The Walking Interventions Through Texting (WalkIT) Trial: Rationale, Design, and Protocol for a Factorial Randomized Controlled Trial of Adaptive Interventions for Overweight and Obese, Inactive Adults

Jane C Hurley, Kevin E Hollingshead, Michael Todd, Catherine L Jarrett, Wesley J Tucker, Siddhartha S Angadi, Marc A Adams, Jane C Hurley, Kevin E Hollingshead, Michael Todd, Catherine L Jarrett, Wesley J Tucker, Siddhartha S Angadi, Marc A Adams

Abstract

Background: Walking is a widely accepted and frequently targeted health promotion approach to increase physical activity (PA). Interventions to increase PA have produced only small improvements. Stronger and more potent behavioral intervention components are needed to increase time spent in PA, improve cardiometabolic risk markers, and optimize health.

Objective: Our aim is to present the rationale and methods from the WalkIT Trial, a 4-month factorial randomized controlled trial (RCT) in inactive, overweight/obese adults. The main purpose of the study was to evaluate whether intensive adaptive components result in greater improvements to adults' PA compared to the static intervention components.

Methods: Participants enrolled in a 2x2 factorial RCT and were assigned to one of four semi-automated, text message-based walking interventions. Experimental components included adaptive versus static steps/day goals, and immediate versus delayed reinforcement. Principles of percentile shaping and behavioral economics were used to operationalize experimental components. A Fitbit Zip measured the main outcome: participants' daily physical activity (steps and cadence) over the 4-month duration of the study. Secondary outcomes included self-reported PA, psychosocial outcomes, aerobic fitness, and cardiorespiratory risk factors assessed pre/post in a laboratory setting. Participants were recruited through email listservs and websites affiliated with the university campus, community businesses and local government, social groups, and social media advertising.

Results: This study has completed data collection as of December 2014, but data cleaning and preliminary analyses are still in progress. We expect to complete analysis of the main outcomes in late 2015 to early 2016.

Conclusions: The Walking Interventions through Texting (WalkIT) Trial will further the understanding of theory-based intervention components to increase the PA of men and women who are healthy, insufficiently active and are overweight or obese. WalkIT is one of the first studies focusing on the individual components of combined goal setting and reward structures in a factorial design to increase walking. The trial is expected to produce results useful to future research interventions and perhaps industry initiatives, primarily focused on mHealth, goal setting, and those looking to promote behavior change through performance-based incentives.

Trial registration: ClinicalTrials.gov NCT02053259; https://ichgcp.net/clinical-trials-registry/NCT02053259 (Archived by WebCite at http://www.webcitation.org/6b65xLvmg).

Keywords: Fitbit; SMS; exercise; inactive; just in time adaptive interventions; mHealth; overweight; percentile schedule of reinforcement; text messaging.

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Illustration of 2x2 factorial design.
Figure 2
Figure 2
Schematic for intensive adaptive intervention system.

References

    1. Beddhu S, Wei G, Marcus RL, Chonchol M, Greene T. Light-Intensity Physical Activities and Mortality in the United States General Population and CKD Subpopulation. Clin J Am Soc Nephrol. 2015 Jul 7;10(7):1145–53. doi: 10.2215/CJN.08410814.
    1. Murtagh EM, Nichols L, Mohammed MA, Holder R, Nevill AM, Murphy MH. The effect of walking on risk factors for cardiovascular disease: an updated systematic review and meta-analysis of randomised control trials. Prev Med. 2015 Mar;72:34–43. doi: 10.1016/j.ypmed.2014.12.041.
    1. Conn VS, Hafdahl AR, Mehr DR. Interventions to increase physical activity among healthy adults: meta-analysis of outcomes. Am J Public Health. 2011 Apr;101(4):751–8. doi: 10.2105/AJPH.2010.194381.
    1. Champion Vl, Skinner Cs. The Health Belief Model. In: Glanz K, Rimer B, Viswanath K, editors. Health Behavior and Health Education: Theory, Research, and Practice. 4th ed. San Francisco: Jossey-Bass; 2008. pp. 45–66.
    1. McAlister A, Perry C, Parcel G. How Individuals, Environments, and Health Behaviors Interact: Social Cognitive Theory. In: Glanz K, Rimer B, Viswanath K, editors. Health Behavior and Health Education: Theory, Research, and Practice. 4th ed. San Francisco: Jossey-Bass; 2008. pp. 169–188.
    1. Pearson ES. Goal setting as a health behavior change strategy in overweight and obese adults: a systematic literature review examining intervention components. Patient Educ Couns. 2012 Apr;87(1):32–42. doi: 10.1016/j.pec.2011.07.018.
    1. Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, Stave CD, Olkin I, Sirard JR. Using pedometers to increase physical activity and improve health: a systematic review. JAMA. 2007 Nov 21;298(19):2296–304. doi: 10.1001/jama.298.19.2296.
    1. Hovell M, Wahlgren D, Adams M. The Logical and Empirical Basis for the Behavioral Ecological Model. In: DeClemente RJ, Crosby RA, Kegler MC, editors. Emerging Theories in Health Promotion Practice and Research. 2nd ed. San Francisco: Jossey-Bass; 2009.
    1. Normand MP. Increasing physical activity through self-monitoring, goal setting, and feedback. Behav Intervent. 2008 Nov 1;23(4):227–236. doi: 10.1002/bin.267.
    1. Moreau KL, Degarmo R, Langley J, McMahon C, Howley ET, Bassett DR, Thompson DL. Increasing daily walking lowers blood pressure in postmenopausal women. Med Sci Sports Exerc. 2001 Nov;33(11):1825–31.
    1. Morgan AL, Tobar DA, Snyder L. Walking toward a new me: the impact of prescribed walking 10,000 steps/day on physical and psychological well-being. J Phys Act Health. 2010 May;7(3):299–307.
    1. Osei-Tutu KB, Campagna PD. The effects of short- vs. long-bout exercise on mood, VO2max, and percent body fat. Prev Med. 2005 Jan;40(1):92–8. doi: 10.1016/j.ypmed.2004.05.005.
    1. O'Donnell S, Greene GW, Blissmer B. The effect of goal setting on fruit and vegetable consumption and physical activity level in a Web-based intervention. J Nutr Educ Behav. 2014;46(6):570–5. doi: 10.1016/j.jneb.2014.03.005.
    1. Tully MA, Cupples ME, Hart ND, McEneny J, McGlade KJ, Chan W, Young IS. Randomised controlled trial of home-based walking programmes at and below current recommended levels of exercise in sedentary adults. J Epidemiol Community Health. 2007 Sep;61(9):778–83. doi: 10.1136/jech.2006.053058.
    1. Shilts MK, Horowitz M, Townsend MS. Goal setting as a strategy for dietary and physical activity behavior change: a review of the literature. Am J Health Promot. 2004;19(2):81–93.
    1. Adams MA, Sallis JF, Norman GJ, Hovell MF, Hekler EB, Perata E. An adaptive physical activity intervention for overweight adults: a randomized controlled trial. PLoS One. 2013;8(12):e82901. doi: 10.1371/journal.pone.0082901.
    1. Riley WT, Serrano KJ, Nilsen W, Atienza AA. Mobile and Wireless Technologies in Health Behavior and the Potential for Intensively Adaptive Interventions. Curr Opin Psychol. 2015 Oct 1;5:67–71. doi: 10.1016/j.copsyc.2015.03.024.
    1. Galbicka G. Shaping in the 21st century: Moving percentile schedules into applied settings. J Appl Behav Anal. 1994;27(4):739–60.
    1. Washington WD, Banna KM, Gibson AL. Preliminary efficacy of prize-based contingency management to increase activity levels in healthy adults. J Appl Behav Anal. 2014;47(2):231–45. doi: 10.1002/jaba.119.
    1. Adams MA. [Dissertation] University of California, San Diego. La Jolla, CA: San Diego State University Press; 2009. A pedometer-based intervention to increase physical activity applying frequent, adaptive goals and percentile schedule of reinforcement.
    1. Donaldson EL, Fallows S, Morris M. A text message based weight management intervention for overweight adults. J Hum Nutr Diet. 2014 Apr;27 Suppl 2:90–7. doi: 10.1111/jhn.12096.
    1. Okorodudu DE, Bosworth HB, Corsino L. Innovative interventions to promote behavioral change in overweight or obese individuals: A review of the literature. Ann Med. 2015 May;47(3):179–85. doi: 10.3109/07853890.2014.931102.
    1. Finkelstein EA, Sahasranaman A, John G, Haaland BA, Bilger M, Sloan RA, Nang Ei Ei Khaing. Evenson KR. Design and baseline characteristics of participants in the TRial of Economic Incentives to Promote Physical Activity (TRIPPA): a randomized controlled trial of a six month pedometer program with financial incentives. Contemp Clin Trials. 2015 Mar;41:238–47. doi: 10.1016/j.cct.2015.01.020.
    1. Thorgeirsson T, Kawachi I. Behavioral economics: merging psychology and economics for lifestyle interventions. Am J Prev Med. 2013 Feb;44(2):185–9. doi: 10.1016/j.amepre.2012.10.008.
    1. Bickel WK, Marsch LA, Carroll ME. Deconstructing relative reinforcing efficacy and situating the measures of pharmacological reinforcement with behavioral economics: a theoretical proposal. Psychopharmacology (Berl) 2000 Dec;153(1):44–56.
    1. Dallery J, Kurti A, Erb P. A New Frontier: Integrating Behavioral and Digital Technology to Promote Health Behavior. Behav Analyst. 2014 Aug 23;38(1):19–49. doi: 10.1007/s40614-014-0017-y.
    1. Eysenbach Gunther, Consort-EHEALTH Group CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J Med Internet Res. 2011;13(4):e126. doi: 10.2196/jmir.1923.
    1. US Census Bureau State and County QuickFacts: Maricopa County, Arizona. 2015. [2015-05-01]. .
    1. Lamb RJ, Morral AR, Kirby KC, Iguchi MY, Galbicka G. Shaping smoking cessation using percentile schedules. Drug Alcohol Depend. 2004 Dec 7;76(3):247–59. doi: 10.1016/j.drugalcdep.2004.05.008.
    1. Bandura A. The anatomy of stages of change. Am J Health Promot. 1997;12(1):8–10.
    1. Sallis J, Owen N, Fisher E. Ecological Models of Health Behavior. In: Glanz K, Rimer BK, Viswanath k, editors. Health Behavior and Health Education: Theory, Research, and Practice. San Francisco: Jossey-Bass; 2008. pp. 465–85.
    1. Noah JA, Spierer DK, Gu J, Bronner S. Comparison of steps and energy expenditure assessment in adults of Fitbit Tracker and Ultra to the Actical and indirect calorimetry. J Med Eng Technol. 2013 Oct;37(7):456–62. doi: 10.3109/03091902.2013.831135.
    1. Mammen G, Gardiner S, Senthinathan A, McClemont L, Stone M, Faulkner G. Is this Bit Fit? Measuring the Quality of the FitBit Step-Counter. Health & Fitness Journal of Canada. 2012;5(4):30–39.
    1. US Department of Health and Human Services. 2008. [2015-05-05]. Be Active Your Way: A Guide for Adults .
    1. American on the Move Foundation 100 ways to add 2000 steps. 2008. [2015-05-05]. .
    1. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381–95. doi: 10.1249/01.MSS.0000078924.61453.FB.
    1. Blikman T, Stevens M, Bulstra SK, van den Akker-Scheek I, Reininga IHF. Reliability and validity of the Dutch version of the International Physical Activity Questionnaire in patients after total hip arthroplasty or total knee arthroplasty. J Orthop Sports Phys Ther. 2013 Sep;43(9):650–9. doi: 10.2519/jospt.2013.4422.
    1. Cerin E, Saelens BE, Sallis JF, Frank LD. Neighborhood Environment Walkability Scale: validity and development of a short form. Med Sci Sports Exerc. 2006 Sep;38(9):1682–91. doi: 10.1249/01.mss.0000227639.83607.4d.
    1. Cerin E, Conway TL, Saelens BE, Frank LD, Sallis JF. Cross-validation of the factorial structure of the Neighborhood Environment Walkability Scale (NEWS) and its abbreviated form (NEWS-A) Int J Behav Nutr Phys Act. 2009;6:32. doi: 10.1186/1479-5868-6-32.
    1. Adams MA, Ryan S, Kerr J, Sallis JF, Patrick K, Frank LD, Norman GJ. Validation of the Neighborhood Environment Walkability Scale (NEWS) items using geographic information systems. J Phys Act Health. 2009;6 Suppl 1:S113–23.
    1. Kirby KN, Maraković NN. Delay-discounting probabilistic rewards: Rates decrease as amounts increase. Psychon Bull Rev. 1996 Mar;3(1):100–4. doi: 10.3758/BF03210748.
    1. Kirby KN. The present values of delayed rewards are approximately additive. Behav Processes. 2006 Jun 1;72(3):273–82. doi: 10.1016/j.beproc.2006.03.011.
    1. Marcus BH, Rakowski W, Rossi JS. Assessing motivational readiness and decision making for exercise. Health Psychol. 1992;11(4):257–61.
    1. Lewis BA, Williams DM, Martinson BC, Dunsiger S, Marcus BH. Healthy for life: a randomized trial examining physical activity outcomes and psychosocial mediators. Ann Behav Med. 2013 Apr;45(2):203–12. doi: 10.1007/s12160-012-9439-5.
    1. Burckhardt CS, Clark SR, Padrick KP. Use of the modified Balke treadmill protocol for determining the aerobic capacity of women with fibromyalgia. Arthritis Care Res. 1989 Dec;2(4):165–7.
    1. Foster C, Crowe AJ, Daines E, Dumit M, Green MA, Lettau S, Thompson NN, Weymier J. Predicting functional capacity during treadmill testing independent of exercise protocol. Med Sci Sports Exerc. 1996 Jun;28(6):752–6.
    1. Peterson MJ, Pieper CF, Morey MC. Accuracy of VO2(max) prediction equations in older adults. Med Sci Sports Exerc. 2003 Jan;35(1):145–9. doi: 10.1249/01.MSS.0000043547.22724.0B.
    1. Hwang MH, Yoo JK, Kim HK, Hwang CL, Mackay K, Hemstreet O, Nichols WW, Christou DD. Validity and reliability of aortic pulse wave velocity and augmentation index determined by the new cuff-based SphygmoCor Xcel. J Hum Hypertens. 2014 Aug;28(8):475–81. doi: 10.1038/jhh.2013.144.
    1. Buckberg GD, Fixler DE, Archie JP, Hoffman JI. Experimental subendocardial ischemia in dogs with normal coronary arteries. Circ Res. 1972 Jan;30(1):67–81.
    1. Psioda M. Random Effects Simulation for Sample Size Calculations Using SAS. 2012. [2015-05-02]. .
    1. Volpp KG, Loewenstein G, Troxel AB, Doshi J, Price M, Laskin M, Kimmel SE. A test of financial incentives to improve warfarin adherence. BMC Health Serv Res. 2008;8:272. doi: 10.1186/1472-6963-8-272.
    1. Taylor AH, Thompson TP, Greaves CJ, Taylor RS, Green C, Warren FC, Kandiyali R, Aveyard P, Ayres R, Byng R, Campbell JL, Ussher MH, Michie S, West R. A pilot randomised trial to assess the methods and procedures for evaluating the clinical effectiveness and cost-effectiveness of Exercise Assisted Reduction then Stop (EARS) among disadvantaged smokers. Health Technol Assess. 2014 Jan;18(4):1–324. doi: 10.3310/hta18040.
    1. Rovniak LS, Hovell MF, Wojcik JR, Winett RA, Martinez-Donate AP. Enhancing theoretical fidelity: an e-mail-based walking program demonstration. Am J Health Promot. 2005;20(2):85–95.
    1. Farrell SW, Cortese GM, LaMonte MJ, Blair SN. Cardiorespiratory fitness, different measures of adiposity, and cancer mortality in men. Obesity (Silver Spring) 2007 Dec;15(12):3140–9. doi: 10.1038/oby.2007.374.
    1. Matheson EM, King DE, Everett CJ. Healthy lifestyle habits and mortality in overweight and obese individuals. J Am Board Fam Med. 2012;25(1):9–15. doi: 10.3122/jabfm.2012.01.110164.
    1. Gaesser GA, Angadi SS, Sawyer BJ. Exercise and diet, independent of weight loss, improve cardiometabolic risk profile in overweight and obese individuals. Phys Sportsmed. 2011 May;39(2):87–97. doi: 10.3810/psm.2011.05.1898.
    1. Gaesser GA, Tucker WJ, Jarrett CL, Angadi SS. Fitness versus Fatness: Which Influences Health and Mortality Risk the Most? Curr Sports Med Rep. 2015;14(4):327–32. doi: 10.1249/JSR.0000000000000170.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren