More than blood: app-tracking reveals variability in heavy menstrual bleeding construct

Abstract

Background: Heavy menstrual bleeding (HMB) is associated with impaired quality of life and may signal serious health problems. Unresolved challenges in measuring menstrual bleeding and identifying HMB have hampered research and clinical care. Self-reported bleeding histories are commonly used but these may be influenced by recall bias, personal beliefs regarding "normal" flow volume, and the experience of other physical symptoms or disruptions to daily life. The potential usefulness of menstrual-tracking mobile applications, which allow real-time user-entered data recording, for assessing HMB has not been studied. We evaluated recall bias in reported period duration, the relationship of tracked period duration and daily flow volume to subsequently reported period heaviness, variation in quality of life associated with increasing period heaviness, and the advantages and limitations of using app-tracked data for clinical and research purposes.

Methods: An online questionnaire was distributed to current users of Clue, a commercially available menstrual health tracking app, asking them to characterize their last period. We compared responses to the user's corresponding Clue app-tracked data. The study sample comprised 6546 U.S.-based users (aged 18-45 years).

Results: Increasing reported heaviness was associated with increasing app-tracked period length and days of heavy flow, impaired quality-of-life (especially body pain severity), and disrupted activities. Of those reporting having had a heavy/very heavy period, ~ 18% had not tracked any heavy flow, but their period length and quality-of-life indicators were similar to those who had tracked heavy flow. Sexual/romantic activities were the most affected across all flow volumes. Compared to app-tracked data, 44% recalled their exact period length; 83% recalled within ± 1 day. Overestimation was more common than underestimation. However, those with longer app-tracked periods were more likely to underestimate period length by ≥ 2 days, a pattern which could contribute to under-diagnosis of HMB.

Conclusion: Period heaviness is a complex construct that encapsulates flow volume and, for many, several other bleeding-associated experiences (period length, bodily impairments, disruptions of daily activities). Even very precise flow volume assessments cannot capture the multi-faceted nature of HMB as experienced by the individual. Real-time app-tracking facilitates quick daily recording of several aspects of bleeding-associated experiences. This more reliable and detailed characterization of bleeding patterns and experiences can potentially increase understanding of menstrual bleeding variability and, if needed, help to guide treatment.

Keywords: Bleeding volume; Heavy menstrual bleeding; Menstrual health; Mhealth; Mobile application; Period heaviness; Period tracking; Period-associated impairments; Quality of life; Recall bias.

Fig. 1

Screen in the Clue app for recording daily bleeding volume (©Clue by Biowink GmbH, Berlin, Germany)

Fig. 2

App-tracked vs. reported period lengths. (a) Histograms of reported (upper) and app-tracked (lower) total bleeding days in the most recently completed period [n = 6338]. (b) Histogram of the difference between reported and tracked period length (positive values = overestimation and negative values = underestimation of reported compared to tracked period length)

Fig. 3

Variability in tracked daily flow volume for each level of reported bleeding heaviness. Each of the five panels is specific to a reported period heaviness: very light, light, moderate; heavy, very heavy (n = number reporting a specific heaviness). Each histogram within a panel is specific to light, medium, or heavy app-tracked days; x-axis (for each histogram in each panel): for each user, number of app-tracked days that had been tracked as light (histogram 1, pale pink), tracked as medium (histogram 2, pink), or tracked as heavy (histogram 3, red); y-axis (for each histogram): % of users in each reported heaviness category; see main text for additional details and an example of interpreting the plotted data

Fig. 4

Impact of period heaviness on wellness. The reported severity (none through very severe) of five impairments [(a) body pain, (b) sleep problems, (c) digestive problems, (d) emotional changes, (e) headache/migraine] experienced by respondents during their last completed period. For each heaviness category (very light to very heavy), the distribution of severity for each impairment is plotted; of those with a specified heaviness, green bar = % with none, and blue bars = % with specified severity

Fig. 5

Period-associated disruption of daily activities. Each panel is one of the six activities listed in survey Question 4, plus a bottom panel (in green) representing those persons who were not prevented from doing any of the listed activities. The y-axis for each panel is the percent of those persons with a reported heaviness (listed on the x-axis, increasing from left to right) who were not able to do the activity at least once. The increase in percentage who couldn’t do an activity from those with very light flow volume to those with very heavy flow volume is shown in the right-most bar of each panel