The Use and Evaluation of Long-acting Injectable Antipsychotic Medications in Community-Dwelling Patients with Schizophrenia in Guangdong Province, China.
Bibliographic record
Abstract
Schizophrenia is a chronic, severe mental disorder with high disability and high recurrence, causing a serious burden to patients, their families, and society, and is an important public health problem.Most of the patients with schizophrenia live in the community, and antipsychotic maintenance treatment is essential to prevent recurrence.However, non-adherence to antipsychotic medications is one of the most important factors increasing relapses in schizophrenia, and nearly 60% of patients with schizophrenia are non-adherent to antipsychotic medications. 1 A systematic review and meta-analysis showed strong superiority of long-acting injectable antipsychotics (LAIs) in improving medication adherence and preventing recurrence compared to oral antipsychotics.2 In the past decade, developed countries like Canada, Australia, and the United States have widely used LAIs for patients with schizophrenia in communities, showing that they can improve patients' treatment compliance and social function and reduce violence and readmission rates.3 However, a study using data from 15 Asian countries/regions showed that the rate of use of LAIs to treat patients with schizophrenia in China is only 0.66%, far lower than the average of 15 countries/regions (17.9%).4 The regional variances in healthcare systems, such as availability of drugs, pharmaco-economics, and prescribing habits of psychiatrists, may play a role in the low rate of use of LAIs.In China, health insurance does not fully cover the cost of LAIs, so the higher price, poorer accessibility of LAIs, and lower socioeconomic level of the patients with schizophrenia could hinder using LAIs.5 Recommendation and Policy Support of Long-acting Injectables in ChinaAccording to the Guidelines for the Management and Treatment of Severe Mental Disorders (2018 edition) issued by the Chinese National Health Commission, LAIs were recommended for patients with poor treatment compliance, poor home care or no caregiver, or high risk of suicides and accidents.6 The Chinese Schizophrenia Coordination Group, Chinese Society of Psychiatry, and Chinese Society of General Practice established an expert group and developed a consensus on LAIs in the treatment of community-dwelling patients with schizophrenia in 2020, and put forward evidence-based recommendations on their clinical use.7 However, most psychiatrists and general practitioners still lack training on using LAIs antipsychotics in China and worry that the side effects of injection treatment may impede their spread and application.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".