COVID-19 vaccination may be associated with change in menstrual cycle length following vaccination. We estimated covariate-adjusted differences in mean cycle length (MCL), measured in days, between pre-vaccination cycles, vaccination cycles, and post-vaccination cycles within vaccinated participants who met eligibility criteria in the Apple Women's Health Study, a longitudinal mobile-application-based cohort of people in the U.S. with manually logged menstrual cycles. A total of 9652 participants (8486 vaccinated; 1166 unvaccinated) contributed 128,094 cycles (median = 10 cycles per participant; inter-quartile range: 4-22). Fifty-five percent of vaccinated participants received Pfizer-BioNTech's mRNA vaccine, 37% received Moderna's mRNA vaccine, and 8% received the Johnson & Johnson/Janssen (J&J) vaccine. COVID-19 vaccination was associated with a small increase in MCL for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimated follicular phase vaccination was associated with increased MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated. 

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Covid-19 vaccination and menstrual cycle length in the Apple Women’s Health Study

ABSTRACT Introduction Postpartum Depression (PPD) is common, persistent, and stigmatized. There are insufficient trained professionals to deliver appropriate screening, diagnosis, and treatment. Areas covered WB001 is a Software as a Medical Device (SaMD) based Agent-Guided Cognitive Behavioral Therapy (AGCBT) program for the treatment of PPD, for which Breakthrough Device Designation was recently granted by the US Food and Drug Administration. WB001 combines therapeutic alliance, human-centered design, machine learning techniques, and established principles from CBT and interpersonal therapy (IPT). We introduce AGCBT as a new model of service delivery, whilst describing Woebot, the agent technology that enables guidance through the replication of some elements of human relationships. The profile describes the device’s design principles, enabling technology, risk handling, and efficacy data in PPD. Expert opinion WB001 is a dynamic and personalized tool with which patients may establish a therapeutic bond. Woebot is designed to augment (rather than replace) human healthcare providers, unlocking the therapeutic potency associated with guidance, whilst retaining the scalability and agency that characterizes self-help approaches. WB001 has the potential to improve both the quality and the scalability of care through providing support to patients on waiting lists, in between clinical encounters, and enabling automation of measurement-based care.

Anatomy of a Woebot® (WB001): agent guided CBT for women with postpartum depression

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Associations between drinking water disinfection byproducts and menstrual cycle characteristics: A cross-sectional study among women attending an infertility clinic.

Purpose of review The aim of this review is to evaluate biological, life history, environmental, and lifestyle factors and exposures that cause variability in menstrual cycle length (MCL). Recent findings Recent literature has detailed a number of factors that influence MCL, with particular emphasis placed on novel environmental exposures, such as air pollution and endocrine disrupting chemicals. Summary MCL varies widely in response to intrinsic and extrinsic inputs and is a useful predictor of reproductive health and fecundability. Video abstract http://links.lww.com/COE/A28.

Menstrual cycle length and modern living: a review.

Design and methods of the Apple Women's Health Study: a digital longitudinal cohort study.

The aim of this study is to determine the most informative pre- and in-cycle variables for predicting success for a first autologous oocyte in-vitro fertilization (IVF) cycle. This is a retrospective study using 22,413 first autologous oocyte IVF cycles from 2001 to 2018. Models were developed to predict pregnancy following an IVF cycle with a fresh embryo transfer. The importance of each variable was determined by its coefficient in a logistic regression model and the prediction accuracy based on different variable sets was reported. The area under the receiver operating characteristic curve (AUC) on a validation patient cohort was the metric for prediction accuracy. Three factors were found to be of importance when predicting IVF success: age in three groups (38-40, 41-42, and above 42 years old), number of transferred embryos, and number of cryopreserved embryos. For predicting first-cycle IVF pregnancy using all available variables, the predictive model achieved an AUC of 68% + /- 0.01%. A parsimonious predictive model utilizing age (38-40, 41-42, and above 42 years old), number of transferred embryos, and number of cryopreserved embryos achieved an AUC of 65% + /- 0.01%. The proposed models accurately predict a single IVF cycle pregnancy outcome and identify important predictive variables associated with the outcome. These models are limited to predicting pregnancy immediately after the IVF cycle and not live birth. These models do not include indicators of multiple gestation and are not intended for clinical application. 

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Informative predictors of pregnancy after first IVF cycle using eIVF practice highway electronic health records

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Purpose of review This review seeks to evaluate the impact of environmental exposures on the menstrual cycle length detailing timing of exposure on pathophysiology. Recent findings Recent literature has examined the relationship between menstrual cycle length and environmental exposures including air pollutants, parabens, and polybrominated biphenyls. Summary Research is limited but suggest importance of further research in evaluating environmental exposures and menstrual cycle length.

Environmental toxicant exposure and menstrual cycle length.

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.

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Alexis de Figueiredo Veiga

Papers

Design and methods of the Apple Women's Health Study: a digital longitudinal cohort study.

Informative predictors of pregnancy after first IVF cycle using eIVF practice highway electronic health records

Informative predictors of pregnancy after first IVF cycle using eIVF practice highway electronic health records

Environmental toxicant exposure and menstrual cycle length.

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