scholarly journals Usability of a psychotherapeutic interactive gaming tool used in Facial Emotion Recognition for people with Schizophrenia (Preprint)

2018 ◽  
Author(s):  
Ingrid Tortadès ◽  
Roberto Gonzalez ◽  
Francesc Alpiste ◽  
Joaquin Fernandez ◽  
Jordi Torner ◽  
...  

UNSTRUCTURED The interactive software “Feeling Master” (a Cartoon Facial Recognition Tool) was developed to investigate the deficit in facial emotion recognition (FER) with a sample of patients with schizophrenia in a pilot project framework. 24 persons with schizophrenia and 17 healthy control (HC) subjects completed the “Feeling Master” including five emotions (happiness, sadness, anger, fear and surprise). Regarding the group with schizophrenia they were evaluated with the Personal and Situational Attribution Questionnaire (IPSAQ) and the Hinting Task (Theory of Mind) to evaluate social cognition. Descriptive data showed suitable usability, adaptability, effectiveness and efficiency of “feeling master”. Patients with schizophrenia showed impairments in emotion recognition. The individuals with schizophrenia remained slower than the HC in the recognition of each emotion. Regarding the impairment in the recognition of each emotion we only have found significant error rates on fear discrimination (P=.07). And the correlations between correct response on the “Feeling Master” and the Hinting Task showed significant values in the correlation of surprise and Theory of Mind (P=.46). In conclusion, the study puts forward the usability of the “feeling master” in FER for people with schizophrenia. These findings lend support to the notion that difficulties in emotion recognition are more prevalent in people with schizophrenia, and those are associated with an imparment in ToM, suggesting the potential utility of the FER in the rehabilitation of people with schizophrenia.

2019 ◽  
Author(s):  
Ingrid Tortadès ◽  
Roberto Gonzalez ◽  
Francesc Alpiste ◽  
Joaquín Fernandez ◽  
Jordi Torner ◽  
...  

BACKGROUND Emotional Recognition (ER) is one of the areas most affected in people with schizophrenia. However, there are no software tools available for the assessment of ER. The interactive software program ‘Feeling Master’ (a cartoon facial recognition tool) was developed to investigate the deficit in facial emotion recognition (FER) with a sample of patients with schizophrenia in a pilot project framework. OBJECTIVE The aim of the study was to test the usability of ‘Feeling Master’ as a psychotherapeutic interactive gaming tool for the assessment of emotional recognition in people with schizophrenia compared with healthy people, and the relationship between FER, attributional style and theory of mind. METHODS Nineteen individuals with schizophrenia and 17 healthy control (HC) subjects completed the ‘Feeling Master’ including five emotions (happiness, sadness, anger, fear, and surprise). Regarding the group with schizophrenia they were evaluated with the Personal and Situational Attribution Questionnaire (IPSAQ) and the Hinting Task (Theory of Mind) to evaluate social cognition. RESULTS Patients with schizophrenia showed impairments in emotion recognition and they remained slower than the HC in the recognition of each emotion (P<.001). Regarding the impairment in the recognition of each emotion we only found a trend toward significance in error rates on fear discrimination (P=.07). And the correlations between correct response on the ‘Feeling Master’ and the hinting task showed significant values in the correlation of surprise and theory of mind (P=.046). CONCLUSIONS In conclusion, the study puts forward the usability of the ‘Feeling Master’ in FER for people with schizophrenia. These findings lend support to the notion that difficulties in emotion recognition are more prevalent in people with schizophrenia, and that these are associated with impairment in ToM, suggesting the potential utility of the FER in the rehabilitation of people with schizophrenia.


2021 ◽  
Vol 11 (3) ◽  
pp. 214
Author(s):  
Roberto Pablo González ◽  
Ingrid Tortadès ◽  
Francesc Alpiste ◽  
Joaquín Fernandez ◽  
Jordi Torner ◽  
...  

The objective of the study was to test the usability of ‘Feeling Master’ as a psychotherapeutic interactive gaming tool with LEGO cartoon faces showing the five basic emotions, for the assessment of emotional recognition in people with schizophrenia in comparison with healthy controls, and the relationship between face affect recognition (FER), attributional style, and theory of mind (ToM), which is the ability to understand the potential mental states and intentions of others. Nineteen individuals with schizophrenia (SZ) and 17 healthy control (HC) subjects completed the ‘Feeling Master’ that includes five basic emotions. To assess social cognition, the group with schizophrenia was evaluated with the Personal and Situational Attribution Questionnaire (IPSAQ) for the assessment of attributional style and the Hinting Task (ToM). Patients with SZ showed significant impairments in emotion recognition and their response time appeared to be slower than the HC in the recognition of each emotion. Taking into account the impairment in the recognition of each emotion, we only found a trend toward significance in error rates on fear recognition. The correlations between correct response on the ‘Feeling Master’ and the hinting task appeared to be significant in the correlation of surprise and theory of mind. In conclusion, this study demonstrated that the ‘Feeling Master’ could be useful for the evaluation of FER in people with schizophrenia. These results sustain the notion that impairments in emotion recognition are more prevalent in people with schizophrenia and that these are related with impairment in ToM.


2019 ◽  
Vol 25 (08) ◽  
pp. 884-889 ◽  
Author(s):  
Sally A. Grace ◽  
Wei Lin Toh ◽  
Ben Buchanan ◽  
David J. Castle ◽  
Susan L. Rossell

Abstract Objectives: Patients with body dysmorphic disorder (BDD) have difficulty in recognising facial emotions, and there is evidence to suggest that there is a specific deficit in identifying negative facial emotions, such as sadness and anger. Methods: This study investigated facial emotion recognition in 19 individuals with BDD compared with 21 healthy control participants who completed a facial emotion recognition task, in which they were asked to identify emotional expressions portrayed in neutral, happy, sad, fearful, or angry faces. Results: Compared to the healthy control participants, the BDD patients were generally less accurate in identifying all facial emotions but showed specific deficits for negative emotions. The BDD group made significantly more errors when identifying neutral, angry, and sad faces than healthy controls; and were significantly slower at identifying neutral, angry, and happy faces. Conclusions: These findings add to previous face-processing literature in BDD, suggesting deficits in identifying negative facial emotions. There are treatment implications as future interventions would do well to target such deficits.


2011 ◽  
Vol 186 (1) ◽  
pp. 80-84 ◽  
Author(s):  
Yang-Tae Kim ◽  
Do-Hoon Kwon ◽  
Yongmin Chang

2011 ◽  
Vol 189 (3) ◽  
pp. 379-384 ◽  
Author(s):  
Diego Javier Martino ◽  
Sergio Adrián Strejilevich ◽  
Guillermo Fassi ◽  
Eliana Marengo ◽  
Ana Igoa

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S163-S163
Author(s):  
Elin Kjellenberg ◽  
Stefan Winblad

Abstract Background Psychotic disorders are associated with impaired facial emotion recognition (FER) and poor functional outcome. Most studies regarding facial emotion recognition have focused on schizophrenia. The aim of this study was to explore FER in patients with different psychotic disorders at psychiatric outpatient facilities. The intention was also to examine if patients diagnosed with schizophrenia differed from patients diagnosed with other psychotic disorders in the ability to recognize facial emotions. Methods FER was examined in forty outpatients, evenly divided between schizophrenia and other psychotic disorders and 33 healthy control persons. The ability to recognize facial emotions was assessed with The Facially Expressed Emotion Labelling (FEEL). To assess the severity of psychotic symptoms in the patient group The Structured Clinical Interview for Symptoms of Remission (SCI-SR) was used. Results Patients performed significantly worse than healthy controls (p&lt;.001, r =-.28) in recognizing facial emotions in general, including expressions of fear, disgust and sadness. Subjects with a schizophrenia diagnosis performed poorer than healthy controls when depicting fear (p&lt;.01, r=.45) or anger (p=.026, r=.36). Compared to other psychotic disorders they were less accurate in recognizing anger (p=.036, r=-.040). We did not find any significant differences between patients with other psychotic disorders and healthy controls in FER. Furthermore, patients performed significantly slower on the FEEL test (p&lt;.001, r=0.44), including both patients with a schizophrenia diagnosis and other psychotic disorders as compared to healthy controls. Patients diagnosed with schizophrenia showed significantly more psychotic symptoms (p= .001, r= -.53). However, there were no significant differences between patients in remission (40 %) and patients with more severe psychotic symptoms regarding the FEEL measures. Discussion In this study, patients with psychotic disorders performed less accurately and slower on the FEEL task as compared to healthy control persons. Patients diagnosed with schizophrenia tended to exhibit more difficulties. The results from this between-group comparison should however be interpreted with caution due to limited statistical power. Since no significant difference in FEEL score was demonstrated between patients in remission and patients suffering from more severe psychotic symptoms, it could be suggested that deficits in FER are independent of current psychotic symptoms. Impaired facial emotion recognition ability may negatively influence social interaction and functional outcome and the results from this study indicate that FER should be further explored in larger cohorts of outpatients with different psychotic disorders.


2014 ◽  
Vol 11 (2) ◽  
pp. 105 ◽  
Author(s):  
Seul Bee Lee ◽  
Se Jun Koo ◽  
Yun Young Song ◽  
Mi Kyung Lee ◽  
Yu-Jin Jeong ◽  
...  

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