Mayara Costa Figueiredo
ABSTRACT
With the recent popularity of self-tracking, individuals are increasingly using and interacting with their personal health data. Fertility is a health issue in which people often track and interact with diverse health-related data potentially associated with their fertility cycles. Fertility tracking is often impacted by different social factors and taboos, and it has been progressively assisted by consumer health technologies. My dissertation research combines multiple studies focusing on understanding the data practices, the influence of technology, and the consequences of using fertility-related personal data and technology in self-tracking for fertility. Based on my findings, I plan to explore how design and technology can be used to reinforce positive experiences, avoid negative emotional burden, and support holistic tracking for fertility.
- Teresa Almeida, Rob Comber, and Madeline Balaam. 2016. HCI and Intimate Care As an Agenda for Change in Women's Health. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16), 2599-- 2611. https://doi.org/10.1145/2858036.2858187Google Scholar
Digital Library
- Jessica S. Ancker, Holly O. Witteman, Baria Hafeez, Thierry Provencher, Mary Van De Graaf, and Esther Wei. 2015. "You get reminded you're a sick person": Personal data tracking and patients with multiple chronic conditions. Journal of Medical Internet Research 17, 8. https://doi.org/10.2196/jmir.4209Google ScholarCross Ref
- Amid Ayobi, Paul Marshall, Anna L. Cox, and Yunan Chen. 2017. Quantifying the Body and Caring for the Mind: Self-Tracking in Multiple Sclerosis. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI'17), 6889--6901. https://doi.org/10.1145/3025453.3025869Google ScholarDigital Library
- Jeffrey Bardzell, Shaowen Bardzell, Amanda Lazar, and Norman Makoto Su. 2019. (Re-)Framing Menopause Experiences for HCI and Design. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19), 115:1--115:13. https://doi.org/10.1145/3290605.3300345Google ScholarDigital Library
- Nadia Campo Woytuk, Linette Nilsson, and Mingxing Liu. 2019. Your Period Rules: Design Implications for Period-Positive Technologies. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA '19), LBW0137:1--LBW0137:6. https://doi.org/10.1145/3290607.3312888Google ScholarDigital Library
- Eun Kyoung Choe, Nicole B. Lee, Bongshin Lee, Wanda Pratt, and Julie A. Kientz. 2014. Understanding Quantified-selfers' Practices in Collecting and Exploring Personal Data. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '14), 1143--1152. https://doi.org/10.1145/2556288.2557372Google ScholarDigital Library
- Felicia Cordeiro, Daniel A Epstein, Edison Thomaz, Elizabeth Bales, Arvind K Jagannathan, Gregory D Abowd, and James Fogarty. 2015. Barriers and Negative Nudges?: Exploring Challenges in Food Journaling. 1159--1162.Google Scholar
- Mayara Costa Figueiredo, Clara Caldeira, Elizabeth V. Eikey, Melissa Mazmanian, and Yunan Chen. 2018. Engaging with Health Data: The Interplay Between Self-Tracking Activities and Emotions in Fertility Struggles. In Proc. ACM Hum.-Comput. Interact. https://doi.org/10.1145/3274309Google ScholarDigital Library
- Mayara Costa Figueiredo, Clara Caldeira, Tera L. Reynolds, Sean Victory, Kai Zheng, and Yunan Chen. 2017. Self-Tracking for Fertility Care: Collaborative Support for a Highly Personalized Problem. Proc. ACM Hum.-Comput. Interact. 1, CSCW: 36:1--36:21. https://doi.org/10.1145/3134671Google ScholarDigital Library
- Mayara Costa Figueiredo, Clara Caldeira, Tera L. Reynolds, Sean Victory, Kai Zheng, and Yunan Chen. 2017. Self-Tracking for Fertility Care: Collaborative Support for a Highly Personalized Problem. Proc. ACM Hum.-Comput. Interact. 1, CSCW: 36:1--36:21. https://doi.org/10.1145/3134671Google ScholarDigital Library
- Marguerite Duane, Alison Contreras, Elizabeth T. Jensen, and Amina White. 2016. The Performance of Fertility Awareness-based Method Apps Marketed to Avoid Pregnancy. Journal of the American Board of Family Medicine: JABFM 29, 4: 508--511. https://doi.org/10.3122/jabfm.2016.04.160022Google ScholarCross Ref
- Elizabeth V. Eikey and Madhu C. Reddy. 2017. "It's Definitely Been a Journey": A Qualitative Study on How Women with Eating Disorders Use Weight Loss Apps. In ACM CHI Conference on Human Factors in Computing Systems (CHI'17), 1--13. https://doi.org/10.1145/3025453.3025591Google ScholarDigital Library
- Daniel A. Epstein, Nicole B. Lee, Jennifer H. Kang, Elena Agapie, Jessica Schroeder, Laura R. Pina, James Fogarty, Julie A. Kientz, and Sean Munson. 2017. Examining Menstrual Tracking to Inform the Design of Personal Informatics Tools. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 6876--6888. https://doi.org/10.1145/3025453.3025635Google ScholarDigital Library
- Jordan Eschler, Amanda Menking, Sarah Fox, and Uba Backonja. 2019. Defining Menstrual Literacy With the Aim of Evaluating Mobile Menstrual Tracking Applications. Computers, informatics, nursing: CIN. https://doi.org/10.1097/CIN.0000000000000559Google ScholarCross Ref
- Sarah Fox, Noura Howell, Richmond Wong, and Franchesca Spektor. 2019. Vivewell: Speculating Near-Future Menstrual Tracking Through Current Data Practices. In Proceedings of the 2019 on Designing Interactive Systems Conference (DIS '19), 541--552. https://doi.org/10.1145/3322276.3323695Google ScholarDigital Library
- Alexander Freis, Tanja Freundl-Schütt, Lisa-Maria Wallwiener, Sigfried Baur, Thomas Strowitzki, Günter Freundl, and Petra Frank-Herrmann. 2018. Plausibility of Menstrual Cycle Apps Claiming to Support Conception. Frontiers in Public Health 6. https://doi.org/10.3389/fpubh.2018.00098Google ScholarCross Ref
- Frost & Sullivan. 2018. Femtech-Time for a Digital Revolution in the Women's Health Market. Frost & Sullivan. Retrieved September 7, 2019 from https://ww2.frost.com/frostperspectives/femtechtime-digital-revolutionwomens-health-market/Google Scholar
- Erik Grönvall and Nervo Verdezoto. 2013. Beyond Self-monitoring: Understanding Non-functional Aspects of Home-based Healthcare Technology. In Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'13), 587--596. https://doi.org/10.1145/2493432.2493495Google ScholarDigital Library
- Sarah Johnson, Lorrae Marriott, and Michael Zinaman. 2018. Can apps and calendar methods predict ovulation with accuracy? Current Medical Research and Opinion 34, 9: 1587--1594. https://doi.org/10.1080/03007995.2018.1475348Google ScholarCross Ref
- Dmitri Katz, Blaine Price, Simon Holland, and Nick Dalton. 2018. Data, Data Everywhere, and Still Too Hard to Link: Insights from User Interactions with Diabetes Apps.Google Scholar
- Tzu-I Lee, Yih-Harn Chiang, Jiayi Guo, Mu-Tsz Chen, and Yue Chen. 2016. Dot-it: Managing Nausea and Vomiting for A Peaceful Pregnancy with Personal Pattern Exploration. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '16), 20--25. https://doi.org/10.1145/2851581.2890631Google ScholarDigital Library
- Ian Li, Anind Dey, and Jodi Forlizzi. 2010. A Stagebased Model of Personal Informatics Systems. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10), 557--566. https://doi.org/10.1145/1753326.1753409Google ScholarDigital Library
- Ian Li, Anind K. Dey, and Jodi Forlizzi. 2011. Understanding My Data, Myself: Supporting Selfreflection with Ubicomp Technologies. In Proceedings of the 13th International Conference on Ubiquitous Computing (UbiComp '11), 405--414. https://doi.org/10.1145/2030112.2030166Google ScholarDigital Library
- Deborah Lupton and Sarah Pedersen. 2016. An Australian survey of women's use of pregnancy and parenting apps. Women and Birth: Journal of the Australian College of Midwives 29, 4: 368--375. https://doi.org/10.1016/j.wombi.2016.01.008Google ScholarCross Ref
- Lena Mamykina, Elizabeth Mynatt, Patricia Davidson, and Daniel Greenblatt. 2008. MAHI: Investigation of Social Scaffolding for Reflective Thinking in Diabetes Management. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '08), 477--486. https://doi.org/10.1145/1357054.1357131Google ScholarDigital Library
- Michelle L. Moglia, Henry V. Nguyen, Kathy Chyjek, Katherine T. Chen, and Paula M. Castaño. 2016. Evaluation of Smartphone Menstrual Cycle Tracking Applications Using an Adapted APPLICATIONS Scoring System. Obstetrics and Gynecology 127, 6: 1153--1160. https://doi.org/10.1097/AOG.0000000000001444Google ScholarCross Ref
- Manideepa Mukherjee, Sana Ali Naqvi, Anushika Verma, Debarka Sengupta, and Aman Parnami. 2019. MenstruLoss: Sensor For Menstrual Blood Loss Monitoring. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 2: 58:1--58:21. https://doi.org/10.1145/3328929Google ScholarDigital Library
- Aisling Ann O'Kane, Sun Young Park, Helena Mentis, Ann Blandford, and Yunan Chen. 2016. Turning to Peers: Integrating Understanding of the Self, the Condition, and Others' Experiences in Making Sense of Complex Chronic Conditions. Computer Supported Cooperative Work (CSCW) 25, 6: 477--501. https://doi.org/10.1007/s10606016--9260-yGoogle ScholarDigital Library
- Hanna Schneider, Julia Wayrauther, Mariam Hassib, and Andreas Butz. 2019. Communicating Uncertainty in Fertility Prognosis. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19), 161:1--161:11. https://doi.org/10.1145/3290605.3300391Google ScholarDigital Library
- K. P. Tang, S. H. Hirano, K. G. Cheng, and G. R. Hayes. 2012. Balancing caregiver and clinician needs in a mobile health informatics tool for preterm infants. In 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, 1--8. https://doi.org/10.4108/icst.pervasivehealth.2012.Google ScholarCross Ref
Index Terms
- Self-Tracking for Fertility Care: A Holistic Approach
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