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

NCT00883350 | Completed Results DMC

• 2 other identifiers: PBRC 280231R03DK083533
• Study Type: interventional
• Target: 40
• Locations: 1 country
• Sites: 1

Brief 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

Keywords

Body weight changes; Overweight; Obesity

Outcome Measures

Primary Outcomes (1)

• Percent Change in Body Weight From Baseline to 12 Weeks

  weight loss calculated as a percentage of initial weight measured at baseline \[((weight at 12 weeks-weight at baseline)/weight at baseline) x 100\]

  12 weeks

Study Arms (2)

RIDE

EXPERIMENTAL

Participants randomized to utilize the RIDE e-health application for the duration of the 12 week intervention.

Behavioral: RIDE e-health application

Control

NO INTERVENTION

Participants assigned to the Health-Ed (control) group will receive health information via the cell phone throughout the 84-day study. We have generated numerous health information tips for other studies on a variety of topics, including stress management, the benefits of eating fruits and vegetables, etc. \[6-9\]. These lessons will be modified for delivery via cell phone. We have found that participants assigned to these health information control groups report being satisfied with the information and their assignment. Importantly, our data also indicate that such health information results in very little behavior change or weight loss, e.g., \[6\].

Interventions

RIDE e-health application BEHAVIORAL

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.

RIDE

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Pennington Biomedical Research Center: lead
• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): collaborator

Study Sites (1)

Pennington Biomedical Research Center

Baton Rouge, Louisiana, 70808, United States

Location

Related Publications (13)

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  PMID: 17510091 BACKGROUND

• Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. Obes Res. 1998 Sep;6 Suppl 2:51S-209S. No abstract available.

  PMID: 9813653 BACKGROUND

• Foster GD, Wadden TA, Vogt RA, Brewer G. What is a reasonable weight loss? Patients' expectations and evaluations of obesity treatment outcomes. J Consult Clin Psychol. 1997 Feb;65(1):79-85. doi: 10.1037//0022-006x.65.1.79.

  PMID: 9103737 BACKGROUND

• Schultz W. Behavioral theories and the neurophysiology of reward. Annu Rev Psychol. 2006;57:87-115. doi: 10.1146/annurev.psych.56.091103.070229.

  PMID: 16318590 BACKGROUND

• Gao T, Greenspan D, Welsh M, Juang R, Alm A. Vital signs monitoring and patient tracking over a wireless network. Conf Proc IEEE Eng Med Biol Soc. 2005;2006:102-5. doi: 10.1109/IEMBS.2005.1616352.

  PMID: 17282121 BACKGROUND

• Weinstein PK. A review of weight loss programs delivered via the Internet. J Cardiovasc Nurs. 2006 Jul-Aug;21(4):251-8; quiz 259-60. doi: 10.1097/00005082-200607000-00003.

  PMID: 16823276 BACKGROUND

• Williamson DA, Walden HM, White MA, York-Crowe E, Newton RL Jr, Alfonso A, Gordon S, Ryan D. Two-year internet-based randomized controlled trial for weight loss in African-American girls. Obesity (Silver Spring). 2006 Jul;14(7):1231-43. doi: 10.1038/oby.2006.140.

  PMID: 16899804 BACKGROUND

• Stewart T, May S, Allen HR, Bathalon CG, Lavergne G, Sigrist L, Ryan D, Williamson DA. Development of an internet/population-based weight management program for the U.S. Army. J Diabetes Sci Technol. 2008 Jan;2(1):116-26. doi: 10.1177/193229680800200117.

  PMID: 19885186 BACKGROUND

• Williamson DA, Champagne CM, Harsha D, Han H, Martin CK, Newton R Jr, Stewart TM, Ryan DH. Louisiana (LA) Health: design and methods for a childhood obesity prevention program in rural schools. Contemp Clin Trials. 2008 Sep;29(5):783-95. doi: 10.1016/j.cct.2008.03.004. Epub 2008 Mar 26.

  PMID: 18448393 BACKGROUND

• Williamson DA, Copeland AL, Anton SD, Champagne C, Han H, Lewis L, Martin C, Newton RL Jr, Sothern M, Stewart T, Ryan D. Wise Mind project: a school-based environmental approach for preventing weight gain in children. Obesity (Silver Spring). 2007 Apr;15(4):906-17. doi: 10.1038/oby.2007.597.

  PMID: 17426326 BACKGROUND

• Schoeller DA. How accurate is self-reported dietary energy intake? Nutr Rev. 1990 Oct;48(10):373-9. doi: 10.1111/j.1753-4887.1990.tb02882.x.

  PMID: 2082216 BACKGROUND

• Martin CK, Han H, Coulon SM, Allen HR, Champagne CM, Anton SD. A novel method to remotely measure food intake of free-living individuals in real time: the remote food photography method. Br J Nutr. 2009 Feb;101(3):446-56. doi: 10.1017/S0007114508027438. Epub 2008 Jul 11.

  PMID: 18616837 BACKGROUND

• Martin CK, Miller AC, Thomas DM, Champagne CM, Han H, Church T. Efficacy of SmartLoss, a smartphone-based weight loss intervention: results from a randomized controlled trial. Obesity (Silver Spring). 2015 May;23(5):935-42. doi: 10.1002/oby.21063.

  PMID: 25919921 DERIVED

MeSH Terms

Conditions

Overweight; Obesity; Body Weight Changes

Condition Hierarchy (Ancestors)

Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Results Point of Contact

• Title: Corby Martin
• Organization: Pennington Biomedical Research Center

corby.martin@pbrc.edu

763-2585

Study Officials

• Corby K Martin, PhD

  Pennington Biomedical Research Center

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: INVESTIGATOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: April 15, 2009
• First Posted: April 17, 2009
• Study Start: May 1, 2009
• Primary Completion: January 1, 2011
• Study Completion: January 1, 2011
• Last Updated: December 3, 2024
• Results First Posted: December 3, 2024

Record last verified: 2024-11

Locations

US (1)