Evidence map›Paper›PMID 40303611›Full record

ArticleFrontiers in neuroscience2025

Assessment of visual function under various lighting conditions in a cohort of active older drivers: dimensionality and principal metrics.

Deyue Yu, Landon Perry, Thomas Kerwin, Jingzhen Yang, Zhong-Lin Lu

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

5 authors.

Deyue YuCollege of Optometry, The Ohio State University, Columbus, OH, United States.
Landon PerryCollege of Optometry, The Ohio State University, Columbus, OH, United States.
Thomas KerwinDriving Simulation Laboratory, The Ohio State University, Columbus, OH, United States.
Jingzhen YangCenter for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, United States.
Zhong-Lin LuDivision of Arts and Sciences, NYU Shanghai, Shanghai, China.

Funding

Efficient Assessment of Visual Deficits in Low VisionR01EY025658 · NEI · OHIO STATE UNIVERSITY · PI YU, DEYUE · 2016 to 2020
$1.9M
NEI NIH HHS R01 EY025658
6 · The paper itself

Abstract

Purpose: While traditional driving ability evaluations typically assess visual acuity (VA) under photopic conditions, visual functions other than photopic VA also play a crucial role in driving. For older individuals, age-related vision change can impact driving abilities, particularly under mesopic lighting conditions with glare during nighttime driving. This study aims to investigate how visual functions vary across different lighting conditions, examine their correlations, and identify the principal visual function metrics that enable a more comprehensive assessment of active older drivers. Methods: Twenty active older drivers (aged 63 to 87 years; mean = 70 years) participated. All possessed valid driver's licenses, drove at least once per week, and did not use any low vision aids for driving. Six participants had undergone cataract surgery. Participants completed a battery of visual tasks with their habitual correction for daily driving. VA, contrast sensitivity function (CSF) and visual field map (VFM) were measured under photopic and mesopic conditions using the qVA, qCSF and qVFM procedures. Additionally, VA and CSF were assessed in the presence of glare under mesopic condition. Correlations and principal component analysis (PCA) were conducted to identify principal visual function metrics. Results: VA and CSF exhibited variation across lighting conditions ( Conclusion: Using a PCA-based selection approach, the minimal set of visual function metrics for evaluating visual function in active older drivers was identified. These findings provide valuable insights for establishing optimal clinical outcome measures for this population.

Indexed as

agingdrivingglaremesopic visionvisual function

Identifiers

PMID40303611
PMCPMC12037606

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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.