Mapping the Research Domain Criteria Social Communication Sub-Constructs to the Social Responsiveness Scale

Background: Impaired social functioning is an early and prominent feature of autism spectrum disorder (ASD) and a wide array of other neurodevelopmental and neuropsychiatric disorders. Given the pervasive negative impact on affected individuals and their families, social deficits constitute an important intervention target. However, current diagnostic systems offer an imprecise characterization of social domains, limiting their utility for etiologically based research and stifling the development of individually tailored treatments. Research Domain Criteria (RDoC) operationalizes a set of basic social dimensions that can be used to deconstruct sources of variation in social impairments across affected individuals, regardless of their diagnostic status. Despite the significant promise, the translation of the RDoC framework into research and clinical practice has been impeded by the lack of dedicated measures for assessing proposed dimensions. Therefore establishing effective means of capturing and extracting relevant RDoC domains from already collected data can offer an important bridge towards providing initial testing of the explanatory power of this framework.

Objectives: To derive estimations of the RDoC social constructs from the Social Responsiveness Scale (SRS) and explore their utility in capturing individual patterns of strengths and weaknesses across the identified factors in a large, clinically diverse sample.

Methods: Data from six distinct databases were combined resulting in total N= 27953 (M_age= 9.55, SD= 3.79; 71.7% male). The sample comprised of individuals with ASD (60%), other neurodevelopmental and neuropsychiatric disorders (NDD/NPD; 6.2%) and normative development (33.8%). Variable-centered (Confirmatory Factor Analysis [CFA] and Exploratory Structural Equation Modeling [ESEM]) and person-centered (Latent Profile Analysis [LPA]) approaches were conducted using individual SRS items. CFA and ESEM explored the following models: (1) a 1-factor model; (2) a 3-factor model with separate Attachment and Affiliation (AA), Social Communication (SC), and Understanding of Mental States (UMS) factors, (3) a 4-factor model where SC was further split into Production of Facial (PFC) and Non-Facial (PNFC) communication, and (4) a bi-factor model with general social processes factor and 4 specific AA, PNFC, PFC, and UMS factors.

Results: The 1-factor solution showed a poor fit. The 3-factor solution had adequate fit (comparative fit index [CFI]= .952, Tucker Lewis index [TLI]= .937, root mean square error of approximation [RMSEA]= .054), however, 4-factor solution had superior fit (CFI= .973, TLI= .961, RMSEA= .042). Finally, the bi-factor model with general and specific AA, PNFC, PFC and UMS factors provided the best fit (CFI= .984, TLI= .975, RMSEA= .034). The identified factors were then utilized in the LPA that suggested a 5-profile solution (based on the BIC and the Bootstrap Likelihood Ratio Test) for the clinical sample (ASD and NDD/NPD). Identified profiles were distinguished in terms of the distinct pattern of peaks and troughs across AA, PNFC, PFC and UMS constructs, rather than being defined only by general severity gradient.

Conclusions: To our knowledge, this is the first study examining estimations of the RDoC social constructs from the existing measures. Our findings show promise for capturing important RDoC social constructs using the SRS and the utility of the identified factors in capturing clinically meaningful subgroups.