Do people with bipolar disorders have access to psychosocial treatments? A survey in Italy
Bibliographic record
Abstract
BACKGROUND: Several guidelines consider psychosocial treatments an essential component of clinical management of bipolar disorders in addition to drug therapy. However, to what extent such interventions are available in everyday practice to the average patient attending mental health services is not known. AIMS: This study aims to investigate access of people with bipolar disorders to psychosocial treatments in a community-based care system. METHOD: Information on care delivery and service utilization were retrieved from the psychiatric database of Lombardy, Italy, covering a population of 9,743,000, for all adults who had at least one contact in 2009 with psychiatric services. Rates of patients with a diagnosis of bipolar disorder who had access to individual psychotherapy, couple/family therapy, group psychotherapy and family interventions were calculated and compared to patients with schizophrenia and depression. RESULTS: A total of 8,899 subjects with bipolar disorder had been in contact with psychiatric services, corresponding to a treated annual prevalence rate of 1.1‰. More than 80% of patients were treated in community settings. Rates of patients receiving structured psychosocial treatments ranged from 0.7% for couple/family therapy to 6.1% for individual psychotherapy. No differences with patients with schizophrenia and depression were found. Patients with schizophrenia received more interventions labeled as rehabilitation. CONCLUSION: Few people with bipolar disorders had access to psychosocial treatments. Even in a well-developed system of community care, offer of psychosocial interventions for bipolar disorders is inadequate. This issue should be a target for future research on dissemination and implementation strategies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".