Associations between population density and clinical and sociodemographic factors in women living with HIV in the Southern United States

To explore the associations of urbanicity with clinical/behavioral outcomes and sociodemographic factors among women living with HIV in the Southern United States, 523 participants of the Women’s Interagency HIV Study were classified into population density quartiles. Rural-Urban Commuting Area codes revealed that 7% resided in areas where >30% commute to urban areas, 2% resided in small towns or rural areas, and 91% resided in varying densities of urban areas. Although women in lower density, mostly suburban areas reported higher socioeconomic indicators such as advanced education and greater annual household income, larger proportions of women in the lowest density quartile perceived discrimination in health care settings and agreed with several internalized HIV stigma scale items. Women in the lower quartiles had higher CD4 counts, while those in the lowest quartile were more likely to have a suppressed HIV viral load, report being employed, and not report a history of drug use or current heavy alcohol use. More research is needed to understand the interplay between population density and mechanisms contributing to HIV control as well as increased internalized stigma and perceived discrimination, along with how to target interventions to improve outcomes for individuals with HIV across urban, suburban, and rural areas

Sentence recognition in noise: Variables in compilation and interpretation of tests

Tests of sentence recognition in noise constitute an essential tool for the assessment of auditory abilities that are representative of everyday listening experiences. A number of recent articles have reported on the development of such tests, documenting different approaches and methods. However, both the development and interpretation of these tests require careful consideration of many variables. This article reviews and categorizes the stimulus, presentation, subject, response, and performance variables influencing the development and interpretation of tests of sentence recognition in noise. A systematic framework is utilized to document published findings on these variables. Recommendations and guidelines, based on test performance requirements and test objectives, are provided concerning the interpretation of results and the development of new test materials

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press