Evidence map›Paper›PMID 41144434›Full record

ArticlePloS one2025

Validation of the Keen Eye computer-based method for diagnosing visual neglect using a dual-task paradigm.

Elizaveta Vasyura, Maria Kovyazina, Georgiy Stepanov, Olga Russkikh, Daria Terentiy, Victoria Propustina, Anatoliy Skvortsov, Nataliya Varako, Svetlana Vasilyeva, Vadim Daminov and 1 more

Abstract readValidation Study
In one paragraph

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

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

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

11 authors.

Elizaveta VasyuraFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.ORCID https://orcid.org/0009-0008-5472-9100
Maria KovyazinaFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.
Georgiy StepanovFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.
Olga RusskikhState Autonomous Healthcare Institution of the Perm Region "City Clinical Hospital No 4", Perm, Russia.
Daria TerentiyFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.ORCID https://orcid.org/0009-0002-9186-9993
Victoria PropustinaFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.ORCID https://orcid.org/0009-0009-0133-3142
Anatoliy SkvortsovFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.
Nataliya VarakoFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.ORCID https://orcid.org/0000-0002-8310-8169
Svetlana VasilyevaFederal Scientific Center of Psychological and Multidisciplinary Research, Moscow, Russia.
Vadim DaminovMedical Rehabilitation Clinic, Pirogov National Medical and Surgical Center, Moscow, Russia.
Yuri ZinchenkoFaculty of Psychology, Lomonosov Moscow State University, Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visual neglect is a common and disabling consequence of right hemisphere damage. Standard paper-and-pencil assessments may fail to detect subtle or well-compensated cases of neglect, especially under low attentional demands. This study presents and validates the Keen Eye computer-based method for diagnosing neglect using a dual-task paradigm. The method involves the simultaneous detection of lateralized visual targets and identification of centrally presented digits, increasing attentional load and sensitivity to spatial biases. We tested 102 patients with right hemisphere damage (38 with neglect, 64 without) using a predefined set of target positions that systematically varied across the visual field. Classification models based on error patterns and asymmetry coefficients demonstrated high sensitivity and specificity in distinguishing patients with neglect. The method also revealed quadrant-specific and vertically biased omissions. The findings support the utility of attention-demanding computer-based tasks for improving diagnostic precision in visual neglect and suggest potential for identifying subclinical or hidden neglect profiles.

Indexed as

Diagnosis, Computer-AssistedPerceptual DisordersAdultAgedAged, 80 and overAttentionFemaleHumansMaleMiddle AgedVisual Fields

Identifiers

PMID41144434
PMCPMC12558459

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.