• Title/Summary/Keyword: Effective learning

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Application of spatiotemporal transformer model to improve prediction performance of particulate matter concentration (미세먼지 예측 성능 개선을 위한 시공간 트랜스포머 모델의 적용)

  • Kim, Youngkwang;Kim, Bokju;Ahn, SungMahn
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.329-352
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    • 2022
  • It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

Strategic Issues in Managing Complexity in NPD Projects (신제품개발 과정의 복잡성에 대한 주요 연구과제)

  • Kim, Jongbae
    • Asia Marketing Journal
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    • v.7 no.3
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    • pp.53-76
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    • 2005
  • With rapid technological and market change, new product development (NPD) complexity is a significant issue that organizations continually face in their development projects. There are numerous factors, which cause development projects to become increasingly costly & complex. A product is more likely to be successfully developed and marketed when the complexity inherent in NPD projects is clearly understood and carefully managed. Based upon the previous studies, this study examines the nature and importance of complexity in developing new products and then identifies several issues in managing complexity. Issues considered include: definition of complexity : consequences of complexity; and methods for managing complexity in NPD projects. To achieve high performance in managing complexity in development projects, these issues need to be addressed, for example: A. Complexity inherent in NPD projects is multi-faceted and multidimensional. What factors need to be considered in defining and/or measuring complexity in a development project? For example, is it sufficient if complexity is defined only from a technological perspective, or is it more desirable to consider the entire array of complexity sources which NPD teams with different functions (e.g., marketing, R&D, manufacturing, etc.) face in the development process? Moreover, is it sufficient if complexity is measured only once during a development project, or is it more effective and useful to trace complexity changes over the entire development life cycle? B. Complexity inherent in a project can have negative as well as positive influences on NPD performance. Thus, which complexity impacts are usually considered negative and which are positive? Project complexity also can affect the entire organization. Any complexity could be better assessed in broader and longer perspective. What are some ways in which the long-term impact of complexity on an organization can be assessed and managed? C. Based upon previous studies, several approaches for managing complexity are derived. What are the weaknesses & strengths of each approach? Is there a desirable hierarchy or order among these approaches when more than one approach is used? Are there differences in the outcomes according to industry and product types (incremental or radical)? Answers to these and other questions can help organizations effectively manage the complexity inherent in most development projects. Complexity is worthy of additional attention from researchers and practitioners alike. Large-scale empirical investigations, jointly conducted by researchers and practitioners, will help gain useful insights into understanding and managing complexity. Those organizations that can accurately identify, assess, and manage the complexity inherent in projects are likely to gain important competitive advantages.

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Prediction of Spring Flowering Timing in Forested Area in 2023 (산림지역에서의 2023년 봄철 꽃나무 개화시기 예측)

  • Jihee Seo;Sukyung Kim;Hyun Seok Kim;Junghwa Chun;Myoungsoo Won;Keunchang Jang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.4
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    • pp.427-435
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    • 2023
  • Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R2. The models with applied correction coefficients achieve R2 values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

Ship Detection from SAR Images Using YOLO: Model Constructions and Accuracy Characteristics According to Polarization (YOLO를 이용한 SAR 영상의 선박 객체 탐지: 편파별 모델 구성과 정확도 특성 분석)

  • Yungyo Im;Youjeong Youn;Jonggu Kang;Seoyeon Kim;Yemin Jeong;Soyeon Choi;Youngmin Seo;Yangwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.997-1008
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    • 2023
  • Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

Secondary School Students' Images of Doing-Science-Well (과학을 잘 하는 모습에 대한 고등학생의 인식)

  • Lee, Wang-Suk;Kim, Hee-Kyong;Song, Jin-Woong
    • Journal of The Korean Association For Science Education
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    • v.28 no.1
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    • pp.1-14
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    • 2008
  • The image of science is one of the recurrent topics in science education research. In particular, we believe that students' images of Doing-Science-Well could be used for identifying not only students' perceived goals of science learning, but also practical guidelines of effective science teaching. In this study, the students' images of Doing-Science-Well were investigated with the following two research questions: (i) what are student's images of Doing-Science-Well?; (ii) in what contexts do students perceive that someone is doing science well? Thirty seven students in a high school in Seoul, Korea were asked to write their personal experiences by which they realized that someone was doing science well. The main results of the study are the following: Firstly, the images of Doing-Science-Well could be categorized into 'Einstein type', 'Socrates type', 'MacGyver type' and six more types. Secondly, with regard to contexts, students tended to realize that somebody is doing science well in terms of two kinds of contexts: 4 physical contexts and 6 psychological contexts. The findings led us to develop a frame of judging Doing-Science-Well, which combines the types and two kinds of contexts. The frame illustrates the multiplicity of the images of Doing-Science-Well.

Strategy for Store Management Using SOM Based on RFM (RFM 기반 SOM을 이용한 매장관리 전략 도출)

  • Jeong, Yoon Jeong;Choi, Il Young;Kim, Jae Kyeong;Choi, Ju Choel
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.93-112
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    • 2015
  • Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

A Study on the Application of Outlier Analysis for Fraud Detection: Focused on Transactions of Auction Exception Agricultural Products (부정 탐지를 위한 이상치 분석 활용방안 연구 : 농수산 상장예외품목 거래를 대상으로)

  • Kim, Dongsung;Kim, Kitae;Kim, Jongwoo;Park, Steve
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.93-108
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    • 2014
  • To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

Multi-Dimensional Analysis Method of Product Reviews for Market Insight (마켓 인사이트를 위한 상품 리뷰의 다차원 분석 방안)

  • Park, Jeong Hyun;Lee, Seo Ho;Lim, Gyu Jin;Yeo, Un Yeong;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.57-78
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    • 2020
  • With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

A Study on Hoslital Nurses' Preferred Duty Shift and Duty Hours (병원 간호사의 선호근무시간대에 관한 연구)

  • Lee, Gyeong-Sik;Jeong, Geum-Hui
    • The Korean Nurse
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    • v.36 no.1
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    • pp.77-96
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    • 1997
  • The duty shifts of hospital nurses not only affect nurses' physical and mental health but also present various personnel management problems which often result in high turnover rates. In this context a study was carried out from October to November 1995 for a period of two months to find out the status of hospital nurses' duty shift patterns, and preferred duty hours and fixed duty shifts. The study population was 867 RNs working in five general hospitals located in Seoul and its vicinity. The questionnaire developed by the writer was used for data collection. The response rate was 85.9 percent or 745 returns. The SAS program was used for data analysis with the computation of frequencies, percentages and Chi square test. The findings of the study are as follows: 1. General characteristics of the study population: 56 percent of respondents was (25 years group and 76.5 percent were "single": the predominant proportion of respondents was junior nursing college graduates(92.2%) and have less than 5 years nursing experience in hospitals(65.5%). For their future working plan in nursing profession, nearly 50% responded as uncertain The reasons given for their career plan was predominantly 'personal growth and development' rather than financial reasons. 2. The interval for rotations of duty stations was found to be mostly irregular(56.4%) while others reported as weekly(16.1%), monthly(12.9%), and fixed terms(4.6%). 3. The main problems related to duty shifts particularly the evening and night duty nurses reported were "not enough time for the family, " "afraid of security problems after the work when returning home late at night." and "lack of leisure time". "problems in physical and physiological adjustment." "problems in family life." "lack of time for interactions with fellow nurses" etc. 4. The forty percent of respondents reported to have '1-2 times' of duty shift rotations while all others reported that '0 time'. '2-3 times'. 'more than 3 times' etc. which suggest the irregularity in duty shift rotations. 5. The majority(62.8%) of study population found to favor the rotating system of duty stations. The reasons for favoring the rotation system were: the opportunity for "learning new things and personal development." "better human relations are possible. "better understanding in various duty stations." "changes in monotonous routine job" etc. The proportion of those disfavor the rotating 'system was 34.7 percent. giving the reasons of"it impedes development of specialization." "poor job performances." "stress factors" etc. Furthermore. respondents made the following comments in relation to the rotation of duty stations: the nurses should be given the opportunity to participate in the. decision making process: personal interest and aptitudes should be considered: regular intervals for the rotations or it should be planned in advance. etc. 6. For the future career plan. the older. married group with longer nursing experiences appeared to think the nursing as their lifetime career more likely than the younger. single group with shorter nursing experiences ($x^2=61.19.{\;}p=.000;{\;}x^2=41.55.{\;}p=.000$). The reason given for their future career plan regardless of length of future service, was predominantly "personal growth and development" rather than financial reasons. For further analysis, the group those with the shorter career plan appeared to claim "financial reasons" for their future career more readily than the group who consider the nursing job as their lifetime career$(x^2$= 11.73, p=.003) did. This finding suggests the need for careful .considerations in personnel management of nursing administration particularly when dealing with the nurses' career development. The majority of respondents preferred the fixed day shift. However, further analysis of those preferred evening shift by age and civil status, "< 25 years group"(15.1%) and "single group"(13.2) were more likely to favor the fixed evening shift than > 25 years(6.4%) and married(4.8%)groups. This differences were statistically significant ($x^2=14.54, {\;}p=.000;{\;}x^2=8.75, {\;}p=.003$). 7. A great majority of respondents(86.9% or n=647) found to prefer the day shifts. When the four different types of duty shifts(Types A. B. C, D) were presented, 55.0 percent of total respondents preferred the A type or the existing one followed by D type(22.7%). B type(12.4%) and C type(8.2%). 8. When the condition of monetary incentives for the evening(20% of salary) and night shifts(40% of. salary) of the existing duty type was presented. again the day shift appeared to be the most preferred one although the rate was slightly lower(66.4% against 86.9%). In the case of evening shift, with the same incentive, the preference rates for evening and night shifts increased from 11.0 to 22.4 percent and from 0.5 to 3.0 percent respectively. When the age variable was controlled. < 25 yrs group showed higher rates(31.6%. 4.8%) than those of > 25 yrs group(15.5%. 1.3%) respectively preferring the evening and night shifts(p=.000). The civil status also seemed to operate on the preferences of the duty shifts as the single group showed lower rate(69.0%) for day duty against 83. 6% of the married group. and higher rates for evening and night duties(27.2%. 15.1%) respectively against those of the married group(3.8%. 1.8%) while a higher proportion of the married group(83. 6%) preferred the day duties than the single group(69.0%). These differences were found to be statistically all significant(p=.001). 9. The findings on preferences of three different types of fixed duty hours namely, B, C. and D(with additional monetary incentives) are as follows in order of preference: B type(12hrs a day, 3days a wk): day shift(64.1%), evening shift(26.1%). night shift(6.5%) C type(12hrs a day. 4days a wk) : evening shift(49.2%). day shift(32.8%), night shift(11.5%) D type(10hrs a day. 4days a wk): showed the similar trend as B type. The findings of higher preferences on the evening and night duties when the incentives are given. as shown above, suggest the need for the introductions of different patterns of duty hours and incentive measures in order to overcome the difficulties in rostering the nursing duties. However, the interpretation of the above data, particularly the C type, needs cautions as the total number of respondents is very small(n=61). It requires further in-depth study. In conclusion. it seemed to suggest that the patterns of nurses duty hours and shifts in the most hospitals in the country have neither been tried for different duty types nor been flexible. The stereotype rostering system of three shifts and insensitiveness for personal life aspect of nurses seemed to be prevailing. This study seems to support that irregular and frequent rotations of duty shifts may be contributing factors for most nurses' maladjustment problems in physical and mental health. personal and family life which eventually may result in high turnover rates. In order to overcome the increasing problems in personnel management of hospital nurses particularly in rostering of evening and night duty shifts, which may related to eventual high turnover rates, the findings of this study strongly suggest the need for an introduction of new rostering systems including fixed duties and appropriate incentive measures for evenings and nights which the most nurses want to avoid, In considering the nursing care of inpatients is the round-the clock business. the practice of the nursing duty shift system is inevitable. In this context, based on the findings of this study. the following are recommended: 1. The further in-depth studies on duty shifts and hours need to be undertaken for the development of appropriate and effective rostering systems for hospital nurses. 2. An introduction of appropriate incentive measures for evening and night duty shifts along with organizational considerations such as the trials for preferred duty time bands, duty hours, and fixed duty shifts should be considered if good quality of care for the patients be maintained for the round the clock. This may require an initiation of systematic research and development activities in the field of hospital nursing administration as a part of permanent system in the hospital. 3. Planned and regular intervals, orientation and training, and professional and personal growth should be considered for the rotation of different duty stations or units. 4. In considering the higher degree of preferences in the duty type of "10hours a day, 4days a week" shown in this study, it would be worthwhile to undertake the R&D type studies in large hospital settings.

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An experimental study on the impact of an agreement on the means to achieve nursing goals in the early postpartum period of primiparous mothers and enhance their self-confidence and satisfaction in maternal role performance (산욕초기 초산모의 간호목표달성방번 합의가 어머니 역할수행에 대한 자신감 및 만족도에 미치는 영향에 관한 실험적 연구)

  • 이영은
    • Journal of Korean Academy of Nursing
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    • v.22 no.1
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    • pp.81-115
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    • 1992
  • The problem addressed by this study was to determine the effect of nurse - patient agreement on the means to achieve nursing goals in the early postpartum period of primiparous mothers. It was hypothesized that the experimental treatment would result in hegher self-confidence and satisfaction in maternal role performance. This purpose was to contribute to the planning of nursing care to enhance self- confidence and satisfaction in maternal role performance and to the development of relevant nursing theory. Especially, the early postpartum period is crucial toward in recovery from childbirth and attainment of the maternal role. Maternal role attaintment is a complex social and cognitive process of stimulus -response accomplished by learning. Most women attain the maternal role sucessfully. But, some primiparous mothers experience difficultites in attainment of the maternal role due to lack of experience and knowledge. Self-confidence and satisfaction in maternal role performance are important factors in attainment and adjustment to the maternal role (Mercer, 1981a, 1981b ; Lederman, Weigarten, and Lederman, 1981 :Bobak and Jensen, 1985). Nursing is defined as behaviors of nurses add patients that attain nursing goals through action, reaction, interaction, and transaction. For attainment of nursing goals, active participating transactions must occur by agreement on the means to achieve those goals through nurse -patient mutual goal setting and establishment of their active relationships(King, 1981, Ha, 1977). Based on King's theory of goal attainment (1981), this stuy was planned as a non-equivalent control group, non -synchronized quasi -experimental design using agreement on the means to achieve nursing goals in early postpartum as the experimental treatment. The data were collected from July 20 to Sep. 1, 1991 by questionnaires with 60 primiparous mothers planing to breast feed after normal deliveries at W hospital in Pusan, Korea. The subjects were divided into a control group(conventional group) -those admitted from July 20 to Aug. 12, and an experimental group(agreement group) - those admitted from Aug. 13 to Sep. 1. The instument for agreement on the means to nursing goals in the early postpartum period included five steps - identification of disturbances of problems through action, reaction, and interaction with primiparous mothers : mutual early postpartal nursing goal setting : exploration of the means to achieve goals ; agreement on the means (self- care, ealry maternal -infant contact, performance of mothering behavior, and communicating about the infant's behavior and health condition) : implementation of the means. This instrument was developed on the basis of King's elements that lead to transactions in nurse-patient interactions. Lederman et al's (1981) scale for Confidence in ability to cope with tasks of motherhood and Lederman et al's(1981) scale for Mother's satisfaction with motherhood and infant care were used to measure self-confidence and satisfaction in maternal role performance ·with the subjects immediately after admission and on the day of discharge. Self-care performance in the experimental group was measured by self -evaluation tool developed by the investigator from the literature concerned. The tools to measure Pelf-confidence and satisfaction in maternal role performance, and the tool to measure self-evaluation of self-care performance were tested for internal reliability. Cronbach's Alphas were 0.94, 0.94, and 0.63. The data were analysed by using in S.P.S.S. computerized program and included percentage, x²-test, t-test, ANOVA, and Pearson Correlation Coefficient. The conclusions obtained from this study are summerized as follows : 1. The degree of self-confidence in maternal role performance of the total subjects group measured before the experimental treatment was above average with a mean score of 2.77(range 2.14-3.64). Out of 14 items, those with relatively high mean scores were ‘I would like to be a better mother than I am’(3.95), and ‘I have my doubts about whether I am a good mother’(2.87). Those with low mean scores were ‘I know that my baby wants most of the times’(2.28), ‘When the baby cries, I can tell what she /he wants’(2.37), and ‘I have confidence in my ability to care for the baby’(2;50). That is, the self - confidence of Primiparous mothers was considerably high in mothering, but rather low in activities concerning the infant care and understanding of the infant behavior. The degree of satisfaction in maternal role performance of the total subjects group measured before the experimental treatment was high with a mean score of 3.18(range 1.92-3.92). Out of 13 items, those with relatively high mean scores were ‘I am glad 1 had this baby now’(3.75), ‘I play with the baby between feedings when s/he is awake and quiet’(3.67), and ‘I enjoy being a mother’(3.27). Those with low mean scores were ‘I am upset about having too many responsibilities as a mother’(2.78), ‘It bothers me to get up for the baby at night’(2.82), and ‘I get annoyed if the baby frequently interrupts my activities’.(2.82), That is, the satisfaction of primiparous mothers was considerably high in mothering and infant care, but rather low in restraints in time or on the mother's self accomplishment and development. 2. Agreement on the means to achieve nursing goals in the early postpartum period included process of mutual goal setting, exploration of the means to achieve goals, and ahreement in concert means to achieve goals based on the mothers' condition, concerns, self-perception of the nurse - patient interactions. In the process of agreement, there was agreement that the means to achieve goals should be through trust and establishment of active relationships with the nurse through identification of problems according to planned nursing goals and active interaction, such as explanations, teaching, changing of opinions, acceptance or rejection of explanations, and proposing of questions. Therefore agreement on the means to achieve nursing goals in the early postpartum period appears to be an effective nursing intervention for primiparous mothers. 3. The degree of self- confidence in maternal role performance of the exprimental group was higher than that of the control group(t=3.95, p<0.01). Out of 14 items, those with higher score in the experimental group were ‘I would like to be a better mother than I am’(t=1.93, p<0.05), ‘I know that my baby wants most of the times’(t=2.75, p<0.01), ‘When the baby cries, 1 can tell what she/he wants’(t=2.10, p<0.05), ‘I have confidence in my ability to care for the baby’(t=3.72, p<0.01), ‘I trust my own judement in deciding how to care for the baby’(t=1.96, p<0.05), ‘I feel that I know my baby and what to do for him /her’(t=2.44, p<0.01), ‘I am concerned about being able to meet the baby's needs’(t=2.87, p<0.01), ‘I know what my baby likes and dislikes’(t=3.26, p<0.01), ‘I don't know to care for the baby as well as I should’(t=2.07, p<0.05), and ‘I am unsure about whether I give enough attention to the baby’(t=3.04, p<0.01), That is, the degree of self-confidence in mothering, activities concerning infant care, and understanding of infant behavior of the experimental group was higher than that of the control group. Therefore, the first hypothesis, that the degree of self-confidence in maternal role performance of the experimental group would be higher than that of the control group, was supported(t=3.95, p<0.01). 4. The degree of satisfaction in the maternal role performance of the exprimental group was higer than that or the control group(t=2.31, p<0.05). Out of 13 items, those with higher score in the experimental group were ‘I am glad I had this baby now’(t=2.29, p<0.05), ‘I enjoy taking care of the baby’(t=2.4g, p<0.01), ‘It is boring for me to care for the baby and do the same thing over and over’(t=2.87, P<0.01), ‘I am unhappy with the amount of time I have for activities other than childcare’(t=2.51, p<0.01), and ‘When bathing and diapering the baby, I would like to be doing something else’(t=2.43, p<0.01). That is, the degree of satisfaction in mothering, infant care, and restraints in time of on the mother's self accomplishment and development in the experimental group was higher than that of the control group. Therefore, the second hypothesis, that the degree of satisfaction in maternal role performance of the experimental group would be higher than that of the control group, was supported(t=2.31, p<0.05). 5. The third hypothesis, that the higher the degree of satisfaction in materenal role performance, the higher the degree of self-confidence in materenal role performance in the experimental group, was supported (r=0.57, p<0.01)

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