Study protocol for a triple-blind randomised controlled trial evaluating a machine learning-based predictive clinical decision support tool for internet-delivered cognitive behaviour therapy (ICBT) for depression and anxiety

Abstract

Introduction Therapist-supported internet-based Cognitive Behavioural Therapy (ICBT) has strong scientific support, but all patients are not helped and further improvements are needed. Personalized medicine could enhance ICBT. One promising approach uses a Machine learning (ML) based predictive decision support tool (DST) to help therapists identify patients at risk of treatment failure and adjust their treatments. ICBT is a suitable clinical context for developing and testing such predictive DST:s, since it’s delivery is quite flexible and can quickly be adapted for probable non-responders, for example by increasing the level and nature of therapist support, to avoid treatment failures and improve overall outcomes. This type of strategy has never been tested in a triple-blind randomised controlled trial (RCT) and has rarely been studied in ICBT. Methods and analysis A triple blind RCT comparing ICBT with a DST (DST arm), to ICBT as usual (TAU arm). The primary objective is to evaluate if DST is superior to TAU in decreasing diagnose-specific symptoms among patients identified to be at risk of failure. Secondary objectives are to evaluate if the DST improves functioning, interaction, adherence, patient satisfaction, and therapist time efficiency and decreases the number of failed treatments. Additionally, we will investigate the therapists’ experience of using the DST. Patients and therapists will be recruited nationally. They are randomised and given a sham rational for the trial to ensure allocation blindness. The total number of patients will be a minimum of 350, and assessments will be administered pre-treatment, weekly during treatment, at post-treatment and at 12-month follow-up. Primary outcome are the diagnosis-specific symptom rating scales and primary analysis is difference in change from pre- to post-treatment for at-risk patients. Human Ethics and Consent to Participate Informed consent to participate in the study will be obtained from all participants. Both therapists and patients are participants in this trial. For patients, informed consent to participate in the study is obtained when they register for the study via the study’s secure web platform and carry out an initial screening before the diagnostic assessment, they will first receive the research subject information and be asked for consent by digitally signing that they have read and understood the information. For therapists who are part of the study, consent is requested after they have registered their interest. They will then receive an email with a link to the study’s secure web platform with the research person's information, and are asked for consent by digitally signing that they have read and understood the information. All documents are then stored in secure, locked filing cabinets on the clinic's premises or on a secure digital consent database. Approval Committee: The study has been approved by the Regional Ethics Review Board in Uppsala, Sweden (record number 2020-05772). Trial registration Registry: ClinicalTrials.gov Trial registration number: NCT05321628 Date of registration: 03/18/2022