Menopausal transition and depression: who is at risk and how to treat it?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The menopausal transition may impose a challenge to clinicians and health professionals who are invested in improving women's quality of life; after all, this period in life is commonly marked by significant hormone fluctuations accompanied by bothersome vasomotor symptoms (e.g., hot flushes and night sweats) and other somatic complaints. In addition, more recent epidemiologic data demonstrate that some women transitioning to menopause may be at higher risk for developing depression when compared with their risk during premenopausal years; this increased risk appears to be true even among those who had never experienced depression before. In this article, putative contributing factors for this window of vulnerability for depression during the menopausal transition are critically reviewed. Hormonal and nonhormonal factors that may contribute to the occurrence of physical and/or psychiatric complaints during the menopausal transition are discussed. Lastly, existing evidence-based treatment strategies are summarized.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it