Women use fertility tracking apps (FTAs) for conception purposes, but user perspectives on FTA use for conception are largely unknown. In collaboration with SPD Clearblue, this study explored: how women trying to conceive use FTAs; women’s knowledge of their conception chances; and women’s feelings towards a potential natural conception prediction app (NCPA).
A mixed methods design was used (online survey and phone interviews). Participants were women 18–40 years old actively trying to conceive.
The survey received 154 responses and 24 interviews were conducted. Thematic analysis of interviews found that women consider several factors before trying to conceive (ex. age, financial and job security, stability of relationship, etc.) and may adopt lifestyle and behaviour changes when trying (ex. increasing exercise, smoking cessation, diet changes, etc.). Survey results indicated that nearly all respondents were aware of FTAs (n = 146, 94.8%), however, several other fertility and conception information sources were also used (ex. health care providers, online sources, family and friends, etc.). Nearly all respondents reported they would use an NCPA (n = 153, 99.4%). During interviews women had positive feelings towards such an app due to it offering new and individualised information, but worried the app could provide upsetting information.
This research elaborates on women’s uses of and interest in FTAs. Stakeholders should use this research to reflect on current conception experiences and possibilities for improvement through development of an NCPA. Future research should seek opinions from a more diverse sample of women to inform the development of an inclusive NCPA.
背景：女性因生育目的使用生育跟踪应用程序（FTA）, 但用户对FTA之于生育目的的看法基本上是未知的。本研究通过与SPD Clearblue合作探讨了：备孕女性如何使用FTA；女性对受孕机会的了解；以及女性对潜在自然受孕预测应用程序（NCPA）的感受。
结果：在线调研共收到154份回复, 电话访谈进行了24次。对访谈的专题分析发现, 女性在备孕前会考虑几个因素（例如年龄、经济状况和工作保障、关系的稳定性等）, 并可能在备孕时改变生活方式和行为（例如增加锻炼、戒烟、改变饮食等）。调查结果表明, 几乎所有受访者都知道FTA（n=146, 94.8%）, 但也使用了其他一些生育和受孕相关信息来源（如医护工作者、在线来源、家人和朋友等）。几乎所有受访者都表示他们会使用NCPA（n=153, 99.4%）。在访谈中, 女性认为这样的应用程序有用, 因为它提供了先进和个性化的信息, 但担心该应用程序会提供令人不安的信息。
We would like to thank all our survey respondents and interview participants, without whom this research would not have been possible. Additionally, we would like to thank the Clearblue team at SPD Development Company Ltd., for their assistance and support with volunteer recruitment and assistance with implementation of the research.
An NCPA is planned for development by researchers at the University of Aberdeen in collaboration with SPD Development Company Ltd. (Clearblue). This study will serve as a proof of concept for the development of this technology.
This study was designed by DB, HMM, and DJM in collaboration with the industry partner SPD Development Company Ltd. (Clearblue). Participant recruitment was led by the industry partner. Data collection was conducted by DB. Analysis was done by DB with statistical analysis support from DJM and qualitative analysis support from HMM including transcript coding work. DB led the writing with contributions and comments provided by HMM and DJM who also approved the final version.
Reflexivity and potential for bias
It should be acknowledged that DB is currently using contraception that affects her menstrual cycle. She does not have any children and has never tried to conceive. She does not currently use any fertility apps although she previously used Clue to track her cycle and symptoms. Although experienced in conducting interviews, and in survey development and collection methods, this is the first research she has conducted using a mixed-methods design, and in the fields of digital health and fertility tracking.
HMM uses no hormonal contraception, has no children, and has never tried to conceive. She has been a quantified self since her teens and early adopter of self-tracking apps and technologies. She is a specialist in the field of digital health and has previously conducted research into fertility tracking.
DJM has no children and has been conducting and leading research in the discipline of reproductive medicine for 10 years. He has led the development of prediction models that can inform couples of their chance of live birth before and during IVF treatment. These have subsequently been converted into freely available online tools which are used by patients and clinicians.