ArticleJournal of medical Internet research2016
Impact of a Mobile Phone Intervention to Reduce Sedentary Behavior in a Community Sample of Adults: A Quasi-Experimental Evaluation.
Article in Journal of medical Internet research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
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Who cites it
24 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Where Does the Time Go? Displacement of Device-Measured Sedentary Time in Effective Sedentary Behaviour Interventions: Systematic Review and Meta-Analysis.Sports medicine (Auckland, N.Z.) · 2022Pooled it
- Interventions for reducing sedentary behaviour in community-dwelling older adults.The Cochrane database of systematic reviews · 2021Pooled it
- Physical Activity Interventions With African American or Latino Men: A Systematic Review.American journal of men's health · 2018Pooled it
- Investigating Best Practices for Ecological Momentary Assessment: Nationwide Factorial Experiment.Journal of medical Internet research · 2024Trial
- A Pilot and Feasibility Mobile Health Intervention to Support Healthy Behaviors in African American Breast Cancer Survivors.Journal of racial and ethnic health disparities · 2021Trial
- HIV and Substance Use Reduction for Youth Experiencing Homelessness: Development and Usability Study.JMIR formative research · 2026Article
- Associations of smart device apps with and without a perceived self-efficacy component in a physical activity context with BMI.Journal of health psychology · 2025Article
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- Article
- An Integrated mHealth App for Smoking Cessation in Black Smokers With HIV: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2024Article
- A Smartphone-Based Intervention for Anxiety and Depression in Racially and Ethnically Diverse Adults (EASE): Protocol for a Randomized Controlled Trial.JMIR research protocols · 2022Article
- Impacts of life-events on sitting, TV viewing and computer use among women from disadvantaged neighbourhoods.BMC public health · 2022Article
- An Integrated mHealth App for Smoking Cessation in Black Smokers With Anxiety: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2022Article
- Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study.JMIR mHealth and uHealth · 2021Article
- Using mHealth to Increase Treatment Utilization Among Recently Incarcerated Homeless Adults (Link2Care): Protocol for a Randomized Controlled Trial.JMIR research protocols · 2018Article
- Participants' Perceptions on the Use of Wearable Devices to Reduce Sitting Time: Qualitative Analysis.JMIR mHealth and uHealth · 2018Article
- Feasibility and Preliminary Effectiveness of the Homework Intervention Strategy (eHIS) Program to Enhance Male Condom Use: Research Protocol.JMIR research protocols · 2018Article
- Ecological Momentary Assessment of Physical Activity: Validation Study.Journal of medical Internet research · 2017Article
- Support Buffers Financial Strain's Effect on Health-related Quality of Life.American journal of health behavior · 2017Article
- Nonworksite Interventions to Reduce Sedentary Behavior among Adults: A Systematic Review.Translational journal of the American College of Sports Medicine · 2017Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundGreater time spent sedentary is linked with increased risk of breast, colorectal, ovarian, endometrial, and prostate cancers. Given steadily increasing rates of mobile phone ownership, mobile phone interventions may have the potential to broadly influence sedentary behavior across settings.
objectiveThe purpose of this study was to examine the short-term impact of a mobile phone intervention that targeted sedentary time in a diverse community sample.
methodsAdults participated in a quasi-experimental evaluation of a mobile phone intervention designed to reduce sedentary time through prompts to interrupt periods of sitting. Participants carried mobile phones and wore accelerometers for 7 consecutive days. Intervention participants additionally received mobile phone prompts during self-reported sitting and information about the negative health impact of prolonged sedentariness. The study was conducted from December 2012 to November 2013 in Dallas, Texas. Linear mixed model regression analyses were conducted to evaluate the influence of the intervention on daily accelerometer-determined estimates of sedentary and active time.
resultsParticipants (N=215) were predominantly female (67.9%, 146/215) and nonwhite (black: 50.7%, 109/215; Latino: 12.1%, 26/215; other: 5.6%, 12/215). Analyses revealed that participants who received the mobile phone intervention had significantly fewer daily minutes of sedentary time (B=-22.09, P=.045) and more daily active minutes (B=23.01, P=.04) than control participants.
conclusionsA simple mobile phone intervention was associated with engaging in less sedentary time and more physical activity. Findings underscore the potential impact of mobile phone interventions to positively influence sedentary behavior and physical activity.
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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.