Kayla Joyce

By Kayla M. Joyce and Sherry H. Stewart

Daily diary methodology is becoming popular in human menstrual cycle (MC) research. However, variations in MC length makes it difficult to examine fluctuations in dependent variables (e.g., substance use levels), across the MC. Existing analytic approaches collapse data across MC phases, examining phase-related changes; however, a loss of potentially vital information can result when data is collapsed across phase. Additionally, current phase designation methods (phase designation and days within each phase) vary substantially across studies, making it difficult to interpret/compare results across studies. To address these problems, two methods were developed to standardize intensive longitudinal data collected via daily diary methodologies—phasic and continuous standardization. Phasic standardization accounts for individual variability in MC length by allowing luteal phase length differences while remaining phases are fixed, enabling the analysis of phasic variations. Alternatively, continuous standardization accounts for individual variability in MC length by standardizing the luteal phase to a seven-day phase, while remaining phases are fixed, allowing for the exploration of continuously reported variables across MC day. This chapter will discuss how to standardize daily diary data collected across the MC using phasic and continuous standardization methods and demonstrate the two standardization methods using two clinically-relevant hypothetical examples.

Part of the book: Menstrual Cycle

By Kayla M. Joyce and Sherry H. Stewart

The Premenstrual Assessment Form–Short Form (PAF-SF) is a 10-item measure that assesses premenstrual symptom severity. There is little research assessing the PAF-SF’s psychometrics and proposed subscales (affect/water retention/pain). This chapter aims to assess the 10-item PAF-SF’s psychometric properties (i.e., internal consistency, and structural/criterion-related/known groups validity). Eighty-seven naturally cycling females (M_age = 28.86 years, SD = 6.11) participated. Participants completed the 10-item PAF-SF; the State-Trait Anxiety Inventory–Trait subscale (STAI-T); and the Structured Clinical Interview for DSM-5 (SCID-5) premenstrual dysphoric disorder (PMDD) module. With principal components analysis, we extracted and compared three-factor (affect/water retention/pain) and two-factor (psychological/physiological) solutions for the PAF-SF. The two-factor solution was selected for its greater interpretability, simple structure, internal consistencies, and parsimony. Participants with versus without a provisional PMDD diagnosis had higher psychological subscale scores; unexpectedly, PMDD group differences were not observed on the physiological subscale. Psychological, but not physiological, subscale scores were positively correlated with trait anxiety and PMDD affective symptom count. Scores on the physiological subscale were positively correlated with the PMDD somatic symptom count. Psychological subscale scores were also positively correlated with the PMDD somatic symptom count. The 10-item PAF-SF appears to be a reliable and valid measure of premenstrual symptom severity and comprises psychological and physiological symptom domains.

Part of the book: New Research on Menstrual Cycle [Working title]