Plausibility of Menstrual Cycle Apps Claiming to Support Conception

Algorithmic surveillance in the era of the mental health appsphere

Digital mental health applications, also known as mHealth apps, are designed to help users manage their mental health using technology such as mobile devices and smartphones. However, there has been little critical engagement surrounding their impact on marginalized communities, and Black people in Canada. This article aims to explore how state and private actors conceptualize the digitalization of mental health access, leading to the creation and implementation of these apps. It is important to consider the links and interconnections between the platform and the app, and to be cautious and curious before adopting yet another app that claims to manage and mitigate moods and address mental health needs. We should be considering the implications of what comes with this access and apparent ease of use.

Fertility and infertility uses of menstrual apps from the perspectives of healthcare providers and patients

BACKGROUND

Menstrual cycle tracking apps are increasingly used by those trying to conceive as well as those diagnosed and treated for infertility. However, the small amount of existing research about the use of these apps does not include the perspectives of healthcare providers.

AIMS

This study explores how healthcare providers describe the role of menstrual apps in fertility and infertility health care, and how this compares with patients' views.

MATERIALS AND METHODS

Responses were collected from an online survey (n = 37 providers and n = 89 patients) and online focus groups (n = 4 providers and n = 6 patients) and analysed using reflexive thematic analysis.

RESULTS

Healthcare providers, as well as some patients, expressed doubts about the accuracy of app estimates of the timing of ovulation. By contrast, many patients, but no healthcare providers, were enthusiastic about ovulation estimates provided by their apps. Apps were described by both groups as having a role in diagnosing and treating infertility, with healthcare providers emphasising the calendar history function of the apps supporting treatment, and patients focused on recognising and diagnosing infertility.

CONCLUSIONS

This exploratory study suggests that apps are viewed by both healthcare providers and patients as having a potential role in fertility and infertility healthcare. Although patients and app users are attentive to app estimates of ovulation timing, healthcare providers are sceptical.

Prediction of ovulation: new insight into an old challenge

Ultrasound monitoring and hormonal blood testing are considered by many as an accurate method to predict ovulation time. However, uniform and validated algorithms for predicting ovulation have yet to be defined. Daily hormonal tests and transvaginal ultrasounds were recorded to develop an algorithm for ovulation prediction. The rupture of the leading ovarian follicle was a marker for ovulation day. The model was validated retrospectively on natural cycles frozen embryo transfer cycles with documented ovulation. Circulating levels of LH or its relative variation failed, by themselves, to reliably predict ovulation. Any decrease in estrogen was 100% associated with ovulation emergence the same day or the next day. Progesterone levels > 2 nmol/L had low specificity to predict ovulation the next day (62.7%), yet its sensitivity was high (91.5%). A model for ovulation prediction, combining the three hormone levels and ultrasound was created with an accuracy of 95% to 100% depending on the combination of the hormone levels. Model validation showed correct ovulation prediction in 97% of these cycles. We present an accurate ovulation prediction algorithm. The algorithm is simple and user-friendly so both reproductive endocrinologists and general practitioners can use it to benefit their patients.

Direct-to-consumer fertility testing: utilization and perceived utility among fertility patients and reproductive endocrinologists

RESEARCH QUESTION

What is the utilization of direct-to-consumer fertility tests (DTCFT) among fertility patients? How does the perceived utility of DTCFT differ between patients and reproductive endocrinologists (REI)?

DESIGN

Infertility patients visiting the Duke Fertility Center between December 2020 and December 2021 were sent an electronic invitation to participate in a patient survey. Members of the Society of Reproductive Endocrinology and Infertility were also sent e-mail invitations to participate in the REI survey. DTCFT were defined as tests not ordered by a physician or performed at a physician's office, including calendar methods of ovulation prediction, urinary ovulation prediction kits, basal body temperature (BBT) monitoring, hormone analysis, ovarian reserve testing and semen analysis. Patients and REI were asked how likely they were to recommend a given DTCFT, on a 0-10 Likert scale.

RESULTS

In total, 425 patients (response rate 50.5%) and 178 REI (response rate 21.4%) completed the surveys. Patients reported the utilization of calendar methods of ovulation prediction (83.8%), urinary ovulation prediction (78.8%), BBT monitoring (30.8%), hormone analysis (15.3%), semen analysis (10.1%) and ovarian reserve testing (9.2%). REI rated the utility of all DTCFT significantly lower than patients did (average discordance -4.2, P < 0.001), except for urinary ovulation prediction, which REI gave a significantly higher score (discordance +1.0, P < 0.001). Prior pregnancy was significantly associated with home ovulation prediction utilization among patients (adjusted odds ratio 3.21, 95% confidence interval 1.2-9.83).

CONCLUSIONS

Methods of ovulation prediction are commonly used by fertility patients. Significant discordance exists in the perceived utility of DTCFT between patients and REI. Patient education and guidelines are needed to better inform individuals considering DTCFT.

A Comparison of Two Hormonal Fertility Monitoring Systems for Ovulation Detection: A Pilot Study

Background and Objectives: Accuracy in detecting ovulation and estimating the fertile window in the menstrual cycle is essential for women to avoid or achieve pregnancy. There has been a rapid growth in fertility apps and home ovulation testing kits in recent years. Nevertheless, there lacks information on how well these apps perform in helping users understand their fertility in the menstrual cycle. This pilot study aimed to evaluate and compare the beginning, peak, and length of the fertile window as determined by a new luteinizing hormone (LH) fertility tracking app with the Clearblue Fertility Monitor (CBFM). Materials and Methods: A total of 30 women were randomized into either a quantitative Premom or a qualitative Easy@Home (EAH) LH testing system. The results of the two testing systems were compared with the results from the CBFM over three menstrual cycles of use. Potential LH levels for estimating the beginning of the fertile window were calculated along with user acceptability and satisfaction. Results: The estimates of peak fertility by the Premom and EAH LH testing were highly correlated with the CBFM peak results (R = 0.99, p < 0.001). The participants had higher satisfaction and ease-of-use ratings with the CBFM compared to the Premom and EAH LH testing systems. LH 95% confidence levels for estimating the beginning of the fertile window were provided for both the Premom and EAH LH testing results. Conclusions: Our pilot study findings suggest that the Premom and EAH LH fertility testing app can accurately detect impending ovulation for women and are easy to use at home. However, successful utilization of these low-cost LH testing tools and apps for fertility self-monitoring and family planning needs further evaluation with a large and more diverse population.

AACC Guidance Document on the Use of Point-of-Care Testing in Fertility and Reproduction

Background

The AACC Academy revised the reproductive testing section of the Laboratory Medicine Practice Guidelines: Evidence-Based Practice for Point-of-Care Testing (POCT) published in 2007.

Methods

A panel of Academy members with expertise in POCT and laboratory medicine was formed to develop guidance for the use of POCT in reproductive health, specifically ovulation, pregnancy, premature rupture of membranes (PROM), and high-risk deliveries. The committee was supplemented with clinicians having Emergency Medicine and Obstetrics/Gynecology training.

Results

Key recommendations include the following. First, urine luteinizing hormone (LH) tests are accurate and reliable predictors of ovulation. Studies have shown that the use of ovulation predicting kits may improve the likelihood of conception among healthy fertile women seeking pregnancy. Urinary LH point-of-care testing demonstrates a comparable performance among other ovulation monitoring methods for timing intrauterine insemination and confirming sufficient ovulation induction before oocyte retrieval during in vitro fertilization. Second, pregnancy POCT should be considered in clinical situations where rapid diagnosis of pregnancy is needed for treatment decisions, and laboratory analysis cannot meet the required turnaround time. Third, PROM testing using commercial kits alone is not recommended without clinical signs of rupture of membranes, such as leakage of amniotic fluid from the cervical opening. Finally, fetal scalp lactate is used more than fetal scalp pH for fetal acidosis due to higher success rate and low volume of sample required.

Conclusions

This revision of the AACC Academy POCT guidelines provides recommendations for best practice use of POCT in fertility and reproduction.

A Comparison of App-Defined Fertile Days from Two Fertility Tracking Apps using Identical Cycle Data

OBJECTIVE

The Natural Cycles app employs daily basal body temperature to define the fertile window via a proprietary algorithm and is clinically established effective in preventing pregnancy. We sought to i) compare the app-defined fertile window of Natural Cycles to that of CycleProGo™, an app that uses BBT and cervical mucus to define the fertile window and ii) compare the app-defined fertile windows to the estimated physiologic fertile window.

STUDY DESIGN

Daily BBT were entered into Natural Cycles from 20 randomly selected regularly cycling women with at least 12 complete cycles from the CycleProGo database. The proportion of cycles with equivalent (+/-1 cycle day) fertile-window starts and fertile-window ends was determined. The app -defined fertile windows were then compared to the estimated physiologic fertile window using Peak mucus to estimate ovulation.

RESULTS

Fifty seven percent of cycles (136/238) had equivalent fertile-window starts and 36% (72/181) had equivalent fertile-window end days. The mean overall fertile-window length from Natural Cycles was 12.8 days compared to 15.1 days for CycleProGo (p<0.001). The Natural Cycles algorithm declared 12%-30% of cycles with a fertile-window start and 13%-38% of cycles with a fertile-window end within the estimated physiologic fertile window. The CycleProGo algorithm declared 4%-14% of cycles with a fertile-window start and no cycles with a fertile-window end within the estimated physiologic fertile window.

CONCLUSIONS

Natural Cycles designated a higher proportion of cycles days as infertile within the estimated physiologic fertile window than CycleProGo.

IMPLICATIONS

Use of cervical mucus in addition to BBT may improve the accuracy of identifying the fertile window. Additional studies with other markers of ovulation and the fertile window would give additional insight into the clinical implications of app-defined fertile window differences.

Multisite Effectiveness Study of the Marquette Method of Natural Family Planning Program

Women of reproductive age need reliable and effective family planning methods to manage their fertility. Natural family planning (NFP) methods or fertility awareness-based methods (FABMs) have been increasingly used by women due to their health benefits. Nevertheless, effectiveness of these natural methods remains inconsistent, and these methods are difficult for healthcare providers to implement in their clinical practice. The purpose of this study is to evaluate the effectiveness of the Marquette Model NFP system to avoid pregnancy for women at multiple teaching sites using twelve months of retrospectively collected teaching data. Survival analysis (Kaplan-Meier) was used to determine typical unintended pregnancy rates for a total of 1,221 women. There were forty-two unintended pregnancies which provided a typical use unintended pregnancy rate of 6.7 per 100 women over twelve months of use. Eleven of the forty-two unintended pregnancies were associated with correct use of the method. The total unintended pregnancy rate over twelve months of use was 2.8 per 100 for women with regular cycles, 8.0 per 100 women for the postpartum and breastfeeding women, and 4.3 per 100 for women with irregular menstrual cycles. The Marquette Model system of NFP was effective when provided by health professionals who completed the Marquette Model NFP teacher training program.

Summary

This study involved determining whether healthcare professionals at ten sites across the United States and Canada trained to provide the Marquette Method NFP services can replicate the effectiveness demonstrated in previous studies of the method. We found a high level of effectiveness (i.e., very low pregnancy rates) in using the Marquette Method among women from various regions across North America with diverse reproductive backgrounds and in particular when using hormonal fertility marker. Healthcare providers who have been trained to teach NFP can successfully incorporate NFP services in their practice and assist their clients in choosing appropriate family planning methods.

Trend natural family planning - an online survey to assess attitudes towards NFP among German-speaking women

PURPOSE

To study trends regarding the use of contraceptive methods and digital health modalities and to identify target groups of natural family planning (NFP).

MATERIAL AND METHODS

Using an online questionnaire specifically developed for this study in German (utilizing the online tool at 'www.surveymonkey.com'), we analysed the attitude towards NFP -methods and -apps, the need for contraceptive effectiveness in general, the perceived contraceptive effectiveness of NFP methods, and differences between NFP users and non-NFP users among 779 sexually active German-speaking women of fertile age (18-50 years) from November 2019 to October 2020.

RESULTS AND CONCLUSIONS

Participants used NFP more frequently than they did five years ago. Women aged 30 years and older, with higher levels of education, who are living with a partner and have children, seem to be the target group for NFP methods. Concerning the wish for contraceptive effectiveness we found significant (p < .001) differences between NFP and non-NFP users. Furthermore, an increasing number of women wants to use NFP-methods and -apps for contraception; thus, non-hormonal contraceptive options should be offered. The majority of current NFP users stated that the handling and effectiveness of NFP have been improved by digitalisation.

Time to Pregnancy for Women Using a Fertility Awareness Based Mobile Application to Plan a Pregnancy

Background: Time to pregnancy (TTP) is a biomarker of fecundability and has been associated with behavioral and environmental characteristics; however, these associations have not been examined in a large population-based sample of application (app) users.

Materials and Methods: This observational study followed 5,376 women with an age range of 18 to 45 years who used an app to identify their fertile window. We included women who started trying to conceive between September 30, 2017 and August 31, 2018. TTP was calculated as the number of menstrual cycles from when the user switched to “Plan” mode up to and including the cycle in which they logged a positive pregnancy test. We examined associations with several characteristics, including age, gravidity, body mass index, cycle length and cycle length variation, frequency of sexual intercourse, and temperature measuring frequency. Discrete time fecundability models were used to estimate fecundability odds ratios.

Results: For the complete cohort the 6-cycle and 12-cycle cumulative pregnancy probabilities were found to be 61% (95% confidence interval [CI]: 59–62) and 74% (95% CI: 73–76), respectively. The median TTP was four cycles. The highest fecundability was associated with an age of less than 35 years, with cycle length variation <5 days and logging sexual intercourse on at least 20% of days added (the proportion of days in which intercourse was logged) (11.5% [n = 613] of entire sample). This group achieved a 6- and 12-cycle cumulative pregnancy probability of 88% (95% CI: 85–91) and 95% (95% CI: 94–97), respectively, and a TTP of 2 cycles.

Conclusions: Natural Cycles was an effective method of identifying the fertile window and a noninvasive educational option for women planning a pregnancy. Women under age 35 with regular cycles showed a high pregnancy rate.

Fecundability in relation to use of mobile computing apps to track the menstrual cycle

STUDY QUESTION

To what extent does the use of mobile computing apps to track the menstrual cycle and the fertile window influence fecundability among women trying to conceive?

SUMMARY ANSWER

After adjusting for potential confounders, use of any of several different apps was associated with increased fecundability ranging from 12% to 20% per cycle of attempt.

WHAT IS KNOWN ALREADY

Many women are using mobile computing apps to track their menstrual cycle and the fertile window, including while trying to conceive.

STUDY DESIGN, SIZE, DURATION

The Pregnancy Study Online (PRESTO) is a North American prospective internet-based cohort of women who are aged 21-45 years, trying to conceive and not using contraception or fertility treatment at baseline.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We restricted the analysis to 8363 women trying to conceive for no more than 6 months at baseline; the women were recruited from June 2013 through May 2019. Women completed questionnaires at baseline and every 2 months for up to 1 year. The main outcome was fecundability, i.e. the per-cycle probability of conception, which we assessed using self-reported data on time to pregnancy (confirmed by positive home pregnancy test) in menstrual cycles. On the baseline and follow-up questionnaires, women reported whether they used mobile computing apps to track their menstrual cycles ('cycle apps') and, if so, which one(s). We estimated fecundability ratios (FRs) for the use of cycle apps, adjusted for female age, race/ethnicity, prior pregnancy, BMI, income, current smoking, education, partner education, caffeine intake, use of hormonal contraceptives as the last method of contraception, hours of sleep per night, cycle regularity, use of prenatal supplements, marital status, intercourse frequency and history of subfertility. We also examined the impact of concurrent use of fertility indicators: basal body temperature, cervical fluid, cervix position and/or urine LH.

MAIN RESULTS AND THE ROLE OF CHANCE

Among 8363 women, 6077 (72.7%) were using one or more cycle apps at baseline. A total of 122 separate apps were reported by women. We designated five of these apps before analysis as more likely to be effective (Clue, Fertility Friend, Glow, Kindara, Ovia; hereafter referred to as 'selected apps'). The use of any app at baseline was associated with 20% increased fecundability, with little difference between selected apps versus other apps (selected apps FR (95% CI): 1.20 (1.13, 1.28); all other apps 1.21 (1.13, 1.30)). In time-varying analyses, cycle app use was associated with 12-15% increased fecundability (selected apps FR (95% CI): 1.12 (1.04, 1.21); all other apps 1.15 (1.07, 1.24)). When apps were used at baseline with one or more fertility indicators, there was higher fecundability than without fertility indicators (selected apps with indicators FR (95% CI): 1.23 (1.14, 1.34) versus without indicators 1.17 (1.05, 1.30); other apps with indicators 1.30 (1.19, 1.43) versus without indicators 1.16 (1.06, 1.27)). In time-varying analyses, results were similar when stratified by time trying at study entry (<3 vs. 3-6 cycles) or cycle regularity. For use of the selected apps, we observed higher fecundability among women with a history of subfertility: FR 1.33 (1.05-1.67).

LIMITATIONS, REASONS FOR CAUTION

Neither regularity nor intensity of app use was ascertained. The prospective time-varying assessment of app use was based on questionnaires completed every 2 months, which would not capture more frequent changes. Intercourse frequency was also reported retrospectively and we do not have data on timing of intercourse relative to the fertile window. Although we controlled for a wide range of covariates, we cannot exclude the possibility of residual confounding (e.g. choosing to use an app in this observational study may be a marker for unmeasured health habits promoting fecundability). Half of the women in the study received a free premium subscription for one of the apps (Fertility Friend), which may have increased the overall prevalence of app use in the time-varying analyses, but would not affect app use at baseline. Most women in the study were college educated, which may limit application of results to other populations.

WIDER IMPLICATIONS OF THE FINDINGS

Use of a cycle app, especially in combination with observation of one or more fertility indicators (basal body temperature, cervical fluid, cervix position and/or urine LH), may increase fecundability (per-cycle pregnancy probability) by about 12-20% for couples trying to conceive. We did not find consistent evidence of improved fecundability resulting from use of one specific app over another.

STUDY FUNDING/COMPETING INTEREST(S)

This research was supported by grants, R21HD072326 and R01HD086742, from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, USA. In the last 3 years, Dr L.A.W. has served as a fibroid consultant for AbbVie.com. Dr L.A.W. has also received in-kind donations from Sandstone Diagnostics, Swiss Precision Diagnostics, FertilityFriend.com and Kindara.com for primary data collection and participant incentives in the PRESTO cohort. Dr J.B.S. reports personal fees from Swiss Precision Diagnostics, outside the submitted work. The remaining authors have nothing to declare.

TRIAL REGISTRATION NUMBER

N/A.

Use of menstruation and fertility app trackers: a scoping review of the evidence

INTRODUCTION

There has been a phenomenal worldwide increase in the development and use of mobile health applications (mHealth apps) that monitor menstruation and fertility. Critics argue that many of the apps are inaccurate and lack evidence from either clinical trials or user experience. The aim of this scoping review is to provide an overview of the research literature on mHealth apps that track menstruation and fertility.

METHODS

This project followed the PRISMA Extension for Scoping Reviews. The ACM, CINAHL, Google Scholar, PubMed and Scopus databases were searched for material published between 1 January 2010 and 30 April 2019. Data summary and synthesis were used to chart and analyse the data.

RESULTS

In total 654 records were reviewed. Subsequently, 135 duplicate records and 501 records that did not meet the inclusion criteria were removed. Eighteen records from 13 countries form the basis of this review. The papers reviewed cover a variety of disciplinary and methodological frameworks. Three main themes were identified: fertility and reproductive health tracking, pregnancy planning, and pregnancy prevention.

CONCLUSIONS

Motivations for fertility app use are varied, overlap and change over time, although women want apps that are accurate and evidence-based regardless of whether they are tracking their fertility, planning a pregnancy or using the app as a form of contraception. There is a lack of critical debate and engagement in the development, evaluation, usage and regulation of fertility and menstruation apps. The paucity of evidence-based research and absence of fertility, health professionals and users in studies is raised.

A scoping review of the information provided by fertility smartphone applications

The growth of smartphone application use across areas of female reproductive health has led to increased interest into their functions and benefits. This scoping review aims to determine the nature and extent of the peer-reviewed literature presented on fertility-based apps, to identify the reliability of the information within the apps, and to determine the ability of this information to educate users. A systematic search of six databases was conducted in April 2020, returning a total of 21,158 records. After duplicate removal, title and abstract screening exclusionary steps, 27 records were reviewed and charted. Records covered a variety of reproductive health themes including contraception, sexual health, and family planning, and used a range of methodologies. The accuracy of fertility information within the apps reported in these studies was variable, but overall there was a lack of depth in the coverage of content in apps. It was common for studies in this review to base fertile window algorithms on stringent cycle length and variability requirements, limiting the applicability of information delivered to users. Furthermore, studies from app affiliates often lacked collaborations with researchers, minimising the potential for fertility knowledge improvements integrated across the suite of female reproductive health apps.

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

Purpose of review

We reviewed published studies on menstrual cycle tracking applications (MCTAs) in order to describe the potential of MCTAs for epidemiologic research.

Recent Findings

A search of PubMed, Web of Science, and Scopus for MCTA literature yielded 150 articles. After exclusions, there were 49 articles that addressed the primary interest areas: 1) characteristics of MCTA users in research, 2) reasons women use or continue using MCTAs, 3) accuracy of identifying ovulation and utility at promoting and preventing pregnancy, and 4) quality assessments of MCTAs across several domains.

Summary

MCTAs are an important tool for the advancement of epidemiologic research on menstruation. MCTA studies should describe the characteristics of their user-base and missing data patterns. Describing the motivation for using MCTAs throughout a user's life and validating the data collected should be prioritized in future research.

Goals, life events, and transitions: examining fertility apps for holistic health tracking

OBJECTIVE

Fertility is becoming increasingly supported by consumer health technologies, especially mobile apps that support self-tracking activities. However, it is not clear whether the apps support the variety of goals and life events of those who menstruate, especially during transitions between them.

METHODS

Thirty-one of the most popular fertility apps were evaluated, analyzing data from three sources: the content of app store pages, app features, and user reviews.

FINDINGS

Results suggest that fertility apps are designed to support specific life goals of people who menstruate, offering several data collection features and limited feedback options. However, users often desire holistic tracking that encompasses a variety of goals, life events, and the transitions among them.

DISCUSSION

These findings suggest fertility patients can benefit more from holistic self-tracking and provide insights for future design of consumer health technologies that better support holistic fertility tracking.

CONCLUSION

Fertility apps have the potential to support varied experiences of people who menstruate. But to achieve that, apps need to expand their support by offering ways for more users to perform holistic, personalized, and personally meaningful tracking, so they can derive long-term benefit from the data they collect.

Fertility and digital technology: narratives of using smartphone app 'Natural Cycles' while trying to conceive

Fertility awareness apps, which help to identify the 'fertile window' when conception is most likely, have been hailed as 'revolutionising' women's reproductive health. Despite rapidly growing popularity, little research has explored how people use these apps when trying to conceive and what these apps mean to them. We draw on in-depth, qualitative interviews, adopting a critical digital health studies lens (a sub-field of science and technology studies), to explore the experiences of cisgender women and partners with one such app, Natural Cycles, in the context of their daily lives. We found that many women valued the technology as a 'natural', inobtrusive alternative to biomedical intervention, and a means of controlling and knowing their bodies, amid a dearth of fertility-related education and care. Yet this technology also intervened materially and affectively into the spaces of their lives and relationships and privileged disembodied metrics (temperature) over embodied knowledge. Meanwhile, app language, advertising and cost have contributed to characterising 'typical' users as white, heterosexual, affluent, cisgender women without disabilities. In the context of neoliberal shifts towards bodily self-tracking, technologies appealing as novel, liberating and 'natural' to individuals who can access them may nevertheless reproduce highly gendered reproductive responsibilities, anxieties and broader health and social inequalities.

Ultradian rhythms in heart rate variability and distal body temperature anticipate onset of the luteinizing hormone surge

The menstrual cycle is characterized by predictable patterns of physiological change across timescales. Although patterns of reproductive hormones across the menstrual cycle, particularly ultradian rhythms, are well described, monitoring these measures repeatedly to predict the preovulatory luteinizing hormone (LH) surge is not practical. In the present study, we explored whether non-invasive measures coupled to the reproductive system: high frequency distal body temperature (DBT), sleeping heart rate (HR), sleeping heart rate variability (HRV), and sleep timing, could be used to anticipate the preovulatory LH surge in women. To test this possibility, we used signal processing to examine these measures in 45 premenopausal and 10 perimenopausal cycles alongside dates of supra-surge threshold LH and menstruation. Additionally, urinary estradiol and progesterone metabolites were measured daily surrounding the LH surge in 20 cycles. Wavelet analysis revealed a consistent pattern of DBT and HRV ultradian rhythm (2-5 h) power that uniquely enabled anticipation of the LH surge at least 2 days prior to its onset in 100% of individuals. Together, the present findings reveal fluctuations in distal body temperature and heart rate variability that consistently anticipate the LH surge, suggesting that automated ultradian rhythm monitoring may provide a novel and convenient method for non-invasive fertility assessment.

Smartphone Applications for Period Tracking: Rating and Behavioral Change among Women Users

Background

The use of mobile apps for health and well-being has grown exponentially in the last decade, as such apps were reported to be ideal platforms for behavioral change and symptoms monitoring and management.

Objective

This study aimed to systematically review period tracking applications available at Google Play and Apple App Stores and determine the presence, features, and quality of these smartphone apps. In addition, behavioral changes associated with the top 5 rated apps were assessed.

Methods

This study used the Systematic Search Criteria through Google Play Store and iTunes Apple Store, using terms related to period tracking. Apps were scanned for matching the inclusion criteria and the included apps were assessed by two reviewers using the Mobile Application Rating Scale (MARS), a tool that was developed for classifying and assessing the quality of mHealth apps.

Results

Forty-nine apps met the inclusion criteria. Most of the apps enabled setting user goals, motivations, and interactivity, tracking multiple symptoms or mood changes, allowed notifications, and used graphs to illustrate the tracking result over a specific period of time. The majority of features and functions within these apps were offered for free, while some apps included limited in-app purchases or needed Internet connection to function. Certain apps were reported by participants to promote behavioral change and increase knowledge and awareness regarding monthly periods.

Conclusions

Period tracking apps were easy to use and navigate and can hence be readily adopted into routine tracking and management of periods. However, most apps were not based on significant evidence and may need further development to support period-related symptom management.

Do fertility tracking applications offer women useful information about their fertile window?

RESEARCH QUESTION

To characterize mobile fertility tracking applications (apps) to determine the use of such apps for women trying to conceive by identifying the fertile window.

DESIGN

An exploratory cross-sectional audit study was conducted of fertility tracking applications. Ninety out of a possible total 200 apps were included for full review. The main outcome measures were the underlying app method for predicting ovulation, the fertile window, or both, price to download and use the app, disclaimers and cautions, information and features provided and tracked, and app marketing strategies.

RESULTS

All the apps except one monitored the women's menstrual cycle dates. Most apps only tracked menstrual cycle dates (n = 49 [54.4%]). The remainder tracked at least one fertility-based awareness method (basal body temperature, cervical mucus, LH) (n = 41 [45.6%]). Twenty-five apps measured dates, basal body temperature, LH and cervical mucus (27.8%). Seventy-six per cent of apps were free to download with free apps having more desirable features, tracking more measures and having more and better quality educational insights than paid apps. Seventy per cent of apps were classified as feminine apps, 41% of which were pink in colour.

CONCLUSIONS

Mobile fertility tracking apps are heterogenous in their underlying methods of predicting fertile days, the price to obtain full app functionality, and in content and design. Unreliable calendar apps remain the most commonly available fertility apps on the market. The unregulated nature of fertility apps is a concern that could be addressed by app regulating bodies. The possible benefit of using fertility apps to reduce time to pregnancy needs to be evaluated.

The Quantified Woman: Exploring Perceptions on Health App Use among Austrian Females of Reproductive Age

Smartphones have become the most important commodity for today’s digitalized society. Besides direct interpersonal communication, their most used features are third-party applications (apps). Apps for monitoring health parameters (health apps) are extremely popular, and their users are part of the Quantified Self movement. Little knowledge is available on how health apps are perceived by a female target audience, the Quantified Woman. We conducted a study among Austrian females of reproductive age (n = 150) to analyze prevalence, perceived benefits, and readiness for health app use. In the cross-sectional online German survey, nearly all participants used these apps (98.0%), predominantly for monitoring physical activity and female health (both 31.3%). For the latter, participants used a large variety of different apps for monitoring contraception and menstruation. Perceived benefits and readiness of health app use were only of medium range. Our study assessed aspects of health app use in an understudied segment of the general population. From a Public Health perspective, the Quantified Woman could be empowered by health data collection by enabling her to take active control over how her health graphs develop. We suggest assuring data security and privacy for sensitive female health data collected by health apps.

Menstrual Cycle Length and Patterns in a Global Cohort of Women Using a Mobile Phone App: Retrospective Cohort Study

Background

There is increasing information characterizing menstrual cycle length in women, but less information is available on the potential differences across lifestyle variables.

Objective

This study aimed to describe differences in menstrual cycle length, variability, and menstrual phase across women of different ages and BMI among a global cohort of Flo app users. We have also reported on demographic and lifestyle characteristics across median cycle lengths.

Methods

The analysis was run based on the aggregated anonymized dataset from a menstrual cycle tracker and ovulation calendar that covers all phases of the reproductive cycle. Self-reported information is documented, including demographics, menstrual flow and cycle length, ovulation information, and reproductive health and diseases. Data from women aged ≥18 years and who had logged at least three cycles (ie, 2 completed cycles and 1 current cycle) in the Flo app were included (1,579,819 women).

Results

Of the 1.5 million users, approximately half (638,683/1,579,819, 40.42%) were aged between 18 and 24 years. Just over half of those reporting BMIs were in the normal range (18.5-24.9 kg/m²; 202,420/356,598, 56.76%) and one-third were overweight or obese (>25 kg/m²; 120,983/356,598, 33.93%). A total of 16.32% (257,889/1,579,819) of women had a 28-day median cycle length. There was a higher percentage of women aged ≥40 years who had a 27-day median cycle length than those aged between 18 and 24 years (22,294/120,612, 18.48% vs 60,870/637,601, 9.55%), but a lower percentage with a 29-day median cycle length (10,572/120,612, 8.77% vs 79,626/637,601, 12.49%). There were a higher number of cycles with short luteal phases in younger women, whereas women aged ≥40 years had a higher number of cycles with longer luteal phases. Median menstrual cycle length and the length of the follicular and luteal phases were not remarkably different with increasing BMI, except for the heaviest women at a BMI of ≥50 kg/m².

Conclusions

On a global scale, we have provided extensive evidence on the characteristics of women and their menstrual cycle length and patterns across different age and BMI groups. This information is necessary to support updates of current clinical guidelines around menstrual cycle length and patterns for clinical use in fertility programs.

Comparison of woman-picked, expert-picked, and computer-picked Peak Day of cervical mucus with blinded urine luteinising hormone surge for concurrent identification of ovulation

BACKGROUND

Previous research has demonstrated that women instructed in fertility awareness methods can identify the Peak Day of cervical mucus discharge for each menstrual cycle, and the Peak Day has high agreement with other indicators of the day of ovulation. However, previous studies enrolled experienced users of fertility awareness methods or were not fully blinded.

OBJECTIVE

To assess the agreement between cervical mucus Peak Day identified by fertile women without prior experience on assessing cervical mucus discharge with the estimated day of ovulation (1 day after urine luteinising hormone surge).

METHODS

This study is a secondary analysis of data from a randomised trial of the Creighton Model FertilityCareTM System (CrM), conducted 2003-2006, for women trying to conceive. Women who had no prior experience tracking cervical mucus recorded vulvar observations daily using a standardised assessment of mucus characteristics for up to seven menstrual cycles. Four approaches were used to identify the Peak Day. The referent day was defined as one day after the first identified day of luteinising hormone (LH) surge in the urine, assessed blindly. The percentage of agreement between the Peak Day and the referent day of ovulation was calculated.

RESULTS

Fifty-seven women with 187 complete cycles were included. A Peak Day was identified in 117 (63%) cycles by women, 185 (99%) cycles by experts, and 187 (100%) by computer algorithm. The woman-picked Peak Day was the same as the referent day in 25% of 117 cycles, within ±1 day in 58% of cycles, ±2 days in 84%, ±3 days in 87%, and ±4 days in 92%. The ±1 day and ± 4 days' agreement was 50% and 90% for the expert-picked and 47% and 87% for the computer-picked Peak Day, respectively.

CONCLUSIONS

Women's daily tracking of cervical mucus is a low-cost alternative for identifying the estimated day of ovulation.

Advances in Precision Health and Emerging Diagnostics for Women

During the Dutch winter famine of 1944–1945, an interesting observation was made about the offspring born during this time—They had an increased risk of developing metabolic syndrome and other chronic diseases. Subsequent research has confirmed this finding as well as noting that health outcomes for many diseases are different, and often worse, for women. These findings, combined with the lack of enrollment of women in clinical trials and/or analysis of sex-specific differences are important factors which need to be addressed. In fact, Women’s health research and sex differences have historically been overlooked or lumped together and assumed equivalent to those of men. Hence, a focus on women’s health and disease prevention is critical to improve the lives of women in the 21st Century. In this review, we point out the critical differences biologically and socially that present both challenges and opportunities for development of novel platforms for precision health. The technologic and scientific advances specific to women’s precision health have the potential to improve the health and wellbeing for all females across the world.

A Comparison of User Behaviors for a Fertility-Tracking App: Does Training in an NFP Method Improve Persistence and Use?

This study explores differences in the use of CycleProGo™ (CPG), a fertility-tracking app developed by Couple to Couple League (CCL), between those exposed to it as a part of natural family planning (NFP) instruction versus those who find it on their own. An anonymous data set of 17,543 CPG accounts opened between April 2013 and June 2016 was used for analysis. Nonmember users opened the most accounts (58 percent, n = 10,134), CCL members represented 38 percent (n = 6,758) of new accounts, and 207 CCL teachers (4 percent) were using CPG for personal charting. Significantly more nonmember accounts had zero days of use after the initial opening compared to CCL member accounts (61 percent vs. 23 percent, respectively, χ² = 2,405.9, p < .001). Conversely, significantly more CCL member accounts were used for ninety days or longer than nonmember accounts (47 percent vs. 13 percent, respectively, χ² = 2,404.2, p < .001). CCL students-those who began using the app as part of a formal NFP teaching curriculum-were more likely to use the app for > six cycles compared to nonmembers. In accounts with at least one complete cycle, CCL students were the most diligent at daily recording (95 percent of cycle days with observation recorded) followed by CCL members (88 percent) and nonmembers (76 percent). CCL teachers had the lowest frequency of cycle days with a recorded observation (73 percent). Within each cohort, accounts with > six recorded cycles had a lower proportion of cycle days with an observation recorded, likely reflecting increasing knowledge of their personal fertility patterns. Long-term users who had no known formal training in NFP still had the lowest proportion cycle days with a fertility observation. We conclude formal NFP instruction increases the probability of long-term app use, and regardless of training, long-term users will likely record observations on about 70 percent of cycle days.

Summary

"CycleProGo™ users with NFP training were more persistent and diligent about daily data input than those without training."

Evaluation of Mobile Applications Intended to Aid in Conception Using a Systematic Review Framework

Objective: This review identified and evaluated apps intended to aid women in conception that were available across major mobile platforms; secondary objectives were to highlight additional criteria and considerations when evaluating conception-related apps. Data Sources: Apple iTunes and Google Play stores were searched using the keywords conception, fertility, and pregnant. Data Selection: Included apps were as follows: contained in the first 50 search results; presented in English; intended for layperson use; updated July 1, 2018, or after; marketed as a conception aid; and used a defined fertility tracking method. Excluded apps were intended for men only, marketed for contraception only, promoted a single fertility service or branded product, or not found in both app stores. Data Extraction: Apps were evaluated using the adapted APPLICATIONS Scoring System. Two additional criteria were assessed: inclusion of a privacy policy and inclusion of a search function, medical terminology glossary, or Frequently Asked Questions section. Data Synthesis: A total of 300 apps were screened; 7 app pairs were analyzed. Scores ranged from 9 to 13 of a possible 15 points (mean = 11; median = 11). No app reported advisement from a health professional during development. Relevance to Patient Care in Clinical Practice: Widely available apps that score highly per the adapted APPLICATIONS Scoring System may be considered for use by and recommended to women seeking apps useful for conception. Conclusion: Evaluation tools should evolve as app features change. Criteria related to privacy and search functions that promote health literacy should be considered for future app evaluation tools.

Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles

The use of apps that record detailed menstrual cycle data presents a new opportunity to study the menstrual cycle. The aim of this study is to describe menstrual cycle characteristics observed from a large database of cycles collected through an app and investigate associations of menstrual cycle characteristics with cycle length, age and body mass index (BMI). Menstrual cycle parameters, including menstruation, basal body temperature (BBT) and luteinising hormone (LH) tests as well as age and BMI were collected anonymously from real-world users of the Natural Cycles app. We analysed 612,613 ovulatory cycles with a mean length of 29.3 days from 124,648 users. The mean follicular phase length was 16.9 days (95% CI: 10-30) and mean luteal phase length was 12.4 days (95% CI: 7-17). Mean cycle length decreased by 0.18 days (95% CI: 0.17-0.18, R 2 = 0.99) and mean follicular phase length decreased by 0.19 days (95% CI: 0.19-0.20, R 2 = 0.99) per year of age from 25 to 45 years. Mean variation of cycle length per woman was 0.4 days or 14% higher in women with a BMI of over 35 relative to women with a BMI of 18.5-25. This analysis details variations in menstrual cycle characteristics that are not widely known yet have significant implications for health and well-being. Clinically, women who wish to plan a pregnancy need to have intercourse on their fertile days. In order to identify the fertile period it is important to track physiological parameters such as basal body temperature and not just cycle length.

Assessment of menstrual health status and evolution through mobile apps for fertility awareness

For most women of reproductive age, assessing menstrual health and fertility typically involves regular visits to a gynecologist or another clinician. While these evaluations provide critical information on an individual's reproductive health status, they typically rely on memory-based self-reports, and the results are rarely, if ever, assessed at the population level. In recent years, mobile apps for menstrual tracking have become very popular, allowing us to evaluate the reliability and tracking frequency of millions of self-observations, thereby providing an unparalleled view, both in detail and scale, on menstrual health and its evolution for large populations. In particular, the primary aim of this study was to describe the tracking behavior of the app users and their overall observation patterns in an effort to understand if they were consistent with previous small-scale medical studies. The secondary aim was to investigate whether their precision allowed the detection and estimation of ovulation timing, which is critical for reproductive and menstrual health. Retrospective self-observation data were acquired from two mobile apps dedicated to the application of the sympto-thermal fertility awareness method, resulting in a dataset of more than 30 million days of observations from over 2.7 million cycles for two hundred thousand users. The analysis of the data showed that up to 40% of the cycles in which users were seeking pregnancy had recordings every single day. With a modeling approach using Hidden Markov Models to describe the collected data and estimate ovulation timing, it was found that follicular phases average duration and range were larger than previously reported, with only 24% of ovulations occurring at cycle days 14 to 15, while the luteal phase duration and range were in line with previous reports, although short luteal phases (10 days or less) were more frequently observed (in up to 20% of cycles). The digital epidemiology approach presented here can help to lead to a better understanding of menstrual health and its connection to women's health overall, which has historically been severely understudied.

The State of the Science of Natural Family Planning Fifty Years after Humane Vitae: A Report from NFP Scientists' Meeting Held at the US Conference of Catholic Bishops, April 4, 2018

A one-day meeting of physicians, professional nurses, and scientists actively involved in Natural Family Planning (NFP) research was held to review the state of the science of NFP and consider future priorities. The meeting had four objectives: (i) determine the gaps in research evidence for secure methods of NFP among women of all reproductive categories, (ii) determine the gaps in the research and development of new technology for providing NFP services, (iii) determine the gaps in the research that determine the benefits and challenges with use of NFP among married couples, and (iv) provide prioritized ideas for future research needs from the analysis of evidence gaps from objectives above. This article summarizes the discussion and conclusions drawn from topics reviewed. While much has been accomplished in the fifty years since Humane vitae, there are still many gaps to address. Five areas for future research in NFP were identified as high priority: (1) well-designed method effectiveness studies among various reproductive categories including important subpopulations (postpartum, perimenopause, posthormonal contraceptive), normally cycling women (especially US women), and comparative studies between NFP methods; (2) validation studies to establish the benefit of charting fertility signs (both currently known and potential new indicators) as a screening tool for women's health issues; (3) ongoing independent evaluation of fertility monitoring apps to provide users perspective on the relative merits of each and to identify those most worthy of further effectiveness testing; (4) studies evaluating the impact of new technologies on NFP adoption, use, and persistence; and (5) creation of a shared database across various NFP methods to collaborate on shared research interests, longitudinal studies, and so on. This summarizes a meeting to review the scientific and medical progress related to natural family planning made in the 50 years since Humane Vitae and to define priorities for future work. Areas reviewed included the evidence for avoiding pregnancy in normally cycling, postpartum, and perimenopausal women, the impact of new technology, including fertility charting apps, on NFP, and the impact on relationships and personal well-being from use of NFP. Five priority focus areas for future research were also identified.