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Many children are growing up in a “digital-by-default” world, where technologies mediate many of their interactions. There is emerging consensus that those who design technology must support children’s privacy and security. However, privacy and security are complex concepts that are challenging to design for, and centering the interests of children is similarly difficult. Through a document analysis of 90 HCI publications, we examine what problems and solutions designing for children’s privacy and security addresses and how this research engages with children. Applying Solove’s privacy taxonomy, we find that research addresses a range of problems related to information collection, processing, dissemination, and invasion at the organizational, system, and individual levels. Children’s participation in this research is largely limited to providing feedback rather than helping to guide the research itself. Based on these findings, we offer recommendations for designers to sharpen their privacy and security contributions and center children in their work. 

The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities. 

Researchers and policymakers advocate teaching children about digital privacy, but privacy literacy has not been theorized for children. Drawing on interviews with 30 families, including 40 children, we analyze children’s perspectives on password management in three contexts—family life, friendship, and education—and develop a new approach to privacy literacy grounded in Nissenbaum’s contextual integrity framework. Contextual integrity equates privacy with appropriate flows of information, and we show how children’s perceptions of the appropriateness of disclosing a password varied across contexts. We explain why privacy literacy should focus on norms rather than rules and discuss how adults can use learning moments to strengthen children’s privacy literacy. We argue that equipping children to make privacy-related decisions serves them better than instructing them to follow privacy-related rules. 

The platformization of households is increasingly possible with the introduction of “intelligent personal assistants” (IPAs) embedded in smart, always-listening speakers and screens, such as Google Home and the Amazon Echo. These devices exemplify Zuboff’s “surveillance capitalism” by commodifying familial and social spaces and funneling data into corporate networks. However, the motivations driving the development of these platforms—and the dataveillance they afford—vary: Amazon appears focused on collecting user data to drive personalized sales across its shopping platform, while Google relies on its vast dataveillance infrastructure to build its AI-driven targeted advertising platform. This paper draws on cross-cultural focus groups regarding IPAs in the Netherlands and the United States. It reveals how respondents in these two countries articulate divergent ways of negotiating the dataveillance affordances and privacy concerns of these IPA platforms. These findings suggest the need for a nuanced approach to combating and limiting the potential harms of these home devices, which may otherwise be seen as equivalents. 

With the recent emergence of highly transmissible variants of the novel coronavirus SARS-CoV-2, the demand for N95 respirators is expected to remain high. The extensive use of N95 respirators by the public is susceptible to demand‐supply gaps and raises concern about their disposal, threatening the environment with a new kind of plastic pollution. Herein, we investigated the filtration performance of the N95 respirator by specifically analyzing the structure in the key filtration layers of meltblown nonwoven after decontamination with one and five cycles of liquid hydrogen peroxide, ultraviolet radiation, moist heat, and aqueous soap solution treatments. With the aid of X-ray microcomputed tomography (microCT) analysis, the local structural heterogeneity of the meltblown nonwoven has been unfolded and subsequently correlated with their filtration performance at a face velocity that matched with speaking conditions (∼3.89 m/s). The filtration efficiency results of the N95 respirator remain unaltered after performing one cycle of treatment modalities (except autoclave).