Evidence map›Paper›PMID 35915231›Full record

ArticleScientific reports2022

Mesopic conditions optimise the detection of visual function loss in drivers with simulated media opacity.

Frederick A Asare, Roger S Anderson, Pádraig J Mulholland, Julie-Anne Little

Abstract read
In one paragraph

Article in Scientific reports, 2022. 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. Observational
  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

4 authors.

Frederick A AsareCentre for Optometry and Vision Science, Biomedical Sciences Research Institute, Ulster University, Coleraine, UK. asare-f@ulster.ac.uk.
Roger S AndersonCentre for Optometry and Vision Science, Biomedical Sciences Research Institute, Ulster University, Coleraine, UK.
Pádraig J MulhollandCentre for Optometry and Vision Science, Biomedical Sciences Research Institute, Ulster University, Coleraine, UK.
Julie-Anne LittleCentre for Optometry and Vision Science, Biomedical Sciences Research Institute, Ulster University, Coleraine, UK.

Funding

Department of Health
6 · The paper itself

Abstract

Drivers have different visual demands across varying contrast and luminance conditions. However, vision assessments for driving are typically conducted under photopic conditions. This study investigated the sensitivity of photopic and mesopic conditions to detect contrast sensitivity (CS) loss in drivers with simulated media opacities. CS was measured in forty-seven healthy drivers aged 18-50 years (mean ± SD: 25.5 ± 6.5) under photopic and mesopic-adapted luminance levels with the Pelli-Robson chart and the Mesotest II (without glare). Media opacities were simulated using white-opacity containing Lee Fog filters (1-5) and CS measured in a randomised order. A significant (p < 0.001) reduction in photopic CS (logCS) was measured with the Pelli-Robson chart only when media opacity was simulated with Fog filter 5 (1.53 ± 0.15, 2.8 triplets reduction) compared to baseline (1.95 ± 0.03). Mean mesopic CS demonstrated a significant (all p < 0.001) reduction from baseline (1.67 ± 0.14) for Fog filters 3 (1.4 triplets, 1.45 ± 0.16), 4 (2.4 triplets, 1.31 ± 0.14) and 5 (4.3 triplets, 1.02 ± 0.15). For Mesotest II, only Fog filter 5 produced a significant reduction (0.10 ± 0.09; p < 0.001) in mean mesopic CS from baseline (0.30 ± 0.01). Mesopic CS is more vulnerable to different levels of simulated media opacity, hence should be considered clinically when assessing visual function in older drivers at risk of media opacity.

Indexed as

Automobile DrivingColor VisionContrast SensitivityMesopic Vision

Identifiers

PMID35915231
PMCPMC9343380

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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.