Disentangling psychological interventions for mental disorders into a taxonomy of active ingredients

Severe mental disorders, like psychotic or borderline personality are associated with higher mortality, both all-cause and by suicide.

Psychological interventions, usually combined with other treatments, are effective options, though less so than for common mental disorders.

However, mechanisms and predictors of treatment response, key for improving effectiveness and for precision medicine, are mostly unknown.

The greatest barrier is our approach to psychological interventions as brands or categories, without knowledge of active ingredients, and particularly of which ingredients are effective.

The proposal will bridge this gap by dismantling psychological interventions into components, integrating these into a taxonomy, and radically reevaluating treatment efficacy and personalization from a novel perspective: components instead of brands and categories.

We will use recent network meta-analyses to assemble a large collection of psychological interventions for severe mental disorders (psychotic, bipolar, substance use, eating and borderline personality). We will retrieve intervention protocols and extract components iteratively, via multiple rounds of independent coding.

We will integrate components in a cross-disorder, comprehensive taxonomy, validated in Delphi surveys and a consensus meeting.

We will reevaluate psychological interventions for severe disorders through component network meta-analysis, to identify the most beneficial ingredients and combinations, for symptoms, functioning and attrition outcomes. We will reassess treatment personalization through a component-based lens using individual patient data for psychosis.

Finally, we will develop an open clinical decision support system, where users can assemble and dismantle interventions, visualizing efficacy gain or loss.

The proposal is a systematic and reproducible approach to advance a perspective shift from treatment brands to active ingredients, potentially upending psychotherapy research.