74 research outputs found

    Focusing on Bilateral Aid from 1991 to 2020

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ตญ์ œ๋Œ€ํ•™์› ๊ตญ์ œํ•™๊ณผ(๊ตญ์ œํ˜‘๋ ฅ์ „๊ณต), 2023. 2. ์€๊ธฐ์ˆ˜.This paper studies the crucial motivations of Korea ODA, concentrating on the bilateral aid granted by KOICA during the last 30 years. The empirical research analyzes major determinants- political, economic, and humanitarian factors-to see what and how these factors have affected Koreas aid allocation to recipients countries through fixed-effects regression model. Based on traditional International Relations theory, the result showed that both political, economic, and humanitarian factor, significantly affect how Korean government allocates ODA. Moreover, it was found that Korea allocates more to countries that will bring more economic incentives. When it comes to humanitarian motives, it showed that whether the recipient country had lower GNI per capita also positively affected the amount of ODA distributed to. The result on political motive turned out to be negative and this contrasts previous studies on ODA allocation determinants. The study sheds light on how Korea, becoming member of the OECD DAC in 2010, has granted aid to recipient countries for the last 30 years.๋ณธ ๋…ผ๋ฌธ์€ ์ง€๋‚œ 30๋…„๊ฐ„ ํ•œ๊ตญ๊ตญ์ œํ˜‘๋ ฅ๋‹จ(KOICA)์ด ์ง€์›ํ•œ ์–‘์ž์›์กฐ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ํ•œ๊ตญ ODA์˜ ์ฃผ์š” ๊ฒฐ์ •์š”์ธ์„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ์‹ค์ฆ์—ฐ๊ตฌ๋Š” ODA ๋ฐฐ๋ถ„์˜ ์ฃผ์š” ๊ฒฐ์ •์š”์ธ- ์ •์น˜์ , ๊ฒฝ์ œ์ , ์ธ๋„์  ์š”์ธ์„ ๋ถ„์„ํ•˜์—ฌ ์ด๋Ÿฌํ•œ ์š”์ธ๋“ค์ด ํ•œ๊ตญ์˜ ์ง€์›๋Œ€์ƒ๊ตญ ๋ฐฐ๋ถ„์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์ณค๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ๊ทธ๋™์•ˆ์˜ ์ „ํ†ต์ ์ธ ๊ตญ์ œ๊ด€๊ณ„ ์ด๋ก ์— ๋”ฐ๋ฅด๋ฉด ๊ฒฝ์ œ์ , ์ธ๋„์ , ์ •์น˜์  ์š”์ธ์€ ์œ ์˜๋ฏธํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ณ ์ •ํšจ๊ณผ ๋ชจ๋ธ์„ ํ†ตํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ, ํ•œ๊ตญ์€ ๋” ๋งŽ์€ ๊ฒฝ์ œ์  ์ธ์„ผํ‹ฐ๋ธŒ๋ฅผ ๊ฐ€์ ธ์˜ฌ ๊ตญ๊ฐ€๋“ค์— ๋” ๋งŽ์ด ํ• ๋‹นํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ฐํ˜€์กŒ๋‹ค. ๋˜ํ•œ ์ธ๋„์ฃผ์˜์  ๋™๊ธฐ์— ์žˆ์–ด์„œ๋Š” ์ˆ˜๋ น๊ตญ์˜ 1์ธ๋‹น GNI๊ฐ€ ๋” ๋‚ฎ์•˜๋Š”์ง€ ์—ฌ๋ถ€๊ฐ€ ODA์˜ ๋ถ„๋ฐฐ๋Ÿ‰์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ •์น˜์  ๋™๊ธฐ์— ๋Œ€ํ•œ ๊ฒฐ๊ณผ๋Š” 2011๋…„๋ถ€ํ„ฐ 2020๋…„๊นŒ์ง€ ๋ฌด์˜๋ฏธํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚˜ ODA ํ• ๋‹น ๊ฒฐ์ •์š”์ธ์— ๋Œ€ํ•œ ์ด์ „์˜ ์—ฐ๊ตฌ์™€ ๋Œ€์กฐ๋˜์–ด ๋ˆˆ์—ฌ๊ฒจ ๋ณผ๋งŒํ•˜๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” 2010๋…„ OECD DAC ํšŒ์›๊ตญ์ด ๋œ ํ•œ๊ตญ์ด ์–ด๋–ป๊ฒŒ 30๋…„ ๋™์•ˆ ๊ฐ๊ตญ์— ์›์กฐ๋ฅผ ์ œ๊ณตํ•ด์™”๋Š”์ง€๋ฅผ ์žฌ์กฐ๋ช…ํ•œ๋‹ค.Introduction 1 Study Background 1 Purpose of the Research 3 Literature Review 4 Definition of ODA 6 Korea ODA History 6 Korea ODA Trend 8 Current Status of Korea ODA 9 Studies on ODA motives 10 Studies on Korea ODA characteristics 11 International Relations Theoreis 13 Determinants of Korea's ODA Allocation 15 Political Motive 15 Economic Motive 17 Humanitarian Motive 18 Empirical Analysis 20 Methodology 20 Data and Variables 21 Hypothesis 25 Empirical Results 26 Conclusion 31 Implications 31 Limitations 32 References 34 Appendix 38 ๊ตญ๋ฌธ์ดˆ๋ก 42์„

    ํ”ผ๋ถ€ ์ง„ํ”ผ ์„ฌ์œ ์•„์„ธํฌ์—์„œ ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์— ์˜ํ•œ Biglycan๊ณผ Decorin ๋ฐœํ˜„ ์ฆ๊ฐ€

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜๊ณผํ•™๊ณผ, 2019. 2. ์ •์ง„ํ˜ธ .Proteoglycans (PGs) are a family of glycosaminoglycan-conjugated proteins. Biglycan and biglycan , members of small leucine repeat-rich PGs, are ones of skin-abundant PGs, and their amount decreases in both intrinsically aged and photoaged skin. However, the regulatory mechanisms of biglycan and decorin expressions have not been revealed clearly. Insulin-like growth factor 1 (IGF-1) is considered as an important factor in biological systems such as cell survival, growth, and apoptosis. As time goes by, it is very well known that secretion and synthesis of IGF-1 decline continuously. Therefore, I examined whether IGF-1 has effects on biglycan and decorin production. Treatment with IGF-1 increased protein levels of biglycan and deocrin in primary cultured human dermal fibroblasts, but did not increase their mRNA levels. An IGF-1R blocker, NVP-AEW541 inhibited IGF-1 induced biglycan and decorin protein expressions. However, an MEK inhibitor, U0126 only inhibited IGF-1 induced protein levels of decorin, not that of biglycan. It is suggesting that the regulation of decorin by IGF-1 was affected by MEK/ERK pathway. On the other hand, biglycan was not influenced by U0126. Therefore, to examine why biglycan protein was increased by IGF-1, I investigated the effect of IGF-1 on the degradation of biglycan. Degradation of biglycan, not that of decorin, was observed by incubation of the cultured media at 37ยฐC. The degradation of biglycan was inhibited by treatment with EDTA, suggesting that those degradation is mediated by metalloproteinases. Moreover, it was inhibited in the IGF-1-treated fibroblast-cultured media. Furthermore, I found that treatment with IGF-1 reduced mRNA and protein expression levels of a disintegrin and metalloproteinase with thrombospondin motifs 5 (ADAMTS5), which is known to degrade biglycan. In addition, the expression of tissue inhibitor of metalloproteinase 4 (TIMP4), which can act as inhibitor of ADAMTS5, were increased by IGF-1, suggesting that the reduction of overall ADAMTS5 activity by IGF-1 is responsible for the increased amount of biglycan. Knockdown of ADAMTS5 with siRNA resulted in augmented biglycan protein level. Taken together, these results suggest that IGF-1 may be a new regulator of biglycan and decorin expressions by inhibition of its degradation by ADAMTS5 and activation of MEK/ERK pathway, respectively.ํ”„๋กœํ…Œ์˜ค๊ธ€๋ฆฌ์นธ(proteoglycan)์€ ๊ธ€๋ฆฌ์ฝ”์‚ฌ๋ฏธ๋…ธ๊ธ€๋ฆฌ์นธ(glycosaminoglycan)์ด๋ผ๊ณ  ๋ถ€๋ฅด๋Š” ํŠน์ˆ˜ํ•œ ๊ตฌ์กฐ์˜ ๋‹น ๋ณตํ•ฉ์ฒด๊ฐ€ ๊ฒฐํ•ฉํ•ด ์žˆ๋Š” ๋‹จ๋ฐฑ์งˆ๋“ค์„ ๋งํ•œ๋‹ค. ๊ทธ ์ค‘์—์„œ๋„ ๋ฐ”์ด๊ธ€๋ฆฌ์นธ(biglycan)๊ณผ ๋ฐ์ฝ”๋ฆฐ(decorin)์€ ํ”ผ๋ถ€์— ํ’๋ถ€ํ•˜๊ฒŒ ์กด์žฌํ•˜๋Š” ํ”„๋กœํ…Œ์˜ค๊ธ€๋ฆฌ์นธ์œผ๋กœ, ๋‚ด์ธ์„ฑ ๋…ธํ™”์™€ ๊ด‘๋…ธํ™” ํ”ผ๋ถ€์—์„œ ๋‹จ๋ฐฑ์งˆ ์–‘์ด ๊ฐ์†Œํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด๋“ค์ด ์–ด๋–ค ๊ธฐ์ „์— ์˜ํ•ด ์กฐ์ ˆ๋˜๋Š”์ง€ ์•„์ง ์•Œ๋ ค์ง„ ๋ฐ”๊ฐ€ ์—†๋‹ค. ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1(insulin-like growth factor-1, IGF-1)์€ ์„ธํฌ์˜ ์ƒ์กด, ์„ฑ์žฅ, ์„ธํฌ์˜ ์ž์—ฐ์‚ฌ์™€ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ์ƒ๋ฌผํ•™์  ํ˜„์ƒ์„ ์กฐ์ ˆํ•˜๋Š” ์ค‘์š”ํ•œ ์ธ์ž๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์‹œ๊ฐ„์˜ ํ๋ฆ„์— ๋”ฐ๋ผ ๋…ธํ™”๊ฐ€ ์ง„ํ–‰๋˜๋ฉด์„œ ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์˜ ํ•ฉ์„ฑ๊ณผ ๋ถ„๋น„๊ฐ€ ๊ฐ์†Œ๋œ๋‹ค๋Š” ์‚ฌ์‹ค์€ ๋งค์šฐ ์ž˜ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ๋…ธํ™”์— ๋”ฐ๋ผ ๊ฐ์†Œํ•˜๋Š” ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์ด ๋ฐ”์ด๊ธ€๋ฆฌ์นธ๊ณผ ๋ฐ์ฝ”๋ฆฐ์˜ ์ƒ์„ฑ์„ ์กฐ์ ˆํ•˜๋Š”์ง€ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ํ”ผ๋ถ€ ์กฐ์ง์—์„œ ๋ถ„๋ฆฌํ•œ ์ง„ํ”ผ ์„ฌ์œ ์•„์„ธํฌ์— ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์„ ์ฒ˜๋ฆฌํ•˜๊ณ  ๋ฐ”์ด๊ธ€๋ฆฌ์นธ๊ณผ๋ฐ์ฝ”๋ฆฐ์˜ mRNA์™€ ๋‹จ๋ฐฑ์งˆ์˜ ๋ณ€ํ™”๋ฅผ ๊ด€์ฐฐํ•˜์˜€์„ ๋•Œ, ์ด๋“ค์˜ ๋‹จ๋ฐฑ์งˆ ์–‘์€ ์ฆ๊ฐ€ํ•˜์˜€์ง€๋งŒ mRNA๋Š” ์œ ์˜ํ•œ ๋ณ€ํ™”๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์˜ ์ˆ˜์šฉ์ฒด์˜ ์–ต์ œ์ œ์ธ NVP-AEW541๊ณผ MEK์˜ ์–ต์ œ์ œ์ธ U0126์ด ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์— ์˜ํ•œ ๋ฐ์ฝ”๋ฆฐ์˜ ์ฆ๊ฐ€ ํšจ๊ณผ๋ฅผ ์ƒ์‡„์‹œ์ผฐ๋‹ค. ๋”ฐ๋ผ์„œ, ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์— ์˜ํ•ด ์ฆ๊ฐ€๋œ ๋ฐ์ฝ”๋ฆฐ์˜ ๋ฐœํ˜„์€ ์ด๊ฒƒ์˜ ์‹ ํ˜ธ ์ „๋‹ฌ ๊ฒฝ๋กœ ์ค‘ ํ•˜๋‚˜์ธ MEK/ERK ๊ฒฝ๋กœ์— ์˜ํ•œ ๊ฒƒ์ž„์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ•œํŽธ, ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์€ U0126์— ์˜ํ•ด ์ฆ๊ฐ€ ํšจ๊ณผ๊ฐ€ ์ƒ์‡„๋˜์ง€ ์•Š์•˜์œผ๋ฏ€๋กœ, ๋ถ„ํ•ด ์–ต์ œ์— ์˜ํ•œ ๋‹จ๋ฐฑ์งˆ ์ถ•์  ํšจ๊ณผ์ธ์ง€๋ฅผ ํ™•์ธํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์„ฌ์œ ์•„์„ธํฌ๋ฅผ ํ‚ค์šด ๋ฐฐ์–‘์•ก์„ 37โ„ƒ์— ๋‘์—ˆ์„ ๋•Œ, ์•„๋ฌด๊ฒƒ๋„ ์ฒ˜๋ฆฌํ•˜์ง€ ์•Š์€ ์„ธํฌ๋กœ๋ถ€ํ„ฐ ์–ป์€ ๋ฐฐ์–‘์•ก(๋Œ€์กฐ๊ตฐ)์—์„œ๋Š” ์‹œ๊ฐ„์ด ๊ฒฝ๊ณผํ•จ์— ๋”ฐ๋ผ ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์˜ ๋ถ„ํ•ด๊ฐ€ ์ผ์–ด๋‚˜๋Š” ๊ฒƒ์ด ๊ด€์ฐฐ๋˜์—ˆ์œผ๋‚˜, ์ธ์Š๋ฆฐ ์„ฑ์žฅ์ธ์ž-1์„ ์ฒ˜๋ฆฌํ•˜์—ฌ ํ‚ค์šด ์„ธํฌ๋กœ๋ถ€ํ„ฐ ์–ป์€ ๋ฐฐ์–‘์•ก์—์„œ ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์˜ ๋ถ„ํ•ด๊ฐ€ ์–ต์ œ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๋ถ„ํ•ด ์–ต์ œ๋Š” ์ธ์Š๋ฆฐ ์„ฑ์žฅ์ธ์ž-1์„ ์ฒ˜๋ฆฌํ•˜์ง€ ์•Š์€ ๋Œ€์กฐ๊ตฐ์— EDTA๋ฅผ ์ฒ˜๋ฆฌํ•˜์—ฌ 37โ„ƒ์— ๋‘์—ˆ์„ ๋•Œ๋„ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฏ€๋กœ, ์ด๋Ÿฌํ•œ ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์˜ ๋ถ„ํ•ด๊ฐ€ ๋ฉ”ํƒˆ๋กœํ”„๋กœํ…Œ๋„ค์ด์ฆˆ(metalloproteinase)์— ์˜ํ•œ ๊ฒƒ์ž„์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. ๊ทธ ์„ธ๋ถ€ ๊ธฐ์ „์„ ํ™•์ธํ•˜์˜€์„ ๋•Œ, ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์„ ๋ถ„ํ•ดํ•  ์ˆ˜ ์žˆ๋Š” ํšจ์†Œ ์ค‘ ํ•˜๋‚˜์ธ ADAMTS5์˜ ๋ฐœํ˜„์ด ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์— ์˜ํ•ด ๊ฐ์†Œ๋˜๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์˜ ์ฒ˜๋ฆฌ์— ์˜ํ•ด ADAMTS5์˜ ์–ต์ œ์ž๋กœ ์•Œ๋ ค์ง„ TIMP4์˜ ๋ฐœํ˜„๋„ ์ฆ๊ฐ€๋จ์„ ํ™•์ธํ•จ์œผ๋กœ์จ, ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์— ์˜ํ•ด ADAMTS5์˜ ์ „์ฒด์ ์ธ ํ™œ์„ฑ์˜ ๊ฐ์†Œ๋กœ ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์˜ ๋ถ„ํ•ด๊ฐ€ ์–ต์ œ๋œ๋‹ค๊ณ  ์ƒ๊ฐ๋œ๋‹ค. ๋”๋ถˆ์–ด, siRNA๋ฅผ ํ†ตํ•ด ADAMTS5์˜ ๋ฐœํ˜„์„ ์–ต์ œํ•˜์˜€์„ ๋•Œ, ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์˜ ๋‹จ๋ฐฑ์งˆ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‚ด์ธ์„ฑ ํ”ผ๋ถ€๋…ธํ™”์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๋ฐ”์ด๊ธ€๋ฆฌ์นธ๊ณผ ๋ฐ์ฝ”๋ฆฐ์˜ ๊ฐ์†Œ ์›์ธ์œผ๋กœ ๋…ธํ™”์— ์˜ํ•ด ๊ฐ์†Œ๋˜๋Š” ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๊ทธ ์„ธ๋ถ€ ๊ธฐ์ „์œผ๋กœ์„œ, ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์€ ADAMTS5์˜ ๊ธฐ์ € ๋ฐœํ˜„์„ ๊ฐ์†Œ์‹œํ‚ค๊ณ , ์ด๊ฒƒ์˜ ์–ต์ œ์ œ์ธ TIMP4์˜ ๋ฐœํ˜„์„ ์ฆ๊ฐ€์‹œํ‚ด์œผ๋กœ์จ, ์ข…ํ•ฉ์ ์œผ๋กœ ADAMTS5์˜ ์ „์ฒด์ ์ธ ํ™œ์„ฑ์„ ๊ฐ์†Œ์‹œ์ผœ ๋ฐ”์ด๊ธ€๋ฆฌ์นธ์˜ ๋ถ„ํ•ด๋ฅผ ์–ต์ œํ•˜๋Š” ๊ธฐ์ „์œผ๋กœ ์ž‘์šฉํ•จ์„ ๋ฐํ˜”๋‹ค. ๋˜ํ•œ, ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์˜ ์‹ ํ˜ธ ์ „๋‹ฌ ๊ฒฝ๋กœ ์ค‘ ํ•˜๋‚˜์ธ MEK/ERK ๊ฒฝ๋กœ์— ์˜ํ•ด ๋ฐ์ฝ”๋ฆฐ์˜ ๋ฐœํ˜„์ด ์ฆ๊ฐ€๋˜์–ด, MEK ์–ต์ œ์ œ์ธ U0126์— ์˜ํ•ด ์ธ์Š๋ฆฐ ์œ ์‚ฌ์„ฑ์žฅ์ธ์ž-1์— ์˜ํ•œ ๋ฐ์ฝ”๋ฆฐ ์ฆ๊ฐ€ ํšจ๊ณผ๊ฐ€ ์ƒ์‡„๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค.Abstract -----------------------------------------------------------------------------------โ…ฐ Contents ----------------------------------------------------------------------------------โ…ณ List of Tables ------------------------------------------------------------------------------โ…ต List of Figures -----------------------------------------------------------------------------โ…ถ Introduction ------------------------------------------------------------------------------- 1 Materials & Methods --------------------------------------------------------------------- 4 Results 1. IGF-1 increased protein levels of biglycan and decorin in NHDFs. --------------- 9 2. IGF-1 did not increase mRNA of biglycan and decorin in NHDFs. --------------- 11 3. IGF-1 receptor blocker, NVP-AEW541, countervailed IGF-1 induced protein levels of biglycan and decorin in NHDFs. ------------------------------------------------ 13 4. MEK inhibitor, U0126, inhibited IGF-1 induced protein expression of decorin, not that of biglycan. -------------------------------------------------------------------- 15 5. Degradations of biglycan, but not that of decorin, occurred in NHDFs cultured media. ------------------------------------------------------------------------------- 17 6. Degradation of biglycan was not observed in IGF-1 treated dermal fibroblast cultured media. --------------------------------------------------------------------- 19 7. IGF-1 regulated expressions of several metalloproteinases that are targets of EDTA. ------------------------------------------------------------------------------- 21 8. Expression of ADAMTS5 was higher than that of ADAMTS4 in NHDFs. -------- 23 9. IGF-1 reduced the protein expression of ADAMTS5. ------------------------------25 10. Expression of ADAMTS5 in aged skin was higher than in young skin. --------- 27 11. TIMP3 and 4, but not TIMP1 and 2, were increased by IGF-1 in NHDFs. ------ 29 12. The protein of TIMP4 was increased by IGF-1 in NHDFs. ----------------------- 31 13. Knockdown of ADAMTS5 resulted in increased biglycan protein level. -------- 33 14. Schematic diagram showing the effects of IGF-1 regulating biglycan and decorin expression. -------------------------------------------------------------------------- 35 Discussion ---------------------------------------------------------------------------------- 36 References ---------------------------------------------------------------------------------- 40 ๊ตญ๋ฌธ ์ดˆ๋ก ----------------------------------------------------------------------------------- 44Maste

    MMPI-2 Profiles of College Students at High-Risk of Internet Game Addiction

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    ๋ณธ ์—ฐ๊ตฌ๋Š” 184๋ช…(๋‚จ 91๋ช…, ์—ฌ 93๋ช…)์˜ ๋Œ€ํ•™์ƒ๊ณผ ์ƒ๋‹ด๊ธฐ๊ด€์— ๋‚ด์›ํ•˜์—ฌ ์ธํ„ฐ๋„ท๊ฒŒ์ž„ ๊ณผ๋‹ค์ด์šฉ ๋ฌธ์ œ๋ฅผ ํ˜ธ์†Œํ•˜๋Š” ๋Œ€ํ•™์ƒ 43๋ช…(๋‚จ 25๋ช…, ์—ฌ 18๋ช…)์„ ๋Œ€์ƒ์œผ๋กœ ๊ฒŒ์ž„์ค‘๋…์œ„ํ—˜ ๋Œ€ํ•™์ƒ๋“ค์˜ MMPI-2 ํ”„๋กœํŒŒ์ผ ํ˜•ํƒœ๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์ธํ„ฐ๋„ท ์ค‘๋…์ฒ™๋„์ ์ˆ˜ 39์  ์ดํ•˜๋กœ์„œ ์ธํ„ฐ๋„ท ํ‰๊ท  ์ด์šฉ์ž์— ํ•ด๋‹นํ•˜๋Š” ๋Œ€ํ•™์ƒ 141๋ช…(๋‚จ 73๋ช…, ์—ฌ 68๋ช…)์—๊ฒŒ ๋‹ค๋ฉด์  ์ธ์„ฑ๊ฒ€์‚ฌ II(MMPI-2)๋ฅผ ์‹ค์‹œํ•˜์—ฌ ๋ถˆ์„ฑ์‹คํ•œ ์‘๋‹ต์„ ์ œ์™ธํ•˜๊ณ  122๋ช…(๋‚จ 66๋ช…, ์—ฌ 56๋ช…)์˜ ์ž๋ฃŒ๋ฅผ ์ •์ƒ์ง‘๋‹จ์— ํฌํ•จ์‹œ์ผฐ๋‹ค. ์ƒ๋‹ด๊ธฐ๊ด€์— ๋‚ด์›ํ•œ ๋Œ€ํ•™์ƒ๋“ค ๊ฐ€์šด๋ฐ ์ธํ„ฐ๋„ท ์ค‘๋…์ฒ™๋„์ ์ˆ˜ 50์  ์ด์ƒ์ด๊ณ , MMPI-2 ๊ฒฐ๊ณผ๊ฐ€ ํƒ€๋‹นํ•œ 41๋ช…(๋‚จ 25๋ช…, ์—ฌ 16๋ช…)์˜ ์ž๋ฃŒ๋ฅผ ์ธํ„ฐ๋„ท๊ฒŒ์ž„ ์ค‘๋…์œ„ํ—˜์ง‘๋‹จ์— ํฌํ•จ์‹œ์ผฐ๋‹ค. ์ค‘๋…์œ„ํ—˜์ง‘๋‹จ์€ ์ •์ƒ์ง‘๋‹จ์— ๋น„ํ•ด ๋‚จ๋…€ ๋ชจ๋‘ ๋‚จ์„ฑ์„ฑ-์—ฌ์„ฑ์„ฑ(Mf)์ฒ™๋„๋ฅผ ์ œ์™ธํ•œ ๋ชจ๋“  ์ž„์ƒ์ฒ™๋„๋“ค์˜ ์ ์ˆ˜๊ฐ€ ์ƒ์Šน๋˜์—ˆ๋Š”๋ฐ, ํŠนํžˆ Pd, Pa, Pt, ๊ทธ๋ฆฌ๊ณ  Sc์ฒ™๋„๋Š” 75์  ์ด์ƒ์œผ๋กœ ๋†’์€ ์ƒ์Šน์„ ๋ณด์˜€๊ณ , D์ฒ™๋„๋Š” 70์ ์— ๊ทผ์ ‘ํ•˜์˜€๋‹ค. ์ฆ‰ ์ธํ„ฐ๋„ท๊ฒŒ์ž„ ์ค‘๋…์œ„ํ—˜์ง‘๋‹จ์€ ์ •์ƒ ๋Œ€ํ•™์ƒ๋“ค์— ๋น„ํ•ด ์šฐ์šธํ•˜๊ณ  ๋ฐ˜์‚ฌํšŒ์ ์ด๊ณ  ์ถฉ๋™์ ์ธ ์„ฑํ–ฅ์ด ๋†’๊ณ , ์˜์‹ฌ์ด ๋งŽ๊ณ  ๊ณผ๋„ํ•˜๊ฒŒ ์˜ˆ๋ฏผํ•˜๋ฉฐ, ๊ฐ•๋ฐ•์ ์ธ ๋ถˆ์•ˆ๊ณผ ๊ณผ๋„ํ•œ ๋‘๋ ค์›€์„ ๋Š๋ผ๊ณ , ํ˜„์‹ค๊ฒ€์ฆ๋ ฅ์ด ์†์ƒ๋˜์—ˆ์„ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์Œ์„ ์‹œ์‚ฌํ•˜์˜€๋‹ค. ๋‚ด์šฉ์ฒ™๋„ ๋น„๊ต์—์„œ๋Š” ํŠนํžˆ ANX, DEP, BIZ, ๋ฐ WRK ์ฒ™๋„์ ์ˆ˜๊ฐ€ 70์  ์ด์ƒ์œผ๋กœ ์ƒ์Šน๋˜์–ด ์ค‘๋…์œ„ํ—˜์ง‘๋‹จ์˜ ๋Œ€ํ•™์ƒ๋“ค์ด ๋ถˆ์•ˆ๊ณผ ์šฐ์šธ์„ ๋งŽ์ด ๋Š๋ผ๊ณ , ๋น„ํ˜„์‹ค์ ์ด๊ณ  ๋•Œ๋กœ๋Š” ๋ง์ƒ๊ณผ ํ™˜๊ฐ๊นŒ์ง€๋„ ๊ฒฝํ—˜ํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์œผ๋ฉฐ, ์—…๋ฌด์ˆ˜ํ–‰์— ์–ด๋ ค์›€์„ ๋Š๋ผ๋Š” ๊ฒฝํ–ฅ์ด ๋†’์€ ๊ฒƒ์œผ๋กœ ๋ณด์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ๊ฐ–๋Š” ์ œํ•œ์ ๊ณผ ํ•จ๊ป˜ ํ–ฅํ›„ ์—ฐ๊ตฌ ๋ฐฉ์•ˆ์ด ๋…ผ์˜๋˜์—ˆ๋‹ค. This study examined the MMPI-2 Profiles of college students at high-risk of internet game addiction. 184 college students (male 91, female 93) were administered the internet addiction scale. 141 students (male 73, female 68) with internet addiction scale scores of 39 or lower were considered average internet users and administered the Korean MMPI-2. 122 students (male 66, female 56) with valid MMPI-2 profiles consisted of final normal sample. High-risk group consisted of 41 college students who received psychological services due to internet game addiction and produced internet addiction scale scores of 50 or greater with valid MMPI-2 profiles. Students at high-risk of internet game addiction obtained significantly elevated scores on all MMPI-2 validity and clinical scales except Mf scale. Scores on Pd, Pa, Pt, and Sc were very much elevated with scores of 75 of greater. When content scale scores were examined, high-risk group produced highly elevated scores on ANX, DEP, BIZ, and WRK. These results suggest that students at high-risk of internet game addiction are more likely to be depressed, anxious, and unrealistic, and may have behaviors or attitudes that contribute to poor work performance. Limitations of this study and suggestions for further research were discussed

    ๊ณจ๋‹ค๊ณต์ฆ ์น˜๋ฃŒ ์•ฝ์ œ์˜ ๋น„์šฉ-ํšจ๊ณผ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋ณด๊ฑด๋Œ€ํ•™์› :๋ณด๊ฑด์ •์ฑ…๊ด€๋ฆฌํ•™๊ณผ ๋ณด๊ฑด์˜๋ฃŒ๊ฒฝ์˜ ์ „๊ณต,2001.Maste

    Eine Studie uber die Anorung im deutschen Verwaltungsverfahrensgesetz(VwVfG)

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋ฒ•ํ•™๊ณผ,2009.8.Maste

    A Preliminary Investigation on Validityof the Korean Version of Beck Anger Inventory for Youth

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญํŒ Beck ์•„๋™์šฉ ๋ถ„๋…ธ ํ‰๊ฐ€์ฒ™๋„์˜ ํƒ€๋‹นํ™”๋ฅผ ์œ„ํ•œ ์˜ˆ๋น„์—ฐ๊ตฌ๋กœ ์ด๋ฃจ์–ด์กŒ๋‹ค. ์ดˆ๋“ฑํ•™์ƒ 155๋ช…๊ณผ ๋ฌธ์ œ ์•„๋™ ์ง‘๋‹จ 30๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์—ฐ๊ตฌํ•œ ๊ฒฐ๊ณผ, ์‹ ๋ขฐ๋„์™€ ํƒ€๋‹น๋„๊ฐ€ ๋ชจ๋‘ ๋น„๊ต์  ์–‘ํ˜ธํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‚ด์  ์ผ๊ด€์„ฑ ์‹ ๋ขฐ๋„๋Š” ฮฑ ๊ณ„์ˆ˜๊ฐ€ .90์œผ๋กœ ์ƒ๋‹นํžˆ ๋†’์•˜๋‹ค. ์š”์ธ ๋ถ„์„์„ ํ†ตํ•ด 3์š”์ธ์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๋‹ค๋Š” ๊ฒฐ๊ณผ๊ฐ€ ์–ป์–ด์กŒ๊ณ , ๊ณต๊ฒฉ์„ฑ ์ฒ™๋„ ๋ฐ ๋น„ํ–‰์ฒ™๋„์™€ ์œ ์˜๋ฏธํ•œ ์ƒ๊ด€์„ ๋ณด์—ฌ ๊ณต์กดํƒ€๋‹น๋„๊ฐ€ ํ™•์ธ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ๋ถ„๋…ธ ์ ์ˆ˜๊ฐ€ ์ •์ƒ ์ง‘๋‹จ์— ๋น„ํ•ด ๋ฌธ์ œ ์ง‘๋‹จ์—์„œ ๋” ๋†’์•„ ์ฒ™๋„์˜ ์ค€๊ฑฐํƒ€๋‹น๋„๊ฐ€ ํ™•์ธ๋˜์—ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ๊ฐ–๋Š” ์ œํ•œ์ ๊ณผ ํ›„์† ์—ฐ๊ตฌ์— ๋Œ€ํ•œ ์‹œ์‚ฌ์ ์„ ๋…ผ์˜ํ•˜์˜€๋‹ค. This study was conducted to provide initial information about reliability and validity of a Korean translation of Beck Anger Inventory for Youth(BANI-Y). Subjects were 155 elementary school students and 30 children with conduct problems currently enrolled in therapy. The Korean version of Beck Anger Inventory for Youth produced high internal consistency reliabilities of .90. Results of factor analysis showed that BANI-Y consisted of 3 underlying dimensions. Significant correlations were found among the scores of BANI-Y and the instruments to measure aggressive and delinquent behavior of children. Limitations of this study and suggestions for future research were discussed

    The Association between Chronotype and Problem Drinking in University Students

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    ์˜ํ•™๊ณผ/์„์‚ฌ๋Œ€ํ•™ ์‹ ์ž…์ƒ ์‹œ์ ˆ์€ ์ดํ›„ ์Œ์ฃผ ํ–‰๋™์„ ์˜ˆ์–ธํ•  ์ˆ˜ ์žˆ์–ด ํ‰์ƒ ์Œ์ฃผ ํ–‰๋™ ํ˜•์„ฑ์— ๋งค์šฐ ์ค‘์š”ํ•œ ์‹œ๊ธฐ์ด๋‹ค. ๋”ฐ๋ผ์„œ ์ˆ ์„ ์ฒ˜์Œ ๋งˆ์‹œ๊ธฐ ์‹œ์ž‘ํ•˜์—ฌ ํ‰์ƒ์˜ ์Œ์ฃผ ์Šต๊ด€์œผ๋กœ ์ •์ฐฉ๋˜๋Š” ๋Œ€ํ•™์ƒ์˜ ์Œ์ฃผ ํ–‰๋™๊ณผ ์ด์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์„ ์ฐพ์•„๋‚ด๋ ค๋Š” ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค. ๋ฌธ์ œ ์Œ์ฃผ์—๋Š” ์ƒ๋ฆฌํ•™์  ์š”์ธ, ์‹ฌ๋ฆฌ์‚ฌํšŒ์  ์š”์ธ์ด ๋ณตํ•ฉ์ ์œผ๋กœ ์ž‘์šฉํ•˜๋ฉฐ ์ผ์ฃผ๊ธฐ์„ฑ ์œ ํ˜•๋„ ๊ทธ ์ค‘ ํ•˜๋‚˜๋กœ ๊ฐ„์ฃผ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ผ ์˜๊ณผ๋Œ€ํ•™ ํ•™์ƒ๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ๋ฌธ์ œ ์Œ์ฃผ์™€ ์ผ์ฃผ๊ธฐ์„ฑ ์œ ํ˜• ์‚ฌ์ด์— ์ง์ ‘์ ์ธ ์—ฐ๊ด€์„ฑ์ด ์žˆ๋Š”๊ฐ€์— ๋Œ€ํ•ด ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด 197๋ช…์˜ ์˜๊ณผ๋Œ€ํ•™ ํ•™์ƒ๋“ค์ด ์„ค๋ฌธ์ง€์— ์‘๋‹ตํ•˜์˜€์œผ๋ฉฐ, ์„ค๋ฌธ์ง€๋Š” ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ํŠน์„ฑ, ์ผ์ฃผ๊ธฐ์„ฑ ์œ ํ˜• ์ฒ™๋„, ์ผ์ฃผ๊ธฐ์„ฑ ์œ ํ˜• ์ฒ™๋„, AUDIT-K, ์ƒํƒœ-ํŠน์„ฑ ๋ถˆ์•ˆ ์ฒ™๋„, Beck์˜ ์šฐ์šธ์ฒ™๋„, Barratt ์ถฉ๋™์„ฑ ์ฒ™๋„, ์ˆ˜๋ฉด์˜ ์งˆ ์ฒ™๋„๋ฅผ ํฌํ•จํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์Œ์ฃผ์™€ ๊ด€๋ จํ•˜์—ฌ, ๋ฌธ์ œ ์Œ์ฃผ๋ฅผ ์‹œ์‚ฌํ•˜๋Š” ํ•™์ƒ์€ 61๋ช…(39.96%)์œผ๋กœ ๋‚จ์ž๊ฐ€ 91.8%์œผ๋กœ ๋ฌธ์ œ์Œ์ฃผ์ž์˜ ๋น„์œจ์ด ๋†’์•˜๋‹ค(p<0.001). ์ €๋…ํ˜• ์œ ํ˜•์ผ์ˆ˜๋ก ์Œ์ฃผ๋ฌธ์ œ๊ฐ€ ๋” ๋งŽ์•˜๋‹ค(p<0.01).MEQ์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ์ธ๊ตฌ ํ†ต๊ณ„ํ•™์  ํŠน์„ฑ์„ ๋ณด์ •ํ•˜์˜€์„ ๋•Œ MEQ ์ ์ˆ˜๋Š” AUDIT์ ์ˆ˜์™€ ์Œ์˜ ์ƒ๊ด€ ๊ด€๊ณ„๋ฅผ ๋ณด์˜€๊ณ (adjusted Rยฒ=0.192, p<0.001), ์‹ฌ๋ฆฌํ•™์  ์š”์ธ์„ ์ถ”๊ฐ€ ๋ณด์ • ํ–ˆ์„ ๋•Œ MEQ์ ์ˆ˜๋Š” AUDIT์ ์ˆ˜์™€ ์Œ์˜ ์ƒ๊ด€ v ๊ด€๊ณ„๋ฅผ ๋ณด์˜€๋‹ค(adjusted Rยฒ=0.209, p<0.001). ๋งˆ์ง€๋ง‰์œผ๋กœ PSQI์ ์ˆ˜๋ฅผ ์ถ”๊ฐ€ ๋ณด์ •ํ–ˆ์„ ๋•Œ๋„ MEQ์ ์ˆ˜๋Š” AUDIT์ ์ˆ˜์™€ ์Œ์˜ ์ƒ๊ด€ ๊ด€๊ณ„๋ฅผ ๋ณด์˜€๋‹ค(adjusted Rยฒ=0.226, p<0.01). ๋ณธ ์—ฐ๊ตฌ๋Š” ํ›„๊ธฐ ์ฒญ์†Œ๋…„๊ธฐ์™€ ์ดˆ๊ธฐ ์„ฑ์ธ๊ธฐ ์‹œ๊ธฐ์— ์ €๋…ํ˜• ์œ ํ˜•์ด ๋ฌธ์ œ ์Œ์ฃผ์˜ ์ง์ ‘์ ์ธ ์œ„ํ—˜ ์š”์ธ์œผ๋กœ ์ž‘์šฉํ•  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค.๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ ๋Œ€ํ•™์ƒ ์Œ์ฃผ๋ฌธ์ œ์˜ ๋ณด๊ฑด ์ •์ฑ…์  ์ ‘๊ทผ์— ์ฐธ๊ณ ์ž๋ฃŒ๊ฐ€ ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ ๋œ๋‹ค.ope

    Relationship between self-efficacy and self-care behavior in open heart surgery patients who received phase I c

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    ๊ฐ„ํ˜ธํ•™๊ต์œก ์ „๊ณต/์„์‚ฌ[ํ•œ๊ธ€] ๋ณธ ์—ฐ๊ตฌ๋Š” ์ œ 1๋‹จ๊ณ„ ์‹ฌ์žฅ์žฌํ™œ ํ”„๋กœ๊ทธ๋žจ์„ ๋ฐ›์€ ๊ฐœ์‹ฌ์ˆ  ํ™˜์ž์˜ ์ž๊ธฐํšจ๋Šฅ๊ฐ๊ณผ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰ ์ •๋„์™€์˜ ๊ด€๊ณ„๋ฅผ ํŒŒ์•…ํ•˜์—ฌ ํ‡ด์›ํ•œ ๊ฐœ์‹ฌ์ˆ  ํ™˜์ž์—๊ฒŒ ์‹ค์ œ๋กœ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์„ ๋†’์ผ ์ˆ˜ ์žˆ๋Š” ํšจ๊ณผ์ ์ธ ์‹ฌ์žฅ์žฌํ™œ ํ”„๋กœ๊ทธ๋žจ์„ ์ ์šฉํ•˜๋Š”๋ฐ ๋„์›€์ด ๋˜๊ณ ์ž ์‹œ๋„๋œ ์ƒ๊ด€๊ด€๊ณ„ ์กฐ์‚ฌ์—ฐ๊ตฌ์ด๋‹ค. ์—ฐ๊ตฌ ๋Œ€์ƒ์€ ์ผ๊ฐœ ๋Œ€ํ•™๋ณ‘์›์— ์ž…์›ํ•˜์—ฌ ๊ฐœ์‹ฌ์ˆ ์„ ๋ฐ›๊ณ  ๊ฐ„ํ˜ธ์‚ฌ, ์˜์–‘์‚ฌ์— ์˜ํ•ด ์ œ 1๋‹จ๊ณ„ ์‹ฌ์žฅ์žฌํ™œ ํ”„๋กœ๊ทธ๋žจ์˜ ๊ต์œก์„ ๋ฐ›์€ ํ›„ ํ‡ด์›ํ•˜์—ฌ ์ˆ˜์ˆ  ๊ฒฝ๊ณผ๊ธฐ๊ฐ„์ด 6๊ฐœ์›” ์ด๋‚ด์ธ ๊ฐœ์‹ฌ์ˆ  ํ™˜์ž 32๋ช…์ด์—ˆ๋‹ค. ์—ฐ๊ตฌ ๋„๊ตฌ๋กœ๋Š” ์ผ๋ฐ˜์  ํŠน์„ฑ 15๋ฌธํ•ญ, ์ž๊ธฐํšจ๋Šฅ๊ฐ ์ธก์ • 26๋ฌธํ•ญ, ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰ ์ธก์ • 32๋ฌธํ•ญ์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ์œผ๋ฉฐ, ๋ณธ ์—ฐ๊ตฌ์—์„œ์˜ ์ž๊ธฐํšจ๋Šฅ๊ฐ ์ธก์ • ๋„๊ตฌ์˜ ์‹ ๋ขฐ๋„๋Š” Cronbachโ€™s ฮฑ ๊ฐ’ .9214์ด์—ˆ๊ณ , ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰ ์ธก์ • ๋„๊ตฌ์˜ ์‹ ๋ขฐ๋„๋Š” Cronbachโ€™s ฮฑ ๊ฐ’ .9374 ์ด์—ˆ๋‹ค. ์ž๋ฃŒ ์ˆ˜์ง‘์€ 2004๋…„ 1์›” 4์ผ๋ถ€ํ„ฐ 5์›” 28์ผ๊นŒ์ง€ ์ด๋ฃจ์–ด์กŒ์œผ๋ฉฐ, ์ˆ˜์ง‘๋œ ์ž๋ฃŒ๋Š” SPSS 11.0 ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ ๋ฐฑ๋ถ„์œจ, ์‚ฐ์ˆ ํ‰๊ท , independent t-test, Pearson Correlation Coefficient๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. 1. ๋Œ€์ƒ์ž์˜ ์ผ๋ฐ˜์  ํŠน์„ฑ์€ ๋‚จ์ž๊ฐ€ 62.5%๋กœ ๋งŽ์•˜๊ณ , ํ‰๊ท  ์—ฐ๋ น์€ 52.34์„ธ (SD=13.48)์ด์˜€๋‹ค. ๋Œ€๋‹ค์ˆ˜๊ฐ€ ๊ธฐํ˜ผ(81.3%)์ด์—ˆ๊ณ , ์ง์—…์ƒํƒœ๋Š” ๋ฌด์ง(40.6%)์ด ๋งŽ์•˜์œผ๋ฉฐ, ํ•™๋ ฅ์€ ๊ณ ์กธ์ดํ•˜๊ฐ€ 34.4%๋กœ ๊ฐ€์žฅ ๋งŽ์•˜๊ณ , ์ข…๊ต๋Š” 50%๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์‹ฌ์žฅ์งˆํ™˜๊ณผ ๊ด€๋ จ๋œ ์ƒํ™œ์Šต๊ด€์—์„œ๋Š” ํก์—ฐ์Šต๊ด€์˜ ๊ฒฝ์šฐ โ€˜ํ˜„ ์žฌ๋„ ํ”ผ์›€โ€™์ด 6.3%์ด์—ˆ๊ณ , ์Œ์ฃผ๋Š” 43.8%๊ฐ€ ํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋™๋ฌผ์„ฑ ์ง€๋ฐฉ์„ญ์ทจ๋Š” โ€˜๋งŽ์ด ๋จน๋Š” ํŽธ์ž„โ€™์ด 9.4%๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ์šด๋™์Šต๊ด€์˜ ๊ฒฝ ์šฐ๋„ โ€˜์ „ํ˜€ ์šด๋™์„ ํ•˜์ง€ ์•Š์Œโ€™์ด 21.9%๋กœ ๋‚˜ํƒ€๋‚˜ ํŠน๋ณ„ํžˆ ์œ„ํ—˜์ธ์ž ๊ต์ •์„ ์œ„ํ•œ ์ƒํ™œ์Šต๊ด€์˜ ๋ณ€ํ™”๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. ์งˆ๋ณ‘๋ ฅ์€ ๊ณ ํ˜ˆ์•• 31.3%๋กœ ๊ฐ€์žฅ ๋งŽ์•˜๊ณ , ์‹ฌ์žฅ์ˆ˜์ˆ ์€ ํŒ๋ง‰์น˜ํ™˜์ˆ ๊ณผ ๊ด€์ƒ๋™ ๋งฅ ์šฐํšŒ์ˆ ์ด ๊ฐ๊ฐ 40.6%์ด์—ˆ๋‹ค. ์‹ฌ์žฅ์žฌํ™œ ๊ด€๋ จ ์ž๊ฐ€๊ฐ„ํ˜ธ ํ•™์Šต์š”๊ตฌ๋Š” ์‹์ด ์š”๋ฒ•์— ๊ด€ํ•œ ๋‚ด์šฉ์„ ๊ฐ€์žฅ ๋งŽ์ด ์•Œ๊ณ  ์‹ถ์–ด ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. 2. ๋Œ€์ƒ์ž๊ฐ€ ์ธ์ง€ํ•œ ์ž๊ธฐํšจ๋Šฅ๊ฐ ์ •๋„๋Š” 5์  ๋งŒ์ ์— ํ‰๊ท ํ‰์  4.14(SD=0.57)๋กœ ๋‚˜ํƒ€๋‚˜ ๋Œ€์ƒ์ž๊ฐ€ ์ธ์ง€ํ•œ ์ž๊ธฐํšจ๋Šฅ๊ฐ ์ •๋„๋Š” ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋ฅผ ์˜์—ญ๋ณ„๋กœ ๋ถ„์„ํ•ด ๋ณด๋ฉด ํˆฌ์•ฝ์— ๋Œ€ํ•œ ์ž๊ธฐํšจ๋Šฅ๊ฐ์ด 4.81(SD=0.49)๋กœ ๊ฐ€์žฅ ๋†’ ์•˜์œผ๋ฉฐ, ์šด๋™ ์˜์—ญ 4.72(SD=0.57), ๊ธˆ์—ฐ ์˜์—ญ 4.63(SD=1.10), ์ผ์ƒํ™œ๋™ ์˜์—ญ 4.21(SD=0.69), ์‹์ด ์˜์—ญ 4.17(SD=0.70), ์‹ฌ๋ฆฌ์  ์ ์‘๋Šฅ๋ ฅ ์˜์—ญ 4.05 (SD=0.84), ์ผ๋ฐ˜์  ์ž๊ธฐํšจ๋Šฅ๊ฐ 3.88(SD=0.82)์˜ ์ˆœ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. 3. ๋Œ€์ƒ์ž์˜ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์ •๋„๋Š” 5์  ๋งŒ์ ์— ํ‰๊ท ํ‰์  4.20(SD=0.59)์œผ๋กœ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์„ ์ž˜ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ์ด๋ฅผ ์˜์—ญ๋ณ„๋กœ ๋ถ„์„ํ•ด ๋ณด๋ฉด ํˆฌ ์•ฝ์— ๊ด€ํ•œ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์ด ์ตœ๋Œ€ 5์ ์— 4.57(SD=0.46)๋กœ ๊ฐ€์žฅ ๋†’์•˜๊ณ , ๊ธˆ์—ฐ ์˜์—ญ 4.56(SD=1.13), ์ถ”ํ›„๊ด€๋ฆฌ ์˜์—ญ 4.41(SD=0.59), ์‹์ด ์˜์—ญ 4.19(SD=0.68), ์ผ์ƒ์ƒํ™œ ์กฐ์ ˆ์˜ ์˜์—ญ 4.02(SD=0.76), ์šด๋™ ์˜์—ญ 3.72(SD=0.93)์˜ ์ˆœ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. 4. ๋Œ€์ƒ์ž์˜ ์ž๊ธฐํšจ๋Šฅ๊ฐ๊ณผ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰ ์ •๋„๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ˆœ์ƒ๊ด€๊ด€ ๊ณ„๋ฅผ ๋ณด์—ฌ(r=.671, p=.000) ์ž๊ธฐํšจ๋Šฅ๊ฐ์ด ๋†’์„์ˆ˜๋ก ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์ •๋„๋Š” ๋†’ ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•˜์œ„ ์˜์—ญ๋ณ„ ์ž๊ธฐํšจ๋Šฅ๊ฐ ์ •๋„์™€ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰ ์ •๋„ ์™€์˜ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ์—์„œ๋Š” ๊ธˆ์—ฐ ์˜์—ญ์˜ ์ž๊ธฐํšจ๋Šฅ๊ฐ์„ ์ œ์™ธํ•œ ์‹์ด (r=.585, p=.000), ์ผ์ƒํ™œ๋™(r=.533, p=.002), ํˆฌ์•ฝ(r=.504, p=.003), ์‹ฌ๋ฆฌ์  ์ ์‘๋Šฅ๋ ฅ(r=.498, p=.004), ์šด๋™(r=.352, p=.048) ์˜์—ญ์˜ ์ž๊ธฐํšจ๋Šฅ๊ฐ์€ ์ „์ฒด ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰ ์ •๋„์™€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ž๊ธฐํšจ๋Šฅ๊ฐ์ด ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์˜ ์ค‘์š”ํ•œ ์˜ˆ์ธก์ธ์ž๋กœ ์ž‘์šฉํ•˜๋ฏ€๋กœ ํ‡ด์› ํ›„ ๊ฐœ์‹ฌ์ˆ  ํ™˜์ž์˜ ์ž๊ฐ€๊ฐ„ํ˜ธ ์ดํ–‰์„ ๋†’์ด๊ธฐ ์œ„ํ•œ ํšจ๊ณผ์ ์ธ ์‹ฌ์žฅ์žฌํ™œ ํ”„๋กœ๊ทธ๋žจ์— ์ž๊ธฐํšจ๋Šฅ๊ฐ์„ ๊ฐ•ํ™”์‹œํ‚ค๋Š” ์ „๋žต์„ ๊ฐ•๊ตฌํ•˜์—ฌ ์ ์šฉํ•˜๋ฉด ๋„์›€์ด ๋  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค. ๋˜ํ•œ ์‹ฌ์žฅ์งˆํ™˜์˜ ์œ„ํ—˜์ธ์ž์™€ ๊ด€๋ จํ•œ ์ƒํ™œ์–‘์‹์˜ ๋ณ€ํ™”๊ฐ€ ์–ด๋ ค์šด ์ž๊ฐ€๊ฐ„ํ˜ธ ์˜์—ญ์— ์ค‘์ ์„ ๋‘์–ด ์ง€์†์ ์ธ ํ–‰๋™๋ณ€ํ™”๋ฅผ ์œ ๋„ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ‡ด์›ํ•œ ๊ฐœ์‹ฌ์ˆ  ํ™˜์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ๊ฐœ๋ณ„์ ์ด๊ณ , ์ฒด๊ณ„์ ์ด๋ฉฐ ์ง€์†์ ์ธ ์ƒ๋‹ด๊ณผ ์ง€๋„๋ฅผ ํšจ์œจ์ ์œผ๋กœ ํ•ด๋‚˜๊ฐ€๊ธฐ ์œ„ํ•œ ํšจ๊ณผ์ ์ธ ์‹ฌ์žฅ์žฌํ™œ ํ”„๋กœ๊ทธ๋žจ์˜ ๊ฐœ๋ฐœ์ด ํ•„์š”ํ•˜๋ฆฌ๋ผ ์ƒ๊ฐํ•œ๋‹ค. [์˜๋ฌธ]The purposes of this study were to identify relationship between self-efficacy and self-behavior in open heart surgery patients who received phase I cardiac rehabilitation program and to observe the effectiveness to raise the self-care behavior. We designed a prospective study from January 4th to May 28th in 2004. The study was performed on 32 patients who were discharged from a university hospital located in Kyeonggi-Do, Korea after phase I cardiac rehabilitation program from nurse and dietitian, and not passed 6 months after open heart surgery. Informed consent was obtained from the patients. Data was obtained from 15 general characters questionnaire, 26 self-efficacy questionnaires and 32 self-care behavior questionnaires. The data were analyzed using SPSS. PC, version 11.0 statistical program. Such as frequency, independent t-test & Pearson correlation coefficient. The values were expressed as meanยฑSD. The important results are as follows : 1. The patients consisted of 62.5% male and 37.5% female, and mean age was 52.34(SD=13.48) year, and most of them were married state(81.3%). 40.6% had no job, the highest education was high school graduates(34.4%), and 50% had religion. Life style related cardiac disease were drinking 43.8%, smoking 6.3%, meal with high animal fat 9.4%, and no exercise 21.9%. Patient past history, hypertension was the most by 31.3%, valve replacement and coronary-bypass surgery were each 40.6%. Self-care behavior studying demand related with cardiac rehabilitation was the most dietary treatment. 2. Self-efficacy degree that subject recognizes was 4.14(SD=0.57) in 5 points score. If analyze this by territory, self efficacy for prescription was the highest by 4.81(SD=0.49), and exercise territory 4.72(SD=0.57), non-smoking territory 4.63(SD=1.10), daily activity territory 4.21(SD=0.69), diet territory 4.17(SD=0.70), psychological adaptation ability territory 4.05(SD=0.84), order of general self-efficacy 3.88(SD=0.82) in the order. 3. Self-care behavior degree that subject performed was the highest by 4.20(SD=0.59) in 5 points score. If analyze this by territory, self-care behavior for prescription was the highest by 4.57(SD=0.46), and non-smoking territory 4.56(SD=1.13), after administration territory 4.41(SD=0.59), diet territory 4.19(SD=0.68), daily life control territory 4.02(SD=0.76), and motion territory 3.72(SD=0.93) in the order. 4. They showed a statistically significant correlation between self-efficacy and self-care behavior(r=.671, p=.000). The correlations between self-care behavior and self-efficacy by sub rank territory were as follows: diet(r=.585, p=.000), daily activity(r=.533, p=.002), prescription(r=.504, p=.003), psychological adaptation ability(r=.498, p=.004), exercise(r=.352, p=.048). In conclusion, self-efficacy is the important predictive factor of self-care behavior. It seems to be necessary to enforce the self-care behavior to improve effective cardiac rehabilitation program for open heart surgery patients. And this study could be basic data to develop systematic and effective cardiac rehabilitation program.ope
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