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Symposia

Women's Issues

Novel Methods in Studying Effects of the Menstrual Cycle on Mood and Behavior: Implications for Research and Practice

2 - (SYM 53) Standardizing Continuous Menstrual Cycle Measurement in Research and Clinical Practice: Introducing the Menstrualcycler Package for Phase-aligned Cycle Time Scaling (PACTS)

Sunday, November 23, 2025
12:42 PM - 1:03 PM CST
Location: Imperial 12, Level 4
Keywords: Women's Health, Research Methods, Emotion
Recommended Readings: Peters JR, Schmalenberger KM, Eng AG, Stumper A, Martel MM, & Eisenlohr-Moul TA (2025). Dimensional Affective Sensitivity to Hormones across the Menstrual Cycle (DASH-MC): A transdiagnostic framework for ovarian steroid influences on psychopathology. Molecular Psychiatry, 30, 251-262.,   Schmalenberger KM, Tauseef HA, Barone JC, Owens SA, Lieberman L, Jarczok MN, Girdler SS, Kiesner J, Ditzen B, Eisenlohr-Moul TA. How to study the menstrual cycle: Practical tools and recommendations. Psychoneuroendocrinology. 2021 Jan;123:104895. doi: 10.1016/j.psyneuen.2020.104895. Epub 2020 Oct 13. PMID: 33113391; PMCID: PMC8363181.,   Andersen EH, Nagpal A, Eisenlohr-Moul TA, Gordon JL. A novel method for quantifying affective sensitivity to endogenous ovarian hormones. Psychoneuroendocrinology. 2024 Sep;167:107095. doi: 10.1016/j.psyneuen.2024.107095. Epub 2024 Jun 6. PMID: 38896987.,   Nolan LN & Hughes L (2022). Premenstrual exacerbation of mental health disorders: a systematic review of prospective studies. Archives of Women's Mental Health, 25(5), 831-852.,  
Abstract Body


Background: Hormonal fluctuations across the menstrual cycle interact with various neural vulnerabilities to drive the symptoms of premenstrual disorders (PMDD, PME of psychiatric disorders) and influence high-risk outcomes like substance use and suicidality. However, standard methods for cycle tracking introduce misalignment between symptom timing and hormonal events, limiting diagnostic accuracy and research insights. Fixed day counting and phase-based grouping fail to account for individual variability in cycle length and ovulation timing, reducing precision and comparability of results in meta-analyses.


Methods: We introduce Phase-Aligned Cycle Time Scaling (PACTS), a standardized protocol and algorithm for coding continuous cycle time, along with the open-source menstrualcycleR R package to facilitate adoption. PACTS anchors cycle time to both menses and ovulation, ensuring correct alignment of the follicular and luteal phases, and expands or contracts observations to align with percentage of phase elapsed and associated hormonal events. We validated PACTS in a longitudinal dataset (N = 67,2315 data points), comparing its ability to align hormone-symptom relationships against traditional counting methods.


Results: PACTS significantly reduced misalignment of estrogen dynamics, particularly in the variable-length follicular phase. Compared to traditional methods, PACTS better captured the follicular periovulatory rise in estradiol (E2). For luteal phase tracking, PACTS performed similarly to backward counting, but may prove more valuable in populations with greater cycle length variability (e.g., puberty, perimenopause). Generalized Additive Mixed Models (GAMMs) demonstrated strong performance in recovering cyclical hormone patterns when combined with PACTS, and can be used to precisely evaluate effect size as percentage of total variance explained by the cycle and individual differences in response to the cycle.


Conclusions: PACTS provides a clinically scalable, standardized approach for menstrual cycle research, improving assessment, diagnosis, and treatment planning for cycle-related mental health conditions. The menstrualcycleR package streamlines implementation, making hormone-aligned symptom tracking more accessible to clinical psychologists and researchers.