• Journal of Preventive Medicine and Public Health
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• v.31 no.4 s.63
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• pp.751-769
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• 1998

This study was conducted to assess the attitude of pregnant women toward delivery method, understanding of the reason for determining her own delivery method, participation in decision-making process and satisfaction with delivery method after labor. Study subjects were 693 pregnant women who had visited obstetric clinic for prenatal care in the last month of pregnancy in one general hospital and one obstetrics-gynecology specialty hospital in Taegu city from February 1 to March 31 in 1998. A questionnaire was administered before and after labor and a telephone interview was done one month after labor. Proportion of women who had health education and/or counselling about delivery method during prenatal care was 24.0% and this proportion was higher for women who had previous c-section(35.5%) than others. Women thought vaginal delivery is better than c-section for both maternal and baby's health regardless of previous delivery method. About 90% of primipara and multiparous women who had previous vaginal delivery wanted vaginal delivery for the index birth, while 85.6% of multiparous women who had previous c-section wanted repeat c-section. Reasons for choosing c-section in pregnant women who preferred vaginal delivery before labor were recommendation of doctors(81.9%), recommendation of husband (0.8%), agreement between doctor and pregnant woman(4.7%), and mother's demand (12.6%). Reasons for choosing vaginal delivery were mother's demand(30.6%) and no indication for c-section(67.2%). Reasons for choosing c-section in pregnant women who preferred c-section before labor were recommendation of doctors(76.2%), mother's demand(20.0%), recommendation of husband(1.3%), and agreement between doctor and pregnant woman(2.5%). Of the pregnant women who had c-section, by doctor's recommendation, the proportion of women who had heard detailed explanation about reason for c-section by doctor was 55.1%. Mother's statement about the reason for c-section was consistent with the medical record in 75.9% . However, over 5% points disparities were shown between mother's statement and medical record in cases of the repeat c-section and mother's demand. In primipara and multiparous women who had previous vaginal delivery, the delivery method for index birth had statistically significant association with the preference of delivery method before labor(p<0.05). All of the women who had previous c-section had delivered the index baby by c-section. Among mothers who had delivered the index baby vaginally, 84.9% of them were satisfied with their delivery method immediately after labor and 85.1% at 1 month after labor. However, mothers who had c-section stated that they are satisfied with c-section in 44.6% immediately after labor and 42.0% at 1 month after labor. Preferred delivery method for the next birth had statistically significant association with delivery method for the index birth both immediately after labor and in 1 month after labor. The proportion of mothers who prefer vaginal delivery for the next birth increased with the degree of satisfaction with the vaginal delivery for the index birth but the proportion of mothers who prefer c-section for the next birth was high and they did not change significantly with the degree of satisfaction with the c-section for the index birth. These results suggest that the current high technology-based, physician-centered prenatal and partritional cares need to be reoriented to the basic preventive and promotive technology-based, and mother-fetus-centered care. It is also suggested that active involvement of pregnant woman in decision-making process for the delivery method will increase the rate of vaginal birth after c-section and decrease c-section rate and improve the degree of maternal satisfaction after delivery.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.