Problems of Perinatal Mental Health Care in Tokyo, Japan
Bibliographic record
Abstract
Recently, a dramatic increase in pregnancies complicated by mental disorders has been observed in Tokyo, Japan [1, 2]. In 2014, the estimated number of deliveries complicated by mental disorders was 1,800 [2]. The rate of general hospital with psychiatric inpatient beds is only about 16% of the delivery facilities in Tokyo; however, about 36% of the deliveries with mental disorders were managed by these general hospitals. These rates are feared to lead to the tremendous burden of both obstetrics and psychiatric staffs of the general hospitals in Tokyo. To know the reason why many deliveries with mild mental disorders are managed in a small number of general hospitals, we requested 85 private obstetric clinics to provide the reason why they introduced even deliveries with mild mental disorders to the general hospitals. Because many of the deliveries with mental disorders managed at the general hospital seemed to be not severe as necessary to be managed at the higher-order facilities. A total of 57 (67%) of them responded. The most common reason (26/57, 46%) was “We cannot examine the severity of mental disorders” and the second common reason was “It is difficult to take reservation of psychiatric clinics for pregnant women”. Therefore, they seemed to introduce all pregnant women suspected having mental disorders to the general hospitals. On the other hand, about 60% of the staffs of the psychiatric clinics in Tokyo seemed to be worried excessively about the influence of medications on both fetuses and pregnant women (Takeuchi and Okano, unpublished data). Therefore, some psychiatrists also seemed to introduce all pregnant women with mental disorders to the general hospitals. For the proper management of perinatal psychosis, it is necessary to build a smooth cooperation system of obstetricians and psychiatrists. As the first step of the cooperation, the guidelines for the determination of severity of mental disorders by obstetricians those obtained a consensus between the obstetricians and psychiatrists are needed.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".