After providing a written inform consent, potential patients will undergo a 2-weeks screening period to determine if they meet eligibility criteria. Baseline information (i.e., derived from semi-structured intake interviews and baseline clinical measures) from patients who meet eligibility criteria and consent to participate in the study, will be use to feed a machine learning algorithm, developed in a previous study, to perform individual predictions and determine which interventions (i.e., cognitive, behavioral, interpersonal, or patient-centered) will be recommended for the individual patient. This recommendation (i.e., about the most personally well-suited intervention for a given patient) will be provided to therapists before the beginning of treatment. Patients will be treated with 15 sessions of psychotherapy. The investigators will examine the extent to which therapists adhered to the recommended interventions as the primary outcome. The investigators will also examine patient symptomatic/functional improvement as a secondary outcome.
The purpose of this study is to evaluate the feasibility of an evidence-based system to recommend core interventions, before the beginning of treatment, to psychotherapists treating low-income patients with depressive or anxiety disorders.