development and validation of multi-dimensional

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318 www.kcp.or.kr Development and Validation of Multi-Dimensional Personality Inventory in Preliminary Study: Integrating Bright and Dark Sides of Personality Sang Jun Lee 1 Yeoul Han 2 Hyowon Kim 1 Heejae J. Lee 3 Jaiyoung Park 2 Kee-Hong Choi 2โ€  Doo Jin Park 1โ€  Jeongwook Choi 3 Myung Ki Kim 3 Dong Gi Seo 3โ€  1 PBCG (Psychology based Consulting Group), Seoul; 2 Department of Psychology, Korea University, Seoul; 3 Department of Psychology, Hallym University, Chuncheon, Korea The purpose of this study was to develop and validate a multidimensional personality inventory (Big 10 Inventory, BTI) to assess general and maladaptive personality dimensions. For the pilot study, an extensive literature review and expertsโ€™ work- shop led to initial personality constructs and 234 preliminary items. A survey was conducted to 1,200 adults to examine item characteristics and factor structures. In the main study, 180 items were administered to 600 adults along with other personal- ity measures. The results indicated that 165 items (80 and 85 items for measuring 5 dimensions of general personality and maladaptive personality, respectively) were best performed and thus chosen as the final items. The BTI showed adequate in- ternal and test-retest reliability. Model fit indices from confirmatory factor analysis were satisfactory. Convergent and diver- gent validity were supported with significant correlation patterns of the BTI factors with the corresponding factors of the Ko- rean Big Five Inventory-15 and Personality Inventory for DSM-5. Finally, the implications, limitations, and suggestions for further research of the BTI were discussed. Keywords: general personality trait, maladaptive personality trait, personality inventory, validation, Big 10 Inventory ์„ฑ๊ฒฉ ์ธก์ • ๋ฐ ํ‰๊ฐ€์™€ ๊ด€๋ จํ•œ ์ฃผ์š”ํ•œ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ์€ ์„ฑ๊ฒฉ์„ ํ–‰๋™๊ณผํ•™ ์  ๊ตฌ์„ฑ๊ฐœ๋…์œผ๋กœ ๋ณด๊ธฐ๋ณด๋‹ค๋Š” ํŠน์งˆ ์š”์ธ์ด ๋ฐœํ˜„๋˜๋Š” ๋ฒ”์ฃผ์  ๊ฐœ๋…์œผ ๋กœ์„œ ์„ค๋ช…ํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค(Allport & Odbert, 1936; Cattell, 1943). ๊ทธ ์— ๋”ฐ๋ผ ์„ฑ๊ฒฉ์„ ์ˆ˜๋ฆฌ์  ์ธก์ •์„ ํ†ตํ•ด ์ •์˜ํ•˜๋Š” ํ–‰๋™๊ณผํ•™์  ์ฐจ์›๋ณด ๋‹ค ๋ณ„๊ฐœ์˜ ๋ฒ”์ฃผ๋กœ ์ด๋ฃจ์–ด์ง„ ๊ฐœ๋…์œผ๋กœ ๊ฐ€์ •ํ•˜์—ฌ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์–ด ์™” ๋‹ค(Morey, 1988). ๋ฏธ๊ตญ ์ •์‹ ์˜ํ•™ํ˜‘ํšŒ(American Psychiatric Asso- ciation, APA) ๋˜ํ•œ ์ด๋Ÿฌํ•œ ํ๋ฆ„์— ๋งž์ถ”์–ด ๋ณ‘๋ฆฌ์  ์„ฑ๊ฒฉํŠน์งˆ์ด ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์งˆ๊ณผ ์งˆ์ ์œผ๋กœ ๋‹ค๋ฅด๋‹ค๊ณ  ๋ณด๋Š” ๋ฒ”์ฃผ์  ์ ‘๊ทผ์„ ๋ฐ”ํƒ•์œผ๋กœ ์„ฑ๊ฒฉ ์žฅ์• ์˜ ์กด์žฌ ์œ ๋ฌด ํ‰๊ฐ€์— ์ค‘์ ์„ ๋‘๋Š” ํ˜•ํƒœ์˜ ์ •์‹ ์žฅ์•  ์ง„๋‹จ์ฒด๊ณ„ ๋ฅผ ์œ ์ง€ํ•ด์™”๋‹ค(APA, 1980, 1987, 1994, 2000). ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ๋ฐฉ์‹ ์€ ๋ฒ”์ฃผ ๊ฐ„ ๊ฒฝ๊ณ„๊ฐ€ ๋ถˆ๋ถ„๋ช… ๋˜๋Š” ๋ถˆ์•ˆ์ •ํ•˜์—ฌ ๋™์ผํ•œ ๋ฒ”์ฃผ์— ์†ํ•œ ๊ฐœ ์ฒด๋“ค์ด ์ด์งˆ์„ฑ(heterogeneity)์„ ๋ณด์ด๊ฑฐ๋‚˜, ํ•˜๋‚˜์˜ ๊ฐœ์ฒด๊ฐ€ ๋‘˜ ์ด์ƒ ์˜ ๋ฒ”์ฃผ์— ๋™์‹œ์— ์†ํ•˜๊ฒŒ ๋˜๋Š” ๋“ฑ์˜ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•˜์˜€๋‹ค(Clark, 2007; Widiger & Trull, 2007). ๋˜ํ•œ ์ •์ƒ ์„ฑ๊ฒฉ๊ณผ ์ด์ƒ ์„ฑ๊ฒฉ์˜ ๊ด€๊ณ„ ๋ฅผ ํƒ์ƒ‰ํ•œ ๋‹ค์ˆ˜์˜ ์—ฐ๊ตฌ์—์„œ๋Š” ์ •์ƒ ์„ฑ๊ฒฉ๊ณผ ์ด์ƒ ์„ฑ๊ฒฉ์ด ์„œ๋กœ ๋ณ„๊ฐœ ๊ฐ€ ์•„๋‹ˆ๋ผ ํฌ๊ฒŒ ๋™์ผํ•œ ๊ตฌ์กฐ๋ฅผ ๊ณต์œ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜๋ฉด์„œ ์„ฑ๊ฒฉ ์žฅ์• ๋ฅผ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ตฌ์กฐ์˜ ๋ถ€์ ์‘์  ์–‘์ƒ์ด๋ผ๊ณ  ๊ฐœ๋…ํ™”ํ•˜์˜€๋‹ค (Clark, 2007; Samuel & Widiger, 2008; Widiger, Costa, & McCrae, 2002). ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ ํ๋ฆ„์€ Diagnostic Statistical Manual of Mental Disorders 5 (DSM-5; APA, 2013) ์˜ ๊ฐœ๋ฐœ ๊ณผ์ •์—๋„ ์˜ํ–ฅ์„ ์ฃผ์–ด, ์„ฑ ๊ฒฉ์žฅ์• ์— ๋Œ€ํ•œ ๊ธฐ๋ณธ์ ์ธ ๋ฒ”์ฃผ์  ์ •๋ณด์— ๋”ํ•˜์—ฌ ์„ฑ๊ฒฉ์„ ์ฐจ์›์ ์œผ๋กœ ์ ‘๊ทผํ•˜๋Š” ๊ด€์ ์˜ ์ค‘์š”์„ฑ์ด ๊ฐ•์กฐ๋˜์—ˆ๋‹ค(Zachar, Krueger, & Kend- ยฉ 2019 Korean Clinical Psychology Association Korean Journal of Clinical Psychology 2019. Vol. 38, No. 3, 318-334 eISSN 2733-4538 โ€  Correspondence to Dong Gi Seo, Department of Psychology, Hallym University, 1 Hallymdaehak-gil, Chuncheon, Korea; E-mail: [email protected] โ€  Correspondence to Kee-Hong Choi, Department of Psychology, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, Korea; E-mail: [email protected] โ€  Correspondence to Doo Jin Park, PBCG (Psychology based Consulting Group), 12 Jangchungdan-ro 8-gil, Jung-gu, Seoul, Korea; E-mail: doopark@pbcgresearch. com Received May 16, 2019; Revised Aug 17, 2019; Accepted Aug 19, 2019 This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5A2A03030006). Original Article https://doi.org/10.15842/kjcp.2019.38.3.005

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318www.kcp.or.kr

Development and Validation of Multi-Dimensional Personality Inventory in Preliminary Study: Integrating

Bright and Dark Sides of PersonalitySang Jun Lee1 Yeoul Han2 Hyowon Kim1 Heejae J. Lee3 Jaiyoung Park2 Kee-Hong Choi2โ€ 

Doo Jin Park1โ€  Jeongwook Choi3 Myung Ki Kim3 Dong Gi Seo3โ€ 

1PBCG (Psychology based Consulting Group), Seoul; 2Department of Psychology, Korea University, Seoul; 3Department of Psychology, Hallym University, Chuncheon, Korea

The purpose of this study was to develop and validate a multidimensional personality inventory (Big 10 Inventory, BTI) to assess general and maladaptive personality dimensions. For the pilot study, an extensive literature review and expertsโ€™ work-shop led to initial personality constructs and 234 preliminary items. A survey was conducted to 1,200 adults to examine item characteristics and factor structures. In the main study, 180 items were administered to 600 adults along with other personal-ity measures. The results indicated that 165 items (80 and 85 items for measuring 5 dimensions of general personality and maladaptive personality, respectively) were best performed and thus chosen as the final items. The BTI showed adequate in-ternal and test-retest reliability. Model fit indices from confirmatory factor analysis were satisfactory. Convergent and diver-gent validity were supported with significant correlation patterns of the BTI factors with the corresponding factors of the Ko-rean Big Five Inventory-15 and Personality Inventory for DSM-5. Finally, the implications, limitations, and suggestions for further research of the BTI were discussed.

Keywords: general personality trait, maladaptive personality trait, personality inventory, validation, Big 10 Inventory

์„ฑ๊ฒฉ ์ธก์ • ๋ฐ ํ‰๊ฐ€์™€ ๊ด€๋ จํ•œ ์ฃผ์š”ํ•œ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ์€ ์„ฑ๊ฒฉ์„ ํ–‰๋™๊ณผํ•™

์  ๊ตฌ์„ฑ๊ฐœ๋…์œผ๋กœ ๋ณด๊ธฐ๋ณด๋‹ค๋Š” ํŠน์งˆ ์š”์ธ์ด ๋ฐœํ˜„๋˜๋Š” ๋ฒ”์ฃผ์  ๊ฐœ๋…์œผ

๋กœ์„œ ์„ค๋ช…ํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค(Allport & Odbert, 1936; Cattell, 1943). ๊ทธ

์— ๋”ฐ๋ผ ์„ฑ๊ฒฉ์„ ์ˆ˜๋ฆฌ์  ์ธก์ •์„ ํ†ตํ•ด ์ •์˜ํ•˜๋Š” ํ–‰๋™๊ณผํ•™์  ์ฐจ์›๋ณด

๋‹ค ๋ณ„๊ฐœ์˜ ๋ฒ”์ฃผ๋กœ ์ด๋ฃจ์–ด์ง„ ๊ฐœ๋…์œผ๋กœ ๊ฐ€์ •ํ•˜์—ฌ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์–ด ์™”

๋‹ค(Morey, 1988). ๋ฏธ๊ตญ ์ •์‹ ์˜ํ•™ํ˜‘ํšŒ(American Psychiatric Asso-

ciation, APA) ๋˜ํ•œ ์ด๋Ÿฌํ•œ ํ๋ฆ„์— ๋งž์ถ”์–ด ๋ณ‘๋ฆฌ์  ์„ฑ๊ฒฉํŠน์งˆ์ด ์ผ๋ฐ˜

์„ฑ๊ฒฉํŠน์งˆ๊ณผ ์งˆ์ ์œผ๋กœ ๋‹ค๋ฅด๋‹ค๊ณ  ๋ณด๋Š” ๋ฒ”์ฃผ์  ์ ‘๊ทผ์„ ๋ฐ”ํƒ•์œผ๋กœ ์„ฑ๊ฒฉ

์žฅ์• ์˜ ์กด์žฌ ์œ ๋ฌด ํ‰๊ฐ€์— ์ค‘์ ์„ ๋‘๋Š” ํ˜•ํƒœ์˜ ์ •์‹ ์žฅ์•  ์ง„๋‹จ์ฒด๊ณ„

๋ฅผ ์œ ์ง€ํ•ด์™”๋‹ค(APA, 1980, 1987, 1994, 2000). ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ๋ฐฉ์‹

์€ ๋ฒ”์ฃผ ๊ฐ„ ๊ฒฝ๊ณ„๊ฐ€ ๋ถˆ๋ถ„๋ช… ๋˜๋Š” ๋ถˆ์•ˆ์ •ํ•˜์—ฌ ๋™์ผํ•œ ๋ฒ”์ฃผ์— ์†ํ•œ ๊ฐœ

์ฒด๋“ค์ด ์ด์งˆ์„ฑ(heterogeneity)์„ ๋ณด์ด๊ฑฐ๋‚˜, ํ•˜๋‚˜์˜ ๊ฐœ์ฒด๊ฐ€ ๋‘˜ ์ด์ƒ

์˜ ๋ฒ”์ฃผ์— ๋™์‹œ์— ์†ํ•˜๊ฒŒ ๋˜๋Š” ๋“ฑ์˜ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•˜์˜€๋‹ค(Clark,

2007; Widiger & Trull, 2007). ๋˜ํ•œ ์ •์ƒ ์„ฑ๊ฒฉ๊ณผ ์ด์ƒ ์„ฑ๊ฒฉ์˜ ๊ด€๊ณ„

๋ฅผ ํƒ์ƒ‰ํ•œ ๋‹ค์ˆ˜์˜ ์—ฐ๊ตฌ์—์„œ๋Š” ์ •์ƒ ์„ฑ๊ฒฉ๊ณผ ์ด์ƒ ์„ฑ๊ฒฉ์ด ์„œ๋กœ ๋ณ„๊ฐœ

๊ฐ€ ์•„๋‹ˆ๋ผ ํฌ๊ฒŒ ๋™์ผํ•œ ๊ตฌ์กฐ๋ฅผ ๊ณต์œ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜๋ฉด์„œ ์„ฑ๊ฒฉ

์žฅ์• ๋ฅผ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ตฌ์กฐ์˜ ๋ถ€์ ์‘์  ์–‘์ƒ์ด๋ผ๊ณ  ๊ฐœ๋…ํ™”ํ•˜์˜€๋‹ค

(Clark, 2007; Samuel & Widiger, 2008; Widiger, Costa, & McCrae,

2002). ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ ํ๋ฆ„์€ Diagnostic Statistical Manual of Mental

Disorders 5 (DSM-5; APA, 2013)์˜ ๊ฐœ๋ฐœ ๊ณผ์ •์—๋„ ์˜ํ–ฅ์„ ์ฃผ์–ด, ์„ฑ

๊ฒฉ์žฅ์• ์— ๋Œ€ํ•œ ๊ธฐ๋ณธ์ ์ธ ๋ฒ”์ฃผ์  ์ •๋ณด์— ๋”ํ•˜์—ฌ ์„ฑ๊ฒฉ์„ ์ฐจ์›์ ์œผ๋กœ

์ ‘๊ทผํ•˜๋Š” ๊ด€์ ์˜ ์ค‘์š”์„ฑ์ด ๊ฐ•์กฐ๋˜์—ˆ๋‹ค(Zachar, Krueger, & Kend-

ยฉ 2019 Korean Clinical Psychology Association

Korean Journal of Clinical Psychology 2019. Vol. 38, No. 3, 318-334

eISSN 2733-4538

โ€ Correspondence to Dong Gi Seo, Department of Psychology, Hallym University, 1 Hallymdaehak-gil, Chuncheon, Korea; E-mail: [email protected]โ€ Correspondence to Kee-Hong Choi, Department of Psychology, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, Korea; E-mail: [email protected]โ€ Correspondence to Doo Jin Park, PBCG (Psychology based Consulting Group), 12 Jangchungdan-ro 8-gil, Jung-gu, Seoul, Korea; E-mail: [email protected]

Received May 16, 2019; Revised Aug 17, 2019; Accepted Aug 19, 2019

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5A2A03030006).

Original Article

https://doi.org/10.15842/kjcp.2019.38.3.005

Multi-dimensional Personality Assessment

319https://doi.org/10.15842/kjcp.2019.38.3.005

ler, 2016). ์ด์— ๋”ฐ๋ผ ์ตœ์‹  ์—ฐ๊ตฌ๋“ค์€ ์„ฑ๊ฒฉ์— ๋Œ€ํ•œ ๋ฒ”์ฃผ์  ์ ‘๊ทผ์˜ ๋Œ€

์•ˆ์  ๋ชจํ˜•์œผ๋กœ์„œ ์ฐจ์›์  ์„ฑ๊ฒฉ ๋ชจ๋ธ์˜ ํƒ€๋‹น์„ฑ์„ ์ง€์ง€ํ•˜๊ณ  ์žˆ๋‹ค

(Bach, Markon, Simonsen, & Krueger, 2015; O'Connor, 2005;

Trull & Durrett, 2005; Widiger & Trull, 2007).

์„ฑ๊ฒฉ์— ๋Œ€ํ•ด ํญ๋„“๊ฒŒ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ฐจ์›์  ์„ฑ๊ฒฉ ๋ชจ๋ธ์„ ํ†ตํ•œ

์ ‘๊ทผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ณผ ๋ถ€์ ์‘์  ์„ฑ๊ฒฉ์˜ ํ†ตํ•ฉ์  ์ธก์ •๋„ ํ•จ๊ป˜

๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ์˜ค๋Š˜๋‚  ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋Š” ์„ฑ๊ฒฉ๊ฒ€์‚ฌ๋Š” ํ†ต์ƒ์ ์œผ๋กœ

์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ณผ ๋ถ€์ ์‘์  ์„ฑ๊ฒฉ์„ ์ธก์ •ํ•˜๋Š” ๊ฒ€์‚ฌ๋กœ ๊ตฌ๋ถ„๋˜์–ด ์‚ฌ์šฉ๋œ

๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒ€์‚ฌ์˜ ์‚ฌ์šฉ์€ ํ•„์š”์™€ ์ƒํ™ฉ์— ๋”ฐ๋ผ ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ์„ ์ธก

์ •ํ•˜๊ฑฐ๋‚˜ ๋ถ€์ ์‘์  ์„ฑ๊ฒฉํŠน์„ฑ์„ ์ธก์ •ํ•˜์—ฌ ์„ฑ๊ฒฉ์˜ ๋‹จํŽธ์ ์ธ ์ธก๋ฉด๋งŒ

์„ ํ‰๊ฐ€ํ•˜๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ผ๋ฐ˜์ธ์—๊ฒŒ๋„ ๋ถ€์ ์‘์  ์„ฑ๊ฒฉํŠน์งˆ

์ด ์ผ๋ถ€ ์กด์žฌํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ์ด๋Š” ๊ฐœ์ธ์˜ ์„ฑ์žฅ์„ ๋ฐฉํ•ดํ•˜๊ณ  ๋Œ€์ธ๊ด€๊ณ„

๋ฐ ์‚ฌํšŒ์ ์‘์„ ์ €ํ•ดํ•  ์ˆ˜ ์žˆ๋‹ค(Fonseca-Pedrero et al., 2011; Glea-

son, Weinstein, Balsis, & Oltmanns, 2014). ๋ฐ˜๋Œ€๋กœ ์ž„์ƒ๊ตฐ๋„ ๊ฐœ๊ฐœ

์ธ์˜ ๊ณ ์œ ํ•œ ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์งˆ์„ ํŒŒ์•…ํ•˜์—ฌ ๊ฐœ์ธ์˜ ์žฅ์•  ์–‘์ƒ ๋ฐ ๊ธฐ๋Šฅ

์ˆ˜์ค€์„ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๋‹ค(Piedmont, Sherman, Sherman, Dy-Liacco,

& Williams, 2009). ๋”ฐ๋ผ์„œ ์„ฑ๊ฒฉ์˜ ์ผ๋ถ€ ์ธก๋ฉด๋งŒ์„ ์ธก์ • ๋ฐ ํ‰๊ฐ€ํ•˜

๋Š” ๋ฐฉ์‹์€ ์„ฑ๊ฒฉ์˜ ๋‹ค๊ฐ์  ์ธก๋ฉด์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ํ•œ๊ณ„๋กœ ์ž‘์šฉํ•œ๋‹ค.

์ฐจ์›์  ์„ฑ๊ฒฉ๋ชจํ˜•์— ๊ทผ๊ฑฐํ•˜์—ฌ ์„ฑ๊ฒฉ์„ ํ†ตํ•ฉ์ ์œผ๋กœ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•ด

์„œ๋Š” ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๊ณผ ๋ถ€์ ์‘์  ์„ฑ๊ฒฉํŠน์„ฑ์˜ ๊ด€๊ณ„๋ฅผ ์ดํ•ดํ•  ํ•„์š”๊ฐ€

์žˆ๋‹ค. ์ตœ๊ทผ์˜ ์—ฐ๊ตฌ๋“ค(Thomas et al., 2013; Watson, Stasik, Ro, &

Clark, 2013)์€ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ์ฐจ์›์„ ์ธก์ •ํ•˜๋Š” 5์š”์ธ ๋ชจ๋ธ์— ๊ทผ๊ฑฐํ•œ ์„ฑ

๊ฒฉํ‰๊ฐ€ ์ฒ™๋„์™€ ๋ณ‘๋ฆฌ์  ์„ฑ๊ฒฉ์ฐจ์›์„ ์ธก์ •ํ•˜๋Š” Personality Inventory

for DSM-5 (PID-5; Krueger, Derringer, Markon, Watson, &

Skodol, 2012)์™€์˜ ๊ด€๋ จ์„ฑ์„ ๋ณด๊ณ ํ•˜์˜€๋Š”๋ฐ, ์ผ๋ฐ˜ ์„ฑ๊ฒฉ์ฐจ์›๊ณผ ์„ฑ๊ฒฉ

์žฅ์•  ์ฐจ์› ๊ฐ„์— ์–ด๋Š ์ •๋„์˜ ์ƒ๊ด€์€ ์กด์žฌํ•˜๋‚˜ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ์ฐจ์›์œผ๋กœ

์„ฑ๊ฒฉ์žฅ์•  ์ฐจ์›์„ ๋ชจ๋‘ ์„ค๋ช…ํ•˜์ง€๋Š” ๋ชปํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ์˜ˆ๋ฅผ ๋“ค

๋ฉด, Thomas ๋“ฑ(2013)์€ ํƒˆ์–ต์ œ(Disinhibition)๊ฐ€ ์„ฑ์‹ค์„ฑ(Conscien-

tiousness)์— ๋Œ€์‘๋  ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์˜€์œผ๋‚˜ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ

ํƒˆ์–ต์ œ ํ•˜์œ„ ์–‘์ƒ ์ค‘ ์ถฉ๋™์„ฑ(Impulsivity)๊ณผ ๊ฒฝ์ง๋œ ์™„๋ฒฝ์ฃผ์˜(Rig-

id perfectionism)๋ฅผ ์ œ์™ธํ•œ ํ•˜์œ„ ์–‘์ƒ์—์„œ ์š”์ธ๋ถ€ํ•˜๋Ÿ‰์ด .3 ์ดํ•˜๋กœ

๋‚˜ํƒ€๋‚˜ ๋†’์€ ๋ถ€ํ•˜๋Ÿ‰์„ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. Watson ๋“ฑ(2013)์€ ๊ฐœ๋ฐฉ์„ฑ

(Openness)์„ ์ •์‹ ์ฆ(Psychoticism)์— ๋Œ€์‘๋˜๋Š” ์˜์—ญ์œผ๋กœ ๊ฐ€์ •ํ•˜

์˜€์œผ๋‚˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์—์„œ๋Š” ๋‘ ์˜์—ญ ๊ฐ„์— ๋‚ฎ์€ ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค(r= .15,

p< .05). ์ฆ‰, ์ผ๋ฐ˜ ์„ฑ๊ฒฉ์ฐจ์›๊ณผ ๋ถ€์ ์‘ ์„ฑ๊ฒฉ์ฐจ์›์€ ๋…๋ฆฝ์ ์œผ๋กœ ์ธก์ •

๋˜์–ด์•ผ ํ•˜๊ณ , ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋‘ ์„ฑ๊ฒฉ์ฐจ์› ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ๋ฐํžˆ๊ณ  ํ†ตํ•ฉ

์ ์œผ๋กœ ์ดํ•ดํ•  ์ˆ˜ ์žˆ์–ด์•ผ ํ•œ๋‹ค. ์ด์™€ ๊ฐ™์ด ์ฐจ์›์  ์„ฑ๊ฒฉ๋ชจํ˜•์— ๊ทผ๊ฑฐ

ํ•œ ์„ฑ๊ฒฉ์˜ ํ†ตํ•ฉ์ ์ธ ์ดํ•ด๋Š” ์ •์‹ ๋ณ‘๋ฆฌ ์ง„๋‹จ, ์‹ฌ๋ฆฌํ‰๊ฐ€ ๋ฐ ์‹ฌ๋ฆฌ์น˜๋ฃŒ๋ฅผ

ํฌํ•จํ•˜๋Š” ์ „๋ฌธ์ ์ธ ์‹ฌ๋ฆฌ์„œ๋น„์Šค๋ฅผ ์ œ๊ณตํ•˜๋Š” ์ž„์ƒ ๋ฐ ์ƒ๋‹ด์‹ฌ๋ฆฌ ์˜์—ญ

์—์„œ ๋ฟ ์•„๋‹ˆ๋ผ(Bach et al., 2015; Cuijpers, van Straten, & Donker,

2005; Hwang, Jo, Park, & Lee, 2015; Samuel & Widiger, 2006), ์ •์‹ 

๋ณ‘๋ฆฌ๊ฐ€ ์—†๋Š” ์ผ๋ฐ˜์ธ, ๋Œ€ํ•™์ƒ ๋ฐ ์ง์žฅ์ธ ๋“ฑ์˜ ์ ์‘๊ณผ ์ž์•„ ์„ฑ์žฅ์„ ์œ„

ํ•ด์„œ๋„ ํ•„์ˆ˜์ ์ด๋‹ค(Ha, Hwang, & Nam, 2008; Judge, Heller, &

Mount, 2002; Lee, 2002; Yoo & Min, 2001).

๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ณผ ๋ถ€์ ์‘ ์„ฑ๊ฒฉ์„ ํ•จ๊ป˜ ์ธก์ •ํ• 

์ˆ˜ ์žˆ๋Š” ๋‹ค์ฐจ์› ์„ฑ๊ฒฉํ‰๊ฐ€ ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ๋ฅผ

๊ฐœ๋ฐœํ•˜๋ฉด์„œ ์•„๋ž˜์— ๊ธฐ์ˆ ํ•œ ๊ธฐ์กด ๊ฒ€์‚ฌ๊ฐ€ ์ง€๋‹ˆ๊ณ  ์žˆ์—ˆ๋˜ ํ•œ๊ณ„๋ฅผ ๋ณด์™„

ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ฒซ์งธ, ๋Œ€๋‹ค์ˆ˜ ์„ฑ๊ฒฉ๊ฒ€์‚ฌ๋Š” ์™ธ๊ตญํŒ์˜ ๋ฒˆ์•ˆ๋ณธ์œผ๋กœ ํ•œ

๊ตญ ๊ณ ์œ ์˜ ๋ฌธํ™”์  ์š”์†Œ์— ๋Œ€ํ•œ ๊ณ ๋ ค๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋œ ์ด๋ฃจ์–ด์กŒ๋‹ค

(Shin & Hwang, 2016; Yoo, Lee, & Ashton, 2004). ์„ฑ๊ฒฉ์€ ๊ธฐ์งˆ๊ณผ ํ™˜

๊ฒฝ์ด ์ƒํ˜ธ์ž‘์šฉํ•˜์—ฌ ๋งŒ๋“ค์–ด์ง€๊ณ  ์‚ฌํšŒ ๋ฌธํ™”์  ํ•™์Šต ์†์—์„œ ์ผ์ƒ ๋™

์•ˆ ์ง€์†์ ์œผ๋กœ ๋ฐœ๋‹ฌํ•˜๋ฉฐ(Oh, Goth, & Min, 2008), ์‚ฌํšŒ์  ๋ฐ ๋ฌธํ™”

์  ๋งฅ๋ฝ์€ ์„ฑ๊ฒฉ์˜ ํ˜•์„ฑ์— ์ค‘์š”ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น  ๋ฟ ์•„๋‹ˆ๋ผ ์„ฑ๊ฒฉ์˜ ์ 

์‘์„ฑ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•˜๋Š” ๋ฐ๋„ ์ค‘์š”ํ•œ ๊ธฐ์ค€์ด ๋œ๋‹ค(Seo & Hwang,

2006). ์ด๋Ÿฐ ์ ์—์„œ ๋ฌธํ™”๋งˆ๋‹ค ๊ฐœ๋ณ„ ํ–‰๋™์˜ ์˜๋ฏธ์™€ ์ค‘์š”์„ฑ๋„ ๋‹ฌ๋ผ์ง€

๋ฉฐ, ์„ฑ๊ฒฉํ‰๊ฐ€ ๋„๊ตฌ์˜ ์›ํŒ๊ณผ ๋‹ค๋ฅธ ์š”์ธ๊ตฌ์กฐ๊ฐ€ ํ™•์ธ๋˜๊ธฐ๋„ ํ•œ๋‹ค

(Min, 1996). ๋‘˜์งธ, ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์˜ ํƒ€๋‹นํ™” ์—ฐ๊ตฌ๋Š” ์ œํ•œ๋œ ํ‘œ๋ณธ์„ ๋Œ€์ƒ

์œผ๋กœ ์ด๋ฃจ์–ด์กŒ๋‹ค. ๊ตญ๋‚ด์—์„œ ์„ฑ๊ฒฉ๊ฒ€์‚ฌ๋กœ ๋งŽ์ด ์‚ฌ์šฉ๋˜๋Š” NEO Per-

sonality Inventory, Revised (NEO-PI-R; Costa & McCrae, 1992)์˜

๊ฒฝ์šฐ๋„ ์ œํ•œ๋œ ํ‘œ๋ณธ์œผ๋กœ ํƒ€๋‹นํ™” ์ž‘์—…์ด ์ด๋ฃจ์–ด์กŒ์œผ๋ฉฐ(Ahn & Chae,

1997; Lee, 1994, 1995; Min & Park, 2000), ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ๊ฒ€์‚ฌ์˜ ๊ตญ

๋‚ด ํƒ€๋‹น์„ฑ์„ ์ผ๋ฐ˜ํ™”ํ•˜๋Š” ๋ฐ ์ œํ•œ์ ์ด๋‹ค. ์…‹์งธ, ๊ธฐ์กด ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์˜ ๊ฒฝ

์šฐ, ๋ฌธํ•ญ ์ˆ˜๊ฐ€ ๋งŽ์•„ ๊ฒ€์‚ฌ๋ฅผ ์‹ค์‹œํ•˜๋Š” ๋ฐ ๋งŽ์€ ์‹œ๊ฐ„๊ณผ ๋น„์šฉ์ด ์†Œ์š”๋˜

์–ด ๋‹ค์–‘ํ•œ ์žฅ๋ฉด์—์„œ ์‚ฌ์šฉํ•˜๊ธฐ์—๋Š” ์ œ์•ฝ์ด ์กด์žฌํ•œ๋‹ค. ์ฆ‰, ๊ฒ€์‚ฌ์˜ ๋น„

์šฉ-ํšจ์œจ์„ฑ์ด ๋ฌธ์ œ์ ์œผ๋กœ ์ œ๊ธฐ๋˜์–ด ์™”๋‹ค(Hong, Kim, & Hwang, 2018;

Jung, Lee, Lee, & Lee, 2011).

์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ์ž„์ƒ์‹ฌ๋ฆฌ์ „๋ฌธ๊ฐ€, ์‹ฌ๋ฆฌ์ธก์ •์ „๋ฌธ๊ฐ€ ๋ฐ ๊ธฐ์—…์ปจ์„คํŒ…

์ „๋ฌธ๊ฐ€์˜ ๊ณต๋™ ์ž‘์—…์„ ํ†ตํ•˜์—ฌ ์ƒ๋Œ€์ ์œผ๋กœ ์ ์€ ์ˆ˜์˜ ๋ฌธํ•ญ์œผ๋กœ ํ•œ

๊ตญ์ธ์˜ ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ์„ ํ‰๊ฐ€ํ•˜๋Š” ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๋ ค๋Š” ๋ชฉ์ ์œผ๋กœ ์ง„

ํ–‰๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•œ๊ตญํ˜• ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ(Big 10 Inventory,

BTI)์˜ ๊ฐœ๋ฐœ๊ณผ์ •์„ ๊ธฐ์ˆ ํ•˜๊ณ , ๊ฒ€์‚ฌ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ 5์š”

์ธ(Bright 5)๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ 5์š”์ธ(Dark 5)์˜ ์š”์ธ ๊ตฌ์กฐ์™€ ์‹ ๋ขฐ

๋„, Bright 5์™€ Dark 5์˜ ํƒ€๋‹น๋„๋ฅผ ๋‹ค๋ฉด์ ์œผ๋กœ ๊ฒ€์ฆํ•˜์˜€๋‹ค.

์˜ˆ๋น„์กฐ์‚ฌ

์˜ˆ๋น„๋ฌธํ•ญ ๊ฐœ๋ฐœ

BTI์˜ ๊ฐœ๋ฐœ์„ ์œ„ํ•ด ์—ฐ๊ตฌ์ง„์€ ์ธ๊ฐ„์˜ ์„ฑ๊ฒฉ์— ๋Œ€ํ•œ ๊ด‘๋ฒ”์œ„ํ•œ ๋ฌธํ—Œ ์—ฐ

๊ตฌ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ Bright 5์™€ Dark 5๋กœ ๊ตฌ์„ฑ๋œ 10์š”์ธ ์„ฑ๊ฒฉ ๋ชจํ˜•์„ ๊ตฌ

์ƒํ•˜์˜€๋‹ค. Bright 5๋Š” ์„ฑ๊ฒฉ์˜ Big 5 ๋ชจํ˜•์„ ๊ธฐ๋ฐ˜์œผ๋กœ, Dark 5๋Š”

Lee et al.

320 https://doi.org/10.15842/kjcp.2019.38.3.005

DSM-5 section III์—์„œ ์ œ์•ˆํ•œ โ€˜๋ณ‘๋ฆฌ์  ์„ฑ๊ฒฉ ํŠน์งˆโ€™ ๋ชจํ˜•(APA, 2013)

์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์ง„์€ Bright 5์˜ ์š”์ธ๋ช…์„ ์™ธํ–ฅ-๋‚ดํ–ฅ

์„ฑ, ์ˆ˜์šฉ์„ฑ, ์„ฑ์‹ค์„ฑ, ๊ฐœ๋ฐฉ์„ฑ, ์ •์„œ์•ˆ์ •์„ฑ์œผ๋กœ, Dark 5์˜ ์š”์ธ๋ช…์„ ๋Œ€

์ธํšŒํ”ผ์„ฑ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ, ์ฃผ์˜๊ณค๋ž€์„ฑ, ์ •์‹ ์ฆ์„ฑ, ๋ถ€์ •์ •์„œ์„ฑ์œผ๋กœ ๋ช…๋ช…

ํ•˜์˜€๋‹ค. ๊ฐ ์š”์ธ๊ณผ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ ๋…ผ๋ฌธ๊ณผ ๊ธฐ์กด ์„ฑ๊ฒฉ๊ฒ€์‚ฌ, ๊ทธ๋ฆฌ๊ณ  ํ•œ๊ตญ

์ธ์—๊ฒŒ์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๊ธฐ์กด ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์˜ ์ ์šฉ ๊ฒฐ๊ณผ ๋“ฑ์„ ํฌ๊ด„์ ์œผ๋กœ

๊ฒ€ํ† ํ•˜์—ฌ ํ•˜์œ„์š”์ธ ๋ฐ ๋ฌธํ•ญ์„ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน

์„ฑ์˜ ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ์€ ํ™œ๋ ฅ, ์‚ฌ๊ต, ์ฃผ๋„, ์ˆ˜์šฉ์„ฑ์€ ์‹ ๋ขฐ, ๊ด€๋Œ€, ์ดํƒ€, ์„ฑ

์‹ค์„ฑ์€ ๋ˆ๊ธฐ, ์„ฑ์ทจ, ์ฒด๊ณ„, ๊ฐœ๋ฐฉ์„ฑ์€ ์‹ฌ๋ฏธ, ํƒ๊ตฌ, ์ฒดํ—˜, ์ •์„œ์•ˆ์ •์„ฑ์€

์ •์„œ์ˆ˜์šฉ, ์ •์„œํ‘œํ˜„, ์ •์„œ์ธ์‹์˜ ํ•˜์œ„์š”์ธ์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ๋ถ€์ ์‘

์œ„ํ—˜ํŠน์„ฑ์˜ ๋Œ€์ธํšŒํ”ผ์„ฑ์€ ๊ณ ๋ฆฝ, ๋ฌด์พŒ, ์˜์‹ฌ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ์€ ์—ฐ๊ธฐ, ์ž

๊ธฐ์• , ์กฐ์ข…, ๋ƒ‰ํ˜น, ์ฃผ์˜๊ณค๋ž€์„ฑ์€ ์‚ฐ๋งŒ, ์ถฉ๋™, ์ง‘์ฐฉ, ๊ฐ•๋ฐ•, ์ •์‹ ์ฆ์„ฑ์€

๊ธฐ์ด, ์กฐํ˜„, ๊ฒฝ์ง, ๋ถ€์ •์ •์„œ์„ฑ์€ ์˜์กด, ๋ถ„๋…ธ, ๋ถˆ์•ˆ, ์—ด๋“ฑ์˜ ํ•˜์œ„์š”์ธ

์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ์ดํ›„ ์ž„์ƒ์‹ฌ๋ฆฌ์ „๋ฌธ๊ฐ€ 1๋ช…, ๊ณ„๋Ÿ‰์‹ฌ๋ฆฌ์ „๋ฌธ๊ฐ€ 1๋ช…, ๊ธฐ

์—…์ปจ์„คํŒ…์ „๋ฌธ๊ฐ€ 1๋ช…, ์ž„์ƒ์‹ฌ๋ฆฌํ•™ ์„์‚ฌ 1๋ช…, ๊ณ„๋Ÿ‰์‹ฌ๋ฆฌํ•™ ์„์‚ฌ 1๋ช…๊ณผ

์ž„์ƒ ๋ฐ ์ƒ๋‹ด์‹ฌ๋ฆฌํ•™ ์ „๊ณต ์„์‚ฌ๊ณผ์ • 1๋ช…, ๊ณ„๋Ÿ‰์‹ฌ๋ฆฌํ•™ ์ „๊ณต ์„์‚ฌ๊ณผ์ •

1๋ช…์ด ํ•จ๊ป˜ ์ž ์ •์  ๋ฌธํ•ญ pool์˜ ๋‚ด์šฉํƒ€๋‹น๋„๋ฅผ ํ™•์ธํ•˜๊ณ , ์š”์ธ์„ ์ž˜

์ธก์ •ํ•  ๊ฒƒ์ด๋ผ๊ณ  ํ•ฉ์˜๋œ ๋ฌธํ•ญ์„ ์„ ๋ณ„ํ•˜์—ฌ ์˜ˆ๋น„๋ฌธํ•ญ์„ ๊ตฌ์„ฑํ•˜์˜€๋‹ค.

๊ทธ ๊ฒฐ๊ณผ๋กœ ์ด 33๊ฐœ ํ•˜์œ„์š”์ธ, 234๊ฐœ ๋ฌธํ•ญ์œผ๋กœ ์ด๋ฃจ์–ด์ง„ ๊ฒ€์‚ฌ๋ฅผ ์ผ

์ฐจ์ ์œผ๋กœ ๊ตฌ์„ฑํ•˜์˜€๋‹ค.

์—ฐ๊ตฌ๋Œ€์ƒ

์˜จ๋ผ์ธ ์„ค๋ฌธ ์ „๋ฌธ์—…์ฒด๋ฅผ ์ด์šฉํ•˜์—ฌ ์„ฑ์ธ 1,200๋ช…์„ ๋ชจ์ง‘ํ•˜์—ฌ ์˜ˆ๋น„

์กฐ์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. 20โ€“50๋Œ€ ๊ฐ 300๋ช…์”ฉ ๊ณ ๋ฃจ ๋ถ„ํฌ๋˜๊ฒŒ ์ˆ˜์ง‘ํ•˜์˜€

์œผ๋ฉฐ, ์„ฑ๋น„๋Š” 1:1๋กœ ์กฐ์ ˆํ•˜์˜€๋‹ค. ์ „์ฒด ๋Œ€์ƒ์ž์˜ ํ‰๊ท  ์—ฐ๋ น์€ 39.49์„ธ

(SD=10.94, ๋ฒ”์œ„=20โ€“59)์˜€๋‹ค. ์ด๋“ค์€ ๊ธฐํ˜ผ 55.1%, ๋ฏธํ˜ผ 44.9%์ด

์—ˆ์œผ๋ฉฐ, ์ตœ์ข…ํ•™๋ ฅ์€ ๊ณ ์กธ 22.6%, ์ „๋ฌธ๋Œ€์กธ 13.8%, ๋Œ€์กธ 55.2%, ๋Œ€ํ•™

์›์กธ 8.4%๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ง์—…์€ ์‚ฌ๋ฌด์ง 42.4%, ๊ธฐ์ˆ ์ง 8.2%, ์„œ๋น„์Šค

์ง 6.5%, ์ž์˜์—… 8.1%, ๋†๋ฆผ์–ด์—… 0.1%, ์ฃผ๋ถ€ 12.6%, ํ•™์ƒ 9.6%, ๋ฌด์ง

5.4%, ๊ธฐํƒ€ 7.2%์ด์—ˆ๋‹ค.

์—ฐ๊ตฌ์ ˆ์ฐจ

์˜จ๋ผ์ธ ์„ค๋ฌธ์œผ๋กœ ์‹ค์‹œํ•˜๊ธฐ์—๋Š” ๋ฌธํ•ญ ์ˆ˜๊ฐ€ ๋งŽ๋‹ค๊ณ  ํŒ๋‹จํ•˜์˜€๋‹ค. ์ด์—

์‘๋‹ต์ž์˜ ๋ถ€๋‹ด์„ ์ค„์ด๊ณ  ํ‘œ๋ณธ ์ˆ˜๋ฅผ ์ถฉ๋ถ„ํžˆ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์‘๋‹ต

์ž 1,200๋ช…์„ 400๋ช…์”ฉ 3๊ฐœ ์ง‘๋‹จ์œผ๋กœ ๋ฌด์ž‘์œ„๋กœ ๋ถ„๋ฅ˜ํ•˜์˜€๊ณ  ๋ถ€๋ถ„์ 

์œผ๋กœ ์ฐจ์ด๊ฐ€ ์žˆ๋Š” ์„ค๋ฌธ์„ ์ œ์‹œํ•˜์—ฌ ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ์ด ๋ฐฉ์‹์€

PID-5์˜ ๊ฐœ๋ฐœ ๊ณผ์ •์„ ์ฐธ์กฐํ•˜์˜€๋Š”๋ฐ(Krueger et al., 2012), ์˜ˆ๋ฅผ ๋“ค

์–ด ํ•˜์œ„์š”์ธ์„ ๊ตฌ์„ฑํ•˜๋Š” 7๊ฐœ ๋ฌธํ•ญ ๊ฐ€์šด๋ฐ 1๊ฐœ ๋ฌธํ•ญ์€ ๊ณตํ†ต ๋ฌธํ•ญ์œผ

๋กœ ์„ธ ์ง‘๋‹จ ๋ชจ๋‘์—๊ฒŒ ์ œ์‹œํ•˜๊ณ , ๋‚˜๋จธ์ง€ 6๊ฐœ ๋ฌธํ•ญ์„ 2๊ฐœ ๋ฌธํ•ญ์”ฉ ๋‚˜๋ˆ„

์–ด ๊ฐ ์ง‘๋‹จ์— ์ œ์‹œํ•˜์˜€๋‹ค. ๊ฐ ์ง‘๋‹จ๋ณ„๋กœ ๊ด€์ฐฐ๋˜์ง€ ์•Š์€ ์ž๋ฃŒ๋ฅผ ๊ฒฐ์ธก

์น˜๋กœ ๋ณด๊ณ  ๋‹ค์ค‘ ๋Œ€์ฒด(multiple imputation) ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ๊ฐ’์„

์ถ”์ •ํ•˜์˜€๋‹ค. ๋‹ค์ค‘ ๋Œ€์ฒด ๋ฐฉ๋ฒ•์€ R 3.3.0 (R Core Team, 2016)์˜ miss-

Forest ํŒจํ‚ค์ง€(Stekhoven & Buhlmann, 2012)๋ฅผ ์ด์šฉํ•˜์—ฌ ๋žœ๋ค ํฌ

๋ ˆ์ŠคํŠธ(random forest)๋ฐฉ์‹์„ ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ, ๋‹ค์ค‘ ๋Œ€์ฒด๋œ ๊ฐ’์œผ๋กœ

ํ›„์† ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋ฌธํ•ญ์„ ์ •์„ ์œ„ํ•ด SPSS 23์„ ์ด์šฉํ•˜์—ฌ ๊ฐ

๋ฌธํ•ญ์˜ ๋ฐ˜์‘๋ถ„ํฌ์™€ ๊ธฐ์ˆ ํ†ต๊ณ„, ํ•˜์œ„์š”์ธ ์ˆ˜์ค€์—์„œ์˜ ๋‚ด์  ์ผ๊ด€์„ฑ์„

ํ™•์ธํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ Mplus 7 (Muthรฉn & Muthรฉn, 2012)์„ ์ด

์šฉํ•˜์—ฌ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„๊ณผ ํ™•์ธ์  ์š”์ธ๋ถ„์„์„ ํ†ตํ•˜์—ฌ ์ „์ฒด ์š”์ธ๊ตฌ

์กฐ์˜ ์ ํ•ฉ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค.

๋ฌธํ•ญ์„ ์ • ๋‹จ๊ณ„์—์„œ๋Š” ๋‹ค์Œ ๊ธฐ์ค€์— ๋”ฐ๋ผ ์‚ญ์ œ ๋ฌธํ•ญ์„ ๊ฒฐ์ •ํ•˜์˜€

๋‹ค. (1) ๋ฌธํ•ญ์ด ์ •๊ทœ์„ฑ(normality)์„ ์œ„๋ฐ˜ํ•˜๋Š” ๊ฒฝ์šฐ, (2) ์š”์ธ์˜ ๋‚ด์ 

์ผ๊ด€์„ฑ์„ ์ €ํ•ดํ•˜๋Š” ๊ฒฝ์šฐ, (3) ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„์—์„œ ์š”์ธ๋ถ€ํ•˜๋Ÿ‰์ด

๋‚ฎ๊ฑฐ๋‚˜(.3 ์ดํ•˜) ๊ต์ฐจ๋ถ€ํ•˜(cross-loading)๊ฐ€ ํ™•์ธ๋˜๋Š” ๊ฒฝ์šฐ, (4) ํ™•

์ธ์  ์š”์ธ๋ถ„์„์—์„œ ์š”์ธ๋ถ€ํ•˜๋Ÿ‰์ด ๋‚ฎ์€(.3 ์ดํ•˜) ๊ฒฝ์šฐ์— ๋ฌธํ•ญ์„ ์‚ญ

์ œํ•˜์˜€๋‹ค. ๋‹ค๋งŒ ์‚ญ์ œ ๊ธฐ์ค€์ด ์ถฉ์กฑ๋˜๋”๋ผ๋„ ์—ฐ๊ตฌ์ง„์˜ ๋…ผ์˜๋ฅผ ๊ฑฐ์ณ

๋‚ด์šฉ์ƒ ํ•ด๋‹น ์š”์ธ์„ ์ธก์ •ํ•˜๋Š” ์ค‘์š”ํ•œ ์ •๋ณด๋ฅผ ๋‹ด๊ณ  ์žˆ๋‹ค๊ณ  ํŒ๋‹จ๋˜๋Š”

๋ฌธํ•ญ์€ ์œ ์ง€ํ•˜์˜€๋‹ค. ์ •๊ทœ๋ถ„ํฌ์˜ ์™œ๋„(skewness)์˜ ์ ˆ๋Œ€๊ฐ’ 2์™€ ์ฒจ๋„

(kurtosis)์˜ ์ ˆ๋Œ€๊ฐ’ 7์„ ๊ธฐ์ค€์œผ๋กœ ์ž๋ฃŒ์˜ ์ •๊ทœ์„ฑ์„ ๊ฒ€์ฆํ•œ ๊ฒฐ๊ณผ

(West, Finch, & Curran, 1995), ๋ชจ๋“  ๋ฌธํ•ญ์ด ์ด ๊ธฐ์ค€์„ ์ถฉ์กฑํ•˜์˜€๋‹ค.

๋‚ด์  ์ผ๊ด€์„ฑ ๊ธฐ์ค€์˜ ๊ฒฝ์šฐ, ์š”์ธ์˜ ๋‚ด์  ์ผ๊ด€์„ฑ์ด .7 ์ดํ•˜, ๋ฌธํ•ญ์ œ๊ฑฐ

ํ›„ ๋‚ด์  ์ผ๊ด€์„ฑ ์ƒ์Šน, ๋ฌธํ•ญ-์ด์  ์ƒ๊ด€(Item total correlation, ITC)

์ด ๋‚ฎ์€ ๋ฌธํ•ญ์„ ์‚ญ์ œ์˜ ์šฐ์„ ์ˆœ์œ„๋กœ ๋‘์—ˆ๋‹ค.

์—ฐ๊ตฌโ€ƒ๊ฒฐ๊ณผ

์ˆ˜์ง‘๋œ ์ž๋ฃŒ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ฌธํ•ญ ์‚ญ์ œ์™€ ์š”์ธ๋ช… ์ˆ˜์ •์˜ ๊ณผ์ •์„ ๊ฑฐ์ณ

์š”์ธ์„ ์žฌ๊ตฌ์กฐํ™”ํ•˜์˜€๋‹ค. Bright 5์˜ ๊ฒฝ์šฐ, ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ(Extraver-

sion-Introversion)์€ ์‚ฌ๋žŒ๋“ค๊ณผ ๊ด€๊ณ„์—์„œ ํ™œ๋ ฅ์„ ์–ป์œผ๋ฉฐ ๋Œ€์ธ๊ด€๊ณ„

๋ฅผ ํ™•์žฅํ•˜๊ณ  ์˜ํ–ฅ๋ ฅ์„ ํ–‰์‚ฌํ•˜๊ณ ์ž ํ•˜๋Š” ์„ฑํ–ฅ, ์ˆ˜์šฉ์„ฑ(Agreeable-

ness)์€ ์›๋งŒํ•œ ๊ด€๊ณ„๋ฅผ ์ค‘์š”์‹œํ•˜๋ฉฐ ํƒ€์ธ์—๊ฒŒ ๊ณต๊ฐํ•˜๋ฉฐ, ๋„ˆ๊ทธ๋Ÿฝ๊ณ 

์‹ ๋ขฐ๋กญ๊ฒŒ ํ–‰๋™ํ•˜๋Š” ์„ฑํ–ฅ, ์„ฑ์‹ค์„ฑ(Conscientiousness)์€ ์งˆ์„œ์™€ ์ฒด

๊ณ„๋ฅผ ์ค‘์‹œํ•˜๋ฉฐ ์‚ฌํšŒ ๊ด€์Šต๊ณผ ๊ธฐ์ค€์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ๋…ธ๋ ฅํ•˜๋Š” ์„ฑํ–ฅ,

๊ฐœ๋ฐฉ์„ฑ(Openness)์€ ์ž๊ธฐ ๋‚ด๋ฉด๊ณผ ์„ธ์ƒ์— ๋Œ€ํ•œ ํ˜ธ๊ธฐ์‹ฌ์ด ํ’๋ถ€ํ•˜๋ฉฐ

์ƒˆ๋กญ๊ณ  ๋‹ค์–‘ํ•œ ๊ฒฝํ—˜์„ ์ถ”๊ตฌํ•˜๋Š” ์„ฑํ–ฅ, ๋งˆ์ง€๋ง‰์œผ๋กœ ์ •์„œ์•ˆ์ •์„ฑ

(Emotional Stability)์€ ๊ฐ์ •์„ ์–ต์••ํ•˜๊ฑฐ๋‚˜ ๋‘๋ ค์›Œํ•˜์ง€ ์•Š๊ณ , ๊ฑด๊ฐ•

ํ•˜๊ณ  ์„ฑ์ˆ™ํ•œ ๋ฐฉ์‹์œผ๋กœ ์ˆ˜์šฉํ•˜๊ณ  ํ‘œํ˜„ํ•˜๋Š” ์„ฑํ–ฅ์œผ๋กœ ์žฌ๊ตฌ์กฐํ™”ํ•˜์˜€

๋‹ค. ๋ฌธํ•ญ์€ ๊ธฐ์กด 108๋ฌธํ•ญ ์ค‘ 46๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜์˜€๊ณ  ๋‚จ์€ 62๋ฌธํ•ญ๊ณผ

์ถ”๊ฐ€ ๊ฐœ๋ฐœํ•œ 27๋ฌธํ•ญ์„ ํฌํ•จํ•˜์—ฌ 89๋ฌธํ•ญ์„ ์ƒˆ๋กญ๊ฒŒ ๊ตฌ์„ฑํ•˜์˜€๋‹ค.

Dark 5์˜ ๊ฒฝ์šฐ, ๋Œ€์ธํšŒํ”ผ์„ฑ(Detachment)์€ ๊ธ์ • ์ •์„œ๋ฅผ ๊ฒฝํ—˜ํ•˜

๊ธฐ ์–ด๋ ต๊ณ  ๋Œ€์ธ๊ด€๊ณ„์— ๋Œ€ํ•œ ์š•๊ตฌ๊ฐ€ ๋‚ฎ์•„ ์‚ฌ๋žŒ๋“ค๊ณผ์˜ ์ •์„œ์  ๊ต๋ฅ˜๋ฅผ

Multi-dimensional Personality Assessment

321https://doi.org/10.15842/kjcp.2019.38.3.005

ํ”ผํ•˜๋Š” ์„ฑํ–ฅ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ(Egocentrism)์€ ์ž์‹ ์˜ ์ด์ต๊ณผ ๋งŒ์กฑ์„ ์ค‘

์š”์‹œํ•˜๋ฉฐ ํƒ€์ธ์˜ ์š•๊ตฌ๋‚˜ ๊ฐ์ •์— ๋‘”๊ฐํ•œ ์„ฑํ–ฅ, ์ฃผ์˜๊ณค๋ž€์„ฑ(Atten-

tion Difficulty)์€ ๋งฅ๋ฝ๊ณผ ์ƒํ™ฉ์— ๋งž๊ฒŒ ์ถฉ๋™์„ ์กฐ์ ˆํ•˜๊ธฐ ์–ด๋ ค์›Œํ•˜

๊ณ  ์ค‘์š”ํ•œ ์ž๊ทน์— ์ฃผ์˜๋ฅผ ์ง‘์ค‘ํ•˜๊ธฐ ํž˜๋“ค์–ดํ•˜๋Š” ์„ฑํ–ฅ, ์ •์‹ ์ฆ์„ฑ

(Psychoticism)์€ ์‚ฌ๊ณ ์˜ ์œตํ†ต์„ฑ์ด ๋ถ€์กฑํ•˜๊ณ  ์ž๊ธฐ ์„ธ๊ณ„์— ๋ชฐ์ž…ํ•˜

์—ฌ ํ˜„์‹ค ์„ธ๊ณ„๋ฅผ ๊ฐ๊ด€์ ์œผ๋กœ ์ธ์‹ํ•˜๊ธฐ ์–ด๋ ค์›Œํ•˜๋Š” ์„ฑํ–ฅ, ๋งˆ์ง€๋ง‰์œผ๋กœ

๋ถ€์ •์ •์„œ์„ฑ(Negative Affectivity)์€ ํ‰์†Œ ๋ถ€์ •์  ์ •์„œ๋ฅผ ์ž์ฃผ ๊ฒฝํ—˜

ํ•˜๋ฉฐ ์‚ฌ์†Œํ•œ ์ž๊ทน์—๋„ ์‰ฝ๊ฒŒ ๊ฐ์„ฑ๋˜๊ณ  ์••๋„๋˜๋Š” ์„ฑํ–ฅ์œผ๋กœ ์žฌ๊ตฌ์„ฑํ•˜

์˜€๋‹ค.

๋ฌธํ•ญ์€ ๊ธฐ์กด 126๋ฌธํ•ญ ์ค‘ 55๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜์˜€๊ณ  ๋‚จ์€ 71๋ฌธํ•ญ๊ณผ ์ถ”

๊ฐ€ ๊ฐœ๋ฐœํ•œ 20๋ฌธํ•ญ์„ ํฌํ•จํ•˜์—ฌ 91๋ฌธํ•ญ์„ ์ƒˆ๋กญ๊ฒŒ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์˜ˆ๋น„

์กฐ์‚ฌ๋ฅผ ํ†ตํ•ด ๋ฌธํ•ญ ์„ ์ •์ด ์™„๋ฃŒ๋œ ์š”์ธ(Bright 5: ํ™œ๋ ฅ, ์‚ฌ๊ต, ์ฃผ๋„, ์‹ 

๋ขฐ, ์ดํƒ€, ๋ˆ๊ธฐ, ์„ฑ์ทจ, ์ฒด๊ณ„, ์ฒดํ—˜; Dark 5: ๋ฌด์พŒ, ๊ณ ๋ฆฝ, ์ž๊ธฐ์• , ์—ฐ๊ธฐ, ์กฐ

์ข…, ๋ƒ‰ํ˜น, ์‚ฐ๋งŒ, ์ถฉ๋™, ์ง‘์ฐฉ, ์˜์กด, ๋ถ„๋…ธ, ๋ถˆ์•ˆ, ์—ด๋“ฑ)์€ ๊ทธ๋Œ€๋กœ ์œ ์ง€ํ•˜

์˜€๊ณ , ์ถ”๊ฐ€ ๋ฌธํ•ญ์„ ์ •์ด ํ•„์š”ํ•œ ์š”์ธ(Bright 5: ๊ด€๋Œ€, ์‹ฌ๋ฏธ, ํƒ๊ตฌ, ์ •์„œ

์ˆ˜์šฉ, ์ •์„œํ‘œํ˜„, ์ •์„œ์ธ์‹; Dark 5: ์˜์‹ฌ, ๊ธฐ์ด, ์กฐํ˜„, ๊ฒฝ์ง)์€ ์ถ”๊ฐ€ ๊ฐœ

๋ฐœ๊ณผ์ •์„ ๊ฑฐ์ณค๋‹ค. ์ถ”๊ฐ€๋กœ ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ ์š”์ธ์˜ ํ•˜์œ„์š”์ธ์œผ๋กœ ๋‚ดํ–ฅ

์„ ์ถ”๊ฐ€ํ•˜์—ฌ ์ƒ์œ„์š”์ธ์˜ ํŠน์ง•์„ ๋ช…ํ™•ํžˆ ํ•˜๊ณ ์ž ํ•˜์˜€์œผ๋ฉฐ, ์ฃผ์˜๊ณค๋ž€

์„ฑ์˜ ๊ฐ•๋ฐ•์š”์ธ์€ ํ•˜๋‚˜์˜ ์š”์ธ์œผ๋กœ ๋ช…ํ™•ํ•˜๊ฒŒ ํ™•์ธ๋˜์ง€ ์•Š์•„ ์‚ญ์ œํ•˜

์˜€๋‹ค.

์—ฐ๊ตฌโ€ƒ๋ฐฉ๋ฒ•

์—ฐ๊ตฌ๋Œ€์ƒ

๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๋ฆผ๋Œ€ํ•™๊ต ์ƒ๋ช…์œค๋ฆฌ์œ„์›ํšŒ์—์„œ ์‚ฌ์ „ ์Šน์ธ์„ ๋ฐ›์•„ ์ง„ํ–‰

ํ•˜์˜€๋‹ค. BTI์˜ ์‹ ๋ขฐ๋„์™€ ํƒ€๋‹น๋„๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์˜จ๋ผ์ธ ์กฐ์‚ฌ์—…

์ฒด๋ฅผ ํ†ตํ•˜์—ฌ ์ „๊ตญ์˜ 20โ€“50๋Œ€ ์„ฑ์ธ, ์ด 600๋ช…์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€

๋‹ค. ์ „์ฒด ๋Œ€์ƒ์ž์˜ ํ‰๊ท  ์—ฐ๋ น์€ 39.25์„ธ(SD=11.14, ๋ฒ”์œ„=20โ€“59)์˜€

๋‹ค(Table 1).

์—ฐ๊ตฌ๋„๊ตฌ

ํ•œ๊ตญํ˜• ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ(Big 10 Inventory, BTI) ๋ณธ ๊ฒ€์‚ฌ

Bright 5๋ฅผ ์ธก์ •ํ•˜๋Š” 16๊ฐœ ํ•˜์œ„์š”์ธ(89๋ฌธํ•ญ)๊ณผ Dark 5๋ฅผ ์ธก์ •ํ•˜๋Š”

17๊ฐœ ํ•˜์œ„์š”์ธ(91๋ฌธํ•ญ)์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๋‹ค. ๋ฌธํ•ญ๋ฐ˜์‘์–‘์‹์€ 4์ 

Likert ์ฒ™๋„(1= โ€˜์ „ํ˜€ ์•„๋‹ˆ๋‹คโ€™, 2= โ€˜์•ฝ๊ฐ„ ์•„๋‹ˆ๋‹คโ€™, 3= โ€˜์•ฝ๊ฐ„ ๊ทธ๋ ‡๋‹คโ€™,

4= โ€˜๋งค์šฐ ๊ทธ๋ ‡๋‹คโ€™)์ด๋‹ค. ์ƒ์œ„์š”์ธ์€ ํ•˜์œ„์š”์ธ์˜ ํ‰๊ท  ์ ์ˆ˜๋กœ ์ฑ„์ ๋˜

๋ฉฐ, ์ ์ˆ˜๊ฐ€ ๋†’์„์ˆ˜๋ก ํ•ด๋‹น ์„ฑ๊ฒฉํŠน์„ฑ์ด ๋†’์€ ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค.

๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด BFI (Big Five Inventory, BFI)

John๊ณผ Srivastava (1999)๊ฐ€ ๊ฐœ๋ฐœํ•œ BFI์— ๊ธฐ์ดˆํ•˜์—ฌ Kim, Kim๊ณผ

Ha (2011)๊ฐ€ ๊ฐœ๋ฐœํ•œ ๊ฒƒ์œผ๋กœ, ์ด 15๊ฐœ ๋ฌธํ•ญ์œผ๋กœ 5์š”์ธ ์„ฑ๊ฒฉํŠน์„ฑ์„ ์ธก

์ •ํ•  ์ˆ˜ ์žˆ๋Š” ํ•œ๊ตญ์–ด BFI ๊ฒ€์‚ฌ๋‹ค. ๊ฐ ๋ฌธํ•ญ์€ 5์  Likert ์ฒ™๋„(1= โ€˜์ „

ํ˜€ ์•„๋‹ˆ๋‹คโ€™, 2= โ€˜์•„๋‹ˆ๋‹คโ€™, 3= โ€˜๋ณดํ†ต์ด๋‹คโ€™, 4= โ€˜๊ทธ๋ ‡๋‹คโ€™, 5= โ€˜๋งค์šฐ ๊ทธ๋ ‡

๋‹คโ€™)๋กœ ํ‰์ •๋œ๋‹ค. ํƒ€๋‹นํ™” ๋…ผ๋ฌธ์—์„œ ๊ฐ ์š”์ธ์˜ Cronbachโ€™ ฮฑ๋Š” ์‹ ๊ฒฝ์ฆ

.75, ์™ธํ–ฅ์„ฑ .74, ๊ฐœ๋ฐฉ์„ฑ .82, ์„ฑ์‹ค์„ฑ .75, ์นœํ™”์„ฑ .67๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ

์—ฐ๊ตฌ์—์„œ๋Š” ์‹ ๊ฒฝ์ฆ .84, ์™ธํ–ฅ์„ฑ .69, ๊ฐœ๋ฐฉ์„ฑ .84, ์„ฑ์‹ค์„ฑ .78, ์นœํ™”์„ฑ

.68์˜ ๋‚ด์  ์ผ๊ด€์„ฑ์„ ๋ณด์˜€๋‹ค.

ํ•œ๊ตญํŒ DSM-5 ์„ฑ๊ฒฉ์งˆ๋ฌธ์ง€(Personality Inventory for DSM-5,

PID-5) ๋‹จ์ถ•ํ˜•

DSM-5 Section III์—์„œ ์„ฑ๊ฒฉ์žฅ์• ๋ฅผ ์ง„๋‹จํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ์ค€ ์ค‘ ํ•œ ๊ฐ€์ง€

๋กœ ๋ณ‘๋ฆฌ์  ์„ฑ๊ฒฉ ํŠน์งˆ์„ ์ œ์•ˆํ•˜์˜€๋Š”๋ฐ, ์ด๋ฅผ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒ€์‚ฌ๋„

๊ตฌ๋กœ PID-5 (Krueger et al., 2012)๊ฐ€ ๊ฐœ๋ฐœ๋˜์—ˆ๊ณ  Shin๊ณผ Hwang

(2016)์ด ํ•œ๊ตญํŒ์œผ๋กœ ํƒ€๋‹นํ™”ํ•˜์˜€๋‹ค. ์ด ์„ค๋ฌธ์ง€๋Š” ๋ณ‘๋ฆฌ์  ์„ฑ๊ฒฉ ํŠน์งˆ

5์š”์ธ๊ณผ 25๊ฐœ์˜ ํ•˜์œ„ ์–‘์ƒ์œผ๋กœ ๊ตฌ์„ฑ๋˜๋ฉฐ ๋ฌธํ•ญ์€ ์ด 220๋ฌธํ•ญ์ด๋‹ค.

๊ฐ ๋ฌธํ•ญ์€ 4์  Likert ์ฒ™๋„(0= โ€˜์ „ํ˜€ ์•„๋‹ˆ๋‹คโ€™, 1= โ€˜์•ฝ๊ฐ„ ์•„๋‹ˆ๋‹คโ€™, 2=

Table 1. Demographic Data of Respondents in the Main Study (N=600)

Variable Frequency (%)

Gender Male 300 (50.0) Female 300 (50.0)Age 20โ€“29 150 (25.0) 30โ€“39 150 (25.0) 40โ€“49 150 (25.0) 50โ€“59 150 (25.0)Marital Status Married 317 (52.8) Single 283 (47.2)Education High school 131 (21.8) College 82 (13.7) Undergraduate school 326 (54.3) Graduate school 61 (10.2)Job Office worker 223 (37.2) Technical post 51 (8.5) Service worker 42 (7.0) Self-employed 45 (7.5) Agricultural, forestry and fishery worker 1 (0.2) Housewife 98 (16.3) Student 63 (10.5) Unemployed 42 (7.0) Other 35 (5.8)

Lee et al.

322 https://doi.org/10.15842/kjcp.2019.38.3.005

โ€˜์•ฝ๊ฐ„ ๊ทธ๋ ‡๋‹คโ€™, 3= โ€˜๋งค์šฐ ๊ทธ๋ ‡๋‹คโ€™)๋กœ ํ‰์ •๋œ๋‹ค. ์ดํ›„ PID-5์˜ ๋ฌธํ•ญ๋ฐ˜

์‘์ด๋ก  ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ 100๊ฐœ ๋ฌธํ•ญ์„ ์„ ๋ณ„ํ•˜์—ฌ ๋‹จ์ถ•ํ˜• PID-5

๊ฐ€ ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค(Maple et al., 2015). ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” Shin๊ณผ Hwang

(2016)์ด ํ•œ๊ตญํŒ์œผ๋กœ ํƒ€๋‹นํ™”ํ•œ ๊ฒ€์‚ฌ ๋ฌธํ•ญ ๊ฐ€์šด๋ฐ Maple ๋“ฑ(2015)

์ด ๋‹จ์ถ•ํ˜•์œผ๋กœ ์„ ๋ณ„ํ•œ ๋ฌธํ•ญ 100๊ฐœ๋ฅผ ์ด์šฉํ•˜์—ฌ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋‹จ์ถ•ํ˜•

๊ฐœ๋ฐœ ๋…ผ๋ฌธ์—์„œ 25๊ฐœ ํ•˜์œ„์–‘์ƒ์˜ Cronbachโ€™ ฮฑ๋Š” .74 (์˜์‹ฌ์„ฑ)โ€“.88

(์šฐ์šธ์„ฑ), ํ‰๊ท  .82์˜ ๋‚ด์  ์ผ๊ด€์„ฑ์„ ๋ณด์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ์˜ Cron-

bachโ€™ ฮฑ๋Š” .54 (๋ณต์ข…์„ฑ)โ€“.88 (์นœ๋ฐ€์„ฑ ํšŒํ”ผ)๋กœ, ํ‰๊ท  .73์˜ ๋‚ด์  ์ผ๊ด€

์„ฑ์„ ๋ณด์˜€๋‹ค.

์—ฐ๊ตฌ์ ˆ์ฐจ

๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•˜์—ฌ ์˜ˆ๋น„์กฐ์‚ฌ ๊ฒฐ๊ณผ๊ฐ€ ๋ฐ˜์˜๋œ BTI์˜ ์ตœ์ข… ๋ฌธํ•ญ์„ ์„ 

์ •ํ•˜๊ณ  ์‹ ๋ขฐ๋„์™€ ํƒ€๋‹น๋„๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ด 600๋ช…์„ ๋Œ€์ƒ์œผ๋กœ

์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋Š” 2๋‹จ๊ณ„๋กœ ๋‚˜๋ˆ„์–ด ์‹ค์‹œํ•˜์˜€๊ณ , ์˜จ๋ผ์ธ ์กฐ

์‚ฌ ์ „๋ฌธ์—…์ฒด๋ฅผ ํ†ตํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. 1๋‹จ๊ณ„์—์„œ๋Š” 600๋ช…์„

๋Œ€์ƒ์œผ๋กœ BTI๋ฅผ ์‹ค์‹œํ•˜์—ฌ ๋ฌธํ•ญํŠน์„ฑ, ์‹ ๋ขฐ๋„์™€ ์š”์ธ๊ตฌ์กฐ๋ฅผ ํ™•์ธํ•˜

์˜€๊ณ , 2๋‹จ๊ณ„์—์„œ๋Š” 1๋‹จ๊ณ„ ์ฐธ์—ฌ์ž 200๋ช…์„ ๋ฌด์„ ํ‘œ์ง‘ํ•˜๊ณ  ํƒ€๋‹น๋„ ๊ฒ€

์ฆ์„ ์œ„ํ•˜์—ฌ ๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด BFI์™€ ํ•œ๊ตญํŒ PID-5 ๋‹จ์ถ•ํ˜•์„ ์ถ”๊ฐ€๋กœ

์‹ค์‹œํ•˜์˜€๋‹ค. ์ˆ˜์ง‘๋œ ๋ฐ์ดํ„ฐ๋ฅผ ํ† ๋Œ€๋กœ ์š”์ธ์˜ ๋‚ด์  ์ผ๊ด€์„ฑ๊ณผ ํ™•์ธ์ 

์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๊ณ , ์ˆ˜๋ ด ๋ฐ ๋ณ€๋ณ„ํƒ€๋‹น๋„๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ

Bright 5์™€ ๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด BFI ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„, Dark 5์™€ ํ•œ๊ตญํŒ

PID-5 ๋‹จ์ถ•ํ˜• ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ํ™•์ธ์  ์š”์ธ๋ถ„์„์€

Mplus 7 (Muthรฉn & Muthรฉn, 2012)์„ ์‚ฌ์šฉํ•˜์˜€๊ณ , ๊ทธ ์™ธ์˜ ๋ถ„์„์€

SPSS 23์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค.

์—ฐ๊ตฌโ€ƒ๊ฒฐ๊ณผ

์ตœ์ข…๋ฌธํ•ญ์„ ์ •

์˜ˆ๋น„์กฐ์‚ฌ๋ฅผ ํ†ตํ•˜์—ฌ ์„ ์ •๋œ BTI์˜ 180๋ฌธํ•ญ์˜ ๋ฌธํ•ญ๋ถ„์„๊ณผ ๋‚ด์  ์ผ

๊ด€์„ฑ, ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์—ฌ ์ตœ์ข… ๋ฌธํ•ญ์„ ์„ ์ •ํ•˜์˜€๋‹ค. ์„ ์ •

๊ธฐ์ค€์€ ์˜ˆ๋น„์กฐ์‚ฌ์™€ ๋™์ผํ•˜๊ฒŒ ์ž๋ฃŒ์˜ ์ •๊ทœ์„ฑ, ๋‚ด์  ์ผ๊ด€์„ฑ, ์š”์ธ๋ถ„

์„์— ๊ทผ๊ฑฐํ•œ ์š”์ธ๋ถ€ํ•˜๋Ÿ‰, ๊ต์ฐจ๋ถ€ํ•˜๋ฅผ ๊ณ ๋ คํ•˜์˜€๋‹ค. ์šฐ์„  ๋ชจ๋“  ๋ฌธํ•ญ

์—์„œ ์™œ๋„์™€ ์ฒจ๋„๊ฐ€ ๊ฐ๊ฐ ์ ˆ๋Œ€๊ฐ’ 2์™€ 7์„ ๋„˜์ง€ ์•Š์•„ ์ž๋ฃŒ์˜ ์ •๊ทœ์„ฑ

์ด ํ™•๋ณด๋˜์—ˆ๋‹ค. Bright 5์˜ ๋‚ดํ–ฅ ์š”์ธ์€ ์ด 6๋ฌธํ•ญ์„ ์ถ”๊ฐ€ ๊ฐœ๋ฐœํ•˜์˜€

๊ณ , ๋‚ด์  ์ผ๊ด€์„ฑ์ด .80์œผ๋กœ ์ ์ ˆํ•˜์˜€์œผ๋‚˜, ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ ์š”์ธ์˜ ํƒ์ƒ‰

์  ์š”์ธ๋ถ„์„์—์„œ 1๊ฐœ์˜ ๋ฌธํ•ญ์ด ๊ต์ฐจ๋ถ€ํ•˜๊ฐ€ ํ™•์ธ๋˜์–ด ์‚ญ์ œํ•˜์˜€๋‹ค

(IN_03= โ€˜์‚ฌ๋žŒ์ด ๋งŽ์€ ๊ณณ์— ๊ฐ€๋ฉด ์‰ฝ๊ฒŒ ํ”ผ๊ณคํ•ด์ง„๋‹ค.โ€™). ๊ด€๋Œ€ ์š”์ธ์˜

๊ฒฝ์šฐ, ITC๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์€(r= .36) 1๊ฐœ ๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜์˜€๋‹ค(AB2_10=

โ€˜๋‚ด๊ฐ€ ์†ํ•ด๋ฅผ ๋ณด๋”๋ผ๋„ ๋‹ค๋ฅธ ์‚ฌ๋žŒ๊ณผ ์›๋งŒํ•œ ๊ด€๊ณ„๋ฅผ ์œ ์ง€ํ•œ๋‹ค.โ€™). ์‹ฌ

๋ฏธ์˜ ๊ฒฝ์šฐ, ์ฒ™๋„์˜ ์‹ ๋ขฐ๋„ ๋ถ„์„์—์„œ ๋ฌธํ•ญ ์‚ญ์ œ๋ฅผ ๊ฐ€์ •ํ–ˆ์„ ๊ฒฝ์šฐ

Cronbachโ€™ ฮฑ (cronbach alpha if item deleted)๊ฐ’์ด ๋†’์€ ๋ฌธํ•ญ(.83)

์„ ์‚ญ์ œํ•˜์˜€๋‹ค(OB1_08= โ€˜์‚ฌ๋žŒ๋“ค์€ ๋‚˜๋ฅผ ๋ณด๊ณ  ๊ฐ์ˆ˜์„ฑ์ด ํ’๋ถ€ํ•˜๋‹ค

๊ณ  ๋งํ•œ๋‹ค.โ€™). ํƒ๊ตฌ ์š”์ธ์—์„œ๋Š” ITC๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์€(.44) ๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜

์˜€๋‹ค(OB2_06= โ€˜์ƒˆ๋กœ์šด ๊ฒƒ์„ ๋ณด๋ฉด ์–ด๋–ค ์›๋ฆฌ๋กœ ์ž‘๋™ํ•˜๋Š”์ง€ ์•Œ๊ณ  ์‹ถ

๋‹ค.โ€™). ์ •์„œ์ˆ˜์šฉ์˜ ๊ฒฝ์šฐ, ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„์—์„œ ์š”์ธ๋ถ€ํ•˜๋Ÿ‰์ด ๋‚ฎ์€ 2

๊ฐœ ๋ฌธํ•ญ(NB1_06= โ€˜๋ถ€์ •์ ์ธ ๊ฐ์ •์„ ๋Š๊ปด๋„ ๊ดœ์ฐฎ๋‹ค.โ€™, NB1_08= โ€˜๋ถ€

์ •์ ์ธ ๊ฐ์ •์ด ๋“ค๋”๋ผ๋„ ๋‚ด ์ž์‹ ์„ ํƒ“ํ•˜์ง€ ์•Š๋Š”๋‹ค.โ€™)์„ ์‚ญ์ œํ•˜์˜€๊ณ ,

์ •์„œ์ธ์‹ ๋ฌธํ•ญ๋“ค๊ณผ ํ•œ ์š”์ธ์œผ๋กœ ๋ถ„๋ฅ˜๋œ 2๊ฐœ ๋ฌธํ•ญ(NB1_04,

NB1_05)์€ ๋‚ด์šฉ ์ธก๋ฉด์—์„œ๋„ ์ •์„œ์ธ์‹ ์š”์ธ์œผ๋กœ ์ดํ•ด๋  ์ˆ˜ ์žˆ๋‹ค๊ณ 

ํŒ๋‹จํ•˜์—ฌ ์ •์„œ์ธ์‹ ๋ฌธํ•ญ์œผ๋กœ ์žฌ๋ถ„๋ฅ˜ํ•˜์˜€๋‹ค. ์ •์„œ์ธ์‹ ์š”์ธ์—์„œ๋Š”

ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ, ๋‹ค๋ฅธ ์š”์ธ์— ์š”์ธ๋ถ€ํ•˜๋Ÿ‰์ด ๋ถ„์‚ฐ๋œ 3๊ฐœ ๋ฌธํ•ญ

์„ ์‚ญ์ œํ•˜์˜€๋‹ค(NB4_01= โ€˜๋‚ด ๊ฐ์ •์ด ์–ด๋–ค์ง€ ์ž˜ ์‚ดํ•€๋‹ค.โ€™, NB4_02=

โ€˜๋‚ด๊ฐ€ ๋Š๋ผ๋Š” ๊ฐ์ •์— ์ฃผ์˜๋ฅผ ๊ธฐ์šธ์ธ๋‹ค.โ€™, NB4_03= โ€˜๋‚ด๊ฐ€ ์–ด๋–ค ๊ฐ์ •

์„ ๋Š๋ผ๋Š”์ง€ ๊ด€์‹ฌ์„ ๊ฐ€์ง€๊ณ  ์ง€์ผœ๋ณธ๋‹ค.โ€™).

Dark 5์˜ ์˜์‹ฌ ์š”์ธ์—์„œ๋Š” ITC๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์€ ๋ฌธํ•ญ(.49)์„ ์‚ญ์ œํ•˜

์˜€๋‹ค(ED3_10= โ€˜๊ธฐํšŒ๋งŒ ์žˆ๋‹ค๋ฉด ์‚ฌ๋žŒ๋“ค์€ ๋‚˜๋ฅผ ํ•ด์ฝ”์ง€ํ•  ๊ฒƒ์ด๋‹ค.โ€™).

๊ธฐ์ด ์š”์ธ์˜ ๊ฒฝ์šฐ์—๋„ ITC๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์€ ๋ฌธํ•ญ(.62)์„ ์‚ญ์ œํ•˜์˜€๋‹ค

(OD1_11= โ€˜๋‚ด ์ƒ๊ฐ์ด ํŠน์ดํ•ด์„œ ์‚ฌ๋žŒ๋“ค๊ณผ ๋Œ€ํ™”ํ•˜๊ธฐ ์–ด๋ ต๋‹ค.โ€™). ์กฐํ˜„

์š”์ธ์—์„œ๋Š” ๋‚ด์šฉ์ƒ ํŠน์ • ์ฆ์ƒ์— ๊ฐ€๊น๋‹ค๊ณ  ํŒ๋‹จํ•œ 2๊ฐœ ๋ฌธํ•ญ์„ ์‚ญ์ œ

ํ•˜์˜€๋‹ค(OD2_05= โ€˜๋ˆ„๊ตฐ๊ฐ€๊ฐ€ ๋‚ด ์ƒ๊ฐ์„ ์กฐ์ข…ํ•˜๋Š” ๊ฒƒ ๊ฐ™๋‹ค.โ€™, OD2_

09 = โ€˜๋ชจ๋ฅด๋Š” ์‚ฌ๋žŒ๋“ค์ด ๋‚ด ์ƒ๊ฐ์„ ์ฝ๊ณ  ์žˆ๋‹ค.โ€™). ๊ฒฝ์ง ์š”์ธ์˜ ๊ฒฝ์šฐ

ITC๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์€ 2๊ฐœ ๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜์˜€๋‹ค(OD3_13= โ€˜์ •์น˜๋‚˜ ๊ฒฝ์ œ

์— ๋Œ€ํ•œ ๋‚ด ์ž…์žฅ์„ ๋ฐ”๊ฟ€ ์ƒ๊ฐ์ด ์ „ํ˜€ ์—†๋‹ค.โ€™, OD3_14= โ€˜์–ด๋–ค ์ƒํ™ฉ์—

์„œ๋“  ์ฐฌ์„ฑ์ด๋‚˜ ๋ฐ˜๋Œ€ ์ค‘ ํ•˜๋‚˜๋ฅผ ์„ ํƒํ•ด์•ผ ํ•œ๋‹ค.โ€™).

๊ฒฐ๊ณผ์ ์œผ๋กœ Bright 5์—์„œ๋Š” 89๊ฐœ ๋ฌธํ•ญ ์ค‘ 9๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜์—ฌ 80

๋ฌธํ•ญ์„ ์ตœ์ข… ๋ฌธํ•ญ์œผ๋กœ ์„ ์ •ํ•˜์˜€๊ณ , Dark 5์—์„œ๋Š” 91๊ฐœ ๋ฌธํ•ญ ์ค‘ ์ด

6๋ฌธํ•ญ์„ ์‚ญ์ œํ•˜์—ฌ 85๋ฌธํ•ญ์„ ์ตœ์ข… ๋ฌธํ•ญ์œผ๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ๊ฐ ํ•˜์œ„์š”

์ธ์˜ ๋ฌธํ•ญ์€ 5๊ฐœ ๋ฌธํ•ญ์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ์œผ๋ฉฐ, ์ด 165๋ฌธํ•ญ์ด ์ตœ์ข…๋ฌธํ•ญ

์œผ๋กœ ์„ ์ •๋˜์—ˆ๋‹ค. ๊ฐ ํ•˜์œ„์š”์ธ์˜ ์ •์˜๋Š” Table 2์— ์ œ์‹œํ•˜์˜€์œผ๋ฉฐ, ๊ตญ

๋ฌธ ์ •์˜๋Š” Appendix I์— ์ œ์‹œํ•˜์˜€๋‹ค.

๋‚ด์  ์ผ๊ด€์„ฑ

๋ฌธํ•ญ์ด ํ™•์ •๋œ ์š”์ธ์˜ ์‹ ๋ขฐ๋„๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ Bright 5์™€ 16๊ฐœ

ํ•˜์œ„์š”์ธ, Dark 5์™€ 17๊ฐœ ํ•˜์œ„์š”์ธ์˜ ๋‚ด์  ์ผ๊ด€์„ฑ์„ ์‚ดํŽด๋ณด์•˜๋‹ค.

Bright 5์˜ ํ‰๊ท  Cronbachโ€™ ฮฑ ๊ณ„์ˆ˜๋Š” .85, ๋ฒ”์œ„๋Š” .76 (์ˆ˜์šฉ์„ฑ)โ€“.92

(์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ)์ด์—ˆ์œผ๋ฉฐ, 16๊ฐœ ํ•˜์œ„์š”์ธ์˜ ํ‰๊ท  Cronbachโ€™ ฮฑ ๊ณ„์ˆ˜๋Š”

.77, ๋ฒ”์œ„๋Š” .62 (์ •์„œ์ˆ˜์šฉ)โ€“.88 (์‚ฌ๊ต)๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. Dark 5์˜ ํ‰๊ท 

Cronbachโ€™ ฮฑ ๊ณ„์ˆ˜๋Š” .88, ๋ฒ”์œ„๋Š” .84 (์ •์‹ ์ฆ์„ฑ)โ€“.90 (๋Œ€์ธํšŒํ”ผ์„ฑ)์ด

์—ˆ๊ณ , 17๊ฐœ ํ•˜์œ„์š”์ธ์˜ ํ‰๊ท  Cronbachโ€™ ฮฑ ๊ณ„์ˆ˜๋Š” .81, ๋ฒ”์œ„๋Š” .71 (์˜

์กด)โ€“.88 (๋ถ„๋…ธ)๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค(Table 3).

Multi-dimensional Personality Assessment

323https://doi.org/10.15842/kjcp.2019.38.3.005

๊ฒ€์‚ฌ-์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„

์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์ฒ™๋„ ์ ์ˆ˜์˜ ์•ˆ์ •์„ฑ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์˜จ๋ผ์ธ ์กฐ์‚ฌ

์ „๋ฌธ์—…์ฒด๋ฅผ ํ†ตํ•˜์—ฌ 186๋ช…์˜ ์ผ๋ฐ˜ ์„ฑ์ธ์—๊ฒŒ 4์ฃผ ๊ฐ„๊ฒฉ์„ ๋‘๊ณ  ๊ฒ€์‚ฌ-

์žฌ๊ฒ€์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. Bright 5์˜ ๊ฒ€์‚ฌ-์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„์˜ ๋ฒ”์œ„๋Š” .52

(์ˆ˜์šฉ์„ฑ)โ€“.85 (์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ), Dark 5์˜ ๊ฒ€์‚ฌ-์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„์˜ ๋ฒ”์œ„

๋Š” .64 (์ •์‹ ์ฆ์„ฑ)โ€“.77 (๋ถ€์ •์ •์„œ์„ฑ)๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค(Table 3).

์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ 5์š”์ธ(Bright 5)๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ 5์š”์ธ(Dark 5)

๊ฐ„ ์ƒ๊ด€

Bright 5์™€ Dark 5 ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค(Table 4). ์™ธํ–ฅ-๋‚ด

ํ–ฅ์„ฑ(EB)์€ ๋Œ€์ธํšŒํ”ผ์„ฑ(ED)๊ณผ ๋ถ€์  ์ƒ๊ด€(r= -.45, p< .01)์„ ๋ณด์˜€์œผ

๋ฉฐ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ(AD)๊ณผ ์ •์  ์ƒ๊ด€(r= .18, p< .01)์„ ๋ณด์˜€๋‹ค. ์ˆ˜์šฉ์„ฑ

(AB)์€ ์ž๊ธฐ์ค‘์‹ฌ์„ฑ(AD)๊ณผ ๋ถ€์  ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค(r= -.31, p< .01). ์„ฑ

์‹ค์„ฑ(CB)๋„ ์ฃผ์˜๊ณค๋ž€์„ฑ(CD)๊ณผ ๋ถ€์  ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค(r = -.27,

p< .01). ๊ฐœ๋ฐฉ์„ฑ(OB)์€ ์ •์‹ ์ฆ์„ฑ(OD)๊ณผ ์œ ์˜ํ•œ ์ƒ๊ด€์„ ๋ณด์ด์ง€ ์•Š

Table 2. Definition of the Big 10 Inventoryโ€™ Sub-Factors

Bright PersonalityFactor Subfactor (KR) Definition

Extraversion- Introversion

Vitality (ํ™œ๋ ฅ) The degree to which a person is energetic, lively, and enthusiastic.Gregariousness (์‚ฌ๊ต) The degree to which a person enjoys social interactions.Assertiveness (์ฃผ๋„) The degree to which a person is self-confident and likes to influence others.Introversion (๋‚ดํ–ฅ) The degree to which a person likes an independent and private lifestyle.

Agreeableness Trust (์‹ ๋ขฐ) The degree to which a person values honesty and acts with transparency.Generosity (๊ด€๋Œ€) The degree to which a person is benevolent and tolerant toward others.Altruism (์ดํƒ€) The degree to which a person emphasizes with and care for others.

Conscientiousness Persistency (๋ˆ๊ธฐ) The degree to which a person is perseverant and tenacious.Perfectionism (์„ฑ์ทจ) The degree to which a person aims for and strives to achieve a high goal.Orderly (์ฒด๊ณ„) The degree to which a person is well-organized and systematic.

Openness Aesthetic openness (์‹ฌ๋ฏธ) The degree to which a person is sensitive to beauty and enjoys artistic activities.Intellectual openness (ํƒ๊ตฌ) The degree to which a person is inquisitive and enjoys abstract thinking.Experience openness (์ฒดํ—˜) The degree to which a person enjoys exploring diverse experiences.

Emotional Stability Emotional acceptance (์ •์„œ์ˆ˜์šฉ) The degree to which a person is natural with embracing oneโ€™s emotions.Emotional expression (์ •์„œํ‘œํ˜„) The degree to which a person is at ease with disclosing oneโ€™s emotions.Emotional awareness (์ •์„œ์ธ์‹) The degree to which a person pays attention to and recognizes oneโ€™s emotions.

Dark PersonalityFactor Subfactor (KR) Definition

Detachment Isolation (๊ณ ๋ฆฝ) The degree to which a person does not feel interpersonal needs and avoids relationships.Anhedonia (๋ฌด์พŒ) The degree to which a person has difficulty with experiencing positive emotions.Suspiciousness (์˜์‹ฌ) The degree to which a person is alert and distrustful of others.

Egocentrism Histrionic (์—ฐ๊ธฐ) The degree to which a person wants to dominate the attentions of others.Narcissism (์ž๊ธฐ์• ) The degree to which a person believes one is superior to others and deserves special treatment.Manipulativeness (์กฐ์ข…) The degree to which a person enjoys controlling others to oneโ€™s own advantage.Callousness (๋ƒ‰ํ˜น) The degree to which a person is cold-hearted and lacks sympathy.

Attention Difficulty Distractibility (์‚ฐ๋งŒ) The degree to which a person has difficulty focusing on a certain task.Impulsivity (์ถฉ๋™) The degree to which a person acts rashly out on a whim.Obsessiveness (์ง‘์ฐฉ) The degree to which a person has difficulty taking oneโ€™s mind off a certain thing.

Psychoticism Eccentricity (๊ธฐ์ด) The degree to which a person behaves in odd and unconventional ways.Untunedness (์กฐํ˜„) The degree to which a person holds irrational, distorted beliefs about the world.Rigidity (๊ฒฝ์ง) The degree to which a person is stubborn and has difficulty tolerating ambiguity.

Negative Affectivity Dependency (์˜์กด) The degree to which a person feels helplessness and relies heavily on others.Irritability (๋ถ„๋…ธ) The degree to which a person is annoyed and angered by minor incidents.Anxiousness (๋ถˆ์•ˆ) The degree to which a person experiences chronic tension and apprehension.Inferiority (์—ด๋“ฑ) The degree to which a person holds negative views on oneself.

Lee et al.

324 https://doi.org/10.15842/kjcp.2019.38.3.005

์•˜๊ณ (r= .00, ns.), ์ž๊ธฐ์ค‘์‹ฌ์„ฑ(AD)๊ณผ ์ •์  ์ƒ๊ด€(r= .11, p< .01)์„ ๋ณด

์˜€๋‹ค. ์ •์„œ์•ˆ์ •์„ฑ(NB)์€ ๋ถ€์ •์ •์„œ์„ฑ(ND)๊ณผ ๋ถ€์  ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค

(r= -.42, p< .01).

๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์˜ ๊ตฌ์„ฑ๊ฐœ๋… ํƒ€๋‹น๋„

Bright 5์™€ Dark 5 ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์‚ดํŽด๋ณด๋ฉด, ์ •์  ๋˜๋Š” ๋ถ€์  ์ƒ๊ด€

์„ ๋ณด์ด๊ฑฐ๋‚˜, ์œ ์˜ํ•œ ์ƒ๊ด€์„ ๋ณด์ด์ง€ ์•Š๋Š” ์š”์ธ์ด ๋ฐœ๊ฒฌ๋˜์—ˆ๋‹ค. ์ฆ‰ ๋‘

์„ฑ๊ฒฉ์˜ ์ธก๋ฉด์€ ์„œ๋กœ ๊ตฌ๋ถ„๋˜๋Š” ๋ฒ”์ฃผ์ธ ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ฐ

์„ฑ๊ฒฉ์ธก๋ฉด์„ ๊ตฌ๋ถ„ํ•˜์—ฌ ๊ตฌ์„ฑ๊ฐœ๋… ํƒ€๋‹น๋„๋ฅผ ๊ฒ€์ฆํ•˜์˜€๋‹ค.

๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์˜ ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜๊ธฐ ์ „์— ํ‘œ๋ณธ์˜ ์ ์ ˆ์„ฑ ๊ฒ€

ํ† ๋ฅผ ์œ„ํ•ด Kaiser-Meyer-Olkin Measure of Sampling Adequacy

(KMO)์™€ Bartlett์˜ ๊ตฌํ˜•์„ฑ๊ฒ€์ •์„ ์‹ค์‹œํ•˜์˜€๋‹ค. Bright 5์˜ KMO

์ง€์ˆ˜๋Š” .898, Bartlett ๊ฒ€์ •๊ฒฐ๊ณผ, 20,543.456, p< .001๋กœ ํ™•์ธ๋˜์—ˆ์œผ

๋ฉฐ, Dark 5์˜ KMO ์ง€์ˆ˜๋Š” .942, Bartlett ๊ฒ€์ •๊ฒฐ๊ณผ, 25,843.212,

p< .001๋กœ ์š”์ธ๋ถ„์„์„ ์œ„ํ•œ ํ‘œ๋ณธ์˜ ์ž๋ฃŒ๊ฐ€ ์ ํ•ฉํ•œ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋˜์—ˆ

๋‹ค. ๋ชจ๋“  ํ™•์ธ์  ์š”์ธ๋ถ„์„์€ ๊ฐœ๋ณ„ ๋ฌธํ•ญ์„ ์ธก์ •๋ณ€์ธ์œผ๋กœ ์„ค์ •ํ•˜์—ฌ

๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„๋‹จ์œ„๋Š” ๊ฐœ๋ณ„ ์ƒ์œ„์š”์ธ์— ๋Œ€ํ•œ ํ™•์ธ์  ์š”์ธ๋ถ„์„๊ณผ

Bright 5์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„, Dark 5์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜

์˜€์œผ๋ฉฐ, ํšŒ์ „๋ฐฉ๋ฒ•์€ Geomin (Oblique)์œผ๋กœ ์„ ํƒํ•˜์˜€๋‹ค. ์ถ”์ •๋ฒ•์˜

๊ฒฝ์šฐ, ๋ณธ ๊ฒ€์‚ฌ์˜ ๋ฌธํ•ญ์€ ๋ฆฌ์ปคํŠธ ์ฒ™๋„๋กœ ๋ฌธํ•ญ๋ฐ˜์‘์„ ์ธก์ •ํ•˜๊ธฐ ๋•Œ๋ฌธ

์— ๋ฒ”์ฃผํ˜• ๋ณ€์ˆ˜๋ฅผ ์—ฐ์†ํ˜• ๋ณ€์ˆ˜๋กœ ๊ฐ€์ •ํ•˜์—ฌ ๋ชจ์ˆ˜๋ฅผ ์ถ”์ •ํ•˜๋Š”

weighted least square adjusted mean and variance (WLSMV: ํ‰๊ท 

๋ถ„์‚ฐ์กฐ์ •๊ฐ€์ค‘์ตœ์†Œ์ œ๊ณฑ)๋ฅผ ์ถ”์ •๋ฒ•์œผ๋กœ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ด ์ถ”์ •๋ฒ•์„

์‚ฌ์šฉํ•˜๋Š” ๊ฒฝ์šฐ์—๋Š” ์—ฐ์†ํ˜• ๋ณ€์ˆ˜์—์„œ๋งŒ ์‚ฐ์ถœ๋˜๋Š” ํ‘œ์ค€ํ™” ์ง€์ˆ˜์ธ

SRMR ๊ฐ’์€ ์‚ฐ์ถœ๋˜์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์— ๋น„ํ‘œ์ค€ํ™” ์ง€์ˆ˜์ธ WRMR ๊ฐ’์„

๋ณด๊ณ ํ•˜์˜€๋‹ค.

๊ฐœ๋ณ„ ์ƒ์œ„์š”์ธ์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„์€ ํ•˜๋‚˜์˜ ์ƒ์œ„์š”์ธ์— ์†ํ•ด ์žˆ

Table 3. Reliability of the Big 10 Inventory

Bright personality Dark personalityฮฑ (N = 600) Test-retest (N = 186) ฮฑ (N = 600) Test-retest (N = 186)

Extraversion-Introversion .92 .85 Detachment .90 .68 Vitality .85 .75 Isolation .81 .60 Gregariousness .88 .78 Anhedonia .87 .57 Assertiveness .87 .80 Suspiciousness .83 .72 Introversion .78 .74 Egocentrism .89 .72Agreeableness .76 .52 Histrionic .77 .59 Trust .67 .48 Narcissism .81 .73 Generosity .69 .52 Manipulativeness .82 .64 Altruism .64 .55 Callousness .83 .59Conscientiousness .86 .68 Attention Difficulty .89 .66 Persistency .83 .62 Distractibility .80 .57 Perfectionism .74 .61 Impulsivity .78 .56 Orderly .80 .68 Obsessiveness .77 .55Openness .88 .77 Psychoticism .84 .64 Aesthetic Openness .84 .70 Eccentricity .86 .63 Intellectual Openness .77 .71 Untunedness .80 .65 Experience Openness .84 .79 Rigidity .72 .60Emotional Stability .84 .58 Negative Affectivity .90 .77 Emotional acceptance .62 .53 Dependency .71 .67 Emotional expression .74 .50 Irritability .88 .71 Emotional awareness .80 .51 Anxiousness .79 .73

- - - Inferiority .86 .69

Table 4. Correlation Analysis between Bright 5 and Dark 5

ED AD CD OD ND

EB -.45** .18** -.26** -.12** -.39**AB -.19** -.31** -.24** -.17** -.18**CB -.15** -.12** -.27** -.14** -.13**OB -.08 .11** -.02 .00 -.13**NB -.45** -.12** -.30** -.37** -.42**

Note. Bright 5 = Bright personality of the BTI; Dark 5 = Dark personality of the BTI; EB = Extraversion-Introversion; AB = Agreeableness; CB = Conscientiousness; OB = Openness; NB = Emotional Stability; ED = Detachment; AD = Egocentrism; CD = Attention Difficulty; OD = Psychoticism; ND = Negative Affectivity. **p < .01.

Multi-dimensional Personality Assessment

325https://doi.org/10.15842/kjcp.2019.38.3.005

๋Š” ๋ฌธํ•ญ๋“ค์„ ์ธก์ •๋ณ€์ˆ˜๋กœ, ๊ฐ ๋ฌธํ•ญ์ด ์ธก์ •ํ•˜๋Š” ํ•˜์œ„์š”์ธ์„ ์ž ์žฌ๋ณ€

์ˆ˜๋กœ, ๊ทธ๋ฆฌ๊ณ  ํ•ด๋‹น ์ƒ์œ„์š”์ธ์„ ํ•˜์œ„์š”์ธ๋“ค์˜ ์ƒ์œ„ ์ž ์žฌ๋ณ€์ˆ˜๋กœ ์„ค์ •

ํ•˜์—ฌ ํ™•์ธ์  ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. Bright 5์˜ 5๊ฐœ ์ƒ์œ„์š”์ธ,

Dark 5์˜ 5๊ฐœ ์ƒ์œ„์š”์ธ, ์ด 10 ์š”์ธ์˜ ๊ฐœ๋ณ„์ ์ธ ํ™•์ธ์  ์š”์ธ๋ถ„์„ ๊ฒฐ

๊ณผ, ๋ชจ๋“  ์ƒ์œ„์š”์ธ์˜ CFI, TLI ๊ฐ’์ด .9 ์ด์ƒ์ด์—ˆ๊ณ , RMSEA ๊ฐ’์€ ์™ธ

ํ–ฅ-๋‚ดํ–ฅ์„ฑ ์š”์ธ(RMSEA= .103 [.097โ€“.108])์„ ์ œ์™ธํ•œ ๋ชจ๋“  ์š”์ธ์ด

.1 ์ดํ•˜๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค(Table 5).

๋‹ค์Œ์œผ๋กœ Bright 5๋ฅผ ์ธก์ •ํ•˜๋Š” 80๊ฐœ ๋ฌธํ•ญ์„ ์ธก์ •๋ณ€์ˆ˜๋กœ, 16๊ฐœ ํ•˜

์œ„์š”์ธ์„ ์ž ์žฌ๋ณ€์ˆ˜๋กœ, ๊ทธ๋ฆฌ๊ณ  ๊ทธ ์ƒ์œ„์š”์ธ์ธ 5๊ฐœ ์š”์ธ์„ 16๊ฐœ ํ•˜์œ„

์š”์ธ์˜ ์ƒ์œ„ ์ž ์žฌ๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜์—ฌ ํ™•์ธ์  ์ƒ๊ด€์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€

๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, Bright 5์˜ ๋ชจํ˜• ์ ํ•ฉ๋„๋Š” ฯ‡2(3,054, N= 600)= 6,011.359,

p< .01, RMSEA= .040[.039โ€“.042], CFI= .880, TLI= .876, WRMR=

1.823์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. Dark 5๋„ ๋™์ผํ•œ ๋ฐฉ์‹์œผ๋กœ ํ™•์ธ์  ์š”์ธ๋ถ„์„

์„ ์‹ค์‹œํ•˜์˜€๋‹ค. Dark 5๋ฅผ ์ธก์ •ํ•˜๋Š” 85๊ฐœ ๋ฌธํ•ญ์„ ์ธก์ •๋ณ€์ˆ˜๋กœ, 17๊ฐœ

ํ•˜์œ„์š”์ธ์„ ์ž ์žฌ๋ณ€์ˆ˜๋กœ, ๊ทธ๋ฆฌ๊ณ  ๊ทธ ์ƒ์œ„์š”์ธ์ธ 5๊ฐœ ์š”์ธ์„ 17๊ฐœ ํ•˜

์œ„์š”์ธ์˜ ์ƒ์œ„ ์ž ์žฌ๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, Dark 5์˜

๋ชจํ˜• ์ ํ•ฉ๋„๋Š” ฯ‡2(3,458, N= 600)=8,198.040, p< .001, RMSEA=

.048[.046โ€“.049], CFI= .883, TLI= .879, WRMR=1.955๋กœ ํ™•์ธ๋˜์—ˆ

๋‹ค. Bright 5 ๊ฐœ๋ณ„ ๋ฌธํ•ญ์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ๋Š” Appendix II,

Dark 5๋Š” Appendix III์— ์ œ์‹œํ•˜์˜€๋‹ค.

์ˆ˜๋ ด ๋ฐ ๋ณ€๋ณ„ํƒ€๋‹น๋„

BTI์˜ ์ˆ˜๋ ด ๋ฐ ๋ณ€๋ณ„ํƒ€๋‹น๋„๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ Bright 5๋Š” ๊ฐ„ํŽธํ˜•

ํ•œ๊ตญ์–ด BFI ๊ฒ€์‚ฌ์™€, Dark 5๋Š” ํ•œ๊ตญํŒ PID-5์™€์˜ ๊ด€๋ จ์„ฑ์„ ํ™•์ธํ•˜

์˜€๋‹ค. Bright 5์™€ ๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด BFI ๊ฐ„์˜ ์ƒ๊ด€๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์‚ดํŽด๋ณด

๋ฉด, ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ์€ BFI์˜ ์™ธํ–ฅ์„ฑ๊ณผ ์œ ์˜ํ•œ ์ •์  ์ƒ๊ด€(r= .59, p< .01)

์„ ๋ณด์˜€๊ณ , ์ˆ˜์šฉ์„ฑ์€ BFI์˜ ์นœํ™”์„ฑ๊ณผ ์ •์  ์ƒ๊ด€(r= .56, p< .01)์„

๋ณด์˜€๋‹ค. ์„ฑ์‹ค์„ฑ์€ BFI์˜ ์„ฑ์‹ค์„ฑ๊ณผ, ๊ฐœ๋ฐฉ์„ฑ์€ BFI์˜ ๊ฐœ๋ฐฉ์„ฑ๊ณผ ์ •์ 

์ƒ๊ด€(r= .63, p< .01; r= .40, p< .01)์„ ๋ณด์˜€๋‹ค. ์ •์„œ์•ˆ์ •์„ฑ์€ BFI์˜

์‹ ๊ฒฝ์ฆ๊ณผ ๋ถ€์  ์ƒ๊ด€(r= -.38, p< .01)์„ ๋ณด์˜€์œผ๋ฉฐ, BFI์˜ ์„ฑ์‹ค์„ฑ๊ณผ๋„

์ •์  ์ƒ๊ด€(r= .43, p< .01)์„ ๋ณด์˜€๋‹ค(Table 6).

Dark 5์™€ ํ•œ๊ตญํŒ PID-5 ๋‹จ์ถ•ํ˜•์˜ ์ƒ๊ด€๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์‚ดํŽด๋ณด๋ฉด, ๋Œ€

์ธํšŒํ”ผ์„ฑ์€ PID์˜ ์• ์ฐฉ์ƒ์‹ค๊ณผ ์œ ์˜ํ•œ ์ •์  ์ƒ๊ด€(r= .76, p< .01)์„

๋ณด์˜€์œผ๋ฉฐ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ๋„ PID์˜ ์ ๋Œ€์„ฑ๊ณผ ์ •์  ์ƒ๊ด€(r= .65, p< .01)

์„ ๋ณด์˜€๋‹ค. ์ฃผ์˜๊ณค๋ž€์„ฑ์€ PID-5์˜ ํƒˆ์–ต์ œ์™€ ์ •์  ์ƒ๊ด€(r= .62, p<

.01)์„ ๋ณด์˜€์œผ๋ฉฐ, PID์˜ ๋ถ€์ •์  ์ •์„œ์„ฑ๊ณผ๋„ ์ •์  ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค(r=

.64, p< .01). ์ •์‹ ์ฆ์„ฑ์€ PID-5์˜ ์ •์‹ ๋ณ‘์  ๊ฒฝํ–ฅ์„ฑ๊ณผ ์ •์  ์ƒ๊ด€(r=

.65, p< .01)์„, ๋ถ€์ •์ •์„œ์„ฑ๋„ PID-5์˜ ๋ถ€์ •์  ์ •์„œ์„ฑ๊ณผ ์ •์  ์ƒ๊ด€

(r= .75, p< .01)์„ ๋ณด์˜€๋‹ค(Table 7).

๋…ผโ€ƒ ์˜

๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•œ๊ตญ์ธ์˜ ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ์„ ๋‹ค์ฐจ

์›์ ์œผ๋กœ ์ธก์ •ํ•˜๋Š” 165๊ฐœ ๋ฌธํ•ญ์œผ๋กœ ๊ตฌ์„ฑ๋œ BTI๋ฅผ ๊ฐœ๋ฐœํ•˜๊ณ  ํƒ€๋‹น

ํ™”ํ•˜๊ธฐ ์œ„ํ•ด ๋‹จ๊ณ„์ ์œผ๋กœ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, BTI๊ฐ€ ํ•œ

๊ตญ์ธ์˜ ๋‹ค์ฐจ์›์  ์„ฑ๊ฒฉ์„ ์ธก์ •ํ•˜๋Š” ๋ฐ ์‹ ๋ขฐ๋กญ๊ณ  ํƒ€๋‹นํ•œ ๊ฒ€์‚ฌ๋กœ ๋ฐ

ํ˜€์กŒ๋‹ค.

๊ตฌ์ฒด์ ์œผ๋กœ ์‚ดํŽด๋ณด๋ฉด, BTI์˜ Bright 5์™€ Dark 5์˜ ๊ฐ 5๊ฐœ ์š”์ธ์—

Table 5. Model Fit for Confirmatory Factor Analysis of the BTI

ฯ‡2 df CFI TLI WRMR RMSEA (90% C.I.)

EB 1,214.963* 166 .942 .934 2.076 .103 (.097โ€“.108)AB 288.096* 87 .921 .904 1.257 .062 (.054โ€“.070)CB 274.321* 87 .973 .968 1.130 .060 (.052.โ€“068)OB 569.989* 87 .931 .917 1.658 .096 (.089โ€“.104)NB 371.497* 87 .944 .932 1.328 .074 (.066โ€“.082)Bright 5 Factor 6,011.359* 3,054 .880 .876 1.823 .040 (.039โ€“.042)

ED 247.333* 87 .983 .979 0.987 .055 (.047โ€“.064)AD 66.726* 166 .936 .927 1.881 .090 (.084โ€“.095)CD 357.451* 87 .963 .956 1.209 .072 (.064โ€“.080)OD 293.825* 87 .972 .967 1.242 .063 (.055โ€“.071)ND 649.937* 166 .961 .955 1.447 .070 (.064โ€“.075)Dark 5 Factor 8,198.040* 3,458 .883 .879 1.955 .048 (.046โ€“.049)

Note. BTI = Big 10 Inventory; Bright = Bright personality of the Big 10 Inventory; Dark = Dark personality of the Big 10 Inventory; EB = Extraversion-Introversion; AB = Agreeableness; CB = Conscientiousness; OB = Openness; NB = Emotional Stability; ED = Detachment; AD = Egocentrism; CD = Attention Difficulty; OD = Psychoticism; ND = Negative Affectivity; RMSEA = root mean square error of approximation; CFI = comparative fit index; TLI = Tucker-Lewis index; WRMR = Weighted root mean square residual.

Lee et al.

326 https://doi.org/10.15842/kjcp.2019.38.3.005

๋Œ€ํ•œ ๋‚ด์  ํ•ฉ์น˜๋„์™€ ๊ฐ ํ•˜์œ„์š”์ธ์˜ ๋‚ด์  ํ•ฉ์น˜๋„์˜ ํ‰๊ท  ๋ชจ๋‘ ์–‘ํ˜ธ

ํ•œ ์ˆ˜์ค€์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. Bright 5์˜ ๋‚ด์  ํ•ฉ์น˜๋„๋Š” ๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด

BFI ์ƒ์œ„ 5์š”์ธ์˜ ๋‚ด์  ํ•ฉ์น˜๋„ ๋ฒ”์œ„(Kim et al., 2011) ๋ฐ ํ•œ๊ตญํŒ

NEO-PI-R์˜ ๋‚ด์  ํ•ฉ์น˜๋„ ๋ฒ”์œ„(Ahn & Chae, 1997)์™€ ์œ ์‚ฌํ•œ ์ˆ˜์ค€

์ด์—ˆ๋‹ค. ๋˜ํ•œ Dark 5์˜ 5๊ฐœ ์š”์ธ์˜ ๋‚ด์  ํ•ฉ์น˜๋„๋Š” ํ•œ๊ตญํŒ PID-5์˜

5๊ฐœ ์˜์—ญ์˜ ๋‚ด์  ํ•ฉ์น˜๋„(Hong et al., 2018)๋ณด๋‹ค ๋” ๋†’์€ ์ˆ˜์ค€์ด์—ˆ

๋‹ค. 4์ฃผ ๊ฐ„๊ฒฉ์œผ๋กœ ๊ฒ€์‚ฌ-์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„๋ฅผ ํ™•์ธํ•œ ๊ฒฐ๊ณผ, Hong ๋“ฑ

(2018)์ด ๋Œ€ํ•™์ƒ์„ ๋Œ€์ƒ์œผ๋กœ ์‹ค์‹œํ•œ PID-5์˜ 3์ฃผ ๊ฐ„๊ฒฉ์˜ ์žฌ๊ฒ€์‚ฌ ์‹ 

๋ขฐ๋„์™€ 31๋ช…์˜ ์ผ๋ฐ˜์ธ์„ ๋Œ€์ƒ์œผ๋กœ ์‹ค์‹œํ•œ NEO-PI์˜ 6๊ฐœ์›” ๊ฐ„๊ฒฉ์˜

์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„(McCrea & Costa, 1983)์— ๋น„ํ•ด ๋‹ค์†Œ ๋‚ฎ์€ ์ˆ˜์ค€์ด์—ˆ

๋‹ค. ์ด๋Š” ์ƒ์ดํ•œ ์žฌ๊ฒ€์‚ฌ ๊ฐ„๊ฒฉ๊ณผ ์—ฐ๊ตฌ๋Œ€์ƒ์˜ ์˜ํ–ฅ์ผ ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ ์ˆ˜

์šฉ์„ฑ๊ณผ ์ •์„œ์•ˆ์ •์„ฑ์˜ ์‹œ๊ฐ„์  ์•ˆ์ •์„ฑ์„ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•œ ์ถ”ํ›„ ์—ฐ๊ตฌ๊ฐ€

ํ•„์š”ํ•˜๋‹ค.

๋‹ค์Œ์œผ๋กœ BTI์˜ ๊ตฌ์„ฑ๊ฐœ๋… ํƒ€๋‹น๋„๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ํ™•์ธ์  ์š”

์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. Bright 5์™€ Dark 5๋ฅผ ๊ตฌ๋ถ„ํ•˜๊ณ  ๊ฐ ์„ฑ๊ฒฉ ์ธก๋ฉด

์„ ์ธก์ •ํ•˜๋Š” ๋ฌธํ•ญ์„ ์ธก์ •๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜์—ฌ ํ•˜์œ„์š”์ธ๊ณผ ์ƒ์œ„์š”์ธ์œผ

๋กœ ๊ตฌ์„ฑํ•œ 2์ˆ˜์ค€ ์œ„๊ณ„์  ๊ตฌ์กฐ๋ชจํ˜•์„ ๊ฒ€์ฆํ•œ ๊ฒฐ๊ณผ, ์ ํ•ฉ๋„ ๊ธฐ์ค€์—๋Š”

๋‹ค์†Œ ๋ฏธ์น˜์ง€ ๋ชปํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฌํ•œ ํ˜„์ƒ์€ PID-5 ์—ฐ๊ตฌ์—

์„œ๋„ ๋‚˜ํƒ€๋‚ฌ๋Š”๋ฐ(Gore, 2013; Hong et al., 2018), ์ด์ „ ์—ฐ๊ตฌ์ž๋“ค์€

PID-5๊ฐ€ ๋‹ค์ˆ˜์˜ ํ•˜์œ„์š”์ธ์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๋‹ค๋Š” ์ ์„ ๊ทธ ์ด์œ ๋กœ ๋“ค

์—ˆ๋‹ค(DeYoung, Carey, Krueger, & Ross, 2016; Gore, 2013). BTI์˜

ํ™•์ธ์  ์š”์ธ๋ถ„์„์—์„œ๋„ Bright 5์˜ ๊ฒฝ์šฐ 80๊ฐœ ๋ฌธํ•ญ, Dark 5์˜ ๊ฒฝ์šฐ

85๊ฐœ์˜ ๋ฌธํ•ญ์ด ์ธก์ •๋ณ€์ˆ˜๋กœ ์‚ฌ์šฉ๋˜์—ˆ๊ณ , 2์ˆ˜์ค€์˜ ์ž ์žฌ๋ณ€์ˆ˜๋ฅผ ๊ฐ€์ง€

๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ชจํ˜•์ด ๋ณต์žกํ•˜๊ณ  ์ธก์ •๋ณ€์ธ์˜ ์ˆ˜๊ฐ€ ๋งŽ์•„ ๋ชจํ˜• ์ ํ•ฉ

๋„๊ฐ€ ๋‚ฎ์•„์งˆ ์ˆ˜ ์žˆ๋‹ค. ๋ชจํ˜• ์ ํ•ฉ๋„ ํ‰๊ฐ€์— ๋Œ€ํ•œ ๋ฐ”๋žŒ์งํ•œ ์ ‘๊ทผ์€ ์ 

ํ•ฉ๋„ ์ง€์ˆ˜๋ฅผ ๊ผญ ๋ณด๊ณ ํ•ด์•ผ ํ•˜์ง€๋งŒ ๋งˆ๋ฒ• ๊ฐ™์€ ์ ํ•ฉ๋„ ์ง€์ˆ˜๊ฐ€ ์—†๊ธฐ ๋•Œ

๋ฌธ์— ์ ํ•ฉ๋„ ์ง€์ˆ˜์˜ ๊ธฐ์ค€์— ๋งŽ์€ ๋น„์ค‘์„ ๋‘๊ธฐ๋ณด๋‹ค๋Š” ์ด๋ก ์ ยท๊ฒฝํ—˜

์  ๋ฐ”ํƒ•์œผ๋กœ ๋ชจํ˜•์„ ์„ ํƒํ•˜๋Š” ๊ฒƒ์ด ์ข‹๋‹ค๋Š” ์„ ํ–‰์—ฐ๊ตฌ๋ฅผ ํ™•์ธํ•  ์ˆ˜

์žˆ์—ˆ๋‹ค(Kline, 2016).

BTI๋Š” ๋ฌธํ•ญ์˜ ์š”์ธ ๋ถ€ํ•˜๋Ÿ‰์ด 1๊ฐœ์˜ ๋ฌธํ•ญ(p< .05)์„ ์ œ์™ธํ•œ ๋ชจ๋“ 

๋ฌธํ•ญ์ด p< .001 ์ˆ˜์ค€์—์„œ ์œ ์˜ํ•˜์˜€์œผ๋ฉฐ, 33๊ฐœ์˜ ํ•˜์œ„์š”์ธ์˜ ์š”์ธ

๋ถ€ํ•˜๋Ÿ‰ ๋˜ํ•œ p< .001 ์ˆ˜์ค€์—์„œ ์œ ์˜ํ•˜์˜€๋‹ค. ๊ทธ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ BTI์˜

Table 6. Correlation Analysis between Bright 5 and K-BFI-15

BFI_E BFI_A BFI_C BFI_O BFI_N

Vitality .47** .32** .25** .34** -.49**Gregariousness .60** .30** .33** .34** -.31**Assertiveness .47** .17* .21** .29** -.29**Introversion(R) .31** .09 .19** .10 -.42**Trust -.21** .22** .23** .25** -.13Generosity .05 .58** .16* .10 -.02Altruism .14* .38** .23** .11 -.07Persistency .04 .12 .56** .26** -.23**Perfectionism .15* .22** .54** .28** -.09Orderly -.03 .23** .33** .10 -.04Aesthetic openness .05 .14* .02 .19** -.02Intellectual openness .13 .16* .18* .40** -.01Experience openness .16* .16* .18** .37** -.13Emotional acceptance .06 .22** .29** .04 -.29**Emotional expression .30** .27** .38** .15* -.36**Emotional awareness .19** .23** .34** .21** -.18**

Extraversion-Introversion .59** .29** .32** .34** -.48**Agreeableness -.01 .56** .29** .22** -.10Conscientiousness .06 .24** .63** .28** -.17*Openness .15* .19** .16* .40** -.07Emotional stability .24** .30** .43** .17* -.35**

Note. Bright 5 = Bright personality of the Big 10 Inventory; K-BFI-15 = the Korean short version of the Big-Five Inventory; BFI_E= Extraversion; BFI_A = Agreeableness; BFI_C = Conscientiousness; BFI_O = Openness; BFI_N = Neuroticism.*p < .05, **p < .01.

Table 7. Correlation Analysis between Dark 5 and K-RV-PID-5

PID_E PID_A PID_C PID_O PID_N

Isolation .67** .08 .30** .36** .38**Anhedonia .66** .02 .38** .36** .58**Suspiciousness .55** .11 .36** .31** .46**Histrionic -.02 .47** .34** .20** .21**Narcissism -.07 .49** .06 .24** -.06Manipulativeness .11 .44** .33** .10 .23**Callousness .21** .46** .28** .30** .22**Distractibility .42** .12 .52** .32** .57**Impulsivity .32** .27** .57** .36** .51**Obsessiveness .41** .05 .46** .30** .52**Eccentricity .41** .18* .36** .50** .40**Untunedness .37** .31** .54** .68** .53**Rigidity .42** .06 .30** .22** .43**Dependency .21** .03 .39** .10 .41**Irritability .46** .25** .45** .40** .54**Anxiousness .52** .01 .45** .31** .67**Inferiority .66** -.01 .42** .36** .65**

Detachment .76** .09 .42** .42** .58**Egocentrism .08 .65** .35** .29** .21**Attention Difficulty .46** .18* .62** .39** .64**Psychoticism .54** .25** .55** .65** .61**Negative Affectivity .63** .09 .56** .40** .75**

Note. Dark 5 = Dark personality of the Big 10 Inventory; K-RV-PID-5 = Korean reduced version of the PID-5; PID_E = Detachment; PID_A = Antagonism; PID_C = Disinhibition; PID_O = Psychoticism; PID_N = Negative Affect.*p < .05, **p < .01.

Multi-dimensional Personality Assessment

327https://doi.org/10.15842/kjcp.2019.38.3.005

์ƒ์œ„ 10๊ฐœ ์š”์ธ์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ, ๋ชจํ˜• ์ ํ•ฉ๋„๊ฐ€ ์–‘ํ˜ธํ•œ ์ˆ˜

์ค€์„ ๋ณด์ด๋Š” ์ ๋“ค์„ ๊ณ ๋ คํ•˜์˜€์„ ๋•Œ(Hong, 2000), ์ฒ™๋„์˜ ๊ตฌ์„ฑํƒ€๋‹น

๋„๊ฐ€ ๊ฒ€์ฆ๋˜์—ˆ๋‹ค๊ณ  ํŒ๋‹จ๋œ๋‹ค. ์ฆ‰, ๊ฐ ์„ฑ๊ฒฉํŠน์„ฑ์„ ์ธก์ •ํ•˜๋Š” 80๋ฌธํ•ญ

๊ณผ 85๋ฌธํ•ญ์ด ๊ฐ ์ƒ์œ„์š”์ธ๊ณผ ํ•˜์œ„์š”์ธ์˜ ํŠน์„ฑ์„ ์ž˜ ์ธก์ •ํ•˜๋Š” ๊ฒƒ์œผ

๋กœ ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋‹ค.

Bright 5์™€ Dark 5์˜ ์š”์ธ ๊ฐ„ ๊ด€๊ณ„์„ฑ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ƒ๊ด€๋ถ„

์„์„ ์‹ค์‹œํ•œ ๊ฒฐ๊ณผ, Bright 5์˜ ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ, ์ˆ˜์šฉ์„ฑ, ์„ฑ์‹ค์„ฑ, ์ •์„œ์•ˆ

์ •์„ฑ์€ Dark 5์˜ ๋Œ€์ธํšŒํ”ผ์„ฑ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ, ์ฃผ์˜๊ณค๋ž€์„ฑ, ๋ถ€์ •์ •์„œ์„ฑ

๊ณผ ๋ถ€์  ์ƒ๊ด€์„ ๋ณด์˜€์ง€๋งŒ ๊ทธ ์ •๋„๋Š” ๋‚ฎ์•˜๋‹ค. ์ด ๊ฒฐ๊ณผ๋Š” ๊ฐ ๋Œ€์‘๋˜๋Š”

์š”์ธ์ด ํ•˜๋‚˜์˜ ์ฐจ์›์ด๊ธฐ๋ณด๋‹ค ๊ตฌ๋ถ„๋˜๋Š” ์„ฑ๊ฒฉํŠน์„ฑ์ด๋ผ๋Š” ๊ฒƒ์„ ์‹œ์‚ฌ

ํ•œ๋‹ค. ์ด ์ ์€ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ 5์š”์ธ ๋ชจ๋ธ(Five-Factor Model)๊ณผ ๋ณ‘๋ฆฌ์ 

์„ฑ๊ฒฉ ๊ฐ„์— ๋‚ฎ์€ ์ค‘๊ฐ„ ์ˆ˜์ค€์˜ ์ƒ๊ด€์ด ์žˆ์—ˆ์Œ์„ ๋ฐํ˜€๋‚ธ Clark (1993)

์˜ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์™€ ์œ ์‚ฌํ•˜๋‹ค. ๋‹ค๋ฅธ ์„ ํ–‰์—ฐ๊ตฌ(Butcher & Rouse, 1996;

Morey, Gunderson, Quigley, & Lyons, 2000)์—์„œ ์ง€์ ๋œ ๋ฐ”์™€ ๊ฐ™์ด

์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ์„ ์ธก์ •ํ•˜๋Š” ๊ฒ€์‚ฌ๋กœ๋Š” ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ์„ ์ธก์ •ํ•˜๊ณ 

์ดํ•ดํ•˜๋Š” ๋ฐ ํ•œ๊ณ„๊ฐ€ ์žˆ๊ณ  ๊ทธ ๋ฐ˜๋Œ€์˜ ๊ฒฝ์šฐ๋„ ํ•œ๊ณ„๊ฐ€ ์กด์žฌํ•˜๊ธฐ ๋•Œ๋ฌธ

์— ๋‘ ์ธก๋ฉด์„ ๋ชจ๋‘ ํ‰๊ฐ€ํ•ด์•ผ ํ•œ๋‹ค. ํ•œํŽธ, ๊ฐœ๋ฐฉ์„ฑ์€ ๋Œ€์‘ํ•˜๋Š” ๊ฐœ๋…์ธ

์ •์‹ ์ฆ์„ฑ๊ณผ ์œ ์˜ํ•œ ์ƒ๊ด€์„ ๋ณด์ด์ง€ ์•Š์•˜๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ๊ฒฝํ–ฅ์„ฑ์€ Kim

(2016), Hong ๋“ฑ(2018), Maples ๋“ฑ(2015)์ด ์‹ค์‹œํ•œ PID-5 ๊ด€๋ จ ์—ฐ๊ตฌ

์—์„œ๋„ ๋ณด๊ณ ๋˜์—ˆ๋‹ค. PID-5์˜ ์ •์‹ ๋ณ‘์  ๊ฒฝํ–ฅ์„ฑ์€ NEO-FFI์˜ ๊ฐœ๋ฐฉ

์„ฑ๊ณผ์˜ ์ƒ๊ด€์ด ์œ ์˜ํ•˜์ง€ ์•Š์•˜๊ณ , ์„ฑ๊ฒฉ์žฅ์• ์™€ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ 5์š”์ธ์˜ ๊ด€

๊ณ„๋ฅผ ๊ฒ€์ฆํ•œ ๋ฉ”ํƒ€๋ถ„์„ ์—ฐ๊ตฌ์—์„œ๋„ ์กฐํ˜„ํ˜• ์„ฑ๊ฒฉ์žฅ์• ์™€ ๊ฐœ๋ฐฉ์„ฑ ๊ฐ„์˜

๊ด€๋ จ์„ฑ์ด ๋‚ฎ์•˜๋‹ค(Samuel & Widiger, 2008; Saulsman & Page,

2004). ๊ฐœ๋ฐฉ์„ฑ์˜ ๊ฒฝ์šฐ, ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ์œผ๋กœ์„œ ๊ฐœ์ธ์˜ ์™ธ์  ๋˜๋Š” ๋‚ด์ 

ํ˜ธ๊ธฐ์‹ฌ์ด ๋†’์€ ํŠน์„ฑ์— ์ดˆ์ ์ด ๋งž์ถ”์–ด์ ธ ์žˆ๊ณ , ์ •์‹ ์ฆ์„ฑ์€ ์™œ๊ณก๋œ

์‚ฌ๊ณ ์™€ ํ–‰๋™ํŒจํ„ด์ด ๊ฒฝ์ง๋˜์–ด ์žˆ๋Š” ํŠน์„ฑ์ด๋ผ๋Š” ์ ์—์„œ ์ด ๋‘ ์š”์ธ์ด

๊ตฌ๋ถ„๋œ๋‹ค. ์ด๋กœ ์ธํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ƒ๊ด€์ด ์œ ์˜ํ•˜์ง€ ์•Š์•˜์„ ๊ฐ€๋Šฅ

์„ฑ์ด ์žˆ๋‹ค.

์ถ”๊ฐ€๋กœ Bright 5์™€ Dark 5์˜ ์š”์ธ ๊ฐ„์— ์ •์  ์ƒ๊ด€์„ ๋ณด์ด๋Š” ์š”์ธ

๋“ค์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ž๊ธฐ์ค‘์‹ฌ์„ฑ์€ ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ, ๊ฐœ๋ฐฉ์„ฑ๊ณผ ์ž‘์€ ์ˆ˜์ค€

์˜ ์ •์  ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ ์š”์ธ์€ ๊ด€๊ณ„์˜ ํ™•์žฅ์ด ํ•ต์‹ฌ ํŠน

์„ฑ์ด๋ผ๊ณ  ๋ณผ ์ˆ˜ ์žˆ๊ณ , ์ž๊ธฐ์ค‘์‹ฌ์„ฑ์€ ๊ด€๊ณ„ ๋งฅ๋ฝ์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ์„ฑ๊ฒฉ

ํŠน์„ฑ์ด๊ธฐ ๋•Œ๋ฌธ์— ์ด ๋‘ ์š”์ธ ๊ฐ„์— ๊ด€๋ จ์„ฑ์ด ๋‚˜ํƒ€๋‚œ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค.

๊ฐœ๋ฐฉ์„ฑ์˜ ๊ฒฝ์šฐ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ์˜ ํ•˜์œ„ ์š”์ธ์ธ ์ž๊ธฐ์•  ์š”์ธ๊ณผ ๋‚ฎ์€ ์ •์ 

์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ์ž๊ธฐ์• ์„ฑ ์„ฑ๊ฒฉ์žฅ์• ๊ฐ€ ์ง€๊ฐ๋œ ์œ ๋Šฅ๊ฐ ๋˜๋Š” ์ 

์‘๋Šฅ๋ ฅ๊ณผ ๊ด€๋ จ์ด ์žˆ๋‹ค๋Š” ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์™€ ์œ ์‚ฌํ•œ ๊ฒฐ๊ณผ๋กœ ๋ณด์ธ๋‹ค

(Hwang, Yoon, & Lee, 2008). ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋“ค์€ ๋‘ ๊ฐ€์ง€ ๊ฐœ๋…์„ ํ•˜

๋‚˜์˜ ์ฐจ์›์œผ๋กœ ํ‰๊ฐ€ํ•˜๊ฑฐ๋‚˜ ํ•ด์„ํ•˜๋Š” ๊ฒƒ์ด ๋ฌด๋ฆฌ๊ฐ€ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ

์ค€๋‹ค. ์ถ”ํ›„ ์—ฐ๊ตฌ์—์„œ ์ด Bright 5์™€ Dark 5์š”์ธ๋“ค ๊ฐ„์˜ ๊ด€๋ จ์„ฑ์„ ์‹ค

ํ—˜์—ฐ๊ตฌ ๋“ฑ์„ ํ†ตํ•ด ๋ณด๋‹ค ์ง์ ‘์ ์œผ๋กœ ๊ฒ€์ฆํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค.

๋‹ค์Œ์œผ๋กœ BTI์˜ ์ˆ˜๋ ด ๋ฐ ๋ณ€๋ณ„ํƒ€๋‹น๋„๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ Bright

5์™€ ๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด BFI, Dark 5์™€ ํ•œ๊ตญํŒ PID-5 ๋‹จ์ถ•ํ˜•๊ณผ์˜ ์ƒ๊ด€

๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. Bright 5์˜ ์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ, ์ˆ˜์šฉ์„ฑ, ์„ฑ์‹ค์„ฑ, ๊ฐœ๋ฐฉ

์„ฑ์€ BFI์˜ ๋Œ€์‘ํ•˜๋Š” ์š”์ธ์ธ ์™ธํ–ฅ์„ฑ, ์ˆ˜์šฉ์„ฑ, ์„ฑ์‹ค์„ฑ, ๊ฐœ๋ฐฉ์„ฑ๊ณผ ์ •

์  ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. Bright 5์˜ ์ •์„œ์•ˆ์ •์„ฑ์€ BFI์˜ ์‹ ๊ฒฝ์ฆ๊ณผ ๋ถ€์ 

์ƒ๊ด€์„ ๋ณด์˜€๋Š”๋ฐ, ์ด๋Š” ์ •์„œ์•ˆ์ •์„ฑ์˜ ๊ฒฝ์šฐ, ๊ฐœ์ธ์˜ ๊ฑด๊ฐ•ํ•œ ์ •์„œ๋„์‹

์„ ์ธก์ •ํ•˜๋Š” ๋ฐ˜๋ฉด, BFI์˜ ์‹ ๊ฒฝ์ฆ์€ ๊ฐœ์ธ์˜ ๋ถ€์ • ์ •์„œ๋ฅผ ์ธก์ •ํ•œ๋‹ค

๋Š” ์ ์—์„œ ์˜ˆ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒฐ๊ณผ๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. Dark 5์˜ ๊ฒฝ์šฐ, ๋Œ€์ธ

ํšŒํ”ผ์„ฑ, ์ž๊ธฐ์ค‘์‹ฌ์„ฑ, ์ฃผ์˜๊ณค๋ž€์„ฑ, ์ •์‹ ์ฆ์„ฑ, ๋ถ€์ •์ •์„œ์„ฑ์€ PID-5์˜

์• ์ฐฉ์ƒ์‹ค, ์ ๋Œ€์„ฑ, ํƒˆ์–ต์ œ, ์ •์‹ ๋ณ‘์  ๊ฒฝํ–ฅ์„ฑ, ๋ถ€์ •์  ์ •์„œ์„ฑ๊ณผ ์ •์ 

์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. ์ฆ‰, Bright 5, Dark 5์™€ ์ค€๊ฑฐ๋„๊ตฌ์™€์˜ ์ƒ๊ด€ ํŒจํ„ด์€ ์ˆ˜

๋ ด ๋ฐ ๋ณ€๋ณ„ํƒ€๋‹น๋„๋ฅผ ์ง€์ง€ํ•˜์˜€๋‹ค.

์ถ”๊ฐ€๋กœ ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์—์„œ Bright 5์™€ Dark 5์˜ ๋‘ ์ธก๋ฉด์—์„œ Big 5

์˜ ์„ฑ์‹ค์„ฑ(C ์š”์ธ)๊ณผ ์‹ ๊ฒฝ์ฆ(N ์š”์ธ)์— ํ•ด๋‹นํ•˜๋Š” ์š”์ธ ๊ฐ„์— ๋†’์€

์ƒ๊ด€์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค๋ฉด, ์ฃผ์˜๊ณค๋ž€์„ฑ ์š”์ธ(Dark C)์˜

๊ฒฝ์šฐ, PID-5์˜ ๋ถ€์ •์  ์ •์„œ์„ฑ(N)๊ณผ ๋†’์€ ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ํ•œ๊ตญ

ํŒ PID-5 ํƒ€๋‹นํ™” ์—ฐ๊ตฌ๊ฒฐ๊ณผ์™€ ์œ ์‚ฌํ•œ ์–‘์ƒ์œผ๋กœ(Shin & Hwang,

2016), PID-5์˜ ํƒˆ์–ต์ œ ์˜์—ญ(C)์˜ ํ•˜์œ„ ์–‘์ƒ์ด PSY-5์˜ NEGE์™€

๋†’์€ ์ƒ๊ด€์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ฃผ์˜ ๊ณค๋ž€๊ณผ ์ถฉ๋™์ ์ธ ํŠน์„ฑ์„ ์ง€๋‹Œ ์‚ฌ๋žŒ์ด

๋ถ€์ •์ ์ธ ์ •์„œ๊ฐ€ ๋†’์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ด ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” ์ฃผ์˜๋ ฅ ๊ฒฐํ•์„ ํŠน

์ง•์œผ๋กœ ํ•˜๋Š” ADHD์˜ ๊ฒฝ์šฐ, ์šฐ์šธ, ๋ถˆ์•ˆ์„ ํ˜ธ์†Œํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ์œผ๋ฉฐ

๋ถ€์ •์  ์ •์„œ์„ฑ์ด ๋†’๋‹ค๋Š” ์ด์ „ ์—ฐ๊ตฌ๊ฒฐ๊ณผ(Wender, 1995; Shin &

Hwang, 2016)์™€ ๋”๋ถˆ์–ด ์ด๋Ÿฌํ•œ ์„ฑํ–ฅ์„ ์ง€๋‹Œ ์‚ฌ๋žŒ๋“ค์ด ์™ธํ˜„์ ์ธ ํ–‰

๋™๋ฌธ์ œ๋ณด๋‹ค๋Š” ๋‚ดํ˜„ํ™”๋œ ๋ฌธ์ œ๋ฅผ ๋ณด๊ณ ํ•œ๋‹ค๋Š” ์—ฐ๊ตฌ๊ฒฐ๊ณผ(Anderson

et al., 2015)์™€๋„ ์œ ์‚ฌํ•˜๋‹ค. ์ฃผ์˜๊ณค๋ž€์„ฑ๊ณผ ๋ถ€์ •์ •์„œ์„ฑ์˜ ๋ช…ํ™•ํ•œ ๊ด€

๋ จ์„ฑ์„ ๋ฐํžˆ๊ธฐ ์œ„ํ•ด์„œ ์ถ”ํ›„ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค.

๋ณธ ์—ฐ๊ตฌ๋Š” ์•„๋ž˜์™€ ๊ฐ™์€ ์ œํ•œ์ ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค. ์ฒซ์งธ, ๋ณธ ์—ฐ๊ตฌ์—์„œ

๋Š” ์ผ๋ฐ˜ ์„ฑ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์˜ ์‹ ๋ขฐ๋„์™€ ํƒ€๋‹น๋„๋ฅผ ๊ฒ€

์ฆํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์— ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์ž„์ƒ์ง‘๋‹จ์œผ๋กœ ์ผ๋ฐ˜ํ™”ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”

์ถ”๊ฐ€ ์ž„์ƒ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ถ”ํ›„ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•˜์—ฌ ์„ฑ๊ฒฉ์žฅ์• ์ง‘๋‹จ์„

๋Œ€์ƒ์œผ๋กœ ๊ฒ€์‚ฌ์˜ ์‹ ๋ขฐ๋„์™€ ํƒ€๋‹น๋„, ์œ ์šฉ์„ฑ์„ ๊ฒ€์ฆํ•˜๊ณ , ์„ฑ๊ฒฉ์žฅ์• 

๊ฐ€ ์—†๋Š” ์ง‘๋‹จ๊ณผ์˜ ์ฐจ์ด๋ฅผ ํ™•์ธํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋‘˜์งธ, ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ

ํŠน์ˆ˜ํ•œ ๋งฅ๋ฝ์ธ ์ธ์‚ฌ ์„ ๋ฐœ๊ณผ ๋ฐฐ์น˜ ๋ฐ ๊ต์œก ๋“ฑ์— ํ™œ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”,

๊ฐ ๋งฅ๋ฝ์—์„œ BTI๊ฐ€ ํƒ€๋‹นํ•œ์ง€์— ๋Œ€ํ•œ ์ถ”ํ›„ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์…‹์งธ,

๋ณธ ๊ฒ€์‚ฌ๋Š” ์ž๊ธฐ๋ณด๊ณ ํ˜• ๊ฒ€์‚ฌ์ด๊ธฐ ๋•Œ๋ฌธ์— ์‘๋‹ต์ž์˜ ์‘๋‹ต ํŽธํ–ฅ์ด ์žˆ

์„ ์ˆ˜ ์žˆ๋‹ค. ์ถ”ํ›„ BTI ๊ฒ€์‚ฌ์— ๋Œ€ํ•œ ๊ฑฐ์ง“ ๋ฐ˜์‘(faking response)์„ ์ธก

์ •ํ•˜๋Š” ์ฒ™๋„๋ฅผ ๊ฐœ๋ฐœํ•˜๊ณ , ํƒ€๋‹น๋„ ์ฒ™๋„๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค.

๋„ท์งธ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” 4์ฃผ์˜ ๊ฐ„๊ฒฉ์„ ๋‘๊ณ  ๊ฒ€์‚ฌ-์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„๋ฅผ ํ™•

์ธํ•˜์˜€๋‹ค. ์ด๋Š” ์„ฑ๊ฒฉ์„ ์ธก์ •ํ•˜๋Š” ๋„๊ตฌ๋ผ๋Š” ์ ์„ ๊ฐ์•ˆํ•  ๋•Œ, ์งง์€ ๊ฐ„

๊ฒฉ์ผ ์ˆ˜ ์žˆ๋‹ค. ์ถ”ํ›„ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋ณด๋‹ค ์žฅ๊ธฐ์ ์ธ ์‹œ๊ฐ„์  ์•ˆ์ •์„ฑ์„ ํ™•

Lee et al.

328 https://doi.org/10.15842/kjcp.2019.38.3.005

์ธํ•˜์—ฌ์•ผ ํ•œ๋‹ค.

์œ„์˜ ์ œํ•œ์ ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์˜์˜๋ฅผ ์ง€๋‹Œ

๋‹ค. ์ฒซ์งธ, ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ์„ ํ†ตํ•ฉ์ ์œผ๋กœ ์ธก์ •ํ• 

์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์™€ ๊ธฐ์กด ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋“ค์ด ์ผ๊ด€๋˜๊ฒŒ ๋ณด๊ณ ํ•˜๋“ฏ์ด,

์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ณผ ๋ถ€์ ์‘ ์„ฑ๊ฒฉ 5์š”์ธ์˜ ๊ฐ ๋Œ€์‘๋˜๋Š” ๊ฐœ๋…๋“ค(์˜ˆ, ์™ธํ–ฅ-๋‚ด

ํ–ฅ์„ฑ vs. ๋Œ€์ธํšŒํ”ผ์„ฑ, ์ˆ˜์šฉ์„ฑ vs. ์ž๊ธฐ์ค‘์‹ฌ์„ฑ ๋“ฑ)์€ ๊ฐ๊ฐ ํ•˜๋‚˜์˜ ์ฐจ

์›์œผ๋กœ ์ธก์ •๋˜๊ธฐ ์–ด๋ ต๋‹ค. ๋‹ค์‹œ ๋งํ•ด, ์ผ๋ฐ˜ ์„ฑ๊ฒฉ์˜ ๊ฐœ๋…(์˜ˆ, ์™ธํ–ฅ-๋‚ด

ํ–ฅ์„ฑ)์—์„œ์˜ ๋‚ฎ์€ ์ ์ˆ˜๊ฐ€ ๋†’์€ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ(์˜ˆ, ๋Œ€์ธํšŒํ”ผ์„ฑ)์„

๋ฐ˜์˜ํ•˜์ง€๋Š” ๋ชปํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด๊ณ ๋˜์—ˆ๋‹ค(Butcher & Rouse, 1996;

Clark, 1993; Morey et al., 2000). ๋”ฐ๋ผ์„œ, ์„ฑ๊ฒฉ์˜ ๋‘ ์ธก๋ฉด์„ ๋™์‹œ์—

์ธก์ •ํ•˜๊ณ  ํ†ตํ•ฉ์ ์œผ๋กœ ํ•ด์„ํ•  ๋•Œ, ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๋ฟ ์•„๋‹ˆ๋ผ ๋ถ€์ ์‘

์„ฑ๊ฒฉํŠน์„ฑ์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ํ‰๊ฐ€๊ฐ€ ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ํŒ๋‹จ๋œ๋‹ค. ๋‘˜์งธ, BTI๋Š”

์˜ˆ๋น„ ๋ฌธํ•ญ์˜ ์ œ์ž‘๋ถ€ํ„ฐ ๊ฒ€์‚ฌ ์š”์ธ๊ตฌ์กฐ์˜ ๊ฒ€์ฆ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ํ•œ๊ตญ์ธ

์„ ๋Œ€์ƒ์œผ๋กœ ์ด๋ฃจ์–ด์กŒ๋‹ค. ๋ฌธํ™”์  ์š”์†Œ๋ฅผ ๋ฐ˜์˜ํ•œ ๊ฒ€์‚ฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๊ธฐ

์œ„ํ•ด, BTI๋Š” ์˜ˆ๋น„ ๋ฌธํ•ญ ์ œ์ž‘ ๊ณผ์ •๊ณผ ๋ฌธํ•ญ์„ ๋ฐœ ๊ณผ์ •์—์„œ ์ดˆ๊ธฐ๋ถ€ํ„ฐ

ํ•œ๊ตญ์–ด์™€ ํ•œ๊ตญ ๋ฌธํ™”์— ์ž์—ฐ์Šค๋Ÿฌ์šด ๋‹จ์–ด์™€ ๋ฌธ์žฅ์„ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ๊ฐ

๋ฌธํ•ญ์— ๋Œ€ํ•œ ํ•œ๊ตญ์ธ์˜ ๋ฐ˜์‘ ํŠน์ˆ˜์„ฑ์„ ๋ฐ˜์˜ํ•˜์—ฌ ์š”์ธ ๊ตฌ์กฐ๋ฅผ ๊ฒ€์ฆ

ํ•˜๊ณ  ๊ทœ์ค€์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์…‹์งธ, BTI๋Š” ๋‹ค์–‘ํ•œ ํ‘œ๋ณธ์„ ๋Œ€์ƒ์œผ๋กœ ํƒ€

๋‹นํ™” ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์˜จ๋ผ์ธ ์ „๋ฌธ์กฐ์‚ฌ ์—…์ฒด๋ฅผ ํ†ตํ•˜์—ฌ ์ „๊ตญ์—

์žˆ๋Š” 20โ€“60๋Œ€ ์„ฑ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ์˜ˆ๋น„์กฐ์‚ฌ์™€ ๋ณธ ์กฐ์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์—ฌ ๊ฒ€

์‚ฌ์˜ ํƒ€๋‹น๋„๋ฅผ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์ œํ•œ๋œ ํ‘œ๋ณธ์œผ๋กœ ํƒ€๋‹นํ™”

๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋˜ ๊ธฐ์กด ๊ฒ€์‚ฌ์˜ ํ•œ๊ณ„์ ์„ ๊ทน๋ณตํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์•ž

์œผ๋กœ BTI๋ฅผ ์ž„์ƒ๊ตฐ์— ํ™œ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”, BTI๋ฅผ ์ž„์ƒ๊ตฐ์„ ๋Œ€์ƒ์œผ

๋กœ ์‹ค์‹œํ•˜๊ณ  ์ž„์ƒ์  ์œ ์šฉ์„ฑ๊ณผ ํƒ€๋‹น์„ฑ์„ ๊ฒ€์ฆํ•ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๋„ท์งธ,

BTI๋Š” ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ์„ ๊ธฐ์กด์˜ ์„ฑ๊ฒฉ๊ฒ€์‚ฌ์— ๋น„

ํ•ด ๊ฐ„๊ฒฐํ•œ ์ˆ˜์˜ ๋ฌธํ•ญ์œผ๋กœ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ธฐ์กด ์„ฑ๊ฒฉ๊ฒ€์‚ฌ๋Š” ๋Œ€์ฒด๋กœ

๋ฌธํ•ญ์˜ ์ˆ˜๊ฐ€ ๋งŽ์•„ ๋‹ค์–‘ํ•œ ํ˜„์žฅ์—์„œ ํ™œ์šฉํ•˜๋Š” ๋ฐ ๋งŽ์€ ์‹œ๊ฐ„๊ณผ ๋น„์šฉ

์ด ๋“ ๋‹ค๋Š” ๋ฌธ์ œ์ ์ด ์žˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์ง„์€ ๋ฌธํ•ญ ์ˆ˜๋ฅผ ๊ฐ„์†Œํ™”ํ•˜๊ณ ,

์˜จ๋ผ์ธ ์‹ค์‹œ๊ฐ€ ๊ฐ€๋Šฅํ•˜๋„๋ก ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ํŠน์ง•์€ ํŠนํžˆ ์˜ค๋žœ

์‹œ๊ฐ„ ๊ฒ€์‚ฌ์— ์ฐธ์—ฌํ•˜๊ธฐ ์–ด๋ ค์šด ์ž„์ƒ๊ตฐ์—๊ฒŒ ์‹ค์‹œํ•  ๊ฒฝ์šฐ ์‘๋‹ต์ž์˜

์ฃผ์˜๋ ฅ ์ €ํ•˜๋กœ ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ์˜ค๋ฅ˜๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒํ•œ

๋‹ค. ๋‹ค์„ฏ์งธ, ๋ณธ ๊ฒ€์‚ฌ์˜ ๊ตฌ์„ฑ๊ฐœ๋… ํƒ€๋‹น๋„๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฐ ๊ฐœ๋ณ„

๋ฌธํ•ญ์„ ์ธก์ •๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜์—ฌ ํ™•์ธ์  ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์ธก์ •

๋ณ€์ˆ˜์— ๋ฌธํ•ญ๋ฌถ์Œ(item parceling)์„ ์‚ฌ์šฉํ•˜๋ฉด ๊ณตํ†ต๋ถ„์‚ฐ์ด ์ฆ๊ฐ€ํ•˜

์—ฌ ๊ด€์ฐฐ๋ณ€์ˆ˜์˜ ์‹ ๋ขฐ๋„ ๋ฐ ํƒ€๋‹น๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ฒŒ ๋˜์–ด ์š”์ธ์˜ ์ถ”์ •์ด

๋ณด๋‹ค ์•ˆ์ •์ ์œผ๋กœ ์ด๋ฃจ์–ด์ง€๊ธฐ ๋•Œ๋ฌธ์—(Bandalos, 2002) ์–‘ํ˜ธํ•œ ๋ชจํ˜•

ํ•ฉ์น˜๋„๋ฅผ ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ๋‹ค(Rogers & Schmitt, 2004). ๊ทธ๋Ÿฌ๋‚˜ ๋‹ค์ฐจ์›

๊ฒ€์‚ฌ์ธ ๊ฒฝ์šฐ ์ด๋Ÿฌํ•œ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜๋ฉด ์œ ์˜ํ•˜์ง€ ์•Š๋˜ ๊ฒฝ๋กœ๊ณ„์ˆ˜๋“ค์ด

์œ ์˜๋ฏธํ•˜๊ฒŒ ๋ณ€ํ™”๋˜๊ฑฐ๋‚˜ ์–‘ํ˜ธํ•˜์ง€ ์•Š๋˜ ๋ชจํ˜•์˜ ํ•ฉ์น˜๋„๊ฐ€ ์–‘ํ˜ธํ•˜๊ฒŒ

๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋‹ค. ์ด๋กœ ์ธํ•ด ๊ฐœ๋…์ ์œผ๋กœ ๋‹ค๋ฅธ ๊ด€์ฐฐ๋ณ€์ˆ˜๋“ค์„ ํ•˜๋‚˜์˜

๊ด€์ฐฐ๋ณ€์ˆ˜๋กœ ๋ฌถ์Œ์œผ๋กœ์จ ์ฒ™๋„๊ฐ€ ๊ฐ€์ง€๋Š” ๋ณธ๋ž˜์˜ ์˜๋ฏธ๊ฐ€ ์™œ๊ณก๋  ๊ฐ€

๋Šฅ์„ฑ์ด ์žˆ๋‹ค(Kim & Kim, 2018; Yu, 2015). ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‹ค์ฐจ

์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๊ณ  ํƒ€๋‹นํ™”ํ•˜๋Š” ์—ฐ๊ตฌ์ด๋ฏ€๋กœ ๊ฐ ๋ฌธํ•ญ์ด ํ•ด๋‹น

๊ตฌ์„ฑ๊ฐœ๋…์„ ๋ฐ˜์˜ํ•˜๋Š” ์ •๋„ ๋ฐ ๋‹ค์ฐจ์› ๊ตฌ์กฐ์˜ ํ™•์ธ์ด ์ค‘์š”ํ•˜๊ธฐ ๋•Œ

๋ฌธ์— ๊ฐœ๋ณ„๋ฌธํ•ญ์„ ๊ด€์ฐฐ๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜๋Š” ๊ฒƒ์ด ๋” ์ ํ•ฉํ•˜๋‹ค๊ณ  ํŒ๋‹จํ•˜

์˜€๋‹ค(Lee & Kim, 2016).

์š”์•ฝํ•˜๋ฉด, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ตญ๋‚ด์™ธ ์ตœ์ดˆ๋กœ ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๊ณผ ๋ถ€์ 

์‘ ์œ„ํ—˜ํŠน์„ฑ์„ ํ†ตํ•ฉ์ ์œผ๋กœ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒ€์‚ฌ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ–ˆ๋‹ค๋Š”

์˜์˜๋ฅผ ์ง€๋‹Œ๋‹ค. ์•ž์œผ๋กœ ๋ณธ ๊ฒ€์‚ฌ๊ฐ€ ์„ฑ๊ฒฉ์˜ ๋‘ ์ธก๋ฉด์„ ์ธก์ •ํ•˜์—ฌ, ๊ธฐ์กด

๊ฒ€์‚ฌ์— ๋น„ํ•ด ๊ฐœ์ธ์˜ ๊ณ ์œ ํ•œ ์„ฑ๊ฒฉํŠน์„ฑ์„ ๋ณด๋‹ค ์ •ํ™•ํ•˜๊ฒŒ ํŒŒ์•…ํ•˜๋Š”์ง€

๋ฅผ ๊ฒ€์ฆํ•˜๊ณ  ๋‹ค์–‘ํ•œ ๋งฅ๋ฝ์—์„œ ํƒ€๋‹นํ™”๊ฐ€ ์ด๋ฃจ์–ด์ง„๋‹ค๋ฉด, ์ž„์ƒ, ๊ธฐ์—…

์žฅ๋ฉด ๋“ฑ์—์„œ ๋„๋ฆฌ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์ƒ๊ฐํ•œ๋‹ค.

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๊ตญ๋ฌธ์ดˆ๋ก

๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ ๋„๊ตฌ์˜ ๊ฐœ๋ฐœ๊ณผ ํƒ€๋‹นํ™” ์˜ˆ๋น„์—ฐ๊ตฌ: ์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ณผ ๋ถ€์ ์‘ ์„ฑ๊ฒฉ์˜ ํ†ตํ•ฉ์  ํ‰๊ฐ€

์ด์ƒ์ค€1 โˆ™ํ•œ์—ฌ์šธ2 โˆ™๊น€ํšจ์›1 โˆ™์ดํฌ์žฌ3 โˆ™๋ฐ•์žฌ์˜2 โˆ™์ตœ๊ธฐํ™2 โˆ™๋ฐ•๋‘์ง„1 โˆ™์ตœ์ •์šฑ3 โˆ™๊น€๋ช…๊ธฐ3 โˆ™์„œ๋™๊ธฐ3

1ํ”ผ๋น„์”จ์ง€(์‹ฌ๋ฆฌ๊ธฐ๋ฐ˜์ปจ์„คํŒ…์—ฐ๊ตฌ์†Œ), 2๊ณ ๋ ค๋Œ€ํ•™๊ต ์‹ฌ๋ฆฌํ•™๊ณผ, 3ํ•œ๋ฆผ๋Œ€ํ•™๊ต ์‹ฌ๋ฆฌํ•™๊ณผ

๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•œ๊ตญ์ธ์˜ ์„ฑ๊ฒฉ์„ ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜๊ณ , ์ด๋ฅผ ๋‹ค์ฐจ์›์ ์œผ๋กœ ์ธก์ •ํ•˜๋Š” ํ•œ๊ตญํ˜• ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ

(Big 10 Inventory, BTI)๋ฅผ ๊ฐœ๋ฐœ ๋ฐ ํƒ€๋‹นํ™”ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์˜ˆ๋น„์กฐ์‚ฌ์—์„œ ๋ฌธํ—Œ ์—ฐ๊ตฌ์™€ ์ „๋ฌธ๊ฐ€์˜ ๋…ผ์˜๋ฅผ ํ†ตํ•˜์—ฌ ์ผ๋ฐ˜ ์„ฑ๊ฒฉ๊ณผ ๋ถ€์ ์‘ ์„ฑ

๊ฒฉ์„ ๊ตฌ์„ฑํ•˜๋Š” ๊ตฌ์„ฑ๊ฐœ๋…์„ ๋„์ถœํ•˜๊ณ , ์˜ˆ๋น„ ๋ฌธํ•ญ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ดํ›„ ์ „๊ตญ ์„ฑ์ธ 1,200๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์˜ˆ๋น„ ์กฐ์‚ฌ๋ฅผ ํ†ตํ•ด ์˜ˆ๋น„ ๋ฌธํ•ญ์˜ ๋ฌธํ•ญ ๋ถ„

์„๊ณผ ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•˜์—ฌ, 1์ฐจ ๋ฌธํ•ญ์„ ์„ ์ •ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์˜ˆ๋น„ ์กฐ์‚ฌ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ถ”๊ฐ€ ๋ฌธํ•ญ ๊ฐœ๋ฐœ ๋ฐ ๊ธฐ์กด ๋ฌธํ•ญ์„ ์ˆ˜์ •ํ•˜์˜€๊ณ ,

์„ฑ์ธ 600๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์ตœ์ข… ๋ฌธํ•ญ์„ ํƒ€๋‹นํ™”ํ•˜๊ธฐ ์œ„ํ•œ ๋ณธ ๊ฒ€์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ 5์š”์ธ(16๊ฐœ์˜ ํ•˜์œ„ ์š”์ธ์œผ๋กœ ๊ตฌ์„ฑ)์„

ํ‰๊ฐ€ํ•˜๋Š” 80๊ฐœ ๋ฌธํ•ญ๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ 5์š”์ธ(17๊ฐœ์˜ ํ•˜์œ„ ์š”์ธ์œผ๋กœ ๊ตฌ์„ฑ)์„ ํ‰๊ฐ€ํ•˜๋Š” 85๊ฐœ ๋ฌธํ•ญ์„ ์ตœ์ข… ์„ ๋ณ„ํ•˜์—ฌ, ์ตœ์ข… 165๋ฌธํ•ญ์œผ๋กœ ๊ตฌ

์„ฑ๋œ BTI๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์‹ ๋ขฐ๋„๋ฅผ ๊ฒ€์ฆํ•œ ๊ฒฐ๊ณผ, ์ ์ ˆํ•œ ๋‚ด์  ์ผ๊ด€์„ฑ๊ณผ ๊ฒ€์‚ฌ-์žฌ๊ฒ€์‚ฌ ์‹ ๋ขฐ๋„๋ฅผ ๋ณด์˜€๋‹ค. ํ™•์ธ์  ์š”์ธ ๋ถ„์„ ๊ฒฐ๊ณผ, ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ

5์š”์ธ๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ 5์š”์ธ ๊ตฌ์กฐ์˜ ์–‘ํ˜ธํ•œ ๋ชจํ˜• ์ ํ•ฉ๋„๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ์ถ”๊ฐ€๋กœ, ๊ฐ„ํŽธํ˜• ํ•œ๊ตญ์–ด Big Five Inventory ๋ฐ PID-5 ๊ฒ€์‚ฌ์™€์˜ ์ƒ

๊ด€๊ด€๊ณ„๋ฅผ ํ†ตํ•ด ์ˆ˜๋ ด ํƒ€๋‹น๋„์™€ ๋ณ€๋ณ„ ํƒ€๋‹น๋„๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ BTI๊ฐ€ ์ผ๋ฐ˜ ํŠน์„ฑ๊ณผ ๋ถ€์ ์‘ ํŠน์„ฑ์„ ์ •ํ™•ํ•˜๊ฒŒ ํ‰๊ฐ€ํ•˜๋Š” ์‹ ๋ขฐ๋กญ๊ณ  ํƒ€

๋‹นํ•œ ๊ฒ€์‚ฌ์ž„์„ ๊ฒ€์ •ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์˜ ์ œํ•œ์ ๊ณผ ์ถ”ํ›„ ์—ฐ๊ตฌ๋‚ด์šฉ์„ ์ œ์•ˆํ•˜์˜€๋‹ค.

์ฃผ์š”์–ด: ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ, ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ, ์„ฑ๊ฒฉ๊ฒ€์‚ฌ, ํƒ€๋‹นํ™”, Big 10 ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ

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Appendix I. Big 10 Inventory์˜ ํ•˜์œ„์š”์ธ์˜ ์ •์˜

์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ

์ƒ์œ„์š”์ธ ํ•˜์œ„์š”์ธ ์ •์˜

์™ธํ–ฅ-๋‚ดํ–ฅ์„ฑ ํ™œ๋ ฅ(EB1) ์—๋„ˆ์ง€๊ฐ€ ๋งŽ์œผ๋ฉฐ ํ™œ๋™์ ์ด๊ณ  ์—ด์ •์ ์œผ๋กœ ์ƒํ™œํ•˜๊ธฐ๋ฅผ ์ฆ๊ธฐ๋Š” ์„ฑํ–ฅ

์‚ฌ๊ต(EB2) ์ƒˆ๋กœ์šด ๋งŒ๋‚จ์„ ์ข‹์•„ํ•˜๊ณ  ์‚ฌ๋žŒ๋“ค๊ณผ ์ ๊ทน์ ์œผ๋กœ ์–ด์šธ๋ฆฌ๋Š” ์„ฑํ–ฅ

์ฃผ๋„(EB3) ์ž๊ธฐ ์ฃผ์žฅ์ด ๊ฐ•ํ•˜๋ฉฐ ๋‹ค๋ฅธ ์‚ฌ๋žŒ์—๊ฒŒ ์˜ํ–ฅ๋ ฅ์„ ํ–‰์‚ฌํ•˜๋ ค๋Š” ์„ฑํ–ฅ

๋‚ดํ–ฅ(IN) ์‚ฌ๋žŒ๋“ค๊ณผ ์–ด์šธ๋ฆฌ๊ธฐ๋ณด๋‹ค๋Š” ๋…๋ฆฝ์ ์œผ๋กœ ์ƒํ™œํ•˜๊ธฐ๋ฅผ ์„ ํ˜ธํ•˜๋Š” ์„ฑํ–ฅ

์ˆ˜์šฉ์„ฑ ์‹ ๋ขฐ(AB1) ๋Œ€์ธ๊ด€๊ณ„์—์„œ ๋ฏฟ์Œ๊ณผ ์‹ ์˜๋ฅผ ์ค‘์‹œํ•˜์—ฌ ํˆฌ๋ช…ํ•˜๊ณ  ์†”์งํ•˜๊ฒŒ ํ–‰๋™ํ•˜๋Š” ์„ฑํ–ฅ

๊ด€๋Œ€(AB2) ๋Œ€์ธ๊ด€๊ณ„์—์„œ ๋„ˆ๊ทธ๋Ÿฝ๊ณ  ๋ฌด๋˜ํ•˜์—ฌ ์›๋งŒํ•œ ๊ด€๊ณ„๋ฅผ ์œ ์ง€ํ•˜๋ ค๋Š” ์„ฑํ–ฅ

์ดํƒ€(AB3) ํƒ€์ธ์˜ ์ƒ๊ฐ๊ณผ ๊ฐ์ •์— ๊ณต๊ฐํ•˜๋ฉฐ ํƒ€์ธ์„ ์ ๊ทน์ ์œผ๋กœ ๋ฐฐ๋ คํ•˜๊ณ  ๋•๋Š” ์„ฑํ–ฅ

์„ฑ์‹ค์„ฑ ๋ˆ๊ธฐ(CB1) ๋ชฉํ‘œ๋ฅผ ์™„์ˆ˜ํ•˜๊ธฐ ์œ„ํ•ด ๋ˆ๊ธฐ ์žˆ๊ฒŒ ๋…ธ๋ ฅํ•˜๋Š” ์„ฑํ–ฅ

์„ฑ์ทจ(CB2) ๋†’์€ ์ˆ˜์ค€์˜ ๋ชฉํ‘œ๋ฅผ ์ง€ํ–ฅํ•˜๊ณ  ์ด๋ฅผ ๋‹ฌ์„ฑํ•˜๋ ค๋Š” ์„ฑํ–ฅ

์ฒด๊ณ„(CB3) ๊ทœ์น™๊ณผ ์ฒด๊ณ„๋ฅผ ์ข‹์•„ํ•˜๋ฉฐ ์งˆ์„œ์ •์—ฐํ•˜๊ฒŒ ํ–‰๋™ํ•˜๋ ค๋Š” ์„ฑํ–ฅ

๊ฐœ๋ฐฉ์„ฑ ์‹ฌ๋ฏธ(OB1) ์˜ˆ์ˆ ๊ณผ ์•„๋ฆ„๋‹ค์›€์— ๋Œ€ํ•œ ๊ฐ์ˆ˜์„ฑ์ด ํ’๋ถ€ํ•˜๋ฉฐ ๋ฏธ์  ํ™ฉ๋™์„ ์ฆ๊ธฐ๋Š” ์„ฑํ–ฅ

ํƒ๊ตฌ(OB2) ์ง€์  ํ˜ธ๊ธฐ์‹ฌ์ด ๊ฐ•ํ•˜๋ฉฐ ์ฒ ํ•™์ ์ด๊ณ  ์ถ”์ƒ์ ์ธ ์‚ฌ๊ณ ์™€ ์ถ”๋ก ์„ ์ฆ๊ธฐ๋Š” ์„ฑํ–ฅ

์ฒดํ—˜(OB3) ์ƒˆ๋กญ๊ณ  ๋‹ค์–‘ํ•œ ํ™œ๋™์„ ์ง์ ‘ ์ฒดํ—˜ํ•˜๊ธฐ๋ฅผ ์ข‹์•„ํ•˜๋Š” ํƒํ—˜์ ์ธ ์„ฑํ–ฅ

์ •์„œ์•ˆ์ •์„ฑ ์ •์„œ์ˆ˜์šฉ(NB1) ์ž์‹ ์ด ๊ฒฝํ—˜ํ•˜๋Š” ๊ฐ์ •์„ ์™œ๊ณกํ•˜๊ฑฐ๋‚˜ ์–ต๋ˆ„๋ฅด์ง€ ์•Š๊ณ  ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ๋ฐ›์•„๋“ค์ด๋Š” ์„ฑํ–ฅ

์ •์„œํ‘œํ˜„(NB2) ๊ฐ์ •์„ ๋“œ๋Ÿฌ๋‚ด๋Š” ๊ฒƒ์„ ๋‘๋ ค์›Œํ•˜๊ฑฐ๋‚˜ ์–ด๋ ค์›Œํ•˜์ง€ ์•Š๊ณ  ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ํ‘œํ˜„ํ•˜๋Š” ์„ฑํ–ฅ

์ •์„œ์ธ์‹(NB4) ์ž์‹ ์ด ๊ฒฝํ—˜ํ•˜๋Š” ์ •์„œ์— ๊ด€์‹ฌ์„ ๊ธฐ์šธ์ด๊ณ  ์ด๋ฅผ ์ •ํ™•ํ•˜๊ณ  ๊ตฌ์ฒด์ ์œผ๋กœ ์ดํ•ดํ•˜๋Š” ์„ฑํ–ฅ

๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ

์ƒ์œ„์š”์ธ ํ•˜์œ„์š”์ธ ์ •์˜

๋Œ€์ธํšŒํ”ผ์„ฑ ๊ณ ๋ฆฝ(ED1) ๋Œ€์ธ๊ด€๊ณ„์— ๋Œ€ํ•œ ์š•๊ตฌ๊ฐ€ ์—†์œผ๋ฉฐ ์นœ๋ฐ€ํ•œ ๊ด€๊ณ„ ํ˜•์„ฑ์„ ํšŒํ”ผํ•˜๋Š” ์„ฑํ–ฅ

๋ฌด์พŒ(ED2) ๊ธ์ •์  ์ •์„œ๋ฅผ ์ž˜ ๊ฒฝํ—˜ํ•˜์ง€ ๋ชปํ•˜๋Š” ์„ฑํ–ฅ

์˜์‹ฌ(ED3) ํƒ€์ธ์„ ์‹ ๋ขฐํ•˜์ง€ ์•Š๊ณ  ํ•ญ์ƒ ๊ฒฝ๊ณ„ํ•˜๊ฑฐ๋‚˜ ์˜์‹ฌํ•˜๋Š” ์„ฑํ–ฅ

์ž๊ธฐ์ค‘์‹ฌ์„ฑ ์—ฐ๊ธฐ(AD1) ํƒ€์ธ์˜ ์‹œ์„ ์„ ๋…์ฐจ์ง€ํ•˜๊ณ  ์ด๋ชฉ์„ ์ง‘์ค‘์‹œํ‚ค๊ณ ์ž ํ•˜๋Š” ์„ฑํ–ฅ

์ž๊ธฐ์• (AD2) ํƒ€์ธ์— ๋น„ํ•ด ์ž์‹ ์ด ์šฐ์›”ํ•˜๋ฉฐ ํŠน๋ณ„ํ•˜๊ฒŒ ๋Œ€์šฐ๋ฐ›์•„์•ผ ํ•œ๋‹ค๊ณ  ๋ฏฟ๋Š” ์„ฑํ–ฅ

์กฐ์ข…(AD3) ์ž์‹ ์˜ ์ด์ต์„ ์ถฉ์กฑํ•˜๊ธฐ ์œ„ํ•ด ํƒ€์ธ์„ ์กฐ์ข…ํ•˜๋ ค๋Š” ์„ฑํ–ฅ

๋ƒ‰ํ˜น(AD4) ๋‹ค๋ฅธ ์‚ฌ๋žŒ์—๊ฒŒ ๊ณต๊ฐํ•˜์ง€ ๋ชปํ•˜์—ฌ ๊ฐ€ํ˜นํ•˜๊ณ  ๋ƒ‰๋‹ดํ•œ ์„ฑํ–ฅ

์ฃผ์˜๊ณค๋ž€์„ฑ ์‚ฐ๋งŒ(CD1) ์ฃผ์˜๊ฐ€ ์‰ฝ๊ฒŒ ๋ถ„์‚ฐ๋˜์–ด ๊ณผ์ œ์— ์ง‘์ค‘ํ•˜์ง€ ๋ชปํ•˜๋Š” ์„ฑํ–ฅ

์ถฉ๋™(CD2) ์ƒํ™ฉ์— ๋”ฐ๋ผ ์ฆ‰ํฅ์ ์ด๊ณ  ๊ธฐ๋ถ„ ๋‚ดํ‚ค๋Š” ๋Œ€๋กœ ํ–‰๋™ํ•˜๋Š” ์„ฑํ–ฅ

์ง‘์ฐฉ(CD3) ์ค‘์š”ํ•˜์ง€ ์•Š์€ ์ผ์ด๋‚˜ ์ž๊ทน์„ ๋–จ์ณ๋‚ด์ง€ ๋ชปํ•˜๊ณ  ๊ณผ๋„ํ•˜๊ฒŒ ๋งค๋‹ฌ๋ฆฌ๋Š” ์„ฑํ–ฅ

์ •์‹ ์ฆ์„ฑ ๊ธฐ์ด(OD1) ๋ณดํ†ต ์‚ฌ๋žŒ๊ณผ ๋‹ฌ๋ฆฌ ํŠน์ดํ•˜๊ณ  ๋น„๊ด€์Šต์ ์ธ ๋ฐฉ์‹์œผ๋กœ ์‚ฌ๊ณ ํ•˜๊ฑฐ๋‚˜ ํ–‰๋™ํ•˜๋Š” ์„ฑํ–ฅ

์กฐํ˜„(OD2) ํ˜„์‹ค์„ ์™œ๊ณก๋œ ๋ฐฉ์‹์œผ๋กœ ํŒ๋‹จํ•˜๊ณ  ๊ฒฝํ—˜ํ•˜์—ฌ ์„ธ๊ณ„์— ๋Œ€ํ•ด ๋น„ํ•ฉ๋ฆฌ์ ์ธ ์‹ ๋…์„ ๋ณด์ด๋Š” ์„ฑํ–ฅ

๊ฒฝ์ง(OD3) ์œตํ†ต์„ฑ์ด ์—†์–ด ๋ชจํ˜ธํ•œ ์ƒํ™ฉ์„ ์ฐธ๊ธฐ ์–ด๋ ค์›Œํ•˜๋ฉฐ ์™„๊ณ ํ•˜๊ฒŒ ์‚ฌ๊ณ ํ•˜๋Š” ์„ฑํ–ฅ

๋ถ€์ •์ •์„œ์„ฑ ์˜์กด(ND1) ๋ถˆ์•ˆ์ •ํ•œ ๊ฐ์ •์„ ๊ฐ๋‹นํ•˜๊ธฐ ์œ„ํ•ด ํƒ€์ธ์—๊ฒŒ ์ „์ ์œผ๋กœ ์˜์ง€ํ•˜๋Š” ์„ฑํ–ฅ

๋ถ„๋…ธ(ND2) ์ž‘์€ ์ผ์—๋„ ์‰ฝ๊ฒŒ ๋ถ„๋…ธํ•˜์—ฌ ์งœ์ฆ์„ ๋‚ด๊ฑฐ๋‚˜ ์„ฑ์„ ๋‚ด๋Š” ์„ฑํ–ฅ

๋ถˆ์•ˆ(ND3) ๋งŒ์„ฑ์ ์œผ๋กœ ๊ธด์žฅํ•˜๊ณ  ๊ฒฝ๊ณ„ํ•˜๋ฉด์„œ ๊ฑฑ์ •ํ•˜๋Š” ์„ฑํ–ฅ

์—ด๋“ฑ(ND4) ์Šค์Šค๋กœ์— ๋Œ€ํ•ด ๋งŒ์„ฑ์ ์œผ๋กœ ๋ถ€์ •์ ์ธ ํ‰๊ฐ€๋ฅผ ํ•˜์—ฌ ์ž์‹ ์„ ๋น„ํ•˜ํ•˜๊ณ  ๋น„๋‚œํ•˜๋Š” ์„ฑํ–ฅ

Multi-dimensional Personality Assessment

333https://doi.org/10.15842/kjcp.2019.38.3.005

Appendix II. ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ(Big 10 Inventory) ์ผ๋ฐ˜ ์„ฑ๊ฒฉํŠน์„ฑ(Bright 5)๊ณผ ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ(Dark 5)์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ

Factor Item Estimate Est./S.E.

ํ™œ๋ ฅ EB101 .766** 38.682

EB102 .843** 44.694

EB103 .850** 43.672

EB105 .880** 50.365

EB106 .736** 30.028

์‚ฌ๊ต EB201 .842** 52.510

EB202 .839** 54.181

EB203 .949** 89.932

EB205 .748** 30.314

EB207 .917** 78.150

์ฃผ๋„ EB301 .885** 60.115

EB302 .906** 65.248

EB303 .707** 22.508

EB305 .882** 60.209

EB307 .766** 30.286

๋‚ดํ–ฅ IN_15r .623** 19.673

IN_16r .818** 25.520

IN_17r .711** 22.766

IN_18r .869** 21.437

IN_19r .659** 21.078

์‹ ๋ขฐ AB102 .807** 16.994

AB103 .548** 12.134

AB104 .614** 14.252

AB105 .442** 9.078

AB107 .601** 12.957

๊ด€๋Œ€ AB203 .499** 11.625

AB205 .597** 12.749

AB207 .787** 24.667

AB208 .335** 6.863

AB209 .789** 18.210

์ดํƒ€ AB302 .356** 6.688

AB303 .784** 26.748

AB305 .699** 17.652

AB306 .642** 14.904

AB307 .619** 13.735

๋ˆ๊ธฐ CB101 .811** 34.090

CB102 .723** 28.106

CB103 .823** 34.893

CB104 .818** 37.178

CB106 .804** 34.247

์„ฑ์ทจ CB201 .754** 24.360

CB203 .714** 19.852

CB204 .585** 16.555

CB206 .604** 16.430

CB207 .775** 24.140

์ฒด๊ณ„ CB302 .816** 35.074

CB303 .718** 19.168

CB305 .698** 19.842

CB306 .833** 31.619

CB307 .759** 20.445

์‹ฌ๋ฏธ OB107 .733** 26.680

OB109 .734** 23.187

OB110 .796** 32.960

OB111 .820** 34.548

OB112 .812** 38.378

Factor Item Estimate Est./S.E.

ํƒ๊ตฌ OB201 .740** 24.499

OB202 .699** 22.016

OB206 .738** 20.721

OB208 .662** 20.113

OB211 .723** 25.943

์ฒดํ—˜ OB302 .768** 33.597

OB303 .832** 33.372

OB305 .714** 27.636

OB306 .723** 26.524

OB307 .840** 36.116

์ •์„œ์ˆ˜์šฉ NB103 .490** 11.310

NB107 .702** 20.608

NB109 .527** 12.714

NB110 .758** 21.247

NB111 .402** 8.360

์ •์„œํ‘œํ˜„ NB201 .702** 21.478

NB202 .435** 10.048

NB205 .795** 27.231

NB208 .601** 17.389

NB209 .670** 18.602

์ •์„œ์ธ์‹ NB104 .699** 23.754

NB105 .781** 28.950

NB404 .818** 30.985

NB405 .878** 42.835

NB406 .689** 18.274

์™ธํ–ฅ์„ฑ EB1 .937** 60.581

EB2 .848** 46.623

EB3 .781** 32.494

INr .432** 11.457

์ˆ˜์šฉ์„ฑ AB1 .680** 15.022

AB2 .602** 15.075

AB3 .804** 25.287

์„ฑ์‹ค์„ฑ CB1 .856** 27.798

CB2 .854** 26.706

CB3 .481** 11.110

๊ฐœ๋ฐฉ์„ฑ OB1 .645** 18.671

OB2 .725** 23.126

OB3 .877** 24.636

์ •์„œ์•ˆ์ •์„ฑ NB1 .829** 22.650

NB2 .861** 31.981

NB4 .820** 29.169

์ƒ๊ด€

AB EB .496** 11.787

CB EB .397** 9.725

AB .683** 15.316

OB EB .588** 16.979

AB .511** 10.244

CB .359** 7.452

NB EB .501** 14.623

AB .675** 15.547

CB .542** 12.973

OB .501** 12.531

**p < .001.

Lee et al.

334 https://doi.org/10.15842/kjcp.2019.38.3.005

Appendix III. ๋‹ค์ฐจ์› ์„ฑ๊ฒฉ๊ฒ€์‚ฌ(Big 10 Inventory) ๋ถ€์ ์‘ ์œ„ํ—˜ํŠน์„ฑ(Dark 5)์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ

Factor Item Estimate Est./S.E.

๊ณ ๋ฆฝ ED101 .773** 24.138

ED102 .850** 32.497

ED103 .585** 14.161

ED104 .758** 26.030

ED107 .790** 28.353

๋ฌด์พŒ ED201 .735** 29.001

ED202 .842** 31.445

ED205 .810** 39.349

ED206 .836** 43.757

ED207 .902** 54.343

์˜์‹ฌ ED303 .808** 32.799

ED304 .753** 27.709

ED305 .697** 25.191

ED308 .814** 33.199

ED309 .794** 32.201

์—ฐ๊ธฐ AD101 .842** 28.103

AD103 .696** 18.475

AD104 .651** 17.355

AD105 .857** 29.464

AD107 .402** 8.487

์ž๊ธฐ์•  AD201 .580** 16.049

AD202 .778** 32.431

AD203 .887** 16.842

AD204 .957** 46.142

AD205 .772** 28.512

์กฐ์ข… AD301 .778** 29.281

AD302 .827** 39.221

AD303 .810** 35.000

AD306 .717** 25.304

AD307 .829** 30.827

๋ƒ‰ํ˜น AD401 .692** 21.410

AD402 .783** 26.919

AD403 .848** 27.065

AD405 .812** 30.832

AD407 .828** 29.111

์‚ฐ๋งŒ CD101 .817** 33.858

CD102 .798** 29.513

CD103 .736** 29.378

CD104 .784** 31.145

CD107 .632** 18.992

์ถฉ๋™ CD202 .633** 19.339

CD204 .754** 28.376

CD205 .801** 36.574

CD206 .661** 22.501

CD207 .728** 26.992

์ง‘์ฐฉ CD301 .687** 20.586

CD302 .707** 23.963

CD304 .626** 17.231

CD306 .755** 26.338

CD307 .731** 26.015

๊ธฐ์ด OD105 .883** 43.766

OD107 .812** 27.864

OD108 .833** 36.854

OD109 .800** 32.863

OD110 .797** 38.165

Factor Item Estimate Est./S.E.

์กฐํ˜„ OD208 .843** 32.215

OD210 .568** 14.911OD211 .765** 27.209OD212 .819** 31.155OD213 .720** 23.828

๊ฒฝ์ง OD308 .573** 14.314OD309 .408** 8.373OD310 .666** 16.223OD311 .794** 21.816OD312 .808** 23.333

์˜์กด ND101 .871** 25.249ND102 .802** 24.477ND105 .482** 10.293ND106 .642** 14.792ND107 .125* 2.114

๋ถ„๋…ธ ND201 .889** 52.768ND203 .884** 49.512ND204 .809** 35.654ND206 .763** 30.641ND207 .864** 48.157

๋ถˆ์•ˆ ND301 .696** 24.691ND302 .715** 24.150ND304 .746** 27.426ND305 .584** 17.146ND307 .867** 34.665

์—ด๋“ฑ ND401 .736** 28.809ND402 .717** 26.223ND404 .899** 53.454ND406 .833** 37.969ND407 .885** 47.872

๋Œ€์ธํšŒํ”ผ์„ฑ ED1 .709** 27.329ED2 .848** 37.255ED3 .818** 39.345

์ž๊ธฐ์ค‘์‹ฌ์„ฑ AD1 .757** 25.462AD2 .411** 9.949AD3 .909** 40.797AD4 .805** 29.436

์ฃผ์˜๊ณค๋ž€์„ฑ CD1 .828** 42.949CD2 .946** 59.209CD3 .858** 47.144

์ •์‹ ์ฆ์„ฑ OD1 .690** 27.677OD2 .713** 30.007OD3 .596** 17.377

๋ถ€์ •์ •์„œ์„ฑ ND1 .683** 25.650ND2 .742** 33.584ND3 .796** 42.221ND4 .818** 45.229

์ƒ๊ด€ AD ED .580** 15.935 CD ED .731** 27.313

AD .647** 24.050 OD ED .952** 38.552

AD .858** 28.378CD .930** 41.153

ND ED .955** 56.164AD .555** 16.421CD .914** 46.126

OD .966** 40.209

*p < .05, **p < .001.