A DSM-5-based tool to monitor concurrent mood and premenstrual symptoms: the McMaster Premenstrual and Mood Symptom Scale (MAC-PMSS)
Bibliographic record
Abstract
BACKGROUND: Despite high co-morbidity between premenstrual dysphoric disorder and mood disorders, there is a gap of research-based tools to monitor concurrent premenstrual and mood symptoms. In this study, we developed a new DSM-5-based questionnaire to prospectively monitor concurrent premenstrual and mood symptoms. METHODS: Fifty-two females with bipolar or major depressive disorder, ages 16-45, were enrolled in the study. Participants completed two months of prospective symptom charting including the McMaster Premenstrual and Mood Symptom Scale (MAC-PMSS) and the Daily Record of Severity of Problems (DRSP). At the end of the prospective charting, participants also completed the Montgomery-Åsberg Depression Rating Scale (MADRS), Hamilton Depression Rating Scale (HDRS) and the Young Mania Rating Scale (YMRS). The MAC-PMSS was correlated with the DRSP, MADRS, HDRS and YMRS. RESULTS: All individual items of the MAC-PMSS correlated strongly with the individual DRSP scores (all p < 0.001). The mood section of the MAC-PMSS also significantly correlated with MADRS (r = 0.572; p < 0.01), HDRS (r = 0.555; p < 0.01) and YMRS scores (r = 0.456; p < 0.01). CONCLUSIONS: The MAC-PMSS is a reliable to tool to measure concurrent mood and premenstrual symptoms in women with mood disorders.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".