There is a rising interest in perinatal mental health studies, and proper psychometric tools to assess autistic traits among this population in Japan are vital.
This study aimed to clarify the optimal factor structure of the AQ as part of a perinatal mental health research project.
We used the Japanese version of the AQ (AQ-J) to measure autistic-like traits in pregnant women. Participants were 4,287 Japanese women who were pregnant or who had given birth within the last month. We performed exploratory factor analysis (EFA) using the first sample group (n = 2,154) to obtain factor structures for the final item selections. We performed confirmatory factor analysis (CFA) using the second sample group (n = 2,133) to obtain a model with good fit, then compared the model to all previously proposed models to determine the best-fitting model.
The EFA analysis identified a model consisting of 25 items distributed across three factors. Cronbach’s alpha for the total 25-item AQ-J, 9-item “Social interaction” factor, 11-item “Non-verbal communication” factor, and 5-item “Restricted interest” factor was 0.829, 0.829, 0.755, and 0.576, respectively. McDonald’s omega and its 95% confidence interval were 0.826 (0.821–0.836), 0.835 (0.821–0.837), 0.755 (0.744–0.766), and 0.603 (0.556–0.596), respectively. CFA confirmed that the three-factor structure had an acceptable fit (goodness of fit index: 0.900, comparative fit index: 0.860, root mean square error of approximation: 0.066). These findings indicated that the three-factor model was better than the 13 existing models.
The findings are discussed in relation to the adequacy of the AQ-J for assessing autistic traits in perinatal women. We recommend the use of this 25-item, three-factor AQ-J model for this population owing to its superiority to all previous models.