Menstrual Cycle Tracking Applications and the Potential for Epidemiological Research: A Comprehensive Review of the Literature

Mobile Application Measurement of Menstrual Cycle Characteristics and Their Association with Dysmenorrhea and Activity Limitation in Early Adolescents

OBJECTIVE

Real-time tracking of menstrual bleeding is a barrier to research due to limitations with traditional data collection tools. This prospective cohort study utilized a mobile application (TDot app) in young adolescents aged 10-14 years to assess the relationship between heavy menstrual bleeding (HMB), dysmenorrhea, and activity limitation.

METHODS

Menstrual cycles were captured over six months in real-time using the Pictorial Blood loss Assessment Chart (PBAC). A median PBAC score of >100 was used to identify participants with HMB. Participants also completed a modified WaLIDD (Working ability, Location, Intensity, Days of pain, Dysmenorrhea) scale. Impact of menses on daily activities was collected for each cycle.

RESULTS

A total of 160 participants enrolled and 100 (63%) participants with ≥3 cycles recorded in the mobile app were analyzed. HMB was noted in 41% of participants. Median modified WaLIDD score was significantly higher in participants with HMB than those without HMB (p=0.01). No significant differences were found in activity limitations between participants with and without HMB (p=0.34). Median modified WaLIDD score for participants with activity limitation was significantly higher than those without activity limitation (p=0.01).

CONCLUSION

Utilizing mobile app technology, we were able to gather real-time menstrual outcome data from young adolescents on heaviness of flow, dysmenorrhea and activity limitations. While we did not find that patients with HMB were more likely to have activity limitations, we did find that those with limitations had modestly higher dysmenorrhea scores. Future studies should focus on identifying additional variables that impact activity limitation during menstruation.

Evaluation of Menstrual Cycle Tracking Behaviors in the Ovulation and Menstruation Health Pilot Study: Cross-Sectional Study

BACKGROUND

Menstrual cycle tracking apps (MCTAs) have potential in epidemiological studies of women's health, facilitating real-time tracking of bleeding days and menstrual-associated signs and symptoms. However, information regarding the characteristics of MCTA users versus cycle nontrackers is limited, which may inform generalizability.

OBJECTIVE

We compared characteristics among individuals using MCTAs (app users), individuals who do not track their cycles (nontrackers), and those who used other forms of menstrual tracking (other trackers).

METHODS

The Ovulation and Menstruation Health Pilot Study tested the feasibility of a digitally enabled evaluation of menstrual health. Recruitment occurred between September 2017 and March 2018. Menstrual cycle tracking behavior, demographic, and general and reproductive health history data were collected from eligible individuals (females aged 18-45 years, comfortable communicating in English). Menstrual cycle tracking behavior was categorized in 3 ways: menstrual cycle tracking via app usage, that via other methods, and nontracking. Demographic factors, health conditions, and menstrual cycle characteristics were compared across the menstrual tracking method (app users vs nontrackers, app users vs other trackers, and other trackers vs nontrackers) were assessed using chi-square or Fisher exact tests.

RESULTS

In total, 263 participants met the eligibility criteria and completed the digital survey. Most of the cohort (n=191, 72.6%) was 18-29 years old, predominantly White (n=170, 64.6%), had attained 4 years of college education or higher (n= 209, 79.5%), and had a household income below US $50,000 (n=123, 46.8%). Among all participants, 103 (39%) were MCTA users (app users), 97 (37%) did not engage in any tracking (nontrackers), and 63 (24%) used other forms of tracking (other trackers). Across all groups, no meaningful differences existed in race and ethnicity, household income, and education level. The proportion of ever-use of hormonal contraceptives was lower (n=74, 71.8% vs n=87, 90%, P=.001), lifetime smoking status was lower (n=6, 6% vs n=15, 17%, P=.04), and diagnosis rate of gastrointestinal reflux disease (GERD) was higher (n=25, 24.3% vs n=12, 12.4%, P=.04) in app users than in nontrackers. The proportions of hormonal contraceptives ever used and lifetime smoking status were both lower (n=74, 71.8% vs n=56, 88.9%, P=.01; n=6, 6% vs n=11, 17.5%, P=.02) in app users than in other trackers. Other trackers had lower proportions of ever-use of hormonal contraceptives (n=130, 78.3% vs n=87, 89.7%, P=.02) and higher diagnostic rates of heartburn or GERD (n=39, 23.5% vs n=12, 12.4%, P.03) and anxiety or panic disorder (n=64, 38.6% vs n=25, 25.8%, P=.04) than nontrackers. Menstrual cycle characteristics did not differ across all groups.

CONCLUSIONS

Our results suggest that app users, other trackers, and nontrackers are largely comparable in demographic and menstrual cycle characteristics. Future studies should determine reasons for tracking and tracking-related behaviors to further understand whether individuals who use MCTAs are comparable to nontrackers.

A randomized trial of web-based fertility-tracking software and fecundability

OBJECTIVE

To assess the effect of randomization to FertilityFriend.com, a mobile computing fertility-tracking app, on fecundability.

DESIGN

Parallel non-blinded randomized controlled trial nested within the Pregnancy Study Online (PRESTO), a North American preconception cohort.

PATIENT(S)

Female participants aged 21 to 45 years attempting conception for ≤6 menstrual cycles at enrolment (2013-2019).

INTERVENTION

Randomization (1:1) of 5532 participants to receive a premium Fertility Friend (FF) subscription.

MAIN OUTCOME MEASURE(S)

Fecundability (per-cycle probability of conception). Participants completed bimonthly follow-up questionnaires until pregnancy or a censoring event, whichever came first. We first performed an intent-to-treat analysis of the effect of FF randomization on fecundability. In secondary analyses, we used a per-protocol approach that accounted for adherence in each trial arm. In both analyses, we used proportional probabilities regression models to estimate fecundability ratios (FR) and 95% confidence intervals (CI) comparing those randomized vs. not randomized and applied inverse probability weights to account for loss-to-follow-up (intent-to-treat and per-protocol analyses) and adherence (per-protocol analyses only).

RESULTS

Using life-table methods, 64% of the 2775 participants randomized to FF and 63% of the 2767 participants not randomized to FF conceived during 12 cycles; these respective percentages were each 70% among those with 0-1 cycles of attempt time at enrolment. Of those randomized to FF, 72% were defined as adherent (68% of observed menstrual cycles). In intent-to-treat analyses, there was no appreciable association overall (FR = 0.97; 95% CI, 0.90-1.04) or within strata of pregnancy attempt time at enrolment, age, education, or other characteristics. In per-protocol analyses, we observed little association overall (FR = 1.06; 95% CI, 0.99-1.14), but weak-to-moderate positive associations among participants who had longer attempt times at enrolment (FR = 1.15; 95% CI, 0.98-1.35 for 3-4 cycles; FR = 1.14; 95% CI, 0.87-1.48 for 5-6 cycles), were aged <25 years (FR = 1.29; 95% CI, 1.01-1.66), had ≤12 years of education (FR = 1.32; 95% CI, 0.92-1.89), or were non-users of hormonal contraception within 3 months before enrolment (FR = 1.10; 95% CI, 1.02-1.19).

CONCLUSION

No appreciable associations were observed in intent-to-treat analyses. In secondary per-protocol analyses that accounted for adherence, randomization to FF was associated with slightly greater fecundability among selected subgroups of participants; however, these results are susceptible to unmeasured confounding.

Feasibility of leveraging menstrual cycle tracking apps for preconception research recruitment

Background

Mobile applications (apps) present a new opportunity to study menstrual cycles and time to pregnancy. Understanding the characteristics of cycle tracking app users is important to evaluate the feasibility of recruiting participants for preconception research.

Methods

Users of a cycle tracking smartphone app, Ovia Fertility, aged 18 or older in the U.S. were randomly invited via email to complete a “fertility research” questionnaire that included demographic and reproductive characteristics. Among those attempting pregnancy without medical assistance, attempt duration, factors influencing pregnancy planning, health history and behaviors while attempting to conceive were queried. Respondents could choose to enter a raffle for a $50 gift card.

Results

Initially, 639 people responded to the demographics portion of the survey representing 49 states and Washington DC. Of these, 344 (54%) were trying to conceive and of those, 297 (86%) were not using medical treatments. Of those not trying to conceive, 12% reported that they planned to start in the next 3 months. Most participants were ages 26–35 (63%), of White race (70%), reported non-Hispanic ethnicity (87%), had at least a bachelor's degree (56%) and an income between $50,000 and $200,000 (58%). One-third were of recommended BMI (35%), 24% overweight, and 41% obese. Most participants reported no fertility-related health conditions (58%). Forty-eight participants (17%) had been trying to conceive for 1 month or less, 88 (31%) had been trying for 2 months or less, and 122 (43%) for 3 months or less. Interruptions in pregnancy attempts were common, 31% reported periods without intercourse. Of those attempting pregnancy, 47% of partners completed their own questionnaire.

Conclusion

This first-of its-kind analysis describes users of a cycle-tracking smartphone app who could be eligible for recruitment to a prospective time-to-pregnancy study. Survey respondents were diverse with respect to geographic location, BMI, and income. However, special recruitment efforts will be needed to recruit participants and partners who identify as other than non-Hispanic White. Participants with fertility-related conditions are not overly represented among app users who are trying to conceive. Targeting and pre-enrolling app users who are planning to begin a pregnancy attempt in the next 3 months may be an advantage of app-based recruitment.

Digital Global Recruitment for Women’s Health Research: Cross-sectional Study

Background

With the increased popularity of mobile menstrual tracking apps and boosted Facebook posts, there is a unique opportunity to recruit research study participants from across the globe via these modalities to evaluate women’s health. However, no studies to date have assessed the feasibility of using these recruitment sources for epidemiological research on ovulation and menstruation.

Objective

The objective of this study was to assess the feasibility of recruiting a diverse sample of women to an epidemiological study of ovulation and menstruation (OM) health (OM Global Health Study) using digital recruitment sources. The feasibility and diversity were assessed via click and participation rates, geographic location, BMI, smoking status, and other demographic information.

Methods

Participants were actively recruited via in-app messages using the menstrual tracking app Clue (BioWink GmbH) and a boosted Facebook post by DivaCup (Diva International Inc.). Other passive recruitment methods also took place throughout the recruitment period (eg, email communications, blogs, other social media). The proportion of participants who visited the study website after viewing and clicking the hypertext link (click rates) in the in-app messages and boosted Facebook post and the proportion of participants who completed the surveys per the number of completed consent and eligibility screeners (participation rates) were used to quantify the success of recruiting participants to the study website and study survey completion, respectively. Survey completion was defined as finishing the pregnancy and birth history section of the OM Global Health Study questionnaire.

Results

The recruitment period was from February 27, 2018, through January 24, 2020. In-app messages and the boosted Facebook post were seen by 104,000 and 21,400 people, respectively. Overall, 215 participants started the OM Global Health Study survey, of which 140 (65.1%), 39 (18.1%), and 36 (16.8%) participants were recruited via the app, the boosted Facebook post, and other passive recruitment methods, respectively. The click rate via the app was 18.9% (19,700 clicks/104,000 ad views) and 1.6% via the boosted Facebook post (340 clicks/21,400 ad views.) The overall participation rate was 44.6% (198/444), and the average participant age was 21.8 (SD 6.1) years. In terms of geographic and racial/ethnic diversity, 91 (44.2%) of the participants resided outside the United States and 147 (70.7%) identified as non-Hispanic White. In-app recruitment produced the most geographically diverse stream, with 44 (32.8%) of the 134 participants in Europe, 77 (57.5%) in North America, and 13 (9.8%) in other parts of the world. Both human error and nonhuman procedural breakdowns occurred during the recruitment process, including a computer programming error related to age eligibility and a hacking attempt by an internet bot.

Conclusions

In-app messages using the menstrual tracking app Clue were the most successful method for recruiting participants from many geographic regions and producing the greatest numbers of started and completed surveys. This study demonstrates the utility of digital recruitment to enroll participants from diverse geographic locations and provides some lessons to avoid technical recruitment errors in future digital recruitment strategies for epidemiological research.

The real-world applications of the symptom tracking functionality available to menstrual health tracking apps

PURPOSE OF REVIEW

The goal of this review was to evaluate whether the fields available in iOS mobile phone apps for recording menstrual cycle symptoms are able to be harmonized across platforms for potential use in research, such as aggregated data analysis.

RECENT FINDINGS

Symptom tracking capabilities are a common feature among menstrual health apps but have been the subject of limited investigations. Apps differ with respect to which symptoms are included and the rationale for these differences is unclear. Epidemiologic studies are poised to incorporate these data; however, a thorough exploration of symptom tracking functionality across apps is required.

SUMMARY

Our review finds that the language used to describe symptoms and the specificity with which symptoms are collected varies greatly across the most used iOS tracking apps. Although some apps allow numerical and qualitative description of symptoms, such as sleep and mood, most simply record the presence or absence of a symptom. Collaborative efforts between clinicians and researchers to guide what and how data is collected may allow tracking apps to realize their potential diagnostic applicability. Regardless, with the increasing use of menstrual health tracking apps, it is imperative that data retrieved from such apps can realize its potential in the research and clinical ecosystems.