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Facial Affect Recognition by Patients with Schizophrenia Using Human Avatars

dc.contributor.authorMuros, Nora I.
dc.contributor.authorGarcía, Arturo S.
dc.contributor.authorForner, Cristina
dc.contributor.authorLópez Arcas, Pablo
dc.contributor.authorLahera, Guillermo
dc.contributor.authorRodríguez Jiménez, Roberto
dc.contributor.authorNieto, Karen N.
dc.contributor.authorLatorre, José Miguel
dc.contributor.authorFernández Caballero, Antonio
dc.contributor.authorFernández Sotos, Patricia
dc.date.accessioned2023-06-17T08:24:01Z
dc.date.available2023-06-17T08:24:01Z
dc.date.issued2021-04-28
dc.description.abstractPeople 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.
dc.description.departmentDepto. de Medicina Legal, Psiquiatría y Patología
dc.description.facultyFac. de Medicina
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)/FEDER
dc.description.sponsorshipInstituto de Salud Carlos III (ISCIII)/FEDER
dc.description.sponsorshipComunidad de Madrid/ FEDER
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/71311
dc.identifier.doi10.3390/jcm10091904
dc.identifier.issn2077-0383
dc.identifier.officialurlhttps://doi.org/10.3390/jcm10091904
dc.identifier.relatedurlhttps://www.mdpi.com/2077-0383/10/9/1904/htm
dc.identifier.urihttps://hdl.handle.net/20.500.14352/6969
dc.issue.number9
dc.journal.titleJournal of Clinical Medicine
dc.language.isoeng
dc.page.initial1904
dc.publisherMPDI
dc.relation.projectIDEQC2019-006063-P and PID2020-115220RB-C21
dc.relation.projectIDPI16/00359, PI19/00766
dc.relation.projectIDAGES-CM 2-CM (S2017/BMD-3740)
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.keywordschizophrenia
dc.subject.keywordsocial cognition
dc.subject.keywordemotion recognition
dc.subject.keywordfacial affect recognition
dc.subject.keyworddynamic virtual humans
dc.subject.ucmPsiquiatría
dc.subject.ucmPsicología (Psicología)
dc.subject.unesco3211 Psiquiatría
dc.subject.unesco61 Psicología
dc.titleFacial Affect Recognition by Patients with Schizophrenia Using Human Avatars
dc.typejournal article
dc.volume.number10
dspace.entity.typePublication
relation.isAuthorOfPublication773f92bc-2db7-4bf8-ab49-1ac5c630b487
relation.isAuthorOfPublication.latestForDiscovery773f92bc-2db7-4bf8-ab49-1ac5c630b487

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