Evidence map›Paper›PMID 33924939›Full record

ArticleJournal of clinical medicine2021

Facial Affect Recognition by Patients with Schizophrenia Using Human Avatars.

Nora I Muros, Arturo S García, Cristina Forner, Pablo López-Arcas, Guillermo Lahera, Roberto Rodriguez-Jimenez, Karen N Nieto, José Miguel Latorre, Antonio Fernández-Caballero, Patricia Fernández-Sotos

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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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

10 authors at 5 institutions in 1 country.

Nora I MurosServicio de Salud Mental, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain.
Arturo S GarcíaDepartamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, 02071 Albacete, Spain.ORCID 0000-0003-0671-324X
Cristina FornerServicio de Salud Mental, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain.
Pablo López-ArcasServicio de Anestesiología, Reanimación y Unidad del Dolor, Hospital General de Villarrobledo, 02600 Villarobledo, Spain.
Guillermo LaheraDepartamento de Medicina y Especialidades Médicas, Universidad de Alcalá, 28805 Madrid, Spain.ORCID 0000-0002-6152-3564
Roberto Rodriguez-JimenezCIBERSAM (Biomedical Research Networking Centre in Mental Health), 28029 Madrid, Spain.ORCID 0000-0003-2251-7249
Karen N NietoServicio de Salud Mental, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain.
José Miguel LatorreDepartamento de Psicología, Universidad de Castilla-La Mancha, 02071 Albacete, Spain.ORCID 0000-0002-6159-5074
Antonio Fernández-CaballeroDepartamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, 02071 Albacete, Spain.ORCID 0000-0002-8211-0398
Patricia Fernández-SotosServicio de Salud Mental, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain.
Complejo Hospitalario Universitario de Albacete · ESCentro de Investigación Biomédica en Red de Salud Mental · ESUniversity of Castilla-La Mancha · ESUniversidad Complutense de Madrid · ESUniversidad de Alcalá · ES

Funding

Agencia Estatal de Investigación EQC2019-006063-PAgencia Estatal de Investigación PID2020-115220RB-C21Instituto de Salud Carlos III PI16/00359Instituto de Salud Carlos III PI19/00766Madrid Regional Government S2017/BMD-3740
6 · The paper itself

Abstract

People with schizophrenia have difficulty recognizing the emotions in the facial expressions of others, which affects their social interaction and functioning in the community. Static stimuli such as photographs have been used traditionally to examine deficiencies in the recognition of emotions in patients with schizophrenia, which has been criticized by some authors for lacking the dynamism that real facial stimuli have. With the aim of overcoming these drawbacks, in recent years, the creation and validation of virtual humans has been developed. This work presents the results of a study that evaluated facial recognition of emotions through a new set of dynamic virtual humans previously designed by the research team, in patients diagnosed of schizophrenia. The study included 56 stable patients, compared with 56 healthy controls. Our results showed that patients with schizophrenia present a deficit in facial affect recognition, compared to healthy controls (average hit rate 71.6% for patients vs 90.0% for controls). Facial expressions with greater dynamism (compared to less dynamic ones), as well as those presented from frontal view (compared to profile view) were better recognized in both groups. Regarding clinical and sociodemographic variables, the number of hospitalizations throughout life did not correlate with recognition rates. There was also no correlation between functioning or quality of life and recognition. A trend showed a reduction in the emotional recognition rate as a result of increases in Positive and Negative Syndrome Scale (PANSS), being statistically significant for negative PANSS. Patients presented a learning effect during the progression of the task, slightly greater in comparison to the control group. This finding is relevant when designing training interventions for people with schizophrenia. Maintaining the attention of patients and getting them to improve in the proposed tasks is a challenge for today's psychiatry.

Indexed as

dynamic virtual humansemotion recognitionfacial affect recognitionschizophreniasocial cognition

Identifiers

PMID33924939
PMCPMC8124197
OpenAlexW3157076295

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.