Literature DB >> 30192907

Efficacy of Contextually Tailored Suggestions for Physical Activity: A Micro-randomized Optimization Trial of HeartSteps.

Predrag Klasnja1,2, Shawna Smith3,4, Nicholas J Seewald5, Andy Lee2, Kelly Hall5, Brook Luers5, Eric B Hekler6, Susan A Murphy7.   

Abstract

BACKGROUND: HeartSteps is an mHealth intervention that encourages regular walking via activity suggestions tailored to the individuals' current context.
PURPOSE: We conducted a micro-randomized trial (MRT) to evaluate the efficacy of HeartSteps' activity suggestions to optimize the intervention.
METHODS: We conducted a 6-week MRT with 44 adults. Contextually tailored suggestions could be delivered up to five times per day at user-selected times. At each of these five times, for each participant on each day of the study, HeartSteps randomized whether to provide an activity suggestion, and, if so, whether to provide a walking or an antisedentary suggestion. We used a centered and weighted least squares method to analyze the effect of suggestions on the 30-min step count following suggestion randomization.
RESULTS: Averaging over study days and types of activity suggestions, delivering a suggestion versus no suggestion increased the 30-min step count by 14% (p = .06), 35 additional steps over the 253-step average. The effect was not evenly distributed in time. Providing any type of suggestion versus no suggestion initially increased the step count by 66% (167 steps; p < .01), but this effect diminished over time. Averaging over study days, delivering a walking suggestion versus no suggestion increased the average step count by 24% (59 steps; p = .02). This increase was greater at the start of study (107% or 271 additional steps; p < .01), but decreased over time. Antisedentary suggestions had no detectable effect on the 30-min step count.
CONCLUSION: Contextually tailored walking suggestions are a promising way of initiating bouts of walking throughout the day. CLINICAL TRIAL INFORMATION: This study was registered on ClinicalTrials.gov number NCT03225521. © Society of Behavioral Medicine 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Behavior change; Micro-randomized trials; Mobile health; Physical activity; Walking

Mesh：

Year:  2019        PMID： 30192907      PMCID： PMC6401341          DOI： 10.1093/abm/kay067

Source DB:  PubMed          Journal:  Ann Behav Med        ISSN： 0883-6612


  21 in total

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Authors:  Brook Luers; Predrag Klasnja; Susan Murphy
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Journal:  Gerontologist       Date:  2014-10-07

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8.  Factorial experiments: efficient tools for evaluation of intervention components.

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  38 in total

1.  Practical Considerations for Data Collection and Management in Mobile Health Micro-randomized Trials.

Authors:  Nicholas J Seewald; Shawna N Smith; Andy Jinseok Lee; Predrag Klasnja; Susan A Murphy
Journal:  Stat Biosci       Date:  2019-01-05

2.  Digital solutions for shaping mood and behavior among individuals with mood disorders.

Authors:  Amanda Victory; Allison Letkiewicz; Amy L Cochran
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3.  Linear mixed models with endogenous covariates: modeling sequential treatment effects with application to a mobile health study.

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4.  Rejoinder: 'Estimating time-varying causal excursion effects in mobile health with binary outcomes'.

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5.  The Effects of Objective Push-Type Sleep Feedback on Habitual Sleep Behavior and Momentary Symptoms in Daily Life: mHealth Intervention Trial Using a Health Care Internet of Things System.

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6.  Microrandomized trials for promoting engagement in mobile health data collection: Adolescent/young adult oral chemotherapy adherence as an example.

Authors:  Shuang Li; Alexandra M Psihogios; Elise R McKelvey; Annisa Ahmed; Mashfiqui Rabbi; Susan Murphy
Journal:  Curr Opin Syst Biol       Date:  2020-07-07

7.  Dose-response research in digital health interventions: Concepts, considerations, and challenges.

Authors:  Megan A McVay; Gary G Bennett; Dori Steinberg; Corrine I Voils
Journal:  Health Psychol       Date:  2019-10-03       Impact factor: 4.267

8.  Predictors and Outcomes of Digital Weighing and Activity Tracking Lapses Among Young Adults During Weight Gain Prevention.

Authors:  Brooke T Nezami; Carmina G Valle; Alison K Nulty; Mark Espeland; Rena R Wing; Deborah F Tate
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9.  Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health.

Authors:  Peng Liao; Predrag Klasnja; Susan Murphy
Journal:  J Am Stat Assoc       Date:  2020-10-01       Impact factor: 5.033

10.  Microrandomized Trial Design for Evaluating Just-in-Time Adaptive Interventions Through Mobile Health Technologies for Cardiovascular Disease.

Authors:  Jessica R Golbus; Walter Dempsey; Elizabeth A Jackson; Brahmajee K Nallamothu; Predrag Klasnja
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