The present study aimed to explore potential differences in how female and male individuals meet the diagnostic criteria for ASD assessed by the ADOS. We aimed to identify a potential female phenotype from behavioral observations in a well-characterized clinical population of children, adolescents, and adults. Using a random forest approach, we compared subsets of diagnostic features of the ADOS that were most indicative of an ASD diagnosis between females and males.

The results revealed similar classifier performances in the female and male samples, but relying on slightly different features for classification. Concentrating on a few core behavioral aspects for female and male samples led to classification performances that were equally as good as those based on information from the complete examination. For an optimal performance, the classifiers needed fewer features in the female sample than in the male sample in both age groups. It has been argued that since the defining diagnostic criteria are historically based on the male phenotype and the diagnostic thresholds are similar, a female phenotype may be missed if it presents differently, even if these females present with a substantial clinical burden [7]. However, the current study demonstrates that although slightly different features were most discriminative, classification in females was just as good as in males.

In the current study, females were older at the time of the diagnostic appointment—an effect that was pronounced in the older adolescent and adult sample. In the young adolescent and adult group, males with ASD scored higher in the RRB domain of the behavior observation than females with ASD, but the effect size was small. We observed no differences in social affect between the sexes in the ASD samples of either age group, but males scored higher on overall symptom severity. These findings are in line with a meta-analysis that reported few differences in communication and social behavior between males and females and only in the RRB domain did girls show fewer symptoms than boys [18].

The present findings indicate, however, that as ASD symptoms present differently across development, the developmental aspect might be important with respect to sex differences: In the older adolescent and adult sample, we found fewer symptoms of RRB and lower overall ASD severity (ADOS CSS total) in females than in males. From the parental perspective (anamnestic data from the ADI-R), females showed fewer symptoms in the communication domain. In the child and young adolescent sample, more parent-reported RRB were observed in males compared to females, with moderate effect sizes. Classification accuracy of the RF models was similar to the diagnostic accuracy of the ADOS-2 algorithm in females as well as males. Interestingly, we found more females than males who were diagnosed with ASD while scoring below the ADOS autism spectrum diagnostic cut-off (18.6% females vs. 13.5% males, i.e., false negative ADOS classifications). This suggests that information from outside the standardized behavioral observation may be of greater importance for the diagnostic decision in females than in males, giving rise to the question of which particular additional information clinicians rely on in order to classify a female as autistic. On the other hand, more males than females did not receive an ASD diagnosis despite exceeding the ADOS diagnostic threshold (6.4% females vs. 14.2% males, i.e., false positive ADOS classifications). This suggests that autistic traits in males may be present during the behavioral observation but are attributed to other underlying conditions or symptoms of a differential diagnosis. However, our female sample had more comorbid diagnoses (e.g., depression, social phobia), and particularly in females with ASD, there is evidence that the presence of depression and anxiety is associated with enhanced ASD symptoms [30,31,32,33,34,35]. The considerable symptom overlap of ASD with depressive and anxiety disorders entails the risk of false-positive evaluations in females. Although the ADOS-2 shows high sensitivity (0.91; [23], p. 243) for detecting autism versus non-spectrum cases, emerging research shows that it may be less accurate in detecting ASD in individuals with complex psychiatric presentations [36]. Moreover, the observation in the current sample that the prevalence of ASD diagnoses increases with age (45.9% of all adolescent/ adult females, but only 33.8% of the younger sample, received an ASD diagnosis) underlines the need to carefully consider differential, potentially overlapping diagnoses during the diagnostic process.

To the best of our knowledge, this is the first study to explore sex differences in an ASD and a non-ASD sample with the aim of identifying those symptoms that are most important for the classification and subsequently comparing these discriminative features between females and males. The most discriminative features all stem from the social communication domain of the ADOS, whereas only speech items (Speech Abnormalities Associated with Autism, and Stereotyped and Idiosyncratic Use of Words or Phrases) of the RBB domain are included in the optimal feature models. This may be due to the rather short time span of the ADOS (45–60 min duration of administration), which limits the time for observations of repetitive behaviors and/or the overall more verbal character of the ADOS modules 3 and 4. Furthermore, although males showed more RBBs than females, the pattern in male and female non-ASD cases seemed similar thus not providing the RF classifier information relevant for the distinction of ASD and non-ASD cases within each group. The effect may also be attributed to basic sex differences in the occurrence of RRB in the diagnostic situation elicited in boys by a male-biased toy selection. As has been pointed out, the restricted and repetitive interests among females may be more “random” and more difficult to categorize and thus to “identify as atypical” [15, p. 1391].

Our optimal models include mainly ADOS items mapping onto “Basic Social Communication Skills.” According to Bishop and colleagues [37], social communication deficits captured by the ADOS can be divided into “Basic Social Communication Skills” (including Gestures, Eye Contact, Facial Expressions, and Shared Enjoyment) and “Interaction Quality” (including Conversation, Amount of Reciprocal Social Communication, and other Quality items). These ‘basic’ impairments seem to be specific for ASD regardless of sex, age, and intelligence [37, 38]. In our models, these basic impairments appear, overall, to be sufficient in order to discriminate females with ASD from those with other mental disorders when flanked by the two additional items of “Interaction Quality,” with good specificity and sensitivity. Moreover, in contrast to the findings for males, they are not correlated with age and IQ (see Additional file 1: Table S3). Some previous studies found that females with ASD exhibit less severe impairments in social communication behaviors [39, 40], although we and others [7, 14] cannot confirm this for the behavior observation. Nevertheless, these items do seem to be essential for the differentiation of ASD from other mental disorders, particularly in females.

In the child and young adolescent sample, we found similarities between females and males concerning the following items: Quality of Social Overtures, Conversation, and Gestures. Differences were especially evident in the communication domain. Speech abnormalities were also relevant for the differentiation from other mental disorders. Such speech abnormalities are important for females: For the female group, all items are algorithm items, whereas for the male group, six items are part of the algorithm and two additional items are needed (Speech Abnormalities and Insight) for the model to reach optimal classification performance. In the older adolescent and adult sample, similarities were only found concerning the basic skills Eye Contact, Facial Expressions, and Gestures. However, for the differentiation from other mental disorders in males, many aspects of the Quality of Interaction are additionally needed; in females, only Empathy and Speech Abnormalities are relevant.

In the male, the most discriminative ADOS items all stem from the classification algorithm plus the item Descriptive, Conventional, Instrumental or Informational Gestures (DGES). In the female sample, though a smaller number of features seem to suffice for an optimal classification, only 3 out of 5 items stem from the ADOS classification algorithm. Particularly, the item Comments on Others’ Emotions/Empathy that is linked to cognitive empathy, a construct often impaired in ASD [41], was of prime importance in the optimal model.

Overall, the optimal models of our RF approach yielded slightly different distinctive features for females and males but did not outperform the ADOS-2 classification algorithm (grouping the autism spectrum and autism cases together). These results do not suggest an adaptation of the ADOS-2 classification algorithm for a female phenotype.

Future aim of the present work is to break down these most discriminative subsets of diagnostic items into their underlying mechanisms or processes and translate them into research on biomarkers in order to identify the behaviorally observed differences between females and males on a molecular level. This needs to be the next step on the way to the identification of a female phenotype as both measures—ADOS and ADI-R—cannot simply be abbreviated, as, e.g., ADOS codes are attained throughout the observation session and are not strictly tied to single subtasks [24] and thus items cannot be observed independently and the impact of each item for the diagnostic decision is difficult to extract.