TRANSFORM- Theoretical Model


TRANSFORM operates under the overarching theoretical and methodological perspective of developmental psychopathology. This perspective integrates Bronfenbrenner’s (1979) ecological approach to understanding environmental contexts, organizational perspectives on development (Cicchetti & Toth, 2015; Cicchetti & Valentino, 2006), Belsky’s (1980) nested, interactive systems of influence on parenting, and Cicchetti and Rizley’s (1981) model of transactions among risk and protective factors. Equifinality and multifinality in developmental processes are seen as central for understanding normative and atypical development. From its inception, the developmental psychopathology framework has proffered the mutually- informative transactions that can occur between basic and applied research, with the ultimate goal of informing the provision of prevention and intervention initiatives. Within this framework, preventive interventions can provide important information on developmental processes in order to examine those factors that are modifiable with treatment. Thus, basic, as well as applied research can shape our understanding of etiological factors, change mechanisms, and sequelae of child maltreatment.


A multi-level analytical approach incorporates multiple influences, including psychosocial as well as neurobiological processes that impact development. Increasingly, the role of the stress response system through the hypothalamic-pituitary-adrenal (HPA) axis, as well as genetic and epigenetic factors, are being examined in high-risk populations to better understand its developmental impact and the opportunity it provides to assess treatment effects. Dysregulations in HPA axis activity and gene by environment interactions have been documented in our corpus of publications on maltreated children. Although advances in science and technology have permitted more detailed examination of processes impacting the development of maltreated children, they also have uncovered variability and transactional challenges for which simplistic solutions have proven inadequate.