Improving Self-Monitoring in Weight Loss With Technology

NCT ID: NCT00277771

Last Updated: 2015-07-07

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 210 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2006-02-28
• Study Completion Date: 2010-06-30

Brief Summary

We propose to conduct a randomized study of standard behavioral weight-loss treatment to test if using an electronic diary with or without tailored feedback will improve adherence to self-monitoring and subsequently improve weight loss. Subjects will be randomly assigned to different methods to self-monitor food and exercise habits: (1) use of the traditional paper diary , (2) use of a personal digital assistant (PDA), or (3) use of a personal digital assistant that also provides daily feedback.

Detailed Description

The prevalence of obesity, a major chronic health problem that is an independent risk factor for coronary heart disease (CHD), continues to increase at an alarming rate. Although weight control research has significantly improved short-term treatment success, long-term weight loss maintenance has lagged behind. Research has demonstrated a consistent relationship between self-monitoring eating and physical activity habits and success in weight loss as well as in maintenance of weight loss. However, the methods primarily used for self-monitoring continue to be the paper diary (PD), which is time consuming and burdensome. Moreover, PDs do not permit immediate external feedback to support and motivate the individual. Emerging technologies could improve self-monitoring and weight loss treatment. However, the use of these technological advances, such as a personal digital assistant (PDA), has not been studied in weight loss treatment. The primary aim of this behavioral weight loss treatment study is to determine if self-monitoring of daily eating and physical activity habits using a PDA, with or without a tailored feedback intervention, is superior to using a PD in terms of promoting and maintaining short- and long-term weight loss. Secondary aims include comparing the effect of treatment group assignment on adherence to self-monitoring and on risk factors for CHD (lipids, glucose, insulin, C-reactive protein). We propose to enroll 198 subjects and randomize them to one of three treatment groups that will use different methods to self-monitor eating and physical activity habits: (1) use of the traditional PD with delayed written feedback, (2) use of a PDA with limited feedback on daily targets, or (3) use of a PDA with limited feedback on daily targets plus receive daily, subject-tailored feedback messages via the PDA. The proposed study includes prolonged (24 months) supervision of self-management with three important components: self-monitoring, feedback, and ongoing contact. Subjects will complete assessments at baseline, 6, 12, 18, and 24 months. This innovative study will provide information on the efficacy of combining technological advances with proven behavioral strategies.

Conditions

Obesity; Overweight

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: FACTORIAL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Interventions

Standard behavioral treatment (SBT) for weight loss

Participants attend group sessions where they learn about healthy eating and exercise. They are asked to self-monitor all calories consumed (food and drink) and all calories expended through exercise. Standard paper diaries are used for self-monitoring.

Intervention Type: BEHAVIORAL

SBT for weight loss using a PDA

Participants attend group sessions where they learn about healthy eating and exercise. They are asked to self-monitor all calories consumed (food and drink) and all calories expended through exercise. Personal Digital Assistants (PDAs) are used for self-monitoring.

Intervention Type: BEHAVIORAL

SBT for weight loss using a PDA with feedback messages

Participants attend group sessions where they learn about healthy eating and exercise. They are asked to self-monitor all calories consumed (food and drink) and all calories expended through exercise. Personal Digital Assistants with a customized feedback program are used for self-monitoring.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

1. age 18 to 59 years

2. BMI ≥ 27 and ≤ 43

3. willing to be randomized to one of the three treatment conditions

4. successful completion of screening

• Note that although residing in Western Pennsylvania is not an explicit eligibility criterion, participants are asked to travel to the University of Pittsburgh frequently.

Exclusion Criteria

1. presence of an eating disorder

2. current serious illness or unstable condition requiring physician-supervised diet and exercise including a glucose level above 125 at baseline

3. physical limitations precluding ability to exercise

4. pregnant or planning to become pregnant in the next 24 mos

5. under current treatment for a psychological disorder

6. reported alcohol intake of 4 drinks/day or more

7. current or recent (past 6 mos) participation in a weight-loss program or use of weight-loss medication

8. planning an extended vacation, absence, or relocation within the next 24 mos

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 59 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

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

NIH

Sponsor Role: collaborator

Lora Burke

OTHER

Sponsor Role: lead

Responsible Party

Lora Burke

Professor of Nursing and Epidemiology

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

Lora E. Burke, PhD, MPH

Role: PRINCIPAL_INVESTIGATOR

University of Pittsburgh

Locations

University of Pittsburgh School of Nursing

Pittsburgh, Pennsylvania, United States

Countries

United States

References

Goode RW, Ye L, Sereika SM, Zheng Y, Mattos M, Acharya SD, Ewing LJ, Danford C, Hu L, Imes CC, Chasens E, Osier N, Mancino J, Burke LE. Socio-demographic, anthropometric, and psychosocial predictors of attrition across behavioral weight-loss trials. Eat Behav. 2016 Jan;20:27-33. doi: 10.1016/j.eatbeh.2015.11.009. Epub 2015 Nov 14.

Reference Type: DERIVED

PMID: 26609668 (View on PubMed)

Turk MW, Elci OU, Wang J, Sereika SM, Ewing LJ, Acharya SD, Glanz K, Burke LE. Self-monitoring as a mediator of weight loss in the SMART randomized clinical trial. Int J Behav Med. 2013 Dec;20(4):556-61. doi: 10.1007/s12529-012-9259-9.

Reference Type: DERIVED

PMID: 22936524 (View on PubMed)

Burke LE, Styn MA, Sereika SM, Conroy MB, Ye L, Glanz K, Sevick MA, Ewing LJ. Using mHealth technology to enhance self-monitoring for weight loss: a randomized trial. Am J Prev Med. 2012 Jul;43(1):20-6. doi: 10.1016/j.amepre.2012.03.016.

Reference Type: DERIVED

PMID: 22704741 (View on PubMed)

Other Identifiers

1R01DK071817-01

Identifier Type: NIH

Identifier Source: secondary_id

View Link

0507098

Identifier Type: -

Identifier Source: org_study_id