Journal of Vocational Behavior 73 (2008) 310–317

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Journal of Vocational Behavior

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Prestige in interest activity assessment q

Sandro M. Sodano a,*, Terence J.G. Tracey b

a University at Buffalo, SUNY, Department of Counseling, School and Educational Psychology, 427 Baldy Hall, Buffalo, NY 14260-1000, USAb Arizona State University, 302 Payne Hall, MC-0611, Tempe, AZ 85287-0611, USA

a r t i c l e i n f o a b s t r a c t

Article history:Received 1 May 2008Available online 10 July 2008

Keywords:Activity preferencesInterest assessmentPersonal globe inventoryPrestigeSpherical model of interests

0001-8791/$ - see front matter � 2008 Elsevier Incdoi:10.1016/j.jvb.2008.07.002

q A preliminary version of this study was presente* Corresponding author. Fax: +1 716 645 6616.

E-mail address: smsodano@buffalo.edu (S.M. Sod

Prestige has been demonstrated to be a component in interest assessment [Tracey, T. J. G.(1997). The structure of interests and self-efficacy expectations: An expanded examinationof the spherical model of interests. Journal of Counseling Psychology, 44, 32–43; Tracey, T. J.G. (2002). Personal Globe Inventory: Measurement of the spherical model of interests andcompetence beliefs [Monograph]. Journal of Vocational Behavior, 60, 113–172; Tracey, T. J.G., & Rounds, J. (1996a). The spherical representation of vocational interests. Journal ofVocational Behavior, 48, 3–41]. However, the content of prestige and thus its meaning inactivity and competency preferences has not been clarified, nor has it been differentiatedfrom alternative explanations such as sex-typing. A vector fitting procedure was utilizedfrom theoretical and empirical approaches with samples of college students who ratedeach activity item from the Personal Globe Inventory (PGI; [Tracey, T. J. G. (2002). PersonalGlobe Inventory: Measurement of the spherical model of interests and competence beliefs[Monograph]. Journal of Vocational Behavior, 60, 113–172]) for the following content: pres-tige, effort required, skill required, competition involved, and female and male sex-typing.These content ratings were matched with the theoretical structure of the PGI scales in thefirst sample (N = 124) and the empirical structure of the PGI items in a second sample(N = 267). Across both approaches, the PGI prestige dimension was highly related to ratingsfor prestige, effort, skill, effort and skill, and competition, but unrelated to sex-typing.These results support the inclusion of prestige in interest activity assessment and alsoassist in its interpretation.

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1. Prestige in interest activity assessment

Prestige is not a new construct in vocational psychology. It has been defined in relation to occupations from such perspec-tives as level of training (Holland, 1997) and status (Holland, 1985), occupational level (Campbell, 1971; Strong, 1943), levelof difficulty and level of responsibility (Roe, 1956), general educational level (Gottfredson & Holland, 1989), socioeconomicstatus (SES) (Stevens & Cho, 1985), and level of prestige for occupations (Stevens & Hoisington, 1987). Prestige has beenincorporated into many models of career choice. However, when included in models of career choice, it is generally includedas supplementary, either as separate and in addition to vocational interests (Gottfredson & Duffy, 2008; Holland, 1997), or asone of many values (Dawis, 1991; Dawis & Lofquist, 1984). However, Tracey and Rounds (1996a) found support for prestigebeing a key aspect of vocational preference ratings and not a separate content, with later research continuing to support thisfinding (Deng, Armstrong, & Rounds, 2007).

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d at the annual meeting of the American, Educational Research Association, New York, 2008.

ano).

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Through an examination of the factor structure of preference responses to a broad set of occupational titles, Tracey andRounds (1996a) demonstrated the presence of four factors: a general factor and three substantive factors. The three substan-tive factors were the People-Things and Data-Ideas factors proposed by Prediger (Prediger, 1982; Prediger & Vansickle, 1992)and a prestige factor. The presence of this prestige factor was a unique result and helped to define the spherical model ofinterests (Tracey & Rounds, 1996a; Tracey & Rounds, 1996b). The construct validity of the occupational prestige factorwas supported by strong correlations with status (Holland, 1985), general education level (Gottfredson & Holland, 1989),SES (Stevens & Cho, 1985), and prestige levels of occupations (Stevens & Hoisington, 1987).

Although evidence supports the presence of the prestige factor, the interpretation of this fourth factor has been de-bated within the literature. Sex-type (i.e., the view that certain activities are more feminine or masculine) was initiallyposited as an alternative interpretation for the prestige factor (Harmon, 1996). Scores on the People-Things dimensionconsistently vary by sex, with males scoring higher on Things and females scoring higher on People (e.g., ACT, 1995;Harmon, Hansen, Borgen, & Hammer, 1994; Holland, 1997; Lippa, 1998; Tracey, 2002). The People-Things dimension alsohas been shown to be related to the constructs of femininity and masculinity (Lippa, 1998). However, the prestige factorwas shown to correlate more highly with an objective representation of the prestige of the occupations (Stevens & Hoi-sington, 1987) than it did with either SES (Stevens & Cho, 1985) or the sex-typing of the occupation (Tracey & Rounds,1996b). Another criticism of the prestige factor has been that it is inherent in the preference ratings of occupational ti-tles, which are used as items in many interest inventories, but not in preference ratings of simple activities (Prediger,1996). However, the same factor structure was demonstrated in preference responses to a broad set of activities (Tracey,1997). The prestige factor for activities correlated highly with the prestige factor for occupational titles (r = .79), and, inaddition, both of these factors correlated with a separate item requesting preference for prestige (r’s = .74 for each).These results demonstrated that indeed a prestige factor was present in activity items as well, although its meaningwas not as clear as it was in occupational preferences.

Using the above results as a base, Tracey (2002) adopted an inductive approach to constructing an interest inventory thatwould represent these three factors, but posited that the three dimensional structure existed as a sphere. The spherical struc-ture implicitly allows for the differential reliance on prestige when rating preferences for occupations and or activities. Assuch, this model of interest preferences is truncated at either end of the prestige pole of the sphere, but is most varied atthe mid-range level of prestige where Prediger (Prediger, 1982; Prediger & Vansickle, 1992) two-dimensional plane resides.The instrument was called the Personal Globe Inventory (PGI; Tracey, 2002) and it included separate scales for activity pref-erences, self-efficacy assessments and occupational title preferences, all of which highly correlated with each other. As a re-sult, the PGI can be scored separately for each of these (activity preferences, self-efficacy, or occupational preferences) ortotal scores aggregating each. The spherical placement of the 18 PGI scales is depicted in Fig. 1. The spherical structurewas found to be supported in separate samples of US high school and college students as well as across most major ethnicgroups (Tracey, 2002). Further studies beyond the US have supported the spherical structure of the PGI in Chinese (Long,Adams, & Tracey, 2005), Irish (Darcy, 2005), Japanese (Long, Watanabe, & Tracey, 2006), Croatian (Sverko, 2008), and Serbiansamples (Hedrih, 2008). However, the issue of the meaning of the ‘‘prestige” factor for activity preferences still remains.

Although the prestige scores for the activity items and the occupational items correlate highly, it is harder to see prestigeas being inherent in activities themselves (i.e., Prediger, 1996). In addition, the approaches to examining prestige in occupa-tions (e.g., Campbell, 1971; Holland, 1985; Holland, 1997; Roe, 1956) do not uniformly apply to the study of activities. Anarea where activities have been studied outside of the traditional application of interest assessments is avocational or leisurepursuits. Although the structure of leisure activity ratings has varied somewhat across studies (Bishop, 1970; Hansen, Dik, &Zhou, 2008; Hansen & Scullard, 2002; London, Crandall, & Fitzgibbons, 1977; Tinsley, Barrett, & Kass, 1977; Tinsley & Eldr-edge, 1995; Tinsley & Kass, 1978; Tinsley & Kass, 1979; Witt, 1971), a common dimension found is competition and this re-sult occurs when either the leisure activities themselves or the needs the activities fulfill for individuals are considered.

While the association of prestige with ratings of occupational titles is obvious, the connection to ratings of activities is lessso. We sought to examine the underlying meaning of prestige in activity ratings. Of course we examined the activity pref-erence items as they varied across potential interpretations (e.g., prestige, sex-typing). However, prestige in activities washypothesized to be composed of a combination of effort required to complete and skill required to complete, as these are syn-onymous with the general difficulty level of a task. Both of these components (effort and skill) will vary across activities;however, it is assumed that both together will relate best to the prestige dimension. In addition, prestige was viewed asbeing related to the amount of competition that was involved in the activities. Competition should in part be related to effortand skill, as these are involved in competition, but competition was also included as it has repeatedly come up in preferencesof avocational or leisure activities (e.g., Hansen & Scullard, 2002). Thus, the major purpose of this study was to examine theunderlying meaning associated with prestige ratings of activities.

2. Method

2.1. Procedures and sample

Two samples of college students drawn from career development classes at a south west university participated. The firstsample consisted of 124 college students (69 females and 55 males with a mean age of 20.1, SD = 1.0; 59% Anglo American,

Fig. 1. Spherical structure of the 18 Personal Globe Inventory scales.

312 S.M. Sodano, T.J.G. Tracey / Journal of Vocational Behavior 73 (2008) 310–317

6% African American, 2% Asian American, 21% Latino(a) American, 6% Native American, and 2% Other). These individualsrated each of the PGI items from different content perspectives.

The second sample consisted of 267 college students (158 female and 109 male with a mean age of 19.9, SD = 1.2) whocompleted the usual activity based version of the PGI. The ethnic distribution of the sample was 70% Anglo American, 7%African American, 5% Asian American, 15% Latino(a) American, and 3% Native American.

2.1.1. Personal globe inventoryPersonal Globe Inventory (PGI; Tracey, 2002) is an instrument consisting of 108 activities and 108 occupational titles to

which individuals respond. Robust psychometric support has been found for the use of activity items as separate from occu-pational preference items (Tracey, 2002). The activity items are responded to twice, once with respect to interest preferences(1 = very strongly dislike to 7 = very strongly like) and once with respect to competence perceptions, (1 = unable to do to7 = very competent). These two response formats are used to generate different profiles of scores: one for interests andone for competence perceptions. Separate scores for each are produced on the following 18 scales that are equidistantlyspaced around a sphere: Social Facilitating, Managing, Business Detail, Data Processing, Mechanical, Nature-Outdoors, Artis-tic, Helping, Social Sciences, Influence, Business Systems, Financial Analysis, Science, Quality Control, Manual Work, PersonalService, Construction-Repair, and Basic Services. There are three dimensions that define this sphere: People-Things, Data-Ideas and Prestige. Detailed information on the items, scales, and psychometric properties of the PGI can be found in Tracey(2002). For this study, only the activity items were used. There was no usage of the scales themselves, only the items, so wedid not calculate internal consistency estimates of these scales.

2.1.2. Content ratingsThe modified PGI consisted of the 108 activities from the PGI except rather than have individuals rate these items for

interest and competence, the individuals were requested to rate each activity item (using a 7 point Likert-type format) on

S.M. Sodano, T.J.G. Tracey / Journal of Vocational Behavior 73 (2008) 310–317 313

(a) prestige involved, (b) effort involved, (c) skill involved, (d) competition involved in the activity, (e) extent to which it wasassociated with girls and women, and (f) the extent to which it was associated with boys and men.

3. Results

A vector fitting approach (Arabie, Carroll, & DeSarbo, 1987) was adopted where the content ratings (i.e., prestige, effortand skill, competition, female sex-type, and male sex-type) were plotted on the space defined by either the PGI scales oritems. Each item loads onto a scale of the PGI, which occupies a specific point in three dimensional structural space. Themean content ratings (a–f) for each item were determined for each sample’s ratings and then these mean content ratingswere correlated with either the scale locations or items on the dimensions of the sphere, depending on how PGI spacewas defined for the analysis.

The PGI space was defined for this vector fitting procedure in two ways: theoretically and empirically. The first method istheoretical, where each original activity item is part of a scale which is placed on an equidistantly dispersed spot on the PGIsphere. The perfect location of each scale on the sphere comprises the theoretical structure of the PGI, as defined in Tracey(2002), and is depicted in Fig. 1. Sample one was used in this theoretically derived examination. The second method wasempirically determined. For this method, the structures of both the PGI interest and competence items were empirically de-rived and then used to examine how the content ratings covaried with dimensions within their respective structures. In thiscase, the responses of the second sample to the PGI activity items were examined using principal component analysis (PCA).

3.1. Theoretical placement

For the theoretical analysis, the content validity means were calculated for each content rating (a–f); these means werethen correlated with the theoretical locations of the scales on each of the three PGI dimensions. Therefore, each correlationrepresents 18 data points; the 18 scale locations on each dimension with each of the seven content validity means. The cor-relations of the content validity scales with the three dimensions of the theoretically placed (N = 18) PGI scales are presentedin Table 1. The Prestige dimension of the PGI was positively and strongly correlated with the Prestige (r = .86, p < .01), Effort(r = .55, p < .01), Skill (r = .50, p < .05), and Competition (r = .78, p < .01) ratings. The sum of Effort and Skill content ratingsalso was strongly correlated with the Prestige dimension (r = .82, p < .01); higher than either rating individually and nearlyas high as that for the Prestige rating itself.

There were small non-significant correlations between either of the sex-typing content variables and prestige: FemaleAssociated (r = �.22, p > .05) and Male Associated (r = .19, p > .05). This supported the lack of sex-typing in the Prestigedimension of the PGI. There also was a small non-significant relation between sex-typing and the Data-Ideas dimension.However, there was a medium significant correlation between Female sex-typing and the People-Things dimension(r = .42, p < .05). Activities that were rated as being more associated with girls and women were more associated with Peopleactivities than Thing activities. The medium correlation of the Male sex-type ratings with the People-Things dimension wasnot significant (r = �.39, p < .10), although the Male associated activities tended to be more likely Things than People. Whileone of these sex-typed correlations was significant and the other was not, it is likely that the absolute values of these twocorrelations were not different from each other. To examine if the absolute value of these two correlations were different weused Steiger’s (1980) modified z statistics as implemented in the DEPCOR program (Silver, Hittner, & May, 2006). This pro-cedure is more appropriate than the common Fisher’s z test because the correlations are not independent. The test of thedifference in the absolute values of correlations was not significant (z = .17, p > .05).

3.2. Empirical Placement

To obtain an empirical placement of each item, an exploratory component analysis was conducted separately for theinterest and competence responses to the PGI items since these are the items that comprise the scales. Because the factor

Table 1Correlations of theoretical scale placement PGI scales with the validity content ratings (Expected relations underlined)

Content Content (N = 124) Dimension (N = 18)

1 2 3 4 5 6 7 People/Things Data/Ideas Prestige

1. Prestige 1.00 �.12 �.06 .86**

2. Effort .72** 1.00 .11 �.19 .55**

3. Skill .66** .51* 1.00 .08 �.20 .50*

4. Effort + Skill .88** .82** .86** 1.00 .10 �.30 .82**

5. Competition .61** .51* .59** .66** 1.00 �.05 .02 .78**

6. Female associated �.03 �.07 .09 .07 .03 1.00 .42* .05 �.227. Male associated .06 .05 .11 .09 .07 �.72** 1.00 �.39 �.17 .19

* p < .05.** p < .01.

314 S.M. Sodano, T.J.G. Tracey / Journal of Vocational Behavior 73 (2008) 310–317

structure is only being generated to provide an added comparison of data covariation in this study, Exploratory Factor Anal-ysis (EFA) via PCA was used instead of Confirmatory Factor Analysis (CFA). Since the spherical model is not a simple structurewith zero off-dimension elements, it is not possible to specify a structure to test in a 4 dimensional CFA context (see Browne,1992, for a procedure for two dimensional circumplex testing in a CFA context). However, since PCA is an orthogonal lineartransformation that reduces the dimensionality of observed data utilizing the total variance (Gorsuch, 1983), it is well suitedfor data summary, thus it best served our purpose here. PCA was conducted on each item set (i.e., interest and competence)with four components extracted from each set. Guadagnoli and Velcier (1988) demonstrated that this sample size is appro-priate with the relatively small number of factors involved (i.e., four). To assess the accuracy of extracting this number ofcomponents in each item set, a parallel analysis (Horn, 1965) was conducted using 1000 randomly generated samples com-posed of the identical number of participants and items as the actual study. A parallel analysis is widely accepted as theempirical method for accurately determining the number of components to extract (Lautenschlager, 1989; Velicer, Eaton,& Fava, 2000; Zwick & Velicer, 1986). Mean Eigenvalues from the 95% band of confidence were obtained from the parallelanalysis and then compared to the actual Eigenvalues obtained for each item set. For both item sets, results indicated thatthe first four eigenvalues obtained in the actual analyses exceeded the mean Eigenvalues obtained at the 95% confidenceinterval in the parallel analysis. These results therefore supported extracting four components in both analyses.

The four components of the PCA for the activity interest ratings accounted for 48% of the variance and the four compo-nents of the PCA for the activity competence ratings accounted for 53% of the variance. In both analyses, the items loaded inline with expectations (i.e., each item loaded highly, greater than .40, on the factor(s) to which it was intended). These com-ponents mirrored the four components found in Tracey & Rounds (1996a), Tracey & Rounds (1996b) and Tracey (1997): thefirst component in each analysis was the General component, the second component was People-Things, the third was Data-Ideas, and the final component was Prestige. The correlations of the components are listed in the top half of Table 2. Thecomponents were unrelated within scale type (i.e., within interest or competence), as would be expected, and were highlycorrelated with similar scales on the other item types (i.e., between interest and competence). The general component cor-related .59 across the interest and competence items. Similar strong correlations were found only between correspondingcomponents in each item set: r = .79 for People-Things, r = .77 for Data-Ideas and r = .59 for Prestige.

This component structure served as the basis of the vector fitting procedure; however, instead of scale locations, the itemsthemselves were examined. The item locations on each of the components obtained above were correlated with each of thecontent validity rating means. Thus, the (N = 108) items located within these empirically derived PGI dimensions were cor-related in this analysis; as different from the 18 scale locations examined above in the theoretical analysis. These correlationsare presented in the bottom half of Table 2.

For the interest items, there were strong and significant positive correlations for the Prestige (r = .83, p < .01), Effort(r = .42, p < .01), Skill (r = .51, p < .01), and Competition (r = .63, p < .01) content scales with the fourth component (i.e., pres-tige). The sum of Effort and Skill had a greater correlation (r = .76, p < .01) with the prestige component than either Effort orSkill alone (.42 and .52, respectively). To statistically examine the value of the Effort and Skill composite over each singleaspect, a hierarchical regression was done with the fourth component loadings as the criterion and Skill and Effort entered

Table 2Correlations of interest and competence empirical item components from PCA with the validity content ratings (Expected relations underlined)

Component Component Content (N = 267)

Interest items (N = 108) Competence items (N = 108) 1 2 3 4 5 6 7

L1 L2 L3 L4 C1 C2 C3 C4

Activity items componentsGeneral (L1) 1People/things (L2) .00 1Data/ideas (L3) .00 .01 1Prestige (L4) .03 .00 .00 1

Self-efficacy items componentsGeneral (C1) .59** �.03 1.0 .06 1People/things (C2) .02 .79** .22 .03 �.08 1Data/ideas (C3) �.09 .17 .77** .08 .07 �.06 1Prestige (C4) �.06 .16 2.0 .59** .04 .05 .01 1

Content ratingsPrestige 20* .05 .09 .83** .13 �.07 �.1 .87** 1Effort .19 .07 �.18 .42** .11 .01 .02 .49** .62** 1Skill .23* �.06 �.27* .51** .17 .13 �.03 .45** .59** .42** 1Effort + skill .00 �.08 �.35** .76** .11 .09 .02 .80** .82** .76** .81** 1Competition .15 �.09 .00 .63** .06 �.01 �.03 .71** .76** .57** .62** .79** 1Female associated .11 .45** .13 �.11 .17 .29* �.05 �.19 .09 �.02 .03 �.05 -.09 1Male associated .08 �.37** .03 .12 1.0 �.35** .06 .20 .15 .08 .14 .12 .11 �.66** 1

* p < .05.** p < .01.

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as predictors in separate steps. Adding the second predictor significantly added to prediction, so the Skill-Effort compositewas a stronger predictor of the prestige component above each separately.

Sex-typing had small and non-significant correlations to the prestige component: female sex-typing (r = �.11, p > .05) andmale sex-typing (r = .12, p > .05). However, sex-typing was related to the second component, People-Things. The female asso-ciated ratings had medium and positive correlations (r = .45, p < .01), indicating that the people oriented items were viewedas being more feminine. The medium correlation for male sex-typing was also significant but negative (r = �.37, p < .01);items associated with more things orientation and less people orientation were viewed as more masculine.

Virtually identical results were obtained for the competence items. There were generally strong and positive significantcorrelations for the Prestige (r = .87, p < .01), Effort (r = .49, p < .01), Skill (r = .45, p < .01), and Competition (r = .71, p < .01)content scales with the fourth competence component. The sum of Effort and Skill was strongly related to the prestige com-ponent (r = .80, p < .01). Examination of the significance of using both over each alone was examined using hierarchicalregression, as above, and the addition of the second variable was significant. The aggregate of Effort and Skill was better thaneach alone and its magnitude was similar to that obtained by prestige.

There were small and non-significant correlations between the sex-typing content ratings and prestige (female sex-typ-ing r = .12, p > .05, male sex-typing r = .12, p > .05). Again, though, the sex-typing ratings had medium correlations with thesecond component (i.e., People-Things). The correlation for female sex-typing was r = .29 (p < .05), indicating that peopleitems were viewed as more feminine and things items as less feminine. The correlation for male sex-typing was the opposite,r = �.35 (p < .01). People items were viewed as less masculine and things items as more masculine.

4. Discussion

These results provide additional support for the validity of prestige as the construct underlying the fourth dimension ofthe PGI and provide further insight into its meaning within activity preferences. The prestige dimension was supported forboth the theoretical and empirical definitions of the PGI structure. The prestige content ratings of the activity items by stu-dents corresponded very highly with their placement in the PGI spherical structure. Across all analyses, the prestige ratingswere consistently highly related to the prestige dimension. Effort and Skill also were viewed as being highly related to pres-tige, but not to the same extent. Students see both the effort and the skill required to engage in different activities as relatedto prestige, but the combination of effort and skill was highly related to the prestige of activities. Thus, it appeared that thecombination of effort and skill are used by students in defining the prestige of everyday activities.

The similar findings for the prestige factor across both interest and competence activity item formats provide further sup-port for how prestige in activities is being defined. Therefore, irrespective of the format of ratings employed, students viewedthe activities as having similar content of prestige, effort and skill, and competition. They also responded consistently acrossformats in not relating sex-typing to prestige. In addition, the high correlation of competition with prestige helps put thescale into context. The students view prestige as being composed of competition to a similar extent as both effort and skill.Activities that require competition are viewed as higher in prestige. This finding of the prestige scale being related to com-petition enables the potential application of the PGI model to leisure research. Recent work examining the structure of lei-sure activity ratings by Hansen et al. (Hansen & Scullard, 2002; Hansen et al., 2008) has yielded the dimensions of artistic,instrumental, competitive, and social. Other than slight orientation differences, three of these are highly similar to the threePGI activity dimensions examined here. This similarity and especially the strong relation between competition and the pres-tige dimension makes it plausible to apply the PGI structure to both a vocational as well as a leisure set of activities. Certainlymore research is needed on the viability of the PGI structure on leisure activities, but this work is promising.

The prestige dimension was not related to sex-typing in any examination. There was a moderate relation of sex-typingfound by Tracey and Rounds (1996a) with regard to the occupations used in their initial proposal of the spherical model.It was not as great as prestige but it was still present. The lack of a relation of sex-typing for the activity items provides fur-ther support for prestige as being separate from and independent of sex-typing. There was clear sex-typing with respect tothe People-Things dimension. This is a common result in all interest inventories (e.g., ACT, 1995; Harmon et al., 1994; Hol-land, 1997; Lippa, 1998; Tracey, 2002). Men score higher on Things items and women score higher on People items. The PGIactivity items also manifest this pattern, but it is unrelated to prestige.

According to the spherical model of interests (Tracey & Rounds, 1996a), more variability is present within the prestigedimension relative to the Data-Ideas and People-Things dimensions at higher or lower levels of prestige. Conversely, morevariability is present in the Data-Ideas and People-Things dimensions at moderate or mid-range levels of prestige. The re-sults of this study extend knowledge about the spherical model of interests, and the PGI in particular, by providing furthervalidity support for the prestige dimension within activity interests and competencies while further clarifying the meaningof prestige within these contexts. Individuals view both their interest in and competency for activities not only from the Peo-ple-Things and Data-Ideas dimensions, with sex-typing being related to the People-Things dimension, but, as the sphericalmodel of interests predicts, from the perspective of the prestige inherent within them. Given the relation of prestige to thecombination of effort and skill along with competition, it can be said that the perception of prestige in activities is based onthe more common activity constructs of effort, skill and competition.

The findings presented here can be used to help clarify the meaning of prestige for clients found to score higher or loweron this dimension. Previously, interpretations of prestige that could be offered to these clients were limited to such factors as

316 S.M. Sodano, T.J.G. Tracey / Journal of Vocational Behavior 73 (2008) 310–317

social status, education level, or simply preference for higher or lower prestige. Vocational psychologists and career coun-selors can add effort and skill, as well as competition, as potential reasons for the high or low preference for prestige in activ-ities and occupations when interpreting the PGI. This new information can allow for richer discussions about how prestigemay influence these clients’ career choices.

An area for further clarification can be regarding the finding that lower prestige is associated with the view of a lowerlevel of effort and skill, which follows from the strong positive relation between prestige and effort and skill. Manual laborcan often require much effort, and perhaps to a lesser degree skill, so it is of interest to speculate on the nature of the effortand skill to which these samples are referring. Given that these were college students and the relation shown between occu-pational prestige and education level (Tracey & Rounds, 1996a; Tracey & Rounds, 1996b), it is likely that effort is not viewedas simply task effort, but may include other aspects of effort such as preparation involved and the ability to delay rewards orgratification. The kind of skill that is likely being associated with prestige is a complex and or high-level skill. However, thefact that effort and skill together relate highly to prestige and therefore low prestige activities are associated with both lowskill and effort warrants further exploration. Future research might also explore the relation between prestige and need forachievement, learning styles, and academic motivation, given the relation between prestige and education level. It may alsoprove fruitful to examine the characteristics of individuals that incur more extreme scores for prestige in either direction.

The results of this study further support the presence of prestige in the PGI and provide added interpretive support. Pres-tige is viewed by students as being related to the combination of effort and skill as well as competition. People thus do attendto the effort required and skill demonstrated in their evaluating the extent to which they prefer certain activities. Henceprestige can be said to underlie both occupational preference and activity items and is an implicit aspect of interestassessment.

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