The influence of dynamism and expression intensity on face emotion recognition in individuals with autistic traits

Figures & data

Table 1. Descriptive statistics for participant demographics (N = 65).

Variable	Low-AQ group	High-AQ group
n	34	31
AQ Score
M (SD)	10.24 (2.28)	26.52 (4.63)
Range	4–13	22–40
Age^a
M (SD)	21.35 (3.94)	22.61 (4.09)
Range	19–40	19–33
Gender^b
Male	5	10
Female	29	20
Non-binary	0	1
Education^c
Postgraduate degree	2	3
Diploma/degree	32	27
High school	0	1

Note: Gender and education are presented as frequency count. Education refers to the highest level of education completed or currently studying.

^a Groups were well-matched for age (t (63) = 1.27, p = .21).

^b Gender ratios in the AQ groups were not significantly different (χ² (1, N = 64) = 3.08, p = .08) when analysing male and female participants only due to small number of non-binary identifying participants.

^c Groups were well-matched for education (χ² (2, N = 65) = 1.34, p = .564).

Figure 1. (a) Mean percentage accuracy in FER across dynamism and expression intensities between AQ groups. **p < .01; *p < .05. (b) Magnitude of the dynamic advantage between AQ groups for peak and partial expressions. The figure shows the mean difference in percentage accuracy of FER (dynamic minus static), which is referred to as the dynamic advantage. *A significant dynamic advantage for that condition (i.e. mean difference is greater than 0), p < .001. Error bars indicate standard error of the mean.