Opt-IN: Optimization of Remotely Delivered Intensive Lifestyle Treatment for Obesity

Weight Loss Clinical Trial

— Opt-IN  

Official title:

Opt-IN: Optimization of Remotely Delivered Intensive Lifestyle Treatment for Obesity

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT01814072
• Other study ID #: NIH NIDDK R01DK097364-01
• Secondary ID: R01DK097364-01
• Status: Completed
• Phase: Phase 2/Phase 3
• Start date: September 2013
• Est. completion date: September 20, 2017

Study information

• Verified date: January 2023
• Source: Northwestern University
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The overall objective of the proposed research is to use an innovative methodological framework, the Multiphase Optimization Strategy (MOST), to design, for the first time, an optimized, scalable version of a technology-supported intensive lifestyle intervention (INLI) for obesity. MOST involves highly efficient randomized experimentation to assess the effects of individual treatment components, and thereby identify which components and component levels make important contributions to the overall program effect on weight loss. This information then guides assembly of an optimized treatment package that achieves target outcomes with least resource consumption and participant burden. Because the intervention strategies being tested minimize in-person coaching and leverage technology that participants already own, the new optimized intervention, to be called Opt-IN, will be more scalable than traditional INLIs. Opt-IN will thus enjoy greatly increased reach, and enable significant progress in the fight against obesity.

Description:

The goal of the proposed study is to determine the optimal composition of a technology supported intervention for obesity that minimizes expense and burden to participants, while achieving 6 month weight loss outcomes comparable or superior to those achieved by the current full cost, full burden form of INLIs. All intervention components to be examined were selected based on the Opt-IN model's prediction that they enhance behavioral adherence to weight regulation via the designated pathways. The five components to be tested will be: (1) coaching intensity (12 vs. 24 phone sessions), (2) text messaging (No vs. Yes), (3) progress report to participant's primary care provider (No vs. Yes), (4) recommendation to use meal replacements (No vs. Yes), (5) training participants' self-selected buddies to be supportive (No vs. Yes).

Recruitment information / eligibility

• Status: Completed
• Enrollment: 562
• Est. completion date: September 20, 2017
• Est. primary completion date: September 20, 2017
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 60 Years

Eligibility

Inclusion Criteria:

• 18 and 60 years old
• BMI 25-40 kg/m2
• Weight stable (no loss or gain >25 lbs for the past 6 months)
• Not enrolled in any formal weight loss program or taking anti-obesity medications, but interested in losing weight.
• Own a Smartphone and be willing to install the Opt-IN app
• Able to use the app to record dietary intake and weight onto the Smartphone

"Buddy" participants must:

• 18 years of age or older
• Have access to a computer and internet
• Be willing to undergo "Buddy Training" and participate in 4 webinars
• Be willing to provide support and encouragement to the participant

Exclusion Criteria:

• Unstable medical conditions (uncontrolled hypertension, diabetes, unstable angina pectoris, myocardial infarction, transient ischemic attack, cancer undergoing active treatment, or cerebrovascular accident within the past six months)
• History of diabetes requiring insulin supplementation, Crohn's Disease, or a diagnosis of obstructive sleep apnea requiring intervention (i.e. CPAP)
• Use an assistive device for mobility (e.g., wheelchair, walker, cane)
• Plantar fasciitis
• Hospitalization for a psychiatric disorder within the past 5 years
• At risk for adverse cardiovascular (CVD) events with moderate intensity activity
• Cannot read the study questionnaires
• Committed to following an incompatible dietary regimen
• Not be pregnant, trying to get pregnant, or lactating
• Bulimia, binge eating disorder, current substance abuse or dependence (besides nicotine dependence) or report active suicidal ideation
• Low motivation to change
• Cannot live with a current or past Opt-IN participant

Related Conditions & MeSH terms

• Weight Loss

Intervention

Behavioral:
• 12 Telephone Coaching Sessions
Participants will receive 12 telephone coaching sessions
• 24 Telephone Coaching Sessions
Participants will receive 24 telephone coaching sessions
• Report to Primary Care Physician
Participants will have a report detailing their weight loss progress sent to their primary care physician
• Text Messages
Participants will receive regular text messages
• Recommendations to use meal replacements
Participants will receive recommendations from their coach to use meal replacements
• Buddy Training
Participants will have a buddy that will be trained via webinars to be a supportive buddy

Locations

Country	Name	City	State
United States	Northwestern University	Chicago	Illinois

Sponsors (3)

Lead Sponsor	Collaborator
Northwestern University	National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Penn State University

Country where clinical trial is conducted

United States, 

References & Publications (31)

Baker TB, Collins LM, Mermelstein R, Piper ME, Schlam TR, Cook JW, Bolt DM, Smith SS, Jorenby DE, Fraser D, Loh WY, Theobald WE, Fiore MC. Enhancing the effectiveness of smoking treatment research: conceptual bases and progress. Addiction. 2016 Jan;111(1):107-16. doi: 10.1111/add.13154. Epub 2015 Nov 19. — View Citation

Baker TB, Smith SS, Bolt DM, Loh WY, Mermelstein R, Fiore MC, Piper ME, Collins LM. Implementing Clinical Research Using Factorial Designs: A Primer. Behav Ther. 2017 Jul;48(4):567-580. doi: 10.1016/j.beth.2016.12.005. Epub 2017 Jan 7. — View Citation

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. — View Citation

Burke LE, Ma J, Azar KM, Bennett GG, Peterson ED, Zheng Y, Riley W, Stephens J, Shah SH, Suffoletto B, Turan TN, Spring B, Steinberger J, Quinn CC; American Heart Association Publications Committee of the Council on Epidemiology and Prevention, Behavior Change Committee of the Council on Cardiometabolic Health, Council on Cardiovascular and Stroke Nursing, Council on Functional Genomics and Translational Biology, Council on Quality of Care and Outcomes Research, and Stroke Council. Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention: A Scientific Statement From the American Heart Association. Circulation. 2015 Sep 22;132(12):1157-213. doi: 10.1161/CIR.0000000000000232. Epub 2015 Aug 13. No abstract available. Erratum In: Circulation. 2015 Nov 10;132(19):e233. — View Citation

Collins LM, Dziak JJ, Kugler KC, Trail JB. Factorial experiments: efficient tools for evaluation of intervention components. Am J Prev Med. 2014 Oct;47(4):498-504. doi: 10.1016/j.amepre.2014.06.021. Epub 2014 Aug 1. — View Citation

Collins LM, Kugler KC, Gwadz MV. Optimization of Multicomponent Behavioral and Biobehavioral Interventions for the Prevention and Treatment of HIV/AIDS. AIDS Behav. 2016 Jan;20 Suppl 1(0 1):S197-214. doi: 10.1007/s10461-015-1145-4. — View Citation

Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med. 2007 May;32(5 Suppl):S112-8. doi: 10.1016/j.amepre.2007.01.022. — View Citation

Collins LM, Nahum-Shani I, Almirall D. Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clin Trials. 2014 Aug;11(4):426-434. doi: 10.1177/1740774514536795. Epub 2014 Jun 5. — View Citation

Cook JW, Collins LM, Fiore MC, Smith SS, Fraser D, Bolt DM, Baker TB, Piper ME, Schlam TR, Jorenby D, Loh WY, Mermelstein R. Comparative effectiveness of motivation phase intervention components for use with smokers unwilling to quit: a factorial screening experiment. Addiction. 2016 Jan;111(1):117-28. doi: 10.1111/add.13161. Epub 2015 Nov 19. — View Citation

Hekler EB, Michie S, Pavel M, Rivera DE, Collins LM, Jimison HB, Garnett C, Parral S, Spruijt-Metz D. Advancing Models and Theories for Digital Behavior Change Interventions. Am J Prev Med. 2016 Nov;51(5):825-832. doi: 10.1016/j.amepre.2016.06.013. — View Citation

Hoffman SA, Ledford G, Cameron KA, Phillips SM, Pellegrini CA. A qualitative exploration of social and environmental factors affecting diet and activity in knee replacement patients. J Clin Nurs. 2019 Apr;28(7-8):1156-1163. doi: 10.1111/jocn.14719. Epub 2018 Dec 10. — View Citation

Kheirkhahan M, Tudor-Locke C, Axtell R, Buman MP, Fielding RA, Glynn NW, Guralnik JM, King AC, White DK, Miller ME, Siddique J, Brubaker P, Rejeski WJ, Ranshous S, Pahor M, Ranka S, Manini TM. Actigraphy features for predicting mobility disability in older adults. Physiol Meas. 2016 Oct;37(10):1813-1833. doi: 10.1088/0967-3334/37/10/1813. Epub 2016 Sep 21. — View Citation

Nahum-Shani I, Dziak JJ, Collins LM. Multilevel factorial designs with experiment-induced clustering. Psychol Methods. 2018 Sep;23(3):458-479. doi: 10.1037/met0000128. Epub 2017 Apr 6. — View Citation

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. — View Citation

Pellegrini CA, Conroy DE, Phillips SM, Pfammatter AF, McFadden HG, Spring B. Daily and Seasonal Influences on Dietary Self-monitoring Using a Smartphone Application. J Nutr Educ Behav. 2018 Jan;50(1):56-61.e1. doi: 10.1016/j.jneb.2016.12.004. — View Citation

Pellegrini CA, Hoffman SA, Collins LM, Spring B. Corrigendum to "Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol" [Contemp. Clin. Trials 38 (2014) 251-259]. Contemp Clin Trials. 2015 Nov;45(Pt B):468-469. doi: 10.1016/j.cct.2015.09.001. Epub 2015 Nov 29. No abstract available. — View Citation

Pellegrini CA, Hoffman SA, Collins LM, Spring B. Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol. Contemp Clin Trials. 2014 Jul;38(2):251-9. doi: 10.1016/j.cct.2014.05.007. Epub 2014 May 17. Erratum In: Contemp Clin Trials. 2015 Nov;45(Pt B):468-469. — View Citation

Pellegrini CA, Hoffman SA, Daly ER, Murillo M, Iakovlev G, Spring B. Acceptability of smartphone technology to interrupt sedentary time in adults with diabetes. Transl Behav Med. 2015 Sep;5(3):307-14. doi: 10.1007/s13142-015-0314-3. — View Citation

Pellegrini CA, Pfammatter AF, Conroy DE, Spring B. Smartphone applications to support weight loss: current perspectives. Adv Health Care Technol. 2015 Jul;1:13-22. doi: 10.2147/AHCT.S57844. — View Citation

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. — View Citation

Piper ME, Cook JW, Schlam TR, Jorenby DE, Smith SS, Collins LM, Mermelstein R, Fraser D, Fiore MC, Baker TB. A Randomized Controlled Trial of an Optimized Smoking Treatment Delivered in Primary Care. Ann Behav Med. 2018 Sep 13;52(10):854-864. doi: 10.1093/abm/kax059. — View Citation

Piper ME, Cook JW, Schlam TR, Smith SS, Bolt DM, Collins LM, Mermelstein R, Fiore MC, Baker TB. Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action. Drug Alcohol Depend. 2017 Feb 1;171:50-58. doi: 10.1016/j.drugalcdep.2016.11.027. Epub 2016 Nov 24. — View Citation

Piper ME, Fiore MC, Smith SS, Fraser D, Bolt DM, Collins LM, Mermelstein R, Schlam TR, Cook JW, Jorenby DE, Loh WY, Baker TB. Identifying effective intervention components for smoking cessation: a factorial screening experiment. Addiction. 2016 Jan;111(1):129-41. doi: 10.1111/add.13162. Epub 2015 Nov 19. — View Citation

Piper ME, Schlam TR, Cook JW, Smith SS, Bolt DM, Loh WY, Mermelstein R, Collins LM, Fiore MC, Baker TB. Toward precision smoking cessation treatment I: Moderator results from a factorial experiment. Drug Alcohol Depend. 2017 Feb 1;171:59-65. doi: 10.1016/j.drugalcdep.2016.11.025. Epub 2016 Nov 25. — View Citation

Schlam TR, Fiore MC, Smith SS, Fraser D, Bolt DM, Collins LM, Mermelstein R, Piper ME, Cook JW, Jorenby DE, Loh WY, Baker TB. Comparative effectiveness of intervention components for producing long-term abstinence from smoking: a factorial screening experiment. Addiction. 2016 Jan;111(1):142-55. doi: 10.1111/add.13153. Epub 2015 Nov 19. — View Citation

Spring B, Ockene JK, Gidding SS, Mozaffarian D, Moore S, Rosal MC, Brown MD, Vafiadis DK, Cohen DL, Burke LE, Lloyd-Jones D; American Heart Association Behavior Change Committee of the Council on Epidemiology and Prevention, Council on Lifestyle and Cardiometabolic Health, Council for High Blood Pressure Research, and Council on Cardiovascular and Stroke Nursing. Better population health through behavior change in adults: a call to action. Circulation. 2013 Nov 5;128(19):2169-76. doi: 10.1161/01.cir.0000435173.25936.e1. Epub 2013 Oct 7. No abstract available. — View Citation

Spring B, Pellegrini CA, Pfammatter A, Duncan JM, Pictor A, McFadden HG, Siddique J, Hedeker D. Effects of an abbreviated obesity intervention supported by mobile technology: The ENGAGED randomized clinical trial. Obesity (Silver Spring). 2017 Jul;25(7):1191-1198. doi: 10.1002/oby.21842. Epub 2017 May 11. — View Citation

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. — View Citation

Terry PE, Brown N, Arnett DK, Cushman M, Spring B, Halpern SD, Burke LE, Grossmeier J, Goetzel R, Lang J, Calitz C, Terry PE, Sanchez E. The Art of Health Promotion ideas for improving health outcomes. Am J Health Promot. 2016 Sep;30(7):563-82. doi: 10.1177/0890117116668866. No abstract available. — View Citation

Watkins E, Newbold A, Tester-Jones M, Javaid M, Cadman J, Collins LM, Graham J, Mostazir M. Implementing multifactorial psychotherapy research in online virtual environments (IMPROVE-2): study protocol for a phase III trial of the MOST randomized component selection method for internet cognitive-behavioural therapy for depression. BMC Psychiatry. 2016 Oct 6;16(1):345. doi: 10.1186/s12888-016-1054-8. — View Citation

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. — View Citation

* Note: There are 31 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Treatment Adherence	Treatment adherence is a hypothesized mediator that will be operationalized as the number of treatment sessions completed divided by the number of treatment sessions offered (12 or 24)	6 months
Other	Self-monitoring Adherence	Self-monitoring is a hypothesized mediator that will be operationalized as the number of days recording weight, dietary intake, and physical activity	6 months
Other	Self-efficacy	Self-efficacy is an exploratory mediator that will be assessed to examine treatment effects on confidence about performing two categories of behaviors associated with weight loss: diet and physical activity	6 months
Other	Self-Regulation	Self-regulation is an exploratory mediator that will be assessed using the Three Factor Eating Questionnaire and Treatment Self-Regulation Questionnaire	6 months
Other	Supportive Accountability	Supportive accountability is an exploratory mediator that will be measured by assessing two constructs that define supportive accountability: therapeutic alliance and perceived autonomy support	6 months
Other	Facilitation	Facilitation is an exploratory mediator that will be measured by rating how much the tools provided by the study have changed their environment and by the Weight Management Support Inventory	6 months
Primary	Weight Change (kg) From Baseline to Month 6, Main Effect of Time	Estimated mean change from Baseline to Month 6 were obtained from a linear mixed models analysis of variance to account for missing data. All randomized participants were utilized in the model (ITT analysis).	From Baseline to Month 6
Primary	Weight Change (kg) From Baseline to Month 6, Time by Factor Interaction	Estimated mean change from Baseline to Month 6 were obtained from a linear mixed models analysis of variance to account for missing data. All randomized participants were utilized in the model (ITT analysis).; This outcome measure is reported as an additional effect beyond that of Outcome Measure 1 (each component has it's own weight loss effect that is above and beyond the weight change calculated in the Outcome Measure 1 analyses).	From Baseline to Month 6
Secondary	Intervention for <$500	Using the results from primary aim 1, an intervention with only active treatment components with the largest treatment effect that can be obtained for implementation costs of $500 or less was identified and built.	6 months