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Self-Tracking for Fertility Care: Collaborative Support for a Highly Personalized Problem

Authors:

Mayara Costa Figueiredo,

Clara Caldeira,

Tera L. Reynolds,

Yunan ChenAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 1, Issue CSCW

Article No.: 36, Pages 1 - 21

https://doi.org/10.1145/3134671

Published: 06 December 2017 Publication History

Abstract

Infertility is a global health concern that affects countless couples trying to conceive a child. Effective fertility treatment requires continuous monitoring of a wide range of health indicators through self-tracking. The process of collecting and interpreting data and information about fertility is complex, and much of the burden falls on women. In this study, we analyzed patient-generated content in a popular online health community dedicated to fertility issues. The objective was to understand the process in which women engage in tracking relevant information, and the challenges they face. Leveraging the Personal Informatics Model, we describe women's self-tracking experiences during their fertility cycles. We discuss how a complex and highly personalized context leads to responsibility, pressure, and emotional burden on women performing self-tracking activities, as well as the role of collaboration in creating individualized solutions. Finally, we provide implications for technologies aiming to support women with fertility care needs.

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Self-Tracking for Fertility Care: Collaborative Support for a Highly Personalized Problem

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 1, Issue CSCW

November 2017

2095 pages

EISSN:2573-0142

DOI:10.1145/3171581

Editors:
Clifford Lampe
University of Michigan
,
Jeff Nichols
Google
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Karrie Karahalios
University of Illinois Urbana-Champaign
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Geraldine Fitzpatrick
Vienna University of Technology
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Uichin Lee
KAIST
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Andres Monroy-Hernandez
Snap Inc.
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Wolfgang Stuerzlinger
Simon Fraser University

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Published: 06 December 2017

Published in PACMHCI Volume 1, Issue CSCW

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https://dl.acm.org/doi/10.1145/3656156.3665134
Su ZKamath STirakitsoontorn PChen Y(2024)The Hidden Burden: Encountering and Managing (Unintended) Stigma in Children with Serious IllnessesProceedings of the ACM on Human-Computer Interaction10.1145/36410218:CSCW1(1-35)Online publication date: 26-Apr-2024
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Lu XPowell JAgapie EChen YEpstein D(2024)Examining the Social Aspects of Pregnancy Tracking ApplicationsProceedings of the ACM on Human-Computer Interaction10.1145/36373288:CSCW1(1-30)Online publication date: 26-Apr-2024
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