A systematic review on the effectiveness of dialectical behavior therapy for improving mood symptoms in bipolar disorders
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Evidence-based psychotherapies available to treat patients with bipolar disorders (BD) are limited. Dialectical behavior therapy (DBT) may target several common symptoms of BD. We conducted a systematic review on the efficacy of DBT for mood symptoms in patients with BD. The systematic search used key words related to DBT and BD in Medline, Embase, PsycInfo, CINAHL, and Cochrane Library databases from 1980 to April 1st, 2022. We included studies that enrolled patients with a BD I or II diagnosis (DSM or ICD), age 12 and older who received a DBT-based intervention. Studies reviewed were clinical trials including observational studies that reported at least one outcome related to BD mood symptoms or severity. We did not exclude based upon psychiatric or physical co-morbidity. RESULTS: We screened 848 abstracts and reviewed 28 full texts; 10 publications with 11 studies met our pre-determined eligibility criteria. All but one were feasibility pilot studies and most included participants in all mood states except for mania. The studies provided preliminary evidence suggesting these interventions may be effective for improving several core symptoms of BD. Overall, all the studies consistently supported that DBT-based interventions are feasible and acceptable for patients with BD. CONCLUSION: DBT may be an effective treatment for BD; however, the confidence in this conclusion is limited by the small sample sizes, heterogeneity, and high risk of bias in all published trials. Larger well-designed RCTs are now required to establish the effectiveness of DBT in BD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it