Error patterns of facial emotion recognition in patients with schizophrenia.

• An error-based detectability index was proposed for unbiased error patterns. • Four error patterns were found in patients with schizophrenia. • Corresponding interventions may be provided based on the four error patterns. • The newly proposed detectability may be an indicator of treatment outcome. • Cross-validations are warranted for the suitability as an outcome measurement. Error patterns of facial emotion recognition (FER) indicate how individuals misinterpret others' facial expressions, which helps clinicians to manage related deficits. However, previous investigations are limited and may have been biased due to methodological issues (e.g., no consideration of response bias). This study aimed to propose a detectability index (d') for adjusting response bias and examine the error patterns of FER in patients with schizophrenia. Responses to 168 photos showing seven basic emotions, obtained from 351 patients with schizophrenia and 101 healthy adults, were extracted from a previous study. The differences in the d' s between the two groups (Δ d') were calculated to examine the error patterns of FER among the seven emotions. The findings were generally overlapped with those identified by the traditional confusion matrix. Four error patterns were found. First, the patients were insensitive to some negative emotions (i.e., sadness [ Δ d' = 0.83] and fear [ Δ d' = 0.72]). Second, they misrecognized happy faces as showing negative emotions (e.g., disgust [ Δ d' = 0.43] and sadness [ Δ d' = 0.37]). Third, they misinterpreted surprised faces as all the other emotions (Δ d' = 0.41–0.87), except neutral. Fourth, they confused some negative emotions (e.g., misrecognizing fear as anger [ Δ d' = 0.87]). Our findings suggest that patients with schizophrenia show four error patterns of FER compared to healthy adults. Accordingly, interventions could be selected to improve their sensitivity to faces with negative emotions, differentiation of faces among positive and negative emotions, understanding of surprised faces, and discrimination of faces with negative emotions. [ABSTRACT FROM AUTHOR]