Medical Advice and Diabetes Self-Management Reported by Mexican-American, Black- and White-Non-Hispanic Adults Across the United States

Background: Diabetes has reached epidemic proportions in the United States, particularly among minorities, and if improperly managed can lead to medical complications and death. Healthcare providers play vital roles in communicating standards of care, which include guidance on diabetes self-management. The background of the client may play a role in the patient-provider communication process. The aim of this study was to determine the association between medical advice and diabetes self care management behaviors for a nationally representative sample of adults with diabetes. Moreover, we sought to establish whether or not race/ethnicity was a modifier for reported medical advice received and diabetes self-management behaviors. Methods: We analyzed data from 654 adults aged 21 years and over with diagnosed diabetes [130 MexicanAmericans; 224 Black non-Hispanics; and, 300 White non-Hispanics] and an additional 161 with ‘undiagnosed diabetes’ [N = 815(171 MA, 281 BNH and 364 WNH)] who participated in the National Health and Nutrition Examination Survey (NHANES) 2007-2008. Logistic regression models were used to evaluate whether medical advice to engage in particular self-management behaviors (reduce fat or calories, increase physical activity or exercise, and control or lose weight) predicted actually engaging in the particular behavior and whether the impact of medical advice on engaging in the behavior differed by race/ethnicity. Additional analyses examined whether these relationships were maintained when other factors potentially related to engaging in diabetes self management such as participants’ diabetes education, sociodemographics and physical characteristics were controlled. Sample weights were used to account for the complex sample design. Results: Although medical advice to the patient is considered a standard of care for diabetes, approximately onethird of the sample reported not receiving dietary, weight management, or physical activity self-management advice. Participants who reported being given medical advice for each specific diabetes self-management behaviors were 4-8 times more likely to report performing the corresponding behaviors, independent of race. These results supported the ecological model with certain caveats. Conclusions: Providing standard medical advice appears to lead to diabetes self-management behaviors as reported by adults across the United States. Moreover, it does not appear that race/ethnicity influenced reporting performance of the standard diabetes self-management behavior. Longitudinal studies evaluating patient-provider communication, medical advice and diabetes self-management behaviors are needed to clarify our findings.

Psychological and Cognitive Factors that Influence Post-Exercise Energy Intake in Normal Weight and Overweight Sedentary Males

The primary purpose of this study was to evaluate the effects of a single bout of moderate-intensity exercise on acute (ad libitum lunch) post-exercise energy intake (PE-EI) and 12-hour energy intake in normal-weight and overweight sedentary males. Accuracy in estimating energy intake (EI) and energy expenditure (EE), solid vs. liquid carbohydrate intake, mood, and perceived hunger were also assessed. The study consisted of two conditions, exercise and rest, with each subject participating in each condition, in a counterbalanced-crossover design on two days. The participants were randomly assigned to either the exercise or resting (seated) control condition on the first day of the experiment, and then the condition was reversed on the second day. Exercise consisted of walking on a treadmill at moderate-intensity for 60 minutes. Eighty males, mean age 30+8 years were categorized into five groups according to weight status (overweight/normal-weight), dietary restraint status (high/low), and dieting status (yes/no). The main effects of condition and group, and the interaction were not significant for acute (lunch) or 12-hour PE-EI. Overall, participants estimated EE for exercise at 46% higher than actual exercise EE, and they estimated EE for rest by 45% lower than actual resting EE. Participants significantly underestimated EI at lunch on both the exercise and rest days by 43% and 44%, respectively. Participants with high restraint were significantly better at estimating EE on the exercise day, and better at estimating EI on the rest day. Mood, perceived hunger, and solid vs. liquid carbohydrate intake were not influenced by dietary restraint, weight, or dieting status. In conclusion, a single bout of moderate-intensity exercise did not influence PE-EI in sedentary males in reference to dietary restraint, weight, and dieting status. Results also suggested that among sedentary males, there is a general inability to accurately estimate calories for moderate-intensity physical activity and EI. Inaccurate estimates of EE and EI have the potential to influence how males manage their weight.

Clinician perceptions of factors that enhance patient compliance in physical therapy

The purpose of this study was to determine physical therapists utilization of methods to increase compliance with home exercise programs, and to determine their perceptions of barriers patients have to completing exercise programs. The secondary purpose of this study was to describe the association, if any, between therapists' age, participation in exercise and/or lifestyle changes and the utilization of methods to increase exercise compliance. A sample of 73 physical therapists attending the American Physical Therapy Association Combined Sections Meeting were surveyed for this study. This study found that barriers listed by patients were similar to those found in the literature. This study also found that a significant association, p = .015, existed between therapists engaging in behavioral changes and use of lifestyle activities.

Statistical Dialog Management for Health Interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.