Efficacy of brief dynamic interpersonal therapy in patients with major depressive disorder: a prospective, multicenter randomized controlled trial protocol
Bibliographic record
Abstract
Abstract Background : Dynamic Interpersonal Psychotherapy (DIT) is a brief manualized depression-focused intervention. This paper describes a study protocol of a multi-site, three-arm randomized controlled trial comparing medication plus DIT to medication alone and medication plus an active control psychotherapy in the treatment of major depressive disorder (MDD). Methods : 240 patients with MDD will be randomly allocated on a 1:1:1 basis to the treatment conditions, with 80 patients in each group. Patients will be assessed pre-and post-intervention and at 6- and 12-months follow-up with the 17-item Hamilton Depression Scale (HAMD-17) and Hamilton Anxiety Scale (HAMA-14) administered by blind evaluators, and the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder-7-item scale(GAD-7), side effect reaction scale (TESS), and The Self-Assessment Scale of the Overall Efficacy and Satisfaction of Patients (SASE). The primary outcome is change from baseline in HAMD-17 scores. Secondary outcomes include rates of response, remission and relapse, change from baseline in self-report depression and measures of anxious symptomatology, and subjective satisfaction of patients. Discussion: This will be the first multicentered RCT in China to assess the potential efficacy of psychotherapy for MDD. The study has the potential to inform clinical treatment guidelines for the treatment of MDD in China. Trial registration : ChiCTR，ChiCTR1800016970， Registered on July 5 th 2018 - Retrospectively registered, http://www.chictr.org.cn/showprojen.aspx?proj=28786 . Key words : Depression; Dynamic Interpersonal Therapy; Multicenter randomized controlled trial,
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".