Effectiveness, Engagement, and Safety of a Digital Therapeutic (CT-155/BI 3972080) for Treating Negative Symptoms in People With Schizophrenia: Protocol for the Phase 3 CONVOKE Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Negative symptoms of schizophrenia, such as lack of motivation, pleasure, social interest, and expression, are key contributors to functional impairments in people with schizophrenia. While psychosocial interventions have demonstrated efficacy, no Food and Drug Administration-approved pharmacotherapies exist specifically to target these symptoms. Evidence-based digital therapeutics (DTx) may offer novel, scalable treatment options to augment existing treatments. OBJECTIVE: This article describes the study design and methods of a phase 3, multicenter, double-blind, randomized controlled study (CONVOKE). It aims to evaluate the effectiveness and safety of CT-155/BI 3972080 (CT-155), a smartphone-based DTx, as an adjunct to standard-of-care antipsychotic medication in adults with experiential negative symptoms of schizophrenia. METHODS: Eligible participants were 18 years or older with a primary diagnosis of schizophrenia receiving stable antipsychotic medication for ≥12 weeks, scored ≥2 on average in at least 2 Clinical Assessment Interview for Negative Symptoms Motivation and Pleasure subscale (CAINS-MAP) domains, and were smartphone owners. Participants were randomized 1:1 to CT-155 (intervention arm) or a digital control app (control arm). CT-155 integrates aspects of multiple evidence-based psychosocial therapeutic techniques, incorporating principles of in-person psychotherapy aimed at targeting negative symptoms. Development of CT-155 was informed by patients during early clinical learning studies using earlier versions of the app. The digital control included elements of the disease educational components of CT-155 and daily digital check-ins. Participants were blinded to their assigned intervention. A blind-to-hypothesis was used so participants appropriately engaged with both apps. Accordingly, participants were informed that they would receive one of 2 interventions under investigation. Investigators, designated site personnel, and central raters were blinded throughout the study. The study comprised a 2-week screening period, 16-week active period, and a 4-week follow-up period. Change in experiential negative symptoms from baseline to Week 16 (primary end point) was assessed using CAINS-MAP (centrally rated). Other study end points included Clinical Assessment Interview for Negative Symptoms Expressivity, Positive and Negative Syndrome Scale, Personal and Social Performance Scale, Dysfunctional Attitudes Scale, Clinical Global Impressions-Severity, and Patient Global Impression of Improvement Scale. Frequency and severity of adverse events were also assessed, as well as engagement and adherence to either app. RESULTS: Study enrollment began in March 2023 and was completed in January 2025. Overall, 457 participants were enrolled across 66 clinical study sites in the United States. CONCLUSIONS: We summarize an innovative trial design for CONVOKE, a phase 3 randomized controlled study aimed at assessing the effectiveness, engagement, and safety of CT-155 as an adjunct to standard-of-care for people with negative symptoms of schizophrenia. CONVOKE is the largest-to-date and most robust clinical trial evaluating the effectiveness and safety of a DTx in schizophrenia. The study protocol included a centrally rated primary end point (CAINS-MAP), blind-to-hypothesis, with an appropriately designed digital control. TRIAL REGISTRATION: ClinicalTrials.gov NCT05838625; https://www.clinicaltrials.gov/study/NCT05838625. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/81293.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.059 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".