Evaluation of the Remote Intervention for Diet and Exercise (RIDE)

Summary

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.

Conditions

• Overweight
• Obesity

Interventions

BEHAVIORAL

RIDE e-health application

The RIDE e-Health application utilizes the latest technology to obtain near real-time food intake, body weight, and exercise data from participants living in their natural environment. The application also provides personalized and timely feedback and treatment recommendations based on participants' data. The application relies on the Remote Food Photography Method (Martin, 2009), which was developed by our research team, to collect freeliving food intake data that is transmitted to the researchers in near realtime using a camera and Bluetooth-enabled cell phone. A scale is used to collect daily body weight data from participants and these data are automatically transmitted to the researchers via the same cell phone. The e-Health application collects exercise data from participants and these data are delivered to the researchers via the internet; personalized feedback and treatment recommendations are sent to the participant every 1 to 3 days via the cell phone.

Sponsors & Collaborators

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

  collaborator NIH

• Pennington Biomedical Research Center

  lead OTHER

Principal Investigators

• Corby K Martin, PhD · Pennington Biomedical Research Center

Study Design

Allocation

RANDOMIZED

Purpose

TREATMENT

Masking

SINGLE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

65 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2009-05-31

Primary Completion

2011-01-31

Completion

2011-01-31

Countries

• United States

Study Locations