ABSTRACT. The purpose of this study is to examine technologically-mediated emotional and social experiences as intimate data sharing by algorithm-based fertility apps. In this article, I cumulate previous research findings indicating that deploying period start dates, algorithm-based fertility apps assess a user’s daily pregnancy risk and determine her distinctive fertile window. I contribute to the literature on smartphone apps for tracking physiological signs of ovulation by showing that fertility apps constitute a digital tool for tracking menstruation and physiological signs of ovulation, generating increased and detailed information as regards the user’s menstrual cycle and predictions in relation to the most fertile days/window in the cycle. Throughout May 2021, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “fertility tracking apps,” “menstrual cycle tracking apps,” “female reproductive health apps,” and “period and fertility tracking apps.” As I inspected research published in 2019 and 2021, only 177 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 21, generally empirical, sources. Subsequent analyses should develop on intimate data sharing through big data-driven apps and algorithms. Future research should thus investigate handling biometric data as regards menstruation. Attention should be directed to precision of fertility data within menstrual cycle tracking apps.

Keywords: intimate; data; sharing; algorithm; fertility; app

How to cite: Ford, C. (2021). “Technologically-mediated Emotional and Social Experiences: Intimate Data Sharing by Algorithm-based Fertility Apps,” Journal of Research in Gender Studies 11(2): 87–99. doi: 10.22381/JRGS11220216.

Received 21 June 2021 • Received in revised form 20 December 2021
Accepted 26 December 2021 • Available online 30 December 2021

Carol Ford
This email address is being protected from spambots. You need JavaScript enabled to view it.
Personalized Clinical Care Research Unit
at CLI, Nottingham, England

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