This paper is in the following e-collection/theme issue:

mHealth for Wellness, Behavior Change and Prevention (2872) mHealth for Patient Education (231) Mobile Health (mhealth) (2941) Pregnancy Information, Education and Lifestyle Interventions (300) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1400) Obstetrics, Gynecology, and Reproductive Medicine (225)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40427, first published .
Characterization of Self-reported Improvements in Knowledge and Health Among Users of Flo Period Tracking App: Cross-sectional Survey

Characterization of Self-reported Improvements in Knowledge and Health Among Users of Flo Period Tracking App: Cross-sectional Survey

Characterization of Self-reported Improvements in Knowledge and Health Among Users of Flo Period Tracking App: Cross-sectional Survey

Authors of this article:

Liudmila Zhaunova1 Author Orcid Image ;   Ryan Bamford2 Author Orcid Image ;   Tara Radovic2, 3 Author Orcid Image ;   Aidan Wickham2 Author Orcid Image ;   Kimberly Peven2, 4 Author Orcid Image ;   Jazz Croft2 Author Orcid Image ;   Anna Klepchukova2 Author Orcid Image ;   Sonia Ponzo2, 5 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

    Original Paper

    1Flo Health LTU, Vilnius, Lithuania

    2Flo Health UK Limited, London, United Kingdom

    3Department of Psychology and Ergonomics, Technische Universitaet Berlin, Berlin, Germany

    4Maternal, Adolescent, Reproductive & Child Health Centre, London School of Hygiene & Tropical Medicine, London, United Kingdom

    5Institute of Health Informatics, University College London, London, United Kingdom

    Corresponding Author:

    Liudmila Zhaunova, PhD

    Flo Health LTU

    Saltoniškių g. 2

    Vilnius, LT-01109

    Lithuania

    Phone: 370 60396823

    Email: l_zhaunova@flo.health


    Background: Research shows that poor knowledge and awareness of menstrual and pregnancy health among women are associated with adverse reproductive health and pregnancy outcomes. Menstrual cycle– and pregnancy-tracking mobile apps are promising tools for improving women’s awareness of and attitudes toward their reproductive health; however, there is little information about subscribers’ perceptions of app functionality and its impact on their knowledge and health.

    Objective: This study aimed to explore knowledge and health improvements related to menstrual cycle and pregnancy, as well as improvements in general health among Flo app users. We also investigated what components of the Flo app were associated with the abovementioned improvements and evaluated whether those improvements differed based on education level, country of residence (low- and middle-income vs high-income countries), free or premium subscription to the app, short- or long-term use of the app, and frequency of use.

    Methods: Flo subscribers who had been using the app for no less than 30 days, completed a web-based survey. A total of 2212 complete survey responses were collected. The survey included demographic questions and questions about motivations guiding the use of the Flo app and which components of the app improved their knowledge and health, as well as to what extent.

    Results: Most study participants reported improvements in menstrual cycle (1292/1452, 88.98%) and pregnancy (698/824, 84.7%) knowledge from Flo app use. Participants with higher levels of education and those from high-income countries reported using the app predominantly for getting pregnant (χ21=4.2, P=.04; χ21=52.3, P<.001, respectively) and pregnancy tracking (χ21=19.3, P<.001; χ21=20.9, P=.001, respectively). Participants with less education reported using the app to avoid pregnancy (χ21=4.2; P=.04) and to learn more about their body (χ21=10.8; P=.001) and sexual health (χ21=6.3; P=.01), while participants from low- and middle-income countries intended to mainly learn more about their sexual health (χ21=18.2; P<.001). Importantly, the intended use of the app across education levels and country income levels matched areas in which they had gained knowledge and achieved their health goals upon use of the Flo app. Period, fertile days, and ovulation predictions as well as symptom tracking were consistently the top 3 components in the app that helped users with their cycle knowledge and general health. Reading articles or watching videos helped with users' education regarding their pregnancy. Finally, the strongest improvements in knowledge and health were observed in premium, frequent, and long-term users.

    Conclusions: This study suggests that menstrual health apps, such as Flo, could present revolutionary tools to promote consumer health education and empowerment on a global scale.

    JMIR Mhealth Uhealth 2023;11:e40427

    doi:10.2196/40427

    Keywords

    health knowledge; menstrual cycle; pregnancy; period-tracking app; digital health; women’s health 


    Background

    Women’s health has long been understudied and underfunded, compromising the amount of health information available to women as well as the quality of health care they receive [1]. Recently, more efforts have been made to include women in clinical trials, and more policies have been introduced to enhance and promote women’s health globally [2-4]. However, many cultures still hold different myths and taboos regarding the reproductive health and menstrual cycle, specifically. Studies have shown that there is a large knowledge gap among adolescent girls and adult women, especially in low- and middle-income countries (LMICs), about menstrual cycle health [5,6], fertility [5,7], healthy pregnancy [8,9], and overall women’s health and well-being [10,11]. For example, a North Indian study found that only 31% of respondents reported the right definition of the menstrual cycle [6], whereas an extremely high prevalence of inadequate knowledge of symptoms, risk factors, and complications of preeclampsia (88.4%) was found among pregnant women in Ghana [9].

    In high-income countries (HICs), despite an increase in growing social and governmental momentum to improve reproductive health education [12-16], there is still a knowledge gap and misconceptions about reproductive and fertility health as well as reluctance to seek medical treatment for some health issues [17,18]. A Chicago-based study reported that one of the main reasons for a delayed fibroid diagnosis was the belief among women that heavy menstrual bleeding was normal [17]. Another study conducted on American women of reproductive age found that almost 60% of all surveyed women did not know when they had higher chances of conception during the menstrual cycle, while more than two-thirds were unaware that pain during menstruation (eg, owing to conditions such as endometriosis) may correlate with a woman’s ability to get pregnant [18]. A study conducted in England found that 30% of adolescent girls were unaware if their periods were regular; furthermore, most of them were considerably less aware of endometriosis than of other chronic diseases such as diabetes or epilepsy [19]. Another study found that only 42% of pregnant women in Italy knew of all the main risk factors in pregnancy such as alcohol consumption, smoking, passive smoking, and obesity [20]. Thus, low menstrual cycle and pregnancy health awareness among women and people who menstruate might cause adverse effects on women’s and newborn health and well-being and can restrict women from their daily sociocultural activities and impact their quality of life [21,22]. In addition, poor knowledge and misconceptions about reproductive health might delay the time to diagnosis and increase medical costs associated with treatment [17,23].

    Given the lack of reproductive health knowledge among women, identifying medically credible, easy-to-access and understand sources of reproductive health–related information is crucial. On the basis of survey data, women’s health care providers (HCPs) are one of the main sources of trustworthy reproductive health–related knowledge; however, more than one-third of survey respondents reported visiting their reproductive HCP less than once per year or having never visited one [18]. Furthermore, the use of medical jargon or more dense language by HCPs can confuse patients and result in inability to recall the information that they received during medical consultations [24-27]. Health-related internet websites are another source of education and empowerment for women [18,28,29]. Nevertheless, web-based health sources vary in quality, accuracy, and reliability, and incorrect information or advice from websites may affect health-related behavior and decisions [30].

    In the past few years, the rapid growth and acceptance of mobile health apps specifically designed to address women’s health needs have made substantial progress in the area of reproductive and pregnancy knowledge improvements [31-33]. Female health apps are often perceived as helpful by their users, as they provide easy-to-access information that helps them feel more knowledgeable and supported [34,35]. In addition to the educational component, apps for women’s health often provide their users with tracking functionality for their self-knowledge, monitoring, and recording [35,36]. Such functionality includes menstrual cycle and pregnancy tracking or tracking of cycle-related symptoms, for example, hormone-triggered migraines or mood swings [33,37-39]. Previous studies have shown that health mobile apps also facilitate good habit formation and health promotion by providing a number of functions to map behavior patterns across time, including, but not limited to, sleep, diet, physical activity, and mental health practices etc [40,41]. Despite the prevalence and apparent popularity of women health–tracking apps, there remains a knowledge gap regarding the accuracy and safety of the medical advice provided as well as the effectiveness of digital health products in changing health behaviors. Researchers, clinicians, and patient groups have recently advocated for more rigorous requirements regarding the validation and evaluation of digital health solutions, with scientists highlighting the need for a unified evidence generation framework [42-45]. As such, there is a need for health app developers to conduct and publish research assessing the effectiveness of products at both pre- and postmarket time points, so that end users and clinicians are provided with sufficient evidence to make an informed decision [46,47].

    One of the mobile apps dedicated to women’s health and well-being is the Flo app (by Flo Health Inc). Flo offers its users artificial intelligence–based period and ovulation predictions and allows them to track their periods, fertile window, ovulation, and symptoms while trying to get pregnant or avoid pregnancy, as well as to track pregnancy symptoms and fetal development. In addition to the tracking functionality, Flo provides its users with evidence-based and expert-reviewed educational content available through the in-app library. Flo app content creation and validation are based on a peer-reviewed practice in which Flo’s in-house medical doctors and external medical and science experts review each piece of content before it is published in the Flo application or on the website. Each content unit (article, graphics, courses, etc) within the app has references to peer-reviewed articles, medical guidelines, and links to internationally recognized health advocacy organizations and academic institutions. Moreover, each article has a link to the profile of the medical expert or organization who reviewed it. To check for symptoms against an array of conditions, Flo also has interactive questions available via so-called “health assistants” or “chatbots” [38]. Finally, Flo has a secure place called “Secret Chats” where women can discuss intimate topics, ask questions anonymously, and obtain support from millions of women worldwide, thus reducing perceived taboos and stigma surrounding topics such as menstrual health and sexual life [48-50].

    Objective

    Although the Flo app provides a range of functionalities, there is an open question as to whether the Flo users obtain any improvements in knowledge and health by using the app. Hence, the aim of this study was to describe the demographic and app use characteristics of a self-enrolled sample of Flo subscribers and explore the relationship between app use and self-reported improvements in knowledge and health related to the menstrual cycle and pregnancy, as well as improvements in general health in Flo users. We hypothesized that subscribers who use Flo Premium instead of a free version, as well as those who used the app more frequently and for a longer period, would be more likely to report increased health benefits with a greater improvement in their knowledge and understanding across different areas. We also aimed to evaluate the components of the Flo app that were associated with the aforementioned improvements.


    Participants

    Users of the Flo app who had the app installed in English for at least 30 days and were >18 years old were eligible to participate in this study. Recruitment took place within the Flo app between December 5, 2021, and January 16, 2022. We collected 5015 partial responses and 2212 complete survey responses. Only responses from the participants who fully completed the survey were used for the analysis (Table 1 provides the sample’s demographics).

    Table 1. Demographics of study participants (N=2212).
    CategoryFrequency, n (%)
    Country (top 10)

    		The United States758 (34.3)

    		The United Kingdom217 (9.8)

    		Canada121 (5.5)

    		India108 (4.9)

    		Australia92 (4.2)

    		South Africa86 (3.9)

    		Nigeria82 (3.7)

    		Ghana63 (2.8)

    		Philippines43 (1.9)

    		Netherlands32 (1.4)
    Age (years)

    		18-24544 (24.6)

    		25-341264 (57.1)

    		35-44370 (16.7)

    		45-5434 (1.5)
    Race

    		White, European-American, or Caucasian1041 (47)

    		Black or African American397 (17.9)

    		Asian or Asian-American223 (10.1)

    		Hispanic, Latino, Spanish origin116 (5.2)

    		Biracial or multiracial88 (4)

    		American Indian or Alaskan12 (0.5)

    		Native Hawaiian or Pacific Islander3 (0.1)

    		Other225 (10.2)

    		Prefer not to say107 (4.8)
    Gender

    		Woman2181 (96.7)

    		Nonbinary22 (1)

    		Genderqueer or gender fluid19 (0.8)

    		Questioning or unsure10 (0.4)

    		Man5 (0.2)

    		Trans man3 (0.1)

    		Trans woman1 (0.1)

    		Agender3 (0.1)

    		I prefer not to say11 (0.5)
    Education

    		Doctorate degree43 (1.9)

    		Master’s degree373 (16.9)

    		Bachelor’s degree759 (34.3)

    		Associate’s degree139 (6.3)

    		High school graduate or diploma600 (27.1)

    		Some high school, no diploma115 (5.2)

    		I prefer not to say112 (5.1)

    		Other71 (3.2)

    Materials

    Participants completed a demographic questionnaire followed by an investigator-developed quantitative survey (Multimedia Appendix 1 provides the full list of survey questions). The survey included questions addressing the aim, frequency, and duration of the app use, as well as whether and what components of the Flo app (and to what extent) helped users to improve their knowledge and health. Specifically, the survey included questions addressing improvements in knowledge and health across 5 different areas: menstrual health and education, irregular cycle and related conditions, getting pregnant and pregnancy health, general health (mental, sexual, physical health, and health behaviors), and communication with an HCP.

    Overall, the survey contained 70 questions. Not every question was available for every participant, as questions were presented only if they were relevant to the participant based on their previous responses. For example, those who reported that they downloaded the app to track their pregnancy were not asked menstrual cycle–related questions. The survey was created using SurveyMonkey software (Momentive Inc).

    Procedure

    Participants were notified of the possibility of participating in a survey via an in-app notification. Upon clicking on the survey button, the participants were redirected to SurveyMonkey and asked to provide electronic informed consent. Those who consented proceeded to complete the survey on their electronic devices, which took an average of 8 minutes.

    Ethical Considerations

    The study was reviewed by the Independent Ethical Review Board (WIRB-Copernicus Group Institutional Review Board), which deemed the study exempt (IRB tracking number: 20216374 ).

    Defining Categories

    To describe app use patterns among Flo users, the following categories were defined: a short-term user was any participant who had been using the Flo app for <1 year, whereas a long-term user was anyone using the Flo app for ≥1 year. A frequent user was defined as a participant who used the app several times a day to several times a week, whereas an infrequent user was a participant who used the app once a week or less. Premium app users are those who use the paid version of the Flo app, while free app users are those who use the free version of the app. Compared with the free version, the paid app version provides users with full access to all in-app content materials (including text and video materials), all symptom- and cycle-related chats with Flo’s health assistant, and all community discussion chats with an additional opportunity to ask for support and advice from a medical professional (“Ask an Expert”). Multimedia Appendix 2 lists the complete app use characteristics.

    Users with higher education were defined as those who had either a bachelor’s, master’s, or doctorate degree, whereas users with less education included those with any education below a completed bachelor’s degree. In terms of age, a younger user was anyone between the ages of 18 and 34 years, whereas older users were defined as anyone between the ages of 35 and 54 years (Table 1).

    Country income level was defined based on the World Bank Country Income classification [51]. In this study, 62.4% (78/125) of countries were defined as LMICs, whereas the remaining 37.6% (47/125) of countries were classified as HICs. Multimedia Appendices 3 and 4 provide a complete breakdown of HICs and LMICs, respectively.

    Statistical Analysis

    Data were analyzed using Python Jupyter Notebook (version 6.0.1; Project Jupyter). All variables in the survey were categorical. Throughout the survey, participants had options to answer questions as binary categorical variables (yes or no), nominal categorical variables (eg, symptoms they believe Flo has helped with) and ordinal categorical variables (eg, 5 categories from “Not at all” to “A great deal”). Throughout the survey, depending on the participants’ choices, the users were directed to answer different questions. Consequently, the number of participants who answered each question differed. Ordinal categorical variables were recoded as dichotomous variables (not at all—a little vs a moderate amount—a great deal).

    Chi-squared tests compared participant responses for the association between user app subscription status (free vs premium), frequency of app use (frequent vs infrequent), and duration of use (short term vs long term). Chi-squared tests were also used to assess whether the country of residence and education level had a relationship with the reasons why they used the app, the areas in which users’ knowledge was improved, and to what extent knowledge was improved. To confirm the relationship between demographic factors (age and education) and the reasons for using the app, we fitted univariate logistic regression models.


    Overall Knowledge and Health Improvements Upon Flo App Use

    Most respondents reported that the Flo app had improved how educated they feel about their overall cycle (1292/1452, 88.98%; Table S1 in Multimedia Appendix 5, question 46) and pregnancy health (698/824, 84.7%; Table S2 in Multimedia Appendix 5, question 34). Users who had tracked their cycle with Flo felt improvements in the following top 3 menstrual health areas: they knew whether their cycle was regular (1085/1292, 84.0%), whether their cycle length was normal (978/1292, 75.7%), and whether it was normal to have certain symptoms during their cycle (755/1292, 58.4%; Table S1 in Multimedia Appendix 5, question 47). Users also reported that they believed Flo had helped them understand how to use their cycle to know when they were most fertile (780/1292, 60.4%) and how their cycle affected their physical (776/1292, 60.1%) and mental health (765/1292, 59.2%; Table S1 in Multimedia Appendix 5, question 51). In addition, 77.3% (1270/1642) of participants reported that Flo had helped them manage their menstrual symptoms, with the top 3 symptoms being “ovulation” (668/1270, 52.6%); “bad mood” (including feeling sad, guilty, irritated, obsessive thoughts, and confused or self-critical; 641/1270, 50.5%); and “cramps” (618/1270, 48.7%; Table S1 in Multimedia Appendix 5; questions 16 and 17). Finally, 65.1% (309/475) of users said that the app had helped them manage their irregular cycles and related conditions (Table S1 in Multimedia Appendix 5, question 21).

    Most of the study cohort (627/824, 76.1%) who used the app to track their pregnancy reported getting pregnant while using Flo (Table S2 in Multimedia Appendix 5, question 29). Of those who became pregnant, 73.5% (461/627) of believed that using Flo had helped them become pregnant (Table S2 in Multimedia Appendix 5, question 30). More than 8 in 10 participants (530/627, 84.5%) said that Flo had helped them to prepare for a healthy pregnancy (Table S2 in Multimedia Appendix 5, question 32). Pregnancy-tracking users reported that Flo had improved their knowledge about their body during pregnancy (589/698, 84.4%); their baby’s development (577/698, 82.7%); and which symptoms did not require medical attention and which did during pregnancy (505/698, 72.3%; Table S2 in Multimedia Appendix 5, question 36). The study participants also reported that Flo had improved their understanding of how pregnancy affected their physical health (509/698, 72.9%); how to manage their pregnancy symptoms (403/698, 57.7%); and how to optimize their life around their pregnancy (393/698, 56.3%; Table S2 in Multimedia Appendix 5, question 39).

    A smaller number of respondents reported improvements in mental (843/2212, 38.1%), sexual (835/2212, 37.7%), and physical health (589/2212, 26.6%); health behaviors (621/2212, 28.1%); and communication with an HCP (587/2212, 26.5%; Table S3 in Multimedia Appendix 5, question 53).

    Period predictions, fertile days and ovulation predictions, and symptom tracking were the top 3 components of the app that have helped users with all the abovementioned areas (Tables S1 and S3 in Multimedia Appendix 5) except pregnancy education where “reading articles or watching video sources” in the app was rated the highest (503/698, 72.1%; Table S2 in Multimedia Appendix 5, question 38). Complete responses regarding knowledge and health improvements in cycle, pregnancy, and general health are shown in Tables S1, S2, and S3 in Multimedia Appendix 5, respectively.

    Knowledge and Health Improvements in Relation to Education Level

    Study participants with less education were more likely to use the Flo app to track irregular cycles and related conditions to learn more about their body and sexual health and to help them not become pregnant (χ21=10.9, P<.001; χ21=10.8, P=.001; χ21=6.3, P=.01; χ21=4.2, P=.04, respectively), while higher-educated users were more likely to use the app to help them become pregnant and for pregnancy tracking (χ21=4.2, P=.04; χ21=19.3, P<.001, respectively; Table 2). Complete statistics on the reasons for using the app in relation to age are shown in Table S1 in Multimedia Appendix 6.

    Table 2. Education versus reasons for using the app (N=2212).
    Reasons for using the appHEa, n (%)LEb, n (%)Chi-square (df)P value
    Menstrual cycle and symptom tracking943 (80.3)851 (82.1)1.1 (1).01
    Irregular cycles and related conditions219 (18.6)254 (24.5)10.9 (1)<.001
    Pregnancy tracking487 (41.4)335 (32.3)19.3 (1)<.001
    To help me get pregnant657 (55.9)537 (51.5)4.2 (1).04
    To help me not get pregnant117 (10)133 (12.8)4.2 (1).04
    Pregnancy loss73 (6.2)78 (7.5)1.3 (1).26
    Sexual health305 (26)320 (30.9)6.3 (1).01
    Get tailored health information390 (33.2)343 (33.1)0.0(1).99
    To learn more about my body444 (38)467 (45)10.8 (1).001

    aHE: higher education.

    bLE: lower education.

    Univariate logistic regression models confirmed the results of the chi-squared tests. Participants with a higher educational background, for example, master’s degree, had significantly higher odds (odds ratio 1.80, 95% CI 1.15-2.86) of using the app for pregnancy tracking and significantly lower odds (odds ratio 0.59, 95% CI 0.39-0.91) of using the app to learn more about their body compared with users with “Some High School, no Diploma.” Tables S2 and S3 in Multimedia Appendix 6 show full logistic regression results for education and age, respectively.

    Furthermore, we examined whether both lower- and higher-educated users achieved health and knowledge improvements in the intended areas of app use. Users with less education were more likely to report that Flo had helped them improve their understanding of how to manage their menstrual symptoms (χ21=4.7; P=.03; Table S1 in Multimedia Appendix 7, question 51) and helped them identify issues related to endometriosis (χ21=8.0; P=.004; Table S1 in Multimedia Appendix 7, question 47). In addition, they were more likely to report that Flo had improved their sexual health knowledge (χ21=9.5; P=.002), such as sexually transmitted infections (STIs) and how to avoid them (χ21=13.1; P<.001); the signs and symptoms of STIs (χ21=19.3; P<.001); safe sex (χ21=11.7; P<.001); contraception options (χ21=11.1; P<.001); the signs and symptoms during sex that were indicative of a health issue (χ21=10.6; P<.001); and how to have more pleasure during sex (χ21=6.7; P=.009; Table S2 in Multimedia Appendix 7, questions 53, 61, and 62).

    Finally, users with less education were more likely to self-report that Flo had helped them improve their skin (χ21=4.8; P=.03) or fitness (χ21=5.4; P=.02) from a moderate to a great deal (Table S2 in Multimedia Appendix 7, question 57). In addition, they reported that Flo had helped them reduce harmful habits (χ21=12.1; P<.001; Table S2 in Multimedia Appendix 7, question 59) and made them more confident about asking their HCPs for resources that they thought they needed (eg, stress relief, birth control, and support: χ21=4.5; P=.03; Table S2 in Multimedia Appendix 7, question 64).

    In contrast, users with higher education mainly reported improvements in pregnancy health education (Table S3 in Multimedia Appendix 7, questions 34, 36, and 39). In addition, they were more likely to report that they conceived while using Flo (χ21=17.8; P<.001; Table S3 in Multimedia Appendix 7, question 29). Complete responses regarding knowledge and health improvements in cycle health, general health, and pregnancy health in relation to education level are shown in Tables S1, S2, and S3, respectively, in Multimedia Appendix 7.

    Knowledge and Health Improvements in Relation to Country of Residence (LMICs vs HICs)

    The study included participants from both HICs (1513/2212, 68.4%) and LMICs (699/2212, 31.6%), with participants from LMICs having a statistically lower level of education compared with those from HICs (χ21=11.0; P<.001). Table 3 shows that participants from HICs were more likely to use the app for menstrual cycle and symptom tracking, for pregnancy tracking, to get help with getting pregnant, and for pregnancy loss (χ21=11.8, P<.001; χ21=20.9, P<.001; χ21=52.3, P<.001; χ21=22.6, P<.001, respectively), while participants from LMICs were more likely to use the app to improve their sexual health (χ21=18.2; P<.001).

    Table 3. Low- and middle-income countries (LMICs) and high-income countries (HICs) versus reasons for using the app (N=2212).
    Reasons for using the appHIC, n (%)LMIC, n (%)Chi-square (df)P value
    Menstrual cycle and symptom tracking1257 (83.1)537 (76.9)11.8 (1)<.001
    Irregular cycles and related conditions324 (21.4)149 (21.3)0.0 (1).99
    Pregnancy tracking611 (40.4)211 (30.2)20.9 (1)<.001
    To help me get pregnant894 (59.1)297 (42.5)52.3 (1)<.001
    To help me not get pregnant172 (11.4)78 (11.2)0.0(1).94
    Pregnancy loss130 (8.6)21 (3)22.6 (1)<.001
    Sexual health385 (25.4)240 (34.4)18.2 (1)<.001
    Get tailored health information502 (33.2)231 (33)0.0(1).99
    To learn more about my body611 (40.4)303 (43.4)1.6 (1).20

    We further tested whether users from LMICs and HICs achieved their health and knowledge improvement in their intended areas of app use. We found that users from HICs were significantly more likely to report that they became pregnant while using the Flo app (χ21=17.0; P<.001; Table S1 in Multimedia Appendix 8, question 29), as well as know more about their baby’s development (χ21=4.2; P=.04; Table S1 in Multimedia Appendix 8, question 36) and communicate better with their HCPs (χ21=6.2; P=.01; Table S2 in Multimedia Appendix 8, question 53) and partners about their cycle (χ21=5.7; P=.02; Table S3 in Multimedia Appendix 8, question 47).

    Users from LMICs were significantly more likely to self-report that using Flo had helped them improve their understanding of sexual health (χ21=17.7; P<.001; Table S2 in Multimedia Appendix 8, question 53)—more specifically, their understanding of STIs and how to avoid them (χ21=8.1; P=.004; Table S2 in Multimedia Appendix 8, question 61) and how to have safe sex (χ21=17.6; P<.001; Table S2 in Multimedia Appendix 8, question 61), as well as their understanding of their sexuality (χ21=14.7; P<.001; Table S2 in Multimedia Appendix 8, question 62) and how to get more pleasure during sex (χ21=5.0; P=.03; Table S2 in Multimedia Appendix 8, question 62). In addition to improving their sexual health, users from LMICs also reported improvements in understanding of whether their period flow was normal or not (χ21=6.3; P=.01; Table S3 in Multimedia Appendix 8, question 47); how to identify issues related to polycystic ovary syndrome (PCOS; χ21=6.7; P=.001; Table S3 in Multimedia Appendix 8, question 47); and how to manage menstrual symptoms (χ21=23.8; P<.001; Table S3 in Multimedia Appendix 8, question 51) and postpartum symptoms (χ21=8.9; P=.002; Table S1 in Multimedia Appendix 8, question 39). Finally, users from LMICs also reported improvements in physical (χ21=25.1; P<.001; Table S2 in Multimedia Appendix 8, question 53) and mental health (χ21=4.7; P=.03; Table S2 in Multimedia Appendix 8, question 53), including having more energy (χ21=4.5; P=.03; Table S2 in Multimedia Appendix 8, question 57); sleeping better (χ21=6.0; P=.01; Table S2 in Multimedia Appendix 8, question 57); having better stress management skills (χ21=5.0; P=.03; Table S2 in Multimedia Appendix 8, question 59); and reducing harmful habits (χ21=5.0, P=.03; Table S2 in Multimedia Appendix 8, question 59). Complete results regarding knowledge and health improvements in the pregnancy, general health, and cycle health between HICs and LMICs are shown in Tables S1, S2, and S3, respectively, in Multimedia Appendix 8.

    Knowledge and Health Improvements in Relation to Paid Versus Free App Use

    Similar to users with higher education, Flo Premium users reported using the app mainly for pregnancy-related issues (pregnancy tracking: χ21=109.8, P<.001; to help get pregnant: χ21=21.4, P<.001) as well as to obtain tailored health information relevant to them (χ21=16.7; P<.001; Table 4).

    Table 4. Reasons for using the app versus app use characteristics (N=2212).
    Reasons for using the appFa, n (%)Pb, n (%)F vs PLTc, n (%)STd, n (%)LT vs STFre, n (%)If, n (%)Fr vs I



    		Chi-square (df)P value

    		Chi-square (df)P value

    		Chi-square (df)P value
    Menstrual cycle and symptom tracking484
    (84.9)    		674
    (80.8)    		3.7
    (1)    		.06719
    (88.4)    		439
    (74.3)    		46.5
    (1)    		<.001889
    (82.2)    		267
    (83.3)    		0.1
    (1)    		.73
    Irregular cycles and related conditions132
    (23.2)    		170
    (20.4)    		1.4
    (1)    		.24194
    (23.9)    		108
    (18.3)    		6.0
    (1)    		.01217
    (20.1)    		85
    (26.3)    		5.4
    (1)    		.02
    Pregnancy tracking137
    (24)    		435
    (52.2)    		109.8
    (1)    		<.001338
    (41.7)    		234
    (39.6)    		0.5
    (1)    		.49481
    (44.5)    		91
    (28.2)    		26.8
    (1)    		<.001
    To help me get pregnant273
    (47.9)    		505
    (60.6)    		21.4
    (1)    		<.001403
    (49.6)    		375
    (63.5)    		26.1
    (1)    		<.001643
    (59.5)    		135
    (41.8)    		30.8
    (1)    		<.001
    To help me not get pregnant69
    (12.1)    		84
    (10.1)    		1.2
    (1)    		.27121
    (14.9)    		32
    (5.4)    		30.6
    (1)    		<.001114
    (10.5)    		39
    (12.1)    		0.5
    (1)    		.50
    Pregnancy loss23
    (4)    		75
    (9)    		12.1
    (1)    		<.00161
    (7.5)    		37
    (6.3)    		0.6
    (1)    		.4385
    (7.9)    		13
    (4)    		5.1
    (1)    		.02
    Sexual health175
    (30.7)    		234
    (28.1)    		1.0
    (1)    		.31273
    (33.6)    		136
    (23)    		18.0
    (1)    		<.001315
    (29.1)    		94
    (29.1)    		0.0
    (1)    		.99
    Get tailored health information163
    (28.6)    		328
    (39.3)    		16.7
    (1)    		<.001310
    (38.1)    		181
    (30.6)    		8.1
    (1)    		.004389
    (36)    		102
    (31.6)    		1.9
    (1)    		.16
    Learn more about my body233
    (40.9)    		351
    (42.1)    		0.2
    (1)    		.69368
    (45.3)    		216
    (36.5)    		10.3
    (1)    		.001456
    (42.2)    		128
    (39.6)    		0.6
    (1)    		.45

    aP: premium app user.

    bF: free app user.

    cLT: long-term app user.

    dST: short-term app user.

    eFr: frequent user of the app.

    fI: infrequent user of the app.

    We investigated whether Flo Premium users achieved health and knowledge improvements in their intended areas of the app use. First, we found that premium users of Flo were more likely to report knowledge improvements in almost all areas of pregnancy health (Table S1 in Multimedia Appendix 9, questions 29, 32, 34, 36, and 39). In addition, premium users were more likely to report knowledge and health improvements regarding their menstrual health (Table S2 in Multimedia Appendix 9, questions 17, 46, 47, and 51). Finally, Flo Premium users were more likely to report that Flo had helped them improve all aspects of general health (except sexual health), as well as improve communication with HCPs; specifically, Flo Premium users felt more confident in sharing what was going on in their body when communicating with their HCPs (Table S3 in Multimedia Appendix 9, questions 53 and 64).

    Complete responses regarding knowledge and health improvements in pregnancy, cycle, and general health in relation to paid versus free app use are shown in Tables S1, S2, and S3, respectively, in Multimedia Appendix 9.

    Knowledge and Health Improvements in Relation to Frequency of the App Use

    Similar to users with higher education and Flo Premium users, participants who used the app frequently reported using the app mainly for pregnancy-related issues (pregnancy tracking: χ21=26.8; P<.001; to get help with becoming pregnant: χ21=30.8; P<.001), whereas infrequent app users were more likely to report using the app to track irregular cycles and related conditions (χ21=5.4; P=.02; Table 4).

    We examined whether frequent users of Flo achieved pregnancy health and knowledge improvements from app use. As shown in Table S1 in Multimedia Appendix 10, frequent Flo app users were more likely to report that Flo app had helped them become pregnant (χ21=4.5; P=.03; question 30); prepare for a healthy pregnancy (χ21=4.9; P=.03; question 32); and improve their pregnancy health knowledge (χ21=16.2; P<.001; question 34). For example, frequent Flo app users reported that Flo had helped them to know more about their baby’s development (χ21=6.6; P=.01); their body during pregnancy (χ21=6.7; P=.01); basic do’s and don’ts during pregnancy (χ21=4.5; P=.03; Table S1 in Multimedia Appendix 10, question 36); and how pregnancy affects their physical health (χ21=4.4; P=.04; Table S1 in Multimedia Appendix 10, question 39).

    In addition to improvements in pregnancy health and knowledge, study participants who used the Flo app frequently were more likely to report improvements in menstrual health knowledge (Table S2 in Multimedia Appendix 10) such as what symptoms were normal throughout the cycle (χ21=6.1; P=.01; question 47) and how to estimate the most fertile period by using cycle-related knowledge (χ21=32.7; P<.001; question 51). Frequent app users were also more likely to say that Flo had helped them to identify issues related to endometriosis (χ21=3.9; P=.047) and improved communication with their partners about their cycle (χ21=30.6; P<.001; Table S2 in Multimedia Appendix 10, question 47). Finally, frequent Flo app users were more likely to report improvements in communication with a HCPs (χ21=13.1; P<.001; Table S3 in Multimedia Appendix 10, question 53), that is, they became more confident in asking questions about their health and body (χ21=6.4; P=.01) and they became more confident in understanding their reproductive health (χ21=9.1; P=.003; Table S3 in Multimedia Appendix 10, question 64).

    Complete responses regarding knowledge and health improvements in pregnancy, cycle, and general health in relation to the frequency of the app use are shown in Tables S1, S2, and S3, respectively, in Multimedia Appendix 10.

    Knowledge and Health Improvements in Relation to Long Versus Short App Use

    As shown in Table 4, short-term users reported using the app mainly for help with becoming pregnant (χ21=26.1; P<.001) as opposed to long-term users who reported using the app to help avoid pregnancy (χ21=30.6; P<.001); track menstrual cycle and symptoms (χ21=46.5; P<.001); track irregular cycles and related conditions (χ21=6.0; P=.01); learn more about their body (χ21=10.3; P=.001); learn more about sexual health (χ21=18.0; P<.001); and obtain tailored health information relevant to them (χ21=8.1; P=.004).

    We found that short-term Flo users were more likely to report that Flo had helped them to know how to use their cycle to know when they were most fertile (χ21=8.1; P=.008; Table S1 in Multimedia Appendix 11, question 51). At the same time, long-term users were more likely to report improvements across multiple areas of cycle, pregnancy, and general health. Long-term Flo app users were more likely to report that Flo had improved their menstrual health knowledge such as knowing whether their cycle was regular (χ21=10.0; P=.002); cycle length was normal (χ21=5.4; P=.02); and period flow was normal (χ21=10.3; P=.001). In addition, they were more likely to say that Flo had helped them to identify issues related to PCOS (χ21=6.9; P=.009) and helped them to reduce premenstrual syndrome symptoms (χ21=14.4; P<.001; Table S1 in Multimedia Appendix 11, question 47). In addition, long-term users were more likely to say that Flo had helped them to better understand how their cycle affected their mental (χ21=12.3; P<.001) and physical health (χ21=14.7; P<.001) and reactions to situations (lack of patience, sadness, etc; χ21=9.3; P=.002), as well as how to optimize their life around their cycle (χ21=4.8; P=.03; Table S1 in Multimedia Appendix 11, question 51).

    In addition, long-term users of Flo reported that had Flo helped them to improve their knowledge of fetal development (χ21=5.0; P=.03) and the management of pregnancy symptoms (χ21=10.0; P=.002) and postpartum symptoms (χ21=26.0; P<.001) as well as the reduction of risk of preterm labor (χ21=6.1; P=.01; Table S2 in Multimedia Appendix 11, question 36 and 39). Finally, long-term users were more likely to report improvements in sexual (χ21=11.7; P<.001); mental (χ21=12.2; P<.001); and physical health (χ21=13.2; P<.001) and health behaviors (χ21=10.9; P<.001; Table S3 in Multimedia Appendix 11, question 53). Most improvements were reported in sexual health knowledge such as STIs and how to avoid them (χ21=20.9; P<.001); the signs and symptoms of STIs (χ21=16.2; P<.001); safe sex (χ21=14.0; P<.001); contraception options (χ21=12.3; P<.001); and the signs and symptoms during sex that were indicative of a health issue (χ21=8.7; P<.003; Table S3 in Multimedia Appendix 11, question 61).

    Complete responses regarding knowledge and health improvements in cycle, pregnancy, and general health in relation to short-term versus long-term app use are shown in Tables S1, S2, and S3, respectively, in Multimedia Appendix 11.


    Summary

    The aim of this study was to investigate the effects of the Flo app on health and knowledge improvements, with a specific focus on menstrual cycle and pregnancy health. In addition, we aimed to explore whether such effects differed based on education level, country of residence, and app use characteristics (ie, free or paid subscription, frequent or infrequent app use, and short- or long-term app use). We found that most participants reported menstrual cycle and pregnancy knowledge and health improvements upon using the Flo app. These improvements were mostly associated with the use of period and fertile day predictions, symptom-tracking features, and the consumption of relevant in-app health content (articles and videos). Users with different levels of education, countries of residence, and app use patterns differed in their selected health goals. The strongest improvements in knowledge and health were observed in premium, frequent, and long-term users.

    Benefits of Using Menstrual Cycle– and Pregnancy-Tracking Apps

    Our study is the first to date examining the effect of the mobile app Flo in improving menstrual and pregnancy knowledge and health as self-reported by its users. Most users who tracked their menstrual cycle with Flo reported that the app had helped them understand whether their menstrual cycle was normal or not; specifically, whether their cycle was regular, whether their cycle length was within the norms, and whether it was typical to have certain symptoms during their cycle. Menstrual cycle is a vital indicator of women’s health, and cycle abnormalities might be a sign of an underlying health issue [52]. For example, prolonged cycle length and cycle irregularity, in combination with other symptoms such as excessive body hair and acne, might be signs of PCOS [38], while painful and heavy periods or bleeding between periods might be indicative of endometriosis [53]. By improving the understanding of what a normal menstrual cycle is and what body symptoms and signs are associated with it, individuals are equipped with tools to make informed decisions as to whether symptoms they experience may require medical attention. Studies show that increased self-awareness promotes successful health behavior changes and makes individuals more proactive about seeking appropriate care when needed [31,54]. This is of vital importance given that the diagnosis of certain conditions such as endometriosis can be delayed for 8 to 12 years [53]. Prevention or early detection of reproductive conditions can improve women’s quality of life as well as decrease the time to diagnosis and medical costs associated with treatment, thereby reducing the economic burden on health care systems [55,56].

    One in 3 participants in our sample reported that the Flo app had helped them to improve communication with an HCP. This is not surprising considering that better self-awareness and understanding of one’s own menstrual cycle and body were shown to be important for improving provider-patient communication [31]. According to the UK Women’s Health Strategy Survey, 1 in 4 women do not feel comfortable talking to health care professionals about their menstrual cycle, while most women do not feel heard by their physician [57]. Our results suggest that women’s health apps could improve the education and self-awareness of one’s menstrual health and facilitate patient-physician conversations.

    Our survey respondents also reported that the use of the Flo app had helped them manage their menstrual symptoms such as bad mood or cramps. Symptoms that women experience during their menstrual cycle can negatively impact their quality of life, work productivity, and increase health care costs [58]. Dysmenorrhea (a commonly reported cramp-like pain occurring before or during periods) can affect approximately 45% to 95% of women and is associated with productivity loss and absenteeism (ie, absence from work) [59-62]. Furthermore, symptoms of endometriosis such as painful periods or chronic pelvic pain can also negatively impact work performance and can lead to 10.8 hours of lost work per week with an annual total productivity loss of €6298 (US $6838) per woman [55,63], in addition to the profound effects on psychological and social well-being [64,65]. In addition, 65.1% (309/475) of the Flo users reported that the app had helped them manage their irregular cycles and related conditions, with 1 in 3 participants reporting improvements in their mental health. Perceived improvements in cycle symptom management were largely associated with period predictions (935/1276, 73.3%) and reading and watching articles and video sources in the app (787/1276, 61.7%). Given that menstrual cycle symptoms have an impact on several aspects of women’s lives, cycle-tracking apps can help with being mentally prepared for upcoming periods (eg, via period predictions) and can provide insights into how to manage cycle symptoms (eg, via educational content).

    Most participants who had used Flo to track their pregnancy reported improvements in pregnancy and postnatal health knowledge (eg, knowing how to manage pregnancy symptoms and which symptoms require medical attention) and well-being (eg, body image issues associated with pregnancy). Women’s health during pregnancy has profound effects on subsequent generations [66]. Poor maternal health can lead to low neonatal weight and reduced chances of survival, congenital abnormalities, problems with child behavior, poor school performance, and adult health and productivity [67-69]. Furthermore, maternal behaviors such as smoking or alcohol consumption during pregnancy may be significant drivers of infant health issues [70,71]. Therefore, health apps that allow pregnancy tracking are promising tools for improving knowledge about maternal and newborn health, thus decreasing the chances of pregnancy-related complications and child health issues.

    Benefits of Using Menstrual Cycle–Tracking Apps for LMICs and HICs

    Although participants from LMICs (699/2212, 32.6% of the sample) intended to use the Flo app to improve their sexual health (eg, gaining knowledge of STIs and how to avoid them, safe sex, etc), they also reported significantly higher improvements in multiple areas of their health (menstrual cycle, mental and physical health, and improved healthy behaviors). Compared with HICs, where reproductive and sexual education is mandatory in many schools and menstrual health has started to gain increasing attention from governmental and health care authorities (eg, Women’s Health Strategy in England in 2021) [72], LMICs often lack formal menstrual health education, resulting in high levels of stigma and shame surrounding menstruation and sex [73]. Poor period education results in a lack of knowledge about menstrual cycle norms; menstrual hygiene; gynecological conditions and their symptoms; and sexual health (eg, contraception and STIs). Specifically, according to the World Bank classification, LMICs have the highest prevalence of STIs (eg, gonorrhea, trichomoniasis, and syphilis), and the awareness of STIs other than HIV in those countries is very low [74-76]. Therefore, menstrual and sexual health apps, together with systemic governmental and societal education efforts, can mitigate long-term repercussions of poor health literacy, thereby decreasing unfavorable health outcomes such as infertility, abortions, preterm delivery, and perinatal and neonatal morbidities and helping with cutting health care costs associated with STI treatment [77-80].

    Flo app users from HICs reported using the app to help them get pregnant and for pregnancy and menstrual cycle tracking. We found that users from HICs were statistically more likely to report that they became pregnant while using the Flo app, while 97.6% (451/462) acknowledged that fertile days and ovulation predictions made by the Flo app helped them become pregnant. Despite an increase in social and governmental momentum to improve menstrual and sexual health literacy in HICs, topics such as fertility and healthy pregnancy have not received the attention they deserve. A survey conducted on a sample of 1000 American participants showed that younger women (aged 18-24 years) demonstrated a low level of knowledge about conception, ovulation, and the effect of age on the length of time to conception and miscarriage risks. Women aged 25 to 40 years were more likely to believe in common myths around fertility and conception. Finally, more than one-quarter of all survey participants were unaware of factors impacting fertility such as STIs or obesity [18]. Therefore, health apps might help to save costs associated with infertility treatments by educating users on factors impacting fertility and providing fertile window– and ovulation-tracking functionalities to optimize conception strategies.

    Menstrual cycle– and pregnancy-tracking apps might represent promising tools for improving reproductive health knowledge and health among women globally. This is largely owing to the anonymity, scalability, and accessibility of such digital solutions. According to a 2019 survey by the Kaiser Family Foundation, 1 in 3 women of reproductive age in the United States used a menstrual cycle–tracking app [81]. At the same time, an increasing adoption of mobile health apps is also observed in LMICs [82]. Thus, app developers and governmental and health authorities should collaborate to promote HCPs encouraging the adoption of menstrual cycle–tracking apps by the target group and facilitate the distribution of health apps in LMICs.

    Modes (Free vs Paid), Frequency, and Length of App Use

    We found that participants who used a paid version of the app, as well as those who used the app more frequently and for a longer period, were more likely to report improvements in knowledge and health compared with free app users and infrequent or short-term users. These results are not surprising, as studies show that health interventions that are used consistently for prolonged periods are more likely to positively impact behavior, thus leading to better health outcomes [83]. For example, a study conducted by Huberty et al [84] found that more frequent use of the meditation app Calm was associated with an increase in the likelihood of noticing changes in mental health, sleep, and stress levels. Another study by Han and Rhee [85] showed that users who frequently monitored their weight, food consumption, and exercise via a weight loss app, Noom, had more efficient weight loss over time. Therefore, health app developers should consider designing user-friendly, easy-to-navigate, and evidence-based technologies to encourage higher and consistent engagement with the app to achieve better health outcomes for the users.

    Limitations

    Although this study is the first to provide insights into the benefits of using Flo app for women’s health and education, it has several limitations. First, most of the study cohort consisted of highly engaged (1650/2212, 74.6% use the Flo app several times a day to several times a week) and loyal (1305/2212, 59% use the Flo app for >1 year) users of the Flo app who may have more favorable opinions about the app and have benefited more from using it. Those who did not find Flo helpful may have elected not to participate.

    Another limitation is that this was a cross-sectional, nonexperimental study that does not allow us to infer causality with regard to the impact of Flo app on user knowledge, health, and well-being. Future randomized controlled trials assessing the efficacy of the Flo app with baseline and follow-up measures should explore these relationships prospectively to determine the extent to which changes can be attributed to Flo app use. Furthermore, systematic exploration of the health benefits of available women’s health apps is needed to allow clinicians and end users to make informed decisions about effective, safe, and trustworthy solutions. To this end, app developers should conduct and make publicly available pre- and postmarket research assessing the effectiveness and efficacy of their health products. Simultaneously, external organizations should conduct rigorous comparisons of such products to facilitate end users’ understanding of benefits and risks. As mentioned in the Introduction section, despite the call for more rigorous evidence generation, research on this topic is scarce, and a more systematic effort is needed across the board.

    Finally, the survey questions were specifically designed for this study; thus, they had not been previously validated in scientific research. This study used self-reported statements about perceived health knowledge and health behaviors. Although perceived health knowledge and behaviors do not equate to actual improvements in health literacy and health outcomes, they provide useful preliminary insights into the awareness of one’s own health. Future studies should extend the findings of this report by using validated questionnaires to assess changes in menstrual and pregnancy health literacy, as well as knowledge assessment quizzes over time.

    Conclusions

    This study provides the first insights into the effectiveness of the menstrual cycle and women’s health app, Flo, in improving user knowledge and health, and it builds toward a much-needed body of evidence in digital health. Our results highlight the opportunity for menstrual health apps to become useful tools for promoting reproductive health education and empowerment among users globally.

    Acknowledgments

    The authors thank the Flo users who took part in the study.

    Conflicts of Interest

    LZ, RB, TR, AW, KP, JC, AK, and SP were employees of Flo Health.

    ‎
    Multimedia Appendix 1

    Survey questions.

    PDF File (Adobe PDF File), 150 KB
    ‎
    Multimedia Appendix 2

    Flo users’ app use characteristics.

    PDF File (Adobe PDF File), 52 KB
    ‎
    Multimedia Appendix 3

    List of high-income countries and total number of users.

    PDF File (Adobe PDF File), 47 KB
    ‎
    Multimedia Appendix 4

    List of low- and middle-income countries and total number of users.

    PDF File (Adobe PDF File), 48 KB
    ‎
    Multimedia Appendix 5

    Cycle, pregnancy, and general health responses.

    PDF File (Adobe PDF File), 76 KB
    ‎
    Multimedia Appendix 6

    Reasons for using the app versus age and education.

    PDF File (Adobe PDF File), 82 KB
    ‎
    Multimedia Appendix 7

    Education level versus cycle, pregnancy, and general health questions.

    PDF File (Adobe PDF File), 84 KB
    ‎
    Multimedia Appendix 8

    High-income and low- and middle-income countries versus cycle, pregnancy, and general health questions.

    PDF File (Adobe PDF File), 76 KB
    ‎
    Multimedia Appendix 9

    Premium and free users versus cycle, pregnancy, and general health questions.

    PDF File (Adobe PDF File), 83 KB
    ‎
    Multimedia Appendix 10

    Frequent and infrequent app use versus cycle, pregnancy, and general health questions.

    PDF File (Adobe PDF File), 83 KB
    ‎
    Multimedia Appendix 11

    Long- and short-term app use versus cycle, pregnancy, and general health questions.

    PDF File (Adobe PDF File), 83 KB
    1. Mirin AA. Gender disparity in the funding of diseases by the U.S. National Institutes of Health. J Womens Health (Larchmt) 2021 Jul;30(7):956-963. [CrossRef] [Medline]
    2. Liu KA, Mager NA. Women's involvement in clinical trials: historical perspective and future implications. Pharm Pract (Granada) 2016 Jan;14(1):708 [FREE Full text] [CrossRef] [Medline]
    3. Peters SA, Woodward M, Jha V, Kennedy S, Norton R. Women's health: a new global agenda. BMJ Glob Health 2016 Nov 01;1(3):e000080 [FREE Full text] [CrossRef] [Medline]
    4. Sommer M, Caruso BA, Torondel B, Warren EC, Yamakoshi B, Haver J, et al. Menstrual hygiene management in schools: midway progress update on the "MHM in Ten" 2014-2024 global agenda. Health Res Policy Syst 2021 Jan 02;19(1):1 [FREE Full text] [CrossRef] [Medline]
    5. Diamond-Smith N, Onyango GO, Wawire S, Ayodo G. Knowledge of menstruation and fertility among adults in rural Western Kenya: gaps and opportunities for support. PLoS One 2020 Mar 03;15(3):e0229871 [FREE Full text] [CrossRef] [Medline]
    6. Ahmad A, Garg SG, Gupta S, Alvi R. Knowledge and practices related to menstruation among Lucknow college students in north India: results from cross-sectional survey. medRxiv 2021 Feb 12. [CrossRef]
    7. Hammarberg K, Zosel R, Comoy C, Robertson S, Holden C, Deeks M, et al. Fertility-related knowledge and information-seeking behaviour among people of reproductive age: a qualitative study. Hum Fertil (Camb) 2017 Jun;20(2):88-95. [CrossRef] [Medline]
    8. Samuel RS, Youness EM, Mohamed HA. Assessment of pregnant women's knowledge and practice about risks of iodine intake deficiency during pregnancy. Minia Sci Nurs J 2021 Dec 30;010(1):2-10 [FREE Full text] [CrossRef]
    9. Fondjo LA, Boamah VE, Fierti A, Gyesi D, Owiredu EW. Knowledge of preeclampsia and its associated factors among pregnant women: a possible link to reduce related adverse outcomes. BMC Pregnancy Childbirth 2019 Dec 02;19(1):456 [FREE Full text] [CrossRef] [Medline]
    10. Hamdanieh M, Ftouni L, Al Jardali B, Ftouni R, Rawas C, Ghotmi M, et al. Assessment of sexual and reproductive health knowledge and awareness among single unmarried women living in Lebanon: a cross-sectional study. Reprod Health 2021 Jan 28;18(1):24 [FREE Full text] [CrossRef] [Medline]
    11. Alshogran OY, Mahmoud FM, Alkhatatbeh MJ. Knowledge and awareness toward menopause and hormone therapy among premenopausal women in Jordan. Climacteric 2021 Apr;24(2):171-178. [CrossRef] [Medline]
    12. Weiss-Wolf J. U.S. policymaking to address menstruation: advancing an equity agenda. In: Bobel C, Winkler IT, Fahs B, Hasson KA, Kissling EA, Roberts TA, editors. The Palgrave Handbook of Critical Menstruation Studies. Singapore: Palgrave Macmillan; Jul 25, 2020:539-549.
    13. Committee opinion no. 585: health literacy. Obstet Gynecol 2014 Feb;123(2 PART 1):380-383 [FREE Full text] [CrossRef]
    14. Reis M, Ramiro L, Gaspar de Matos M, Diniz JA. The effects of sex education in promoting sexual and reproductive health in Portuguese university students. Procedia Soc Behav Sci 2011;29:477-485 [FREE Full text] [CrossRef]
    15. Janiak E, Rhodes E, Foster AM. Translating access into utilization: lessons from the design and evaluation of a health insurance web site to promote reproductive health care for young women in Massachusetts. Contraception 2013 Dec;88(6):684-690. [CrossRef] [Medline]
    16. Bush D, Brick E, East MC, Johnson N. Endometriosis education in schools: a New Zealand model examining the impact of an education program in schools on early recognition of symptoms suggesting endometriosis. Aust N Z J Obstet Gynaecol 2017 Aug;57(4):452-457. [CrossRef] [Medline]
    17. Ghant MS, Sengoba KS, Vogelzang R, Lawson AK, Marsh EE. An altered perception of normal: understanding causes for treatment delay in women with symptomatic uterine fibroids. J Womens Health (Larchmt) 2016 Aug;25(8):846-852 [FREE Full text] [CrossRef] [Medline]
    18. Lundsberg LS, Pal L, Gariepy AM, Xu X, Chu MC, Illuzzi JL. Knowledge, attitudes, and practices regarding conception and fertility: a population-based survey among reproductive-age United States women. Fertil Steril 2014 Mar;101(3):767-774 [FREE Full text] [CrossRef] [Medline]
    19. Randhawa AE, Tufte-Hewett AD, Weckesser AM, Jones GL, Hewett FG. Secondary school girls' experiences of menstruation and awareness of endometriosis: a cross-sectional study. J Pediatr Adolesc Gynecol 2021 Oct;34(5):643-648. [CrossRef] [Medline]
    20. Esposito G, Ambrosio R, Napolitano F, Di Giuseppe G. Women's knowledge, attitudes and behavior about maternal risk factors in pregnancy. PLoS One 2015 Dec 29;10(12):e0145873 [FREE Full text] [CrossRef] [Medline]
    21. Armour M, Hyman MS, Al-Dabbas M, Parry K, Ferfolja T, Curry C, et al. Menstrual health literacy and management strategies in young women in Australia: a national online survey of young women aged 13-25 Years. J Pediatr Adolesc Gynecol 2021 Apr;34(2):135-143. [CrossRef] [Medline]
    22. Armour M, Parry K, Al-Dabbas MA, Curry C, Holmes K, MacMillan F, et al. Self-care strategies and sources of knowledge on menstruation in 12,526 young women with dysmenorrhea: a systematic review and meta-analysis. PLoS One 2019 Jul 24;14(7):e0220103 [FREE Full text] [CrossRef] [Medline]
    23. Simpson CN, Lomiguen CM, Chin J. Combating diagnostic delay of endometriosis in adolescents via educational awareness: a systematic review. Cureus 2021 May 20;13(5):e15143 [FREE Full text] [CrossRef] [Medline]
    24. Chapple A, Campion P, May C. Clinical terminology: anxiety and confusion amongst families undergoing genetic counseling. Patient Educ Couns 1997 Sep;32(1-2):81-91. [CrossRef] [Medline]
    25. Michie S, McDonald V, Marteau TM. Genetic counselling: information given, recall and satisfaction. Patient Educ Couns 1997 Sep;32(1-2):101-106. [CrossRef] [Medline]
    26. Roter DL, Erby L, Larson S, Ellington L. Oral literacy demand of prenatal genetic counseling dialogue: predictors of learning. Patient Educ Couns 2009 Jun;75(3):392-397. [CrossRef] [Medline]
    27. Watson M, Lloyd S, Davidson J, Meyer L, Eeles R, Ebbs S, et al. The impact of genetic counselling on risk perception and mental health in women with a family history of breast cancer. Br J Cancer 1999 Feb;79(5-6):868-874 [FREE Full text] [CrossRef] [Medline]
    28. Huberty J, Dinkel D, Beets MW, Coleman J. Describing the use of the internet for health, physical activity, and nutrition information in pregnant women. Matern Child Health J 2013 Oct;17(8):1363-1372. [CrossRef] [Medline]
    29. Horgan Á, Sweeney J. University students' online habits and their use of the Internet for health information. Comput Inform Nurs 2012 Aug;30(8):402-408. [CrossRef] [Medline]
    30. Kitchens B, Harle CA, Li S. Quality of health-related online search results. Decis Support Syst 2014 Jan;57:454-462 [FREE Full text] [CrossRef]
    31. Levy J, Romo-Avilés N. "A good little tool to get to know yourself a bit better": a qualitative study on users' experiences of app-supported menstrual tracking in Europe. BMC Public Health 2019 Sep 03;19(1):1213 [FREE Full text] [CrossRef] [Medline]
    32. Karasneh RA, Al-Azzam SI, Alzoubi KH, Muflih SM, Hawamdeh SS. Smartphone applications for period tracking: rating and behavioral change among women users. Obstet Gynecol Int 2020 Sep 01;2020:2192387 [FREE Full text] [CrossRef] [Medline]
    33. Hughson JP, Daly JO, Woodward-Kron R, Hajek J, Story D. The rise of pregnancy apps and the implications for culturally and linguistically diverse women: narrative review. JMIR Mhealth Uhealth 2018 Nov 16;6(11):e189 [FREE Full text] [CrossRef] [Medline]
    34. Lupton D, Pedersen S. An Australian survey of women's use of pregnancy and parenting apps. Women Birth 2016 Aug;29(4):368-375. [CrossRef] [Medline]
    35. Epstein DA, Lee NB, Kang JH, Agapie E, Schroeder J, Pina LR, et al. Examining menstrual tracking to inform the design of personal informatics tools. Proc SIGCHI Conf Hum Factor Comput Syst 2017 May 02;2017:6876-6888 [FREE Full text] [CrossRef] [Medline]
    36. Ford A, De Togni G, Miller L. Hormonal health: period tracking apps, wellness, and self-management in the era of surveillance capitalism. Engag Sci Technol Soc 2021 Oct 05;7(1):48-66 [FREE Full text] [CrossRef]
    37. Gambier-Ross K, McLernon DJ, Morgan HM. A mixed methods exploratory study of women's relationships with and uses of fertility tracking apps. Digit Health 2018 Jul 25;4:2055207618785077 [FREE Full text] [CrossRef] [Medline]
    38. Jain T, Negris O, Brown D, Galic I, Salimgaraev R, Zhaunova L. Characterization of polycystic ovary syndrome among Flo app users around the world. Reprod Biol Endocrinol 2021 Mar 03;19(1):36 [FREE Full text] [CrossRef] [Medline]
    39. Grieger JA, Norman RJ. Menstrual cycle length and patterns in a global cohort of women using a mobile phone app: retrospective cohort study. J Med Internet Res 2020 Jun 24;22(6):e17109 [FREE Full text] [CrossRef] [Medline]
    40. Bert F, Giacometti M, Gualano MR, Siliquini R. Smartphones and health promotion: a review of the evidence. J Med Syst 2014 Jan;38(1):9995 [FREE Full text] [CrossRef] [Medline]
    41. McKay FH, Cheng C, Wright A, Shill J, Stephens H, Uccellini M. Evaluating mobile phone applications for health behaviour change: a systematic review. J Telemed Telecare 2018 Jan;24(1):22-30. [CrossRef] [Medline]
    42. Kowatsch T, Otto L, Harperink S, Cotti A, Schlieter H. A design and evaluation framework for digital health interventions. It Inf Technol 2019;61(5-6):253-263. [CrossRef]
    43. Guo C, Ashrafian H, Ghafur S, Fontana G, Gardner C, Prime M. Challenges for the evaluation of digital health solutions-a call for innovative evidence generation approaches. NPJ Digit Med 2020 Aug 27;3:110 [FREE Full text] [CrossRef] [Medline]
    44. Mathews SC, McShea MJ, Hanley CL, Ravitz A, Labrique AB, Cohen AB. Digital health: a path to validation. NPJ Digit Med 2019 May 13;2:38 [FREE Full text] [CrossRef] [Medline]
    45. Murray E, Hekler EB, Andersson G, Collins LM, Doherty A, Hollis C, et al. Evaluating digital health interventions: key questions and approaches. Am J Prev Med 2016 Nov;51(5):843-851 [FREE Full text] [CrossRef] [Medline]
    46. Scott KM, Gome GA, Richards D, Caldwell PH. How trustworthy are apps for maternal and child health? Health Technol (Berl) 2015 Mar 12;4(4):329-336 [FREE Full text] [CrossRef]
    47. Wicks P, Chiauzzi E. 'Trust but verify'--five approaches to ensure safe medical apps. BMC Med 2015 Sep 25;13:205 [FREE Full text] [CrossRef] [Medline]
    48. Cook RJ, Dickens BM. Reducing stigma in reproductive health. Int J Gynaecol Obstet 2014 Apr;125(1):89-92. [CrossRef] [Medline]
    49. Johnston-Robledo I, Chrisler JC. The menstrual mark: menstruation as social stigma. Sex Roles 2011 Jul 31;68(2):9-18 [FREE Full text] [Medline]
    50. Babbar K, Martin J, Ruiz J, Parray AA, Sommer M. Menstrual health is a public health and human rights issue. Lancet Public Health 2022 Jan;7(1):e10-e11 [FREE Full text] [CrossRef] [Medline]
    51. World Bank country and lending groups. World Bank Data Help Desk. 2021.   URL: https:/​/datahelpdesk.​worldbank.org/​knowledgebase/​articles/​906519-world-bank-country-and-lending-groups [accessed 2022-11-28]
    52. Foster C, Al-Zubeidi H. Menstrual irregularities. Pediatr Ann 2018 Jan 01;47(1):e23-e28. [CrossRef] [Medline]
    53. Kiesel L, Sourouni M. Diagnosis of endometriosis in the 21st century. Climacteric 2019 Jun;22(3):296-302. [CrossRef] [Medline]
    54. Anderson K, Burford O, Emmerton L. Mobile health apps to facilitate self-care: a qualitative study of user experiences. PLoS One 2016 May 23;11(5):e0156164 [FREE Full text] [CrossRef] [Medline]
    55. Simoens S, Dunselman G, Dirksen C, Hummelshoj L, Bokor A, Brandes I, et al. The burden of endometriosis: costs and quality of life of women with endometriosis and treated in referral centres. Hum Reprod 2012 May;27(5):1292-1299. [CrossRef] [Medline]
    56. Jensen JT, Lefebvre P, Laliberté F, Sarda SP, Law A, Pocoski J, et al. Cost burden and treatment patterns associated with management of heavy menstrual bleeding. J Womens Health (Larchmt) 2012 May;21(5):539-547. [CrossRef] [Medline]
    57. Results of the ‘women’s health – let’s talk about it’ survey. Department of Health & Social Care, UK. 2022 Apr 13.   URL: https:/​/www.​gov.uk/​government/​consultations/​womens-health-strategy-call-for-evidence/​outcome/​results-of-the-womens-health-lets-talk-about-it-survey [accessed 2022-12-02]
    58. Ponzo S, Wickham A, Bamford R, Radovic T, Zhaunova L, Peven K, et al. Menstrual cycle-associated symptoms and workplace productivity in US employees: a cross-sectional survey of users of the Flo mobile phone app. Digit Health 2022 Dec 15;8:20552076221145852 [FREE Full text] [CrossRef] [Medline]
    59. Titilayo A, Agunbiade OM, Banjo O, Lawani A. Menstrual discomfort and its influence on daily academic activities and psychosocial relationship among undergraduate female students in Nigeria. Tanzan J Health Res 2009 Oct;11(4):181-188. [CrossRef] [Medline]
    60. Sharma A, Taneja DK, Sharma P, Saha R. Problems related to menstruation and their effect on daily routine of students of a medical college in Delhi, India. Asia Pac J Public Health 2008;20(3):234-241. [CrossRef] [Medline]
    61. Ballagh SA, Heyl A. Communicating with women about menstrual cycle symptoms. J Reprod Med 2008 Nov;53(11):837-846. [Medline]
    62. Iacovides S, Avidon I, Baker FC. What we know about primary dysmenorrhea today: a critical review. Hum Reprod Update 2015 Nov;21(6):762-778. [CrossRef] [Medline]
    63. Nnoaham KE, Hummelshoj L, Webster P, d'Hooghe T, de Cicco Nardone F, de Cicco Nardone C, World Endometriosis Research Foundation Global Study of Women's Health consortium. Reprint of: impact of endometriosis on quality of life and work productivity: a multicenter study across ten countries. Fertil Steril 2019 Oct;112(4 Suppl1):e137-e152 [FREE Full text] [CrossRef] [Medline]
    64. Unsal A, Ayranci U, Tozun M, Arslan G, Calik E. Prevalence of dysmenorrhea and its effect on quality of life among a group of female university students. Ups J Med Sci 2010 May;115(2):138-145 [FREE Full text] [CrossRef] [Medline]
    65. Iacovides S, Avidon I, Bentley A, Baker FC. Reduced quality of life when experiencing menstrual pain in women with primary dysmenorrhea. Acta Obstet Gynecol Scand 2014 Feb;93(2):213-217 [FREE Full text] [CrossRef] [Medline]
    66. Zylbersztejn A, Gilbert R, Hjern A, Wijlaars L, Hardelid P. Child mortality in England compared with Sweden: a birth cohort study. Lancet 2018 May 19;391(10134):2008-2018 [FREE Full text] [CrossRef] [Medline]
    67. Kahn RS, Wilson K, Wise PH. Intergenerational health disparities: socioeconomic status, women's health conditions, and child behavior problems. Public Health Rep 2005 Jul;120(4):399-408 [FREE Full text] [CrossRef] [Medline]
    68. Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, MaternalChild Undernutrition Study Group. Maternal and child undernutrition: consequences for adult health and human capital. Lancet 2008 Jan 26;371(9609):340-357 [FREE Full text] [CrossRef] [Medline]
    69. Ahmad K, Kabir E, Keramat SA, Khanam R. Maternal health and health-related behaviours and their associations with child health: evidence from an Australian birth cohort. PLoS One 2021 Sep 13;16(9):e0257188 [FREE Full text] [CrossRef] [Medline]
    70. Burns L, Breen C, Bower C, O' Leary C, Elliott EJ. Counting fetal alcohol spectrum disorder in Australia: the evidence and the challenges. Drug Alcohol Rev 2013 Sep;32(5):461-467. [CrossRef] [Medline]
    71. Sutin AR, Flynn HA, Terracciano A. Maternal smoking during pregnancy and offspring personality in childhood and adulthood. J Pers 2018 Aug;86(4):652-664 [FREE Full text] [CrossRef] [Medline]
    72. Results of the women’s health strategy call for evidence – written responses from organisations and experts. Department of Health & Social Care, UK. 2022 Apr 13.   URL: https://tinyurl.com/ysazn7r4 [accessed 2022-11-24]
    73. Hennegan J, Shannon AK, Rubli J, Schwab KJ, Melendez-Torres GJ. Women's and girls' experiences of menstruation in low- and middle-income countries: a systematic review and qualitative metasynthesis. PLoS Med 2019 May 16;16(5):e1002803 [FREE Full text] [CrossRef] [Medline]
    74. Mayaud P, Mabey D. Approaches to the control of sexually transmitted infections in developing countries: old problems and modern challenges. Sex Transm Infect 2004 Jun;80(3):174-182 [FREE Full text] [CrossRef] [Medline]
    75. Rowley J, Vander Hoorn S, Korenromp E, Low N, Unemo M, Abu-Raddad LJ, et al. Chlamydia, gonorrhoea, trichomoniasis and syphilis: global prevalence and incidence estimates, 2016. Bull World Health Organ 2019 Aug 01;97(8):548-62P [FREE Full text] [CrossRef] [Medline]
    76. Vasudeva M, Nakka R, Stock S, Ghebremichael M. Associations between awareness of sexually transmitted infections (STIs) and prevalence of STIs among sub-Saharan African men and women. Trop Med Infect Dis 2022 Jul 26;7(8):147 [FREE Full text] [CrossRef] [Medline]
    77. Wynn A, Bristow CC, Cristillo AD, Murphy SM, van den Broek N, Muzny C, et al. Sexually transmitted infections in pregnancy and reproductive health: proceedings of the star sexually transmitted infection clinical trial group programmatic meeting. Sex Transm Dis 2020 Jan;47(1):5-11 [FREE Full text] [CrossRef] [Medline]
    78. Adachi K, Xu J, Yeganeh N, Camarca M, Morgado MG, Watts DH, NICHD HPTN 040 Study Team. Combined evaluation of sexually transmitted infections in HIV-infected pregnant women and infant HIV transmission. PLoS One 2018 Jan;13(1):e0189851 [FREE Full text] [CrossRef] [Medline]
    79. Korenromp EL, Rowley J, Alonso M, Mello MB, Wijesooriya NS, Mahiané SG, et al. Global burden of maternal and congenital syphilis and associated adverse birth outcomes-estimates for 2016 and progress since 2012. PLoS One 2019 Feb 27;14(2):e0211720 [FREE Full text] [CrossRef] [Medline]
    80. Meites E, Gaydos CA, Hobbs MM, Kissinger P, Nyirjesy P, Schwebke JR, et al. A review of evidence-based care of symptomatic trichomoniasis and asymptomatic trichomonas vaginalis infections. Clin Infect Dis 2015 Dec 15;61 Suppl 8(Suppl 8):S837-S848 [FREE Full text] [CrossRef] [Medline]
    81. Health Apps and Information Survey. Henry J Kaiser Family Foundation. 2019 Sep.   URL: https://files.kff.org/attachment/Topline-Health-Apps-and-Information-Survey-September-2019 [accessed 2022-12-07]
    82. Alaiad A, Alsharo M, Alnsour Y. The determinants of m-Health adoption in developing countries: an empirical investigation. Appl Clin Inform 2019 Oct;10(5):820-840 [FREE Full text] [CrossRef] [Medline]
    83. Kim M, Yang J, Ahn WY, Choi HJ. Machine learning analysis to identify digital behavioral phenotypes for engagement and health outcome efficacy of an mHealth intervention for obesity: randomized controlled trial. J Med Internet Res 2021 Jun 24;23(6):e27218 [FREE Full text] [CrossRef] [Medline]
    84. Huberty J, Vranceanu A, Carney C, Breus M, Gordon M, Puzia ME. Characteristics and usage patterns among 12,151 paid subscribers of the calm meditation app: cross-sectional survey. JMIR Mhealth Uhealth 2019 Nov 03;7(11):e15648 [FREE Full text] [CrossRef] [Medline]
    85. Han M, Rhee SY. Effect of adherence to smartphone app use on the long-term effectiveness of weight loss in developing and OECD countries: retrospective cohort study. JMIR Mhealth Uhealth 2021 Jul 12;9(7):e13496 [FREE Full text] [CrossRef] [Medline]

    ‎
    HCP: health care provider
    HIC: high-income country
    LMIC: low- and middle-income country
    PCOS: polycystic ovary syndrome 
    STI: sexually transmitted infection

    Edited by L Buis; submitted 20.06.22; peer-reviewed by D Reifegerste, S Meherali, L Xu; comments to author 04.11.22; revised version received 16.12.22; accepted 06.03.23; published 26.04.23

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    ©Liudmila Zhaunova, Ryan Bamford, Tara Radovic, Aidan Wickham, Kimberly Peven, Jazz Croft, Anna Klepchukova, Sonia Ponzo. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 26.04.2023.

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