Supporting Athletes’ Various Needs – A Design Study Approach to Menstrual Tracking

Introduction: &

Purpose: Cycle‑aware training has gained traction in both popular media and sports science. While social platforms promote “cycle syncing” (Pfender EJ, 2025) current evidence favors symptom‑informed, athlete‑specific approaches over prescriptive cycle‑phase guidance (Stitelmann, Bruyneel, & Enea, 2026). To act on symptoms in practice, athletes need simple, integrated ways to relate menstruation (bleeding) and menstrual symptoms to training load and recovery, without over‑interpreting phases (Carmichael, Clarke, Perry, & Roberts, 2026). In our setting, rowers log their daily training and subjective and physiological well-being indicators in a custom app. The athletes may voluntarily complete a menstrual questionnaire to document symptoms primarily associated with the menstrual bleeding phase.This potentially creates a rich dataset in which menstrual-cycle information can be interpreted in relation to well-being and training descriptors (Antero, et al., 2023). However, menstrual entries are prompted only once per day and cannot be revisited, so “no entry” is indistinguishable from “no menstruation,” resulting in ambiguous missing data. Menstrual information is also siloed from training and recovery metrics and not visualized back to athletes, limiting meaningful reflection.This study, therefore,

Aims: to (primary) characterize elite rowers’ tracking and visualization needs for integrating menstruation (bleeding), menstrual symptoms, training, and well‑being, and (secondary) articulate athlete‑led requirements that respect privacy and mitigate coach-athlete power asymmetries, inspired by the concept of Data Feminism (Klein, 2020).Our

Goal: is to derive actionable

Design: requirements, such as explicit data states to disambiguate missingness, configurable low‑ vs high‑burden inputs, integrated overlays with core sport metrics, and granular sharing controls. Subsequent designs should support symptom‑informed reflection and planning for athletes and coaches alike.

Design: We conducted a problem‑driven qualitative

Design: We conducted a problem‑driven qualitative design study following the

Design: We conducted a problem‑driven qualitative design study following the design study methodology (Sedlmair, Meyer, & Munzner, 2012) collaborating with domain experts (elite rowers) to derive actionable tracking and visualization requirements. Consistent with data feminism principles (Klein, 2020), we emphasized participant agency in what to disclose and how data may be used.Participants and recruitment: After two pilot interviews with recreational athletes to refine the protocol (excluded from analysis), we conducted eight semi‑structured interviews with Tier‑2 to Tier‑5 rowers (McKay, 2021), aged 17–27, who actively used our training app. Two athletes competed in the lightweight class, the rest in the open class. Athletes were recruited via email invitations to app users (invited: n=32; responded: n=9; interviewed: n=8).Inclusion and exclusion criteria: Inclusion criteria were: (i) currently training at the time of interview; (ii) app use within the previous 3 months; (iii) ≥100 logged days in the app (to ensure longitudinal experience across multiple cycles). We did not exclude athletes using hormonal contraception.Procedures: Interviews (approximately 35–60 minutes) were conducted via Zoom, audio‑recorded, transcribed verbatim, and anonymized. The guide covered current menstrual and symptom tracking, integration with training and well‑being data, desired inputs and visualizations, privacy/sharing preferences, and perceptions of how menstruation and symptoms relate to training.Analysis: Two researchers coded transcripts with a focus on tasks, data elements, visualization/interaction needs, and privacy/agency requirements. Coding discrepancies were resolved through

Discussion: and debriefing between coders as well as with other researchers familiar with the topic and methodology. Themes were iteratively clustered into functional and visualization requirements. Researchers mostly had backgrounds in data visualization and data science, with one researcher being a competitive athlete themselves.Ethics: All procedures were approved by the Ethics Committee of the University of Vienna as an addendum to the previously approved project protocol (Approval ID: 00897). Data were stored on secure university servers and processed in accordance with GDPR.

Results: Our contribution at this stage is a structured characterization of athlete needs and visualization requirements, a recognized primary contribution type in

design studies. The interviews revealed that many menstrual-tracking preferences among elite athletes align with those of the general population (Lin, et al., 2024), as even elite athletes use tracking to assess whether their cycle is regular or “normal for them” and to plan for future cycles. All participants highly valued a regular, healthy cycle and explicitly mentioned assessing cycle regularity as a tracking

design studies. The interviews revealed that many menstrual-tracking preferences among elite athletes align with those of the general population (Lin, et al., 2024), as even elite athletes use tracking to assess whether their cycle is regular or “normal for them” and to plan for future cycles. All participants highly valued a regular, healthy cycle and explicitly mentioned assessing cycle regularity as a tracking goal. Four athletes (4/8) said they are especially interested in assessing the regularity of their bleeding phase; one of them uses hormonal contraception, which makes predictions very unreliable since she also experiences intermenstrual bleeding. Two (2/8) said they are mainly interested in planning for their next bleed and thus care more about predictions. And the remaining two (2/8) athletes value both components of tracking tools equally.Requirement: Common menstrual tracking visualizations, such as calendar views with uncertainty‑aware period prediction windows; avoid prescriptive phase‑based guidance.Interestingly, there seems to be a dichotomy in both usability preferences and primary visualization tasks. While four (4/8) athletes explicitly mentioned simpler designs to make tracking more convenient, such as binary menstruation/spotting toggles to confirm whether they have their period, two (2/8) athletes preferred extensive symptom lists with severity ratings and comment options. The remaining two (2/8) athletes had no opinions on usability.Requirement: mandatory, revisitable daily check‑in (explicit data states: menstruation present, menstruation absent, not recorded, and not applicable) to resolve ambiguous missingness with optional detailed symptom entry.Regarding training, all participants (8/8) reported that they sometimes feel affected by the menstrual cycle but lack the data to report patterns. Four (4/8) athletes reported that resistance training can feel harder at certain times of the menstrual cycle. Five (5/8) of the athletes were interested in their resting heart rate throughout the cycle, and those in the lightweight class (two athletes) also wanted to track their body mass changes over the cycle to plan accordingly, while one other athlete was very opposed to entering and seeing her weight every day. All athletes (8/8) felt that well-being is tightly correlated with the menstrual cycle, especially sleep and rest. The interviews confirmed that symptom burden is a major perceived performance impairment, as reported by Stitelmann et al. (Stitelmann, Bruyneel, & Enea, 2026), with five (5/8) athletes stating that they are influenced more by individual symptoms than by distinct menstrual-cycle phases (such as the PMS phase or the bleeding phase). Requirement: user‑configurable overlays with saved preferences (RHR, sleep/rest, training load [RPE × duration]; body mass as opt‑in and hidden by default).The possibility of self-assessing the effects of menstruation on their training was mentioned by three (3/8) participants. All athletes stated that they would not object to discussing their cycle with their mostly male coaches, while four (4/8) have already done so at least once in the past. However, four (4/8) athletes also felt they would not benefit from sharing details with their coaches, since coaches probably lack the knowledge on what to change. All athletes mentioned their coach's gender and stated that speaking to female coaches is or would be easier for them. Requirement: privacy‑by‑default and athlete‑led sharing.

design studies. The interviews revealed that many menstrual-tracking preferences among elite athletes align with those of the general population (Lin, et al., 2024), as even elite athletes use tracking to assess whether their cycle is regular or “normal for them” and to plan for future cycles. All participants highly valued a regular, healthy cycle and explicitly mentioned assessing cycle regularity as a tracking goal. Four athletes (4/8) said they are especially interested in assessing the regularity of their bleeding phase; one of them uses hormonal contraception, which makes predictions very unreliable since she also experiences intermenstrual bleeding. Two (2/8) said they are mainly interested in planning for their next bleed and thus care more about predictions. And the remaining two (2/8) athletes value both components of tracking tools equally.Requirement: Common menstrual tracking visualizations, such as calendar views with uncertainty‑aware period prediction windows; avoid prescriptive phase‑based guidance.Interestingly, there seems to be a dichotomy in both usability preferences and primary visualization tasks. While four (4/8) athletes explicitly mentioned simpler designs to make tracking more convenient, such as binary menstruation/spotting toggles to confirm whether they have their period, two (2/8) athletes preferred extensive symptom lists with severity ratings and comment options. The remaining two (2/8) athletes had no opinions on usability.Requirement: mandatory, revisitable daily check‑in (explicit data states: menstruation present, menstruation absent, not recorded, and not applicable) to resolve ambiguous missingness with optional detailed symptom entry.Regarding training, all participants (8/8) reported that they sometimes feel affected by the menstrual cycle but lack the data to report patterns. Four (4/8) athletes reported that resistance training can feel harder at certain times of the menstrual cycle. Five (5/8) of the athletes were interested in their resting heart rate throughout the cycle, and those in the lightweight class (two athletes) also wanted to track their body mass changes over the cycle to plan accordingly, while one other athlete was very opposed to entering and seeing her weight every day. All athletes (8/8) felt that well-being is tightly correlated with the menstrual cycle, especially sleep and rest. The interviews confirmed that symptom burden is a major perceived performance impairment, as reported by Stitelmann et al. (Stitelmann, Bruyneel, & Enea, 2026), with five (5/8) athletes stating that they are influenced more by individual symptoms than by distinct menstrual-cycle phases (such as the PMS phase or the bleeding phase). Requirement: user‑configurable overlays with saved preferences (RHR, sleep/rest, training load [RPE × duration]; body mass as opt‑in and hidden by default).The possibility of self-assessing the effects of menstruation on their training was mentioned by three (3/8) participants. All athletes stated that they would not object to discussing their cycle with their mostly male coaches, while four (4/8) have already done so at least once in the past. However, four (4/8) athletes also felt they would not benefit from sharing details with their coaches, since coaches probably lack the knowledge on what to change. All athletes mentioned their coach's gender and stated that speaking to female coaches is or would be easier for them. Requirement: privacy‑by‑default and athlete‑led sharing. Discussion This study provides insights into athletes' menstrual tracking needs alongside training and well-being data.

Findings: indicate that participants want practical, personalized insights rather than one‑size‑fits‑all guidance. A central

design opportunity is integrating menstrual information with training and well‑being data to enable meaningful reflection. Existing ecosystems tend to silo these domains, which even non-athletes find fault with (Lin, et al., 2024). Menstrual apps rarely include sports variables, and sports trackers rarely include menstrual symptoms, limiting athletes’ ability to relate cycle experiences to performance and recovery. Additionally, resolving ambiguous missingness is critical; our requirements specify explicit data states (menstruation present/absent, not recorded, not applicable) and revisitable entries with provenance to maintain data quality over time.

design opportunity is integrating menstrual information with training and well‑being data to enable meaningful reflection. Existing ecosystems tend to silo these domains, which even non-athletes find fault with (Lin, et al., 2024). Menstrual apps rarely include sports variables, and sports trackers rarely include menstrual symptoms, limiting athletes’ ability to relate cycle experiences to performance and recovery. Additionally, resolving ambiguous missingness is critical; our requirements specify explicit data states (menstruation present/absent, not recorded, not applicable) and revisitable entries with provenance to maintain data quality over time.Design research with rowers demonstrates the value of combined views that place bleeding and symptoms alongside resting heart rate, rest, and training load (Wundsam, Gomez Ortega, & Cila, 2024). This enables athletes to self-assess when their training and well-being may be affected by their menstrual cycle. At the level of visualization tasks, our

design opportunity is integrating menstrual information with training and well‑being data to enable meaningful reflection. Existing ecosystems tend to silo these domains, which even non-athletes find fault with (Lin, et al., 2024). Menstrual apps rarely include sports variables, and sports trackers rarely include menstrual symptoms, limiting athletes’ ability to relate cycle experiences to performance and recovery. Additionally, resolving ambiguous missingness is critical; our requirements specify explicit data states (menstruation present/absent, not recorded, not applicable) and revisitable entries with provenance to maintain data quality over time.Design research with rowers demonstrates the value of combined views that place bleeding and symptoms alongside resting heart rate, rest, and training load (Wundsam, Gomez Ortega, & Cila, 2024). This enables athletes to self-assess when their training and well-being may be affected by their menstrual cycle. At the level of visualization tasks, our findings mirror heterogeneous preferences observed in prior work (Lin, et al., 2024): some athletes seek concise, low‑burden inputs and high‑level overviews, while others want rich symptom detail. Providing configurable “paths” that let athletes tailor daily check‑ins and views to their priorities can respect this diversity while maintaining continuity over time. For analysis, tools should support both retrospective review (e.g., cycle regularity and symptom trends) and cautious forward‑looking cues, so athletes do not over‑interpret predictions. Prior

design opportunity is integrating menstrual information with training and well‑being data to enable meaningful reflection. Existing ecosystems tend to silo these domains, which even non-athletes find fault with (Lin, et al., 2024). Menstrual apps rarely include sports variables, and sports trackers rarely include menstrual symptoms, limiting athletes’ ability to relate cycle experiences to performance and recovery. Additionally, resolving ambiguous missingness is critical; our requirements specify explicit data states (menstruation present/absent, not recorded, not applicable) and revisitable entries with provenance to maintain data quality over time.Design research with rowers demonstrates the value of combined views that place bleeding and symptoms alongside resting heart rate, rest, and training load (Wundsam, Gomez Ortega, & Cila, 2024). This enables athletes to self-assess when their training and well-being may be affected by their menstrual cycle. At the level of visualization tasks, our findings mirror heterogeneous preferences observed in prior work (Lin, et al., 2024): some athletes seek concise, low‑burden inputs and high‑level overviews, while others want rich symptom detail. Providing configurable “paths” that let athletes tailor daily check‑ins and views to their priorities can respect this diversity while maintaining continuity over time. For analysis, tools should support both retrospective review (e.g., cycle regularity and symptom trends) and cautious forward‑looking cues, so athletes do not over‑interpret predictions. Prior design efforts in rowing suggest that integrating tracking with reflective practices can illuminate risks such as amenorrhea and relative energy deficiency in sport (RED‑S), underscorin