Person. in&id. DI# Vol. 5. No. 6. pp. 615-632. 1984 Printed in Great Britain. All rights reserved OIVI-8869/84 $3.00 + 0.00 Copyright Q 1984 Pergamon Press Ltd THE ASSESSMENT OF PERSONALITY FACTORS ACROSS 25 COUNTRIES PAUL BARRETT and SYBIL EYSENCK Institute of Psychiatry, Department of Psychology, De Crespigny Park, Denmark Hill, London SE5 8AF, England (Received 18 April 1984) Sununary-The means for each scale score from the Eysenck Personality Questionnaire were compared individually and conjointly across 25 countries. Comparisons were carried out using coded difference scores, Pearson correlations, Euclidean distances, cluster analyses and non-metric multidimensional scaling. It was possible to compare the personality (as defined by the scale scores on E, N, P and L) of each country with all other countries, culminating in a one-dimensional non-metric scale of distances for both the male and female data from each country. The assumptions underlying the rationale of the measures used and the comparisons undertaken are briefly discussed. INTRODUCTION The Eysenck Personality Questionnaire (EPQ), introduced by Eysenck and Eysenck (1975) measures four trait dimensions of personality-Extraversion (E), Neuroticism (N), Psychoticism (P) and Social Desirability (L). The construction and validation of this questionnaire was initially undertaken in the U.K. When other countries wished to use this questionnaire, it became pertinent to ask whether it would be valid for them to do so without a fresh standardization. Would the same factors of P, E, N and L necessarily be replicated everywhere? Could appropriate items be found so that reliable scales would ensue? Many questionnaires are simply imported into other countries and confidently used, scoring as in the country where they were standardized, without questioning the possible inappropriateness of some of the items. As far as the EPQ was concerned, Eysenck and Eysenck (1982) began a series of cross-cultural studies designed to investigate the appropriateness of the factors of P, E, N and L of the EPQ in other cultures. This was done by first obtaining as good a translation of the questionnaire as possible, usually obtaining a back-translation which is invaluable in showing up any discrepancies of meaning. Next, samples of roughly 500 men and 500 women of different ages were asked to complete the EPQ anonymously. The forms were then coded and factor analyses for each of the sexes separately were performed. (Product-moment correlations beween the items were factor analysed by principal components, rotated by Varimax and then by Promax, using the first four factors in rotation.) The whole approach to these cross-cultural studies has been set out in detail by Eysenck (1983), so it will suffice here to outline the steps briefly. The first aim was to show that the EPQ factors emerged in other cultures as in England, and this was done by the method of factor comparisons (Kaiser, Hunka and Bianchini, 1971). Arbitrarily it was agreed by Eysenck and Eysenck (1982) that 0.95 or above indicated similarity and 0.98 indicated essential indentity of factors between populations, although a fair degree of similarity is obvious with values over 0.90. The next aim was to provide valid scoring keys in different countries, where factor similarity was high but occasionally certain items were found inappropriate and had to be substituted or just omitted in order to achieve reliable scales. The method adopted here was to scrutinize the factor loadings, hoping that the British scoring key would be equally valid elsewhere, but improving on this, when certain items showed weak loadings, by introducing better loading items or dropping them until reasonable reliabilities were found. When reliable scoring keys were recommended for use, the final task was to compute comparisons of British and foreign means of the scales, using only those items both scoring keys had in common. After over 20 countries had co-operated in cross-cultural projects on the EPQ, it seemed desirable, and of considerable interest, to compare personality norms, not only of each country with British norms, but to make direct comparisons between all the countries. To this end, Table 615
Transcript
Person. in&id. DI# Vol. 5. No. 6. pp. 615-632. 1984 Printed in Great Britain. All rights reserved
THE ASSESSMENT OF PERSONALITY FACTORS ACROSS 25 COUNTRIES
PAUL BARRETT and SYBIL EYSENCK Institute of Psychiatry, Department of Psychology, De Crespigny Park, Denmark Hill,
London SE5 8AF, England
(Received 18 April 1984)
Sununary-The means for each scale score from the Eysenck Personality Questionnaire were compared individually and conjointly across 25 countries. Comparisons were carried out using coded difference scores, Pearson correlations, Euclidean distances, cluster analyses and non-metric multidimensional scaling. It was possible to compare the personality (as defined by the scale scores on E, N, P and L) of each country with all other countries, culminating in a one-dimensional non-metric scale of distances for both the male and female data from each country. The assumptions underlying the rationale of the measures used and the comparisons undertaken are briefly discussed.
INTRODUCTION
The Eysenck Personality Questionnaire (EPQ), introduced by Eysenck and Eysenck (1975) measures four trait dimensions of personality-Extraversion (E), Neuroticism (N), Psychoticism (P) and Social Desirability (L). The construction and validation of this questionnaire was initially undertaken in the U.K. When other countries wished to use this questionnaire, it became pertinent to ask whether it would be valid for them to do so without a fresh standardization. Would the same factors of P, E, N and L necessarily be replicated everywhere? Could appropriate items be found so that reliable scales would ensue? Many questionnaires are simply imported into other countries and confidently used, scoring as in the country where they were standardized, without questioning the possible inappropriateness of some of the items.
As far as the EPQ was concerned, Eysenck and Eysenck (1982) began a series of cross-cultural studies designed to investigate the appropriateness of the factors of P, E, N and L of the EPQ in other cultures. This was done by first obtaining as good a translation of the questionnaire as possible, usually obtaining a back-translation which is invaluable in showing up any discrepancies of meaning. Next, samples of roughly 500 men and 500 women of different ages were asked to complete the EPQ anonymously. The forms were then coded and factor analyses for each of the sexes separately were performed. (Product-moment correlations beween the items were factor analysed by principal components, rotated by Varimax and then by Promax, using the first four factors in rotation.)
The whole approach to these cross-cultural studies has been set out in detail by Eysenck (1983), so it will suffice here to outline the steps briefly. The first aim was to show that the EPQ factors emerged in other cultures as in England, and this was done by the method of factor comparisons (Kaiser, Hunka and Bianchini, 1971). Arbitrarily it was agreed by Eysenck and Eysenck (1982) that 0.95 or above indicated similarity and 0.98 indicated essential indentity of factors between populations, although a fair degree of similarity is obvious with values over 0.90.
The next aim was to provide valid scoring keys in different countries, where factor similarity was high but occasionally certain items were found inappropriate and had to be substituted or just omitted in order to achieve reliable scales. The method adopted here was to scrutinize the factor loadings, hoping that the British scoring key would be equally valid elsewhere, but improving on this, when certain items showed weak loadings, by introducing better loading items or dropping them until reasonable reliabilities were found. When reliable scoring keys were recommended for use, the final task was to compute comparisons of British and foreign means of the scales, using only those items both scoring keys had in common.
After over 20 countries had co-operated in cross-cultural projects on the EPQ, it seemed
desirable, and of considerable interest, to compare personality norms, not only of each country with British norms, but to make direct comparisons between all the countries. To this end, Table
615
616 PAUL BAKKETT and SYOIL EYSENCK
1 lists all the a-coefficients of reliability for the adult EPQ in the various countries which have been studied to date. (These are in alphabetical order for convenience.) Since the scoring keys sometimes contained scales of slightly different length, transformed means are given in Table 2, where each scale mean is presented as though it were derived from a 30-item scale. Finally, a method was adopted for comparison of means on the personality factors and details of this follow in the next
section. Appendix A provides a specific bibliography for each country’s data analysis. Where any
particular analysis has not yet been published, the name and address of the principal author has been provided.
METHODOLOGY
The complete methodology for the factoring, identification and scale construction of the personality factors within each country, is provided in Eysenck and Eysenck (1982) and Eysenck (1983). In brief, the male and female data from each country were submitted to a principal- components factor analysis, four factors being extracted and rotated to simple structure using the Promax (Hendrickson and White, 1964) algorithm. Factor identification was carried out using the configurational matching algorithm of Kaiser et al. (1971), with the U.K. being the universal reference country. Scale formation was subsequently implemented culminating in the assessment of the a-internal consistency for each scale.
From these analyses, it was concluded that the data from 25 countries (including those from the U.K.) were essentially measuring the same four factors of E, N, P and L, which enabled the further analyses described below to be implemented.
Initially, in order to compare each country’s mean scale scores to every other country’s data, a transformation of means was effected. This was specifically required to overcome the fact that each country’s scales were composed of a different number of items, this difference spanning the range from 0 to 6 items. Thus each mean was based on a different total number of items in each scale. The transformation that allowed all countries to be assigned means based on equal numbers of items was:
where M, = the transformed mean, M0 = the untransformed mean,
and
M, = @4,/N) x 30, (1)
N = the number of items in the scale which has mean M,,. This provided scale mean values computed as if they were taken from a 30-item scale. The assumption implicit within this transformation is that the patterning of responses for each S would have remained the same on a scale with an increased number of items. Thus an increase in the mean scale score would be directly proportional to the mean score based on the actual number of items assessed.
Having established the comparability of each country’s scale means, each scale mean for E, N, P and L was compared to every other same scale mean for all countries. This was implemented on both the male and female data. For example, the E-scale male means for all countries were compared using the following procedure.
1. Take one country’s scale mean and subtract all other country scale means from
it. 2. Encode these differences (for convenience) into an integer difference scale ranging
from -5 to +5. 3. Perform steps 1 and 2 above for every country in turn. 4. Place all the difference values into a matrix where the rows define the country from
which all the other country means are subtracted. The columns contain the difference values observed for each comparison country.
Assessment of personality factors across 25 countries 617
In this way, eight tables were generated containing the difference values for the four personality factors and both sexes.
In order to compare countries in terms of their personality defined as a pattern of scale means for E, N, P and L, two matrices (one for each sex) were composed containing Euclidean distances computed between every country’s four scale means. That is, a measure was computed that indicated the overall disparity of one country’s set of scale scores from any other country. If all scale scores between two countries were the same, the distance measure would be 0. If, however, only one of the scale scores were different, the distance measure would correspondingly indicate the disparity. Of course, the measure cannot indicate which of the scale means is disparate; this can be achieved by direct observation of the scale means themselves.
Euclidean distance is a general property of Euclidean geometry (see Sommerville (1958) for an exposition of the basic axioms). It can be shown that, given the specific axioms of the geometry, the shortest distance between two points in space is a straight line. This can be formally proven from the theorem of Pythagoras and the distance measure computed using the formula
I ,A’
where
D, = Euclidean distance, X, = the value for scale mean i on country j
and X, = the value for scale mean i on country k.
The choice of this measure makes no assumptions as to the underlying distributions of the scale means or their measurement properties.
Given the Euclidean distance matrices, it was possible to further compute the degree of association between each country’s male and female distance arrays. That is, in order to comment upon the similarity of male and female personality within any one country, the array (row) of distances for both sexes was compared using the Pearson correlation coefficient. Thus, if both the males and females from one country had similar distance measures from all the other countries, then the correlation coefficient would be high. If, however, the males had a completely different distance pattern in comparison with the females, the coefficient would be low. Of course, three sources of disparity may affect this coefficient. Either the males and females have completely different scale scores, or the patterning of male distances could be different from that for the female distances, or both. Inspection of scale means can isolate the first problem, inspection of the Euclidean distance tables can help with both the second and third problems.
Finally, as an aid to simple identification of country similarity defined by the four scores on E, N, P and L, a non-metric multidimensional scaling solution was computed using the Guttman-Lingoes smallest space analysis algorithm (Lingoes, 1973). In addition a k-means metric cluster analysis was undertaken using the BMDP software package program PKM (Dixon, Brown, Engelman, Frane. Hill, Jennrich and Toporek, 1983).
RESULTS
Table 1 presents the cr-coefficients for each sex on each scale across countries. As is usual, the P scale generally has a lower cc than E, N or L.
Table 2 presents the transformed scale means for cross-cultural comparisons. Each mean is for a scale of 30 items in length, thus the figures are directly comparable to one another. The minimum number of actual items in any one scale is 16, the maximum number is 26. In addition, the number of Ss who provided the data within each country is included.
Tables 3-10 present the difference matrices for each scale. These matrices, as described in the Methodology section, provide a coded difference measure that allows simple and direct comparison between any one country’s mean scale score and all other countries’ mean scores. By comparing each row to the columns, a positive or negative code (- 5 to + 5) will indicate a particular country (row) mean scale score bigger or smaller than that for any ‘column’ country. The names for each
618 PAUL BARRETT and SYBIL EYSENCK
Table 1. Coeficxnt 0~ consistency/homogeneity values for each adult EPQ scale
country are abbreviated within these tables; the order of the countries is, however, the same as in Tables 1 and 2 where the full country name is given. For example, looking at Table 3, Australia’s E-scale mean is negligibly different from Bangladesh, Brazil and Bulgaria, but is much greater than China’s mean scale score. It is, however, much lower than Nigeria’s mean scale score.
Table 11 provides the Euclidean distance matrices for the male and female samples. These symmetric tables provide a simple way of comparing each country’s ‘total’ personality with every other country’s personality. Thus it is possible to see how different any one country is from another in terms of its combined P, E, N and L scores. For example, the males most similar to the French males are those from Hungary. For the U.K., the Nigerian males are the most dissimilar. By referring back to Table 2, the actual mean scores can be used to provide the specific reasons for such overall similarity or dissimilarity.
Table 2. Transformed scale means for cross-cultural comoarisons
Assessment of personality factors across 25 countries 623
AU
S B
ND
B
RA
B
UL
C
HI
EG
Y
FRA
G
ER
G
RC
H
-K
AU
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ND
B
RA
B
UL
C
HI
EG
Y
FRA
G
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Tab
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8. C
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di
lTer
ence
m
atri
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r fe
mal
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to
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t1.0
f4
.0
t2.0
-1
.0
t2.0
to
.0
t3.0
to
.0
+o.
o t1
.0
+3.
0 +
o.o
-2.0
to
.0
-20
t-20
-1
I-
J -I
ll co
n
Not
es
as
give
n m
T
able
3
Assessment of personality factors across 25 countries 625
Tab
le
10.
Cod
ed d
iffe
renc
e m
atri
x fo
r fe
mal
es-L
sc
ale
(Soc
ial
Des
irab
ility
)
AU
S B
ND
B
RA
B
UL
C
HI
EG
Y
FRA
G
ER
G
RC
H
-K
HU
N
ICE
IN
D
IRN
IS
R
JAP
NIG
FT
R
SIC
SG
P S
PN
SR
L
UG
A
U.K
. Y
UG
A
US
+O
.O
-5.0
-5
.0
-5n
-5n
-5n
-3.0
-2
.0
-5.0
-4
.0
-5.0
-2
.0
-5.0
-5
.0
-5.0
-2
.0
-5.0
-5
.0
-5.0
-5
.0
-5.0
-5
.0
+1.
0 -3
.0
-5.0
_.
_ .._
__
_ +
2.0
-1.0
-2
.0
+4.
o +
5.0
+2.
0 +
3.0
+2.
0 +
5.0
+o.
o +
2.0
f2.0
+
5.o
+2.
0 +
1.o
+2.
o +
2.o
+2.
o -2
.0
+5.
o +
4.o
+,.o
+
1.0
-2.0
-3
.0
+3.
0 +
4.0
+1.
0 +
2.0
+2.
0 f4
.0
i-o.
0 +
1.0
+o.
o +
5.o
+1.
0 +
o.o
+1.
o f1
.O
+2.
o -3
.0
+5.
o +
3.o
+o,
o B
ND
+
5.0
fO.0
+
I.0
B
RA
+
5.0
-1.0
+
o.o
BU
L
+5.
0 -2
.0
-1.0
C
HI
+5.
0 +
l.O
f2.0
E
GY
+
5.0
+2.
0 +
3.0
FRA
f3
.0
-4.0
-3
.0
GE
R
+2.
0 -5
.0
-4.0
G
RC
i5
.0
-2.0
-1
.0
H-K
f4
.0
-3.0
-2
.0
HU
N
+5.
0 -2
.0
-2.0
IC
E
+2.
0 -5
.0
-4.0
IN
D
+5.
0 +
O.O
+
O.O
IR
N
f5.0
-2
.0
- 1.
0 IS
R
+5.
0 -2
.0
+o.
o JA
P f2
.0
-5.0
-5
.0
NIG
+
5.0
-2.0
-1
.0
PT
R
f5.0
-1
.0
+o.
o SI
C
f5.0
-2
.0
-1.0
SG
P t5
.0
-2.0
-1
.0
SP
N
+5.
0 -2
.0
2.0
SRL
f5
.0
f2.0
+
3.0
UG
A
-1.0
-5
.0
-5.0
U
.K.
+3.
0 -4
.0
-3.0
Y
UG
+
5.0
-5.0
+
o.o
Not
es
as
give
n in
T
able
3.
+o.
o -3
.0
-4.0
+
2.0
1-3.
0 +
o.o
+ I
.0
+o.
o +
3.0
-2.0
+
o.o
- I.
0 +
4.0
+o.
o -2
.0
+o.
o +
o.o
+o.
o -4
.0
f5.0
+
2.0
-2.0
+
3.0
fO.0
-1
.0
f5.0
+
5.0
+3.
0 +
4.0
+3.
0 +
5.o
+2.
0 +
3.0
+2.
0 +
5.0
+3.
0 f2
.0
+3.
0 +
3.0
f3.0
-1
.0
+5.
0 +
5.0
+2.
0 ?
+4.
0 fl
.0
fO.0
+
5.0
+5.
0 +
3.0
+4.
0 +
4.0
+5.
0 f2
.0
+3.
0 +
3.0
+5.
0 +
3.0
+3.
0 +
3.0
+3.
0 +
4.0
+o.
o +
5.0
+5.
0 +
2.0
-2.0
-
5.0
-5.0
+
o.o
+1.
0 -3
.0
-1.0
-2
.0
+2.
0 -3
.0
-2.0
-3
.0
+2.
0 -2
.0
-3.0
-2
.0
-2.0
-2
.0
-5.0
+
4.0
+o.
o -3
.0
5
-3.0
-5
.0
-5.0
-1
.0
fO.0
-3
.0
-2.0
-3
.0
fO.0
-4
.0
-3.0
-4
.0
+1.
0 -3
.0
-4.0
-3
.0
-3.0
-3
.0
-5.0
f3
.0
-1.0
-4
.0
r
fO.0
-3
.0
-3.0
+
3.0
+3.
0 +
o.o
+2.
0 +
1.0
+4.
0 -1
.0
+o.
o +
o.o
f4.0
+
o.o
-1.0
+
o.o
+o.
o fl
.0
-3.0
+
5.0
+2.
0 -1
.0
- 1.
0 -4
.0
-4.0
+
I.0
f2.0
-2
.0
+o.
o -1
.0
+3.
0 -2
.0
-1.0
-2
.0
+3.
0 -1
.0
-2.0
-1
.0
-1.0
+
o.o
-4.0
+
5.0
+1.
0 -2
.0
E
+o.
o -3
.0
-4.0
+
2.0
+3.
0 -1
.0
f1.0
fO
.0
+3.
0 -2
.0
+o.
o -1
.0
+3.
0 +
o.o
-2.0
fO
.0
+o.
o +
o.o
-4.0
+
5.0
+2.
0 -2
.0
?
-3.0
-5
.0
-5.0
-2
.0
+o.
o -4
.0
-3.0
-3
.0
+o.
o -4
.0
-4.0
-4
.0
fO.0
-3
.0
-4.0
-3
.0
-3.0
-3
.0
-5.0
+
3.o
-2.0
-4
.0
+ 2
.0
- 2.
0 -2
.0
+3.
0 +
4.0
+1.
0 +
2.0
+2.
0 +
4.0
fO.0
+
1.0
+1.
0 +
5.0
+2.
0 fO
.0
+2.
0 +
2.0
+2.
0 -2
.0
+5.
0 f3
.0
+o.
o ;
+o.
o -
3.0
-3.0
+
2.0
+3.
0 fO
.0
+1.
0 fO
.0
+4.
0 -
I.0
+o.
o +
o.o
+4.
0 +
o.o
- 1.
0 fO
.0
+o.
o +
1.0
-3.0
+
5.0
+2.
0 -
I.0
? +
1.0
-
2.0
-3.0
+
3.0
+4.
0 +
o.o
+2.
0 +
1.0
1-4.
0 -1
.0
fO.0
+
o.o
f4.0
+
o.o
fO.0
+
1.0
+o.
o +
1.0
-3.0
+
5.0
+3.
0 -1
.0
r?
r -4
.0
-5.0
-
5.0
-2.0
-1
.0
-4.0
-3
.0
-3.0
+
o.o
-5.0
-4
.0
-4.0
+
o.o
-4.0
-5
0 -4
.0
-4.0
-
3.0
-5.0
+
3.0
-2.0
-5
.0
+o.
o -3
.0
-3.0
f2
.0
f3.0
+
o.o
+1.
0 +
o.o
+3.
0 -2
.0
+o.
o +
o.o
+4.
0 +
o.o
-1.0
fO
.0
+o.
o fO
.0
-3.0
+
5.0
+2.
0 -1
.0
[:
+ 2
.0
- 2.
0 -3
.0
+3.
0 +
4.0
+ I
.0
+2.
0 +
2.0
f4.0
+
o.o
fl.0
+
o.o
+5.
0 +
1.0
+
o.o
+ I
.0
+ 1
.0
+2.
0 -3
.0
f5.0
f3
.0
+o.
o k?
+
o.o
-3.0
-3
.0
+2.
0 +
3.0
+o.
o +
1.0
+
o.o
+3.
0 -2
.0
fO.0
-1
.0
+4.
0 +
o.o
-1.0
+
o.o
+o.
o +
o.o
-3.0
+
5.0
+2.
0 -2
.0
5 +
o.o
-3.0
-3
.0
+2.
0 +
30
+o.
o +
1.0
+o.
o +
3.0
-2.0
fO
.0
+o.
o +
40
+o.
o -1
.0
+o.
o +
o.o
+1.
0 -3
.0
+5.
o +
2.o
-1.0
x
fO.0
-3
.0
-4.0
+
2n
f3.0
-1
.0
+o.
o +
o.n
f3.0
-2
.0
- I.
0 -1
.0
f3.0
+
o.o
-2.0
fO
.0
- 1.
0 fO
.0
-4.0
+
5.0
+2.
0 -2
.0
+4.
0 +
I.0
+o.
o +
5.0
+s.
o +
3 0
+4.
0 f4
0 +
s.o
+in
+3.
o +
3.0
f5
.0
f3.n
+
3.0
+3.
n +
3.o
+4.
0 f0
.n
+5.
0 +
5.0
f2.0
-
5.0
- 5.
0 -5
.0
-4.0
-3
.0
-5.0
-5
.0
-5.0
-3
.0
-5.0
-5
.0
-5.0
-3
.0
-5.0
-5
.0
-5.0
-5
.0
-5.0
-5
.0
+o.
o -4
.0
-5.0
-2
0 -
5.n
-5.0
to
.0
+I.
0 -
2.0
- I.
0 -2
.0
+2.
0 -3
.0
-2.0
-3
.0
+2.
0 -2
.0
-3.0
-2
.0
-2.0
-2
.0
-5.0
+
4.o
+o.
o -3
.0
+ 2
.0
-2.0
-2
.0
+3.
0 +
4.0
fl.0
+
2.0
+2.
0 +
4.0
+o.
o fl
.0
fl.0
+
5.0
fl.0
+
o.o
+2.
0 +
1.0
f2.O
-2
.0
+5.
o f3
.O
+o.
o
Tabl
e 1 I
. M
ale
and
fem
ale
Euc
lidea
n di
stan
ce
mat
rice
s co
mm
uted
on
the
four
EPO
sc
ale
scor
es
AU
S B
ND
BR
A
BUL
CH
I EG
Y
FRA
G
ER
GR
C
H-K
H
UN
IC
E IN
D
IRN
IS
R
JAP
NIG
PT
R
SIC
SG
P SP
N
SRL
UG
A
U.K
. Y
UG
AU
S B
ND
BR
A
BUL
CH
I EG
Y
FRA
G
ER
GR
C
H-K
H
UN
0.
0 12
.2
10.8
7.
7 12
.9
13.4
9.
7 4.
1 9.
4 6.
4 8.
9 12
.2
0.0
2.8
4.8
6.2
4.7
3.3
8.5
6.1
7.0
4.0
10.8
2.
8 0.
0 4.
0 5.
2 3.
7 2.
3 7.
6 4.
8 5.
5 2.
7 7.
7 4.
8 4.
0 0.
0 8.
0 7.
3 2.
9 4.
1 5.
3 4.
3 2.
1 12
.9
6.2
5.2
8.0
0.0
5.8
5.4
10.1
8.
3 6.
6 6.
2 13
.4
4.7
3.7
7.3
5.8
0.0
5.8
10.7
5.
0 7.
9 6.
3 9.
7 3.
3 2.
3 2.
9 5.
4 5.
8 0.
0 6.
0 5.
9 4.
5 I.1
4.
1 8.
5 1.
6 4.
1 10
.1
10.7
6.
0 0.
0 7.
5 4.
1 5.
3 9.
4 6.
1 4.
8 5.
3 8.
3 5.
0 5.
9 7.
5 0.
0 5.
6 5.
8 6.
4 7.
0 5.
5 4.
3 6.
6 7.
9 4.
5 4.
I 5.
6 0.
0 4.
2 8.
9 4.
0 2.
7 2.
1 6.
2 6.
3 I.1
5.
3 5.
8 4.
2 0.
0 5.
3 8.
6 7.
6 3.
8 11
.1
10.8
6.
3 2.
7 7.
7 5.
9 5.
4 Il
.2
6.2
6.4
7.0
8.9
6.2
7.2
9.0
3.8
7.1
7.5
10.1
4.
9 3.
8 4.
6 4.
3 6.
9 2.
2 6.
7 7.
5 4.
6 2.
7 14
.1
6.3
8.6
7.8
12.0
10
.6
8.1
10.3
10
.3
Il.0
8.3
4.5
II.0
9.
0 6.
6 II
.1
11.6
8.
1 4.
8 8.
7 5.
9 7.
2 15
.4
6.7
9.1
9.0
12.7
10
.2
9.2
II.9
10
.2
12.0
9.
5 9.
2 4.
0 3.
8 2.
9 8.
2 5.
8 4.
1 6.
1 3.
4 5.
4 3.
9 9.
2 5.
1 2.
6 4.
3 5.
3 4.
4 3.
5 6.
7 3.
6 3.
8 3.
5 9.
7 2.
9 2.
8 2.
3 6.
5 6.
3 1.
3 5.
9 6.
0 5.
1 1.
6 10
.0
4.7
2.4
3.6
6.6
5.1
3.1
7.0
5.2
5.7
2.7
12.5
1.
0 2.
9 5.
4 5.
8 4.
2 3.
7 9.
0 6.
0 7.
0 4.
5 7.
0 5.
8 4.
5 2.
6 8.
3 6.
8 4.
4 4.
4 3.
2 3.
7 3.
8 5.
5 7.
x 6.
6 3.
1 9.
8 IO
.0
5.2
2.3
74
4.x
4.2
9.Y
4.
4 3.
6 4.
‘)
4.0
5.4
3.3
6.Y
5.
3 3.
6 3.
‘)
ICEI
ND
5.
3 11
.2
8.6
6.2
7.6
6.4
3.8
7.0
11.1
8.
9 10
.8
6.2
6.3
7.2
2.7
9.0
7.1
3.8
5.9
7.1
5.4
7.5
0.0
9.8
9.8
0.0
7.4
8.7
IO.0
9.
1 4.
7 Il
.6
II.5
8.
6 6.
0 4.
4 7.
2 6.
0 5.
9 7.
0 6.
4 7.
9 9.
2 5.
8 4.
6 5.
5 1.
6 9.
5 8.
1 5.
7
FtT
?ld
C
AU
S I)
ND
Ill
</\
BUL
CH
I EG
Y
FRA
G
ER
GR
C
H-K
H
UN
IC
E IN
D
IRN
IS
R
JAP
NIG
PT
R
SIC
SG
P SP
N
SRL
UG
A
U.K
. Y
UG
AU
S B
ND
BR
A
BUL
CH
I EG
Y
FRA
G
ER
GR
C
H-K
H
UN
0.
0 12
.6
Il.2
9.
1 15
.2
15.1
5.
9 4.
3 10
.2
8.3
9.7
12.6
I)
0 35
55
A
.5
h.4
x5
x7
76
0.O
ft
.0
Il.2
1.
5 0
0 2
h s
0 .(I
6.
2 74
5
I 4.
2 2.
‘)
YI
5.5
2.6
0.0
7.7
6.2
4.1
5.x
3.3
4.0
2.7
15.2
6.
5 5.
6 7.
7 0.
0 6.
6 10
.0
I I.1
9.
2 6.
9 6.
6 IS
.1
6.4
5.1
6.2
6.6
0.0
9.6
11.7
5.
7 8.
7 7.
3 5.
9 8.
5 6.
2 4.
1 10
.0
9.6
0.0
3.5
4.9
4.1
5.0
4.3
8.7
7.4
5.8
II.1
Il
.7
3.5
0.0
7.8
4.2
6. I
10.2
7.
6 5.
I 3.
3 9.
2 5.
7 4.
Y
7.x
0.0
6.5
5.6
8.3
6.0
4.2
4.0
6.9
8.7
4. I
4.2
6.5
0.0
3.3
9.7
6.0
2.9
2.7
6.6
7.3
5.0
6.1
5.6
3.3
0.0
4.5
9.1
7.7
6.0
12.4
12
.1
4.9
3.1
8.1
6.0
6.4
12.0
7.
4 7.
3 6.
7 10
.3
6.9
7.6
9.5
5.2
8.3
9.0
10.8
5.
0 3.
1 4.
5 4.
9 7.
7 6.
5 6.
7 7.
3 2.
9 2.
1 12
.0
5.0
7.6
8.3
Il.3
10
.0
10.1
9.
0 10
.3
8.5
9.2
4.3
10.7
8.
4 6.
4 12
.0
12.4
3.
6 3.
5 7.
9 5.
7 6.
2 11
.4
6.6
8.7
8.8
12.9
I I
.3
10.1
9.
1 10
.2
9.4
10.2
11
.0
3.2
3.7
4.1
8.6
6.2
7.0
7.6
5.5
6.1
5.9
9.7
7.0
4.1
2.8
7.0
6.3
3.8
6.5
3.2
4.0
3.7
10.0
4.
0 2.
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628 PAUL BARRETT and SYBIL EYSENCK
Table 12 Pearson correlations between the male and female Euclidean dtstances for each countrv
The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between The correlation between
Males and females = +0.8327 Males and females = +0.7057 Males and females = to.7012 Males and females = +0.5976 Males and females = f0.8250 Males and females = to.771 I Males and females = +0.2013 Males and females = +0.8715 Males and females = to.5679 Males and females = f0.6650 Males and females = +0.7549 Males and females = to.8861 Males and females = +0.6308 Males and females = +0 7842 Males and females = +0.8025 Males and females = +0.9003 Males and females = f0.7625 Males and females = +0.3775 Males and females = +0.7189 Males and females = f0.6626 Males and females = +0.7216 Males and females = +0.7313 Males and females = +0.2703 Males and females = +0.8323 Males and females = +0.7175
These correlations do not include the same country distance of (0.0) m their computations
Table 12 provides the Pearson correlation coefficients between the male and female Euclidean distance measures for each country in turn. That is, for each country the male Euclidean distances of a country (compared to all 24 other countries) are correlated with the corresponding female distances. This provides a measure of how similar the males and females of any one country are to one another in terms of their respective pattern of distances from the other countries. Notably it is the French and the Ugandan males and females who differ most from one another in this manner.
Finally, Fig. 1 presents a one-dimensional non-metric smallest space analysis of both the male and female data from Table 11. For the male solution the Guttman-Lingoes coefficient of alienation was 0.209, for the female solution it was 0.237; both coefficients indicating greater than 94% of the Euclidean distances being accounted for by the one-dimensional model. The countries are arrayed on an arbitrary scale ranging from - 100 to + 100.
Each country can now be viewed in terms ‘of its distance from any other country based upon the combined scores on P, E, N and L. Thus for the male sample data, Australia and China are the most dissimilar. For the female data, China and Uganda are the most dissimilar, Australia and Uganda being more similar to one another than any other country.
As indicated in the Methodology section, a comprehensive series of cluster analyses was undertaken. However, although several solutions could have been accepted based upon 2, 3, 4, 5, 6 or 7 clusters, the lack of any criterion upon which to decide the optimal solution led the authors to discard these results. No cluster solutions were forthcoming that could be explained by any coherent rationale or theory, i.e. clusters could not be identified as determining geographical location, temperature regions, race similarity, politics or hemisphere. Hence the one-dimensional smallest space dimension appeared to be the optimal solution providing an easily interpretable visual characterization of country personality similarity. In addition, the advantage of dropping any metric constraints upon the data was also a bonus.
DISCUSSION
While the results above are clear-cut and straightforward in their interpretation, there are nevertheless three assumptions underlying the whole exercise.
Firstly, it is assumed that P, E, N and L are reliable, valid and replicable measurement constructs that are psychologically useful. Evidence from innumerable sources indicates this is so. [See Kline and Barrett (1983) and Eysenck and Eysenck (1982) for a comprehensive review of this evidence.] Gray (1981) has cast doubt upon the validity of E and N by specifying alternative rotational positions for the factor axes, redefining the dimensions as Impulsivity and Anxiety. Given the lack of any empirical evidence for this, in addition to the implicit negation of the empirical evidence of the efficacy of the simple structure criterion in determining the unique and ‘true’ spatial configuration of any set of factors (Cattell and Dickman, 1962; Cattell, 1978) it is apparent that such criticisms are unfounded. Alternatively, to suggest P, E, N and L are not psychologically meaningful is to simply ignore the hundreds of published results indicating the opposite; the results spanning the areas of behavioural genetics, psychophysiology and psychology (Eysenck and Eysenck, 1984).
Secondly, it is assumed that P, E, N and L can be measured in countries other than the U.K. The empirical evidence for this assumption is fully documented in (Eysenck and Eysenck, 1982). This evidence is based upon the mathematical assertion of factor similarity between any one country’s data and the data from the U.K. calibration sample. This approach at determining construct similarity is solely concerned with the objective mathematical determination of similarity. To assert (as some anthropologists might) that such measurement does not take into account the cultural relevance of the questionnaire items, or that it ignores the idiosyncracies of an individual’s interpretation of the items, is irrelevant. The option is either to attempt to use well-validated objective measurement instruments or to resort to intuitive guesswork and subjective observation. Cross-cultural psychology can only advance through the former, as the latter invariably yields only the opinions of the observer or a deluge of descriptive observations. The only assumption made in the former approach is that the patterning of responses to individual items will yield a particular factor-analytic solution. If two such solutions are congruent to a sufficient degree, then one might reasonably assume that the constructs underlying the reported behaviours/preferences etc. are also congruent to a sufficient degree. To assume that such results are based upon chance is to ignore the high congruence measures for the 25 countries data.
Thirdly, the transformation of the mean scores (Table 2 above) does assume that the response patterning to additional ‘hypothetical’ items remains exactly the same as for the actual items in the scale. In other words, an extrapolation is made that provides a proportional increase in scale score dependent entirely upon the existing mean proportional response per item. By keeping the maximum value at 30 items, spurious increases in scale score differences are effectively minimized. To assert that somehow this transformation has changed the scale score in a detrimental manner is not justified. Given the underlying theory of test error and trait measurement based upon factor analytic concepts, the introduction of ‘bad’ items into a scale would simply not yield the solution congruences required to assert similarity. Hence, given the assumption that ‘new‘ items introduced would have been from the same item universe from which the existing items were taken, it is reasonable to assume the means transformation is valid.
Thus, the results above can be viewed with some confidence in their validity and applicability to cross-cultural psychology. They certainly show the remarkable generality of the four personality
Assessment of personahty factors across 25 countries 631
factors E, N, P and L across the 25 countries data presented here. Whether or not specific cultural personality factors also exist is not a question that can be answered by the data given here. What has been demonstrated, however, is that E, N, P and L, are pervasive constructs that would be expected to have significant measurement power in other countries. Their significance in the U.K. is beyond serious question; it remains to be seen if the constructs retain this same explanatory power in dissimilar cultures.
Acknowledgemenf-P. Barrett was supported by a special grant from the Council for Tobacco Research.
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APPENDIX Specific References for Every Country’s Dala Analyses
Abdel-Khalek A. M. (Ed.) and Eysenck S. B. G. (1983) A cross-cultural study of personality: Egypt and England. Res. Behav. Person. 3, 215-226.
Dimitriou E. C. and Eysenck S. B. G. (1978) National differences in personality: Greece and England. In!. J. infercult. Relar. 2, 266282.
Eysenck H. J. and Eysenck S. B. G. (1975) Manual of the Eysenck Personal& Questionnaire. Hodder & Stoughton, London. Eysenck H. J., Eysenck S. B. G., Gauquelin M., Gauquelin F., Pascal C. and Pascal D. (1980) La structure de la personnahte
chez des Francais confrontee a celle des Anglais comparaison “cross-culturelle”. Personnalire Nos l-2, 7-29. Eysenck H. J., Gupta B. S. and Eysenck S. B. G. (1984)National differences in personality: India and England. Psl,cho/.
Res. J. (India). In press. (Dr B. S. Gupta, Department of Psvchologv. Gurd Nanak Dev Universitv. Amritsar. India.) Eysenck S: B. d. (1981) National differences in’personality: Sicily an; England. Ital. J. Psychol. VIiI, 87-93. ’ Eysenck S. B. G. (1982) A cross-cultural study of personality: Germany and England. Z. d$ diagn. Psychol. 3, 293-300. Eysenck S. B. G. and Chart J. (1982) A comparative study of personality in adults and children: Hong Kong vs England.
Person. individ. dr# 3, 153-160. Eysenck S. B. G. and Haraldsson E. (1983) National differences in personality: Iceland and England. Psychol. Rep. 53,
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Eysenck S. B. G. and Matolcsi A. (1984) National differences in personality: Hungary and England. Pszichologia 4(2), 231-240.
Eysenck S. B. G. and Opolet Y. A. (1983) A comparative study of personality in Ugandan and English subjects. Person. individ. D@ 4, 583-589.
Eysenck S. B. G., Paspalanov 1. and Stetinsky D. (1984) National differences in personality: Bulgaria and England. Psychology. In press. (Dr I. Paspalanov, University of Sofia ‘Kliment Ochridsky’, Department of Psychology, I5 Rousky Boulevard, Sofia, Bulgaria.)
Eysenck S. B. G. and Porrata J. L. (1984) Un estudio trans-cultural de personalidad: Puerto Rico e Inglaterra. Revfa lat.-am. Psicol. In press. (Dr J. L. Porrata, Clinica Femandez Garcia, Hato Rey, Puerto Rico.)
Eysenck S. B. G. and Yanai 0. (1984) A cross-cultural study of personality: Israel and England. In press. (0. Yanai, The Institute of Applied Psychology, 12 Pinsker Street, Tel-Aviv, Israel.)
Eysenck S. B. G., Adelaja 0. and Eysenck H. J. (1977) A comparative study of personality in Nigerian and English subjects, J. sot. Psychol. 102, 2-10.
632 PAUL BARRETT and SYBIL EYSENCK
Eysenck S. B. G., Humphery N. and Eysenck H. J. (1980) The structure of personality in Australian as compared with English subjects. J. sot. Psychol. 112, 167-173.
Eysenck S. B. G., Escolar V. and Lobe A. (1983) National differences in personality: Spain and England. Reota Psiquiaf. Psicol. mid. Eur. Am. lat. XV, No. 5.
Iwawaki S., Eysenck S. B. G. and Eysenck H. J. (1977) Differences in personality between Japanese and English. J. sot. Psychol. 102, 27-33.
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Perera K. M. H. and Eysenck S. B. G. (1984) A cross-cultural study of personality: Sri Lanka and England. J. cross-cull. Psychol. In press. (Dr K. M. H. Perera, Department of Physiology, The University of Peradeniya, Faculty of Medicine, Peradeniya, Sri Lanka.)
Rahman A. and Eysenck S. B. G. (1980) National differences In personality Bangladesh and England. Bangladesh J. Psychol. 6, 113-I 19.
Tarrier N., Eysenck S. B. G. and Eysenck H. J. (1980) National differences in personality: Brazil and England. Person. indiuid. D$ 1, 164-171.
Yao-Xian Gong K. Y. (1984) Use of the Eysenck Personality Questionnaire in China. Person. indiuid. Difl 5, 431438.
