Evidence map›Paper›PMID 41283056›Full record

ArticleFrontiers in public health2025

Analysis of factors influencing dengue prevention KAP among urban residents in Guangzhou and evaluation of mHealth intervention effects.

Zhihui Huang, Zhaohong Li, Lifen Li, Shiqi Wu, Changming Chen, Nengjiu Li, Jianyun Lu

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Zhihui HuangGuangzhou Baiyun District Center for Disease Control and Prevention, Guangzhou, China.
Zhaohong LiGuangzhou Baiyun District Center for Disease Control and Prevention, Guangzhou, China.
Lifen LiGuangzhou Huadu District Huadong Town Health Center, Guangzhou, China.
Shiqi WuGuangzhou Huadu District Huadong Town Health Center, Guangzhou, China.
Changming ChenGuangzhou Baiyun District Center for Disease Control and Prevention, Guangzhou, China.
Nengjiu LiGuangzhou Baiyun District Center for Disease Control and Prevention, Guangzhou, China.
Jianyun LuGuangzhou Baiyun District Center for Disease Control and Prevention, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to analyze the factors influencing dengue fever prevention knowledge, attitude, and practice (KAP) among urban residents in Guangzhou and to evaluate the effectiveness of an mHealth intervention based on the KAP model. Methods: A cross-sectional study was conducted with 3,571 participants from an online survey. A quasi-experimental study (84 in the intervention group and 83 in the control group) was carried out over 2 months. Electronic questionnaires assessed baseline KAP levels, and the groups' differences were compared post-intervention. Results: The baseline survey revealed a knowledge awareness rate of 80.29%, with the lowest levels found in males aged 55 and above, low-education groups, and temporary housing residents. Significant demographic differences were observed in prevention motivation and behavior ( Conclusion: The mHealth intervention effectively improved knowledge, but had limited impact on belief formation and behavior change. Future interventions should integrate community-specific strategies to enhance behavioral change mechanisms.

Indexed as

DengueHealth Knowledge, Attitudes, PracticeTelemedicineUrban PopulationAdultAgedChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and Questionnairesattitudedengueinterventionknowledgemobile health educationpractice (KAP)

Identifiers

PMID41283056
PMCPMC12634570

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.