Psychosocial interventions in bipolar disorders: A guidelines’ review
Bibliographic record
Abstract
INTRODUCTION: Psychosocial interventions are essential in the treatment of severe mental disorders, including Bipolar Disorder. These interventions aim to enhance patients' psychopathology, alongside pharmacological treatments, while also improving personal functioning and quality of life. METHODS: We conducted a comprehensive review of available international guidelines concerning the treatment of Bipolar Disorder, specifically examining their recommendations on the efficacy and implementation of psychosocial interventions across different phases of the illness. The guidelines included in our review were from the National Institute for Health and Care Excellence (NICE), the Scottish Intercollegiate Guidelines Network (SIGN), the Royal Australian and New Zealand College of Psychiatrists (RANZCP), the American Psychiatric Association (APA), the Canadian Network for Mood and Anxiety Treatments (CANMAT), the International Society for Bipolar Disorders (ISBD), the British Association for Psychopharmacology (BAP), Bangladesh Association of Psychiatrists (BAP 2022), and the World Federation of Societies of Biological Psychiatry (WFSBP). RESULTS: The international guidelines endorse psychosocial interventions as supportive treatments in conjunction with pharmaceutical or psychotherapeutic approaches for Bipolar Disorder. CONCLUSIONS: Further research is needed to validate the suggested effectiveness of psychosocial interventions on the long-term outcomes of Bipolar Disorder.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".