A cross-validation of the factor structure of the Profile of ... - CiteSeerX

Bond University From the SelectedWorks of Gregory J. Boyle

1987

A cross-validation of the factor structure of the Profile of Mood States: Were the factors correctly identified in the first instance? Gregory J. Boyle, Bond University

Available at: http://works.bepress.com/greg_boyle/108/

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A cross-validation of the factor structure of the Profile of Mood States: Were the factors correctly identified in the first instance?

Gregory J. Boyle University of Melbourne

1 This research was supported by a University of Melbourne research grant. Requests for reprints should be addressed to Dr. Gregory J. Boyle, University of Melbourne, Parkville, Victoria 3052, Australia.

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Abstract The present study investigated further the factorial structure of the Profile of Mood States in an Australian college sample of 289 undergraduate students. Responses for all 65 items were intercorrelated and subjected to an iterative principal factoring procedure together with rotation to oblique simple structure. Results indicated that the basic subscale structure of the profile is reliable, although some additional factors of emotionality could be discerned. A subsequent higher-order analysis suggested that at the typological mood-state level, the Profile of Mood States primarily indexes three state dimensions of Neuroticism, Extraversion, and Arousal.

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Among the currently available multidimensional mood-state inventories, the Profile of Mood States (POMS; McNair, Lorr, & Droppleman, 1981) is one of the most popular and frequently used (Boyle, 1985b). In the most recent Ninth Mental Measurements Yearbook (Mitchell, 1985), numerous new studies in both applied clinical psychology and psychiatry were listed as having used the profile. Given this widespread use of the instrument, it is germane to examine the construct validity of the subscales across many different samples of subjects, including both normal and psychopathological groups, as well as samples from countries other than the USA to establish convincingly the validity of the instrument. In its present form, the profile comprises 65 separate mood-state items, presented in the form of an adjective check-list with a 5-point rating scale for each item. Basically this instrument is an extension of the Multiple Affect Adjective Check List (Zuckerman & Lubin, 1980), with the first three sub- scales being those of the MAACL (namely, Anxiety, Depression, Hostility). As Boyle (1985b) indicated, the profile represents a definite advance over the MAACL (even though the latter has enjoyed enormous respectability and has been used extensively in many research and applied clinical studies), given that it does at least provide the opportunity for indexing additional and important mood states. The question of multidimensional as opposed to univariate measurement in psychology is a critical one. In regard to measurement of depression, Boyle (1985b, p. 52) argued that, "The use of instruments designed only to index depression is a risky procedure. The difficulty in using such scales is that elevations in other psychological states such as anxiety or stress may go undetected. While scores on a single depression measure may alter due to therapeutic intervention, the greatest effect might involve other unmeasured states. Change in the depression score might even result from its correlation with other states. One can never really be certain that alterations to scores on a single scale of depression are due to alterations in depression itself.

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Contemporary psychometry of depression phenomena requires a multivariate perspective." Clearly the profile provides a multidimensional basis of measurement and as such is useful in measuring mood states, provided that it can stand the empirical test of cross-validation with varying samples and settings. In the development of the profile, six factor analyses were reported in the test manual (McNair, et al., 1981, pp. 26-29). Taken overall, these studies suggested the construct validity of six primary mood-state dimensions (labelled: Tension-Anxiety, Depression-Dejection, Anger-Hostility, Vigour-Activity, Fatigue-Inertia, Confusion-Bewilderment, respectively). Some evidence also suggested a Friendliness factor. Although the profile currently includes items to measure all seven dimensions (the number of items per subscale range from 7 to 15), in practice, only the first six are typically scored in view of the uncertainty surrounding the Friendliness factor (McNair, et al., p. 7). One of the difficulties with mood-state scales is the finding of high intercorrelations between the subscales (Boyle, 1985b). In this regard, Cattell (1978, p. 163) has discussed "time-coordinated ambient situation changes" wherein situational determinants often cause alterations in several mood states simultaneously. Accordingly, some reduction in the number of mood states indexed in the profile might be justified. Jacobson, Weiss, Steinbock, Brauzer, and Goldstein (1978) tested this possibility by factoring the intercorrelations of the profile items and those of the Symptom Distress Checklist (SCL), and provided partial confirmation of the profile's structure. However, the factor analytic methodology used by Jacobson, et al. (1978) has been challenged (Boyle, 1985b, p. 52) as inappropriate. More recently, Norcross, Guadagnoli, and Prochaska (1984) examined the factor structure in two separate samples and reported strong evidence for only three of the subscales (i.e., Anger- Hostility, Vigour-Activity, and Fatigue-Inertia). According to Norcross et al. (p. 1270), "The remaining three

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scales were factorially complex and tended to merge, partially attributable to social desirability, to high scale intercorrelations, and to the inherent confluence of psychopathology. . . . Caution is recommended in the separate scoring and interpretation of several POMS scales." Furthermore, Redden, Marceau, and Holden ( 1985) conducted a confirmatory factor analysis of the profile item intercorrelations on three separate samples (involving college males, college females, and prison inmates, respectively) and reported ( p. 243) that, "a smaller number of mood scales would offer a more justifiable interpretation of this inventory." Reddon et al. further concluded (p. 257) that, "the results suggest the consideration of a more parsimonious subspace for the POMS." Early reviews (Spielberger, 1972, p. 388; Weckowicz, 1978, p. 1019) had already questioned the sensitivity of the subscales to transient mood alterations, and by implication, the construct validity of the subscales. As the profile is a frequently used instrument in both research studies and applied clinical settings, it is important to ensure that the subscale structure is indeed valid. Accordingly, the present study aims to provide further evidence regarding the construct validity of the subscales by subjecting the item intercorrelations for all 65 items to factor analysis. It is hoped that investigating the factor structure in a different cultural setting from those of previous studies may help to provide important crossvalidational support for the purported structure of the instrument.

Method Subjects and Procedure The sample comprised 289 (about 80% female) Australian college students enrolled either at the Melbourne College of Advanced Education or the Institute of Catholic Education, Melbourne. The mean age of the sample was 22.06 yr. (SD = 6.58 yr.). Almost all subjects were Australian by birth and were of middle-class

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socioeconomic status. Administration of the profile was undertaken as part of the students' regularly scheduled lecture sessions, taking only a few minutes at the most to complete. Although students responded to the items anonymously, they were entirely free not to participate, or to withdraw at any time. In practice, virtually all students chose willingly to participate in the study. As sex differences in the factor structure of the profile have not been prominent in previous studies (McNair, et al., 1981, p. 29; Reddon et al., 1985), data from the combined-sex sample were utilized in the present factoring of the instrument.

Factor Analytic Methodology An iterative principal factoring procedure, together with determination of the appropriate factor extraction number by the Scree test (Cattell, 1966) , and rotation to oblique (direct Oblimin) simple structure via SPSS (Nie, Hull, Jenkins, Steinbrenner, & Bent, 1975) was employed in accord with the guide- lines and recommendations advocated by Cattell (1973, pp. 282-287; 1978, 1979, p. 351), Gorsuch (1983), Kline (1979, pp. 38-41; 1980, pp. 323-324), and Nunnally (1978, pp. 327-436). An iterative procedure was employed rather than a principal components approach, given that the latter method adds spurious variance into the factor solution due to inflated communalities (Lee & Comrey, 1979, p. 301). Moreover, while principal components may be mathematically elegant, they often are less meaningful in substantive terms. Use of the Scree test rather than the eigenvalue greater than unity (Kaiser-Guttman) criterion in estimating the appropriate number of factors had the advantage of providing a more accurate decision as shown empirically by Cattell and Vogelmann (1977), Hakstian, Rogers, and Cattell ( 1982), and also Yeomans and Golder (1982). As Child (1970, pp. 43-44) pointed out, the Kaiser-Guttman criterion underestimates the number of factors when there are fewer than about 20 variables but overestimates the number

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of factors when there are more than about 50 variables ( 65 in the present instance) in the analysis. On the issue of rotation, an oblique solution was clearly desirable, rather than an artificially imposed orthogonal solution (Loo, 1979). As Cattell (1978, pp. 136-137) indicated, even in the unusual situation where factors actually are independent, an oblique rotation carried to maximum simple structure will stop at the appropriate special orthogonal position. Finally, it was important to test the obtained factors for statistical significance, using Sine and Kameoka's (1978) tables, and to examine the approximation to simple-structure of the final rotated factor-pattern solution in terms of the ± .10 hyperplane count (cf. Cattell, 1978, pp. 140-146). Results and Discussion The means and standard deviations for each of the profile's items are presented in Table 1. The manual (McNair et al., 1981) does not provide normative data of this kind, with the profile administered to undergraduate college samples in the "Right Now" format (which was used in the present study). As can be seen from the pattern of responses, the subjects tended not to ascribe to themselves feelings of spitefulness, bitterness, worthlessness, fear, or guilt. On the other hand, items pertaining to friendliness, consideration, helpfulness, cheerfulness, and trust were assented to readily. Therefore, the responses to the items were almost certainly influenced strongly by social desirability effects. The evident transparency of the items with their corresponding high face validities must therefore be regarded as a critical distorting influence on the scores obtained from the instrument. As for the present factor analysis, the 65 X 65 item intercorrelation matrix served as the starting point for the multivariate analysis. Pearson product-moment correlations were calculated for all 65 items. Several of the items were moderately intercorrelated, and some exhibited quite high intercorrelation coefficients.

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Interestingly, sex correlated significantly (-.21, p < .01) with Item 51 (Alert), suggesting that women considered themselves less alert than men. Likewise age exhibited significant correlations, .24 (p < .01) and .23 (p < .01) with Item 25 (Sympathetic) and Item 51, respectively. It is not clear that these statistically significant correlations were due to anything other than chance, nor that they were practically meaningful.

Table 1 MEANS AND STANDARD DEVIATIONS FOR POMS ITEMS AND SUBSCALES (N = 289) Item

M

SD

Item

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33.

2.55 1.38 0.60 2.16 0.97 1.97 1.76 1.22 1.03 0.57 1.20 0.99 2.33 1.01 1.67 1.15 0.790.96 1.58 0.83 0.68 1.90 0.63 0.42 2.00 0.92 1.44 1.73 1.88 2.06 0.84 1.07 0.67

0.93 1.21 0.95 1.38 1.07 1.14 1.20 1.27 1.19 0.96 1.17 1.11 0.98 1.18 1.24 1.23 1.07 1.17 1.26 1.14 1.05 1.21 1.04 0.85 1.15 1.10 1.18 1.31 1.42 1.08 1.08 1.21 1.08

34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63. 64. 65.

Subscale 10.40 8.01 Vigour Tension 11.12 9.78 Fatigue Depression 9.14 7.74 Confusion Anger Note.-No comparable norms available in POMS manual, but items are listed.

M

0.82 0.90 0.88 0.99 2.00 0.51 1.64 1.26 0.68 2.44 0.82 0.55 1.23 0.87 0.73 1.58 0.85 1.79 0.58 0.43 1.73 2.37 1.39 0.68 0.57 1.12 1.54 0.37 0.62 1.13 1.60 1.74

SD 1.14 1.19 1.21 1.20 1.19 1.00 1.44 1.26 1.08 1.12 1.09 1.03 1.23 1.18 1.12 1.33 1.09 1.16 1.06 0.92 1.16 1.07 1.20 1.03 1.06 1.14 1.21 0.83 1.00 1.14 1.31 1.43

12.23 8.99 10.54 6.74 10.94 9.76

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In fact, the overwhelming observation is that almost all of the correlations of the items with sex and age were non-significant. A plot of the eigenvalues suggested 10 significant factors by the KaiserGuttman criterion, but nine factors by the Scree test. The finding was consistent with the empirical observations of Cattell and Vogelmann (1977), Hakstian et al. (1982), and with the comments of Child (1970) referred to above. The obliquely rotated factor-pattern solution is presented in Table 2.

Table 2 OBLIQUE FACTOR PATTERN SOLUTION FOR PROFILE OF MOOD STATES Item No. 1 1.

-.13

2. 3. 4. 5. 6. 7.

-.06 -.04 -.09 .56 -.03 -.04 .17 .34 .15 .16 .06 -.02 .56 .06 .00 .21 .50 -.05 .01 .47 .07 .58 .19 .02 .20 .05 -.12 .06 .07 .23 .41 .12 .02 .55 .65 .26

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9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42.

-.13 .19 .08 .15 -.03

2

3

Factor No. 4 5

h2

6

7

.02 .02 -.18 -.04 -.02 .08 .14 .64 -.12 .26 .04 .65 -.03 .11 .09 .03 .05 -.13 .80 -.02 .06 .15 .08 -.04 .16 -.13 .12 .07 -.10 .13 .09 .15 -.16 .00 .01 .68 -.07 .08 -.09 -.01 .12 .16 .05 -.43 -.08 .06 -.40 .10 .11 -.04 .10 -.04 .08 .15 -.06 .13 .58 -.22 .18 .10 .19 -.11 -.03 -.04 .12 .42 .05 -.19 .22 .05 -.03 -.05 .00 -.09 .00 -.03 .20 .28 .oo -.02 .15 .00 .10 .93 -.02 -.10 -.01 .60 -.18 .12 -.05 .13 .16 -.01 .25 .43 .17 .07 .13 .21 -.23 .12 .05 -.03 .09 .88 -.08 -.01 .04 -.05 .05 .08 .09 .08 .65 -.10 -.11 -.03 .14 -.02 .24 -.15 -.22 .22 -.09 -.09 -.42 .03 -.07 -.02 -.01 .03 .08 -.14 -.19 .11 -.03 .00 .09 -.01 .52 .11 .06 .03 -.01 -.04 .13 .15 .06 .03 .51 -.14 .10 -.02 .15 .16 .26 -.34 .05 .33 -.03 .09 .09 -.48 -.03 -.07 .84 .04 -.04 -.02 -.05 .22 -.02 -.08 -.05 .05 -.07 -.09 .07 .59 -.01 -.20 .18 .21 -.10 .10 .11 -.25 .01 .08 -.03 .54 .18 -.19 .02 .06 .09 .07 .75 .05 .00 -.07 .09 .19 .01 .02 .01 -.01 .18 .06 .15 -.03 .04 -.06 .21 .11 .17 -.24 -.18 .03 -.05 -.23 -.08 -.19 .44 -.05 -.06 .57 .17 .03 .05 .02 .84 -.08 .10 .10 .01 -.04 .04 -.05 .51 -.28 .02 .11 -.08 .54 .02 -.09 -.05 (Continued on next page) .25 -.07 -.06

8

9

-.37 -.04 -.02 .07 -.02 -.10 -.08 .02 .15 -.04 -.15 .06 -.67 -.03 -.05 .05 .12 -.07 -.13 -.01 -.19 -.12

.15 -.12 -.07 .01 -.08 .45 .08 -.17 .03 -.03 -.14 -.04 -.02 -.05 -.08 .03 .07 -.04 -.19 -.06

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.13 .11

.07 -.07 .02 .00 .07 -.10 .07 .14 .05 .09 .01 -.05 -.11 -.04 -.17 -.13 .23 .00 -.05 .01 -.03 .05 .14 .09 .08 .04 -.68 .04 -.02 .03 .01 -.52 .00 .09 .14 -.03 -.09 .01 -.06

.48

.72 .51 .74

.71 .52 .68 .59 .46 .61 .48 .47 .49 .74 .86 .74 .67 .69 .81 .64

.71 .48 .57 .52 .50 .67 .48 .56 .79 .55 .76 .69 .68 .66 .55 .80 .69 .68 .62 .75 .53 .35

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Table 2 (Continued) OBLIQUE FACTOR PATTERN SOLUTION FOR PROFILE OF MOOD STATES

2

1

43.

-.04

44.

.44

45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63. 64. 65. Eigenvalue: ± Hyperplane Count:

h.

Factor No.

Item No.

.21 .09 -.03 .04 .25 -.01 .20 -.10 -.08 -.25 .48 .13 .08 -.03 .66 -.05 .05 -.03 .00 .78 -.07 .19 -.17 .03 .12 .51 -.11 .01 -.01 .51 -.06 -.05 .73 .22 -.06 .13 .01 -.03 -.09 .60 -.19 .04 .57 .03 .22 -.02 .15 .18 .07 .31 .18 .00 .02 .36 -.05 .00 .14 .11 -.01 -.06 .63 -.06 .07 -.10 .13 .02 -.11 .64 .01 6.22 2.90 1.91

.14 .04 -.11 .51

.07 .24 .02 .25 .10 .11 -.03 .05 .02

.47 .00 -.18 .12 .24 -.04

.34 .05 24.87 30

4

3

42

36

34

5

6

-.20 -.11 -.06 .21 -.08 -.04 .37 -.28 -.17 -.07 -.19 -.13 .01 -.12 .09 .26 -.10 -.22 .09 -.03 -.01 -.02 -.36 -.28 .06 .04 .05 .00 -.11 .05 -.02 .02 -.16 .17 -.09 .13 .04 -.04 -.08 .05 -.12 .05 .07 .07 .01 .16 .16 -.37 -.06 -.09 -.26 -.06 -:14 -.25 .17 -.28 .54 .17 -.28 -.15 .05 .07 -.08 .14 -.26 .02 .06 -.05 -.06 1.73 1.47 1.29 36

36

8

9

-.43

.32

7

38

.13 -.06 .06 .11 -.09 -.08 -.06 .08 .05 -.02 .00 -.08 -.08 -.06 .00 .39 -.03 -.16 .05 -.05 -.20 .44

-.30

.43

-.08 .12 .16 .07 .02 -.08 -.03 -.07 .00 .23 -.06 .00 -.15 -.21 -.04 .09 -.11 -.16 .01 .05

.62 .64 .60 .62 .49 .68 .75 .58 .64 .57 .65 .52 .33 .63 .54 .74 .27 .42 .55 .45 .53 .55 .59

1.18 1.16

45

42 Total= 57.95%

Note.-Factor loadings to two decimal places only. Significant loadings are italicized. The factors represent respectively: 1. Depression-Rejection, 2. Vigour, 3. Fatigue, 4. Anger-Hostility, 5. Tension-Anxiety, 6. Confusion-Bewilderment, 7. Worthless Depression, 8. Friendliness, 9. Arousal-Alertness. Hence all of the prior factors are supported, together with the finding of additional factors from the total 65 items. Eigenvalues for the additional principal components were: 1.02, .97, .95, .91, .83, .80, .75, .74, .69, .65, .63, .62, .59, .57, .55, .52, .50, .49, .48, .44, .43, .42, .41, .39, .38, .37, .35, .33, .32, .32, .30, .29, .27, .26, .24, .23, .22, .22, .22, .21, .20, .20, .19, .18, .18, .17, .16, .15, .15, .14, .13, .12, .11, .10, .10, .09, respectively. (See manual for item names).

The ± .10 hyperplane count for the nine-factor solution was 57.95% which suggested only moderate approximation to maximum simple structure. However, all nine extracted factors were statistically significant by Sine and Kameoka's (1978) tables. Boyle (1985a) has discussed the conservative nature of these tables, and it is apparent that. extraction and rotation of all nine factors was justified. It is evident also that the total seven factors purported to have a measurement basis in the profile were readily identifiable from the factor-pattern solution, providing strong support for the construct validity of the subscale structure and, as well, two additional smaller factors.

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Factor 1 (accounting for 38.3% of the total variance associated with the 65 unrotated principal components) was clearly the Depression-Dejection dimension, with significant loadings on 12 of the 15 items in that subscale. The subscale items which did not exhibit significant loadings on this factor were Items 45, 61, and 62 (Desperate, Terrified, Guilty, respectively). On the other hand, Item 64 (Uncertain about things) loaded positively on the Depression- Dejection factor. Factor 2 (which accounted for 9.6% of the unrotated variance) had significant factor loadings on all of the items in the Vigour subscale only. Factor 2 therefore provided complete support for this subscale. Factor 3 (4.5% of the variance) represented the Fatigue subscale, although Item 11 (Listless) did not load significantly on this factor, whereas Items 28 and 59 (Unable to concentrate, Forgetful, respectively) exhibited significant loadings on the Fatigue factor. Factor 4 (2.9% of the variance) supported the Anger-Hostility subscale perfectly, with significant loadings on all of the items in that subscale and only on those items: Factor 5 (2.7% of the variance) exhibited significant item loadings in complete accord with the Tension-Anxiety subscale, but in addition loaded positively on Items 45 and 61 (Desperate, Terrified, respectively). Both these additional items appear to fit in well with the Tension-Anxiety dimension of emotionality. Factor 6 (2.3% of the variance) clearly represented the Confusion subscale, although Items 54 and 59 (Efficient, Forgetful, respectively) did not exhibit significant loadings on this factor. However, additional Items 9, 27, and 62 (Sorry for things done, Rest- less, Guilty, respectively) loaded significantly on this Confusion dimension, thereby adding to its qualitative explication. Factor 7 (2.0% of the variance) exhibited significant loadings on items pertaining to tension, bewilderment, and worthlessness, along with forgetfulness, and fear, suggesting perhaps, an interpretation of Worthless Depression. Clearly then, in the present nine-factor solution, the Depression dimension of emotionality is more complex than

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suggested by the single subscale provided in the profile. This finding accords with previous research evidence (Cattell, 1979, pp. 73-82; Krug, 1980) suggesting the presence of at least seven major types of Depression states (Price, Cattell, & Patrick, 1981). Factor 8 (1.8% of the variance) gave strong support for the Friendliness dimension, with significant loadings on all of the appropriate items, except for Item 6 (Clear-headed). In fact, Item 6 loaded significantly along with items pertaining to alertness, efficiency, and trust, on Factor 9 (1.8% of the unrotated variance), suggesting an interpretation of Arousal-Alertness. This factor probably relates directly to concomitant physiological CNS activation in the ascending reticular activating system (ARAS) and in the cerebral cortex, respectively. This additional dimension of emotionality has been reported in previously published studies into mood-state factors by Boyle (1986a, 1986b). Although nine factors were extracted and rotated on empirical grounds, it should be recognized that there is no definitive solution to the question of number of factors. The Scree test works reasonably well in most situations, but it is only a psychometric rule-of-thumb and is not a statistical test with a sampling distribution. In the present instance, the more conservative estimate of the appropriate number of factors based on the Scree test (rather than the KaiserGuttman criterion which indicated 10 factors) was used in line with Walkey (1983). With extraction and rotation of fewer than nine factors, the basic subscale structure of the Profile of Mood States began to collapse, with a number of the subscales combining into more complex factors in support of the findings by Norcross, et al. (1984) as well as Reddon et al. (1985). To check further on the factor structure of the instrument, a higher-order iterative principal factor analysis together with oblique simple structure rotation was performed on the primary factor intercorrelations for the nine-factor solution. The 9 X 9 matrix of intercorrelations is presented in Table 3. Evidently, several of

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the first-order factors exhibited significant intercorrelations, a finding frequently reported in the area of mood states. Extraction of factors by the Scree test indicated three significant dimensions, as shown in the factor pattern matrix in Table 4. The resultant higher-order Profile of Mood States factors clearly represented state dimensions of Neuroticism (33.7% of the un- rotated variance) with significant loadings on Depression-Dejection, Anger- Hostility, Tension-Anxiety, and also Confusion-Bewilderment; Extraversion ( 17.2% of the unrotated variance) , with significant loadings on Vigour-Inertia, Friendliness, and Alertness; and ArousalFatigue (10.4% of the variance) with loadings on Vigour-Inertia, Fatigue, and Alertness. Each of these three higher- order mood-state dimensions has been reported in previous studies of the central typological dimensions of emotionality (Boyle, 1986a, 1986b, 1987).

Table 3 PEARSON lNTERCORRELATION MATRIX FOR THE FIRST-ORDER POMS FACTORS (N = 289)

=

Primary Factor

1

2

3

4

5

6

7

8

9

1. Depression

2. Vigour -.24 3. Fatigue .38 -.48 4. Anger .52 -.05 .34 5. Tension .56 -.28 .44 .53 6. Confusion -.34 .11 -.35 -.35 -.31 -.11 -.09 -.10 -.12 -.06 7. Worthlessness .14 8. Friendliness .10 -.35 .11 .16 .14 -.08 .11 .11 -.07 -.30 -.20 .41 -.22 -.05 -.22 9. Alertness Note.-Correlations to two decimal places only. Correlations > .12 are significant at the 5% level, while those > .15 are significant at the 1% level (Child, p. 95).

These findings taken together across various samples and instruments suggest that Watson and Tellegen's ( 1985) claim that there are only two higher-order mood- state factors of positive and negative affectivity is inadequate, being based on unsound factor analytic procedures in many instances (Boyle, 1985b). In any event, the resemblance of

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Table 4 HIGHER-ORDER OBLIQUE FACTOR PATTERN FOR POMS Primary Factors

Secondary POMS Factors 2 1 3

h2

-.04 .67 -.09 1. Depression-Dejection .51 2. Vigour-Activity .10 .33 .73 .71 -.68 .21 .19 3. Fatigue-Inertia .61 .85 -.05 .18 .61 4. Anger-Hostility -.07 -.14 5. Tension-Anxiety .66 .53 -.10 .14 6. Confusion-Bewilderment .24 -.40 -.13 -.26 7. W Worthless Depression .03 .09 .18 -.04 -.54 8. Friendliness .33 .28 -.09 9. A Arousal-Alertness .38 .30 Eigenvalue 3.03 1.55 0.93 17.2 33.7 10.4 % Variance (unrotated) Notes.-Factor loadings to two decimal places only. Significant loadings are italicized. Interestingly, Factor 7 exhibits a negligible communality thereby suggesting that this factor is unimportant. If the last three factors are excluded, it can be seen that all of the regularly scored six subscales are supported by Factors 1 to 6 inclusive. Higher-order factors represent Neuroticism State, Extraversion State, and Arousal State, respectively. Superfactor 1 (S1) correlates .07 with S2, and -.45 with S3, while S2 correlates .25 with S3. The nine eigenvalues (based on the unrotated principal components) were 3.03, 1.55, 0.93, 0.83, 0.75, 0.68, 0.47, 0.42, 0.34, respectively, which indicated three higher-order factors (Child, 1970, pp. 44-45 regarding application of the Scree test).

the present findings to Eysenck's (1983, 1984) superfactors is quite evident, although at the state rather than the trait level. Interestingly, there is no evidence from the present factoring of the profile of an emotionality factor of Psychoticism (which is an integral component in Eysenck's tripartite typological personality trait model). Accordingly, use of the profile with individuals diagnosed as psychotic would seem inappropriate on the present evidence. Indeed, the authors of the profile have counselled against its use with psychiatric inpatients on the grounds of insufficient usage on such populations to judge its reliability and validity in these circumstances. The present findings arrive at a similar recommendation, given the structural limitation of the profile in measuring psychotic states. Clearly the instrument is highly. susceptible to distorting influences such as effects of social desirability and other response sets, inadequate self-insight, and even downright dissimulation, given the obvious item transparency. As Eichman

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(1978, p. 1017) stated, "There is considerable redundancy in these scales, and it is not surprising that internal consistency is high. How could a person say that he was nervous and deny that he was tense, or say that he was hopeless but deny that he was unworthy?" On the other hand, the present cross-validational study has strongly supported the purported factor structure of the instrument which suggests that the subscales are construct valid, provided that the items are responded to honestly and in an unbiased fashion. It may be however, that the factor structure reproduced in the present instance might be partially an outcome influenced universally by social desirability response sets. In any event, the item and subscale structure of the profile has been reproduced almost perfectly (the Vigour-Inertia and Anger-Hostility subscales exhibited a perfect reproduction of their item structure). While a few specific items loading on some of the subscales may differ slightly from sample to sample, the degree of concordance with the purported factor structure of the instrument is remarkable, especially in view of the usual degree of variation in factor loadings derived from the same variables across different samples reported in the extant research literature. Clearly, the present findings provide strong support for the factorial validity of the Profile of Mood States.

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