Structural Barriers to HIV Prevention and Services: Perspectives of African American Women in Low-Income Communities

Background African American women are at a disproportionate HIV risk compared with other U.S. women. Studies show that complex structural and social determinants, rather than individual behaviors, place African American women at greater risk of HIV infection; however, little is known about women's views of what puts them at risk.AimsThis study sought to comprehend the perceptions of African American women living in low-income housing regarding the factors that influence both their personal sexual health behaviors and use of HIV prevention services. Methods We conducted seven focus groups with 48 African American women from 10 public housing communities in a small city in the southeastern United States. We analyzed the focus group transcripts using thematic data analysis to identify salient themes and points of interest related to the study aim. Results Women identified factors related to the health care system (trustworthiness of the health care system), the external environment (racism, classism, patriarchal structures, and violence/crime), as well as predisposing (health beliefs, stigma, and gender norms), enabling (agency to negotiate gendered power), and need (perceived HIV risk and perceptions of partner characteristics) features of individuals in the population. Conclusion African American women living in public housing are especially vulnerable to HIV infection due to intersectional discrimination based on racism, classism, gender power dynamics, and community conditions. Our findings confirm the need to develop HIV intervention programming addressing intersectional identities of those making up the communities they plan to address, and being informed by those living in the communities they plan to act on

Consistency of Recommendations for Evaluation and Management of Hypertension

Dermatology-oncolog

Nursing's ways of knowing and dual process theories of cognition

Aim.This paper is a comparison of nursing's patterns of knowing with the systems identified by cognitive science, and evaluates claims about the equal-status relation between scientific and non-scientific knowledge. Background.Ever since Carper's seminal paper in 1978, it has been taken for granted in the nursing literature that there are ways of knowing, or patterns of knowing, that are not scientific. This idea has recently been used to argue that the concept of evidence, typically associated with evidence-based practice, is inappropriately restricted because it is identified exclusively with scientific research. Method.The paper reviews literature in psychology which appears to draw a comparable distinction between rule-based, analytical cognitive processes and other forms of cognitive processing which are unconscious, holistic and intuitive. Findings.There is a convincing parallel between the 'patterns of knowing' distinction in nursing and the 'cognitive processing' distinction in psychology. However, there is an important difference in the way the relation between different forms of knowing (or cognitive processing) is depicted. In nursing, it is argued that the different patterns of knowing have equal status and weight. In cognitive science, it is suggested that the rule-based, analytical form of cognition has a supervisory and corrective function with respect to the other forms. Conclusions.Scientific reasoning and evidence-based knowledge have epistemological priority over the other forms of nursing knowledge. The implications of this claim for healthcare practice are briefly indicated

Computational Drug Repurposing: Current Trends

Biomedical discovery has been reshaped upon the exploding digitization of data which can be retrieved from a number of sources, ranging from clinical pharmacology to cheminformatics-driven databases. Now, supercomputing platforms and publicly available resources such as biological, physicochemical, and clinical data, can all be integrated to construct a detailed map of signaling pathways and drug mechanisms of action in relation to drug candidates. Recent advancements in computer-aided data mining have facilitated analyses of 'big data' approaches and the discovery of new indications for pre-existing drugs has been accelerated. Linking gene-phenotype associations to predict novel drug-disease signatures or incorporating molecular structure information of drugs and protein targets with other kinds of data derived from systems biology provide great potential to accelerate drug discovery and improve the success of drug repurposing attempts. In this review, we highlight commonly used computational drug repurposing strategies, including bioinformatics and cheminformatics tools, to integrate large-scale data emerging from the systems biology, and consider both the challenges and opportunities of using this approach. Moreover, we provide successful examples and case studies that combined various in silico drug-repurposing strategies to predict potential novel uses for known therapeutics