Evidence mapPaperPMID 42274402Full record

SynthesisInquiry : a journal of medical care organization, provision and financing

Effectiveness of Fitbit-Based Interventions in Improving 24-hour Movement Behaviors: A Systematic Review and Meta-Analysis.

Wentao Wang, Cong Huang, Yi Shen, Jing Cheng, Ling Wang

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Wentao WangDepartment of Basic Education, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou, China.ORCID 0000-0003-0801-1196
Cong HuangDepartment of Sports and Exercise Science, Zhejiang University, Hangzhou, China.
Yi ShenDepartment of Basic Education, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou, China.
Jing ChengDepartment of Basic Education, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou, China.
Ling WangDepartment of Sports and Arts, Zhejiang Gongshang University Hangzhou College of Commerce, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionAll activities performed by an individual over a 24-hour period can be classified into four categories-moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior (SB), and sleep-collectively referred to as 24-hour movement behaviors. Fitbit devices can not only monitor all components of 24-hour movement behaviors but are also cost-effective and reliable. The aim of this meta-analysis was to assess the impact of Fitbit-based interventions on 24-hour movement behaviors outcomes.MethodsTo identify studies that employed Fitbit devices as intervention tools to improve 24-hour movement behaviors, the following five electronic databases were searched: PubMed, Embase, SCOPUS, Cochrane Library, and Web of Science. Study quality was evaluated using the Cochrane Risk-of-Bias tool. Meta-analysis was performed using a random-effects model to assess the pooled effects of Fitbit-based interventions on MVPA, LPA, SB, and sleep.ResultsForty-five studies involving 5234 participants were included in this meta-analysis. Fitbit-based interventions can significantly increase MVPA (MD 4.44 min/day; 95% CI 2.77 to 6.10;

Indexed as

ExerciseFitness TrackersHumansSedentary BehaviorSleepSleep Duration24-hour movement behaviorsfitbit devicesLPAmeta-analysisMVPASBsleep

Identifiers

PMID42274402
PMCPMC13260979

What Socratic holds

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Registered trials

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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 Socratic graph.