Predictors and Effects of Participation in Peer Support: A Prospective Structural Equation Modeling Analysis.

BACKGROUND: Peer support provides varied health benefits, but how it achieves these benefits is not well understood. PURPOSE: Examine a) predictors of participation in peer support interventions for diabetes management, and b) relationship between participation and glycemic control. METHODS: Seven peer support interventions funded through Peers for Progress provided pre/post data on 1,746 participants' glycemic control (hemoglobin A1c), contacts with peer supporters as an indicator of participation, health literacy, availability/satisfaction with support for diabetes management from family and clinical team, quality of life (EQ-Index), diabetes distress, depression (PHQ-8), BMI, gender, age, education, and years with diabetes. RESULTS: Structural equation modeling indicated a) lower levels of available support for diabetes management, higher depression scores, and older age predicted more contacts with peer supporters, and b) more contacts predicted lower levels of final HbA1c as did lower baseline levels of BMI and diabetes distress and fewer years living with diabetes. Parallel effects of contacts on HbA1c, although not statistically significant, were observed among those with baseline HbA1c values > 7.5% or > 9%. Additionally, no, low, moderate, and high contacts showed a significant linear, dose-response relationship with final HbA1c. Baseline and covariate-adjusted, final HbA1c was 8.18% versus 7.86% for those with no versus high contacts. CONCLUSIONS: Peer support reached/benefitted those at greater disadvantage. Less social support for dealing with diabetes and higher PHQ-8 scores predicted greater participation in peer support. Participation in turn predicted lower HbA1c across levels of baseline HbA1c, and in a dose-response relationship across levels of participation.

An experimental evaluation of a group- versus computer-based intervention to improve food portion size estimation skills.

The ability to accurately estimate and measure food portion sizes is important for preventing and treating obesity. This study describes the development, implementation and evaluation of a group- versus computer-based intervention to improve food portion estimation abilities using real food and food models. A convenience sample of 76 women was randomly assigned to one of three conditions: computer training, group training or a waitlist control condition. Assessments at baseline and 2 weeks post-intervention included portion size testing using real foods and food models, self-efficacy for judging portion sizes and using measuring utensils, and knowledge of portion information. At baseline, greater estimation errors were observed for amorphous foods. No group by time interaction was observed on estimation of real foods; however, both the computer and group training resulted in significant improvements in estimating the size of food models, greater self-efficacy for judging portion sizes and more accurate knowledge of portion information compared with the control condition. Process measures indicated that the group training was deemed more helpful and more personally relevant to the participants.