Evidence map›Paper›PMID 38687568›Full record

SynthesisJMIR mHealth and uHealth2024

Effectiveness of mHealth App-Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic Review and Meta-Analysis.

Jun-Wei Wang, Zhicheng Zhu, Zhang Shuling, Jia Fan, Yu Jin, Zhan-Le Gao, Wan-Di Chen, Xue Li

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 10 pooled it
–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

33 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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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

8 authors.

Jun-Wei WangSchool of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.ORCID 0000-0001-8245-8741
Zhicheng ZhuPhysical education institute, Xinyu University, Xinyu, China.ORCID 0009-0006-2782-8539
Zhang ShulingSchool of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.ORCID 0000-0002-5140-3278
Jia FanSchool of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.ORCID 0009-0006-2214-6336
Yu JinSchool of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.ORCID 0009-0001-9925-1875
Zhan-Le GaoSchool of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.ORCID 0000-0001-6754-473X
Wan-Di ChenAcademic Administration, Chengdu Sport University, Chengdu, China.ORCID 0009-0002-9822-0978
Xue Li *School of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.ORCID 0000-0003-4988-4495

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app-based interventions and potential moderators in this population are not yet fully understood.

objectiveThis study aims to review and analyze the effectiveness of mHealth app-based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app-based interventions in children and adolescents.

methodsWe searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes.

resultsWe included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app-based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95% CI 0.13-0.45; P<.001), reduced SB (SMD -0.97, 95% CI -1.67 to -0.28; P=.006) and BMI (weighted mean difference -0.31 kg/m

conclusionsOur meta-analysis suggests that mHealth app-based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app-based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research.

trial registrationPROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf.

Indexed as

ExerciseMobile ApplicationsPandemicsPhysical FitnessTelemedicineAdolescentChildCOVID-19Health PromotionHumansInfection ControlRandomized Controlled Trials as Topicchildren and adolescentsmeta-analysismHealth appsmobile healthmobile phonephysical activityphysical fitnesssystematic review

Identifiers

PMID38687568
PMCPMC11094610

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.