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    ์ค‘์†Œ๊ธฐ์—…์€ํ–‰ ์‚ฌ๋ก€๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2020. 8. ๊น€๋™์šฑ.๋ณธ ์—ฐ๊ตฌ๋Š” 2014๋…„ 7์›” ์ •๋ถ€๊ฐ€ ๊ธฐ์ˆ ๊ธˆ์œต์˜ ํ™œ์„ฑํ™”๋ฅผ ํ†ตํ•˜์—ฌ ์ค‘์†Œ๊ธฐ์—…์˜ ์ž๊ธˆ์กฐ๋‹ฌ๊ฒฝ๋กœ๋ฅผ ๋‹ค์–‘ํ™”ํ•  ๋ชฉ์ ์œผ๋กœ ๊ธฐ์กด์˜ ๊ธฐ์ˆ ๊ธˆ์œต์„ ํ™•๋Œ€โ‹…๊ฐœํŽธํ•˜์—ฌ ์ถ”์ง„์ค‘์ธ TCB(Technology Credit Bureau)ํ‰๊ฐ€ ๊ธฐ๋ฐ˜์˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ์˜ ํšจ์œจ์„ฑ๊ณผ ํ•„์š”์„ฑ์„ ํ™•์ธํ•˜๊ณ ์ž ์‹œ์ž‘๋˜์—ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์ฒซ์งธ, ๊ธฐ์ˆ ๋ ฅ์„ ํ™•๋ณดํ•œ ์ค‘์†Œ๊ธฐ์—…์„ ๋ฐœ๊ตด ๋ฐ ์ง‘์ค‘์œก์„ฑํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ถ”์ง„์ค‘์ธ TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜์˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ์„ ์ง€์›๋ฐ›์€ ์ค‘์†Œ๊ธฐ์—…์ด ์ผ๋ฐ˜๋Œ€์ถœ์„ ์ง€์›๋ฐ›์€ ์ค‘์†Œ๊ธฐ์—…๋ณด๋‹ค ์–‘ํ˜ธํ•œ ์žฌ๋ฌด์„ฑ๊ณผ๋ฅผ ๋‹ฌ์„ฑํ•˜๋„๋ก ๊ธฐ์—ฌํ•˜์˜€๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ๋‘˜์งธ, ๊ธฐ์ˆ ๊ธˆ์œต ํ™œ์„ฑํ™”๋ฅผ ์œ„ํ•˜์—ฌ ๊ธฐ์—… ๋Œ€์ถœ์‹ฌ์‚ฌ์— ํ™œ์šฉ๋˜๋Š” TCBํ‰๊ฐ€์˜ ํ•ต์‹ฌ์ธ ๊ธฐ์ˆ ํ‰๊ฐ€๋“ฑ๊ธ‰(T๋“ฑ๊ธ‰)์—์„œ ์ƒ์œ„๋“ฑ๊ธ‰์„ ๋ฐ›์€ ๊ธฐ์—…๊ตฐ์ด ํ•˜์œ„๋“ฑ๊ธ‰์„ ๋ฐ›์€ ๊ธฐ์—…๊ตฐ๋ณด๋‹ค ์–‘ํ˜ธํ•œ ์žฌ๋ฌด์„ฑ๊ณผ๋ฅผ ๋‹ฌ์„ฑํ•˜๋„๋ก ๊ธฐ์—ฌํ•˜์˜€๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ๋˜ํ•œ, ์„ฑ์žฅ์„ฑ, ์ˆ˜์ต์„ฑ, ์•ˆ์ •์„ฑ ์ธก๋ฉด์—์„œ ์ง€์› ์—ฐ๋„ ๋Œ€๋น„ T+1, T+2, T+3๊ธฐ์˜ ์–‘ ์ง‘๋‹จ๊ฐ„ ์žฌ๋ฌด์„ฑ๊ณผ์˜ ์ฐจ์ด๊ฐ€ ์กด์žฌํ•˜๋Š”์ง€ ์„ฑํ–ฅ์ ์ˆ˜๋งค์นญ(PSM : Propensity Score Matching)์„ ํ†ตํ•œ ๋Œ€์กฐ๊ตฐ ์„ ๋ณ„ ํ›„, ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„(Multiple regression)์„ ํ†ตํ•˜์—ฌ ์žฌ๋ฌด์„ฑ๊ณผ์— ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š”์ง€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ์‹ค์ฆ์  ์žฌ๋ฌด์„ฑ๊ณผ ๋น„๊ต๋ถ„์„ ๊ฒฐ๊ณผ, ์„ฑ์žฅ์„ฑ ์ง€ํ‘œ์˜ ๋งค์ถœ์•ก์ฆ๊ฐ€์œจ๊ณผ ์ˆ˜์ต์„ฑ ์ง€ํ‘œ์˜ ์ž๊ธฐ์ž๋ณธ์˜์—…์ด์ต์œจ์˜ ๊ฒฝ์šฐ TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ ๋ฐ ๊ธฐ์ˆ ํ‰๊ฐ€(T)๋“ฑ๊ธ‰ ์ƒ์œ„๊ทธ๋ฃน ๋ชจ๋‘ ์ดˆ๊ธฐ์—๋Š” ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ฐœ๊ฒฌํ•˜์ง€ ๋ชปํ•˜์˜€์œผ๋‚˜, T+3๋…„์— ์ด๋ฅด๋Ÿฌ ์ผ์ • ์ˆ˜์ค€์˜ ๊ฐœ์„ ํšจ๊ณผ๋ฅผ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์•ˆ์ •์„ฑ ์ง€ํ‘œ์˜ ์ž๊ธฐ์ž๋ณธ์ฆ๊ฐ€์œจ์˜ ๊ฒฝ์šฐ T+1๋…„์—๋Š” ์ผ๋ฐ˜ ์ง€์›๊ธฐ์—…๊ณผ ๋น„๊ตํ•˜์—ฌ ์—ด์œ„๋ฅผ ๋‚˜ํƒ€๋‚ด์—ˆ์œผ๋‚˜, ์ดํ›„์—๋Š” ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋‚˜ํƒ€๋‚ด์ง€ ์•Š์•„ ๋‹จ๊ธฐ์  ์—ด์œ„๋ฅผ ๋‹ค์†Œ ๊ฐœ์„ ํ•œ ๊ฒƒ์œผ๋กœ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฐ™์€ ํ•ญ๋ชฉ์—์„œ ๊ธฐ์ˆ ํ‰๊ฐ€(T)๋“ฑ๊ธ‰ ์ƒ์œ„๊ทธ๋ฃน์˜ ๊ฒฝ์šฐ ์ดˆ๊ธฐ์—๋Š” ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋‚˜ํƒ€๋‚ด์ง€ ์•Š์•˜์œผ๋‚˜ T+2๋…„ ์ดํ›„๋ถ€ํ„ฐ ๋น„๊ต์ง‘๋‹จ ๋Œ€๋น„ ๊ธ์ •์  ๊ฐœ์„ ํšจ๊ณผ๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜์˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ ์ง€์›๊ธฐ์—…์ด ์ผ๋ฐ˜ ์ค‘์†Œ๊ธฐ์—…์— ๋น„ํ•ด ์„ฑ์žฅ์„ฑ, ์ˆ˜์ต์„ฑ, ์•ˆ์ •์„ฑ์— ์ธก๋ฉด์—์„œ ๋‹จ๊ธฐ์  ํšจ๊ณผ๋ณด๋‹ค๋Š” ์ค‘๊ธฐ์  ํšจ๊ณผ๋ฅผ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ธฐ์ˆ ํ‰๊ฐ€๋“ฑ๊ธ‰์„ ํ†ตํ•˜์—ฌ ๊ธฐ์ˆ ๋ ฅ์ด ๋” ์šฐ์ˆ˜ํ•˜๋‹ค๊ณ  ์ธ์ •๋ ์ˆ˜๋ก ๊ทธ ํšจ๊ณผ๋ฅผ ์ƒ๋Œ€์ ์œผ๋กœ ๋” ํฌ๊ฒŒ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ผ์ • ๋ถ€๋ถ„ ์˜๋ฏธ ์žˆ๋Š” ๊ฒฐ๋ก ์„ ๋„์ถœํ•˜์˜€๋‹ค.In July 2014, the government expanded and reorganized existing technology financing to diversify the funding channels for small and medium enterprises through the revitalization of technology financing. This study was initiated to identify the efficiency and necessity of small business loans based on the Technology Credit Bureau (TCB) assessment. To this end, we first examined whether small and medium-sized enterprises that received TCB-based loans contributed to achieving better financial performance than those that received general loans. Second, to facilitate technology financing, we looked at whether the group of companies that received the highest rating in the technology evaluation (T-rated), which is the core of the TCB evaluation used in the corporate loan review, contributed to achieving better financial performance than the group of companies that received the lower grade. In addition, a control group screening (PSM) to determine whether there is a difference in financial performance between the two groups in terms of growth, profitability and stability compared to the support year(T+1, T+2 and T+3), and a multi-regression analysis to confirm whether there are significant differences in financial performance. Comparative analysis of empirical financial performance found no significant difference in the initial period between the TCB-based loan and the T-rated upper group for the growth index and the return on equity operations of the profitability index. However, a certain level of improvement could be estimated by T+3 and the equity increase rate in the stability index was inferior to that of the general support company in T+1, but later it was estimated that the short-term position was somewhat improved because it did not show any significant difference. In the same category, the T-rated higher groups did not initially show significant differences, but it could be estimated that there would be a positive improvement over the comparative group from T+2. This led to some meaningful conclusions that TCB-based loan-supporting entities could expect medium-term effects rather than short-term effects in terms of growth, profitability and stability over comparators, and that the more technology is recognized through technology ratings, the greater the effect.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฐฉ๋ฒ• 5 ์ œ 2 ์žฅ ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  7 ์ œ 1 ์ ˆ ์ค‘์†Œ๊ธฐ์—… 7 ์ œ 2 ์ ˆ ์ค‘์†Œ๊ธฐ์—… ์ •์ฑ…๊ธˆ์œต 9 ์ œ 3 ์ ˆ ๊ธฐ์ˆ ๊ธˆ์œต 12 1. ๊ธฐ์ˆ ๊ธˆ์œต์˜ ์˜์˜ 12 2. ๊ธฐ์ˆ ๊ธˆ์œต ํ˜„ํ™ฉ 14 3. TCBํ‰๊ฐ€ ๊ฐœ์š” 16 4. TCB์˜ ํ‰๊ฐ€๋‚ด์šฉ 18 ์ œ 4 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  21 1. ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  21 2. ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 23 ์ œ 3 ์žฅ ์—ฐ๊ตฌ์„ค๊ณ„ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 24 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ชจํ˜• ๋ฐ ๊ฐ€์„ค์„ค์ • 24 1. ์—ฐ๊ตฌ๋ชจํ˜• 24 2. ๊ฐ€์„ค์„ค์ • 26 ์ œ 2 ์ ˆ ๋ณ€์ˆ˜์„ค์ • 28 1. ์ข…์†๋ณ€์ˆ˜ 28 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 29 3. ํ†ต์ œ๋ณ€์ˆ˜ 29 ์ œ 3 ์ ˆ ์ž๋ฃŒ์˜ ์ˆ˜์ง‘๊ณผ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 30 1. ์ž๋ฃŒ์˜ ์ˆ˜์ง‘ 30 2. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 31 2.1 ์„ฑํ–ฅ์ ์ˆ˜๋งค์นญ(Propensity Score Matching).................. 31 2.2 ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„(Multiple Regression)................................ 32 ์ œ 4 ์žฅ ์‹ค์ฆ๋ถ„์„๊ฒฐ๊ณผ 34 ์ œ 1 ์ ˆ ๊ธฐ์ˆ ์  ํ†ต๊ณ„๋ถ„์„ 34 ์ œ 2 ์ ˆ ๋ณ€์ˆ˜ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 39 ์ œ 3 ์ ˆ TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜ ๋ฐ ์ผ๋ฐ˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ ์ง€์›๊ธฐ์—… ๋น„๊ต ๋ถ„์„ 45 1. ์„ฑ์žฅ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 45 1.1 ๋งค์ถœ์•ก์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 45 1.2 ์ด์ž์‚ฐ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 46 2. ์ˆ˜์ต์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 47 2.1 ์ž๊ธฐ์ž๋ณธ์˜์—…์ด์ต์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 47 3. ์•ˆ์ •์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 48 3.1 ๋ถ€์ฑ„์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 48 3.2 ์ž๊ธฐ์ž๋ณธ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 49 ์ œ 4 ์ ˆ ๊ธฐ์ˆ ํ‰๊ฐ€(T)๋“ฑ๊ธ‰ ์ƒํ•˜์œ„๊ทธ๋ฃน ๋น„๊ต๋ถ„์„ 51 1. ์„ฑ์žฅ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 51 1.1 ๋งค์ถœ์•ก์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 51 1.2 ์ด์ž์‚ฐ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 52 2. ์ˆ˜์ต์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 53 2.1 ์ž๊ธฐ์ž๋ณธ์˜์—…์ด์ต์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 53 3. ์•ˆ์ •์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 54 3.1 ๋ถ€์ฑ„์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 54 3.2 ์ž๊ธฐ์ž๋ณธ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 55 ์ œ 5 ์žฅ ๊ฒฐ๋ก  57 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ ๋ฐ ์‹œ์‚ฌ์  57 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 59 ์ฐธ๊ณ ๋ฌธํ—Œ 61 Abstract 64Maste

    (A) study about building-related health symptoms of workers at dental collage hospitals in Seoul : ์„œ์šธ์‹œ๋‚ด ์†Œ์žฌ ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ™˜๊ฒฝ๋ณด๊ฑดํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์€ ๋งŽ์€ ๊ณ ๊ฐ(ํ™˜์ž)๋“ค์ด ์™•๋ž˜ํ•˜๊ณ , ๋‹ค์–‘ํ•œ ์œ ํ•ดํ™˜๊ฒฝ์ด ์กด์žฌํ•˜๊ณ  ์žˆ์–ด ์—ฌ๋Š ๋นŒ๋”ฉ์˜ ์‹ค๋‚ด๊ณต๊ฐ„๋ณด๋‹ค ๋” ๋งŽ์€ ์˜ค์—ผ๋ฌผ์งˆ์— ๋…ธ์ถœ๋  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์˜ ํšจ์œจ์ ์ธ ์‹ค๋‚ด๊ณต๊ธฐ์งˆ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์ข…์‚ฌ์ž๋“ค์ด ๊ฒฝํ—˜ํ•˜๋Š” ์‹ค๋‚ด์ž๊ฐ์ฆ์ƒ์„ ์กฐ์‚ฌํ•˜๊ณ , ๊ฐ ํŠน์„ฑ์„ ๋Œ€๋ณ€ํ•˜๋Š” ๋ณ€์ˆ˜๋“ค๊ณผ์˜ ๊ด€๋ จ์„ฑ์„ ํ‰๊ฐ€ํ•˜์—ฌ ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์˜ ์‹ค๋‚ดํ™˜๊ฒฝ ๊ฐœ์„ ์„ ๋„๋ชจํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์„œ์šธ์‹œ๋‚ด์— ์†Œ์žฌํ•œ ์„ธ ๊ฐœ์˜ ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์› ์ข…์‚ฌ์ž 682๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์—ฌ 2004๋…„ 9์›” 20์ผ๋ถ€ํ„ฐ 10์›” 8์ผ๊นŒ์ง€ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ ์ง€ํ‘œ๋กœ๋Š” THI(Todai Health Index)์˜ ๋ฌธํ•ญ ์ค‘ ๋นŒ๋”ฉ์ฆํ›„๊ตฐ๊ณผ ๊ด€๋ จํ•œ 39๋ฌธํ•ญ์„ ๋ฐœ์ทŒํ•˜์—ฌ ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ, ํ†ต๊ณ„๋ถ„์„์€ SAS 8.01 ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ t-test, ๋ถ„์‚ฐ๋ถ„์„ ๋ฐ ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์› ์ข…์‚ฌ์ž๋“ค์€ ๋นŒ๋”ฉ ๋‚ด ์†Œ์Œ, ๋ถˆ์ถฉ๋ถ„ํ•œ ํ™˜๊ธฐ์ƒํƒœ, ๋จผ์ง€ ๋ฐ ๊ฑด์กฐํ•จ์œผ๋กœ ์ธํ•ด ์น˜๊ณผ๋ณ‘์› ๋‚ด ์‹ค๋‚ดํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์ธ์ง€๋„๋ฅผ ๋‚ฎ๊ฒŒ ํ‰๊ฐ€ํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ผ๋ฐ˜์  ํŠน์„ฑ๊ณผ ๊ด€๋ จํ•œ ์š”์ธ์œผ๋กœ๋Š” ์„ฑ๋ณ„, ์ง์ข…, ๊ทผ๋ฌด๋…„์ˆ˜, ์—…๋ฌด๋งŒ์กฑ, ์ˆ˜๋ฉด์‹œ๊ฐ„, ์ฝ˜ํ…ํŠธ๋ Œ์ฆˆ ์ฐฉ์šฉ์—ฌ๋ถ€๊ฐ€ ์˜๋ฏธ ์žˆ๋Š” ๋ณ€์ˆ˜๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋‚จ์ž์— ๋น„ํ•ด ์—ฌ์ž๊ฐ€, ์ผ๋ฐ˜์‚ฌ๋ฌด์ง์— ๋น„ํ•ด ์น˜๊ณผ์˜์‚ฌ๊ฐ€, ์˜ค๋ž˜ ๊ทผ๋ฌดํ•œ ์ข…์‚ฌ์ž๋ณด๋‹ค 1๋…„ ๋ฏธ๋งŒ์˜ ์ข…์‚ฌ์ž๊ฐ€, ์—…๋ฌด์— ๋งŒ์กฑํ•œ๋‹ค๊ณ  ์‘๋‹ตํ•œ ์ข…์‚ฌ์ž๋ณด๋‹ค ๋งŒ์กฑํ•˜์ง€ ์•Š๋Š”๋‹ค๊ณ  ์‘๋‹ตํ•œ ์ข…์‚ฌ์ž๊ฐ€, ๊ทธ๋ฆฌ๊ณ  ์ˆ˜๋ฉด์‹œ๊ฐ„์ด ์ ์„์ˆ˜๋ก, ์ฝ˜ํ…ํŠธ๋ Œ์ฆˆ๋ฅผ ์ฐฉ์šฉํ• ์ˆ˜๋ก ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ ํ‰๊ท  ์ ์ˆ˜๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. ๊ทผ๋ฌด์กฐ๊ฑด, ๊ฑด๋ฌผ ๋ฐ– ์™ธ์ถœํšŸ์ˆ˜, ์—ฌ๋ฆ„๊ณผ ๊ฒจ์šธ ์ž์—ฐํ™˜๊ธฐ, ์‹ค๋‚ด๊ณต๊ธฐํ™˜๊ฒฝ๊ณผ ๊ฐ™์€ ์ผ๋ฐ˜์  ๊ทผ๋ฌดํ™˜๊ฒฝ๊ณผ ๊ด€๋ จํ•œ ์š”์ธ๋„ ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ง„๋ฃŒ์‹ค์—์„œ ๊ทผ๋ฌดํ• ์ˆ˜๋ก, ๊ฑด๋ฌผ ๋ฐ– ์™ธ์ถœํšŸ์ˆ˜๊ฐ€ ์ ์„์ˆ˜๋ก, ์ž์—ฐํ™˜๊ธฐ ํšŸ์ˆ˜๊ฐ€ ์ ์„์ˆ˜๋ก, ์‹ค๋‚ด๊ณต๊ธฐ๊ฐ€ ๋ถˆ์พŒํ•˜๋‹ค๊ณ  ๋Š๋‚„์ˆ˜๋ก ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ ํ‰๊ท ์ ์ˆ˜๊ฐ€ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. ์น˜๊ณผ์˜๋ฃŒ ํ–‰์œ„์™€ ๊ด€๋ จ๋œ ์ง„๋ฃŒํ™˜๊ฒฝ ์ค‘์—์„œ๋Š” ์†Œ๋…์šฉ์•Œ์ฝœ๊ณผ ๋ ˆ์ง„๋ฅ˜(monomerํฌํ•จ)์‚ฌ์šฉ ์œ ๋ฌด๊ฐ€ ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ณ€์ˆ˜๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ด์ƒ์˜ ์—ฐ๊ตฌ์— ์˜ํ•˜๋ฉด, ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์€ ํŠน์ˆ˜ํ•œ ์น˜๊ณผ์˜๋ฃŒ ํ–‰์œ„๋กœ ์ธํ•ด ๋งŽ์€ ์†Œ์Œ, ๋ถ„์ง„ ๋ฐ ์•…์ทจ๋ฅผ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ๋Š” ์‹ค๋‚ดํ™˜๊ฒฝ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ์กฐ์‚ฌ๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์‹ค๋‚ดํ™˜๊ฒฝ ์š”์ธ๋“ค์ด ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์› ์ข…์‚ฌ์ž๋“ค์ด ๋Š๋ผ๋Š” ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์—ˆ๋‹ค. ์ด์— ์น˜๊ณผ์˜๋ฃŒ ํ–‰์œ„์™€ ๊ด€๋ จ๋œ ํŠน์ˆ˜ํ•œ ์‹ค๋‚ดํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์ ์ ˆํ•œ ๊ด€๋ฆฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค๊ณ  ๋ณธ๋‹ค. [์˜๋ฌธ]Indoor air pollution has become a big concern at dental college hospitals, because patients are crowded and they have more harmful conditions than other buildings. In this study, building-related health recognition symptoms of various workers in dental college hospitals are surveyed and analyzed in order to improve indoor environment at dental college hospitals. The sample of this study is 682 workers in three dental college hospitals located in Seoul from September 20 to October 8, 2004. Sampled workers respond 39 Sick Building Syndrome-related items selected from Todai Health Index(THI), and the models of t-test, ANOVA, and multiple regression are applied for statistical analysis by using version sas 8.01. Most workers at dental hospitals complained about noise, poor ventilation, lots of dust, and air dryness. Building-related health recognition symptoms are significantly related to gender, tasks, working experience, job-satisfaction, sleeping hours and wearing contact lens. Females rather than males, dentists rather than office workers, less-than-1-year workers rather than more-than-1-year workers, less sleeping workers, less satisfied workers, and workers wearing contact lens tend to report more building-related health recognition symptoms. Also working places and ventilation are significantly related to the symptom. That is, workers report more building-related health recognition symptoms when working at a treatment office, less going out of a building, having less natural ventilation, and feeling uncomfortable about indoor air. Building-related health recognition symptoms scores are significantly high as using sterilization alcohol and resin type materials(including monomer). Based on the results, it can be said that special dental treatment causes undesirable environment such as noise, dust, and bad smell. It is also related to building related health recognition symptoms reported by workers at dental hospitals. So managemental efforts are needed to improve indoor environment which is related dental treatment. Keywords:sick building syndrome, indoor air quality, building related health recognition symptoms, natural ventilation.ope

    ์• ๋„๋ฆฌ์ŠคํŠธ์˜ ์ถ”์ฒœ ์˜๊ฒฌ ๋ณ€๊ฒฝ์— ๋Œ€ํ•œ ์ •๋ณดํšจ๊ณผ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ฒฝ์˜ํ•™๊ณผ ๊ฒฝ์˜ํ•™์ „๊ณต,2002.Maste
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