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Technologically-mediated Emotional and Social Experiences: Intimate Data Sharing by Algorithm-based Fertility Apps

Technologically-mediated Emotional and Social Experiences: Intimate Data Sharing by... 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Research in Gender Studies Addleton Academic Publishers

Technologically-mediated Emotional and Social Experiences: Intimate Data Sharing by Algorithm-based Fertility Apps

The Journal of Research in Gender Studies , Volume 11 (2): 13 – Jan 1, 2021

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
2164-0262
eISSN
2378-3524
Publisher site
See Article on Publisher Site

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

Journal

The Journal of Research in Gender StudiesAddleton Academic Publishers

Published: Jan 1, 2021

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