Development of a Wellness Index for Workers

PURPOSE: The purpose of this study was to develop a wellness index for workers (WIW) and examine the validity and reliability of the WIW for assessing workers' wellness. METHODS: The developmental process for the instrument included construction of a conceptual framework based on a wellness model, generation of initial items, verification of content validity, preliminary study, extraction of final items, and psychometric testing. Content validity was verified by 4 experts from occupational health nursing and wellness disciplines. The construct validity, convergent validity and discriminant validity were examined with confirmatory factor analysis. The reliability was examined with Cronbach's alpha. The participants were 494 workers from two workplaces. RESULTS: Eighteen items were selected for the final scale, and the results of the confirmatory factor analysis supported a five-factor model of wellness with acceptable model fit, and factors named as physical . emotional . social . intellectual . occupational wellness. The convergent and discriminant validity were also supported. The Cronbach's alpha coefficient was .91. CONCLUSION: The results indicate that the WIW is a valid and reliable instrument to comprehensively assess workers' wellness, and to provide basic directions for developing workplace wellness program.

Association Rules to Identify Complications of Cerebral Infarction in Patients with Atrial Fibrillation / 대한의료정보학회지

OBJECTIVES: The purpose of this study was to find risk factors that are associated with complications of cerebral infarction in patients with atrial fibrillation (AF) and to discover useful association rules among these factors. METHODS: The risk factors with respect to cerebral infarction were selected using logistic regression analysis with the Wald's forward selection approach. The rules to identify the complications of cerebral infarction were obtained by using the association rule mining (ARM) approach. RESULTS: We observed that 4 independent factors, namely, age, hypertension, initial electrocardiographic rhythm, and initial echocardiographic left atrial dimension (LAD), were strong predictors of cerebral infarction in patients with AF. After the application of ARM, we obtained 4 useful rules to identify complications of cerebral infarction: age (>63 years) and hypertension (Yes) and initial ECG rhythm (AF) and initial Echo LAD (>4.06 cm); age (>63 years) and hypertension (Yes) and initial Echo LAD (>4.06 cm); hypertension (Yes) and initial ECG rhythm (AF) and initial Echo LAD (>4.06 cm); age (>63 years) and hypertension (Yes) and initial ECG rhythm (AF). CONCLUSIONS: Among the induced rules, 3 factors (the initial ECG rhythm [i.e., AF], initial Echo LAD, and age) were strongly associated with each other.

Support Vector Regression-based Model to Analyze Prognosis of Infants with Congenital Muscular Torticollis / 대한의료정보학회지

OBJECTIVES: Congenital muscular torticollis, a common disorder that refers to the shortening of the sternocleidomastoid in infants, is sensitive to correction through physical therapy when treated early. If physical therapy is unsuccessful, surgery is required. In this study, we developed a support vector regression model for congenital muscular torticollis to investigate the prognosis of the physical therapy treatent in infants. METHODS: Fifty-nine infants with congenital muscular torticollis received physical therapy until the degree of neck tilt was less than 5degrees. After treatment, the mass diameter was reevaluated. Based on the data, a support vector regression model was applied to predict the prognoses. RESULTS: 10-, 20-, and 50-fold cross-tabulation analyses for the proposed model were conducted based on support vector regression and conventional multi-regression method based on least squares. The proposed methodbased on support vector regression was robust and enabled the effective analysis of even a small amount of data containing outliers. CONCLUSIONS: The developed support vector regression model is an effective prognostic tool for infants with congenital muscular torticollis who receive physical therapy.

Implementation of Chest X-ray Observation Report Entry System / 대한의료정보학회지

OBJECTIVES: X-rays are widely used in medical examinations. In particular, chest X-rays are the most frequent imaging test. However, observations are usually recorded in a free-text format. Therefore, it is difficult to standardize the information provided to construct a database for the sharing of clinical data. Here, we describe a simple X-ray observation entry system that can interlock with an electronic medical record system. METHODS: We investigated common diagnosis indices. Based on the indices, we have designed an entry system which consists of 5 parts: 1) patient lists, 2) image selection, 3) diagnosis result entry, 4) image view, and 5) main menu. The X-ray observation results can be extracted in an Excel format. RESULTS: The usefulness of the proposed system was assessed in a study using over 500 patients' chest X-ray images. The data was readily extracted in a format that allowed convenient assessment. CONCLUSIONS: We proposed the chest X-ray observation entry system. The proposed X-ray observation system, which can be linked with an electronic medical record system, allows easy extraction of standardized clinical information to construct a database. However, the proposed entry system is limited to chest X-rays and it is impossible to interpret the semantic information. Therefore, further research into domains using other interpretation methods is required.

A New Method for Non-Invasive Measurement of Skin in the Low Frequency Range / 대한의료정보학회지

OBJECTIVES: The purpose of our study was to estimate skin structure and conductivity distribution in a cross section of local tissue using non-invasive measurement of impedance data. The present study was designed to evaluate the efficiency of skin depth information through computer simulations. The multilayer tissue model was composed of epidermis, dermis tissues, and subcutaneous. METHODS: In this study, electrical characteristics of skin models were used for conductivity of 0.13 S/m, 0.26 S/m, 0.52 S/m, permittivity of 94,000 F/m, and a frequency of 200 Hz. The effect of the new method was assessed by computer simulations using three-electrode methods. A non-invasive electrical impedance method has been developed for analysis using computer simulation and a skin electrical model with low frequency range. Using the three-electrode method differences through the potentials between measurement electrodes and reference electrodes can be easily detected. The Cole electrical impedance model, which is better suited for skin was used in this study. RESULTS: In this study, experiments using three-electrode methods were described by computer simulation based on a simple model. This electrical impedance model was fitted and developed in comparison with our model for measurement of skin impedance. CONCLUSIONS: The proposed electrical model for skin is suitable for use in interpretation of changes in impedance characterization of the skin. Using the computer simulation method, information on skin impedance depth can be more accurately developed and predicted.

Variable Threshold based Feature Selection using Spatial Distribution of Data / 대한의료정보학회지

OBJECTIVE: In processing high dimensional clinical data, choosing the optimal subset of features is important, not only for reduce the computational complexity but also to improve the value of the model constructed from the given data. This study proposes an efficient feature selection method with a variable threshold. METHODS: In the proposed method, the spatial distribution of labeled data, which has non-redundant attribute values in the overlapping regions, was used to evaluate the degree of intra-class separation, and the weighted average of the redundant attribute values were used to select the cut-off value of each feature. RESULTS: The effectiveness of the proposed method was demonstrated by comparing the experimental results for the dyspnea patients' dataset with 11 features selected from 55 features by clinical experts with those obtained using seven other classification methods. CONCLUSION: The proposed method can work well for clinical data mining and pattern classification applications.