Multicausal systems ask for multicausal approaches: A network perspective on subjective well-being in individuals with autism spectrum disorder

Abstract

Given the heterogeneity of autism spectrum disorder, an important limitation of much autism spectrum disorder research is that outcome measures are statistically modeled as separate dependent variables. Often, their multivariate structure is either ignored or treated as a nuisance. This study aims to lift this limitation by applying network analysis to explicate the multivariate pattern of risk and success factors for subjective well-being in autism spectrum disorder. We estimated a network structure for 27 potential factors in 2341 individuals with autism spectrum disorder to assess the centrality of specific life domains and their importance for well-being. The data included both self- and proxy-reported information. We identified social satisfaction and societal contribution as the strongest direct paths to subjective well-being. The results suggest that an important contribution to well-being lies in resources that allow the individual to engage in social relations, which influence well-being directly. Factors most important in determining the network's structure include self-reported IQ, living situation, level of daily activity, and happiness. Number of family members with autism spectrum disorder and openness about one's diagnosis are least important of all factors for subjective well-being. These types of results can serve as a roadmap for interventions directed at improving the well-being of individuals with autism spectrum disorder.

How predictable are symptoms in psychopathological networks? A reanalysis of 18 published datasets

“…This procedure leads to spurious relationships, because variables become related via their shared missing value pattern that is determined by the structure of the skip questions (0s are imputed for multiple variables at the same time, inducing correlations among these items). We also observed a very high predictability of two items in the paper on autism by Deserno et al (2016) (see the outliers in Fig. 3)age and age of diagnosis.…”

“…Datasets predominantly feature symptoms or clinical problems as nodes, although some contain contextual variables (e.g. age of diagnosis in Deserno et al 2016).…”

“…Authors who did not respond to our initial email were reminded end of August. We consider all datasets (2013) Obtained Boschloo et al (2015) New policy of US National Institute on Alcohol Abuse and Alcoholism does not allow sharing data anymore (personal communication) Boschloo et al (2016b) Obtained Boschloo et al (2016b) Requirements to obtain data from NESDA for re-analysis unfeasible for this project Curtiss & Klemanski (2016) Did not share their data Deserno et al (2016) Obtained Fried et al (2015) Obtained…”

A network theory of mental disorders

“…The network theory of mental disorders, as advanced here, offers a consistent and transparent theoretical framework for thinking about psychopathology. The first empirical steps along the lines of this theory have already been taken, in the form of explorative studies that chart the network architecture of symptomatology. Assuming that, in time, the structure of symptom networks becomes increasingly clear, the second empirical step would be to connect (individual differences in) the architecture of these networks to (individual differences in) relevant biological, psychological and socio‐cultural factors.…”

“…Methodological research within this approach has focused on developing statistical techniques designed to identify network structures among psychiatric symptoms from empirical data 7-12 . These techniques have now been applied to a range of constructs, such as depression [13][14][15][16][17][18][19][20] , anxiety disorders 21,22 , post-traumatic stress 23 , complex bereavement 24 , autism 25,26 , psychotic disorders [27][28][29] , substance abuse 30 , the general structure of psychiatric symptomatology [31][32][33][34] , diagnostic manuals themselves 34,35 , health-related quality of life 36 , and personality traits 37 .…”