An Exploration of the Mental Health impact among Menopausal Women: The MARIE Project Protocol (UK arm)
Bibliographic record
Abstract
ABSTRACT Introduction Menopause marks the end of the menstruation period which can incur naturally or due to surgery where the ovaries or the uterus is removed, or the use of other treatments like chemotherapy. Menopause elicits both physiological and psychological changes such as joint or pelvic pain, headaches or migraine, cognitive function and mental health problems such as anxiety. In order to assess the mental health impact of menopause, the physiological, psychological and sociological composites need to be evaluated. It is increasingly recognised that the associated symptoms experienced by women and trans-men are specific to menopause transition, making it challenging to diagnose and treat using conventional methods. We developed a menopause tool called MenopAuse mental hEalth (MARiE) rating tool following a co-production workshop. The MenopAuse mental hEalth (MARIE) project’s overall aim is to explore the mental health impact of menopause through several work stream packages and assess the MARiE tool. The current work package (WP 2a and 2b) that is represented within this study aim to further explore menopause symptoms and then validate and, determine the efficacy of the MARiE tool. Methods We will conduct a prospective mixed methods study in the United Kingdom (UK) among women and trans-men ≥18 years old that are perimenopausal, menopausal or post-menopausal. The quantitative portion will use the Hospital Anxiety and Depression Scale, Insomnia Severity Index Scale, Menopause Rating Scale, Greene Climacteric Scale, Health related quality of life, Quebec Pain Disability Scale, and Burnout Assessment Tool in addition to the MARiE tool within the scope of WP2a and WP2b, respectively. The qualitative component will use a topics guide. Research Ethics and Health Research Authority approval has been obtained with a reference of 22/EE/0159. Dissemination The findings will be submitted for publication in peer-reviewed journals and presented at women’s health, primary care, and mental health themed conferences.
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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 | 0.034 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".