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Pregnancy brings physical, emotional, and economic challenges for expectant parent(s), close relatives, and friends. Existing technology support, including tracking technology, largely targets pregnant people and ignores other stakeholders. We therefore lack an understanding of how to approach designing collaborative pregnancy tracking technology. To understand how people collaborate around pregnancy tracking and wish to do so, we interviewed 13 pregnant people and 11 non-pregnant stakeholders in the U.S., including partners, friends, and grandparents-to-be. We find that people collaborate for goals like social bonding and jointly managing various pregnancy data. Stakeholders collaborated by either dividing up data types or collectively monitoring the same information. We also identify tensions and challenges, such as pregnant people’s privacy concerns and stakeholders’ varied levels of interest in tracking. In light of socio-cultural norms and stakeholders’ distinctive roles around pregnancy, we point to opportunities for designing collaborative technology that aligns with as well as challenges socio-cultural practices around pregnancy tracking. 

Family informatics often uses shared data dashboards to promote awareness of each other’s health-related behaviors. However, these interfaces often stop short of providing families with needed guidance around how to improve family functioning and health behaviors. We consider the needs of family co-regulation with ADHD children to understand how in-home displays can support family well-being. We conducted three co-design sessions with each of eight families with ADHD children who had used a smartwatch for self-tracking. Results indicate that situated displays could nudge families to jointly use their data for learning and skill-building. Accommodating individual needs and preferences when family members are alone is also important, particularly to support parents exploring their co-regulation role, and assisting children with data interpretation and guidance on self and co-regulation. We discuss opportunities for displays to nurture multiple intents of use, such as joint or independent use, while potentially connecting with external expertise. 

Pregnancy is a significant but stressful life transition, requiring effort from multiple stakeholders including expectant parents, family members, and friends to navigate. Existing work has primarily focused on understanding and supporting the technology use of pregnant people, neglecting other stakeholders' needs and participation. We therefore consider how pregnancy tracking apps both improve and interfere with the reconfiguration of social relationships caused by pregnancy, drawing on insights from family sociology to examine how these relationships evolve over pregnancy and the transition to parenthood. We reviewed the features of 20 pregnancy tracking apps, and analyzed 4,709 public reviews of them, finding that stakeholders used apps to bond with one another around the excitement of pregnancy, build a prenatal relationship with the fetus, and co-manage pregnancy-related logistical tasks. We find that not accounting for fetal demographics and users' identities, along with socio-cultural norms around gender and parenting roles, often inhibit these collaborative practices. We therefore suggest designing collaborative pregnancy tracking technology that considers both inclusiveness and specificity regarding stakeholders' different roles and relationships to pregnancy. 

Recently, there has been a proliferation of personal health applications describing to use Artificial Intelligence (AI) to assist health consumers in making health decisions based on their data and algorithmic outputs. However, it is still unclear how such descriptions influence individuals' perceptions of such apps and their recommendations. We therefore investigate how current AI descriptions influence individuals' attitudes towards algorithmic recommendations in fertility self-tracking through a simulated study using three versions of a fertility app. We found that participants preferred AI descriptions with explanation, which they perceived as more accurate and trustworthy. Nevertheless, they were unwilling to rely on these apps for high-stakes goals because of the potential consequences of a failure. We then discuss the importance of health goals for AI acceptance, how literacy and assumptions influence perceptions of AI descriptions and explanations, and the limitations of transparency in the context of algorithmic decision-making for personal health.