Evidence map›Paper›PMID 37204981›Full record

ArticleIndian journal of psychiatry2023

The emotional facial recognition performance of Chinese patients with schizophrenia: An event-related potentials study.

Yangjun Zhang, Ding Zhao, Jianfan Wu, Lixin Lin, Jiawu Ji

Open access · diamondAbstract read
In one paragraph

Article in Indian journal of psychiatry, 2023. 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
0.5field-weighted citation impact, top 39% of its field
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, 3 citations in OpenAlex.

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 at 1 institution in 1 country.

Yangjun ZhangDepartment of Psychiatry, Fujian Medical University Affiliated Fuzhou Neuropsychiatric Hospital, Fuzhou, China.
Ding ZhaoDepartment of Psychiatry, Fujian Medical University Affiliated Fuzhou Neuropsychiatric Hospital, Fuzhou, China.
Jianfan WuDepartment of Psychiatry, Fujian Medical University Affiliated Fuzhou Neuropsychiatric Hospital, Fuzhou, China.
Lixin LinDepartment of Psychiatry, Fujian Medical University Affiliated Fuzhou Neuropsychiatric Hospital, Fuzhou, China.
Jiawu JiDepartment of Psychiatry, Fujian Medical University Affiliated Fuzhou Neuropsychiatric Hospital, Fuzhou, China.
Fujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with schizophrenia have deficits in identifying and recognizing emotional facial expressions. Aim: This study aimed to explore the event-related potential (ERP) responses of patients with schizophrenia (SZ) and healthy controls (HC) using the Chinese Facial Affective Picture System (CFAPS). Methods: This study included 30 SZs and 31 HCs. We asked them to complete the task based on the oddball paradigm, in which three emotional faces (happy, fearful, and neutral) were used as target stimuli. Additionally, the amplitude and latency of the N170 component and the P300 component were recorded synchronously. Results: Compared with HCs, SZs had significantly smaller amplitudes of N170 and P300 to all facial expressions. The pairwise comparison revealed that fearful faces could trigger a significantly larger P300 amplitude in HCs than neutral faces, while the such a difference was not found in SZs. Conclusion: These findings indicated that SZs had a noticeable deficiency in the structural coding of face recognition and available attentional resources.

Indexed as

Chinese facesemotional facesevent-related potentialschizophrenia

Identifiers

PMID37204981
PMCPMC10187868
OpenAlexW4323025114

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.