform theory about how specific types of intrafamily dynamics contribute to adolescent behavior problems and family members' mental health. Methodologically, grid-sequence analysis extends the toolbox of techniques for analysis of family experience sampling and daily diary data. Substantively, we identify patterns of family level microdynamics that may serve as new markers of risk/protective factors and potential points for intervention in families. (PsycINFO Database Record
Source: Journal of Family Psychology
DOI: 10.1037/fam0000371
Authors: Miriam Brinberg, Gregory M. Fosco, Nilam Ram
Institution: Pennsylvania State University
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Awards: Penn State Clinical and Translational Science Institute, Penn State Biomedical Big Data to Knowledge (B2D2K) Training Program, Toward a Unifying Model of Self-Regulation and its Development, Population Research Institute, G9000228955, Penn State Clinical and Translational Science Institute, The Population Research Institute
OpenAlex ID: W2784051439
