48 research outputs found

    A Corpus-based Study on Whom and Who in the Preposed PP

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜์–ด์˜๋ฌธํ•™๊ณผ, 2017. 2. ์†์ฐฝ์šฉ.Piles of researches covered the use of whom and who, and the differences between them. Most of them argued that not only in the subject position but also in positions that were originally thought of as whom-only areas, who seems to appear. Nevertheless, scholars such as Jespersen (1969), Sohn (1978), Quirk et al. (1985), Walsh and Walsh (1989), and Bauer (1994) claimed that there still exists an exclusive area for whom, and this is known to be a preposed PP. The term refers to a prepositional phrase that has been moved to the front from the following clause behind. This paper searched for whom and who in the preposed PP from two big corpora (COHA and COCA spoken data), and compared them to see if whom was exclusively used in that position. It turned out that when used with a preposition, who (although not as many as whom) could be found to a certain extent. However, in the preposed PP, whom-only area, who was seldom used and even nonexistent in some prepositional phrase. The result was quite the contrary to that of whom and who found in the postverbal position. Here, who was used as equally as, or even more (with some verbs) than whom. In addition, from the data organized by genre, this paper could also find that whom itself triggers a formal register. The possible explanation for such results is that the preposed PP has been a formal register throughout the history. The preposed PP was believed to be a more graceful and perspicuous expression. It has been perceived as more natural, formal, and grammatical than preposition stranding ever since the Middle English. Accordingly, we can assume that in a formal register like the preposed PP, whom is exclusively used because it triggers a formal register, too. Based on those findings, this study concludes that the preposed PP is indeed an exclusive area for whom, and that whom would last, or at least, it would take a very long time for who to finally replace the place of whom in the preposed PP.Chapter 1. Introduction 1 1.1 Introduction 1 1.2 Organization of the Study 3 Chapter 2. Previous Studies and Research Questions 4 2.1 Previous Studies 4 2.1.1 Controversy over Areas for Whom and Who 4 2.1.2 History of Whom and Who 6 2.1.3 Lee (2010)'s Study 9 2.2 Research Questions 11 Chapter 3. Data Analysis and Results 14 3.1 Data and Method 14 3.1.1 Data 14 3.1.1.1 Corpus of Historical American English (COHA) 15 3.1.1.2 Corpus of Contemporary American English (COCA) 15 3.1.2 Method 16 3.1.2.1 Preposition selection 16 3.1.2.2 Random sampling 17 3.2 Data Analysis 18 3.2.1 Preposition+Whom/Who in COHA 18 3.2.1.1 Preposed PP criterion 22 3.2.1.2 To/For/With+whom 24 3.2.1.3 To/For/With+who 28 3.2.2 Preposition+Who in COCA Spoken Data 36 3.2.2.1 To who 38 3.2.2.2 For who 40 3.2.2.3 With who 41 3.3 Summary 44 3.3.1 Summarized Results 44 3.3.2 Whom versus Who 46 Chapter 4. Discussions 51 4.1 Pied-piping and Preposition Stranding 52 4.2 Preposed PP and Formality 53 4.3 Other Hypotheses 58 Chapter 5. Conclusion 62 5.1 Summary 62 5.2 Limitations and Further Studies 63 Bibliography 65 ๊ตญ๋ฌธ์ดˆ๋ก 71Maste

    ์ •์ฑ…๊ณผ์ •์—์„œ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ์—ญํ•  - ์ œ์ฃผ๋ฏผ๊ตฐ๋ณตํ•ฉํ˜•๊ด€๊ด‘๋ฏธํ•ญ ์ •์ฑ… ๋ณ€๋™๊ณผ์ •์„ ์ค‘์‹ฌ์œผ๋กœ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› : ํ–‰์ •ํ•™๊ณผ, 2015. 2. ๊ธˆํ˜„์„ญ.์ •์ฑ…์€ ์‚ด์•„์žˆ๋Š” ์ƒ๋ช…์ฒด์ฒ˜๋Ÿผ ๋Š์ž„์—†์ด ๋ณ€ํ™”ํ•˜๊ณ  ์ง„ํ™”ํ•œ๋‹ค. ๋ณต์žกํ•˜๊ณ  ๋†’์€ ์ „๋ฌธ์„ฑ์ด ์š”๊ตฌ๋˜๋Š” ํ˜„๋Œ€์‚ฌํšŒ์—์„œ ์ด๋Ÿฌํ•œ ์ •์ฑ…๋ณ€๋™ ๊ณผ์ •์˜ ์ฃผ์š” ํ–‰์œ„์ž๋Š” ํ–‰์ •๋ถ€๋ผ๋Š” ๊ฒƒ์ด ์ผ๋ฐ˜์ ์ธ ์‹œ๊ฐ์ด๋‹ค. ํŠนํžˆ ๊ตญ๋ฐฉ์ •์ฑ…์€ ๋‹ค๋ฅธ ๋ถ„์•ผ์— ๋น„ํ•ด ๊ณ ๋„์˜ ์ „๋ฌธ์„ฑ๊ณผ ๋ณด์•ˆ์„ฑ์ด ์š”๊ตฌ๋˜๋Š” ๋ถ„์•ผ๋กœ ๊ตญํšŒ๋‚˜ ์ง€๋ฐฉ์˜ํšŒ์˜ ์ ‘๊ทผ์„ฑ๊ณผ ์ •์ฑ…๊ฒฐ์ •๊ถŒ์ด ๋”์šฑ ํฌ๊ฒŒ ์ œํ•œ๋˜์–ด ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์šฐ๋ฆฌ์‚ฌํšŒ์˜ ๋‹ค์›ํ™”, ๋ฏผ์ฃผํ™”, ์ง€๋ฐฉํ™”๋กœ ๊ตญ๋ฐฉ์˜์—ญ์—์„œ ๊ธˆ๊ธฐ์‹œ๋˜์—ˆ๋˜ ์ด์ตยท๊ฐ€์น˜๊ฐˆ๋“ฑ์ด ์ˆ˜๋ฉด์œ„๋กœ ๋ถ€์ƒํ•˜๊ฒŒ ๋˜์—ˆ๊ณ , ๊ตญ๋ฐฉ์ •์ฑ…์— ์žˆ์–ด์„œ๋„ ๊ตญ๋ฏผ์˜ ๋Œ€์˜๊ธฐ๊ด€์ธ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ์ง€์ง€๊ฐ€ ์ „์ œ๋˜์–ด์•ผ ์„ฑ๊ณต์ ์ธ ์ง‘ํ–‰์ด ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ •์ฑ…๋ณ€๋™๊ณผ์ •์—์„œ์˜ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ๋Š” ์–ด๋– ํ•œ ์—ญํ• ์„ ํ•˜๋ฉฐ, ์„ฑ๊ณต์ ์ธ ์ •์ฑ…์ถ”์ง„์„ ์œ„ํ•ด ์ •๋ถ€๋Š” ์–ด๋– ํ•œ ๋…ธ๋ ฅ์„ ํ•ด์•ผ ํ•˜๋Š”๊ฐ€? ๋ผ๋Š” ๋ฌธ์ œ์˜์‹ ํ•˜์—์„œ ์ •์ฑ…์˜ ๋ณ€๋™๊ณผ์ •์„ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ์—ญํ• ์„ ์ค‘์‹ฌ์œผ๋กœ ๋ถ„์„ํ•ด ๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ถ„์„์‚ฌ๋ก€๋กœ ๊ตญ๋ฐฉ์ •์ฑ… ์ค‘ ๋Œ€ํ‘œ์ ์ธ ์ •์ฑ…๋ณ€๋™ ์‚ฌ๋ก€์ธ ์ œ์ฃผ๋ฏผ๊ตฐ๋ณตํ•ฉํ˜•๊ด€๊ด‘๋ฏธํ•ญ ๊ฑด์„ค ์‚ฌ์—…์„ ์„ ์ •ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ œ์ฃผ๋ฏผ๊ตฐ๋ณตํ•ฉํ•ญ ์‚ฌ์—…์˜ ๋ณ€๋™๊ณผ์ •์„ Kingdon์˜ ์ •์ฑ…ํ๋ฆ„ ๋ชจํ˜•๊ณผ ์ฒด์ œ์ด๋ก ์„ ์ ์šฉํ•˜์—ฌ ์ฒซ์งธ, ์ œ์ฃผํ•ด๊ตฐ๊ธฐ์ง€ ์‚ฌ์—…์˜ ์˜์ œํ™” ๊ณผ์ •, ๋‘˜์งธ, ํˆฌ์ž… ํ›„ ์ •์น˜์ฒด์ œ ๋‚ด ์ „ํ™˜ ๋‹จ๊ณ„์—์„œ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ๊ฐ€ Kingdon์˜ ์„ธ ๊ฐ€์ง€ ํ๋ฆ„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ, ์…‹์งธ, ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ๊ฐ€ ์ •์ฑ…์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ฐฉ์‹์˜ ์ฐจ์ด์ ์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์—ฐ๊ตฌ๊ฒฐ๊ณผ ์ฒซ์งธ, ์ œ์ฃผํ•ด๊ตฐ๊ธฐ์ง€ ์‚ฌ์—…์˜ ์˜์ œํ™” ๊ณผ์ •์€ Kingdon์˜ ์„ธ๊ฐ€์ง€ ํ๋ฆ„์˜ ๊ฒฐํ•ฉ์œผ๋กœ ์„ค๋ช…์ด ๊ฐ€๋Šฅํ•˜๊ณ , ๋‘˜์งธ, ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ๋Š” ๋ฌธ์ œ์˜ ํ๋ฆ„์„ ๋ถ„ํ™”์‹œํ‚ค๊ณ , ์ •์ฑ… ํ๋ฆ„์˜ ์†๋„ ์กฐ์ ˆ, ๋‚ด์šฉ์˜ ์ˆ˜์ •ยท๋ณด์™„์— ์˜ํ–ฅ์„ ๋ฏธ์ณค์œผ๋ฉฐ, ์ •์น˜์˜ ํ๋ฆ„์„ ํ†ตํ•ด ํ๋ฆ„์˜ ์žฌ๊ฒฐํ•ฉ์„ ๊ฒฐ์ •์ง“๋Š”๋‹ค๋Š” ์‚ฌ์‹ค์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์…‹์งธ, ๊ตญํšŒ๋Š” ์ฃผ๋กœ ์˜ˆ์‚ฐ์˜ ์‹ฌ์‚ฌ๋ฅผ ํ†ตํ•ด ๊ฐ€์žฅ ์‹ค์งˆ์ ์œผ๋กœ ์ •์ฑ…์˜ ๋ชฉํ‘œ๋ฅผ ๊ฒฐ์ •์ง€์—ˆ๊ณ , ์ œ์ฃผ๋„์˜ํšŒ๋Š” ํ–‰์ •์ ˆ์ฐจ์™€ ๊ด€๋ จํ•œ ๋™์˜๊ถŒ ์œ ๋ณด๋ฅผ ํ†ตํ•ด ์‚ฌ์—…์˜ ์ถ”์ง„ ์†๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ ์ž ํ–ˆ๋‹ค๋Š” ๊ฒƒ ์—ญ์‹œ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋ก ์ ์œผ๋กœ๋Š” Kingdon์˜ ์„ธ ๊ฐ€์ง€ ํ๋ฆ„์ด ์ •์ฑ…๋ณ€๋™์˜ ์ „ ๊ณผ์ •์—์„œ ๋ณ€ํ™”ํ•˜๋Š” ๊ณผ์ •์„ ์ถ”์ ํ•จ์œผ๋กœ์จ ์ •์ฑ…์˜ ์—ญ๋™์  ๋ณ€๋™ ํ˜„์ƒ์„ ๋ณด๋‹ค ์ž์„ธํžˆ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ , ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ๋ผ๋Š” ๋‘ ๊ฐ€์ง€ ์ฐจ์›์˜ ์ •์น˜์ฒด์ œ์˜ ํ™œ๋™ ์–‘์ƒ์„ ๋ถ„์„ํ•จ์œผ๋กœ์จ ์ •๋ถ€์˜ ๋‹ค์ฐจ์›์  ๋Œ€์‘์ „๋žต ๋งˆ๋ จ์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ๊ฐ€ ํ–‰์‚ฌํ•  ์ˆ˜ ์žˆ๋Š” ๋ชจ๋“  ๊ถŒํ•œ์— ๋Œ€ํ•ด ์ข…ํ•ฉ ๋ถ„์„ํ•จ์œผ๋กœ์จ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ์—ญํ• ์— ๋Œ€ํ•œ ์„ค๋ช…๋ ฅ์„ ๋†’์˜€๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ ์ •์ฑ…์ ์œผ๋กœ๋Š” ์ •๋ถ€์˜ ์„ฑ๊ณต์ ์ธ ์ •์ฑ… ์ถ”์ง„์„ ์œ„ํ•ด์„œ ๊ตญํšŒ, ์ง€๋ฐฉ์˜ํšŒ์˜ ์ง€์ง€ ํš๋“์ด ํ•„์ˆ˜์ ์ด๋ฉฐ, ์ •๋ถ€์˜ ๋Œ€๊ตญ๋ฏผ ์‹ ๋ขฐ ๊ตฌ์ถ•, ๊ตฐ์˜ ์ด๋ฏธ์ง€ ๊ฐœ์„ ์ด ์ ˆ์‹คํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, CNDP์™€ ๊ฐ™์€ ์ค‘๋ฆฝ์ ์ธ ๊ณต๋ก ๊ธฐ๊ด€ ์„ค์น˜๊ฐ€ ํ•„์š”ํ•˜๋ฉฐ, ๋ฌด์—‡๋ณด๋‹ค๋„ ์„ฑ์ˆ™ํ•œ ์‹œ๋ฏผ์˜์‹์ด ์ค‘์š”ํ•˜๋‹ค๋Š” ์‹œ์‚ฌ์ ์„ ์–ป์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค.์ œ1์žฅ ์„œ ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  ๋ฐ ํ•„์š”์„ฑ 1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฒ”์œ„ 3 1. ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ 3 2. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ 5 ์ œ2์žฅ ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  6 ์ œ1์ ˆ ์ด๋ก ์  ๋…ผ์˜ 6 1. ์ •์ฑ…๋ณ€๋™์— ๊ด€ํ•œ ์ด๋ก ์  ๋…ผ์˜ 6 1) ์ •์ฑ…๋ณ€๋™์˜ ๊ฐœ๋… 6 2) ์ •์ฑ…๋ณ€๋™์— ๊ด€ํ•œ ์ด๋ก  7 3) ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•๊ณผ ์ฒด์ œ๋ชจํ˜• 9 2. ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์— ๊ด€ํ•œ ์ด๋ก ์  ๋…ผ์˜ 11 1) ์ •์น˜์ฒด์ œ๋กœ์„œ์˜ ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ 11 2) ์ •์ฑ…๊ณผ์ •์— ์žˆ์–ด ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ๊ธฐ๋Šฅ๊ณผ ์—ญํ•  12 ์ œ2์ ˆ ์„ ํ–‰์—ฐ๊ตฌ๊ฒ€ํ†  14 1. ์ œ์ฃผ๋ฏผ๊ตฐ๋ณตํ•ฉํ•ญ ๊ฑด์„ค์‚ฌ์—…์— ๋Œ€ํ•œ ์—ฐ๊ตฌ 14 2. ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ์ •์ฑ…๊ณผ์ •์— ๋Œ€ํ•œ ์˜ํ–ฅ ์—ฐ๊ตฌ 16 3. ์„ ํ–‰์—ฐ๊ตฌ์˜ ๋ฌธ์ œ์  18 ์ œ3์žฅ ์—ฐ๊ตฌ์„ค๊ณ„ 19 ์ œ1์ ˆ ์—ฐ๊ตฌ๋ฌธ์ œ ๋ฐ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 19 1. ์—ฐ๊ตฌ๋ฌธ์ œ 19 2. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 19 ์ œ2์ ˆ ๋ถ„์„์˜ ํ‹€ 20 ์ œ3์ ˆ ๋ถ„์„์˜ ๋ณ€์ˆ˜ 22 1. ๋ฌธ์ œ์˜ ํ๋ฆ„ 22 2. ์ •์น˜์˜ ํ๋ฆ„ 22 3. ์ •์ฑ…์˜ ํ๋ฆ„ 22 4. ์ •์ฑ…์˜ ์ฐฝ 23 5. ๊ตญํšŒ์™€ ์ง€๋ฐฉ์˜ํšŒ์˜ ๊ถŒํ•œ 24 ์ œ4์žฅ ์˜์ œ์„ค์ • ๋ฐ ํˆฌ์ž…๋‹จ๊ณ„ (2002. 5. โˆผ 2005. 8.) 24 ์ œ1์ ˆ ์ง„ํ–‰๊ฒฝ๊ณผ 24 ์ œ2์ ˆ ์ •์ฑ…ํ๋ฆ„ ๋ชจํ˜•์— ์˜ํ•œ ๋ถ„์„ 27 1. ๋ฌธ์ œ์˜ ํ๋ฆ„ 27 1) ํ‰ํ™”์˜ ์„ฌ ์ •์ฑ…๊ณผ์˜ ์–‘๋ฆฝ๊ฐ€๋Šฅ์„ฑ 27 2) ์ง€์—ญ๊ฒฝ์ œ ๋ฐœ์ „ ํšจ๊ณผ 28 2. ์ •์น˜์˜ ํ๋ฆ„ 29 1) ์—ฌ๋ก ์˜ ๋ณ€ํ™” 29 2) ์„ ๊ฑฐ์™€ ๊ณต์•ฝ 31 3. ์ •์ฑ…์˜ ํ๋ฆ„ 32 4. ์ •์ฑ…์˜ ์ฐฝ 33 ์ œ5์žฅ ์ฒด์ œ๋‚ด ์ „ํ™˜๋‹จ๊ณ„์ •์ฑ… 1๊ธฐ(2005. 9.โˆผ2008. 9.) 34 ์ œ1์ ˆ ์ง„ํ–‰๊ฒฝ๊ณผ 34 ์ œ2์ ˆ ๊ตญํšŒ์˜ ์˜์‚ฌ๊ฒฐ์ • 37 1. ์˜ˆ์‚ฐ ์‹ฌ์‚ฌ๊ถŒ 37 1) 2006๋…„โˆผ2007๋…„ ์˜ˆ์‚ฐ ์‹ฌ์‚ฌ 37 2) 2008๋…„ ์˜ˆ์‚ฐ ์‹ฌ์‚ฌ 38 2. ๋Œ€์ •๋ถ€๊ฒฌ์ œ๊ถŒ 39 1) ๋Œ€์ •๋ถ€์งˆ๋ฌธ 40 2) ๊ตญ์ •๊ฐ์‚ฌ 40 ์ œ3์ ˆ ์ง€๋ฐฉ์˜ํšŒ์˜ ์˜์‚ฌ๊ฒฐ์ • 41 1. ์ง‘ํ–‰๊ธฐ๊ด€ ๊ฒฌ์ œ๊ถŒ 41 1) ๋„์ •์งˆ๋ฌธ 41 2) ๊ตฐ์‚ฌ๊ธฐ์ง€๊ฑด์„ค๊ด€๋ จํŠน๋ณ„์œ„์›ํšŒ 42 3) ํ–‰์ •์‚ฌ๋ฌด์กฐ์‚ฌ 44 ์ œ4์ ˆ ๊ฐ ํ๋ฆ„์˜ ๋ณ€ํ™”์™€ ์ •์ฑ…์˜ ์ฐฝ 45 1. ๋ฌธ์ œ์˜ ํ๋ฆ„์˜ ๋ณ€ํ™” 45 1) ์ž…์ง€๊ฐˆ๋“ฑ 45 2) ๊ณต๊ตฐ์ „๋žต๊ธฐ์ง€ ๊ฑด์„ค, ์–‘ํ•ด๊ฐ์„œ ์‚ฌ์ „ ์œ ์ถœ 47 2. ์ •์น˜์˜ ํ๋ฆ„์˜ ๋ณ€ํ™” 48 1) ์—ฌ๋ก ์˜ ๋ณ€ํ™” 48 2) ์„ ๊ฑฐ์™€ ๊ณต์•ฝ 49 3. ์ •์ฑ…์˜ ํ๋ฆ„์˜ ๋ณ€ํ™” 50 4. ์ •์ฑ…์˜ ์ฐฝ 52 ์ œ6์žฅ ์ฒด์ œ๋‚ด ์ „ํ™˜๋‹จ๊ณ„ : ์ •์ฑ… 2๊ธฐ(2008. 9.โˆผ2013. 12.) 53 ์ œ1์ ˆ ์ง„ํ–‰๊ฒฝ๊ณผ 53 ์ œ2์ ˆ ๊ตญํšŒ์˜ ์˜์‚ฌ๊ฒฐ์ • 56 1. ์˜ˆ์‚ฐ ์‹ฌ์‚ฌ๊ถŒ 56 1) 2009๋…„โˆผ2011๋…„ ์˜ˆ์‚ฐ ์‹ฌ์‚ฌ 56 2) 2012๋…„โˆผ2013๋…„ ์˜ˆ์‚ฐ ์‹ฌ์‚ฌ 56 2. ์ž…๋ฒ•๊ถŒ 58 3. ๋Œ€์ •๋ถ€๊ฒฌ์ œ๊ถŒ 60 1) ๊ตญ์ •๊ฐ์‚ฌ 60 2) ์กฐ์‚ฌ์†Œ์œ„์›ํšŒ 62 ์ œ3์ ˆ ์ง€๋ฐฉ์˜ํšŒ์˜ ์˜์‚ฌ๊ฒฐ์ • 64 1. ํ–‰์ •์ ˆ์ฐจ์— ๋Œ€ํ•œ ์˜๊ฒฌ์ฒญ์ทจ ๋ฐ ๋™์˜๊ถŒ 64 1) ํ™˜๊ฒฝ์˜ํ–ฅํ‰๊ฐ€์„œ ๋™์˜์•ˆ 64 2) ์ ˆ๋Œ€๋ณด์ „์ง€์—ญ ๋ณ€๊ฒฝ๋™์˜์•ˆ 65 3) ๊ณต์œ ์ˆ˜๋ฉด๋งค๋ฆฝ๊ธฐ๋ณธ๊ณ„ํš์—์„œ ๋ฐ˜์˜๊ณ„ํš์— ๋Œ€ํ•œ ์˜๊ฒฌ์ฒญ์ทจ 66 2. ์ง‘ํ–‰๊ธฐ๊ด€ ๊ฒฌ์ œ๊ถŒ 67 1) ๊ฐˆ๋“ฑํ•ด์†Œ ํŠน๋ณ„์œ„์›ํšŒ 68 2) ํ–‰์ •์‚ฌ๋ฌด์กฐ์‚ฌ 69 3. ์˜๊ฒฌํ‘œ๋ช…๊ถŒ 70 ์ œ4์ ˆ ๊ฐ ํ๋ฆ„์˜ ๋ณ€ํ™”์™€ ์ •์ฑ…์˜ ์ฐฝ 72 1. ๋ฌธ์ œ์˜ ํ๋ฆ„์˜ ๋ณ€ํ™” 72 1) ๊ตฐํ•ญ์ค‘์‹ฌ ๊ฐœ๋ฐœ ์šฐ๋ ค 72 2) ์ง€์—ญ๋ฐœ์ „ ์‚ฌ์—… 74 3) ํ™˜๊ฒฝํ›ผ์† 76 2. ์ •์น˜์˜ ํ๋ฆ„์˜ ๋ณ€ํ™” 77 1) ์—ฌ๋ก ์˜ ๋ณ€ํ™” 78 2) ์„ ๊ฑฐ์™€ ๊ณต์•ฝ 79 3. ์ •์ฑ…์˜ ํ๋ฆ„์˜ ๋ณ€ํ™” 80 4. ์ •์ฑ…์˜ ์ฐฝ 81 ์ œ7์žฅ ๊ฒฐ ๋ก  82 ์ œ1์ ˆ ์ข…ํ•ฉ๋ถ„์„ 82 ์ œ2์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 85 ์ œ3์ ˆ ์—ฐ๊ตฌ์˜ ์ด๋ก ์ ยท์ •์ฑ…์  ์‹œ์‚ฌ์  88 ์ œ4์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ๋ฐœ์ „๋ฐฉํ–ฅ 91 ์ฐธ๊ณ ๋ฌธํ—Œ 93 Abstract 97Maste

    Statistical methods for medical studies

    Get PDF
    Most textbooks for biostatistics only explain each individual statistical test with its mathematical formula. However, it is crucial to understand the relationships among the statistical methods and to properly integrate the individual methods to effectively apply them to real clinical research settings. The choice for valid statistical tests greatly depends on the dependency of the sample and the number of independent variables in the analyses as well as the measurement scale of dependent variables and independent variables. In this report, many statistical tests such as the two sample t-test, ANOVA, non-parametric tests, chi-square test, log-rank test, multiple linear regression, logistic regression, mixed model, and Cox regression model are addressed through hypothetical examples. The key for a successful analysis of a clinical experiment is to adopt suitable statistical tests. This study presents a guideline to clinical researchers for selecting valid and powerful statistical tests in their study design. The choice of suitable statistical tests increases the reliability of analytical results and therefore the possibility of accepting a researcher's clinical hypothesis. The proposed flowchart of appropriate tests of statistical inference will be of help to many clinical researchers to their study.ope

    Appraisals of Hardship by The Timing, The Type, and The Lay Faith

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2021.8. ์ตœ์ธ์ฒ .์—ญ๊ฒฝ์˜ ๊ฒฝํ—˜์€ ์ธ๊ฐ„์ด ๊ธฐ๋Šฅํ•˜๋Š” ๋ฐ์— ์žˆ์–ด ์—ฌ๋Ÿฌ๊ฐ€์ง€ ์˜ํ–ฅ์„ ๋ถˆ๋Ÿฌ ์ผ์œผํ‚จ๋‹ค. ์ •์„œ์  ํ›„์œ ์ฆ๊ณผ ๊ทธ ์•ˆ์—์„œ์˜ ๊ฐœ์ธ ์ฐจ๊นŒ์ง€ ์—ญ๊ฒฝ์˜ ๋‹ค์–‘ํ•œ ์ธก๋ฉด์ด ์—ฐ๊ตฌ๋˜์–ด ์™”์œผ๋‚˜, ์‚ฌ๋žŒ๋“ค์ด ํƒ€์ธ์˜ ์—ญ๊ฒฝ์— ๋Œ€ํ•ด ์–ด๋–ป๊ฒŒ ์ดํ•ดํ•˜๊ณ  ํ‰๊ฐ€ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ํƒ์ƒ‰์€ ์•„์ง๊นŒ์ง€ ๊ฑฐ์˜ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์•˜๋‹ค. ์ด์— ๋”ฐ๋ผ, ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‘๊ฐ€์ง€ ์ž๊ทน์ œ ์—ญํ• ์˜ ์กฐ์ ˆ ๋ณ€์ธ(์ข…๋ฅ˜์™€ ์‹œ์ ) ๊ทธ๋ฆฌ๊ณ  ํ•œ๊ฐ€์ง€ ์ง€๊ฐ์ž ์ˆ˜์ค€์˜ ์กฐ์ ˆ ๋ณ€์ธ(์—ญ๊ฒฝ์— ๋Œ€ํ•œ ์‹ ๋…)์„ ๊ตฌ๋ถ„ํ•˜๊ณ , ํ•ด๋‹น ์š”์†Œ๋“ค์ด ์—ญ๊ฒฝ์— ๋ถ€์—ฌ๋˜๋Š” ๊ฐ€์น˜๋ฅผ ๋ณ€ํ™” ์‹œํ‚ค๋Š”์ง€ ํ™•์ธํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ 1 ์—์„œ๋Š” ์‚ฌ๋žŒ๋“ค์ด ์œ ๋…„ ์‹œ์ ˆ์˜ ๊ฒฝ์ œ์  ์—ญ๊ฒฝ์„ ์„ฑ์ธ ์ดํ›„์˜ ๊ฒฝ์ œ์  ์—ญ๊ฒฝ์ด๋‚˜ ์‹œ์ ๊ณผ ์ƒ๊ด€ ์—†๋Š” ๋ชจ๋“  ๊ด€๊ณ„์  ์—ญ๊ฒฝ๋ณด๋‹ค ์œ ๋Šฅ๊ฐ(competence)๊ณผ ์‹ฌ๋ฆฌ์  ์•ˆ๋…•๊ฐ(psychological well-being)์— ์œ ์ตํ•˜๋‹ค๊ณ  ๋ฏฟ๋Š”๋‹ค๋Š” ์‚ฌ์‹ค์ด ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ์—ฐ๊ตฌ 2 ์—์„œ์˜ ๋งค๊ฐœ๋œ ์กฐ์ ˆํšจ๊ณผ ๋ถ„์„์€ ์ด๋Ÿฌํ•œ ๋ฏฟ์Œ์ด ํšŒ๋ณต ํƒ„๋ ฅ์„ฑ(resilience) ๋ฐ ์ฑ…์ž„๊ฐ(responsibility) ๋ฐœ๋‹ฌ์— ๋Œ€ํ•œ ๊ธฐ๋Œ€์— ๊ธฐ๋ฐ˜ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ์—ฐ๊ตฌ 3 ์—์„œ๋Š” ์œ ๋…„ ์‹œ์ ˆ์˜ ๊ฒฝ์ œ์  ์—ญ๊ฒฝ์— ๋Œ€ํ•œ ๊ธ์ •์  ํ‰๊ฐ€โ€”์ฆ‰, ๊ทธ๊ฒƒ์ด ์œ ๋Šฅ๊ฐ๊ณผ ์‹ฌ๋ฆฌ์  ์•ˆ๋…•๊ฐ์„ ๋†’์ผ ๊ฒƒ์ด๋ผ๋Š” ๋ฏฟ์Œ์ด ๊ณง ์—…๋ฌด ๊ด€๋ จ ์„ ํ˜ธ๋„๋กœ ์ด์–ด์ง์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์—ฐ๊ตฌ 4 ์—์„œ๋Š” ๊ฐœ๊ฐœ์ธ์ด ์—ญ๊ฒฝ์— ๋Œ€ํ•ด ๊ฐ–๊ณ  ์žˆ๋Š” ์‹ ๋…์— ๋”ฐ๋ผ ์•ž์„œ ๋“œ๋Ÿฌ๋‚œ ๊ฒฝํ–ฅ์„ฑ์ด ๋”์šฑ ๊ฐ•ํ™” ํ˜น์€ ์•ฝํ™”๋  ์ˆ˜ ์žˆ์Œ์„ ๋ฐœ๊ฒฌํ•˜์˜€๋‹ค. ์ข…ํ•ฉ ๋…ผ์˜์—์„œ ๋ณธ ์—ฐ๊ตฌ์˜ ํ•จ์˜์™€ ํ•œ๊ณ„์ , ๊ทธ๋ฆฌ๊ณ  ์ถ”ํ›„ ์—ฐ๊ตฌ ์•„์ด๋””์–ด์— ๋Œ€ํ•ด ์ด์•ผ๊ธฐํ•œ๋‹ค.Experiences of hardship have a substantial bearing on human functioning. While the impact of hardship has been studied on many dimensions, fromnhealth to emotion and its individual difference, little exploration has been made of how people actually understand and evaluate the hardship of others. To unravel this matter, this study classified two stimulus-level moderators (i.e., the type and the timing of hardship) and one perceiver level moderator (i.e., faith in hardship) and examined whether these factors differentiate the value granted to hardships. Study 1 showed that participants expect financial hardship in early life to enhance competence and psychological well-being (i.e., PWB) than do that in later life or relational hardship at any time point. Moderated mediation analyses in Study 2 confirmed that these pathways are partly explained by expectations for resilience and responsibility development. In Study 3, these resulting expectations for competence and PWB further permeated participantsโ€™ work-related behavioral intention. Lastly, Study 4 demonstrated the discerned patterns are reinforced or mitigated by the lay faith that participants hold in youth hardship. Theoretical implications, limitations, and future research ideas are discussed.Introduction 1 Overview of Studies 16 Study 1 17 Study 2 32 Study 3 44 Study 4 52 General Discussion 60 References 68 Abstract in Korean 103์„

    ๋งŒ์„ฑ ๊ธฐ๊ด€์ง€์—ผ์˜ ์œ„ํ—˜ ์ธ์ž๋กœ์„œ์˜ ์ฃผ์š” ์šฐ์šธ ์žฅ์• : 2-ํ‘œ๋ณธ ๋ฉ˜๋ธ๋ฆฌ์–ธ ๋ฌด์ž‘์œ„๋ฐฐ์ • ์—ฐ๊ตฌ

    No full text
    Background and objective: Previous studies have reported an association between major depressive disorder (MDD) and chronic bronchitis. We performed a two-sample Mendelian randomization (MR) study to investigate the causal association of major depressive disorder with chronic bronchitis. Methods: To clarify the influence of major depressive disorder on chronic bronchitis through two-sample Mendelian randomization, we used genome-wide association study (GWAS) summary data in the MR-Base GWAS repository. A total of 36 genetic instruments for a major depressive disorder were extracted from 173,005 individuals of European ancestry on Psychiatric Genomics Consortium (PGC) data and a total of 24 genetic instruments for doctor-diagnosed chronic bronchitis were extracted from 112,583 individuals of European ancestry on UK biobank data. We performed the inverse variance weighted (IVW) and also other MR analyses, MR-Egger regression, weighted median and weighted mode. We also performed sensitivity analyses such as single nucleotide polymorphism (SNP) analysis and leave-one-out analysis. Moreover, we carried out the latest MR method, Radial MR to detect outlier genetic instruments and checked the MR results after removing outlier SNPs. Results: According to the inverse variance weighted (IVW) method, we found that major depressive disorder has a significant causal association with chronic bronchitis, but the odds ratio was not high [odds ratio (OR) = 1.007, 95% CI = 1.001-1.013, p-value = 0.018]. Moreover, after excluding an outlier SNP for major depressive disorder, radial IVW analysis revealed no significant causal association between major depressive disorder and chronic bronchitis [ฮฒ=0.005, p-value=0.068]. Conclusion: The present study showed that major depressive disorder has causal association with chronic bronchitis. However, the statistically significant results were not repeated in some MR analyses and analyses without an outlier. ๋ฐฐ๊ฒฝ ๋ฐ ์—ฐ๊ตฌ ๋ชฉ์ : ์„ ํ–‰ ์—ฐ๊ตฌ์—์„œ ์ฃผ์š” ์šฐ์šธ ์žฅ์•  (MDD)์™€ ๋งŒ์„ฑ ๊ธฐ๊ด€์ง€์—ผ ๊ฐ„ ์—ฐ๊ด€์„ฑ์ด ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ์ฃผ์š” ์šฐ์šธ ์žฅ์• ์™€ ๋งŒ์„ฑ ๊ธฐ๊ด€์ง€์—ผ์˜ ์ธ๊ณผ๊ด€๊ณ„๋ฅผ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด 2-ํ‘œ๋ณธ ๋ฉ˜๋ธ๋ฆฌ์–ธ ๋ฌด์ž‘์œ„๋ฐฐ์ • (MR) ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•: 2-ํ‘œ๋ณธ ๋ฉ˜๋ธ๋ฆฌ์–ธ ๋ฌด์ž‘์œ„๋ฐฐ์ • ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์ฃผ์š” ์šฐ์šธ ์žฅ์• ์˜ ๋งŒ์„ฑ ๊ธฐ๊ด€์ง€์—ผ์— ๋Œ€ํ•œ ์˜ํ–ฅ์„ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด, MR-Base GWAS ์ €์žฅ์†Œ์˜ GWAS ์š”์•ฝ ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. Psychiatric Genomics Consortium (PGC) ์ž๋ฃŒ์—์„œ 173,005๋ช…์˜ ์œ ๋Ÿฝ์ธ์— ๋Œ€ํ•œ ์ž๋ฃŒ๋กœ๋ถ€ํ„ฐ ์ฃผ์š” ์šฐ์šธ ์žฅ์• ์— ๋Œ€ํ•œ ์ด 36๊ฐœ์˜ ์œ ์ „ ๋„๊ตฌ๊ฐ€ ์ถ”์ถœ๋˜์—ˆ์œผ๋ฉฐ UK ๋ฐ”์ด์˜ค๋ฑ…ํฌ ์ž๋ฃŒ์—์„œ 112,583๋ช…์˜ ์œ ๋Ÿฝ์ธ์— ๋Œ€ํ•œ ์ž๋ฃŒ๋กœ๋ถ€ํ„ฐ ์˜์‚ฌ ์ง„๋‹จ ๋งŒ์„ฑ๊ธฐ๊ด€์ง€์—ผ์— ๋Œ€ํ•œ ์ด 24๊ฐœ ์œ ์ „ ๋„๊ตฌ๊ฐ€ ์ถ”์ถœ๋˜์—ˆ๋‹ค. ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•œ ๋ฐฉ๋ฒ•์ธ ์—ญ๋ถ„์‚ฐ ๊ฐ€์ค‘ ๋ฐ ๊ธฐํƒ€ MR ๋ถ„์„์ธ MR-Egger ํšŒ๊ท€, Weighted Median and Weighted Mode๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ฏผ๊ฐ๋„ ๋ถ„์„, ๋‹จ์ผ SNP ๋ถ„์„ ๋ฐ leave-one-out ๋ถ„์„์„ ํ•˜์˜€์œผ๋ฉฐ, ์ตœ์‹  MR ๋ฐฉ๋ฒ•์ธ, radial MR์„ ํ•˜์—ฌ ์ด์ƒ์น˜ ์œ ์ „ ๋„๊ตฌ๋ฅผ ํƒ์ง€ํ•˜๊ณ  ์ด์ƒ์น˜ SNP ์ œ๊ฑฐ ํ›„ MR ๊ฒฐ๊ณผ๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ: IVW ๋ฐฉ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฃผ์š” ์šฐ์šธ ์žฅ์• ๋Š” ๋งŒ์„ฑ๊ธฐ๊ด€์ง€์—ผ์— ๋Œ€ํ•˜์—ฌ ์œ ์˜ํ•œ ์ธ๊ณผ์  ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜์˜€์ง€๋งŒ, ์˜ค์ฆˆ๋น„๊ฐ€ ๋†’์ง€ ์•Š์•˜๋‹ค [odds ratios (ORs)=1.007, 95% CI=1.001-1.013, p-value=0.018]. ๋˜ํ•œ, Radial MR ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ํƒ์ง€๋œ ์ฃผ์š” ์šฐ์šธ ์žฅ์• ์— ๋Œ€ํ•œ ์ด์ƒ์น˜ SNP์„ ์ œ์™ธํ•œ radial IVW ๋ถ„์„ ๊ฒฐ๊ณผ ์ฃผ์š” ์šฐ์šธ ์žฅ์• ์˜ ๋งŒ์„ฑ ๊ธฐ๊ด€์ง€์—ผ์— ๋Œ€ํ•ด ์œ ์˜ํ•œ ์ธ๊ณผ์  ์—ฐ๊ด€์„ฑ์ด ์—†์—ˆ๋‹ค [ฮฒ=0.005, p-value=0.068]. ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ฃผ์š” ์šฐ์šธ ์žฅ์• ๊ฐ€ ๋งŒ์„ฑ ๊ธฐ๊ด€์ง€์—ผ๊ณผ ์œ ์˜ํ•œ ์ธ๊ณผ์  ๊ด€๊ณ„๊ฐ€ ์žˆ์—ˆ์œผ๋‚˜, ์ผ๋ถ€ MR ๋ถ„์„ ๋ฐ ์ด์ƒ์น˜ ์ œ๊ฑฐ ํ›„ ๋ถ„์„์—์„œ๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค.open์„

    Linkage analysis of longitudinal data : an application to Framingham Heart study

    No full text
    Thesis (master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ†ต๊ณ„ํ•™๊ณผ,2003.Maste

    Relationship between commuting time and depressive symptom : Korean working conditions survey (2011-2017)

    No full text
    ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ํ•œ๊ตญ์ธ์˜ ํ†ต๊ทผ ์‹œ๊ฐ„๊ณผ ์šฐ์šธ๊ฐ ๊ฐ„์˜ ์—ฐ๊ด€์„ฑ์„ ๋ถ„์„ํ•˜๊ณ ์ž ํ–ˆ๋‹ค. ์ œ3,4,5์ฐจ ํ•œ๊ตญ์ธ ๊ทผ๋กœํ™˜๊ฒฝ์กฐ์‚ฌ์ž๋ฃŒ (Korean Working Conditions Survey, KWCS)๋ฅผ ์ด์šฉํ•˜์—ฌ ์ฃผ๊ฑฐ์ง€์—์„œ ๊ทผ๋ฌด์ง€๋กœ ํ†ต๊ทผ์ด ์ •๊ธฐ์ ์œผ๋กœ ๋ฐœ์ƒํ•˜๋Š” ๊ทผ๋กœ์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ–ˆ๊ณ  ์ฃผ๊ฐ„ ๊ทผ๋ฌด 3์ผ ๋ฏธ๋งŒ ์ผํ•˜๋Š” ๊ทผ๋กœ์ž๋Š” ์ œ์™ธํ•˜์˜€๋‹ค. ํ†ต๊ทผ ์‹œ๊ฐ„๊ณผ ์šฐ์šธ๊ฐ ๊ฐ„์˜ ๊ด€๋ จ์„ฑ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋‹ค์ค‘ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ด 108,309๋ช…์˜ ๊ทผ๋กœ์ž(๋‚จ์ž 53,926, ์—ฌ์ž 54,383) ์ค‘ ๋‚จ์„ฑ์˜ 1.35%์™€ ์—ฌ์„ฑ์˜ ๊ฒฝ์šฐ 2.14%์—์„œ ์šฐ์šธ๊ฐ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‚ฌ์—…์žฅ ๊ทœ๋ชจ, ์ฃผ๋‹น ๊ทผ๋กœ์‹œ๊ฐ„, ๊ต๋Œ€๊ทผ๋ฌด ์—ฌ๋ถ€, ์ผ๊ณผ ์‚ถ์˜ ๊ท ํ˜•, ์ง์—…๋งŒ์กฑ๋„, ๊ต์œก์ˆ˜์ค€, ์†Œ๋“๊ณผ ๊ฐ™์€ ์‚ฌํšŒ ํ†ต๊ณ„ํ•™์  ์š”์ธ์„ ๋ณด์ •ํ•œ ํ›„ ํ†ต๊ทผ์‹œ๊ฐ„ ๋Œ€๋ณ„๋กœ ์šฐ์šธ๊ฐ์„ ๋ถ„์„ํ•ด๋ณธ ๊ฒฐ๊ณผ ๋‚จ๋…€ ๋ชจ๋‘ 30~45๋ถ„์˜ ํ†ต๊ทผ ์‹œ๊ฐ„์„ ๊ฐ€์ง€๋Š” ์ง‘๋‹จ์ด ์šฐ์šธ๊ฐ์„ ๊ฒฝํ—˜ํ•  ์œ„ํ—˜๋„๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์•˜๋‹ค. 30๋ถ„ ๋ฏธ๋งŒ ์ง‘๋‹จ์˜ ๊ฒฝ์šฐ ํ†ต๊ทผ์‹œ๊ฐ„์ด ์งง์„์ˆ˜๋ก ์šฐ์šธ๊ฐ์ด ์ ์  ๋†’์•„์กŒ๊ณ , ์ด๋Š” ์ž์˜์—…์ž ์ง‘๋‹จ์˜ ์ฃผ๊ฑฐ์ง€์™€ ๊ทผ๋ฌด์ง€๊ฐ„ ๋ถ„๋ฆฌ ๋ถ€์กฑ์—์„œ ๊ธฐ์ธํ•œ ๊ฒƒ์œผ๋กœ ์ถ”์ •๋œ๋‹ค. ๋ฐ˜๋ฉด 45๋ถ„ ์ด์ƒ ์ง‘๋‹จ์˜ ๊ฒฝ์šฐ 30-45๋ถ„ ํ†ต๊ทผ์‹œ๊ฐ„์„ ๊ฐ€์ง€๋Š” ์ง‘๋‹จ ๋Œ€๋น„ ์šฐ์šธ๊ฐ์ด ๋†’์•˜์œผ๋‚˜ ์ง€์†์ ์ธ ์ฆ๊ฐ€์„ธ๋ฅผ ๋ณด์—ฌ์ฃผ์ง„ ์•Š์•˜๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ํ†ต๊ทผ ์‹œ๊ฐ„์€ ์ •์‹  ๊ฑด๊ฐ• ์žฅ์• ์™€ ์ง์ ‘์ ์œผ๋กœ ๊ด€๋ จ์ด ์žˆ์—ˆ๊ณ , ์ž์˜์—…์ž์™€ ์ž„๊ธˆ๊ทผ๋กœ์ž๊ฐ„ ๋‹ค๋ฅธ ํ˜•ํƒœ๋กœ ์šฐ์šธ๊ฐ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ํŠนํžˆ ๊ทผ๋กœ์ž์˜ ํ†ต๊ทผ ์‹œ๊ฐ„์€ ํ†ต๊ทผ์ž์˜ ์ผ์ƒ์ƒํ™œ ๋“ฑ ์‚ถ์˜ ๋„“์€ ์˜์—ญ์— ๊ฑธ์ณ ๋ฐ€์ ‘ํ•˜๊ฒŒ ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ์ ์„ ๊ณ ๋ คํ•˜์—ฌ ์ค‘์š”ํ•œ ๋ณ€์ˆ˜๋กœ ์ธ์‹๋˜์–ด์•ผ ํ•จ์„ ๊ฐ•์กฐํ•œ๋‹ค. This study attempted to analyze the relationship between commuting time and depressive symptom in Koreans. The 3rd, 4th and 5th Korean Working Conditions Survey (KWCS) was used to analyze workers who regularly commute from their residence to work. Workers working less than 3 days of weekly work were excluded. Multiple logistic regression analysis was used to confirm the relationship between commuting time and depressive symptom. Among a total of 108,309 workers (53,926 men, 54,383 women), 1.35% of men and 2.14% of women had depressive symptom. After correcting for socio-statistic factors such as workplace size, weekly working hours, shift work, work-life balance, job satisfaction, education level, and income, depressive symptom was analyzed by commuting time. As a result, the group with 30-45 minutes commuting time for both men and women has the lowest risk of experiencing depressive symptom. In the case of the group of less than 30 minutes, the shorter the commuting time, the more depressed. This is presumed to be due to the lack of separation between the residential and working areas of the self-employed group. On the other hand, the group with more than 45 minutes did not show a significant increase in the feeling of depressive symptom even if the commute time increased. This study found that commuting time was directly associated with mental health problems, and it was verified that the self-employed and waged workers had different effects on depressive symptom. In particular, it is emphasized that workers' commuting time should be recognized as an important variable in consideration of the fact that it can have a close influence over a wide area of life such as the daily life of commuters.open์„

    Factors Related to Fatigue in Community-dwelling Elderly people

    No full text
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฐ„ํ˜ธํ•™๊ณผ, 2017. 2. ์ตœ์Šค๋ฏธ.ํ”ผ๋กœ๋Š” ๋…ธ์ธ์ด ํ”ํžˆ ํ˜ธ์†Œํ•˜๋Š” ๊ฑด๊ฐ•๋ฌธ์ œ๋กœ ์งˆํ™˜์˜ ๋ฐœ๋ณ‘ ๋ฐ ์•…ํ™”์™€ ๊ด€๋ จ๋˜์–ด ์žˆ๋‹ค. ์ด๋Š” ๋งŒ์„ฑ์งˆํ™˜ ์œ ๋ณ‘๋ฅ ์ด ๋†’์€ ๋…ธ์ธ์˜ ์‚ถ์˜ ์งˆ ๊ฐ์†Œ์™€ ์˜๋ฃŒ๋น„ ์ฆ๊ฐ€๋กœ ์ด์–ด์งˆ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ํ”ผ๋กœ๋Š” ๋…ธํ™”๊ณผ์ •์„ ์ด‰์ง„ํ•˜๊ณ  ์‚ฌ๋ง๋ฅ ์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋ณด๊ณ ๋˜์–ด ๊ด€๋ จ์š”์ธ์„ ํŒŒ์•…ํ•˜์—ฌ ์˜ˆ๋ฐฉํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ์žฌ๊ฐ€ ๋…ธ์ธ์˜ ํ”ผ๋กœ ์ •๋„์™€ ํŠน์„ฑ์„ ์กฐ์‚ฌํ•˜๊ณ , ํ”ผ๋กœ ์•…ํ™” ๋ฐ ์™„ํ™” ์š”์ธ์„ ํ†ตํ•ฉ์ ์œผ๋กœ ์กฐ์‚ฌํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด์ฐจ์ž๋ฃŒ๋ถ„์„์—ฐ๊ตฌ๋กœ, 2015๋…„ 7์›”๋ถ€ํ„ฐ 9์›”๊นŒ์ง€ ์„œ์šธ์‹œ๋‚ด 1๊ฐœ ๋ณต์ง€๊ด€์„ ์ด์šฉํ•˜๋Š” ๋…ธ์ธ 200๋ช…์˜ ์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋Œ€์ƒ์ž์˜ ์ผ๋ฐ˜์  ํŠน์„ฑ๊ณผ ๊ฑด๊ฐ•๊ด€๋ จ ํŠน์„ฑ, ํ”ผ๋กœ(Fatigue severity scale, FSS), ์šฐ์šธ(Geriatric Depression Scale Short Form Korea Version, GDSSF-K), ํ†ต์ฆ(Numeric rating scale, NRS), ์‹ ์ฒดํ™œ๋™(Korean Version of Physical activity scale for elderly, K-PASE), ์ˆ˜๋ฉด(Verran&synder-Halpern(VSH) Sleep Scale)์„ ์„ค๋ฌธ์ง€๋กœ ์ธก์ •ํ•œ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ž๋ฃŒ๋Š” SPSS 22.0 program์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ ์žฌ๊ฐ€ ๋…ธ์ธ์˜ ํ”ผ๋กœ๋„๋Š” 3.46์ ์œผ๋กœ 35.5%์˜ ๋…ธ์ธ์ด ํ”ผ๋กœ๊ตฐ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋…ธ์ธ์˜ ํ”ผ๋กœ ๊ด€๋ จ์š”์ธ์— independent t-test, one-way ANOVA๋ฅผ ํ†ตํ•ด ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ ์—ฐ๋ น(p=.009), ์†Œ๋“์ˆ˜์ค€(p=.003), ์งˆํ™˜์˜ ์ˆ˜(p<.001) ๋ฐ ๋ณต์šฉ์•ฝ๋ฌผ์˜ ์ˆ˜(p<.001), ์ฃผ๊ด€์  ๊ฑด๊ฐ•์ƒํƒœ(p<.001)์— ๋”ฐ๋ผ ๋…ธ์ธ์˜ ํ”ผ๋กœ ์ •๋„์— ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค.๋ฐ˜๋ฉด ์„ฑ๋ณ„, ๊ต์œก ์ •๋„, BMI๋Š” ํ”ผ๋กœ์™€ ์œ ์˜ํ•œ ๊ด€๋ จ์ด ์—†์—ˆ๋‹ค. ํ”ผ๋กœ ์˜ํ–ฅ์š”์ธ์— ๋Œ€ํ•ด multiple linear regression์œผ๋กœ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, ์—ฐ๋ น์ด ๋†’์„์ˆ˜๋ก(p<.001), ์šฐ์šธํ• ์ˆ˜๋ก(p<.001), ์ฃผ๊ด€์  ๊ฑด๊ฐ•์ƒํƒœ๊ฐ€ ๋‚˜์ ์ˆ˜๋ก(p<.001), ํ†ต์ฆ์ด ์‹ฌํ• ์ˆ˜๋ก(p=.001), ๊ทœ์น™์ ์œผ๋กœ ์šด๋™์„ ํ•˜์ง€ ์•Š๋Š” ๋…ธ์ธ์—์„œ(p=.013) ํ”ผ๋กœ๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ๋…ธ์ธ์˜ ํ”ผ๋กœ์™€ ๊ด€๋ จ๋œ ์กฐ์ ˆ ๊ฐ€๋Šฅํ•œ ์š”์ธ์œผ๋กœ ์šฐ์šธ๊ณผ ํ†ต์ฆ, ๊ทœ์น™์ ์ธ ์‹ ์ฒดํ™œ๋™์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์žฌ๊ฐ€๋…ธ์ธ์˜ ํ”ผ๋กœ ๊ฐ์†Œ๋ฅผ ์œ„ํ•ด ์šฐ์šธ๊ณผ ํ†ต์ฆ, ์‹ ์ฒดํ™œ๋™์„ ์ค‘์‹ฌ์œผ๋กœ ์ ์ ˆํ•œ ํ”ผ๋กœ๊ด€๋ฆฌ ํ”„๋กœ๊ทธ๋žจ์˜ ๊ฐœ๋ฐœ๊ณผ ์ ์šฉ์ด ํ•„์š”ํ•˜๋‹ค.Fatigue is one of the most common symptoms experienced by elderly people. It has been reported to be associated with high prevalence of, and deterioration of chronic diseases which may lead to a decrease in quality of life and increased medical expenses for elderly people. In addition, fatigue is reported to promote aging process and increase mortality. Recent studies reported that depression,, pain, physical activity, and sleep disorders are associated with fatigue. However, the related factors and the characteristics of fatigue in community dwelling elderly are yet to be determined. The purpose of this study, therefore, was to investigate the level and characteristics of fatigue of elderly people, and to identify the factors associated with fatigue using an integrated approach. This study was a secondary data analysis study. The raw data was collected from one of the welfare centers in Seoul from July to September, 2015, and the data of 200 elderly people were selected to be analyzed. The general characteristics and health-related characteristics of the subjects, fatigue (Fatigue severity scale, FSS), depression (Geriatric Depression Scale Short Form Korea Version, GDSSF-K), pain (Numeric Rating Scale, NRS), physical activity (Korean Version of Physical Activity Scale for Elderly, KPASE), and sleep (Verran & Synder-Halpern (VSH) Sleep Scale) were collected. The data was analyzed using Windows SPSS program (Version 22.0). As a result, the fatigue of elderly people was found to be 3.46, and 35.5% of them fell under the category of fatigue group. Fatigue was higher with such situationsolder age (p=.009), lower income (p=.003), the higher number of diseases (p<.001), the higher number of medications (p<.001), and lower perceived health status (p<.001). On the other hand, gender, education, and body mass index (BMI) were found to be unrelated to fatigue. In multiple linear regressions, (the explanatory power, 47.5%), fatigue increases with older age (p<.001), depression (p<.001), pain (p=.001), irregular exercise (p=.013), and lower perceived health status (p<.001). In conclusion, our study results suggest that depression, pain, and regular physical activity were identified as manageable risk factors for fatigue alleviation of elderly people. Therefore, these factors should be considered when developing fatigue management programs for elderly people.โ… . ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ 1 2. ์—ฐ๊ตฌ ๋ชฉ์  3 3. ์šฉ์–ด์˜ ์ •์˜ 3 โ…ก. ๋ฌธํ—Œ๊ณ ์ฐฐ 6 1. ์žฌ๊ฐ€ ๋…ธ์ธ์˜ ํ”ผ๋กœ 6 2. ์žฌ๊ฐ€ ๋…ธ์ธ์˜ ํ”ผ๋กœ ๊ด€๋ จ ์š”์ธ 8 โ…ข. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 15 1. ์—ฐ๊ตฌ์„ค๊ณ„ 15 2. ์—ฐ๊ตฌ ๋Œ€์ƒ 15 3. ์—ฐ๊ตฌ ๋„๊ตฌ 16 4. ์œค๋ฆฌ์  ๊ณ ๋ ค 21 5. ์ž๋ฃŒ ์ˆ˜์ง‘ ๋ฐฉ๋ฒ• 22 6. ์ž๋ฃŒ ๋ถ„์„ ๋ฐฉ๋ฒ• 23 โ…ฃ. ์—ฐ๊ตฌ๊ฒฐ๊ณผ 24 1. ๋Œ€์ƒ์ž์˜ ํŠน์„ฑ 24 2. ๋Œ€์ƒ์ž์˜ ํ”ผ๋กœ 29 3. ๋Œ€์ƒ์ž ์šฐ์šธ, ํ†ต์ฆ, ์‹ ์ฒดํ™œ๋™, ์ˆ˜๋ฉด 32 4. ๋Œ€์ƒ์ž ํŠน์„ฑ์— ๋”ฐ๋ฅธ ํ”ผ๋กœ ์ฐจ์ด 34 5. ํ”ผ๋กœ ์ƒ๊ด€๊ด€๊ณ„ 38 6. ํ”ผ๋กœ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ 40 7. ์ถ”๊ฐ€๋ถ„์„ 42 โ…ค. ๋…ผ์˜ 44 VI. ๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 56 ์ฐธ๊ณ ๋ฌธํ—Œ 57 ๋ถ€๋ก 66 Abstract 68Maste

    An acoustic speech study of children who received anterior crossbite correction

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์น˜์˜ํ•™๊ณผ ์†Œ์•„์น˜๊ณผํ•™์ „๊ณต,2002.Docto

    ํ–„์Šคํ„ฐ ๊ฐ„์•”๋ชจ๋ธ์—์„œ oval cell์˜ ๋ถ„๋ฆฌ, ๋™์ • ๋ฐ ๋ถ„ํ™”์— ๊ด€ํ•œ ์—ฐ๊ตฌ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ˆ˜์˜ํ•™๊ณผ ์ˆ˜์˜๋ณ‘๋ฆฌํ•™์ „๊ณต,1999.Maste
    corecore