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Previous research on emotion processing in autism spectrum disorder (ASD) has predominantly focused on human faces and speech prosody, with little attention paid to other domains such as nonhuman faces and music. In addition, emotion processing in different domains was often examined in separate studies, making it challenging to evaluate whether emotion recognition difficulties in ASD generalize across domains and age cohorts. The present study investigated: (i) the recognition of basic emotions (angry, scared, happy, and sad) across four domains (human faces, face-like objects, speech prosody, and song) in 38 autistic and 38 neurotypical (NT) children, adolescents, and adults in a forced-choice labeling task, and (ii) the impact of pitch and visual processing profiles on this ability. Results showed similar recognition accuracy between the ASD and NT groups across age groups for all domains and emotion types, although processing speed was slower in the ASD compared to the NT group. Age-related differences were seen in both groups, which varied by emotion, domain, and performance index. Visual processing style was associated with facial emotion recognition speed and pitch perception ability with auditory emotion recognition in the NT group but not in the ASD group. These findings suggest that autistic individuals may employ different emotion processing strategies compared to NT individuals, and that emotion recognition difficulties as manifested by slower response times may result from a generalized, rather than a domain-specific underlying mechanism that governs emotion recognition processes across domains in ASD.

It was recently reported that learning one is autistic earlier in life is associated with greater quality of life and well-being in university students. In a pre-registered extension of this work, we addressed several limitations of this study by (a) recruiting a larger sample of more diverse ages and education levels, (b) distinguishing between learning about and receiving an autism diagnosis, (c) accounting for additional confounding variables, and (d) studying different quality of life dimensions. Autistic adults ( N = 300) reported when they first learned they were autistic, as well as when they actually received an autism diagnosis, and provided detailed socio-demographic information. Participants also completed measures of their autistic traits, as well as well-being and quality of life across multiple domains. In contrast to recent research, we found the age participants first learned they were autistic did not significantly and uniquely predict their quality of life and well-being. Rather, having more autistic traits was the strongest predictor of poorer quality of life and well-being, while other socio-demographic factors were also relevant. We discuss the implications of these findings for understanding and improving outcomes in autistic adults and call for higher quality open science on this important topic. Lay abstract An interesting recent study found that people who learned they were autistic at a younger age felt more positive about their lives (i.e., had better quality of life) than those who learned at an older age. However, this study has some limitations: (a) the study only involved a fairly small group of university students, (b) whether ‘learning one is autistic’ referred to learning about one’s diagnosis or receiving one’s diagnosis was unclear, (c) the influence of other factors on the link between age of learning one is autistic and quality of life was not considered, and (d) the assessment of different areas of quality of life was limited. Addressing these limitations, we re-examined whether the age at which one learns they are autistic relates to quality of life in adulthood. Contrary to the previous study, we found the age at which one learns about their autism does not have a significantly independent impact on their quality of life as an adult. Rather, other factors (e.g., autistic traits, sex, and additional mental health conditions) may have a greater impact. Given our participant sample was larger and more diverse in age and education level compared to previous research, this finding is likely to be more applicable to autistic adults from different backgrounds. Importantly, however, we are not suggesting that individuals should be made aware of their diagnosis later than sooner. Getting a timely diagnosis remains crucial for autistic people and their families to access appropriate support.

Most audio-visual (AV) emotion databasesconsist of clips that do not reflect real-life emotion processing (e.g., professional actors in bright studio-like environment), contain only spoken clips, and none have sung clips that express complex emotions. Here, we introduce a new AV database, the Reading Everyday Emotion Database (REED), which directly addresses those gaps. We recorded the faces of everyday adults with a diverse range of acting experience expressing 13 emotions—neutral, the six basic emotions (angry, disgusted, fearful, happy, sad, surprised), and six complex emotions (embarrassed, hopeful, jealous, proud, sarcastic, stressed)—in two auditory domains (spoken and sung) using everyday recording devices (e.g., laptops, mobile phones, etc.). The recordings were validated by an independent group of raters. We found that: intensity ratings of the recordings were positively associated with recognition accuracy; and the basic emotions, as well as the Neutral and Sarcastic emotions, were recognised more accurately than the other complex emotions. Emotion recognition accuracy also differed by utterance. Exploratory analysis revealed that recordings of those with drama experience were better recognised than those without. Overall, this database will benefit those who need AV clips with natural variations in both emotion expressions and recording environment.