Efficacy of brief dynamic interpersonal therapy in patients with major depressive disorder: a prospective, multicenter randomized controlled trial protocol
Bibliographic record
Abstract
BACKGROUND: In China, psychodynamic psychotherapies are widely used as a treatment for depression. However, very few efficacy studies of psychodynamic therapies have been conducted with the Chinese population. This paper describes a study protocol of a multicenter randomized controlled trial of dynamic interpersonal psychotherapy (DIT), a brief manualized depression-focused intervention, in Chinese adults with major depressive disorder (MDD). METHODS: Recruitment is planned in five hospitals. Two hundred forty patients with MDD will be randomly allocated on a 1:1:1 basis to either medication plus DIT, medication plus an active control psychotherapy, or medication alone. Patients will be assessed at baseline and at weeks 2, 4, 8, 12, and 16 during the acute treatment phase and 1, 3, 6, and 12 months posttreatment. The primary outcome is change from baseline in the 17-item Hamilton Depression Rating Scale, administered by independent raters who are blind to treatment allocation. The Hamilton Anxiety Rating Scale, Patient Health Questionnaire-9, Generalized Anxiety Disorder 7-item scale, response, remission and relapse rates, self-assessment of overall efficacy and satisfaction of patients, and side effect profiles are secondary measures. DISCUSSION: This will be the first multicentered RCT in China to assess the efficacy of a brief psychodynamic intervention for MDD. The study has the potential to inform clinical treatment guidelines for the treatment of depression in China. TRIAL REGISTRATION: ChiCTR, ChiCTR1800016970 . Registered on July 5, 2018.
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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 | 0.025 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.038 | 0.006 |
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".