Published analysis of contraceptive effectiveness of Daysy and DaysyView app is fatally flawed

Mapping ethical concerns in algorithm-driven period and fertility tracking technologies

OBJECTIVE

The proliferation of algorithms in period and fertility tracking technologies has increased reliance on data and analytics to interpret menstrual cycle symptoms and guide health and fertility-related action. We set out to map the ethical concerns of the (often invisible) algorithmic influence on users' experience of, and behavior related to their menstrual cycle and fertility.

STUDY DESIGN

Reviewing literature and media, we map six ethical concerns of algorithms in period and fertility tracking technologies - inconclusive evidence, inscrutable evidence, misguided evidence, unfair outcomes, transformative effects, traceability - and highlight their potential implications, particularly for vulnerable groups.

RESULTS

Based on this mapping, we identify three overarching themes for further analysis: self-knowledge, power and control, representation and inclusion. We find that organizational activity, individual user activity and societal dynamics interact with each other and influence how we can prevent and address the mapped ethical concerns of algorithms.

CONCLUSION

Algorithm-driven period and fertility tracking technologies carry more (and more nuanced) ethical concerns than those currently discussed in the literature and in media. We call for future research to integrate the ethics of (AI) algorithms into the field of sexual and reproductive health, recognizing the complex connections between individual, organizational, and societal levels.

IMPLICATIONS

When taking the mapped ethical concerns seriously, we see a potential for algorithm-driven period and fertility tracking technologies to empower - and not discriminate - its users; for users to learn about their bodies and use the technologies responsibly; and for society to actively scrutinize its biases and achieve health equity.

Promotion of an Algorithm-Based Tool for Pregnancy Prevention by Instagram Influencers

Objective: Despite growing concerns that some digital algorithm-reliant fertility awareness-based methods of pregnancy prevention are marketed in an inaccurate, opaque, and potentially harmful manner online, there has been limited systematic examination of such marketing practices. This article therefore provides an empirical examination of how social media influencers have promoted the fertility tracking tool Daysy on Instagram. We investigate: (1) how the tool is framed in relation to pregnancy prevention using Health Belief Model (HBM) constructs, and (2) the promotional and disclosure practices adopted by influencers. Materials and Methods: We collected Instagram posts mentioning Daysy made between June 2018 and May 2022 using the tool CrowdTangle. Using a qualitative content analysis approach, we coded a random sample of 400 Daysy posts. This yielded 122 Instagram influencer posts promoting Daysy for pregnancy prevention that we coded for promotional content and HBM constructs. Results: Posts originated primarily from Europe (n = 62, 50.82%) and the United States (n = 37, 30.33%). Findings indicate that barriers to use (n = 18, 15.57%) and the severity of risks from unplanned pregnancy (n = 8, 6.56%) were rarely conveyed, whereas benefits of use (n = 122, 100%) and the severity of risks of hormonal contraception (n = 31, 25.41%) were covered more extensively. Only about one third of posts disclosed any formal relationship to the brand Daysy. Conclusions: With many posts emphasizing benefits and obscuring potential limitations, we argue that accurate and transparent information about the effectiveness and limitations of fertility tracking technologies is critical for supporting informed decision-making and, as such, should remain a public health priority.

Use of Fertility Awareness-Based Methods for Pregnancy Prevention Among Ghanaian Women: A Nationally Representative Cross-Sectional Survey

Few studies in low- and middle-income countries have examined the use of fertility awareness-based methods (FABMs) for pregnancy prevention. Understanding the prevalence of FABM use among Ghanaian contraceptors and the characteristics and practices of users is essential. Our 2018 nationally representative survey of Ghanaian women included detailed questions on the use of rhythm and Standard Days Method/Cycle Beads (SDM). After considering multimethod use patterns, we estimated likely FABM prevalence among contraceptors, identified characteristics associated with current use of an FABM (vs. current use of a hormonal method/intrauterine device [IUD]), and described how women report using FABMs. At least 18% of contracepting Ghanaian women likely use an FABM, though this may be underreported. Among FABM users, 57% reported current use of an FABM alone; the remainder reported concurrent use of other methods. Women who were older, richer, more educated, and had fewer children had higher odds of current FABM use versus IUD/hormonal method. Although FABM users were more likely than other contraceptors to correctly identify the approximate fertile time, only 50% of FABM users did so correctly. Most (92%) rhythm users were interested in making their method use more effective. While 72% had heard of SDM, less than 25% had heard of various other ways to make the rhythm method more effective. Only 17% of rhythm users had ever discussed the method with a health professional. Rhythm users indicated substantial willingness to track additional biomarkers (e.g., daily temperature or cervical mucus) or to use a phone to enhance the effectiveness of their method, and most indicated no substantial difficulty getting partners to abstain or withdraw on fertile days. A nontrivial proportion of reproductive age Ghanaian women are using an FABM, nearly all of whom are interested in learning how to improve its effectiveness. The family planning field should better address these women's contraceptive needs in commitment to reproductive autonomy and choice.

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.

Natural Cycles app: contraceptive outcomes and demographic analysis of UK users

PURPOSE

Digital fertility awareness-based contraception offers an alternative choice for women who do not wish to use hormonal or invasive methods. The aim of this study was to investigate the key demographics of current users of the Natural Cycles app and assess the contraceptive outcomes of women preventing pregnancy in a UK cohort of women.

MATERIALS AND METHODS

This was a real world observational prospective observational study. The typical-use effectiveness of the method was calculated using both 13-cycle cumulative probability of pregnancy (life table analysis) and Pearl Index for the entire study cohort. Perfect-use PI was calculated using data from cycles where sexual intercourse during the fertile window was marked as protected and no unprotected sex was recorded on fertile days.

RESULTS

12,247 women were included in the study and contributed an average of 9.9 months of data for a total of 10,066 woman years of exposure. The mean age of the cohort was 30, mean BMI 23.4, the majority were in a stable relationship (83.2%) and had a university degree or higher (83%). The one year typical use, PI was 6.1 (95% CI: 5.6, 6.6) and with perfect-use was 2.0 (95% CI: 1.3, 2.8). 13 cycle pregnancy probability was 7.1%.

CONCLUSIONS

This is the first study which describes the use of a digital contraceptive by women in the UK. It describes the demographics of users and how they correlate with the apps effectiveness at preventing pregnancy.

Contraceptive Effectiveness of an FDA-Cleared Birth Control App: Results from the Natural Cycles U.S. Cohort

Background: Digital fertility awareness-based methods of birth control are an attractive alternative to hormonal or invasive birth control for modern women. They are also popular among women who may be planning a pregnancy over the coming years and wish to learn about their individual menstrual cycle. The aim of this study was to assess the effectiveness of the Natural Cycles app at preventing pregnancy for a cohort of women from the United States and to describe the key demographics of current users of the app in such a cohort. Materials and Methods: This prospective real-world cohort study included users who purchased an annual subscription to prevent pregnancy. Demographics were assessed through answers to in-app questionnaires. Birth control effectiveness estimates for the entire cohort were calculated using 1-year pearl index (PI) and 13-cycle cumulative pregnancy probability (Kaplan-Meier life table analysis). Results: The study included 5879 women who contributed an average of 10.5 months of data for a total of 5125 woman-years of exposure. The average user was 30 years old with a body mass index of 24 and reported being in a stable relationship. With typical use, the app had a 13-cycle cumulative pregnancy probability of 7.2% and a 1-year typical use PI of 6.2. When the app was used under perfect use, the PI was 2.0. Conclusions: The data presented in this study give insights into the cohort of women using this app in the United States, and provide country-specific effectiveness estimates. The contraceptive effectiveness of the app was in line with previously published figures from Natural Cycles (PI of seven for typical use and two for perfect use).

CE: An Evidence-Based Update on Contraception

Contraception is widely used in the United States, and nurses in all settings may encounter patients who are using or want to use contraceptives. Nurses may be called on to anticipate how family planning intersects with other health care services and provide patients with information based on the most current evidence. This article describes key characteristics of nonpermanent contraceptive methods, including mechanism of action, correct use, failure rates with perfect and typical use, contraindications, benefits, side effects, discontinuation procedures, and innovations in the field. We also discuss how contraceptive care is related to nursing ethics and health inequities.

What is the clinical value of mHealth for patients?

Despite growing interest from both patients and healthcare providers, there is little clinical guidance on how mobile apps should be utilized to add value to patient care. We categorize apps according to their functionality (e.g. preventative behavior change, digital self-management of a specific condition, diagnostic) and discuss evidence for effectiveness from published systematic reviews and meta-analyses and the relevance to patient care. We discuss the limitations of the current literature describing clinical outcomes from mHealth apps, what FDA clearance means now (510(k)/de novo FDA clearance) and in the future. We discuss data security and privacy as a major concern for patients when using mHealth apps. Patients are often not involved in the development of mobile health guidelines, and professionals' views regarding high-quality health apps may not reflect patients' views. We discuss efforts to develop guidelines for the development of safe and effective mHealth apps in the US and elsewhere and the role of independent app reviews sites in identifying mHealth apps for patient care. There are only a small number of clinical scenarios where published evidence suggests that mHealth apps may improve patient outcomes.

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.

The State of Digital Interventions for Demand Generation in Low- and Middle-Income Countries: Considerations, Emerging Approaches, and Research Gaps

The recent introduction of digital health into generating demand for health commodities and services has provided practitioners with an expanded universe of potential tools to strengthen demand and ensure service delivery receipt. However, considerable gaps remain in our understanding of which interventions are effective, which characteristics mediate their benefit for different target populations and health domains, and what is necessary to ensure effective deployment. This paper first provides an overview of the types of digital health interventions for demand generation, including untargeted client communication, client-to-client communication, on-demand information services, personal health tracking, client financial transactions, and targeted client communication. It then provides a general overview of 118 studies published between January 1, 2010, and October 3, 2017, that used digital interventions to generate demand for health interventions. The majority (61%) of these studies used targeted client communication to provide health education or reminders to improve treatment adherence, and the most frequently (27%) studied health condition was HIV/AIDS. Intervention characteristics that have been found to have some effect on gains in demand generation include modality, directionality, tailoring, phrasing, and schedule. The paper also explores new emergent digital approaches that expand the potential effect of traditional demand generation in terms of personalization of content and services, continuity of care, and accountability tracking. Applying existing frameworks for monitoring and evaluation and reporting, research on emerging approaches will need to consider not only their feasibility but also their effectiveness in achieving demand generation outcomes. We propose a research agenda to help guide the field of digital demand generation studies and programs within a broader health systems strengthening agenda, including establishing and documenting the influence of intervention characteristics within different populations and health domains and examining the long-term effects and cost-effectiveness of digital demand generation interventions, as well as equity in access to such interventions.

Effectiveness of Fertility Awareness-Based Methods for Pregnancy Prevention: A Systematic Review

OBJECTIVE

To summarize best available prospective data on typical and perfect use effectiveness of fertility awareness-based methods for avoiding pregnancy.

DATA SOURCES

We conducted a systematic review of studies published in English, Spanish, French, or German by June 2017 in MEDLINE, EMBASE, CINAHL, Web of Science, and ClinicalTrials.gov.

METHODS OF STUDY SELECTION

We reviewed 8,755 unique citations and included 53 studies that contained 50 or greater women using a specific fertility awareness-based method to avoid pregnancy, calculated life table pregnancy probabilities or Pearl rates, and prospectively measured pregnancy intentions and outcomes. We systematically evaluated study quality.

TABULATION, INTEGRATION, AND RESULTS

Of 53 included studies, we ranked 0 high quality, 21 moderate quality, and 32 low quality for our question of interest. Among moderate-quality studies, first-year typical use pregnancy rates or probabilities per 100 woman-years varied widely: 11.2-14.1 for the Standard Days Method, 13.7 for the TwoDay Method, 10.5-33.6 for the Billings Ovulation Method, 4-18.5 for the Marquette Mucus-only Method, 9.0-9.8 for basal body temperature methods, 13.2 for single-check symptothermal methods, 11.2-33.0 for Thyma double-check symptothermal methods, 1.8 for Sensiplan, 25.6 for Persona, 2-6.8 for the Marquette Monitor-only Method, and 6-7 for the Marquette Monitor and Mucus Method. First-year perfect use pregnancy rates or probabilities among moderate-quality studies were 4.8 for the Standard Days Method, 3.5 for the TwoDay Method, 1.1-3.4 for the Billings Ovulation Method, 2.7 for the Marquette Mucus Method, 0.4 for Sensiplan, 12.1 for Persona, and 0 for the Marquette Monitor.

CONCLUSION

Studies on the effectiveness of each fertility awareness-based method are few and of low to moderate quality. Pregnancy rates or probabilities varied widely across different fertility awareness-based methods (and in some cases, within method types), even after excluding low-quality studies. Variability across populations studied precludes comparisons across methods.