A survey of women’s experiences of using period tracker applications: Attitudes, ovulation prediction and how the accuracy of the app in predicting period start dates affects their feelings and behaviours

Attentional, anticipatory and spatial cognition fluctuate throughout the menstrual cycle: Potential implications for female sport

Current research suggests that menstruating female athletes might be at greater risk of musculoskeletal injury in relation to hormonal changes throughout the menstrual cycle. A separate body of work suggests that spatial cognition might also fluctuate in a similar manner. Changes in spatial cognition could, in theory, be a contributing risk factor for injury, especially in fast-paced sports that require precise, millisecond accuracy in interactions with moving objects in the environment. However, existing theories surrounding causes for increased injury risk in menstruating females largely focus on biomechanical mechanisms, with little consideration of possible cognitive determinants of injury risk. Therefore, the aim of this proof-of-principle study was to explore whether menstruating females exhibit fluctuations in cognitive processes throughout their cycle on a novel sport-oriented cognitive test battery, designed to measure some of the mental processes putatively involved in these sporting situations. A total of 394 participants completed an online cognitive battery, a mood scale and a symptom questionnaire twice, 14 days apart. After exclusions, 248 eligible participants were included in the analyses (mean: 28 ± 6 years) (male = 96, female(menstruating) = 105, female(contraception) = 47). Cycle phase for menstruating females was based on self-reported information. The cognitive battery was designed to measure reaction times, attention, visuospatial functions (including 3D mental rotation) and timing anticipation. Three composite scores were generated using factor analysis with varimax rotation (Errors, Reaction Time, Intra-Individual Variability). Mixed model ANOVAs and repeated measures ANOVAs were performed to test for between and within-subject effects. There was no group difference in reaction times and accuracy between males and females (using contraception and not). However, within subject analyses revealed that regularly menstruating females performed better during menstruation compared to being in any other phase, with faster reaction times (10ms c.ca, p < 0.01), fewer errors (p < 0.05) and lower dispersion intra-individual variability (p < 0.05). In contrast they exhibited slower reaction times (10ms c.ca, p < 0.01) and poorer timing anticipation (p < 0.01) in the luteal phase, and more errors in the predicted ovulatory phase (p < 0.01). Self-reported mood, cognitive and physical symptoms were all worst during menstruation (p < 0.01), and a significant proportion of females felt that their symptoms were negatively affecting their cognitive performance during menstruation on testing day, which was incongruent with their actual performance. These findings suggest that visuospatial and anticipatory processes may fluctuate throughout the menstrual cycle in the general population, with better performance during the menstrual phase and poorer performance during the luteal phase. If these extend to associations between phase-specific cognitive performance and injury incidence, they would support a cognitive theory of determinants of injury risk in cycling female athletes, opening an opportunity to develop mitigation strategies where appropriate.

Experiences of users of period tracking apps: which app, frequency of use, data input and output and attitudes

RESEARCH QUESTION

What are the experiences of users of period tracking apps in relation to which apps they use, their frequency of use, the type of data and their attitudes to period tracking apps?

DESIGN

This was an observational mixed-methods study using an online survey designed using Qualtrics XM. The survey included 50 open-ended and multiple choice questions, but only specific questions were analysed in this study. The survey was promoted via social media for 22 days between 30 June and 21 July 2021.

RESULTS

Of the 375 total participants, 326 responses were complete and included in analysis. In the results section further down, this is explained as 330 complete responses, with 4 additional responses excluded due to data inconsistencies. The participants' age range was 14-54 years, with a mean of 26.0 (±7.81) years. Most participants (61.9%) had been using a period tracking app for 2 years or longer. Of these 85.6% entered more data when on their period, 31% at a frequency of once a day. There were approximately equivalent proportions of participants who felt that entering data into their app was either 'part of their normal routine' (43.3%) or 'not a priority' (38.0%). Thematic analysis of the participants' experiences of using period-tracking apps revealed five main themes: symptom tracking and understanding general health; concerns with period start date predictions; the problems with fertility tracking; concerns about cost; and concerns about data privacy.

CONCLUSIONS

The infrequency of data inputting and the wide range of symptoms tracked reflects the differing needs of participants from their period-tracking apps. This highlights the need for increased education and research into understanding the realities of variations in using apps.

Innovative Approaches to Menstruation and Fertility Tracking Using Wearable Reproductive Health Technology: Systematic Review

BACKGROUND

Emerging digital health technology has moved into the reproductive health market for female individuals. In the past, mobile health apps have been used to monitor the menstrual cycle using manual entry. New technological trends involve the use of wearable devices to track fertility by assessing physiological changes such as temperature, heart rate, and respiratory rate.

OBJECTIVE

The primary aims of this study are to review the types of wearables that have been developed and evaluated for menstrual cycle tracking and to examine whether they may detect changes in the menstrual cycle in female individuals. Another aim is to review whether these devices are effective for tracking various stages in the menstrual cycle including ovulation and menstruation. Finally, the secondary aim is to assess whether the studies have validated their findings by reporting accuracy and sensitivity.

METHODS

A review of PubMed or MEDLINE was undertaken to evaluate wearable devices for their effectiveness in predicting fertility and differentiating between the different stages of the menstrual cycle.

RESULTS

Fertility cycle-tracking wearables include devices that can be worn on the wrists, on the fingers, intravaginally, and inside the ear. Wearable devices hold promise for predicting different stages of the menstrual cycle including the fertile window and may be used by female individuals as part of their reproductive health. Most devices had high accuracy for detecting fertility and were able to differentiate between the luteal phase (early and late), fertile window, and menstruation by assessing changes in heart rate, heart rate variability, temperature, and respiratory rate.

CONCLUSIONS

More research is needed to evaluate consumer perspectives on reproductive technology for monitoring fertility, and ethical issues around the privacy of digital data need to be addressed. Additionally, there is also a need for more studies to validate and confirm this research, given its scarcity, especially in relation to changes in respiratory rate as a proxy for reproductive cycle staging.

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.

The Impact of Ovulation Calculators on the Stress Levels of Fertility-Seeking Couples: An Evaluation Study

Introduction Infertility affects a significant portion of couples seeking pregnancy, leading to stress and emotional strain. Ovulation calculators, widely used as a tool to predict fertile days, may play a role in the stress experienced by couples undergoing fertility treatments. The aim of this study was to evaluate the impact of ovulation calculators on the stress levels of couples seeking fertility. Methods Participants were recruited from the University of Miami Health System Clinics. Fifty couples consulting for infertility were asked to participate in the study and complete anonymous self-reported surveys. The surveys consisted of validated questions related to stress levels and the use of ovulation calculators. The completed surveys were collected and analyzed using descriptive statistics. The data collected included age, number of years trying to conceive, and answers to questions related to stress levels and the use of ovulation calculators. Responses from 50 couples who met the inclusion criteria were included in the final analysis. Results A total of 50 couples who were attempting conception and who completed all the questionnaires were included in the study. Whether or not they were using ovulation calculators, females scored similarly in the four variables of the Female Sexual Function Index (FSFI), including arousal, orgasm, satisfaction, and lubrication. When evaluating International Index of Erectile Function (IIEF) scores for male erectile function, the average score of males tracking ovulation was 12.0 ± 4.8, compared to 11.5 ± 5.4 in male patients who were not (P = 0.81). The results showed no statistically significant difference in stress levels between couples who used ovulation calculators and those who did not. However, in couples experiencing higher stress levels due to infertility, both male and female participants reported higher levels of sexual dysfunction. Fertility-related stress was also found to be significantly associated with mental health implications, with increased anxiety and depression reported by couples undergoing fertility treatments. Conclusion The findings suggest that the use of ovulation calculators did not significantly influence the stress experienced by couples seeking fertility treatment. However, the study highlights the significant impact of infertility-related stress on sexual function and mental health in both male and female partners. These results emphasize the importance of addressing the psychological aspects of infertility and providing comprehensive support to couples undergoing fertility treatments. Further research is warranted to explore the complex interplay between ovulation calculator usage, infertility-related stress, sexual dysfunction, and mental health implications in couples seeking to conceive. Healthcare providers should consider incorporating mental health support into fertility treatment programs to optimize patient outcomes and overall well-being.

A mixed methods study investigating sources of fertility and reproductive health information in the UK

OBJECTIVES

This study aimed to assess the different sources used by individuals when seeking fertility information in order to understand what's working, what isn't, and opportunities for improvement.

METHODS

A mixed-method study was conducted via UK-wide cross-sectional survey and semi-structured interviews. 1082 survey-participants were recruited nationwide via online-newspaper and social-media adverts. Of those who agreed to follow-up interview, 35 were purposively sampled to reflect the diversity of gender, age-range, ethnicity and education. Tableau software was used for surveys and NVIVO for interviews. Interview data was transcribed and analysed via thematic framework analysis.

RESULTS

Sources of information identified included: school-education; healthcare-professionals; internet, social-media, smartphone-apps, online-forums and blogs; family, friends, and communities; books, magazines, newspapers; fertility-products; workplace, communities and sexual-health clinics/centres, charities, and third-party organisations. Participants reported varying levels of access, reliability, and trust, in relation to these sources. Interview themes around veracity showed that healthcare-professionals were highly trusted but not easily accessible. The internet was very popular due to accessibility and perceived anonymity but untrusted, and "the plethora of information can be overwhelming." There were recurring themes around discomfort. A respondent recalled that her first discussion of sex with her mother was on her wedding night stating, "…Mum, I'm 28! And you're just discussing this with me now?"

CONCLUSIONS

School education remains a consistent but sometimes inadequate source of fertility information. In addition to online-platforms and products based on robust scientific evidence, opportunities for improvement include using underexploited sources, such as workplace and community settings, with training for providers.