• Clinical and Experimental Pediatrics
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• v.51 no.6
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• pp.584-596
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• 2008

Purpose : This study was conducted to investigate treatment compliance and related factors in pediatric patients. Methods : Three hundred and fifty-five patients diagnosed with various acute diseases at a teaching hospital or clinic in October 2003 were enrolled. Data were analyzed using the Health Belief Model, which includes items on self-efficacy and family assistance. Results : The study found that 62.9% of pediatric patients adhered faithfully to agreed-upon hospital revisits, 41.6% complied with dose timings instructions, 65.8% precisely took medication, and 27.2% complied with all of these requirements. According to ${\chi}^2$ test analysis, the factors found to be related to therapeutic compliance (the taking of medicines requested) were; susceptibility, severity, benefit, barriers, mother's self-efficacy, and family assistance (P<.05). Multiple logistic analysis and path analysis showed that susceptibility, severity, barriers, and mother's self-efficacy were related to therapeutic compliance (P<.05). Moreover, mother's self-efficacy was identified as the most important factor. Conclusion : To improve therapeutic compliance among pediatric patients, parental education is necessary, and a health care professional must take a thorough history of how the medication was taken before it is assumed that treatment failure is attributable to the medication prescribed. Furthermore, the type of device recommended for dosing should be determined by clinicians. In addition, it is important that pediatric medications be discussed in relation to their palatability and internal acceptability.

• Journal of Nutrition and Health
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• v.42 no.5
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• pp.486-495
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• 2009

The purpose of this study was to analyze the performance evaluation index for a salt reduction project. Questionnaires were developed in order to investigate salt reduction programs nationwide. The evaluation index and programs were analyzed through the case study of a salt reduction program in public health centers. The validity of the salt reduction program's evaluation index was determined based on study of the Delphi survey and on discussion with nutrition and health care professionals. The Delphi survey showed that daily salt intake was the most valid nutritional evaluation index. Stroke mortality and stomach cancer mortality were good health care evaluation indexes. The method for measuring salt intake that had the greatest validity was a 24-hour urine collection. However, 24-hour urine collection had the lowest score for ease of performance. The combined scores of validity and ease of performance showed that the survey method for dietary attitude and dietary behavior, dietary frequency analysis (DFQ 15), and a salty taste assessment, in that order, were proper methods. The high reliability of the salty taste assessment indicated that the percentage of the population that exhibits proper salt intake (2,000 mg sodium or less daily) and the percentage of the population that consumes low-salt diets as nutritional evaluation indexes also will be helpful to evaluate performance of salt reduction programs.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Tuberculosis and Respiratory Diseases
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• v.47 no.3
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• pp.356-364
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• 1999

Backgrounds: Previous reports have revealed a high morbidity and mortality in fatal asthma patients, especially those treated in the medical intensive care unit(MICU). But it has not been well known about the predictable factors for the mortality of fatal asthma(F A) with acute respiratory failure. In order to define the predictable factors for the mortality of FA at the admission to MICU, we analyzed the relationship between the clinical parameters and the prognosis of FA patients. Methods: A retrospective analysis of all medical records of 59 patients who had admitted for FA to MICU at a tertiary care MICU from January 1992 to March 1997 was performed. Results: Over all mortality rate was 32.2% and 43 patients were mechanically ventilated. In uni-variate analysis, the death group had significantly older age ($66.2{\pm}10.5$ vs. $51.0{\pm}18.8$ year), lower FVC($59.2{\pm}21.1$ vs. $77.6{\pm}23.3%$) and lower $FEV_1$($41.4{\pm}18.8$ vs. $61.l{\pm}23.30%$), and longer total ventilation time ($255.0{\pm}236.3$ vs. $98.1{\pm}120.4$ hour) (p<0.05) compared with the survival group (PFT: best value of recent 1 year). At MICU admission, there were no significant differences in vital signs, $PaCO_2$, $PaO_2/FiO_2$, and $AaDO_2$, in both groups. However, on the second day of MICU, the death group had significantly more rapid pulse rate ($121.6{\pm}22.3$ vs. $105.2{\pm}19.4$ rate/min), elevated $PaCO_2$ ($50.1{\pm}16.5$ vs. $41.8{\pm}12.2 mm Hg$), lower $PaO_2/FiO_2$, ($160.8{\pm}59.8$ vs. $256.6{\pm}78.3 mm Hg$), higher $AaDO_2$ ($181.5{\pm}79.7$ vs. $98.6{\pm}47.9 mm Hg$), and higher APACHE III score ($57.6{\pm}21.1$ vs. $20.3{\pm}13.2$) than survival group (p<0.05). The death group had more frequently associated with pneumonia and anoxic brain damage at admission, and had more frequently developed sepsis during disease progression than the survival group (p<0.05). Multi-variate analysis using APACHE III score and $PaO_2/FiO_2$, ratio on first and second day, age, sex, and pneumonia combined at admission revealed that APACHE III score (40) and $PaO_2/FiO_2$ ratio (<200) on second day were regarded as predictive factors for the mortality of fatal asthma (p<0.05). Conclusions: APACHE III score ($\geq$40) and $PaO_2/FiO_2$ ratio (<200) on the second day of MICU, which might reflect the response of treatment, rather than initially presented clinical parameters would be more important predictable factors of mortality in patients with FA.