Facial emotion recognition and its association with quality of life and socio-occupational functioning in patients with bipolar disorder and their first-degree relatives

2021 ◽  
pp. 102843
Author(s):  
Swapnil G Nigam ◽  
Sonia Shenoy ◽  
PSVN Sharma ◽  
Rishikesh V Behere
2018 ◽  
Vol 52 (3) ◽  
pp. 110-116
Author(s):  
Vinuprasad Venugopalan ◽  
Manas Elkal ◽  
Rishikesh V Behere ◽  
Samir K Praharaj ◽  
Haridas Kanaradi

1995 ◽  
Vol 16 (5) ◽  
pp. 383-391 ◽  
Author(s):  
Elliott W. Simon ◽  
Marvin Rosen ◽  
Elliot Grossman ◽  
Edward Pratowski

2010 ◽  
Vol 16 (3) ◽  
pp. 474-483 ◽  
Author(s):  
LAURA A. BROWN ◽  
ALEX S. COHEN

AbstractFacial emotion recognition deficits have been widely investigated in individuals with schizophrenia; however, it remains unclear whether these deficits reflect a trait-like vulnerability to schizophrenia pathology present in individuals at risk for the disorder. Although some studies have investigated emotion recognition in this population, findings have been mixed. The current study uses a well-validated emotion recognition task, a relatively large sample, and examines the relationship between emotion recognition, symptoms, and overall life quality. Eighty-nine individuals with psychometrically defined schizotypy and 27 controls completed the Schizotypal Personality Questionnaire, Penn Emotion Recognition Test, and a brief version of Lehman’s Quality of Life Interview. In addition to labeling facial emotions, participants rated the valence of faces using a Likert rating scale. Individuals with schizotypy were significantly less accurate than controls when labeling emotional faces, particularly neutral faces. Within the schizotypy sample, both disorganization symptoms and lower quality of life were associated with a bias toward perceiving facial expressions as more negative. Our results support previous research suggesting that poor emotion recognition is associated with vulnerability to psychosis. Although emotion recognition appears unrelated to symptoms, it probably operates by means of different processes in those with particular types of symptoms. (JINS, 2010, 16, 474–483.)


2018 ◽  
Vol 264 ◽  
pp. 354-360 ◽  
Author(s):  
Umesh Thonse ◽  
Rishikesh V. Behere ◽  
Samir Kumar Praharaj ◽  
Podila Sathya Venkata Narasimha Sharma

2016 ◽  
Vol 68 ◽  
pp. 18-23 ◽  
Author(s):  
Francy de Brito Ferreira Fernandes ◽  
Alexandre Duarte Gigante ◽  
Mariangeles Berutti ◽  
José Antônio Amaral ◽  
Karla Mathias de Almeida ◽  
...  

2021 ◽  
Author(s):  
Lisa S. Furlong ◽  
Susan L. Rossell ◽  
James A. Karantonis ◽  
Vanessa L. Cropley ◽  
Matthew Hughes ◽  
...  

2014 ◽  
Vol 153 (1-3) ◽  
pp. 32-37 ◽  
Author(s):  
Alexander R. Daros ◽  
Anthony C. Ruocco ◽  
James L. Reilly ◽  
Margret S.H. Harris ◽  
John A. Sweeney

2020 ◽  
Vol 65 ◽  
pp. 9-14
Author(s):  
Selen Işık Ulusoy ◽  
Şeref Abdurrahman Gülseren ◽  
Nermin Özkan ◽  
Cüneyt Bilen

2016 ◽  
Vol 22 (6) ◽  
pp. 652-661 ◽  
Author(s):  
Nicole Joshua ◽  
Tamsyn E. Van Rheenen ◽  
David J Castle ◽  
Susan L. Rossell

AbstractObjectives: Use of appropriate face processing strategies is important for facial emotion recognition, which is known to be impaired in schizophrenia (SZ) and bipolar disorder (BD). There is preliminary evidence of abnormalities in the use of face processing strategies in the former, but there has been no explicit attempt to assess face processing in patients with BD. Methods: Twenty-eight BD I, 28 SZ, and 28 healthy control participants completed tasks assessing featural and configural face processing. The facial inversion effect was used as a proxy of second order configural face processing and compared to featural face processing performance (which is known to be relatively less affected by facial inversion). Results: Controls demonstrated the usual second-order inversion pattern. In the BD group, the absence of a second-order configural inversion effect in the presence of a disproportionate bias toward a featural inversion effect was evident. Despite reduced accuracy performance in the SZ group compared to controls, this group unexpectedly showed a normal second-order configural accuracy inversion pattern. This was in the context of a reverse inversion effect for response latency, suggesting a speed-versus-accuracy trade-off. Conclusions: To our knowledge, this is the first study to explicitly examine and contrast face processing in BD and SZ. Our findings indicate a generalized impairment on face processing tasks in SZ, and the presence of a second-order configural face processing impairment in BD. It is possible that these face processing impairments represent a catalyst for the facial emotion recognition deficits that are commonly reported in the literature. (JINS, 2016, 22, 652–661)


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