Psychometric Properties of a DSM-5-Based Screening Tool for Women's Perceptions of Premenstrual Symptoms
Bibliographic record
Abstract
A premenstrual screening tool is needed when time constraints and attrition limit the feasibility of daily ratings. The present study examines the utility of a novel, 33-item, retrospective, dimensional, DSM-5-based, screening measure developed to explore women's perceptions of premenstrual symptomatology. This is the first measure that examines perception of impairment for each DSM-5 symptom and assesses the frequency criterion. Participants (N = 331) reported symptoms ranging from none to a level consistent with a provisional DSM-5 diagnosis of Premenstrual Dysphoric Disorder (PMDD). Initial psychometric properties indicated a five-factor structure: (1) affective symptoms; (2) fatigue, sleep, and anhedonia; (3) symptom frequency; (4) impairment and severity of appetite change and physical symptoms; and (5) difficulty concentrating. The total symptom scale and the frequency, severity, and impairment subscales demonstrated high internal consistency. Strong correlations between this dimensional measure and other retrospective and prospective premenstrual symptom measures suggest strong convergent, concurrent, and predictive validity. Premenstrual symptom groups created using this screening measure (minimal, mild/moderate, severe) differed on other retrospective and prospective measures of premenstrual symptoms. There was evidence of divergent validity and lack of an acquiescence bias. We also report data describing women's perceptions of the frequency, level of impairment, and level of severity for each DSM-5 PMDD symptom over a 12-month period and discuss implications for future research on premenstrual phenomenology. Initial evidence for the reliability and construct validity of this symptom screening measure suggests potential value for assessing premenstrual symptomatology in research and practice.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".