Exploring Self-Reported Symptoms for Developing and Evaluating Digital Symptom Checkers for Polycystic Ovarian Syndrome, Endometriosis, and Uterine Fibroids: Exploratory Survey Study (Preprint)

Aidan P Wickham, Yella Hewings-Martin, Frederick Gb Goddard, Allison K. Rodgers, Adam C Cunningham, Carley Prentice, Octavia Wilks, Yusuf C Kaplan, Andrei Marhol, András Meczner, Heorhi Stsefanovich, Anna Klepchukova, Liudmila Zhaunova
2024 · doi:10.2196/preprints.65469 · W4405299956
preprint OA: gold CC0
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⚙ AI-generated summary by claude@2026-06, 2026-06-08 ⓘ

This study identified key predictive symptoms for PCOS, endometriosis, and uterine fibroids and evaluated the accuracy of three Flo symptom checkers in diagnosing these conditions.

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Abstract

BACKGROUND Reproductive health conditions such as polycystic ovary syndrome (PCOS), endometriosis, and uterine fibroids pose a significant burden to people who menstruate, health care systems, and economies. Despite clinical guidelines for each condition, prolonged delays in diagnosis are commonplace, resulting in an increase to health care costs and risk of health complications. Symptom checker apps have the potential to significantly reduce time to diagnosis by providing users with health information and tools to better understand their symptoms. OBJECTIVE This study aims to study the prevalence and predictive importance of self-reported symptoms of PCOS, endometriosis, and uterine fibroids, and to explore the efficacy of 3 symptom checkers (developed by Flo Health UK Limited) that use self-reported symptoms when screening for each condition. METHODS Flo’s symptom checkers were transcribed into separate web-based surveys for PCOS, endometriosis, and uterine fibroids, asking respondents their diagnostic history for each condition. Participants were aged 18 years or older, female, and living in the United States. Participants either had a confirmed diagnosis (condition-positive) and reported symptoms retrospectively as experienced at the time of diagnosis, or they had not been examined for the condition (condition-negative) and reported their current symptoms as experienced at the time of surveying. Symptom prevalence was calculated for each condition based on the surveys. Least absolute shrinkage and selection operator regression was used to identify key symptoms for predicting each condition. Participants’ symptoms were processed by Flo’s 3 single-condition symptom checkers, and accuracy was assessed by comparing the symptom checker output with the participant’s condition designation. RESULTS A total of 1317 participants were included with 418, 476, and 423 in the PCOS, endometriosis, and uterine fibroids groups, respectively. The most prevalent symptoms for PCOS were fatigue (92%), feeling anxious (87%), BMI over 25 (84%); for endometriosis: very regular lower abdominal pain (89%), fatigue (85%), and referred lower back pain (80%); for uterine fibroids: fatigue (76%), bloating (69%), and changing sanitary protection often (68%). Symptoms of anovulation and amenorrhea (long periods, irregular cycles, and absent periods), and hyperandrogenism (excess hair on chin and abdomen, scalp hair loss, and BMI over 25) were identified as the most predictive symptoms for PCOS, while symptoms related to abdominal pain and the effect pain has on life, bleeding, and fertility complications were among the most predictive symptoms for both endometriosis and uterine fibroids. Symptom checker accuracy was 78%, 73%, and 75% for PCOS, endometriosis, and uterine fibroids, respectively. CONCLUSIONS This exploratory study characterizes self-reported symptomatology and identifies the key predictive symptoms for 3 reproductive conditions. The Flo symptom checkers were evaluated using real, self-reported symptoms and demonstrated high levels of accuracy.

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Condition tags

endometriosis

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