Women's mental health: current issues and controversies
Bibliographic record
Abstract
Much has been learned about female-specific psychiatric disturbances since Hippocrates's disciples described, in a treatise titled The Sickness of Virgins, a range of behavioral changes including delusions, hallucinations and suicidal thoughts, supposedly attributed to "retained menstrual blood".Many centuries afterwards, Maudsley pointed out the possibility of ovarian failure being associated with behavioral changes in aging women, with his definition of climacteric melancholia.Much has yet to be learned or fully understood though.In the 21st century, epidemiologic surveys show that depression now is one of the top three causes of disease burden among females, leading to a significant negative impact on women's quality of life and social functioning.Yet, there is a paucity of consistent data on gender differences with respect to treatment outcomes, or on the association between sex hormones and psychiatric disturbances.I am thrilled that the Editors of the Revista Brasileira de Psiquiatria acknowledged the need for increasing awareness of women's mental health issues by supporting this supplement.We have chosen the theme Women's mental health: current issues and controversies and were fortunate to gather an excellent team of clinicians and investigators to collaborate with us.In this supplement, the readers will find updated reviews on gender differences in anxiety (by Kinrys & Wygant), domestic violence, trauma and addiction (by Zilberman & Blume), postpartum depression (by Zinga et al), and reproductive-cycle related trauma (by Born et al).Lastly Rennó et al report on some current challenges and perspectives in research in women's mental health in Brazil.We hope this supplement will serve as 'food for thought' for clinicians and health professionals, and inspire more colleagues to dedicate their clinical and research time to this important but understudied field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.038 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 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".