Evidence map›Paper›PMID 40336319›Full record

ArticleNew solutions : a journal of environmental and occupational health policy : NS2025

Demonstration of a Home Laundering Method for Cloth Facepieces to Achieve Hygienic and Sustainable Reuse.

William Mackay, Chris Baglin, Paul Baglin, Claire Chalmers, Fiona Henriquez, Ngozi Amaeze

Abstract read
In one paragraph

Article in New solutions : a journal of environmental and occupational health policy : NS, 2025. 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

6 authors.

William MackaySchool of Health and Life Sciences, University of the West of Scotland, Glasgow, UK.ORCID 0000-0003-0293-8054
Chris BaglintensARC, Stirling, UK.ORCID 0000-0003-2137-9411
Paul BaglintensARC, Stirling, UK.ORCID 0009-0004-7852-8240
Claire ChalmersSchool of Health and Life Sciences, University of the West of Scotland, Glasgow, UK.
Fiona HenriquezDepartment of Civil & Environmental Engineering, University of Strathclyde, Glasgow, Scotland, UK.ORCID 0000-0002-5534-1019
Ngozi AmaezeSchool of Health and Life Sciences, University of the West of Scotland, Glasgow, UK.ORCID 0000-0001-8580-9383

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mask shortages during COVID-19 led to the adoption of reusable textile masks; research into their performance and optimal washing conditions can guide domestic laundering to encourage their use, decreasing plastic pollution. The study tested four washing methods for cleaning artificially contaminated facepieces. These conditions included nonbiological detergent at 30°C, Reference Detergent 3 (RD3) at 40°C and 60°C, and fortified RD3 (sodium perborate + tetraacetylethylenediamine) at 40°C. After washing, the facepieces were tumble- or air-dried. The effectiveness was determined by measuring bacteria reduction by standard plate count, achieving a target reduction of ≥99.99% and a benchmark cleanliness requirement (for surgical masks) of ≤ 30 CFU/g (EN 14683: 2019). All met the benchmark except 30°C nonbiological detergent washes with air drying. Oxidative bleach reduced RD3 performance. This research demonstrates that heavily contaminated reusable masks can be effectively decontaminated using domestic machines on a normal wash cycle (40 degrees).

Indexed as

COVID-19Equipment ReuseLaunderingMasksDetergentsHumansSARS-CoV-2TextilesDetergentsface maskfacepiecelaunderingreprocessingreusable

Identifiers

PMID40336319
PMCPMC12222837

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.