Premenstrual Symptom Screening Tool for Working Women

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Abstract

The assessment of premenstrual syndrome (PMS) within occupational contexts has historically been constrained by instruments designed primarily for clinical psychiatric diagnosis. This newly developed screening tool represents a significant paradigm shift, moving away from purely mood-focused diagnostic criteria to capture the functional and physical realities of menstruating Employees. By integrating both somatic complaints and psychological distress, the instrument provides a more holistic picture of how premenstrual symptoms manifest in the workplace and disrupt occupational functioning.

Developed through a rigorous, multidisciplinary consensus process, the scale was specifically tailored for working women. It addresses a critical blind spot in existing psychometric assessments by explicitly linking symptom severity to workplace productivity metrics, such as absenteeism and presenteeism. The development phase utilized a large, representative sample of Japanese working women, ensuring the tool's relevance to contemporary occupational health challenges.

For psychometricians and occupational health researchers, this instrument offers a validated, standardized method to quantify the often-invisible burden of premenstrual distress. By providing a reliable metric for symptom severity that correlates with actual work impairment, the tool enables organizations to make data-driven decisions regarding workplace accommodations, menstrual leave policies, and targeted employee wellness interventions.

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Keywords
premenstrual syndrome
occupational health
absenteeism
psychometrics
workplace productivity
screening tool

📊 Psychometric Scorecard

Items Count
47
Structure
Multidimensional
Validation Country
📍 Japan

Authors

👤 Chihiro Takenoshita

👤 Kisho Shimizu

👤 Miho Iida

👤 Fumiaki Taka

👤 Eri Maeda

👤 Songee Jung

👤 Kyoko Nomura
✉ [email protected]
🏛 Akita University

Purpose

Existing diagnostic frameworks for premenstrual disorders, such as the Premenstrual Symptoms screening tool (PSST) and the Daily Record of Severity of Problems (DRSP), were fundamentally designed to align with DSM criteria. Consequently, they heavily weight affective and mood-related symptoms while frequently underrepresenting the somatic and physical complaints that drive functional impairment. This creates a significant measurement gap in occupational health, where physical discomfort often directly precipitates absenteeism and reduced work efficiency.

This novel screening tool was engineered specifically to bridge that gap by capturing a comprehensive spectrum of functionally relevant symptoms. Rather than attempting to redefine the clinical diagnosis of Premenstrual Dysphoric Disorder (PMDD), the developers sought to create a practical, workplace-oriented metric. For researchers and occupational health clinicians, this instrument is vital because it translates subjective premenstrual distress into quantifiable data that can predict productivity loss, thereby justifying and guiding structural workplace support systems.

Construct

The instrument is grounded in a multidimensional, biopsychosocial model of premenstrual distress, conceptualizing PMS not merely as a psychiatric or purely physiological phenomenon, but as a complex syndrome that interacts with a woman's occupational environment. The theoretical framework posits that premenstrual symptoms operate across distinct but interconnected domains that collectively degrade an individual's functional capacity at work.

During the initial item generation phase, the construct was operationalized into four primary conceptual domains: physical symptoms, psychological symptoms, work-related functioning, and abdominal symptoms. This structure acknowledges that while mood lability and emotional exhaustion (psychological symptoms) are critical, localized pain (abdominal symptoms) and systemic physical fatigue (physical symptoms) are equally responsible for occupational impairment. By mapping these symptoms directly to work-related functioning, the scale captures the downstream behavioral consequences of the syndrome, such as decreased motivation and impaired interpersonal dynamics in the workplace.

Validity

The validation framework for this instrument was highly robust, employing a tripartite approach to establish concurrent, criterion, and construct validity. To demonstrate concurrent validity, the researchers mapped the new scale against the Copenhagen Burnout Inventory (CBI). This was a strategic choice based on the hypothesis that the autonomic and psychological burden of PMS exacerbates emotional exhaustion and burnout, which serve as proxies for occupational health status.

Criterion validity was evaluated by comparing the new tool's performance against the established Premenstrual Symptoms screening tool (PSST), ensuring that while the new scale expands into physical and occupational domains, it remains anchored to recognized clinical benchmarks for premenstrual distress. Finally, construct and predictive validity were rigorously tested using logistic regression models to determine how well the scale scores could predict actual self-reported absenteeism. By demonstrating that higher symptom burdens on this scale reliably forecast missed workdays, the developers provided compelling evidence of the tool's practical utility in real-world occupational settings.

Convergent & Discriminant Validation Correlations

Reference Instrument Correlation Coefficient (r)
Copenhagen Burnout Inventory (CBI)
Premenstrual Symptoms screening tool (PSST)

Reliability

To ensure the stability and internal consistency of the instrument, the psychometric evaluation utilized both Cronbach's alpha and McDonald's omega coefficients. While Cronbach's alpha remains the traditional standard for estimating reliability, the inclusion of McDonald's omega represents a more contemporary and rigorous psychometric practice, as it does not assume tau-equivalence among items and often provides a more accurate reflection of a scale's true reliability.

Furthermore, the researchers analyzed item-test and item-rest correlations to verify that each individual question meaningfully contributed to its respective subscale without introducing excessive noise. This meticulous approach to internal consistency ensures that the distinct domains of the scale—whether measuring psychological distress or physical pain—are psychometrically cohesive and reliably capture the intended facets of the premenstrual experience across different administrations.

Factor Analysis

The structural integrity of the scale was evaluated using a highly rigorous cross-validation methodology. Rather than running analyses on the entire dataset simultaneously, the researchers utilized Bernoulli sampling to randomly split their large cohort of 3,239 participants into two independent subsamples. The first half (n = 1,597) was subjected to Exploratory Factor Analysis (EFA) using maximum likelihood estimation and Promax oblique rotation, which appropriately accounts for the expected correlations between different symptom clusters.

Following the EFA, which trimmed the initial 47-item pool by eliminating items with factor loadings below 0.50 or significant cross-loadings, the derived structure was strictly tested on the second subsample (n = 1,642) using Confirmatory Factor Analysis (CFA). The researchers targeted stringent, modern fit indices to confirm the model, aiming for an RMSEA of less than 0.08, a CFI greater than 0.90, and a TLI exceeding 0.95. Convergent validity within the factor structure was further verified by ensuring the Average Variance Extracted (AVE) met the acceptable threshold of 0.50, confirming that the latent factors adequately explained the variance of their constituent items.

Instrument

Test Type screening tool
Format 47 initial items, 5-point Likert scale
Scoring 0 = no symptoms, 1 = slight symptoms, 2 = moderate symptoms, 3 = severe symptoms, 4 = very severe symptoms
Language Japanese
Population Employees, Adults
Age Group 18-41 years
Administration Self-administered online questionnaire

Premenstrual Symptom Screening Tool for Working Women Items

📋 Items are currently not available

The individual items of this scale are not publicly available. Researchers interested in using this instrument should contact the original authors directly to request the scale materials.

Sample

The study utilized a sample of 3,239 Japanese working women aged 18 to 41 years (mean age = 32.6, SD = 5.3). Participants were recruited via an internet research agency (GMO Research, Inc.). The sample excluded pregnant, postpartum, and postmenopausal women. The cohort was diverse in occupation, comprising clerical workers (49%), service workers (18%), and professional/technical workers (15%).

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Cite This Paper

Chihiro Takenoshita, Kisho Shimizu, Miho Iida, Fumiaki Taka, Eri Maeda, Songee Jung, Kyoko Nomura (2025). Premenstrual Symptom screening tool for Working Women. BMC women's health. https://doi.org/10.1186/s12905-025-04092-5

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References
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Cite this article

(2026). Premenstrual Symptom Screening Tool for Working Women. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/s/premenstrual-symptom-screening-tool-for-working-women/

. "Premenstrual Symptom Screening Tool for Working Women." PSYCHOLOGICAL SCALES, 12 Aug. 2026, https://scales.arabpsychology.com/s/premenstrual-symptom-screening-tool-for-working-women/.

. "Premenstrual Symptom Screening Tool for Working Women." PSYCHOLOGICAL SCALES, 2026. https://scales.arabpsychology.com/s/premenstrual-symptom-screening-tool-for-working-women/.

(2026) 'Premenstrual Symptom Screening Tool for Working Women', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/s/premenstrual-symptom-screening-tool-for-working-women/.

[1] , "Premenstrual Symptom Screening Tool for Working Women," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, August, 2026.

. Premenstrual Symptom Screening Tool for Working Women. PSYCHOLOGICAL SCALES. 2026;vol(issue):pages.

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