AUTHOR=Edwards Darren J. 

TITLE=Going beyond the DSM in predicting, diagnosing, and treating autism spectrum disorder with covarying alexithymia and OCD: A structural equation model and process-based predictive coding account

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.993381

DOI=10.3389/fpsyg.2022.993381

ISSN=1664-1078

ABSTRACT=Background: There is much overlap between the symptomology of autistic spectrum disorders (ASD), obsessive compulsive disorders (OCD), and alexithymia, which all typically involve impaired social interactions, repetitive impulsive behaviors, problems with communication, and mental health. Aim: To identify direct and indirect associations between alexithymia, OCD, cardiac interoception, psychological inflexibility, and self-as-context, with the DVs ASD and depression, whilst controlling for vagal related aging. Methodology: The data involved electrocardiogram (ECG) heart rate variability (HRV) and questionnaire data. 1,089 participant’s data of ECG recordings of healthy resting state HRV were recorded and grouped into age categories. In addition to this, another 224 participants completed an online survey which included the following questionnaires: Yale-Brown Obsessive Compulsive Scale (Y-BOCS); Toronto Alexithymia Scale 20 (TAS-20); Acceptance and Action Questionnaire (AAQII); Depression, Anxiety, and Stress Scale 21 (DAS21); Multidimensional Assessment of Interoceptive Awareness Scale (MAIA); and the self-as-context scale (SAC).  Results: HRV was shown to decrease with age when controlling for BMI and gender. In the two SEM models produced, it was found that OCD and alexithymia were causally associated to autism and depression indirectly through psychological inflexibility, SAC and ISen interoception. Conclusion: Results are discussed in relation to limitations of the DSM with its categorical focus of protocols for syndromes and provides support for more flexible ideographic approaches in diagnosing and treating mental health and autism within the Extended Evolutionary Meta Model (EEMM).  Graph theory approaches are discussed in their capacity to depict processes of change potentially even at the level of the relational frame.