Evidence map›Paper›PMID 38815257›Full record

ArticleJMIR mental health2024

Tablet-Based Cognitive and Eye Movement Measures as Accessible Tools for Schizophrenia Assessment: Multisite Usability Study.

Kentaro Morita, Kenichiro Miura, Atsuhito Toyomaki, Manabu Makinodan, Kazutaka Ohi, Naoki Hashimoto, Yuka Yasuda, Takako Mitsudo, Fumihiro Higuchi, Shusuke Numata and 14 more

Abstract readMulticenter Study
In one paragraph

Article in JMIR mental health, 2024. 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

24 authors.

Kentaro MoritaDepartment of Rehabilitation, The University of Tokyo Hospital, Bunkyo-ku Tokyo, Japan.ORCID 0000-0002-0490-5013
Kenichiro MiuraDepartment of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan.ORCID 0000-0002-3722-7837
Atsuhito ToyomakiDepartment of Psychiatry, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.ORCID 0000-0001-9333-8833
Manabu MakinodanDepartment of Psychiatry, Nara Medical University, Kashihara, Japan.ORCID 0000-0003-4339-9413
Kazutaka OhiDepartment of Psychiatry, Graduate School of Medicine, Gifu University, Gifu, Japan.ORCID 0000-0001-9577-9640
Naoki HashimotoDepartment of Psychiatry, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.ORCID 0000-0001-8311-7148
Yuka YasudaLife Grow Brilliant Mental Clinic, Medical Corporation Foster, Kita-ku Osaka, Japan.ORCID 0000-0002-2746-1590
Takako MitsudoDivision of Clinical Research, National Hospital Organization Hizen Psychiatric Center, Kanzaki-gun, Japan.ORCID 0000-0002-4123-4247
Fumihiro HiguchiDepartment of Neuroscience, Division of Neuropsychiatry, Yamaguchi University School of Medicine, Ube City, Japan.ORCID 0000-0001-7966-2928
Shusuke NumataDepartment of Psychiatry, Graduate School of Biomedical Science, Tokushima University, Tokushima, Japan.ORCID 0009-0009-0697-8871
Akiko YamadaDepartment of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Sakyo-ku Kyoto, Japan.ORCID 0009-0002-8464-5844
Yohei AokiHealthcare Innovation Group, Future Corporation, Shinagawa-ku Tokyo, Japan.ORCID 0009-0002-0445-0685
Hiromitsu HondaHealthcare Innovation Group, Future Corporation, Shinagawa-ku Tokyo, Japan.ORCID 0009-0009-1025-1747
Ryo MizuiDepartment of Psychiatry, Nara Medical University, Kashihara, Japan.ORCID 0009-0008-9836-2128
Masato HondaDepartment of Psychiatry, Nara Medical University, Kashihara, Japan.ORCID 0009-0003-1103-7204
Daisuke FujikaneDepartment of Psychiatry, Graduate School of Medicine, Gifu University, Gifu, Japan.ORCID 0009-0009-0705-5710
Junya MatsumotoDepartment of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan.ORCID 0000-0003-4228-3208
Naomi HasegawaDepartment of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan.ORCID 0000-0002-3834-4859
Satsuki ItoDepartment of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan.ORCID 0000-0003-4720-3166
Hisashi AkiyamaDepartment of Psychiatry, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.ORCID 0009-0000-5193-2754
Toshiaki OnitsukaNational Hospital Organization Sakakibara Hospital, Tsu, Japan.ORCID 0000-0001-6583-6405
Yoshihiro SatomuraDepartment of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku Tokyo, Japan.ORCID 0000-0002-2495-6782
Kiyoto KasaiDepartment of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku Tokyo, Japan.ORCID 0000-0002-4443-4535
Ryota HashimotoDepartment of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan.ORCID 0000-0002-5941-4238

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchizophrenia is a complex mental disorder characterized by significant cognitive and neurobiological alterations. Impairments in cognitive function and eye movement have been known to be promising biomarkers for schizophrenia. However, cognitive assessment methods require specialized expertise. To date, data on simplified measurement tools for assessing both cognitive function and eye movement in patients with schizophrenia are lacking.

objectiveThis study aims to assess the efficacy of a novel tablet-based platform combining cognitive and eye movement measures for classifying schizophrenia.

methodsForty-four patients with schizophrenia, 67 healthy controls, and 41 patients with other psychiatric diagnoses participated in this study from 10 sites across Japan. A free-viewing eye movement task and 2 cognitive assessment tools (Codebreaker task from the THINC-integrated tool and the CognitiveFunctionTest app) were used for conducting assessments in a 12.9-inch iPad Pro. We performed comparative group and logistic regression analyses for evaluating the diagnostic efficacy of the 3 measures of interest.

resultsCognitive and eye movement measures differed significantly between patients with schizophrenia and healthy controls (all 3 measures; P<.001). The Codebreaker task showed the highest classification effectiveness in distinguishing schizophrenia with an area under the receiver operating characteristic curve of 0.90. Combining cognitive and eye movement measures further improved accuracy with a maximum area under the receiver operating characteristic curve of 0.94. Cognitive measures were more effective in differentiating patients with schizophrenia from healthy controls, whereas eye movement measures better differentiated schizophrenia from other psychiatric conditions.

conclusionsThis multisite study demonstrates the feasibility and effectiveness of a tablet-based app for assessing cognitive functioning and eye movements in patients with schizophrenia. Our results suggest the potential of tablet-based assessments of cognitive function and eye movement as simple and accessible evaluation tools, which may be useful for future clinical implementation.

Indexed as

Computers, HandheldSchizophreniaAdultCognitionCognitive DysfunctionEye Movement MeasurementsEye MovementsFemaleHumansJapanMaleMiddle AgedNeuropsychological Testscognitive functiondiagnostic biomarkersdigital health toolseye movementschizophrenia

Identifiers

PMID38815257
PMCPMC11176872

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