Evidence map›Paper›PMID 42088233›Full record

ArticleFrontiers in public health2026

Effect of an artificial intelligence-assisted community-based intervention on child restraint system practices in Shanghai, China.

Ning Gao, Xihui Wang, Shuna Gao, Juanjuan Peng, Yang Zheng, Bo Chen, Fengqian Qiu, Yan Yu, Weihua Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2026. 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

9 authors.

Ning Gao *Division of Noncommunicable Disease and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Xihui Wang *Department for Prevention of Tumor and Injury, Shanghai Huangpu District Center for Disease Control and Prevention (Shanghai Huangpu District Health Supervision Institute), Shanghai, China.
Shuna GaoDepartment for Prevention of Tumor and Injury, Shanghai Huangpu District Center for Disease Control and Prevention (Shanghai Huangpu District Health Supervision Institute), Shanghai, China.
Juanjuan PengDivision of Noncommunicable Disease and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Yang ZhengDivision of Noncommunicable Disease and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Bo ChenDepartment for Prevention of Tumor and Injury, Shanghai Huangpu District Center for Disease Control and Prevention (Shanghai Huangpu District Health Supervision Institute), Shanghai, China.
Fengqian QiuDepartment for Prevention of Tumor and Injury, Shanghai Huangpu District Center for Disease Control and Prevention (Shanghai Huangpu District Health Supervision Institute), Shanghai, China.
Yan YuDivision of Noncommunicable Disease and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Weihua ChenDepartment for Prevention of Tumor and Injury, Shanghai Huangpu District Center for Disease Control and Prevention (Shanghai Huangpu District Health Supervision Institute), Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Child restraint systems (CRS) can effectively prevent injuries to children in road traffic crashes. However, in China, the rates of CRS ownership and use remain relatively low. Methods: We conducted a community-based intervention trial with an integrated multimodal intervention from August 2024 to March 2025 in five communities in Huangpu District, Shanghai. A total of 501 participants were recruited (201 in the intervention group, 300 in the control group). The intervention included (1) distribution of CRS educational brochures and health education materials, (2) dissemination of online educational articles, and (3) Artificial intelligence-assisted (AI-assisted) voice calls delivering standardized reminders and safety education. The control group received only pamphlets on dietary nutrition. Results: A total of 501 participants completed the study. After the intervention, the rate of CRS ownership showed no significant difference between the intervention and control groups (90.05% versus 91.33%, Conclusion: An integrated community-based intervention combining conventional health education with AI-assisted follow-up improved consistent CRS use and reduced orientation-related installation errors. This approach may be a useful complement to current CRS promotion strategies.

Indexed as

Artificial IntelligenceChild Restraint SystemsHealth EducationAccidents, TrafficChildChild, PreschoolChinaFemaleHumansMaleartificial intelligence-assistedchild restraint systemcommunity-based interventionownership rateuse rate

Identifiers

PMID42088233
PMCPMC13135966

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.