MENSTRUAL CYCLE AFFECTIVE CHANGE AS A DIMENSIONAL CLINICAL PHENOMENON IN PSYCHIATRIC OUTPATIENTS AND CONTROLS: SUPPORT FOR CONTINUOUS RATHER THAN CATEGORICAL CONCEPTUALIZATION

The fluctuating ovarian hormones of the menstrual cycle can affect psychiatric symptom patterns of almost any disorder, ranging from mild, transient symptoms (often termed “premenstrual syndrome”), to clinically significant exacerbation of a chronic underlying disorder (perimenstrual exacerbation), to severe symptoms that arise exclusively prior to menses and remit completely (premenstrual dysphoric disorder). Regardless of severity or underlying diagnosis, each of these examples represent a manifestation of Menstrual Cycle Affective Change (MCAC), or affective symptoms that are influenced by predictable fluctuations in estradiol and progesterone during the normal menstrual cycle. MCAC is often studied in case-control research designs; however, MCAC as a biological phenomenon likely exists on a continuous spectrum, without a natural cutoff point that would separate cases or controls in a biologically meaningful way. In the present study, we argue that MCAC is often better conceptualized for research studies as a continuous outcome variable, rather than a dichotomous grouping variable. We then run multilevel models to identify the best-fitting model parameters for analyses where both menstrual cycle time and MCAC symptom trajectories are represented as continuous variables. While case-control designs are necessary and appropriate in many clinical contexts, the present work illustrates an example whereby with a transdiagnostic psychiatric sample, continuous variables are a truer representation of the data distribution than artificial dichotomization. This work lays the foundation for future studies of MCAC in this transdiagnostic sample of psychiatric outpatients.