The p Factor Consistently Predicts Long-Term Psychiatric and Functional Outcomes in Anxiety-Disordered Youth

Abstract

Objective: Pediatric anxiety disorders can have a chronic course and are considered gateway disorders to adult psychopathology, but no consistent predictors of long-term outcome have been identified. A single latent symptom dimension that reflects features shared by all mental health disorders, the p factor, is thought to reflect mechanisms that cut across mental disorders. Whether p predicts outcome in youth with psychiatric disorders has not been examined. We tested whether the p factor predicted long-term psychiatric and functional outcomes in a large, naturalistically followed-up cohort of anxiety-disordered youth. Method: Children and adolescents enrolled in a randomized controlled treatment trial of pediatric anxiety were followed-up on average 6 years posttreatment and then annually for 4 years. Structural equation modeling was used to estimate p at baseline. Both p and previously established predictors were modeled as predictors of long-term outcome. Results: Higher levels of p at baseline were related to more mental health disorders, poorer functioning, and greater impairment across all measures at all follow-up time points. p Predicted outcome above and beyond previously identified predictors, including diagnostic comorbidity at baseline. Post hoc analyses showed that p predicted long-term anxiety outcome, but not acute treatment outcome, suggesting that p may be uniquely associated with longterm outcome. Conclusion:Children and adolescents with anxiety disorders who present with a liability toward broad mental health problems may be at a higher risk for poor long-term outcome across mental health and functional domains. Efforts to assess and to address this broad liability may enhance long-term outcome.

Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes

“…Moreover, some studies concluded that a single model does not provide the best fit to capture general psychopathology and that a 3-factor model (Vollebergh et al, 2001) or a bifactor model (Caspi et al, 2014; Lahey et al, 2012) may be better. Some studies suggest that a robust p -factor is yet to be defined (Cervin et al, 2020). The challenges in defining the p -factor might arise from the absence of a positive manifold in mental health scores (van Bork et al, 2017).…”

“…While it might not be adequate to represent the general dimension of psychiatric disorders, it can be interpreted as a measurement of general mental health that is potentially more informative than binary case control distinctions (Coleman, 2021). We acknowledge that p -factor derived from factor modelling is less well validated as in other measures, for example the g -factor, and results should be considered accordingly (Cervin et al, 2020; van Bork et al, 2017; Watts et al, 2020). Nonetheless, other studies do support the existence of general dimensions to capture psychopathology (Caspi et al, 2020; Lund et al, 2020; Plana-Ripoll et al, 2019; Sprooten et al, 2022), and further investigate the polygenic p -factor derived from polygenic scores for different psychiatric disorders (Allegrini et al, 2020; Selzam et al, 2018).…”

The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research

“…Moreover, HiTOP dimensions can improve prognostication over traditional diagnoses. Dimensions were found to predict clinical improvement, treatment needs, and community functioning – in the short-term and long-term – across various outpatient and inpatient populations (Cervin et al, 2021; Conway et al, 2021; Forbush et al, 2018; Martin et al, 2021; Morey et al, 2012). HiTOP also outperformed traditional diagnoses in predicting important life outcomes, such as all-cause mortality (Kim et al, 2021).…”

The Exposome and its Associations with Broad Mental and Physical Health Measures in Early Adolescence

“…We first aimed to test whether the association of exposome factors with mental health depends on the measure used to model mental health. In the main analyses, we modeled mental health dimensionally using that the P-factor, which is a reliable measure of psychopathology in youth samples 65, 66 that represents life course vulnerability to psychiatric disorders 67 and is predictive of long term psychiatric and functional outcomes 68 . In sensitivity analyses we tested associations of exposome factors with parent-reported child psychopathology available in ABCD (using the total child behavior checklist [CBCL] t-score).…”