Evidence map›Paper›PMID 33092675›Full record

ArticleEpidemiology and infection2020

Social media use as a predictor of handwashing during a pandemic: evidence from COVID-19 in Malaysia.

Stephen X Zhang, Lorenz Graf-Vlachy, Kim Hoe Looi, Rui Su, Jizhen Li

Abstract read
In one paragraph

Article in Epidemiology and infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed, 1 synthesis or guideline 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

5 authors.

Stephen X ZhangUniversity of Adelaide, Adelaide, Australia.ORCID 0000-0001-6123-1193
Lorenz Graf-VlachyESCP Business School, Berlin, Germany.ORCID 0000-0002-0545-6643
Kim Hoe LooiXiamen University Malaysia, Malaysia.ORCID 0000-0002-9873-0591
Rui SuXiamen University Malaysia, Malaysia.
Jizhen LiTsinghua University, Beijing, China.ORCID 0000-0003-1940-5633

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although handwashing is an effective way to prevent infections, there is scarce evidence on predictors of handwashing during a pandemic. This paper aims to identify behavioural and demographic predictors of handwashing. The study surveyed 674 adults in Malaysia in May 2020 regarding whether the time spent on social media predicted handwashing contingent on gender and number of children. More time spent on social media was positively associated with handwashing for males with three or more children. However, for males without children, social media use was negatively associated with handwashing. The association was not significant for males with one or two children. For females, more time spent on social media was significantly linked to more handwashing only for females with one child. Gender, a traditional predictor of handwashing, was a useful predictor only for those who spent more than three hours per day on social media and had at most one child. Number of children was a novel negative predictor for males who did not use social media and who averaged one hour per day on social media, a positive predictor for males who spent lots of time on social media, but not a predictor for females. In sum, social media use predicts handwashing, and is thus a helpful variable for use in targeted health communication during a pandemic - particularly through social media. Further, more conventional predictors like gender and number of children exhibit contingency effects with social media use.

Indexed as

Hand DisinfectionSocial MediaAdultBetacoronavirusCoronavirus InfectionsCOVID-19Family CharacteristicsFemaleHumansMalaysiaMaleMiddle AgedPandemicsPneumonia, ViralSARS-CoV-2Young Adult2019-nCoVCOVID-19epidemichealth informationhygienesocial media use

Identifiers

PMID33092675
PMCPMC7653491

What OpenQuestion holds

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Registered trials

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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.