Job Analysis of Visiting Nurses in the Process of Change Using FGI and DACUM

Purpose@#This study conducted a job analysis of visiting nurses in the process of change. @*Methods@#Participants were the visiting nurses working for the Seoul Metropolitan city. On the basis of the Public Health Intervention Wheel model, two times of the focus group interview (FGI) with seven visiting nurses and one time of the Developing a Curriculum (DACUM) with 34 visiting nurses were performed. A questionnaire survey of 380 visiting nurses was conducted to examine the frequency, importance and difficulty levels of the tasks created by using the FGI and DACUM. @*Results@#Visiting nurses’ job was derived as the theme of present versus transitional roles. The present role was categorized as ‘providing individual- and group-focused services’ and ‘conducting organization management’, while the transitional role was categorized as ‘providing district-focused services’ and ‘responding to new health issues’. The job generated 13 duties, 28 tasks, and 73task elements. The tasks showed the levels of frequency (3.65 scores), importance (4.27 scores), and difficulty (3.81 scores). All the tasks were determined as important, exceeding the average 4.00 scores. The group- and district-focused services of the tasks were recognized as more difficult but less frequent tasks. @*Conclusion@#The visiting nurses exert both present and transitional roles. The transitional roles identified in the present study should be recognized as an extended role of visiting nurses in accordance with the current changing healthcare needs in South Korea. Finally, the educational curriculum for visiting nurses that reflects the transitional roles from the present study is needed.

Publication Delay of Korean Medical Journals

Publication lag is a determinant to journal efficiency that was not yet studied concerning Korean medical journals. To measure publication lag, we investigated the publication timestamps of 4,762 articles published by 10 Korean medical journals indexed in Scopus database, randomly selected from the KoreaMed Synapse since 2013. The total publication lag was 246.5 (Q1, Q3; 178.0, 347.0) days. The overall acceptance lag was 102.0 (65.0, 149.0) days. The overall lead lag was 123.0 (63.0, 236.0) days. The year of publication did not significantly affect the acceptance lag (P = 0.640), supposedly shortening it by about 1.4 (97.5% confidence interval [CI], −5.2 to 8.0) days/year, while the date affected the lead lag (P = 0.028), shortening it by about 12.9 (1.3 to 24.5) days/year. The Korean medical journals have reduced the total publication delay entirely by means of reducing the lead lag, not by reducing the acceptance lag.

Nonlinear Dynamic Projection for Noise Reduction of Dispersed Manifolds.

The search for a low-dimensional structure in high-dimensional data is one of the fundamental tasks in machine learning and pattern recognition. Manifold learning algorithms have recently emerged as alternatives to traditional linear dimension reduction techniques. In this paper, we propose a novel projection method that can be combined with any manifold learning methods to improve their dimension reduction performance when applied to high-dimensional data with a high level of noise. The method first builds a dispersion function that describes the distribution of dispersed manifold where the data lie. It then projects the noisy data onto a region wrapping the true manifold sufficiently close to it by applying a dynamical projection system associated with the constructed dispersion function. The effectiveness of the proposed projection method is validated by applying it to some real-world data sets with promising results.