Psychobiological stress and premenstrual symptoms across the menstrual cycle: protocol for an ecological momentary assessment (ISSAC) study.

All EMA assessments will be carried out via the smartphone-based app ‘movisensXS’ (V.1.8.1 46 ]. The EMA study period will span approximately two menstrual cycles and is designed to capture two perimenstrual windows, including the week prior to the onset of menses (cycle days −7 to −1) and a postmenstrual reference week (cycle days +4 to +10). EMA assessments will commence mid-cycle, prior to ovulation in the first cycle, and continue through to cycle day 10 of the third cycle, ensuring coverage of the targeted phases across two cycles. After the baseline assessment, participants will start with the daily assessments 4 days prior to the earliest estimated day of ovulation (Earliest estimated day of ovulation = (shortest cycle length of the previous 3 cycles) – 14 days. See recommendations by Schmalenberger et al. 44 ). The EMA period will be divided into two study phases. Phase 1, spanning from the start of the EMA period to 2 days after a positive LH-test in cycle 2, will be an intensive data collection phase involving five daily assessments at specific time points: (1) on awakening, (2) 30 min after awakening, (3) 14:00, (4) 19:00 and (5) before bedtime (see figure 1 ). The assessments on awakening and before bedtime will be self-initiated by participants, while the remaining assessments (30 min after awakening, at 14:00 and at 19:00) will be automatically triggered by the study application. Saliva samples will be collected via passive drool during the two morning assessments (on awakening and 30 min after awakening) and the 19:00 assessment. Participants will be instructed to initiate the awakening assessment and collect the first saliva sample while still lying in bed. Phase 2 will start on the third day after the positive LH-test in cycle 2 and continue until cycle day 10 of cycle 3, following a less intensive protocol that will consist solely of the daily assessment before bedtime.

The Interactions between premenstrual Symptoms and Stress Across the menstrual Cycle (ISSAC) study aims to delineate how psychobiological stress patterns—indexed by subjective stress together with endocrine (cortisol) and autonomic (sAA) measures—relate to the emergence and intensity of premenstrual symptoms across the menstrual cycle. This study employs a comprehensive EMA design encompassing multiple daily assessments across two consecutive menstrual cycles, complemented by a baseline assessment before the EMA period and a post assessment after its completion. These EMA assessments collect real-time data on momentary and daily stress levels and premenstrual symptoms, alongside ambulatory saliva sampling for salivary cortisol (sCort) and sAA as biomarkers of HPA-axis and SNS-related activity, respectively. Aiming to provide a deeper understanding of the temporal dynamics between stress and PMDD symptoms, the study examines daily associations, concurrent associations (ie, at the same time point) and time-lagged associations (i.e., from one time point to the next). The study design and hypotheses (except hypothesis 5) were preregistered with Open Science Framework ( https://doi.org/10.17605/OSF.IO/F3T5U ).

Before the main data collection, we conducted a feasibility study (May–June 2024; n=7 psychology students) to assess protocol feasibility and app functionality. The findings informed the finalised study design described here. Participants completed a 14-day protocol comprising five EMA prompts and three saliva samples per day. In addition, they were instructed to self-initiate an assessment in moments of acute stress and to collect a saliva sample at stress onset and 20 min later to index cortisol responses in daily life. Participants were generally satisfied with the study (71.4%), found the app items easy to understand (100%) and judged the overall burden as appropriate (71.4%). However, most (85.7%) reported difficulty completing app entries during acute stress episodes. Based on these findings, event-based assessments during acute stress were omitted and app usability was further improved for the finalised design.

There was no patient or public involvement in developing this study protocol. All participants will receive feedback on their individual premenstrual symptom patterns and have the option to schedule an individual feedback session.

Baseline assessment will include demographic information (age, gender, education), medical history (medication, somatic and psychiatric diagnoses), reproductive history and status 44 and questionnaires on trauma exposure (International Trauma Exposure Measure; ITEM 47 ), symptoms of Posttraumatic Stress Disorder (PTSD Checklist for DSM-5; PCL-5 48 ), chronic stress (Perceived Stress Scale; PSS 49 ), emotion regulation (Emotion Regulation Questionnaire; ERQ 50 ), a questionnaire on premenstrual symptoms 51 and depressive symptoms (Patient Health Questionnaire-9; PHQ-9 52 ). At the follow-up assessment, on completion of the EMA period, participants will again complete the PSS and ERQ. Additionally, they will be asked to provide feedback on their experience with the study, including questions about the representativeness of the study period for their everyday life experiences. Multiple EMA assessments per day will be conducted to assess daily levels of PMDD symptoms and stress, as well as to capture real-time fluctuations in these variables throughout the day (see figure 1 ). Daily assessments will be completed during the bedtime assessment, while momentary assessments will be conducted at the remaining time points (excluding awakening). A complete list of EMA items can be found in the Supplemental file 1 . The following measures will be included. To assess overall premenstrual symptom patterns and classify participants as MRMD or PMDD, premenstrual symptoms will be evaluated daily in the evening using a validated symptom diary. 53 The diary was adapted to a 6-point Likert scale to support the application of the Carolina Premenstrual Assessment Scoring System (C-PASS) algorithm 7 for identifying symptom patterns consistent with MRMD or PMDD. For each symptom the C-PASS requires (a) a minimum of 30% premenstrual symptom elevation, (b) postmenstrual clearance (maximum mid-follicular (cycle days +4 to +10) rating ≤3—mild), (c) sufficient severity (premenstrual week (cycle days −7 to −1) maximum rating ≥4—moderate), (d) sufficient duration (≥2 days in the premenstrual week in which the symptom is rated ≥4—moderate). PMDD requires at least five symptoms, including at least one core affective symptom, whereas MRMD requires at least one core affective symptom without a minimum total symptom count. At the person level, PMDD or MRMD is classified when the respective cycle-level criteria are met in at least two cycles. Details on the diagnostic procedure can be found in. 54 The C-PASS algorithm will also be applied to identify symptom patterns suggestive of PME (a minimum of 30% premenstrual symptom elevation). PME cases will be included in all primary analyses. In the group comparisons, PME cases will be assigned to the diagnostic group alongside MRMD and PMDD cases. To assess the robustness of the findings, all analyses will be repeated with PME as a covariate. In addition, exploratory analyses will examine outcomes specifically associated with PME, contingent on sufficient statistical power. We will continuously monitor whether participants meet MRMD/PMDD criteria as data collection progresses. If interim monitoring indicates that too few participants meet criteria to adequately power group-based hypotheses, we will implement targeted enrichment strategies, including recruitment through clinical practices and support organisations. Eligible individuals whose prescreening responses (“Do you regularly experience psychological symptoms before the onset of your menstrual bleeding, such as mood swings, depressed mood, anxiety, or irritability, that interfere with your daily life?” answered with “moderate” or “severe” symptoms) indicate higher levels of premenstrual symptoms will be oversampled. To capture real-time fluctuations in affective symptoms, momentary affective symptoms will be assessed at four daily time points (all besides awakening) using items adapted from the validated premenstrual symptom diary. 53 Participants will rate their current affective states on a 6-point Likert scale. The diary item ‘Had conflicts or problems with people’ was split into two momentary items to assess both the internal state (‘Feeling like I could easily get into an argument with someone’) and its behavioural consequence (‘Have you had conflicts with others since the last assessment?’). To evaluate participants’ overall perception of daily stress, participants will be asked during the bedtime assessment to indicate how stressed they felt throughout the day. Responses will be recorded on a visual analogue scale (VAS) ranging from 0 (‘not at all’) to 100 (‘very much’). To assess fluctuations in stress levels throughout the day, momentary stress will be measured at four daily time points (all besides awakening) using a single-item question: ‘How stressed do you feel at the moment?’. Participants will respond on a VAS ranging from 0 (‘not at all’) to 100 (‘very much’). To control for unusual major stressors, participants will be asked daily during the bedtime assessment whether that day was a typical day in their lives (‘Was today a typical day in your life?’) and if it was not, they will be asked to indicate what has been unusual about the day. Saliva samples will be collected at the two morning assessments (on awakening and 30 min after awakening) and the 19:00 assessment. The smartphone app will guide participants through each saliva collection. Participants will be instructed to accumulate saliva in their mouth for 2 min while a timer runs in the app recording the collection duration. They will then transfer the saliva collected via passive drool into a polypropylene tube using a straw. Participants will be instructed to store their samples in a freezer at home throughout the study period. At the follow-up assessment, samples will be returned to the study team and subsequently stored at −30°C. To capture within-day dynamics of sCort and salivary sAA, trapezoid-based and change-based indices will be computed separately for each biomarker and day. 55 The AUC with respect to ground (AUC G ) will index overall output across all three daily samples, whereas the delta increase (awakening to 30 min post-awakening) will index the awakening response. In addition, daily cortisol and alpha-amylase slopes will be calculated by subtracting the awakening value from the evening value (at 19:00). sAA and sCort are influenced by multiple potential confounders that may bias results if not adequately controlled. 56 57 Therefore, the following control variables will be assessed at every saliva collection: Participants will be asked whether they have (1) slept in the last 2 hours, (2) drunk anything other than water in the last 2 hours, (3) consumed nicotine in the last hour, (4) eaten in the last hour, (5) been physically active in the last 2 hours, as well as (6) taken any medication in the last hour and if so, what medication. Additionally, awakening time will be recorded within the app, and all analyses will include timing of sampling relative to awakening. Accurate sampling timing is critical for validity of sCort and sAA indices, particularly for the awakening response. 56 Accordingly, the precise collection time for each saliva sample will be logged in the app (timestamp) and securely matched with the respective sample via a unique identifier. Ovulation will be identified by a chromatographic ovulation test (Ovulation Test Digital, Clearblue, SPD Swiss Precision Diagnostics GmbH) detecting the surge of LH (sensitivity: 25 mIU/mL). Participants will begin daily testing 4 days prior to the earliest estimated day of ovulation and continue until a positive result is obtained or until cycle day 21 if no positive result occurred by then. Cycle lengths will be determined based on self-reported dates of at least three menstrual onsets prior to the study, the menses onsets during the study period, and the first menstruation following study completion.

Before entering the study, eligibility criteria will be checked in an online questionnaire and confirmed in personal contact with the study team. After enrolment, the procedure will consist of an on-site baseline assessment during the follicular phase (days +4 to +10 after menstrual onset), daily EMA assessments across two menstrual cycles and an on-site follow-up assessment during the late-luteal phase (days −8 to −5 before the expected onset of menstruation). The mid-follicular phase was selected as a low-symptom reference window for the baseline assessment, 7 whereas the follow-up assessment will be scheduled during the late-luteal phase to capture the period of expected peak symptom severity. This timing maximises the contrast between cycle phases and enables within-person comparisons for questionnaires administered during both assessments. A study overview is presented in figure 1 . At the on-site baseline appointment, participants will meet with a trained member of the study team to provide written informed consent and complete baseline questionnaires (see ‘Measures’ for details). They will then receive standardised instructions for the two-cycle EMA protocol, urinary ovulation tests (luteinising hormone-tests; LH-tests) with usage guidance, a study manual and—if their personal device does not meet software requirements or participants decline the use of their own—a study smartphone. Participants will also receive sampling tubes for saliva collection for the assessment of sCort and sAA. Saliva will be collected via passive drool using SaliCaps (IBL International GmbH, Hamburg, Germany). During the baseline visit, participants will complete a trial saliva collection to familiarise themselves with the procedure and will receive written and verbal instructions regarding sample handling and storage. Data collection began on 5 March 2025 and is projected to be completed by the end of 2026.

This study protocol outlines an EMA design spanning two consecutive menstrual cycles to investigate the temporal coupling between psychobiological stress patterns and PMDD symptoms. To our knowledge, this will be the first study to capture these associations at such high temporal resolution across the entire menstrual cycle. This design will enable a nuanced characterisation of both within-day and between-day associations between stress and symptoms, while integrating self-report on stress with endocrine and autonomic indices. Leveraging EMA in daily life ensures high ecological validity, minimising recall bias and enables high temporal resolution. By repeatedly sampling symptoms and stress in real time, the design is well suited to identify concurrent and lagged associations that are typically obscured in cross-sectional or retrospective approaches. The continuous coverage across two cycles further allows for the examination of reliability and person-specific patterns. Another key strength of the study is the inclusive sampling across the full continuum of premenstrual experiences, including considering PME-patterns, facilitating a dimensional understanding of stress-symptom dynamics and clarifying whether associations are specific to clinically significant presentations such as MRMD or PMDD or reflect graded vulnerabilities across the spectrum. The synchronised, multimodal assessment—combining subjective ratings with endocrine and autonomic indices—allows for a holistic characterisation of how stress relates to premenstrual symptomatology. At the same time, several limitations inherent to the study design should be kept in mind. The eligibility criteria may yield a relatively healthy, conscientious sample and thus constrain generalisability to populations with greater health burdens or daily schedules that do not permit participation in an intensive protocol. This may also lead to potentially excluding individuals with particularly high stress levels. In addition, recruitment for a menstrual-cycle study may also introduce selection and participation bias, attracting individuals who ascribe greater impact to the cycle, which could increase measurement reactivity. Furthermore, while momentary assessment reduces recall bias, it may systematically miss peak stress periods if participants are unable or unwilling to respond during acute stress, leading to underestimation of momentary stress levels. Additionally, the three-sample biomarker schedule may undercharacterise full diurnal profiles of cortisol and alpha-amylase, limiting sensitivity to diurnal dynamics. Finally, with regard to PME, this study can only capture premenstrual worsening of symptom domains that overlap with PMDD criteria, and therefore cannot fully account for cycle-related exacerbation across all possible psychiatric or somatic conditions. This protocol uses a multimodal, within-person approach that can guide clinical practice and future research. Identifying phase-specific windows of vulnerability can guide timing of stress-management strategies alongside standard treatments and facilitate the development of just-in-time interventions. From a research perspective, the synchronised assessment of subjective stress with endocrine and autonomic markers enables a more fine-grained examination of whether stress systems converge or dissociate in daily life and how psychobiological stress patterns relate to premenstrual symptoms across the menstrual cycle. Important next steps include extending this work to more diverse samples and clinical settings to improve generalisability, incorporating additional mechanistic pathways such as inflammatory processes 64 65 and neurosteroid-GABAergic sensitivity, 22 66 and examining potential moderators including trauma history and chronic stress exposure. 18 Taken together, the ISSAC study addresses fundamental questions about how psychobiological stress patterns unfold across the menstrual cycle and couple with premenstrual symptoms. With its multimodal approach—combining subjective ratings with biological assessments of endocrine and autonomic stress systems—the study findings are expected to deepen mechanistic insight into how stress physiology relates to premenstrual symptom expression. By identifying phase-specific windows of vulnerability, the study can further inform the development and timing of targeted stress-management strategies as a potential complementary treatment for MRMD and PMDD.

Daily associations: Higher daily mean subjective stress will be associated with greater daily PMDD symptom severity, with stronger associations in the premenstrual phase (days −7 to −1) than in the postmenstrual phase (days +4 to +10). Momentary associations: Higher momentary subjective stress will be associated with greater concurrent momentary affective symptoms, with stronger associations in the premenstrual than in the postmenstrual phase. Group differences: Individuals with MRMD/PMDD will show higher mean subjective stress levels than those without MRMD/PMDD. Within-person cyclicity: Individuals with MRMD/PMDD will exhibit higher stress in the premenstrual than the postmenstrual phase, whereas individuals without MRMD/PMDD will show no cycle-related within-person changes. Spillover effect: Higher stress levels during the follicular phase will relate to more severe symptoms during the subsequent luteal phase. Additionally, we will test bidirectional time-lagged associations between daily/momentary subjective stress and daily/momentary (affective) premenstrual symptoms. HPA axis (sCort): Individuals with MRMD/PMDD will show blunted cortisol dynamics relative to those without MRMD/PMDD—namely, a reduced cortisol awakening response (CAR), lower overall output (area under the curve; AUC) and a flatter diurnal slope—and lower CAR/AUC and a flatter slope will be associated with greater same-day PMDD symptom severity, with stronger differences in the premenstrual phase. Autonomic nervous system (sAA): Individuals with MRMD/PMDD will differ from those without MRMD/PMDD in sAA parameters—the awakening response, overall output (AUC), and diurnal slope—and these parameters will predict same-day PMDD symptom severity. As exploratory sensitivity analyses, we will further investigate whether examined associations differ among individuals with a symptom pattern suggestive of PME, characterised by premenstrual symptom worsening without full remission after the onset of menses.

All statistical analyses will be performed in R. 58 Preregistered hypotheses will be tested using multilevel (mixed-effects) regression models implemented in lme4 59 with two levels for the daily associations (observations on level 1 nested within individuals on level 2) and three levels for the concurrent associations (daily observations on level 1 nested within days on level 2 and within individuals on level 3). We will include random intercepts for individuals and random slopes for time-varying predictors. Categorical predictors will be dummy-coded; time-varying predictors will be person-mean centred and time-invariant predictors grand-mean centred. Where theoretically motivated, non-linear trends will be examined using polynomial terms. Model fit will be evaluated using likelihood-based comparisons and information criteria. All analyses will follow the preregistered data-processing and modelling decisions, with any deviations transparently documented. Cycle phase will be derived from daily LH-test results and participants’ reports of menstrual onset. To align observations across participants with different cycle lengths, cycle day will be mapped onto a standardised, cycle-referenced scale following Nagpal and colleagues 60 : menstruation is set to 0, negative values index the premenstrual (luteal) days from ovulation to menstruation, and positive values index the postmenstrual (follicular) days from menstruation to the next ovulation. This standardised cycle-day variable will be used to model and visualise continuous stress-symptom dynamics across the menstrual cycle. We will exclude participants or data entries from analysis under the following conditions: (a) The participant completes fewer than 50% of EMA entries, (b) the participant does not provide the data required for a specific hypothesis (exclusion only for the corresponding hypothesis), (c) for C-PASS-based MRMD/PMDD diagnosis, participants will be excluded if they do not meet the minimum threshold of three daily ratings within each premenstrual and postmenstrual week across two cycles. Additionally, all EMA data entries triggered by mistake will be excluded. Such entries will be identified based on participant reports and notes or by missing responses at the corresponding time points. To account for missing data, we plan to employ full-information maximum likelihood estimation for all variables in the multilevel models. Saliva sample data will be retained only when collection occurs within predefined timing windows. Based on the reported awakening time, awakening samples collected within 0–15 min and second morning samples (awakening+30 min) collected within 15–45 min after awakening will be considered valid. 56 Evening samples scheduled for 19:00 will be considered valid if collected between 18:00 and 20:00. 61 Samples collected outside these windows will be excluded from the analyses. With a target sample size of ~80 participants (expected compliance ~75%), we anticipate adequate power (≈ 0.80) to detect effects in the medium range under typical EMA assumptions (approximately 60 study days with an average of three assessments per day, averaged across study phases), based on calculations using EMAtools. 62 More fine-grained power calculations were not feasible at the protocol stage because the number and timing of observations are person-specific (varying cycle length, phase-specific sampling intensity, and variable compliance). Moreover, a realistic Monte-Carlo power analysis (e.g., 63 ) would require empirically grounded inputs (e.g., variance components and autocorrelation) from a comparable EMA design. To our knowledge, no such study exists. To contextualise sensitivity, we will therefore report detailed realised compliance (days observed, assessments completed) and the resulting estimation precision in the final manuscript. The study has been approved by the ethics committee of the University of Vienna (reference number: 00883). All participants will give written informed consent before taking part in the study. Findings will be disseminated through peer-reviewed journal articles and conference presentations, as well as targeted outreach to stakeholders, including patient groups and clinicians. To support transparency and reproducibility, the R code for all statistical analyses along with the corresponding datasets will be made openly available.

Participants will include 80 individuals between 21 and 45 years with regular menstrual cycles, representing a spectrum of premenstrual symptom severity. This ranges from those reporting no or mild symptoms to those experiencing symptoms severe enough to meet the diagnostic criteria for PMDD. Participants will be recruited via flyers distributed at healthcare centres, gynaecologists, universities, local facilities such as stores and social networks. To ensure representation across the full spectrum of premenstrual symptomatology, two targeted recruitment strategies will be employed: (1) materials that framed the study as a ‘menstrual cycle study’ to attract individuals at the healthier end of the spectrum and (2) materials specifically seeking individuals ‘suffering from premenstrual syndrome’ to recruit those with more severe symptoms. Individuals will be eligible if (a) they are aged between 21 and 45 years, (b) have a regular menstrual cycle (between 21 and 35 days, with fluctuations of less than 5 days in the preceding three cycles), (c) have working knowledge of German and (d) a body mass index of at least 17 and below 35 kg/m 2 . To exclude individuals undergoing the perimenopausal transition, participants older than 40 years will be asked additional screening questions informed by item 8 of the Reproductive Status Questionnaire 44 and the Stages of Reproductive Aging Workshop criteria. 45 Those reporting fluctuations in menstrual cycle length of more than 7 days within the previous 12 months or an episode of amenorrhoea lasting at least 60 days within this time period will be excluded. Individuals will be excluded if they (a) are pregnant or lactating during the last 3 months, (b) are taking psychotropic drugs or (c) medication known to affect stress-reactive somatic functioning or (d) hormonal contraceptives, (e) if they had been diagnosed with schizophrenia or bipolar disorder at any time during their life or with substance-induced disorders (unless in remission for at least 2 years), (f) suffer from a current severe somatic disease (eg, cancer, Morbus Crohn) or (g) endocrine disorders (Cushing, Addison), (h) gynaecological disorders that impact the menstrual cycle (eg, endometriosis, polyendocrine metabolic syndrome), (i) report heavy alcohol use in the past 3 months (defined as average number of drinks per week >8), (j) report use of illicit drugs in the 14 days preceding the study or were not capable and willing to refrain from these substances during the study period, (k) are shift workers and (l) have regular awakening times after 11:00. Participants will be reimbursed €120 for their participation, contingent on completing at least 90% of the EMA assessments. For compliance rates below 90%, the reimbursement will be reduced proportionally to the completion rate. As additional compensation, participants will be provided with individualised feedback on their premenstrual symptom patterns.