Evidence map›Paper›PMID 38625277›Full record

ArticleEuropean transport research review2022

Informing about the invisible: communicating en route air pollution and noise exposure to cyclists and pedestrians using focus groups.

Heike Marquart

Abstract read
In one paragraph

Article in European transport research review, 2022. 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

1 author.

Heike MarquartInstitute of Transport Research, German Aerospace Center (DLR) Berlin, Rudower Chaussee 7, 12489 Berlin, Germany.ORCID 0000-0003-1561-8543

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Active mobility and public transport are considered beneficial for health and wellbeing and valuable for climate change mitigation. However, cyclists and pedestrians have high air pollution and noise exposure alongside traffic, which adversely impact health and wellbeing. The measured exposure can differ from the perceived exposure, hence, communicating en route exposure is crucial. Therefore, this study investigates how to communicate route-based exposure to cyclists and pedestrians and explores if exposure communication, e.g. via smartphones, is worthwhile for healthy and pleasant commute. It is investigated how exposure feedback influences the motivation to protect oneself and how exposure information should be designed. Three focus groups with 20 cyclists/pedestrians living in Berlin, Germany, were conducted. Based on Protection Motivation Theory and Environmental Health Literacy concept, (1) experiences and practices after recognizing exposure were discussed and (2) information needs and communication strategies were developed. The results reveal a feeling of helplessness regarding the ubiquity and uncertainty of pollution and a heightened threat appraisal. Anger, anxiety and rejection were stated. Making sense of pollution levels and protective alternatives were central. A healthy routing app, including also pleasant route factors, was desired. However, information provision was also denied. Participants argued the responsibility should not be left to the commuters and planning for exposed road users would be crucial. Information provision may not be worthwhile if planning authorities do not provide healthy alternatives. People-centered approaches for tackling air pollution and noise exposure en route should be investigated further.

Indexed as

Air pollutionEnvironmental health literacyFeedbackInformationNoise pollutionPersonal exposure

Identifiers

PMID38625277
PMCPMC9643997

What OpenQuestion holds

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LicenceCC BY
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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.