ArticleJournal of medical Internet research2016
Who Self-Weighs and What Do They Gain From It? A Retrospective Comparison Between Smart Scale Users and the General Population in England.
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 10 papers.
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.
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Who cites it
10 citing papers in PubMed, 21 citations in OpenAlex.
- Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture.JMIR mHealth and uHealth · 2024Trial
- Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users.Journal of medical Internet research · 2021Observational
- Accuracy of Smart Scales on Weight and Body Composition: Observational Study.JMIR mHealth and uHealth · 2021Observational
- Associations of Physical Activity Level and Variability With 6-Month Weight Change Among 26,935 Users of Connected Devices: Observational Real-Life Study.JMIR mHealth and uHealth · 2021Observational
- Characterization and Correction of Bias Due to Nonparticipation and the Degree of Loyalty in Large-Scale Finnish Loyalty Card Data on Grocery Purchases: Cohort Study.Journal of medical Internet research · 2020Article
- The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study.Journal of medical Internet research · 2019Review
- Understanding Pregnancy and Postpartum Health Using Ecological Momentary Assessment and Mobile Technology: Protocol for the Postpartum Mothers Mobile Study.JMIR research protocols · 2019Article
- Best practices for analyzing large-scale health data from wearables and smartphone apps.NPJ digital medicine · 2019Review
- The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial.JMIR mHealth and uHealth · 2018Article
- An International Study on the Determinants of Poor Sleep Amongst 15,000 Users of Connected Devices.Journal of medical Internet research · 2017Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundDigital self-monitoring, particularly of weight, is increasingly prevalent. The associated data could be reused for clinical and research purposes.
objectiveThe aim was to compare participants who use connected smart scale technologies with the general population and explore how use of smart scale technology affects, or is affected by, weight change.
methodsThis was a retrospective study comparing 2 databases: (1) the longitudinal height and weight measurement database of smart scale users and (2) the Health Survey for England, a cross-sectional survey of the general population in England. Baseline comparison was of body mass index (BMI) in the 2 databases via a regression model. For exploring engagement with the technology, two analyses were performed: (1) a regression model of BMI change predicted by measures of engagement and (2) a recurrent event survival analysis with instantaneous probability of a subsequent self-weighing predicted by previous BMI change.
resultsAmong women, users of self-weighing technology had a mean BMI of 1.62 kg/m(2) (95% CI 1.03-2.22) lower than the general population (of the same age and height) (P<.001). Among men, users had a mean BMI of 1.26 kg/m(2) (95% CI 0.84-1.69) greater than the general population (of the same age and height) (P<.001). Reduction in BMI was independently associated with greater engagement with self-weighing. Self-weighing events were more likely when users had recently reduced their BMI.
conclusionsUsers of self-weighing technology are a selected sample of the general population and this must be accounted for in studies that employ these data. Engagement with self-weighing is associated with recent weight change; more research is needed to understand the extent to which weight change encourages closer monitoring versus closer monitoring driving the weight change. The concept of isolated measures needs to give way to one of connected health metrics.
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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.