SMART Weight Loss Management

NCT02997943 | Completed DMC

• 2 other identifiers: NIH NIDDK R01DK108678R01DK108678
• Study Type: interventional
• Target: 400
• Locations: 1 country
• Sites: 1

Brief Summary

The overall objective of this study is to use an innovative experimental approach, the SMART (Sequential Multiple Assignment Randomized Trial), to determine the best way to sequence the delivery of mHealth tools and traditional treatment components in a stepped program of obesity treatments. The SMART approach is a highly efficient strategy for identifying and constructing efficacious adaptive interventions: it accommodates sequential decision-making based on the participant's response to early weight loss treatment components. The proposed treatment package begins with the least expensive components, and for participants identified as treatment non-responders, provides sequential step-up of additional treatment components. By sequentially delivering treatment components based on participant response, SMART permits achievement of the target outcome, weight loss, with least resource consumption and participant burden.

Conditions

Weight Loss

Keywords

Obesity; Weight Loss; Diet; Physical Activity; Mobile Health

Outcome Measures

Primary Outcomes (1)

• Change in weight at 6 months

  Weight measured in the lab, taken without shoes, wearing light clothing on a calibrated beam balance scale

  baseline, 6 months

Other Outcomes (2)

• Change in weight at 12 months

  baseline, 12 months

• Cost effectiveness

  12 months

Study Arms (2)

Step 1: Optimal First Line Treatment

EXPERIMENTAL

Participants will first be randomized to an optimal first line treatment in order to compare APP vs. APP + coaching. Participants assigned to Step 1 treatment "APP" will receive a study-specific smartphone application. Participants assigned to Step 1 treatment "APP + coaching" will receive a study-specific smartphone application plus 12 weekly telephone coaching sessions.

Behavioral: Step 1 Treatment: APP; Behavioral: Step 1 Treatment: APP + Coaching

Step 2: Optimal Strategy to Address Nonresponse

EXPERIMENTAL

Beginning at week 2, participants who are identified as treatment non-responders will be re-randomized in order to compare two strategies to address non-response: a modest step-up or vigorous step-up treatment augmentation tactic. Step 2 treatment strategy: modest step-up will include provision of an additional mHealth intervention component (push notifications). Step 2 treatment strategy vigorous step-up will include provision of an additional mHealth intervention component (push notifications), plus a traditional weight loss intervention component (coaching, meal replacements). Participants will continue to receive their first line treatment.

Behavioral: Step 2 Treatment Strategy: Modest Step-up; Behavioral: Step 2 Treatment Strategy: Vigorous Step-up

Interventions

Step 1 Treatment: APP BEHAVIORAL

Participants will receive a smartphone app to track weight, dietary intake and physical activity, and a technology core consisting of web-based weekly lessons, wireless scale, and activity tracker. Participants will use their own smartphone to receive the study smartphone application.

Step 1: Optimal First Line Treatment

Step 1 Treatment: APP + Coaching BEHAVIORAL

Participants will receive a smartphone app to track weight, dietary intake and physical activity; a technology core consisting of web-based weekly lessons, wireless scale, and activity tracker; 12 weekly telephone coaching sessions. Participants will use their own smartphone to receive the study smartphone application.

Step 1: Optimal First Line Treatment

Step 2 Treatment Strategy: Modest Step-up BEHAVIORAL

In addition to first line treatment, participants identified as non-responders will be provided an additional mHealth intervention component (push notifications) for the remaining 12 weeks.

Step 2: Optimal Strategy to Address Nonresponse

Step 2 Treatment Strategy: Vigorous Step-up BEHAVIORAL

In addition to the first line treatment, participants identified as non-responders will be provided an additional mHealth intervention component (push notifications) plus a traditional weight loss intervention component (coaching, meal replacements).

Step 2: Optimal Strategy to Address Nonresponse

Eligibility Criteria

• Age: 18 Years - 60 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• through 60 years old
• BMI between 27 - 45 kg/m2
• \< 350 lbs
• Weight stable (no loss or gain \>25 lbs. for the past 6 months)
• Interested in losing weight and not enrolled in a formal weight loss program or taking medications or supplements that may cause weight change
• Own a Smartphone and be willing to install the SMART App
• Reside in the Chicago area for the duration of their participation (12 months)

You may not qualify if:

• Unstable medical conditions (uncontrolled hypertension, diabetes - uncontrolled or treated with insulin, uncontrolled hypothyroidism, unstable angina pectoris, transient ischemic attack, cancer undergoing active treatment, cerebrovascular accident or myocardial infarction within the past six months, or Crohn's disease)
• Pregnancy, lactation, or intended pregnancy
• Active suicidal ideation, anorexia, bulimia, binge eating disorder, current substance abuse or dependence (besides nicotine dependence)
• Require assistive device for mobility or current condition that may limit or prevent participation in moderate activity
• Use of pacemaker or other electrical implanted device
• History of bariatric (or LapBand) surgery, or considering or currently on a wait-list for bariatric or LapBand surgery
• May not live with a current or past SMART study participant

Sponsors & Collaborators

• Northwestern University: lead
• University of Michigan: collaborator
• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): collaborator

Study Sites (1)

Northwestern University

Chicago, Illinois, 60611, United States

Location

Related Publications (15)

• Pfammatter AF, Nahum-Shani I, DeZelar M, Scanlan L, McFadden HG, Siddique J, Hedeker D, Spring B. SMART: Study protocol for a sequential multiple assignment randomized controlled trial to optimize weight loss management. Contemp Clin Trials. 2019 Jul;82:36-45. doi: 10.1016/j.cct.2019.05.007. Epub 2019 May 23.

  PMID: 31129369 BACKGROUND

• Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, Murphy SA. Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Ann Behav Med. 2018 May 18;52(6):446-462. doi: 10.1007/s12160-016-9830-8.

  PMID: 27663578 BACKGROUND

• Spring B, Pfammatter A, Alshurafa N. First Steps Into the Brave New Transdiscipline of Mobile Health. JAMA Cardiol. 2017 Jan 1;2(1):76-78. doi: 10.1001/jamacardio.2016.4440. No abstract available.

  PMID: 27973672 BACKGROUND

• Spring B, Stump T, Penedo F, Pfammatter AF, Robinson JK. Toward a health-promoting system for cancer survivors: Patient and provider multiple behavior change. Health Psychol. 2019 Sep;38(9):840-850. doi: 10.1037/hea0000760.

  PMID: 31436465 BACKGROUND

• Walton A, Nahum-Shani I, Crosby L, Klasnja P, Murphy S. Optimizing Digital Integrated Care via Micro-Randomized Trials. Clin Pharmacol Ther. 2018 Jul;104(1):53-58. doi: 10.1002/cpt.1079. Epub 2018 Apr 19.

  PMID: 29604043 BACKGROUND

• Almirall D, Kasari C, McCaffrey DF, Nahum-Shani I. Developing Optimized Adaptive Interventions in Education. J Res Educ Eff. 2018;11(1):27-34. doi: 10.1080/19345747.2017.1407136. Epub 2017 Nov 29.

  PMID: 29552270 BACKGROUND

• Wagner B 3rd, Liu E, Shaw SD, Iakovlev G, Zhou L, Harrington C, Abowd G, Yoon C, Kumar S, Murphy S, Spring B, Nahum-Shani I. ewrapper: Operationalizing engagement strategies in mHealth. Proc ACM Int Conf Ubiquitous Comput. 2017 Sep;2017:790-798. doi: 10.1145/3123024.3125612.

  PMID: 29362728 BACKGROUND

• Welch WA, Spring B, Phillips SM, Siddique J. Moderating Effects of Weather-Related Factors on a Physical Activity Intervention. Am J Prev Med. 2018 May;54(5):e83-e89. doi: 10.1016/j.amepre.2018.01.025. Epub 2018 Mar 15.

  PMID: 29551330 BACKGROUND

• Booth JN 3rd, Allen NB, Calhoun D, Carson AP, Deng L, Goff DC Jr, Redden DT, Reis JP, Shimbo D, Shikany JM, Sidney S, Spring B, Lewis CE, Muntner P. Racial Differences in Maintaining Optimal Health Behaviors Into Middle Age. Am J Prev Med. 2019 Mar;56(3):368-375. doi: 10.1016/j.amepre.2018.10.020.

  PMID: 30777156 BACKGROUND

• Nahum-Shani I, Ertefaie A, Lu XL, Lynch KG, McKay JR, Oslin DW, Almirall D. A SMART data analysis method for constructing adaptive treatment strategies for substance use disorders. Addiction. 2017 May;112(5):901-909. doi: 10.1111/add.13743. Epub 2017 Feb 18.

  PMID: 28029718 BACKGROUND

• Lu X, Nahum-Shani I, Kasari C, Lynch KG, Oslin DW, Pelham WE, Fabiano G, Almirall D. Comparing dynamic treatment regimes using repeated-measures outcomes: modeling considerations in SMART studies. Stat Med. 2016 May 10;35(10):1595-615. doi: 10.1002/sim.6819. Epub 2015 Dec 6.

  PMID: 26638988 BACKGROUND

• Spring B, Champion KE, Acabchuk R, Hennessy EA. Self-regulatory behaviour change techniques in interventions to promote healthy eating, physical activity, or weight loss: a meta-review. Health Psychol Rev. 2021 Dec;15(4):508-539. doi: 10.1080/17437199.2020.1721310. Epub 2020 Feb 17.

  PMID: 31973666 BACKGROUND

• Ertefaie A, Wu T, Lynch KG, Nahum-Shani I. Identifying a set that contains the best dynamic treatment regimes. Biostatistics. 2016 Jan;17(1):135-48. doi: 10.1093/biostatistics/kxv025. Epub 2015 Aug 3.

  PMID: 26243172 BACKGROUND

• Spring B, Pfammatter AF, Scanlan L, Daly E, Reading J, Battalio S, McFadden HG, Hedeker D, Siddique J, Nahum-Shani I. An Adaptive Behavioral Intervention for Weight Loss Management: A Randomized Clinical Trial. JAMA. 2024 Jul 2;332(1):21-30. doi: 10.1001/jama.2024.0821.

  PMID: 38744428 DERIVED

• Metzendorf MI, Wieland LS, Richter B. Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity. Cochrane Database Syst Rev. 2024 Feb 20;2(2):CD013591. doi: 10.1002/14651858.CD013591.pub2.

  PMID: 38375882 DERIVED

MeSH Terms

Conditions

Weight Loss; Obesity; Motor Activity

Condition Hierarchy (Ancestors)

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

Study Officials

• Bonnie Spring, PhD

  Northwestern University

  PRINCIPAL INVESTIGATOR

• Inbal Nahum-Shani, PhD

  University of Michigan

  PRINCIPAL INVESTIGATOR

Study Design

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

Study Record Dates

• First Submitted: December 5, 2016
• First Posted: December 20, 2016
• Study Start: June 19, 2017
• Primary Completion: September 17, 2020
• Study Completion: March 18, 2021
• Last Updated: May 18, 2021

Record last verified: 2021-05

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)