Roberto Pablo González
This work presents the development and the assessment of Feeling Master, a novel psychotherapeutic interactive gaming application that uses cartoon stimuli to measure facial emotion recognition in schizophrenic patients. A pilot study among 24 patients with schizophrenia (PS) and 17 healthy control (HC) subjects was conducted to assess the usability of Feeling Master as a tool to measure facial emotion recognition ability in schizophrenic patients. The usability assessment of the application was based on three criteria: adaptability, effectiveness, and efficiency of the tool (Nielsen, 1994; Schwebel, McClure, & Severson, 2014). The study also attempted to determine whether people with schizophrenia would show emotion recognition deficits and if such deficits would vary among the basic emotions described by Ekman and Friesen (1971). Moreover, our team aimed to relate the results of facial emotion recognition within the schizophrenia group to clinical variables such as the Personal and Situational Attribution Questionnaire (IPSAQ). Descriptive data reveal that Feeling Master is a useful tool for measuring facial emotion recognition in patients with schizophrenia. Schizophrenia patients showed impairments in the emotions recognition. PS subjects remained slower than HC (Average time: F(1.38) = 15.1, p = 0.000). On the other hand, we did not find significant values for the overall emotion discrimination (average accuracy: F(1.38) = 0.733, p>0.05), but we found significant error rates for discrimination in fear: F=(1.38)=8.2, p < 0.007) ) using Fisher¿s exact test to compare errors between PS and HC groups. Using the Feeling Master tool, the performances of patients with schizophrenia were compared to those of healthy control volunteers on computerized tasks of emotion recognition, and the Personal and Situational Attribution Questionnaire (IPSAQ) was administered to determine whether emotion processing deficits were correlated with the attributional style. The correlations between correct response on the Feeling Master and Personal and Situational Attribution Questionnaire (IPSAQ) were not significant, but they showed interesting relations: Sad vs. External Situational Negative, Rho= 0.346, p=0.106; Sad vs. External Situational Positive, Rho=0.320, p=0.136. Finally, the Technology Acceptance Model (TAM) was used to study the acceptance among professionals of the Feeling Master as a tool to measure facial emotion recognition in rehabilitation psychiatric units. The TAM study was conducted among 66 experienced mental health professionals. Except for Perceived Ease of Use (PEOU), which has a high value, the other TAM construct values (i.e., Perceived usefulness (PU), Attitude Toward Using (ATU), Enjoyment (E), and Behavioral Intention (BI)) should be improved. In conclusion, the study puts forward the usability of a novel, psychotherapeutic interactive gaming tool used in Facial Emotion Recognition for people with schizophrenia. These findings lend support to the notion that difficulties in emotion recognition are associated with key cognitive deficits among individuals with schizophrenia. These findings were consistent with previous studies.
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