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BackgroundLifestyle modification is the most important factor in the management of obesity. It is therefore essential to enhance client participation in voluntary and continuous weight control.ObjectiveThe aim of this study was to develop an obesity management ontology for application in the mobile-device domain. We considered the concepts of client participation in behavioral modification for obesity management and focused on minimizing the amount of information exchange between the application and the database when providing tailored interventions.MethodsAn obesity management ontology was developed in seven phases: (1) defining the scope of obesity management, (2) selecting a foundational ontology, (3) extracting the concepts, (4) assigning relationships between these concepts, (5) evaluating representative layers of ontology content, (6) representing the ontology formally with Protégé, and (7) developing a prototype application for obesity management.ResultsBehavioral interventions, dietary advice, and physical activity were proposed as obesity management strategies. The nursing process was selected as a foundation of ontology, representing the obesity management process. We extracted 127 concepts, which included assessment data (eg, sex, body mass index, and waist circumference), inferred data to represent nursing diagnoses and evaluations (eg, degree of and reason for obesity, and success or failure of lifestyle modifications), and implementation (eg, education and advice). The relationship linking concepts were “part of”, “instance of”, “derives of”, “derives into”, “has plan”, “followed by”, and “has intention”. The concepts and relationships were formally represented using Protégé. The evaluation score of the obesity management ontology was 4.5 out of 5. An Android-based obesity management application comprising both agent and client parts was developed.ConclusionsWe have developed an ontology for representing obesity management with the nursing process as a foundation of ontology.

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Background: The likelihood of inpatient mortality has been found to be reduced by increased nurse staffing in several settings, including general wards, emergency departments, and intensive care units. However, less research has investigated cases where patients die in the community setting due to a health problem that occurred after they were discharged post-surgery, because it is difficult to integrate hospital data and local community data. Therefore, this study investigated the association between the bed-to-nurse ratio and 30-day post-discharge mortality in patients undergoing surgery using national administrative data. Methods: The study analyzed data from 129,923 patients who underwent surgery between January 2014 and December 2015. The bed-to-nurse ratio was categorized as level 1 (less than 2.5), level 2 (2.5-3.4), level 3 (3.5-4.4), and level 4 (4.5 or greater). The chi-square test and GEE logistic regression analyses were used to explore the association between the bed-to-nurse ratio and 30-day post-discharge mortality. Results: 1355 (0.01%) patients died within 30 days post-discharge. The 30-day post-discharge mortality rate in hospitals with a level 4 was 2.5%, representing a statistically significant difference from the rates of 0.8, 2 and 1.8% in hospitals with level 1, level 2, and level 3 staffing, respectively. In addition, the death rate was significantly lower at hospitals with a level 1 (OR = 0.62) or level 2 (OR = 0.63) bed-to-nurse ratio, using level 4 as reference. Conclusion: The results of this study are highly meaningful in that they underscore the necessity of in-hospital discharge nursing and continued post-discharge nursing care as a way to reduce post-discharge mortality risk. Furthermore, the relationship between nurse staffing levels and 30-day post-discharge mortality implies the need for a greater focus on discharge education. Policies are required to achieve proper nurse staffing levels in Korea, and thereby to enhance patient outcomes.

This study aimed to examine the association of depression with metabolic syndrome and to investigate levels of awareness and treatment of depression in Korean adults. We analyzed data extracted from the Korea National Health and Nutrition Examination Survey (2014 and 2016) using the Patient Health Questionnaire-9 depression screening instrument. Among the survey participants, 10 459 were selected for data analysis. Of them, 7.2% had depression, 24.4% had metabolic syndrome, and 10.0% had both depression and metabolic syndrome. Among those with depression, 33.1% were aware of their condition and 25.7% received treatment, with significant differences found between those with and without metabolic syndrome. The mean Patient Health Questionnaire-9 scores significantly increased with the number of metabolic syndrome components (F = 6.06, P = <.001). In logistic regression analysis, the odds ratio (OR) for depression with metabolic syndrome was 1.41 (95% confidence interval [CI] = 1.12-1.76). For the number of metabolic syndrome components, having 2 (OR = 1.37, 95%