Evidence map›Paper›PMID 31906432›Full record

ArticleInternational journal of environmental research and public health2020

Assessing the Treatment of Potential Effect Modifiers Informing World Health Organisation Guidelines for Environmental Noise.

Owen Douglas, Enda Murphy

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. 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

2 authors.

Owen DouglasSchool of Architecture, Planning and Environmental Policy, University College Dublin, Dublin 4, Ireland.
Enda MurphySchool of Architecture, Planning and Environmental Policy, University College Dublin, Dublin 4, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methodologies employed in the production of systematic reviews used to inform policy must be robust. In formulating the recent World Health Organisation (WHO) Environmental Noise Guidelines for the European Region, seven systematic reviews of evidence were commissioned to assess the relationship between environmental noise exposure and a range of health outcomes, six of which were nonauditory. Within the methodological guidance document devised for these reviews, inclusion and exclusion criteria for individual studies and existing reviews were applied in accordance with the Population-Exposure-Comparator-Outcome-Study (PECOS) framework for the evaluation of evidence. Specific criteria were defined for "populations" and source-specific "exposure", but no criteria were defined for the treatment of potential "effect modifiers". Furthermore, no criteria were set for the treatment of combined exposures. Employing a custom-designed assessment matrix, we assess the treatment of potential effect modifiers in the formulation of the aforementioned systematic reviews, all published in a Special Issue of the International Journal of Environmental Research and Public Health (IJERPH), titled "WHO Noise and Health Evidence Reviews". We identify substantial methodological variation in their treatment and propose the differentiation of "moderators" and "mediators" from "confounders" as the basis for criteria development-including combined exposures-for future systematic reviews.

Indexed as

Environmental ExposureNoiseSystematic Reviews as TopicWorld Health OrganizationForecastingHumansassessmentconfounderseffect modificationhealthmediatorsmethodologymoderatorsoutcomessystematic reviewswellbeing

Identifiers

PMID31906432
PMCPMC6982344

What OpenQuestion holds

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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.