20118
Depression As a Predictive Factor of Emotion Recognition in High-Functioning Autism
Depression is one of the most frequently diagnosed comorbid psychiatric disorders in individuals with autism spectrum disorders (ASD; Ghaziuddin et al., 1992). It is firmly established that both depression and ASD manifest distinct abnormal emotion recognition impairments. For example, depressed individuals tend to negatively interpret neutral valence (Ashwin et al., 2006), whereas those with ASD tend to mislabel negative or ambiguous emotions (George et al., 1998). Some findings report high-functioning individuals with ASD (HFA) are as adept at emotion recognition tasks as typically developing (TD) individuals. This has been attributed to the use of compensation strategies such as greater effortful processing (Tracy, et al., 2011). However, effortful processing may not be effective in comorbid ASD and depression, as it appears to be disrupted by depression (Hartlage, et al., 1993).
Objectives:
The primary aim of this study was to investigate the combined effect of ASD and depression on emotion recognition ability. We hypothesized that individuals with HFA and mild-to-no depression would perform comparable to TD individuals on emotion recognition tasks; whereas, individuals with HFA and depression would exhibit emotion recognition impairment.
Methods:
Participants were 18 to 26-year-old males with an IQ>80. Eighteen individuals with HFA and 30 TD controls completed the Wechsler Abbreviated Scale of Intelligence to estimate IQ, the Wechsler Adult Intelligence Scale – IV ACS Emotion Recognition task, and the self-report Beck Depression Inventory (BDI). Autism diagnosis was confirmed using the Autism Diagnostic Observation Scale. A multiple regression analysis with moderation was implemented to analyze depression severity score as a moderator of the relationship between group (TD vs. ASD) and emotion recognition ability. Predictors included depression severity and group affiliation, while the emotion recognition score was the outcome.
Results:
The multiple regression analysis revealed no main effects for depression severity or group on predicting the emotion recognition score. However, there was a significant interaction between group and depression severity on the prediction of emotion recognition ability. The model predicted 26% of the variance in emotion recognition score. Post-hoc, a Johnson Neyman technique revealed HFA and TD groups differed in emotion recognition ability when BDI depression scores were 18.34 and greater (moderate to severe symptoms). Finally, a simple slopes analysis revealed a significant negative relationship between depression and emotion recognition score in the HFA group (p=.001), but not in the TD group.
Conclusions:
Results of the current study indicate that it may be important to consider depression symptomology when investigating emotion recognition in ASD. In our study, emotion recognition skills in individuals with HFA were comparable to those of TD individuals in the absence of depression. However, those with HFA and moderate to severe depression symptomology showed greater impairment in emotion recognition than in similarly depressed TD controls. Additionally, these findings raise questions as to whether depression disrupts otherwise successful compensatory strategies for emotion recognition in ASD individuals. Further research is needed to investigate the specific mechanisms affected in the interaction between depression and ASD on emotion recognition.