Advancing Bipolar Disorder: Key Lessons from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD)
Bibliographic record
Abstract
OBJECTIVE: To review the overall clinical research findings from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD), the world's largest study of BD. METHODS: STEP-BD was conducted from 1998 to 2005, enrolling participants (n = 4361) across 22 clinical sites in the United States. Each individual was followed for up to 2 years in naturalistic practice with blinded research assessments, while subgroups participated in randomized controlled trials (RCTs) for bipolar depression. The naturalistic database was used to examine the course of BD, comorbidity with other psychiatric disorders, and suicidality. Relevant studies in English, published from January 1, 1994, to May 31, 2009, were identified using computerized searches of electronic databases (PubMed, PsycINFO, and Cochrane Register of Clinical Trials), inspection of bibliographies, and review of other major reports. RESULTS: One large RCT involving the addition of either paroxetine or bupropion to mood stabilizers in acute depression found neither more effective than placebo in achieving sustained recovery (8 weeks of euthymia). A second large RCT found intensive psychosocial interventions superior to a brief psychosocial intervention as an adjunct to medication in acute depression. A third small RCT found minimal effects of lamotrigine, risperidone, or inositol in refractory depression. Recovery was difficult to achieve, with subsyndromal symptoms or full relapse very common. Anxiety disorders and smoking in particular were treatable conditions that adversely affected the course of BD. CONCLUSIONS: STEP-BD yielded numerous clinical and systems observations that provide fresh direction for research and treatment of BD, including setting new benchmarks for outcome and demonstrating the viability of large BD networks.
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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 | 0.051 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".