Acceptance and Commitment Therapy and white matter plasticity in individuals with subclinical depression and psychotic experiences: A Randomised Controlled Trial

Abstract

Background: Research indicates that Acceptance and Commitment Therapy in Daily Life (ACT-DL) is effective in reducing symptoms of depression, anxiety and psychosis. During adolescence, vulnerability to psychopathology peaks, creating a window for early interventions, while white matter development is ongoing. This study aims to examine microstructural white matter after ACT-DL intervention in youngsters with mild psychopathology. Methods: Forty-five individuals with mild psychopathology were randomly allocated to ACT-DL (n=20) or topic discussion control (TD, n=25). Symptomatology was assessed with the Community Assessment of Psychic Experiences (CAPE), Montgomery–Åsberg Depression Rating Scale (MADRS) and the Experience Sampling Method (ESM). Diffusion Weighted Imaging (DWI) and network-connectivity parameters were obtained and compared before and after the intervention/control condition. Interactions between microstructural white matter change and condition were examined in models of CAPE positive symptoms and ESM subclinical psychotic experiences (PE) and negative affect (NA) levels. Results: ACT-DL, compared to TD, was associated with changes on subclinical depressive and psychotic symptom levels. There was no significant change in DWI or network connectivity in either condition and no significant difference between both conditions. In the model of NA, several regional interactions between condition and network measures were significant, but stratification per condition provided no significant associations. There were no significant interactions between DWI or network connectivity parameters and condition in the models of the CAPE positive symptoms, MADRS and PE. Conclusions: The findings suggest that behavioral (symptom) changes are more sensitive to a five-week psychological training than microstructural white matter changes which did not show significant changes over time.