Evidence map›Paper›PMID 42018994›Full record

SynthesisJMIR mHealth and uHealth2026

Effectiveness of Mobile Health Interventions in Pediatric Cancer: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Huilu Yao, Yiting Wen, Hongxiu Wang, Ying Xiao, Meiling Deng, Wei Yang, Yuqin Li, Xiaorong Mao

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Huilu YaoCollege of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, China.ORCID 0009-0000-9075-0814
Yiting WenSchool of Medicine, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0009-0007-3225-3474
Hongxiu WangCollege of Nursing, North Sichuan Medical College, Nanchong, China.ORCID 0009-0004-1486-6953
Ying XiaoSchool of Medicine, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0009-0009-6965-0347
Meiling DengDepartment of Neurosurgery, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0009-0009-3501-4326
Wei YangDepartment of Thoracic Surgery, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0009-0000-2161-5360
Yuqin LiDepartment of Cancer Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0009-0009-7779-0139
Xiaorong MaoDepartment of Nursing, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, No. 32, West Section 2, 1st Ring Road, Qingyang District, Chengdu, Sichuan Province, 610072, China, 86 13551093555, 86-028-87795585.ORCID 0000-0003-4407-2471

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cancer poses a significant threat to children's health, and mobile health (mHealth) is emerging as a key tool for remote disease management, health education, and follow-up. However, evidence of its effectiveness remains limited. Objective: This study aimed to summarize the effects of mHealth interventions for pediatric cancer compared with usual care, providing evidence-based support for optimizing intervention models and improving patient outcomes. Methods: A systematic search of 14 databases identified randomized controlled trials (RCTs) on mHealth apps for pediatric patients with cancer from inception to August 1, 2025. Two reviewers independently screened studies, extracted data, assessed bias risk, and graded evidence quality. The meta-analysis was conducted using RevMan 5.4 and Stata 15. Results: A total of 24 RCTs involving 2645 patients were included. This review found that mHealth interventions significantly reduced infection rates (odds ratio [OR] 0.25, 95% CI 0.10-0.60; P=.002) and the overall incidence of peripherally inserted central catheter (PICC) complications (OR 0.16, 95% CI 0.10-0.24; P<.001), while improving quality of life (standardized mean difference [SMD] 1.34, 95% CI 0.13-2.55; P=.03), self-management ability (SMD 6.39, 95% CI 1.26-11.53; P=.01), and treatment adherence (OR 2.83, 95% CI 1.41-5.66; P=.003). However, mHealth interventions had no significant effect on PICC catheter displacement (OR 0.44, 95% CI 0.15-1.29; P=.13) or health knowledge (SMD 4.44, 95% CI -2.40 to 11.29; P=.20). Further high-quality studies are needed to verify their impact in these areas. The intervention components covered 9 behavior change techniques: goals and planning, feedback and monitoring, social support, shaping knowledge, repetition and substitution, reward and threat, comparison of outcomes, natural consequences, and regulation. Conclusions: This systematic review and meta-analysis synthesized evidence from RCTs. The findings support the use of mHealth to reduce infections and PICC-related complications among pediatric patients with cancer while improving quality of life, self-management capabilities, and treatment adherence. These results underscore the importance of incorporating mHealth strategies into pediatric cancer care and guide the development and enhancement of future mHealth interventions.

Indexed as

NeoplasmsPediatricsTelemedicineChildDigital HealthHumansRandomized Controlled Trials as Topicadherencemeta-analysismobile healthpediatric cancerquality of life

Identifiers

PMID42018994
PMCPMC13102325

What OpenQuestion holds

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LicenceCC BY
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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.