ArticleJMIR research protocols2015
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.
Article in JMIR research protocols, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Walking Intervention Through Texting Study: A Factorial Trial
Preventing Posttraumatic Osteoarthritis With Physical Activity Promotion
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Walking Green: Developing an Evidence Base for Nature Prescriptions.International journal of environmental research and public health · 2019Trial
- Adaptive step goals and rewards: a longitudinal growth model of daily steps for a smartphone-based walking intervention.Journal of behavioral medicine · 2018Trial
- Adaptive goal setting and financial incentives: a 2 × 2 factorial randomized controlled trial to increase adults' physical activity.BMC public health · 2017Trial
- Delay Discount Rate Moderates a Physical Activity Intervention Testing Immediate Rewards.Behavioral medicine (Washington, D.C.)Trial
- Systematic review of dynamically tailored eHealth interventions targeting physical activity and healthy diet in chronic disease.NPJ digital medicine · 2025Article
- Optimizing and Testing an Individualized and Adaptive Physical Activity Digital Health Intervention: Protocol for a Control Optimization Trial Embedded Within a Randomized Controlled Trial.JMIR research protocols · 2025Article
- Evaluation Methods Applied to Digital Health Interventions: What Is Being Used beyond Randomised Controlled Trials?-A Scoping Review.International journal of environmental research and public health · 2022Article
- Feasibility of a Wearable-Based Physical Activity Goal-Setting Intervention Among Individuals With Anterior Cruciate Ligament Reconstruction.Journal of athletic training · 2021Article
- The TeMPO trial (treatment of meniscal tears in osteoarthritis): rationale and design features for a four arm randomized controlled clinical trial.BMC musculoskeletal disorders · 2018Article
- Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review.JMIR mHealth and uHealth · 2018Review
- What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study.JMIR mHealth and uHealth · 2017Article
- Effect of a WhatsApp walking trial on daily steps among female Saudi Arabian university students.International journal of health sciencesArticle
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Authors and funding
7 authors.
Funding
Abstract
backgroundWalking 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.
objectiveOur 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.
methodsParticipants 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.
resultsThis 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.
conclusionsThe 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 registrationClinicalTrials.gov NCT02053259; https://clinicaltrials.gov/ct2/show/NCT02053259 (Archived by WebCite at http://www.webcitation.org/6b65xLvmg).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.