Evidence map›Paper›PMID 40890236›Full record

ArticleScientific reports2025

Household adoption of domestic water filtration for combating waterborne diseases in developing countries.

Sohaib Mustafa, Long Ying, Khalid Jamil, Xinyu Wang

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Sohaib MustafaCollege of economics and management, Beijing University of Technology, Beijing, 100124, People's Republic of China.
Long YingBasic Education Development Center, Beijing University of Technology, Beijing, 100124, People's Republic of China. running@bjut.edu.cn.
Khalid JamilCollege of economics and management, Beijing University of Technology, Beijing, 100124, People's Republic of China.
Xinyu WangSchool of Economics and Management, North China University of Technology, Beijing, 100124, People's Republic of China.

Funding

Beijing Natural Science Foundation 9244023
6 · The paper itself

Abstract

Drinking contaminated water is a leading cause of several waterborne diseases. Domestic water filtration plants are treated as one of the possible alternative tools to combat the disease caused by contaminated drinking water. Little is known about the usage behaviour of households to use water filtration plants at the domestic level in combating waterborne disease. Unveiling how different social, economic, and technological factors can mold household usage behavior to use domestic water filtration plants can be helpful in combating the spread of diseases caused by contaminated water. We have collected a cross-sectional dataset from one of the developing countries and applied the SEM-ANN dual-stage hybrid model to test the proposed hypotheses and rank the social, economic, and technological factors according to their normalised importance. Results revealed that awareness of risks associated with contaminated water, social influence, and water pollution knowledge are the most significant predictors behind the use of domestic water filtration plants, whereas cost is a potential barrier. Gender was found to be a significant moderator and caused a small moderation in our study. Our study results have important policy suggestions for governments and other stakeholders to combat waterborne disease and achieve the WHO's clean water goal 2030.

Indexed as

Drinking WaterFiltrationWaterborne DiseasesWater PurificationCross-Sectional StudiesDeveloping CountriesFamily CharacteristicsFemaleHumansMaleWater SupplyDrinking WaterGender differenceSEM-ANNWaterborne diseaseWater filtration plantsWater pollution knowledge

Identifiers

PMID40890236
PMCPMC12402535

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.