Trial reportInternational journal of medical informatics2014
Are we sure that Mobile Health is really mobile? An examination of mobile device use during two remotely-delivered weight loss interventions.
Trial report in International journal of medical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 4 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 4 syntheses or guidelines pooled it, 25 citations in OpenAlex.
- Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity.The Cochrane database of systematic reviews · 2024Pooled it
- Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Twitter as a Tool for Health Research: A Systematic Review.American journal of public health · 2017Pooled it
- The role of interdisciplinary research team in the impact of health apps in health and computer science publications: a systematic review.Biomedical engineering online · 2016Pooled it
- Refining an algorithm-powered just-in-time adaptive weight control intervention: A randomized controlled trial evaluating model performance and behavioral outcomes.Health informatics journal · 2020Trial
- Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions.Journal of the Academy of Nutrition and Dietetics · 2019Trial
- Telemonitoring and Mobile Phone-Based Health Coaching Among Finnish Diabetic and Heart Disease Patients: Randomized Controlled Trial.Journal of medical Internet research · 2015Trial
- Introducing an Integrated Model of Adults' Wearable Activity Tracker Use and Obesity Information-Seeking Behaviors From a National Quota Sample Survey.JMIR formative research · 2021Article
- Using Commercial Physical Activity Trackers for Health Promotion Research: Four Case Studies.Health promotion practice · 2019Article
- mHealth Application Areas and Technology Combinations*. A Comparison of Literature from High and Low/Middle Income Countries.Methods of information in medicine · 2017Article
- The Impact of Information Technology on Patient Engagement and Health Behavior Change: A Systematic Review of the Literature.JMIR medical informatics · 2016Article
- From black box to toolbox: Outlining device functionality, engagement activities, and the pervasive information architecture of mHealth interventions.Internet interventions · 2015Article
- Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe "m" in mHealth is often thought of as the ability to receive health information and monitor behaviors on the go. Little is known about how people actually use mobile vs. traditional access methods and if access method affects engagement and health outcomes.
methodsThis study examines the 3-month outcomes of two mobile weight loss interventions (Pounds Off Digitally (POD) and mobile POD (mPOD)) where participants were required to own a mobile device for study entry and received weight loss information via podcast. Only participants in both studies who were randomized to receive the same theory-based podcast (TBP) were used in this analysis. In POD, 41 participants were randomized to the TBP condition (37 to a control not included in this analyses). In mPOD, 49 participants were randomized to the TBP (n=49) and 47 to the TBP+mobile group (a self-monitoring app and Twitter app for social support). The goal of this study is to examine how participants accessed study components and to examine how type of device impacts engagement and weight loss.
resultsExamining data from both studies in aggregate, despite a mobile delivery method, 58% of participants reported using a non-mobile device to access the majority of the podcasts (desktop computers), 76% accessed the podcasts mostly at their home or work, and 62% were mainly non-mobile (e.g., sitting at work) when listening. Examining objective download data for mPOD, 49% of downloads (2889/5944) originated from non-mobile delivery methods vs. mobile platforms (3055/5944). At 3 months, 55% of Twitter posts originated from the website (n=665 posts) vs. a mobile app (n=540; 45%). There was no difference in the number of podcasts participants reported listening to by device. There were more Twitter posts by mobile app users (51±11) than Twitter website users (23±6, p<0.05). There was a trend (p=0.055) in greater weight loss among mobile users for podcasts (-3.5±0.5%) as compared to non-mobile users (-2.5±0.5%). Weight loss was significantly greater in Twitter mobile app users (-5.6±0.9%) than website users (-2.2±0.5%, p<0.01).
conclusionType of device used for podcast listening did not affect engagement but there was a trend toward greater weight loss among mobile users. Method of Twitter posting was associated with engagement and weight loss with mobile app users posting more to Twitter and losing more weight.
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Registered trials
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.