Comparing Online and On-Site Cognitive Behavior Therapy in Major Depressive Disorder: Protocol for a Noninferiority Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND The incidence of mental health disorders in Canada is increasing with costs of CAD $51 billion (US $40 billion) per year. Depression is the most prevalent cause of disability while cognitive behavioral therapy (CBT) is the best validated behavioral depression treatment. CBT, when combined with mindfulness meditation (CBT-M), has strong evidence for increased efficacy. While randomized controlled trials (RCTs) have demonstrated online CBT-M efficacy, comparisons with in-office delivery are lacking. OBJECTIVE The aim of this research is to assess whether online group CBT-M (with standard psychiatric care) is non-inferior in efficacy and more cost-effective than office-based, on-site group CBT-M at post-intervention and 6-months follow-up in major depressive disorder. The study will also assess whether digitally recorded data (ie, online workbooks completed, Fitbit step count, and online text messages) predict depression symptom reduction in online participants. METHODS This single-center, two-arm, noninferiority RCT employs assessor-blinded and self-report outcomes and economic evaluation. The research site is the Centre for Addiction and Mental Health (Toronto), a research-based psychiatry institution where participants will be identified from service wait lists and through contacts with other Toronto clinics. Inclusion criteria are as follows: (1) aged 18-60 years, any ethnicity; (2) Beck Depression Inventory-II (BDI-II) of mild severity (score ≥14) with no upper severity limit; (3) Mini-International Neuropsychiatric Interview-confirmed, psychiatric major depressive disorder diagnosis; (4) fluent in English. All patients are diagnosed by staff psychiatrists. Exclusion criteria are as follows: (1) receipt of weekly structured psychotherapy; (2) observation of Diagnostic and Statistical Manual of Mental Disorders (5th Edition) criteria for severe alcohol or substance use disorder (in past 3 months), borderline personality disorder, schizophrenia (or other primary psychotic disorder), bipolar disorder, or obsessive-compulsive disorder; (3) clinically significant suicidal ideation (imminent intent or attempted suicide in the past 6 months); and (4) treatment-resistant depression. All participants receive standard psychiatric care, experimental participants receive online group CBT-M, and controls receive standard care in-office group CBT-M. The online group program (in collaboration with NexJ Health, Inc) combines smartphone and computer-accessed workbooks with mental health phone counselling (16 hours in 16 weeks) that coordinates software interactions (eg, secure text messaging and Fitbit-tracked walking). The primary outcome is BDI-II, and secondary outcomes are anxiety (Beck Anxiety Inventory), depression (ie, Quick Inventory of Depressive Symptomatology and 17-item Hamilton Depression Rating Scale), mindfulness (Five-Facet Mindfulness Questionnaire), quality of life (European Quality of Life Five Dimension), and pain (Brief Pain Inventory). RESULTS Based on prior studies with the BDI-II and 80% power to reject an inferiority hypothesis with a 1-sided type I error rate of 5%, a sample of 78 per group is adequate to detect small-to-medium–effect sizes. CONCLUSIONS This study assesses online CBT-M efficacy and noninferiority in relation to in-person CBT, and the cost-effectiveness of both interventions. CLINICALTRIAL ClinicalTrials.gov NCT04825535; https://www.clinicaltrials.gov/ct2/show/NCT04825535 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/29726
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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 | 0.050 | 0.049 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.108 | 0.021 |
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".