Evaluation of the Remote Intervention for Diet and Exercise (RIDE)
Evaluation of the Remote Intervention for Diet and Exercise (RIDE)
A large proportion of the adult population in the United States qualifies for weight loss
 treatment based on the NIH treatment recommendations, but traditional clinic-based weight
 loss treatments have a number of limitations. For example, access to healthcare facilities is
 limited among people living in rural communities and people of low socioeconomic status, yet
 a disproportionate number of these people would benefit from services. Internet-based weight
 loss interventions have been used to deliver services to these populations, but these
 "e-Health" interventions suffer from a number of limitations and produce only modest weight
 loss. The limitations associated with internet-based interventions include decreased use of
 the internet application over time; patients must logon to the internet to receive treatment
 recommendations, yet few patients regularly logon to the application and this negatively
 affects treatment outcome. An additional limitation is the quality of self-reported food
 intake, exercise, and body weight data that participants enter into the internet application
 or report to their online counselor. Self-reported data are associated with error and
 accurate data are needed to formulate effective treatment recommendations for participants.
 Lastly, most applications rely on asynchronous communications between the patient and the
 counselor, and patients do not always receive personalized treatment recommendations in a
 reasonable amount of time (1 to 3 days), which limits the extent to which the recommendations
 result in behavior change and weight loss.

 The purpose of the proposed pilot and feasibility project is to test the efficacy of the
 Remote Intervention for Diet and Exercise (RIDE) e-Health application at promoting weight
 loss compared to a control condition. The RIDE e-Health application addresses the limitations
 of internet-based interventions that are noted above. The application relies on novel
 technology to collect near real-time food intake, body weight, and exercise data from
 participants while they reside in their free-living environments. These data are transmitted
 to the researchers in near real-time: food intake data are collected and transmitted with
 camera and Bluetoothenabled cell phones using the Remote Food Photography method that was
 developed by this laboratory, body weight data is automatically transmitted daily from a
 bathroom scale using the same phones, and accelerometry is used to collect exercise data that
 is transmitted via the internet. These data are analyzed and personalized treatment
 recommendations are sent to the participant in a timely manner, e.g., every 1 to 3 days,
 using the cell phones. The RIDE e-Health application was developed based on learning and
 behavioral theory to maximize behavior change and weight loss. The findings of this study
 will have significant implications for the affordable delivery of effective weight management
 interventions to patients with limited access to health care.
The prevalence of overweight and obesity has increased significantly over the past four
 decades, resulting in 66% of the adult population in the United States (U.S.) being
 classified as overweight or obese (Wang, 2007).

 Moreover, there is an over-representation of overweight and obesity among rural and low
 socioeconomicstatus groups (Wang, 2007). Consequently, a large proportion of the adult
 population in the U.S. qualifies for weight loss treatment based on the NIH treatment
 recommendations (NHLBI, 1998). Nevertheless, traditional weight loss treatments have a number
 of limitations, including lifestyle change (diet, exercise, and behavior therapy), which is
 one of the first options for treating overweight and obesity. First, delivering clinical
 services to the number of individuals who qualify for treatment would overwhelm the
 healthcare system. Second, many people who qualify for and would benefit from treatment
 cannot obtain services due to financial limitations or geographic location. Third, lifestyle
 change requires a significant time-commitment on the part of the patient and a team of
 professionals, resulting in fairly costly treatment. Despite the cost, lifestyle change fails
 to consistently promote long-term weight loss maintenance and the amount of weight lost in
 the short-term frequently fails to meet patient expectations (Foster, 1997). Lastly,
 lifestyle change typically involves meeting with the patient regularly, e.g., fortnightly,
 and patients do not always receive timely feedback about modifying behaviors to achieve an
 energy deficit. This is a significant limitation since learning theory indicates that
 behavior change is fostered by receiving specific feedback that is temporally contiguous to
 the target behavior. Feedback that is delayed or unspecific is less effective at inducing
 behavior change (Schultz, 2006).

 The application of novel technology to health problems has improved some areas of health
 care. For example, telemedicine applications have been used to monitor the vital signs of
 victims of mass casualty disasters (Gao, 2005). Technology-based methodologies have also been
 applied to weight loss treatments in an effort to improve treatment efficacy and more
 affordably deliver services to individuals with limited health care access, such as people
 living in rural communities. To date, these "e-Health" applications have focused primarily on
 internet-based interventions, which have been found to produce only modest weight loss
 (Weinstein, 2006; Williamson, 2006).

 Our group has conducted many internet-based weight management studies (Williamson, 2006;
 Stewart, 2008; Williamson, 2008; Williamson, 2007) and we have identified limitations that
 negatively affect the efficacy of e-Health applications. First, patients must logon to the
 internet to report their progress and data (e.g., amount of food intake) and to receive
 treatment recommendations, yet few patients regularly logon to the internet application.
 Second, most e-Health applications rely on the participant to self-report food intake and
 exercise data, and these self-reported data are typically inaccurate (Schoeller, 1990).
 Consequently, the quality of the feedback that the participant receives is limited by the
 poor quality of the self-reported data. Third, no application has been able to: a) obtain
 accurate free-living food intake, exercise, and body weight data from participants in near
 real-time, b) evaluate these data as they are received, and c) provide specific feedback to
 participants in a reasonable amount of time (1 to 3 days).

 Based on learning theory, this ability would result in superior behavior change (Schultz,
 2006) and subsequent weight loss.

 The purpose of the proposed pilot and feasibility study is to test the efficacy of the Remote
 Intervention for Diet and Exercise (RIDE) e-Health application at promoting weight loss. The
 RIDE e-Health application addresses the limitations of internet-based interventions noted
 above. The application relies on novel technology to collect near real-time food intake, body
 weight, and exercise data from participants while they reside in their free-living
 environments. These data are transmitted to the researchers in near real-time: food intake
 data are collected and transmitted with camera and Bluetooth-enabled cell phones, body weight
 data are automatically transmitted from a bathroom scale using the same phones, and
 accelerometry is used to collect exercise data that is transmitted via the internet. These
 data are analyzed and personalized treatment recommendations are sent to the participant via
 the cell phone in a timely manner, e.g., every 1 to 3 days.
Inclusion Criteria:

 -  Body mass index (BMI) is > 25 kg/m2 and < 35 kg/m2.

 -  Willing to use cell phones provided by the PBRC or personal cell phones to take
 pictures of foods during the study and to receive messages from study personnel.

 -  Willing to wear an activity monitor on your shoe and to use the internet to send
 information as frequently as once daily.

 -  Willing to weigh on a scale provided by the PBRC as frequently as once per day

 -  Willing to accept random assignment to either the e-Health (RIDE group) or control
 group.

 -  Weight stable, defined as no greater than 4.4 lbs. (2 kg) weight change over the
 previous 60 days.

 Exclusion Criteria:

 -  Diagnosed with a chronic disease that affects body weight, appetite, or metabolism,
 namely diabetes, cardiovascular disease, cancer, and thyroid diseases or conditions.

 -  Currently in a weight loss program.

 -  Unable to engage in moderate intensity exercise.

 -  Unable to diet or exercise due to your medical history or current health status.

 -  Current use of prescriptions or over-the-counter medications or herbal products that
 affect appetite, body weight, or metabolism (e.g., weight loss medications such as
 sibutramine, antipsychotic medications such as olanzapine, ephedrine, and diuretics).

 -  Diagnosed with uncontrolled hypertension (high blood pressure), defined as systolic
 blood pressure >159 mmHg & diastolic blood pressure >99 mmHg.

 -  For females, current pregnancy, or plans to become pregnant in the duration of the
 study.