Nursing Advising Using a MOOC: A Case Study

Advanced technology has moved online courses from being available to exclusively to elite students to literally being open to the general public. The proliferation of Massive Open Online Courses (MOOCs) has led to expanding public access to a wide range of information including careers in health care fields. Our group developed a MOOC to assist people from around the world who are interested in pursuing a career in nursing get the information they need to be successful in the nursing program and in the profession of nursing. In this article, we describe course content, who the students were who enrolled in the free MOOC, and the course outcomes we developed. In addition, we discuss lessons learned and provide recommendations to assist others seeking to develop a MOOC for career advising

Classifying nursing organization in wards in Norwegian hospitals: self-identification versus observation

<p>Abstract</p> <p>Background</p> <p>The organization of nursing services could be important to the quality of patient care and staff satisfaction. However, there is no universally accepted nomenclature for this organization. The objective of the current study was to classify general hospital wards based on data describing organizational practice reported by the ward nurse managers, and then to compare this classification with the name used in the wards to identify the organizational model (self-identification).</p> <p>Methods</p> <p>In a cross-sectional postal survey, 93 ward nurse managers in Norwegian hospitals responded to questions about nursing organization in their wards, and what they called their organizational models. K-means cluster analysis was used to classify the wards according to the pattern of activities attributed to the different nursing roles and discriminant analysis was used to interpret the solutions. Cross-tabulation was used to validate the solutions and to compare the classification obtained from the cluster analysis with that obtained by self-identification. The bootstrapping technique was used to assess the generalizability of the cluster solution.</p> <p>Results</p> <p>The cluster analyses produced two alternative solutions using two and three clusters, respectively. The three-cluster solution was considered to be the best representation of the organizational models: 32 team leader-dominated wards, 23 primary nurse-dominated wards and 38 wards with a hybrid or mixed organization. There was moderate correspondence between the three-cluster solution and the models obtained by self-identification. Cross-tabulation supported the empirical classification as being representative for variations in nursing service organization. Ninety-four per cent of the bootstrap replications showed the same pattern as the cluster solution in the study sample.</p> <p>Conclusions</p> <p>A meaningful classification of wards was achieved through an empirical cluster solution; this was, however, only moderately consistent with the self-identification. This empirical classification is an objective approach to variable construction and can be generally applied across Norwegian hospitals. The classification procedure used in the study could be developed into a standardized method for classifying hospital wards across health systems and over time.</p

Epidemiology of Dengue Virus in Iquitos, Peru 1999 to 2005: Interepidemic and Epidemic Patterns of Transmission

To develop prevention (including vaccines) and control programs for dengue fever, a significant mosquito-borne disease in the tropics, there is an urgent need for comprehensive long term field epidemiological studies. We report results from a study that monitored ∼2,400 school children and some adult family members for dengue infection at 6 month intervals from 1999 to 2005, in the Amazonian city of Iquitos, Peru. At enrollment, ∼80% of the participants had a previous infection with DENV serotypes 1 and 2 or both. During the first 15 months, about 3 new infections for every 100 participants were observed among the study participants. In 2001, DENV-3, a serotype not previously observed in the region, invaded Iquitos in a process characterized by 3 distinct periods: amplification over at least a 5–6 month period, replacement of previously circulating serotypes, and epidemic transmission when incidence peaked. Incidence patterns of new infections were geographically distinct from baseline prevalence rates prior to arrival of DENV-3, but closely mirrored them during the invasion. DENV transmission varied geographically corresponding to elevated mosquito densities. The invasion of a novel serotype is often characterized by 5–6 months of silent transmission before traditional surveillance programs detect the virus. This article sets the stage for subsequent publications on dengue epidemiology

Spatial Dimensions of Dengue Virus Transmission across Interepidemic and Epidemic Periods in Iquitos, Peru (1999–2003)

To target prevention and control strategies for dengue fever, it is essential to understand how the virus travels through the city. We report spatial analyses of dengue infections from a study monitoring school children and adult family members for dengue infection at six-month intervals from 1999–2003, in the Amazonian city of Iquitos, Peru. At the beginning of the study, only DENV serotypes 1 and 2 were circulating. Clusters of infections of these two viruses were concentrated in the northern region of the city, where mosquito indices and previous DENV infection were both high. In 2002, DENV-3 invaded the city, replacing DENV-1 and -2 as the dominant strain. During the invasion process, the virus spread rapidly across the city, at low levels. After this initial phase, clusters of infection appeared first in the northern region of the city, where clusters of DENV-1 and DENV-2 had occurred in prior years. Most of the clusters we identified had radii >100 meters, indicating that targeted or reactive treatment of these high-risk areas might be an effective proactive intervention strategy. Our results also help explain why vector control within 100 m of a dengue case is often not successful for large-scale disease prevention

Spatial dimensions of dengue virus transmission across interepidemic and epidemic periods in Iquitos, Peru (1999-2003).

BackgroundKnowledge of spatial patterns of dengue virus (DENV) infection is important for understanding transmission dynamics and guiding effective disease prevention strategies. Because movement of infected humans and mosquito vectors plays a role in the spread and persistence of virus, spatial dimensions of transmission can range from small household foci to large community clusters. Current understanding is limited because past analyses emphasized clinically apparent illness and did not account for the potentially large proportion of inapparent infections. In this study we analyzed both clinically apparent and overall infections to determine the extent of clustering among human DENV infections.Methodology/principal findingsWe conducted spatial analyses at global and local scales, using acute case and seroconversion data from a prospective longitudinal cohort in Iquitos, Peru, from 1999-2003. Our study began during a period of interepidemic DENV-1 and DENV-2 transmission and transitioned to epidemic DENV-3 transmission. Infection status was determined by seroconversion based on plaque neutralization testing of sequential blood samples taken at approximately six-month intervals, with date of infection assigned as the middate between paired samples. Each year was divided into three distinct seasonal periods of DENV transmission. Spatial heterogeneity was detected in baseline seroprevalence for DENV-1 and DENV-2. Cumulative DENV-3 seroprevalence calculated by trimester from 2001-2003 was spatially similar to preexisting DENV-1 and DENV-2 seroprevalence. Global clustering (case-control Ripley's K statistic) appeared at radii of ∼200-800 m. Local analyses (Kuldorf spatial scan statistic) identified eight DENV-1 and 15 DENV-3 clusters from 1999-2003. The number of seroconversions per cluster ranged from 3-34 with radii from zero (a single household) to 750 m; 65% of clusters had radii &gt;100 m. No clustering was detected among clinically apparent infections.Conclusions/significanceSeroprevalence of previously circulating DENV serotypes can be a predictor of transmission risk for a different invading serotype and, thus, identify targets for strategically placed surveillance and intervention. Seroprevalence of a specific serotype is also important, but does not preclude other contributing factors, such as mosquito density, in determining where transmission of that virus will occur. Regardless of the epidemiological context or virus serotype, human movement appears to be an important factor in defining the spatial dimensions of DENV transmission and, thus, should be considered in the design and evaluation of surveillance and intervention strategies