Objective Social isolation and loneliness are associated with increased mortality and higher health care spending in older adults. Hearing loss is a common condition in older adults and impairs communication and social interactions. The objective of this review is to summarize the current state of the literature exploring the association between hearing loss and social isolation and/or loneliness. Data Sources PubMed, Embase, CINAHL Plus, PsycINFO, and the Cochrane Library. Review Methods Articles were screened for inclusion by 2 independent reviewers, with a third reviewer for adjudication. English-language studies of older adults with hearing loss that used a validated measure of social isolation or loneliness were included. A modified Newcastle-Ottawa Scale was used to assess the quality of the studies included in the review. Results Of the 2495 identified studies, 14 were included in the review. Most of the studies (12/14) were cross-sectional. Despite the heterogeneity of assessment methods for hearing status (self-report or objective audiometry), loneliness, and social isolation, most multivariable-adjusted studies found that hearing loss was associated with higher risk of loneliness and social isolation. Several studies found an effect modification of gender such that among women, hearing loss was more strongly associated with loneliness and social isolation than among men. Conclusions Our findings that hearing loss is associated with loneliness and social isolation have important implications for the cognitive and psychosocial health of older adults. Future studies should investigate whether treating hearing loss can decrease loneliness and social isolation in older adults.

Word clouds continue to be a popular tool for summarizing textual information, despite their well-documented deficiencies for analytic tasks. Much of their popularity rests on their playful visual appeal. In this paper, we present the results of a series of controlled experiments that show that layouts in which words are arranged into semantically and visually distinct zones are more effective for understanding the underlying topics than standard word cloud layouts. White space separators and/or spatially grouped color coding led to significantly stronger understanding of the underlying topics compared to a standard Wordle layout, while simultaneously scoring higher on measures of aesthetic appeal. This work is an advance on prior research on semantic layouts for word clouds because that prior work has either not ensured that the different semantic groupings are visually or semantically distinct, or has not performed usability studies. An additional contribution of this work is the development of a dataset for a semantic category identification task that can be used for replication of these results or future evaluations of word cloud designs.

Introduction: There are no standard practices for considering sensory impairment in studies measuring cognitive function among older adults. Exclusion of participants with impairments may inaccurately estimate the prevalence of cognitive impairment and dementia. Methods:We surveyed prospective cohort studies measuring cognitive function in older adults, determined the proportion that excluded participants based on sensory impairment and the proportion that assessed each type of sensory impairment, and described the methods of sensory assessment.Results: Investigators/staff from 85 (of 192 cohorts) responded; 6 (7%) excluded participants with severe impairment; 80 (94%) measured hearing and/or vision impairment, while 5 (6%) measured neither. Thirty-two (38%) cohorts assessed hearing objectively and 45 (53%) assessed vision objectively.Discussion: Findings indicate variation in methods used to assess sensory impairment, with potential implications for resource allocation. To ensure equitable inclusion of study participants, consensus is needed on best practices standardized protocols for assessment and accommodations of sensory impairment.

Online content creators have to manage their relations with opaque, proprietary algorithms that platforms employ to rank, filter, and recommend content. How do content creators make sense of these algorithms and what does that teach us about the roles that algorithms play in the social world? We take the case of YouTube because of its widespread use and the spaces for collective sense-making and mutual aid that content creators (YouTubers) have built within the last decade. We engaged with YouTubers in one-on-one interviews, performed content analysis on YouTube videos that discuss the algorithm, and conducted a wiki survey on YouTuber online groups. This triangulation of methodologies afforded us a rich understanding of content creators' understandings, priorities, and wishes as they relate to the algorithm. We found that YouTubers assign human characteristics to the algorithm to explain its behavior; what we have termed algorithmic personas. We identify three main algorithmic personas on YouTube: Agent, Gatekeeper, and Drug Dealer. We propose algorithmic personas as a conceptual framework that describes the new roles that algorithmic systems take on in the social world. As we face new challenges around the ethics and politics of algorithmic platforms such as YouTube, algorithmic personas describe roles that are familiar and can help develop our understanding of algorithmic power relations and potential accountability mechanisms. CCS Concepts: • Human-centered computing → Computer supported cooperative work.