Evidence map›Paper›PMID 40255868›Full record

ArticleEnvironmental epidemiology (Philadelphia, Pa.)2025

Military aircraft noise and drug administrations in psychiatric patients: Follow-up and in-depth case-time series analysis.

Benedikt Wicki, Danielle Vienneau, Beat Schäffer, Thomas J Müller, Charlotte Pervilhac, Martin Röösli

Abstract read
In one paragraph

Article in Environmental epidemiology (Philadelphia, Pa.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Benedikt WickiSwiss TPH (Swiss Tropical and Public Health Institute), Allschwil, Switzerland.ORCID https://orcid.org/0000-0003-4906-7719
Danielle VienneauSwiss TPH (Swiss Tropical and Public Health Institute), Allschwil, Switzerland.
Beat SchäfferEmpa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland.
Thomas J MüllerTranslational Research Centre, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
Charlotte PervilhacPrivate Clinic Meiringen, Meiringen, Switzerland.
Martin RöösliSwiss TPH (Swiss Tropical and Public Health Institute), Allschwil, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In a previous study, we demonstrated that military aircraft noise increases the short-term probability of on-demand drug administrations in patients in a psychiatric clinic located in close proximity to a military airfield. The aim of this article was to: (1) apply refined exposure assessment methods; (2) compare results for various noise exposure measures reflecting different assumptions about outdoor-indoor noise attenuation and explore possible effect thresholds; and (3) conduct an independent validation study with 1 year of more recent follow-up. Methods: We conducted noise measurements during 1 year at the clinic to validate the modeled noise exposure of hourly military aircraft noise (equivalent continuous sound pressure level, Results: There was a moderate (Pearson's Conclusion: Our results suggest that predicting indoor noise levels and the addition of informed background noise estimates improves specificity in the exposure assessment and likely provides more reliable exposure-response associations. With additional follow-up data, we could confirm our previous findings that loud noise events can have acute effects on psychiatric patients' sedative drug consumption.

Indexed as

Aircraft noiseExposure assessmentMental healthPsychiatry

Identifiers

PMID40255868
PMCPMC12005937

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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.