Over the past 50 years, obesity has become a significant problem for an increasing number of Americans. The costs range from emotional distress to a wide range of health consequences, including increased risk of cardiovascular disease. Controlled studies over the past 30 years demonstrate that many traditional weight loss regimens are ineffective in producing lasting eating or exercise changes associated with healthier weights (Garner & Wooley, 1991). Systematic review of the studies yielding positive results indicates that lifestyle changes in eating behaviors, exercise patterns, and body image can produce lasting weight change. Foreyt and Goodrick (1994) identified the factors correlated with effective weight loss and maintenance as self-monitoring, goal setting, social support, and regular physical activity. They advocated that future treatment include enhancing self-esteem.
Advancing the implementation of these treatment components would improve outcome. Specifically, recent development of portable, electronic recording devices may facilitate the use of self-monitoring and treatment adherence. Personal Digital Assistants (PDA's) have been used increasingly by treating professionals (Keplar & Urbanski, 2003), but have yet to be utilized by treatment recipients.
This study proposes to examine the efficacy of PDA assisted self-monitoring in the interdisciplinary treatment of obesity. Four cohorts of 30 obese adults will be treated over 24 weeks with a sequenced combination of exercise promotion, dietary consultation, eating behavior change training, and enhancement of self-esteem and body image. Participants will be randomly assigned to groups using either paper-and-pencil or PDA assisted self-monitoring. The PDA's will also be programmed to provide reinforcement for data entry and consistent behavior changes. Measures of weight, body mass, self-esteem, activity, and emotional well-being will be utilized. To examine the effect of type of self-monitoring, results will be analyzed using MANOVAs with repeated measures. Effect size and correlations among the outcome measures will also be calculated.