The widespread acceptance of the Big Five model implies that personality consists of relatively independent dimensions that form a taxonomy whereby individual differences may be explained. The purpose of this study was to investigate whether the subscales of an established personality inventory that measures narrow traits of personality, the Occupational Personality Questionnaire (OPQ), could be reduced meaningfully to fit a broad factor model within a South African context. The OPQ 5.2 concept model was administered to 453 job applicants in the telecommunications sector. An exploratory factor analysis yielded a six-factor structure that included five factors corresponding to the Big Five model of personality. The sixth factor, labeled Interpersonal Relationship Harmony, resembled the description of the Chinese tradition factor, extracted in a non-Western society.<p> <strong>Opsomming</strong> <br>Die wye aanvaarding van die Groot-Vyfmodel impliseer dat persoonlikheid uit relatief onafhanklike dimensies bestaan wat ’n taksonomie vorm waarmee individuele verskille verklaar kan word. Die doel van die ondersoek was om vas te stel of die subskale van ’n gevestigde persoonlikheidsvraelys wat gedetailleerde persoonlikheidstrekke meet, die Occupational Personality Questionnaire (OPQ), op sinvolle wyse gereduseer kon word tot ’n breë faktormodel in ’n Suid-Afrikaanse konteks. Die OPQ 5.2 konsepmodel is toegepas op 453 werkapplikante in die telekommunikasiesektor. ’n Ondersoekende faktorontleding het ’n sesfaktorstruktuur gelewer, insluitende vyf faktore wat met die Groot Vyf persoonlikheidsmodel ooreenstem. Die sesde faktor wat as Interpersoonlike Verhoudingsharmonie benoem is, toon ooreenstemming met die Chinese tradisiefaktor wat in ’n nie-Westerse samelewing onttrek is
One of the quickest and easiest-though probably not the most accurate or valid-methods of comparing profiles of scores on subtests is that devised by Du Mas(', 2 ) . While Du Mas takes elevation and scatter also into the present note concerns only the similarity in the shapes of profiles, and the quantitative index of profile similarity, rps, suggested by him.I n the main Du Mas' method amounts t o the comparison of the direction of slope of the segments of the two profile graphs, and the index is defined aswhere S is the number of segments with similar slope, and T the total number of segments in each graph. When any segment of either profile is horizontal, a chance decision is to be made to determine whether to regard the slope as upward or downward(3).It is clear that the value of rps obtained depends to a large extent on the chance juxtaposition of subtests, and since there is no unique order of arranging such subtests, there is no unique value of rps that can be found in this way. To illustrate we may consider the profiles recently used by Du Mas by way of example(4). In the case as shown in Du Mas' fig. 1, the value of rps amounts to .111. If the order of the variables had, however, happened to be TI, T3,.T2, Tg, Td, Ts, Ts, Ts, T7, TIO, a value of .554 would have been obtained for rPJ. Similarly almost any other arrangement would yield a different value for rps. This is merely what is to be expected, as a sample of only 0 out of the 45 relationships actually existing between the 10 variables is being taken into consideration in each case.Clearly an index whose value depends to such an extent on an arbitrarily determined order of recording of the several variables cannot be considered very valid. If this index is to be at all useful, even as a rough measure for clinical use only, it is evidently imperative that stability should be attained and the value arrived at should be a function of the test results and the constant relationships between all of them and not of method or order of recording. Another disadvantage of Du Mas' method is the high values required for significance. In few cases of profile comparison do we deal with more than ten subscores, which imply nine segments only. In such a case the value for significance a t the 5 percent level, according to DuMas' table@), is .78.In order to obtain a stable value, independent of the order of recording, and also to lower the significance limits by increasing the number of segments concerned, the following modified procedure is suggested: Instead of considering the slopes of segments between adjacent scores only, the gradients between every score and every other score of each profile should be utilized. I n the example referred to above, the directions of slope would be as presented in abbreviated form in Table 1. The gradients between all possible pairs of scores for the two profiles having been determined, they are compared and the rps calculated as before. The value so obtained is in no way dependent on chance juxtaposition of scores and therefore, as...
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