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Health Data in Fertility Care: An Ecological Perspective

Authors:

Mayara Costa Figueiredo,

Yunan ChenAuthors Info & Claims

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Article No.: 204, Pages 1 - 17

https://doi.org/10.1145/3411764.3445189

Published: 07 May 2021 Publication History

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Abstract

Fertility tracking and technology are characterized by logging varied health-related data potentially associated with female fertility cycles. Such data are often seen as private and restricted to the individual level. We conducted an interview study with 21 people (16 in the U.S.) facing challenges to conceive and 5 U.S. healthcare providers specialized in infertility to analyze (in)fertility experiences with data. Our findings suggest that although fertility data are considered personal and private, they are embedded in larger ecological systems of use, influencing and being influenced by different stakeholders, institutional contexts, and sociocultural factors. Leveraging the Ecological Systems Theory, we analyze the relationships and factors shaping individuals’ fertility trajectories, discussing how the different layers influence the work individuals have to engage and the burden imposed on them through various social, institutional, and cultural boundaries. We propose an ecological perspective on fertility data practices and discuss opportunities to counter-influence broader environmental systems through data tracking.

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cover image ACM Conferences

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

May 2021

10862 pages

ISBN:9781450380966

DOI:10.1145/3411764

General Chairs:
Yoshifumi Kitamura
Tohoku University, Japan
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Aaron Quigley
University of New South Wales, Australia
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University of California Santa Cruz, USA
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Takeo Igarashi
The University of Tokyo, Japan
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University of Copenhagen, Denmark
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Microsoft Research, USA

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Singh B(2024)Cruising Deep Convolution Neural Networks (DCNN) and Internet of Medical Things (IoMT) Fostering Smart HealthcareResponsible AI for Digital Health and Medical Analytics10.4018/979-8-3693-6294-5.ch009(211-240)Online publication date: 13-Dec-2024
https://doi.org/10.4018/979-8-3693-6294-5.ch009
Singh BKaunert CRaghav AJermsittiparsert KRavesangar K(2024)Adaptability of Wearable Sensors in Data Assimilation and Real-Time Monitoring in Health GatewaysPhysical Health, Mental Health, and Human Well-Being in the Age of AI10.4018/979-8-3693-6190-0.ch020(477-502)Online publication date: 18-Oct-2024
https://doi.org/10.4018/979-8-3693-6190-0.ch020
Nikkhah SRode AKulkarni NMittal PMueller EMiller A(2024)Family Resilience in Care Coordination Technologies: Designing for Families as Adaptive SystemsProceedings of the ACM on Human-Computer Interaction10.1145/36869988:CSCW2(1-28)Online publication date: 8-Nov-2024
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Lu XPowell JAgapie EChen YEpstein D(2024)Unpacking the Lived Experience of Collaborative Pregnancy TrackingProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642652(1-17)Online publication date: 11-May-2024
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Wani AJoshi INahvi NSingh P(2024)"Unrest and trauma stays with you!": Navigating mental health and professional service-seeking in KashmirProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642507(1-17)Online publication date: 11-May-2024
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