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

Area of Science:

• Reproductive Health
• Digital Health
• Women's Health

Background:

• Heavy menstrual bleeding (HMB) significantly impacts quality of life and can indicate serious health issues.
• Accurate measurement of menstrual bleeding and HMB identification remain challenging, hindering research and clinical care.
• Current self-reported bleeding histories are prone to recall bias and subjective interpretations of 'normal' flow.

Purpose of the Study:

• To evaluate recall bias in self-reported period duration compared to app-tracked data.
• To assess the relationship between tracked period duration/flow volume and reported period heaviness.
• To examine quality of life variations with increasing period heaviness and the utility of app data for HMB assessment.

Main Methods:

• An online questionnaire was administered to 6546 U.S. users (aged 18-45) of the Clue menstrual health tracking app.
• Participants characterized their last period via questionnaire and responses were compared to their app-tracked data.
• The study analyzed recall bias, correlations between tracked data and reported heaviness, and quality of life impacts.

Main Results:

• Increasing reported heaviness correlated with longer app-tracked periods, more heavy flow days, impaired quality of life (pain), and disrupted activities.
• Approximately 18% reporting heavy periods had not tracked heavy flow, yet showed similar period length and quality of life indicators.
• While 83% recalled period length within ±1 day, longer tracked periods increased underestimation by ≥2 days, potentially leading to HMB under-diagnosis.

Conclusions:

• Period heaviness is a complex experience involving flow volume, duration, and associated impairments, not solely quantifiable by flow volume.
• Real-time app tracking provides a more reliable and detailed characterization of bleeding patterns and experiences than self-reporting alone.
• Utilizing app-tracked data can enhance understanding of menstrual bleeding variability and aid in guiding HMB diagnosis and treatment.