INTRODUCTION: Overweight and obesity is a common diagnosis that affects approximately two in three adults in the US. This disease results in enormous economic costs to society and large personal costs to individuals and families. There is a strong association between overweight and obesity and poor health-related quality of life (HRQOL). Research findings indicate that as many as 52% of obese persons experience high levels of mental or physical disability. According to the Rural Healthy People Report, 2020 (RHP2020); access to quality health services is the leading priority for providers in rural communities. Diabetes, mental health, nutrition and weight status, physical activity and health, older adults, and community health education were all identified as top 10 priorities in the RHP2020 report. With the understanding that obesity is a multi-faceted constellation of causative factors, the researcher included an intensive behavioral therapy (IBT) component using a distant technology-based platform. Prior studies indicate this approach results in small but significant reductions in BMI, anxiety and depression, and improves HRQOL. By addressing these barriers in rural communities via technology the researchers wanted to compare results to those of traditional face-to-face studies employing IBT as a component of weight loss management.
DESIGN: An experimental design with a treatment group and a control group measured pre- and post- intervention.
SUBJECTS: Participants who met the inclusion criteria for inclusion in a monitored weight loss management program (n = 54).
METHODS: All participants were screened using teleconferencing technology prior to inclusion in the study. The study period was 12 weeks and the treatment consisted of decision making skills regarding, healthy eating choices and beginning or increasing exercise to a moderate activity level at least five days per week. Additional information was obtained regarding participant’s willingness to engage in cognitive skill development related to mindful food consumption. The primary outcomes of interest were weight change (BMI), and measures on the Impact of Weight on Quality of Life Scale (IWQOL).
RESULTS: There were statistically significant changes from pre- to post- treatment in BMI and two measures of the IWQOL in the intervention group. However, three measures on the IWQOL scale did not indicate a positive treatment outcome. Data analysis was conducted using the intention-to-treat principle as few participants dropped out as this assumes stability of findings from pretreatment. A conservative power estimation was calculated and yielded an expected standardized mean difference of d=0.50. With conventional levels of confidence (p<0.05) a sample of 64 would be required. Since enrollment did not reach 64 participants the study was underpowered. Data were analyzed using ANOVA and MANOVA to detect interaction effects in the 2X2 design for continuous variables, and x2 for categorical variables.
CONCLUSIONS: Findings suggest that an internet-based cognitive behavioral intervention can serve as a complement with local primary care providers for individuals who are obese or overweight and who prefer this treatment and have difficulties accessing obesity-training clinical specialists in their local communities. Limitations to this study include a lack of long-term follow-up data, and the number of outcome measures included which may have influenced findings related to benefit from treatment. Results should be replicated by other researchers and long-term benefits investigated.