The Diabetes Control and Complications Trial (DCCT) proved that Intensive Therapy (IT) for insulin-dependent diabetes mellitus targeting near-normoglycemia delays the onset and slows the progression of long-term complications. The DCCT enrolled only highly motivated adults and adolescents and it is unclear if this success can be duplicated with a broader sample of youth. The cost of IT impedes its dissemination; strategies of delivering IT more efficiently are needed to maximize the DCCT's public health impact. At each DCCT assessment, about 25 percent of adolescents in the Conventional Therapy group had HbA1c levels less than 8.0 percent, while a similar number of IT patients did not. Thus, some patients may approach normoglycemia with CT and others may not even with IT. Specification of factors differentiating these patients could optimize resource allocation for clinical translation of the DCCT and maximize treatment benefits from either approach. This proposal builds on the team's clinical experience, previous studies of psychological aspects of IDDM in youth and their collaboration on an NIH-funded project. The application is based on a conceptual model which asserts that developmentally appropriate self care autonomy and IDDM self-management competence mediate the influence of demographic factors, family function and psychological stress on diabetic control. Families with moderate self management competence are hypothesized to accrue the most benefit from IT. A sample of 160 youth with IDDM and their parents will be randomized to either IT or to continue in their usual care (UC; intensified conventional therapy). Baseline assessment will include pertinent demographic, psychological and family factors. Evaluations will occur quarterly for 18 months, including assessment of IDDM self care autonomy, treatment adherence, family use of blood glucose data, family interactions with health care providers, affective adjustment to IDDM and health status. Extensive measures are proposed to ensure that UC patients are exposed to no added risks due to study participation. Prediction of UC and IT treatment response will be analyzed using flexible individual growth modeling methods. The study will specify behavioral and psychological factors that mediate IT and UC response, promoting the development of interventions targeting these mechanisms and of well validated protocols for the selection of patients for IT.
