, : *,,. 248 ( ), ( ), ( ),,,. < <, (4 ).,.,,.,,,.,. * 2011.. :,, 201 Tel : 053-850-6362, E-mail : eunap@daegu.ac.kr
2014 2,, 66.3%.,,. 2014 5.4%. 3,845 36%., 4.6%, 2.4%, 1.3%, 1.4% 5.4% (2014 )., 2009 78, GDP 7.3% (, 2012. 8. 21)., (, 2003)., 6000 (Custer, 1982). (, 2006),. (Pelletier & Ladouceur, 2007). 1967,, 2000.,,,, (, 2003). 2000 (, 2009). (,, 2003;, 2003;,,, 2004;,,, 2006 ), (, 2002;, 2003;,,,,, 2008;,
2009;, 2010;,,,, 2011;,,, 2011 ). (APA, 1980) (DSM- ). (pathlolgical gambling) APA(1994),. (,,, 2003;, 2005;, 2006;, 2006;,,, 2013).,,, - (, 2006). Ladouceur Walker (1996),,,,,. (2003),., (, 2003;, 2006).,.,.,,.,,..
.,,. (, 2003)..,. Wagenaar(1988) (hindsight bias), (flexible attribution), (biased learning structures), (illusion of control), (illusory correlations), (reduction of complexity) 17. Griffiths (1994) 6 ( 1). 1 (locus of control) (attributional bias), 4. (illusion of control) (Thompson, Armstrong, & Thomas, 1998), (internal locus of control). (flexible attributions), (illusion of control) (flexible attributions) (representativeness) (availability bias) (illusory correlations) (fixation on absolute frequency),, ( : )
(attributional bias). 4,,,,. (2002) 295 Steenbergh (1998) GBQ(Gambling Belief Questionnaire), Langer Roth (1975) 30,. / 2. (2003), /...,. (chance). /. Griffiths(1994),.,,, (2002).,.. Heider(1958),..,,, 3 (, 2002). Jones Davis (Malle, 2008),,,, ( ),,
( ). Rotter(1965).. (locus of control),.,.,. Rotter(1966).. Moore Ohtsuka(1997) 20%. 80%.,,. Ladouceur Dube (1997)..,.,, (Ladouceur, Sylvain, Letarte, Giroux & Jaques, 1998). (personality traits).,,,.,.,,.,!,.. (2009).,,.,.
(2009). ( ). (Fiske & Taylor, 1991).,,. Heider (1958) Rotter(1965),,. Zuckerman(1977) 3. /.,. (self-serving bias),..,..,,,...,.,. Feather(1969) 167,. ( ) ( ), /, / /., ( ), / /. Feather(1968),, /
. /. ( / ) / Ohtsuka Hyam(2003),., ( ), / ( )., SOGS,.,.,,. Gilovich & Douglas (1986), Griffiths(1990),.,, ( )... (, 2003). ( ). / ( ).. ( ).,,.
( ), ( ), ( ). 1.. 1-1.,,,. 1-2.,,,. 2.. 2-1.,. (, 2002). (, ) (, ).. /.. ( ) ( ), ( ). 3.. 3-1.,,,. 3-2.,,,. (Kahneman & Tversky, 1974). 2.,. Taylor Riess(1989)..,... 4.
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(representative- ness). 2.. 5, 4 5?,,, 3. (1 ), (2 ).?,,, 3. (1 ),, (2 )., Rotter(1966). ( ),,. 3. ( / ),,,, 3, (1 ) (7 ) 7., Rosenberg(1979) (2003). 10 6 6.,..,.,?,,?,,?,,? 4. (1 ), (2 ), (3 ), (4 ), (5 ), (6 )
6.. SPSS 19.0,,, (Logistic). 29-67 47.3 (SD=10.01), 20-49 25.1 (SD=5.99). 100%(81 ), 48.5%(81 ), 51.5%(86 ). 2. ( ) (%) ( ) (%) 81 100 81 48.5 - - 86 51.5 81 100 167 100 8 9.9 1 0.6 30 37.0 44 26.3 / 43 53.1 122 73.1 81 100 167 100 200 27 33.3 38 22.8 201-300 19 23.5 49 29.3 301-400 17 21.0 41 24.6 401-500 4 4.9 19 11.4 501 14 17.3 20 12.0 81 100 167 100 12 14.8 5 3.0 5 6.2 13 7.8 9 11.1 29 17.4 34 42.0 9 5.4 / 8 9.9 21 12.6 ( / ) 13 16.0 90 53.9 81 100 167 100
.,, 21. 248 ( ), ( ), ( ) 3. ( ) ( ) ( ) 146 (100%) - - - 14 (34.2%) 51 (83.6%) ( ) 1 / - 6 (14.6%) 9 (14.8%) - 21 (51.2%) 1 (1.6%) 146 (100%) 41 (100%) 61 (100%) 146 (100%) - - 1-18 (43.9%) 2 (3.3%) 1-5 - 15 (36.6%) 12 (19.7%) 5-10 - 6 (14.6%) 31 (50.8%) 10-2 (4.9%) 16 (26.2%) 146 (100%) 41 (100%) 61 (100%) 146 (100%) - - 1-2 - 19 (46.3%) - 3-4 - 2 (4.9%) - 5-6 - 17 (41.5%) 8 (13.1%) 7-3 (7.3%) 53 (86.9%) 146 (100%) 41 (100%) 61 (100%) 146 (100%) - - 3-19 (46.3%) 1 (1.6%) 3-5 - 13 (29.4%) 5 (8.2%) 5-7 - 7 (19.5%) 9 (14.8%) 7-10 - 1 (2.4%) 26 (42.6%) 10-1 (2.4%) 20 (32.8%) 146 (100%) 41(100%) 61 (100%) 146 (100%) 22 (53.7%) 1 (1.6%) 1-15 (36.6%) 17 (27.9%) 1-3 - 3 (7.3%) 11 (18.0%) 3-5 - 1 (2.4%) 8 (13.1%) 5 - - 24 (39.3%) 146 (100%) 41 (100%) 61 (100%)
21, 1, 1, 4 (M=3.62) ( ) ( ). 3.. 2 9, 2, 2 ( / ) 6, 2 1 2 3 4 5 6 7 8 (α) 6( ).845 3( ).826 7( ).794 8( ).765 2( ).731 9( ).569.873 1.832 2.824 3.793 4.752 5.744 6.536.865 1( ).880 4( ).871 5( ).729.797 _ 2.848 _ 3.799 _ 1.737.724 _ 2.868 _ 3.341.698 _ 1.337.581 _ 2.871 _ 1.830 _ 1.755 _ 2.740 1.792 2.724.730.768.751.593 Initial eigenvalue 4.050 3.718 2.248 2.183 1.850 1.673 1.582 1.371 - (%) 15.001 13.769 8.325 8.086 6.851 6.195 5.848 5.078 - (%) 19.094 28.770 37.094 45.181 52.032 58.227 64.085 69.163 - ).30
( / ) 4, 6 27 8,., 2 (Cronbach's alpha).70 ( 4). 1 ( ) ( ), ( ). 5 (F (2,245)=42.835, p<.001). (M=3.81, SD=1.25), (M= 3.15, SD=1.20), (M=2.13, SD=1.00) (F (2,245)=54.028, p<.001), (F (2,245)=2.981, p>.05)., 1-1, 1-2. 2 ( 6), (F (2,245)= 10.005, p<.001)., (chance) post-hoc M SD F ῃ 2 (Duncan) ( ) (N=146) 2.90.86 ( ) (N=41) 3.76.92 ( ) (N=61) 4.11 1.02 3.34 1.05 ( ) (N=146) 2.13 1.00 ( ) (N=41) 3.15 1.20 ( ) (N=61) 3.81 1.25 2.71 1.31 ( ) (N=146) 4.45 1.34 42.835*.259 1<2<3 54.028*.306 1<2<3 ( ) (N=41) 4.99 1.35 ( ) (N=61) 4.76 1.45 2.981 (p=.053).024-4.61 1.38 * p<.001, 1: 2: 3:
M SD F ῃ 2 post-hoc (Duncan) ( ) (N=146) 1.18.29 ( ) (N=41) ( ) (N=61) 1.37 1.41.46.44 1.28.38 * p<.001 1: 2: 3: 10.005*.076 1<2,3,. 2-1. 3. ( 7). 7 (M=4.03, SD=1.32), (M=3.11, SD=1.41), (M=2.75, SD=1.16) (F (2,245) = 22.477, p<.001).., M SD F ῃ 2 post-hoc (Duncan test) ( ) (N=146) 2.75 1.16 ( / ) ( ) (N=41) ( ) (N=61) 3.11 4.03 1.41 1.32 (N=248) ( ) (N=146) 4.90 1.06 ( ) (N=41) 4.89 1.19 ( / ) ( ) (N=61) 4.45 1.25 (N=248) 4.79 1.14 ** p<.001, * p<.05 1: 2: 3: 22.477**.155 1,2<3 3.591*.028 1,2>3
, (M=4.90, SD=1.06) (M=4.89, SD=1.19) (M=4.45, SD=1.25) (F (2,245) =3.591, p<.05)., 3-1 3-2.,. 8 (M=2.15, SD=1.72) (M=1.79, SD=1.97) (M=.43, SD=1.39).,,.. 9, (M=4.44, SD=.91) (M=4.37, SD=.98) (M=3.40, SD=1.11) (F (2,245)= 25.311, p<.001)., (M=3.96, SD=.72), (M=3.71, SD=1.06), (M=4.09, SD=1.15) (F (2,245)= 2.223, p>.05)., (M= 4.00, SD=.68), (M=4.27, SD=.90) (M=4.59, SD=.89) ( ) (F (2,245) = 12.672, p<.001)., Gilovich(1983), Griffth(1990)., post-hoc M SD F ῃ 2 (Duncan test) ( ) (N=146) 2.15 1.72 - ( ) (N=41) 1.79 1.97 22.519*.155 1,2>3 ( ) (N=61).43 1.39 (N=248) 1.66 1.83 * p<.001, *p<.05 1: 2: 3: ) - =( - ),.
post-hoc M SD F ῃ 2 (Duncan) ( ) (N=146) 4.44.91 ( ) (N=41) 4.37.98 ( ) (N=61) 3.40 1.11 25.311*.171 1,2>3 (N=248) 4.17 1.07 ( ) (N=146) 3.96.72 ( ) (N=41) 3.71 1.06 ( ) ( ) (N=61) 4.09 1.15 2.223.018 - (N=248) 3.95.91 ( ) (N=146) 4.00.68 ( ) (N=41) 4.27.90 ( ) ( ) (N=61) 4.59.89 12.672*.094 1,2<3 (N=248) 4.19.81 * p<.001 1: 2: 3: ) ( ).,,. 4-1, 4-2, 4-3. 1 4,.,..,. ( ) ( ) ( 10). 10 ( ). (r=.344, p<.01), (r=.414, p<.01). (r=.415, p<.01) (r=.337, p<.01).
1 2 3 4 5 6 7 8 (1).162.087.190*.073.035.103 -.012 (2).135 -.020.304* -.055 -.123.214* -.095 (3).344**.200 -.193*.221**.182* -.107 -.032 (4).087.414**.420** -.036 -.270**.202* -.252** (5).170.415**.255*.153.252* -.079.084 (6).147.337**.405**.178.693** -.193* -.051 (7) -.073 -.195 -.090.042 -.271* -.361** -.035 (8).048 -.173 -.081 -.201.049 -.188 -.162 ** p<.01, * p<.05 ) : (N=61), : (N=146) (+) (r=.420, p<.01).., ( ) (-) (r= -.193, p<.05), (r=.190, p<.05), (r=.304, p<.05), (r=.214, p<.05) (+).,,., (r=.202, p<.05), (r=-.252, p<.01) (-).,,,. 11 B,,,, (-), (-), (-), 87.5%. 67.3%(167/248 ), 20.2%. Exp(B) 1 Exp(B)., Exp(B) (4.105), (3.966), (2.160),
B SE Wald df p Exp (B) ( ).770.180 18.387 1.000 2.160 ( ) -.585.238 6.041 1.014.557 ( ) 1.412.285 24.467 1.000 4.105 ( ) -.635.195 10.643 1.001.530 ( ).522.178 8.567 1.003 1.686 1.378.481 8.218 1.004 3.966 -.486.206 5.575 1.018.615-5.304 1.976 7.209 1.007.005 Nagelkerke R 2.602 (%) 87.5 (1.686), (.615), (.557), (.530).,,,. ( )..,,., (, 2002),,. 81 167, ( ), ( ), ( )..
, 2. ( ), ( ), ( ).,., (p>.05),. (M=4.61/7 ) (M= 2.71/7 ).,,..,,. (illusion of control),.,,.,, (2014).,., (chance),.,.,.,., ( ) ( ) ( ), ( ). 80% Moore Ohtsuka(1997).,,
(Ladouceur & Dube, 1997)., /,,.,..,,.,., ( ),., ( )., Griffiths(1990) ( ), ( ),.., (4 ), (M=4.61). (illusion of control) (Langer & Roth, 1975; Thompson, Armstrong & Thomas, 1998),. Bergen, Newby-Clark Brown(2014),.,.,,,,,.,,,,,..,
,., ( / ),.,,, ( ),.,,..,.,.,. 2014 8.9%, 2.0% 4 (2014 ),.,,.,.,,.,, 3,.,,.,.
,, (2006).. (2), 225-241. (2003). K-NODS. (3), 487-509. (2006). :. (2), 243-274. (2010).., 418-419., (2003).. (2), 261-277.,, (2004).. (2), 285-320.,,, (2011). CPGI, (4), 1011-1038.,, (2011).. (1), 135-163. (2007).. (2003). :. (2), 35-56., (2014). 2014. (2009).. (2006).,..,, (2013).. (3), 751-759. (2009). (CPGI). (3), 667-675.,, (2003). :. (1), 169-189.,,,, (2008). :. (2006). (GABS). (1), 2891-2898. (2005). (GABS). (4), 531-546.,, (2014).,?. (2), 155-176. (2002).. (2003)..
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Differences in attributional bias and irrational gambling beliefs between gamblers and non-gamblers Eun-A Park Jonghan Yi Daegu University The aims of this study were 1) to compare irrational gambling beliefs of gamblers and non-gamblers, 2) to investigate the role of cognitive error on winning probability thinking error, and 3) to examine the relationship between attributional bias and gambling behavior. A total of 248 subjects were recruited for this study. All subjects were classified into non-gamblers, social gamblers and pathological gamblers, and administered self-report questionnaires to measure irrational gambling beliefs, the probability inference error, the attriburional style, and the attributional bias. A pathological gambler group scored highest on irrational gambling beliefs, especially the overestimation of self-ability factor, and a social gambler group and a non-gambler group follow. All three groups scored higher on the magnification of gambling skills than the mean (4.0) of the scale. Pathological gamblers and social gamblers scored higher on the probability thinking error than non-gamblers. Pathological gamblers displayed higher external attribution, lower internal attribution in their daily life events and higher internal attribution in failure situation than social gamblers and non-gamblers. The results indicate that cognitive errors would be a factor that differentiates pathological gamblers from social gamblers and non-gamblers. In predicting gambling behaviors, overestimation of self-ability of irrational gambling beliefs, internal attribution in failure situation, external attribution in daily live event, and probability thinking error were identified as significant factors. It is concluded that a public education about common cognitive bias featured in gamblers might be important in prevention of pathological gambling behaviors. Key words : attributional bias, irrational gambling beliefs, probability thinking error, gambling addiction