Vocational and Leisure Interests

Abstract

Although much attention has been devoted to examining the measurement of vocational interests, much less attention has been directed to studying leisure interests, despite suggestions for incorporation of leisure interests into career counseling, particularly for college students. Furthermore, research on the relations between leisure and vocational interests highlights that some leisure interests are highly related to vocational interests, such as interests in Social, Artistic, and Realistic activities. To advance understanding on interests and the relations between leisure and vocational interests, the current study used Latent Profile Analysis, a novel approach to examining interest profiles that identifies groups of individuals with similar profiles. Support was found for seven different interest profiles in a sample of college students. Additionally, a number of mean differences on work values, work centrality, and personality traits among the seven profiles were examined.

Keywords

vocational interests leisure interests profiles latent profile analysis

Understanding individuals’ work preferences, or interests, has long been a central focus of career interventions (Larson, Bonitz, & Pesch, 2013). The plethora of scholarship on interests is not surprising, given the relation between vocational interests and other constructs (e.g., abilities, personality) as well as the relation of vocational interests to many career outcomes, such as job satisfaction, tenure, and performance (see Hansen, 2005 for review). While much attention has been focused on vocational interests, fewer efforts have been made to expand assessment of interests to incorporate assessment of leisure interests or preferences in activities for pleasure (Tinsley & Tinsley, 1982). While leisure interests may seem peripheral to career interventions, research suggests that leisure interests and leisure participation have implications for work attitudes. Several studies by Melamed and Meir (Meir & Melamed, 1986; Melamed & Meir, 1981; Melamed, Meir, & Samson, 1995) examined individuals with incongruent vocational choices (i.e., vocational choices that do not match their vocational interests or personality) and leisure activities congruent to their personalities and concluded that leisure participation can be beneficial and compensatory when work activities are inconsistent with one’s vocational interests. Miller (1991) found that engagement in leisure activities that are congruent with individuals’ personalities leads to higher work satisfaction for those with vocational choices that are incongruent with their vocational interests. Furthermore, Trenberth (2005) advised that engaging in leisure activities helps people cope with stress and sustains good attitudes, which may reduce negative outcomes of work-related stress. Therefore, participating in leisure activities congruent with one’s interests may improve an individual’s satisfaction with jobs that may be less congruent with her or his personality and also may lessen feelings of stress.

Many authors have noted the importance of assessing and incorporating leisure interests into career interventions, particularly with college students. During emerging adulthood, which occurs between the ages of 18 years and 25 years, establishing relationships with others, setting goals, and vocational development are the main foci (Arnett, 2000). Kleiber and Kelly (1980) concluded this developmental period is a crucial stage in vocational development because young adults are exposed to the process of vocational exploration and career planning, with much of this happening during the college experience. During this time as well, young adults are focused on social leisure activities, which not only allow them to find romantic partners but also allow opportunities to engage in occupational networking. Super (1957) also contended that leisure participation allows young adults to develop more realistic appraisals of work, increase their job skills, and expand potential career options to enhance their overall understanding of the world of work. Hendel and Harrold (2004) have echoed Super’s sentiments, suggesting that examining the leisure activities of college students is especially imperative because leisure activities encourage identity development, a crucial component of the personal and vocational growth of students.

Cuseo (2005) notes that the majority of college students have not solidified their vocational interests prior to college, which is supported by data on the stability of vocational interests that shows interests may fluctuate during young adulthood, a period that corresponds to the time many young adults are enrolled in college (Low, Yoon, Roberts, & Rounds, 2005). The instability of interests during this developmental stage ultimately may create challenges in finding a focus in college and committing to a major or career path or may lead to dropping out of college (Cuseo, 2005). Therefore, providing guidance on leisure interests and vocational interests simultaneously may encourage earlier exploration and awareness of vocational options and increase retention in higher learning institutions. Ultimately, many have suggested participation in leisure activities leads to development of vocational interests and job skills (Bloland, 1984; Hendel & Harrold, 2004) and have advocated that career counseling should include not only vocational counseling but also leisure counseling.

Despite the importance of understanding leisure interests and the call to incorporate leisure counseling into career interventions (Bloland, 1984; Bloland & Edwards, 1981; McDaniels, 1984), little attention has been devoted to fully understand the relations between leisure and vocational interests. Moreover, no research has examined interest profiles of individuals that include assessment of both leisure and vocational interests. Newer methodologies, however, may offer a fresh approach to understanding the relations between leisure and vocational interests. In particular, examining data at the person-centered level, or profile level, is made possible using Latent Profile Analysis (LPA). Also known as Latent Class Analysis (when used with categorical variables) or Mixture Modeling, LPA is analogous to cluster analysis except that groups are differentiated by latent, unobserved variables rather than observed variables. In other words, like cluster analysis, LPA is a statistical procedure that allows for the identification of different groups (i.e., classes) of individuals to be determined, given differences on latent variables. However, unlike cluster analyses, LPA offers the advantage of being able to use fit indices to assist with determining the number of groups to retain and the ability to compare the fit of different solutions (Nylund, Asparouhov, & Muthen, 2007).

Although only two studies have been identified that have used LPA with vocational interests (see Johnson & Bouchard, 2009; McLarnon, Carswell, & Schneider, 2014), LPA offers a unique way of examining possible underlying traits that explain profile differences in vocational and leisure interests. As Tay, Su, and Rounds (2011) note, person-centered approaches to studying interests may allow for different career interventions to be tailored to subgroups of clients given profile differences. Given this assumption, and the lack of research looking at interests holistically, we sought to investigate (a) the number of different interest profiles that summarized vocational and leisure interests and (b) the relations between these different profiles and other vocational constructs (e.g., work values, work centrality, and personality traits).

Vocational Interests

Scholarship on interests has focused almost exclusively on vocational or work preferences. As the most prominent theory on vocational interests, Holland’s (1997) theory asserted that one’s preferences for activities in the workplace can be summarized into six themes—Realistic, Investigative, Artistic, Social, Enterprising, and Conventional (RIASEC). Briefly, Holland (1997) describes that Realistic interests reflect appreciation of working with one’s hands, the outdoors, and mechanical and physical work. Investigative interests are typified by interests in science, medicine, and problem solving. An interest in creating or appreciating aesthetics, creativity, and language define Artistic interests. Social and Enterprising themes are both characterized by an interest in working with others; however, the Social theme captures a preference for working with others in a helping or teaching role, while the Enterprising theme is focused on persuading and leading others. Additionally, the Enterprising theme includes interests in business and entrepreneurial pursuits. Last, the Conventional theme is characterized by interests in numbers, organization, and office practices. The crux of Holland’s theory (1997) is that individuals are motivated to seek out environments that best match their constellation of interests and that this fit between a person and the work environment translates to increased job satisfaction.

Newer methods of studying interests have provided clarity on the relations between RIASEC themes by taking a person-centered rather than the traditional variable-centered approach. For instance, Tay et al. (2011) used cluster heat maps to cluster individuals by profile similarity on Realistic and Social interests (i.e., people/things). Their findings indicated that individuals’ profiles were clustered into groups that endorsed high Realistic interests and low Social interests, and vice versa, but also clusters of individuals who endorsed high or low interests in Realistic and Social interest independent of each other. Results of this study advanced research on interests by suggesting profile examination of interests may be important, as individuals’ particular constellation of interests may vary widely, despite having one theme, such as Realistic, being higher than others. Because the primary goal of Tay et al.’s (2011) study was to examine Prediger’s dimensions (i.e., Social vs. Realistic), data on other interest themes (e.g., I, A, E, and C) were not examined.

Recent research by McLarnon, Carswell, and Schneider (2014) has also examined interest scales using a person-centered approach. They used Basic Interest Scales (BISs) on the Jackson Career Explorer (Schermer, MacDougall, & Jackson, 2012) as markers of the RIASEC themes in a sample of college students and found support for eight different interest profiles. The first group contained individuals with high interests in Realistic, Artistic, and Conventional themes; the second had high interests in the Investigative theme, while the third group had high interests in Conventional and Enterprising themes. The fourth group had high Enterprising interests, with moderate interests in Social and Conventional areas. The fifth group had lower interests overall, with scores at or below the mean level on all RIASEC themes. Remaining groups included a group with high interests in Realistic, Investigative, and Artistic themes, a group with Artistic dominant interests, and a final group with neutral scores that had similar scores on all themes. McLarnon et al.’s findings suggest that many individuals’ interests are not typified by one dominate RIASEC theme, and moreover, that while some profiles may share the same theme as being the highest, they may differ in the magnitude of the remaining themes. However, some methodological issues with McLarnon and colleagues’ study may limit the generalizability of their findings. For instance, they note that the Jackson Career Explorer was not created to assess Holland’s RIASEC themes, while other measures, such as the Strong Interest Inventory (SII), have been noted as more psychometrically sound measures of these themes (Savickas, Taber, & Spokane, 2002). Additionally, their sample was largely comprised of women (78%), suggesting that studies using samples with more equal distributions of women and men are needed.

Leisure Interests

In contrast to vocational interests, research on leisure interests has been limited. Leisure has been defined as engagement in an activity for personal enjoyment, with the decision to participate in the activity as freely chosen (Tinsley & Tinsley, 1982). Research has shown that engagement in leisure activities relates to improved overall subjective well-being (see Newman, Tay, & Diener, 2014 for review), including improved physical and mental health (Iso-Ahola & Mannell, 2004).

Measurement of leisure interests has typically been challenging. Little attention has been devoted to their assessment, and psychometric data generally have been lacking for the few measures that are available (Frisbie, 1984). Assessment strategies for measuring leisure interests have varied as well. Some measures ask respondents to report engagement in different leisure activities or plans for future participation to assess leisure interests (McKechnie, 1975; Ragheb & Beard, 1992; Ritchie, 1975). This approach, noted by Hansen and Scullard (2002), may limit a respondent’s ability to express interest in a leisure activity due to not having engaged in the activity. An alternative approach measures leisure interests in a manner similar to the assessment of vocational interests by asking respondents if they like, are indifferent to, or dislike an activity, regardless of whether they have or plan to participate in the activity (Frisbie, 1984; Hansen & Scullard, 2002). This approach may be particularly beneficial in a counseling context, as suggestions for leisure participation can be discussed regardless of past participation in an activity.

Leisure and Vocational Interests

Researchers and scholars have hypothesized that leisure and vocational interests are mostly related. Holland (1997) explained that interests are stable personality traits and, as such, influence one’s preferences in both work and nonwork contexts and thus assumes one’s work and leisure interests should be highly correlated. Indeed, Cario (1979) found that vocational interests were predictive of engagement in similar leisure activities. However, research comparing vocational and leisure interests suggest, while the two are highly related, some leisure activities do not translate to work activities and vice versa (Gaudron & Vautier, 2007; Hansen & Scullard, 2002). Analysis of a contextualized measure of interests, where interest in the same activities were assessed in the context of family, leisure, or work, by Gaudron and Vautier (2007), found interests in some activities were highly consistent across contexts, such that high interests in Social activities in a work setting, for example, related to high Social interests in a leisure setting. However, interests in other areas were not consistent across contexts, such as interests in Enterprising and Conventional themes. Data from Hansen and Scullard (2002) support that leisure and vocational interests are highly related to correlations between scores on the Leisure Interest Questionnaire (LIQ) and the RIASEC themes measured on the SII (Harmon, Hansen, Borgen, & Hammer, 1994) reaching .77 in some instances, such as the relations between LIQ Building and Restoring scale and SII Realistic theme and LIQ Cultural Arts and the SII Artistic theme. Yet, they also found that some leisure activities, such as playing card games, partying, and travel, had little overlap with vocational interests. Thus, Hansen and Scullard advised that independent assessment of leisure and vocational interests may be preferable in research and practice settings.

Additional analysis of Hansen and Scullard’s (2002) data further illustrates the relations between leisure and vocational interests. Armstrong and Rounds (2008) used a property vector fitting statistical analysis to determine the placement of leisure interests on Holland’s RIASEC hexagon by reanalyzing the data from Hansen and Scullard (2002). Their results showed that most leisure interests were placed on the hexagon closest to the vocational interest area that would be assumed to be more similar (e.g., Building and Restoring leisure interests with Realistic vocational interests). They noted that in a few cases, however, the leisure interest scales were not oriented consistently with the RIASEC model. For instance, Camping and Outdoors were located closer to Investigative interests, and Sports leisure scales were located closer to Conventional interests rather than these leisure scales being more aligned with Realistic vocational interests, which include athletic and outdoor activities according to Holland’s (1997) theory. Little other research has examined the relations between vocational and leisure interests.

The Current Study

In light of the shortcomings of past research, the goals of the current study were to examine interests from a person-centered approach, adding much needed information about the relations between work and leisure interests. Furthermore, we expanded our study to examine the relations between other relevant variables and these interest profiles to inform career professionals’ conceptualization of different types of clients. As research on interest profiles is scant, we approached our study as exploratory, with few expectations about the number of different types of profiles that would be produced from the data using LPA, but generally expected that the profiles produced would partially replicate the findings of McLarnon and colleagues (2014) who found support for eight different vocational interest profiles. With the addition of leisure interests, it was expected that leisure interests that were highly similar to some areas of vocational interests would vary together. For instance, high interests in artistic and cultural leisure activities would be reflected in a group that also endorses high Artistic vocational interests. Similarly, we expected that groups with high Social vocational interests would also endorse high interests in social leisure activities, and interests in building or physical activities captured by Realistic vocational interests and interest in building, repairing, and physical leisure activities would vary together.

We made additional assumptions about the relations between possible profiles and our related constructs of interest in this study. We selected additional constructs that, similar to interests, have been found to be related to career outcomes such as job satisfaction, organizational commitment, and career choice (e.g., Eby, Freeman, Rush, & Lance, 1999; Judge & Bretz, 1992; Judge, Heller, & Mount, 2002), focusing on work values, work centrality, and personality. Moreover, examination of the relations between interest profiles and other variables can provide evidence of validity and further understanding on the nature of each profile group.

First, research on the relations between work values and vocational interests suggest that the two are related. While interests capture one’s preferences for activities, work values capture what one feels is important. Consistently, research has demonstrated support for the relations between Social interests and the importance of relationships at work and organizational culture (Hirschi, 2008; Leuty & Hansen, 2013; Smith & Campbell, 2009) and Enterprising interests and the importance of status (Leuty & Hansen, 2013; Rottinghaus & Zytowski, 2006; Super, 1962). Thus, we expected any subgroups that were typified by higher Social or Enterprising interests would replicate these patterns. The relations between leisure interests and work values have not been investigated.

Work centrality also was presumed to relate to interest profiles. Work centrality refers to the importance ascribed to the work role (Hirschfeld & Field, 2000; Paullay, Aliger, & Stone-Romero, 1994), in contrast to importance attributed to leisure or family roles. High work centrality has been found to relate to increased organizational commitment, job involvement, and job satisfaction (Hirschfeld & Field, 2000; Kanungo, 1982; Paullay et al., 1994). In a sample of employed adults, Hirschfeld and Field (2000) found a significant negative correlation between work centrality and leisure ethic, highlighting that those attributing more importance to the work role are likely to attribute less importance to leisure. No research has examined relations between interests and work centrality, however.

Empirically, interest and actual engagement in activities are related for both vocational interests/activities and leisure interest/activities. A main proposition of Holland’s (1997) theory of vocational choice is that individuals’ interests predict engagement in similar activities, or seeking environments with congruent interests, which has strong empirical support (see for review; Holland, 1997; Nauta, 2010). Additionally, data support the connection between leisure interests and leisure participation (Hansen & Scullard, 2002). Thus, we expected that work centrality would likely be higher for interest profiles where vocational interests were higher overall than leisure interests and lower for profiles where interests in leisure activities were substantially higher, given the likelihood that these individuals engaged in more leisure activities than work activities.

Finally, the last construct we examined in relation to interest profiles was personality. A large body of work has been devoted to research on the relations between vocational interests and personality. An updated meta-analysis by Mount, Barrick, Scullen, and Rounds (2005) on RIASEC interests and personality found a total of four correlations above .20; Openness and Artistic (ρ = .41), Extraversion and Enterprising (ρ = .40), Extraversion and Social (ρ = .29), and Openness and Investigative (ρ = .25). Furthermore, McLarnon and colleagues (2014) included in their investigation of the latent profiles of interests the relations between their eight interest groups and personality. While they found that the eight groups did not differ significantly on Agreeableness or Neuroticism, they found higher Conscientiousness scores for the group with higher Enterprising interests, higher Openness to Experience scores among those in the group with higher Enterprising interests and the Artistic dominate group, and slightly lower Extraversion scores for the group with dominant Investigative interests.

Research on the relations between leisure interests and personality is limited. Wilkinson and Hansen (2006) found that that Openness to Experience, measured by the NEO Personality Inventory–Revised (NEO PI-R; Costa & McCrae, 1985), positively correlated with cultural and artistic leisure interests, whereas Extraversion and Neuroticism were found to be positively correlated with leisure interests that involved social activities, such as socializing and partying. Other studies on the relationships between personality and leisure participation suggest that Extraversion may be related to sports or exercise participation (Courneya & Hellsten, 1998; Eysenck, Nias, & Cox, 1982; Hills & Argyle, 1998; Sale, Guppy, & El-Sayed, 2000). Given this, it was expected that Extraversion would be related to profiles that had dominant Social, Enterprising, or sports leisure interests, while Openness would be higher among those with higher artistic or creative leisure interests.

Method

Participants

The sample included 188 students at a large Midwestern university who were enrolled in a psychology course, for which they received partial class credit for their participation. The sample was comprised of slightly more women (61.0%) than men. Of the participants, 154 identified their ethnic background as White/European (82.4%) and 21 as Asian (11.2%). The remaining 12 participants identified their ethnicity as multicultural (3.2%), Black (2.1%), Hispanic (0.5%), or Pacific Islander (0.5%). Demographic data were missing for one participant. The average age of participants was 19.11 years (SD = 1.75 years), and the average number of years in college was 1.66 years (SD = 0.96).

Measures

LIQ

While few measures of leisure interests are available, the LIQ (Hansen, 1998) has been noted to be one of the more comprehensive assessments (Hansen & Scullard, 2002). The LIQ consists of 250 items pertaining to leisure activities that comprise 20 scales. Each item is rated on a three-point scale (like, indifferent, and dislike) that reflected the degree of interest in the various activities (e.g., snowboarding and stamp collecting) listed.

Through the use of exploratory factor analysis, Hansen and Scullard (2002) found that the 20 LIQ scales can be reduced to four categories, namely, athletic activities (e.g., individual sports, adventure sports, and team sports), artistic activities (e.g., cultural arts, dancing, literature and writing, and arts and crafts), social activities (e.g., socializing, partying, and community involvement), and outdoor activities (e.g., gardening and nature, camping, and outdoors). The consistency of the scale items (Median = .85), estimated with Cronbach’s α, resembles those of well-established measures of vocational interests, demonstrating the LIQ’s reliability (Hansen & Scullard, 2002). Evidence of validity was established, given positive correlations between the scales and similarly themed BISs of the SII, where correlations were greater than .45 (Hansen & Scullard, 2002).

SII

Vocational interests were measured using the Strong-Campbell Interest Inventory (SII; Campbell & Hansen, 1981). The SII provides information about a person’s interests to assist with career development using three categories of scales, namely, General Occupational Themes, Basic Interests Scales, and Occupational Scales. Participants were asked to rate each item on a three-point scale (like, indifferent, and dislike). Of note are the General Occupational Themes (GOTs) of the SII, which assess Holland’s (1997) six RIASEC themes. The GOTs are an overall assessment of one’s vocational interests and thus were used in this study. Estimates of internal reliability range from .84 (Enterprising) to .92 (Realistic; Harmon et al., 1994) for the GOTs, and supportive evidence of validity between the six types measured by the SII and six Vocational Preference Inventory types (Holland, 1985) has been found, given the high median correlation (r = .76) between scales across measures (Hansen, 1983).

International personality item pool

Personality was measured using 100 items from the International Personality Item Pool (IPIP; Goldberg, 1999), which were developed as an alternative to the NEO-PI (Costa & McCrae, 1985), to assess the Big Five personality factors (Openness to Experience, Conscientiousness, Extroversion, Agreeableness, and Neuroticism) using 20 items per scale. These factors are measured by asking participants to rate a series of statements describing various behaviors on a scale from one to five (1 = very inaccurate and 5 = very accurate) to assess how accurately each statement describes them. Goldberg (1999) found acceptable evidence of validity for IPIP scores, given significant correlations with the NEO-PI (Costa & McCrae, 1985). Internal consistency estimates (Cronbach’s α) for the current sample ranged from .88 (Openness) to .93 (Extraversion).

Work centrality

Twelve items developed by Paullay, Aliger, and Stone-Romero (1994) were used to assess the importance of the work role and its centrality in regard to one’s life roles. Items, such as “Life is only worth living when people get absorbed in work,” are endorsed on a 6-point scale (e.g., 1 = Strongly disagree to 6 = Strongly agree), with higher scores reflecting more importance attributed to the role of work. Paulley et al. provide supportive evidence of internal consistency (α = .80) and convergent validity, given significant correlations between their measure of work centrality and job involvement and Protestant Work Ethic. Hirschfeld and Field (2000) also found similar results comparing work centrality to measures of job involvement and Protestant Work Ethic and a negative relationship between work centrality and leisure ethic. Internal consistency for the current sample was acceptable (α = .80).

Work values

The Minnesota Importance Questionnaire (MIQ, paired-comparison version; Rounds, Henley, Dawis, Lofquist, & Weiss, 1981) was used to assess the work values of Achievement, Altruism, Autonomy Comfort, Safety, and Status for the current study. The MIQ is an instrument with statements representing 20 lower order needs being presented in all possible pairs to determine one’s values that comprise the six higher order values scales (Lofquist & Dawis, 1978). Scores are reported in z-scores, with positive scores indicating an importance for that value. The median profile stability of .87 found by Hendel and Weiss (1970) suggests acceptable evidence of reliability. Evidence of discriminant and convergent validity for MIQ scores provide support for construct validity (Leuty & Hansen, 2011).

Data Analyses

Because including all 20 LIQ scales, in addition to the six GOTs from the SII, in profile analyses would increase the probably of not converging on a solution or creating a solution that poorly classifies individuals into groups (Steinly & Brusco, 2011), the first step was to reduce the number of LIQ scales. To do this, we conducted an exploratory factor analysis with the 20 LIQ scales using unweighted least squares, with oblique rotation, replicating analyses by Hansen and Scullard (2002). Four factors were retained based on both Kaiser’s (1974) criterion of retaining factors with eigenvalues greater than 1 and examination of the scree plot. The four factors accounted for 57.27% of the variance (data available from the first author). The first factor captured interest in artistic or cultural activities (e.g., LIQ scales of Arts & Crafts, Gardening & Nature, Cultural Arts, Literature & Writing, Dancing, Shopping & Fashion, and Culinary Pursuits), the second factor was comprised of interests in competitive or instrumental activities (e.g., Computer Activities, Building & Restoring, Collecting, Hunting & Fishing, and Cards & Games scales), the third factor included outdoor or athletic interests (e.g., adventure sports, camping and outdoors, and individual sports), and the last factor captured interests in social activities (e.g., socializing, community involvement, partying, travel, and team sports LIQ scales). The highest loading LIQ scales for each factor were summed to create four new scales (arts, competitive, athletic, and social, respectively). The LIQ factor scores were converted to T scores so that both LIQ and SII data used for the latter analyses were on the same scale for easier interpretation of the results.

LPAs

LPA can be approached as both exploratory, when no a priori assumptions about the number resulting groups are made, and confirmatory, to confirm hypotheses about the types or number of profiles produced, given the fit of hypothesized models. Although LPA has been applied in prior research on vocational interests (Johnson & Bouchard, 2009; McLarnon et al., 2014) and we used these results to guide our expectations, we took an exploratory approach to determining the number of classes, given the novelty of this methodology with interest data. Because we were taking an exploratory approach, we examined models of groups ranging in number from 2 to 10.

As mentioned, an advantage of LPA over other person-centered approaches is the availability of fit indices to aid in determining the final number of profile groups. Available indices include the Akaike’s Information Criterion (Akaike, 1987), Bayesian Information Criterion (BIC; Schwarz, 1978), and adjusted BIC (aBIC; Sclove, 1987), which takes into account sample size. Simulation studies suggest that the aBIC is superior (Tofighi & Enders, 2008; Yang, 2006), with smaller values indicating a better fit of the model to the data. Although there is little guidance in the literature, most researchers use the aforementioned indices and the log likelihood ratio test (LRT), which is based on a χ² distribution, to determine the number of groups or classes that provides the best solution (Nylund, Asparouhov, & Muthén, 2007). However, as some have discussed, most models violate a χ² distribution, making the significance of the LRT unreliable or inaccurate (Geiser, 2013; Nylund et al., 2007). Therefore, Nylund, Asparouhov, and Muthén (2007) suggest use of the bootstrap likelihood test (BLRT; McLachlan & Peel, 2000) that compares the fit of a k class model to the fit of a k − 1 class solution (e.g., comparing the fit of an eight-group model with the fit of a seven-group model). Thus, Nylund and colleagues (2007) suggest the preferred method of deciding on the number of groups to retain is to choose the solution that has a significant (p < .05) BLRT, suggesting a better fit than the k − 1 model, and the lowest BIC and aBIC values. Furthermore, Geiser (2013) suggests that interpretability of the groups also should be considered when deciding on the final number of groups. In comparing different solutions, we used the BIC, aBIC, BLRT, and interpretability of the groups to determine the final number of groups to retain.

LPAs also assume conditional independence. In other words, the assumption is that indicator variables (i.e., interests) are not correlated within groups or classes, and instead group membership explains correlations among indicators. Violations of this assumption can result in solutions that contain a number of spurious groups to obtain acceptable indicators of fit (Lubke & Muthén, 2005). A number of authors have established that vocational interests are highly correlated, with a general factor accounting for 31% (Johnson & Bouchard, 2009) to 41% (Tay, Su, & Rounds, 2011) of the variance in interest scores, suggesting that interest data violate assumptions of conditional independence. Further, Hansen and Scullard’s data (2002) suggest correlations between SII and LIQ scores are high, and this is further supported, given bivariate correlations in the current study (Table 1). Therefore, a common factor model was estimated as a part of our LPA to account for these relationships. This approach is typically called factor mixture modeling or analysis (Lubke & Muthén, 2005) but is interpreted identically to traditional LPA models where a common factor, to account for correlations between indicators, is not included.

Table 1.
Descriptive Data on Study Variables.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

1 Realistic

2 Investigative .64

3 Artistic .33 .42

4 Social .28 .44 .36

5 Enterprising .44 .35 .24 .50

6 Conventional .57 .45 .15 .46 .74

7 LIQ Arts .15 .33 .71 .44 .17 .11

8 LIQ Competitive .71 .50 .23 .18 .34 .46 .23

9 LIQ Social .14 .32 .19 .51 .38 .27 .38 .36

10 LIQ Athletic .36 .38 .22 .32 .26 .20 .34 .50 .56

11 Achievement −.09 .11 .07 .01 −.04 −.09 .12 −.06 .13 .07

12 Comfort .01 .08 .03 .06 .06 .05 .10 .05 .10 .05 .56

13 Status −.04 .03 −.05 .02 .19 .03 −.03 .03 .19 .00 .55 .66

14 Altruism −.06 .19 .17 .26 −.11 −.11 .24 −.02 .23 .14 .48 .43 .23

15 Safety .08 .21 .12 .13 .14 .14 .21 .11 .23 .16 .44 .64 .43 .46

16 Autonomy .03 .13 .09 .00 .06 .00 .11 .10 .12 .14 .64 .64 .58 .34 .40

17 Work Centrality .11 .12 .00 .10 .06 .19 .09 .18 .06 .05 −.03 −.01 −.03 −.02 .06 .02

18 Conscientiousness −.13 −.03 −.08 −.09 .02 −.02 .05 .03 .19 .13 .09 −.01 .01 .00 .00 .07 .18

19 Neuroticism −.04 −.06 .08 −.01 −.06 −.04 .11 −.20 −.26 −.33 .00 .02 .07 −.04 .01 −.10 −.08 −.29

20 Extraversion −.10 −.02 .05 .08 .16 −.05 .06 .01 .39 .29 .14 .07 .08 .15 .12 .08 −.06 .19 −.47

21 Openness .06 .19 .60 −.03 −.02 −.09 .49 .10 .08 .11 .15 .07 .00 .16 .08 .16 −.04 .16 −.02 .21

22 Agreeableness −.24 −.07 .09 .13 −.15 −.18 .17 −.21 .15 .11 .16 .01 −.13 .34 .11 .03 −.08 .33 −.40 .29 .14

Mean 42.63 46.42 46.09 50.19 48.35 48.41 8.07 −5.49 28.17 19.51 1.37 .59 .76 1.15 .83 .78 34.96 73.09 49.89 74.46 71.15 75.47

SD 10.36 9.00 11.14 10.45 11.03 11.39 33.19 18.93 16.16 17.01 .63 .53 .70 .66 .58 .68 8.05 10.79 13.22 12.85 11.94 10.54

Note. For correlations above .14, p < .05, and for correlations above .19, p < .01.

The final analysis examined mean differences across the profiles on work values, work centrality, and personality. Similar to other researchers (McLarnon et al., 2014; Morin, Morizot, Boudrias, & Madore, 2011), we chose to examine the Wald’s χ² test of significance, which is based on the assumption of equal means for each variable across group profiles (see Asparouhouv & Muthén, 2007 for more technical information on this procedure). Larger values for the Wald’s test (and subsequently lower p values) indicate higher rejection of the assumption of equal means or an indication of significant mean differences on that variable across profiles.

Results

Descriptive data and correlations between study variables are presented in Table 1. A number of LPA solutions were conducted varying the number of groups ranging from 2 to 10 (see Table 2). Examining the fit indices across these different solutions, we found that the seven-group solution had the lowest BIC value (BIC = 13,553.37). Significance values for the BLRT suggested a significant improvement in the fit for each subsequent solution from the two- to seven-class models, but improvement in fit between models from eight to ten groups was not significant at the p < .01 level. Examination of the posterior probabilities of the seven-class solution, listed in Table 3, suggested that the different profiles were distinct, given the high probability of classification into one of the seven groups. Given these data, we decided that the seven-group solution was optimal.

Table 2.
Fit Indices of LPA Results for 2- to 10-Group Models.

Number of Groups

2 3 4 5 6 7 8 9 10

Entropy .81 .85 .84 .86 .89 .91 .91 .91 .92

Loglikelihood −6,706.99 −6,660.10 −6,624.18 −6,588.01 −6,558.80 −6,525.34 −6,507.09 −6,488.71 −6,470.49

AIC 13,495.98 13,424.20 13,374.35 13,324.02 13,287.60 13,242.67 13,228.17 13,213.41 13,198.99

BIC 13,628.67 13,592.50 13,578.25 13,563.52 13,562.69 13,553.37 13,574.47 13,595.31 13,616.49

Adjusted BIC 13,498.81 13,427.79 13,378.70 13,329.13 13,293.46 13,249.29 13,235.55 13,221.55 13,207.88

BLRT −6,783.31 −6,706.99 −6,660.10 −6,624.18 −6,588.01 −6,558.80 −6,525.34 −6,507.09 −6,488.71

BLRT p value .00 .00 .00 .00 .00 .00 .02 .02 .01

Note. AIC = Akaike’s Information Criterion; BIC = Bayesian Information Criterion; BLRT = bootstrap likelihood test; LIQ = Leisure Interest Questionnaire.

Table 3.
Average Posterior Probabilities of the Seven-Group Solution.

Group

1 2 3 4 5 6 7

1 .92 .01 .02 .01 .00 .02 .02

2 .01 .96 .00 .00 .02 .00 .01

3 .02 .00 .95 .01 .00 .00 .02

4 .02 .01 .00 .94 .02 .00 .01

5 .00 .00 .00 .05 .94 .00 .01

6 .03 .02 .01 .00 .00 .93 .01

7 .01 .00 .02 .02 .02 .00 .94

Note. Bold-faced values refer to average posterior probabilities for the group the individuals were assigned. Probabilities do not sum to 1 due to rounding.

Interpretation of the Seven Profiles

Means for each of the six RIASEC interests and the four leisure scales for each profile group are depicted in Figure 1. To assist with interpretation, we assigned a label to each of the different profiles. Profile labels were generated via consensus among the current authors and a group of five graduate students on the first author’s research team. Furthermore, interpretation of the profiles, and subsequent labeling, took into account the relative high- and low-interest areas endorsed. As well, the overall magnitude of interests was considered, given guidelines for interpreting the results of the SII GOTs (Campbell & Hansen, 1981), suggesting scores approximately half a standard deviation above and below the mean are considered in the average range (i.e., scores 45–55).

Figure 1.
Scores on Strong Interest Inventory (SII) and Leisure Interest Questionnaire (LIQ) scales for the seven-profile groups.

The first class was the largest (n = 44) and was comprised mostly of women (84.1% women). This profile was characterized by above-average Social vocational and leisure interests and labeled Socials. This class also reported low Realistic and Artistic vocational interests. The second profile was comprised of all men who had high Enterprising and Conventional SII scores and high LIQ Competitive interests, while reporting moderate SII Realistic interests and low-SII Artistic and LIQ Artistic interests. We labeled this profile Competitive Business. Comprised almost exclusively of women (n = 29, 96.6% women), Profile 3 was typified by higher SII Artistic and LIQ Arts interests and low SII Realistic interests and was assigned the name Artists. The fourth profile was the second largest class with 30 individuals and included slightly more women (76.7% women). This class was characterized by higher than average scores on all LIQ leisure scales, and reported average interests on all SII scales, except low Realistic interests. Given this group’s endorsement of more interest in leisure pursuits, they were labeled Leisurites. The fifth class (n = 21, 71.4% men) was defined by an overall elevated profile, as defined by endorsing all areas of interest above average (Hansen, 2000). In particular, this group reported very high Competitive leisure interests but also high Realistic vocational interests. Given this groups overall elevated profile, they were labeled the Enthusiasts group. The sixth profile group was the smallest class (n = 13) and included slightly more women (69.2% women). This class produced a mostly depressed profile. Despite this, however, the profile had defined interests in SII Enterprising and Conventional interests although only average. This group was labeled the Defined Business group to reflect this. The final profile group (n = 29) was labeled the Flat group, as flat profiles are defined by their endorsement of all interests in the average range (Hansen, 2000), although their highest interests were in Realistic, Investigative, and Artistic areas. This class reported lower interest in LIQ Social and Athletic activities, relative to other interest areas, and included slightly more men (62.1%) than women.

Relation of work values, work centrality, and personality to profile groups

Further analyses on the seven profile groups were conducted to examine how work values, work centrality, and personality related to each profile (see Table 4, and Figure 2). For scores on the MIQ, significant differences across profiles were only found for the value of Altruism (Wald’s χ² = 25.49, p < .01), with the Competitive Business group reporting the lowest importance of this value, being significantly lower than most other profile groups. The value of Achievement was highest for the Leisurite group and lowest among the Flat group, with the difference between these groups being significant as well as the mean difference between the next highest group, Socials and the Flat group, being significant. Status was only significantly different among Competitive Business and the Flat group, the groups with the highest and lowest endorsement of this value, respectively. The remaining values of Comfort, Safety, and Autonomy were endorsed equally across all profile groups.

Table 4.
Means for Each of the Seven-Profile Groups on Study Variables.

Socials Competitive Business Artists Leisurites Enthusiasts Defined Business Flat

% Women, % Men n = 44 n = 22 n = 29 n = 30 n = 21 n = 13 n = 29

84.1, 15.9 0, 100 96.6, 3.4 76.7, 23.3 28.6, 71.4 69.2, 30.8 37.9, 62.1 Global Wald’s χ²

Realistic 35.34 47.98 36.26 41.99 59.18 32.60 48.70

Investigative 43.55 44.80 42.28 49.06 55.32 38.80 50.43

Artistic 38.96 35.16 56.41 52.07 51.45 32.82 50.62

Social 52.88 46.31 49.31 50.64 53.26 44.34 50.49

Enterprising 45.91 56.32 45.90 45.34 52.24 50.04 47.86

Conventional 45.71 55.22 40.81 45.39 56.21 49.93 51.63

LIQ Arts 47.79 37.51 56.14 58.91 55.29 41.34 47.39

LIQ Competitive 42.13 56.47 40.79 57.12 65.21 40.14 51.52

LIQ Social 53.17 51.45 46.62 57.42 54.59 40.46 40.84

LIQ Athletic 51.49 53.65 44.76 58.48 56.09 31.09 45.38

Achievement 1.47^a 1.20^a,b 1.38^a,b 1.64^a 1.37^a,b 1.35^a,b 1.10^b 12.24

Comfort .62 .47 .43 .74 .74 .66 .50 9.10

Status .78^a,b .95^a .68^a,b .89^a,b .74^a,b .84^a,b .54^b 5.29

Altruism 1.28^a,c .78^b 1.11^a,b,c 1.44^a 1.28^a,c .98^a,b,c .95^b,c 25.49*

Safety .84 .69 .68 1.05 1.01 .82 .69 10.82

Autonomy .81 .73 .67 1.08 .84 .58 .61 7.97

Work Centrality 34.42^a,b 34.23^a,b 31.35^a 38.93^b 34.63^a,b 33.01^a,b 36.86^b 15.84

Conscientiousness 75.52^b 73.09^a,b 73.37^a,b 75.64^b 72.46^a,b 72.36^a,b 67.41^a 6.99

Neuroticism 48.17^b,c 44.47^b,c 56.73^a 44.38^b 49.47^a,b,c 57.20^a,c 52.58^a,c 20.73*

Extraversion 76.33^a 77.60^a 73.96^a,b 78.51^a 73.81^a,b 70.24^a,b 67.96^b 7.68

Openness 65.64^a,d 62.88^d 80.65^b 76.77^b,c 73.99^b,c 63.87^a 71.46^a,c 74.45*

Agreeableness 80.03^a 70.32^b 79.22^a,c 77.92^a,d 71.88^b,c,d 71.27^a,b,c 71.03^b 18.67*

Note. Means with different superscripts are significantly different (p < .01), while those sharing a superscript do not significantly differ. Interest scores are reported as t scores.

p < .01.

Figure 2.
Scores on work values, work centrality, and personality for each profile group. Note.* Scores were transformed to z-scores for easier interpretation.

Differences in the overall importance of the work role in one’s life, or work centrality, were not significant overall (Wald’s χ² = 15.84, p > .01). However, interestingly, work centrality was highest for the Leisurite group and lowest for the Artists who scored significantly lower than both the Leisurite and the Flat groups.

Finally, significant overall differences in mean scores were found for Neuroticism (Wald’s χ² = 20.73, p < .01), Openness (Wald’s χ² = 74.45, p < .01), and Agreeableness (Wald’s χ² = 18.67, p < .01). Comparisons between profile groups found significant mean differences in Neuroticism between Artists and a number of other groups (e.g., Socials, Competitive Business, and Leisurites), as Artists had the highest mean score on Neuroticism. The difference between Leisurites and the Flat profile group was also significant. Means for Openness across profile groups were the most variable. Openness was highest for the Artist profile group, being significantly higher than the Socials, Competitive Business, Defined Business, and Flat groups. The lowest group on Openness, which was Competitive Business, reported significantly lower Openness than Leisurites, Enthusiasts, and Flat profile groups. The Defined Business group, which was second lowest on Openness, also was significantly different from Artists and Leisurites. Agreeableness was highest for the Socials profile, being significantly different from Competitive Business, Enthusiasts, and Flat groups. The group lowest on Agreeableness, Competitive Business, was also significantly different from the groups of Artists and Leisurites. The difference between Leisurites and Flat groups on Agreeableness was also significant, with Leisurites scoring higher. Conscientiousness was lowest for the Flat profile group, which scored significantly lower than did the Socials and Leisurites groups. Last, there was a significant mean difference on Extraversion between groups endorsing the highest (Leisurites) and lowest (Flat) amount of this trait. The lowest on Extraversion, the Flat profile group, also scored significantly lower than the Socials and Competitive Business groups.

Discussion

Theories on the relations between work and leisure suggest that leisure may be an extension of one’s work and spillover across domains (Staines, 1980) or compensate for job dissatisfaction (Wilensky, 1960). Research, which has found that participation in congruent leisure activities may improve an individual’s job satisfaction in jobs that may be less congruent with her or his personality and possibly lessen stress (Meir & Melamed, 1986; Melamed et al., 1995; Melamed & Meir, 1981; Trenberth, 2005), as well as research suggesting that students with increased leisure participation report greater career exploration (Munson & Savickas, 1998), suggests attention to leisure participation may enhance career interventions. Thus, additional information that allows counselors ways to integrate both vocational and leisure interests may facilitate aiding clients to find environments to satisfy some, if not all, of their interests. Moreover, for college students, engaging in leisure activities may help build relationships with others, develop positive emotions, and acquire knowledge, skills, and abilities (Brajša-Žganec, Merkaš, & Šverko, 2011), which may subsequently lead to progress in identifying a career path (Bloland, 1984; Hendel & Harrold, 2004). Others (Armstrong & Rounds, 2008; Hendel & Harrold, 2004) have proposed that career counseling may be enhanced by integrating considerations of leisure into work considerations and may subsequently lead to more effective career counseling practices. The profile groups discerned in this study may provide additional information for counselors to help them offer a more holistic approach to career counseling (Tinsley & Tinsley, 1982).

Results of the current study found support for seven unique interest profiles. Comparison of the current results to the results by McLarnon et al (2014), which is the only other study using LPA on general vocational interests, suggests some consistency across studies, as four similar profiles were produced in both investigations. Although finding support for eight profiles, McLaron and colleagues found one group high in Enterprising and Conventional interests, similar to the Competitive Business group in this study, and also identified a group with dominate Artistic interests, similar to the Artists group. Their sample also produced a group with low interests overall, which was somewhat similar to the Defined Business group in the current study and another profile with a relatively neutral or flat profile. Given that leisure interests were included in the current study and thus used to form groups, it is noteworthy that these four vocational interest profiles were mostly replicated across studies.

The addition of leisure interests in the current study provides some initial insight into the relations between vocational interest profiles in conjunction with leisure interest profiles. For some groups, leisure interests appeared to be highly consistent with vocational interests, as was the case for the Socials and Artists, as anticipated. The Enthusiasts group, although reporting high interests overall, highest elevation was in Realistic vocational interests and Competitive leisure interests, which includes interest in a number of mechanical activities. Prior research on the relations between vocational and leisure interests has found that leisure interests relate highest to Social, Artistic, and Realistic vocational interests (Armstrong & Rounds, 2008) which supports the current findings. Furthermore, research by Gaudron and Vautier (2007) found that individuals express less consistency in interest for activities that fall within the Enterprising or Conventional areas across work and leisure contexts. Other profile groups appeared to express either more interest in vocational activities (Defined Business group) or leisure activities (e.g., Leisurites) overall.

The distribution of women and men across profile groups is also remarkable. A meta-analysis by Su, Rounds, and Armstrong (2009) reports that men have stronger Realistic and Investigative interests, while women report stronger Social, Artistic, and Conventional interests. The current results partially support this, finding more women than men with dominate Social and Artistic Profiles. While few gender differences in Enterprising interests have been found (Su et al., 2009), our results suggest that men’s patterns of interests in business pursuits may differ from women’s (e.g., Conventional Business versus Defined Business) and may be due to differences in interest in Realistic as well as competitive leisure activities that tend to be endorsed more by men (Twenge, 1999). Furthermore, the higher number of men placed in the Enthusiasts groups may be related to a similar pattern (e.g., higher Realistic and Competitive interests). Further research that focuses on examining gender differences in interests at the profile level may be useful in fully understanding how women’s and men’s interests may diverge in both vocational and leisure contexts.

Additional analyses on the differences between profile groups on personality traits, work values, and work centrality provide further evidence of external validity about the uniqueness of each profile. Mean differences between profile groups on work values were as predicted. Results confirmed higher importance in status for the Competitive Business group, which was highest in Enterprising interests, adding to the number of studies that have consistently found a relationship between Enterprising interests and the importance of status in one’s job (Leuty & Hansen, 2013, Rottinghaus & Zytowski, 2006; Super, 1962). The relationship between Social interests and values related to relationships or serving others has been established in prior research (Hirschi, 2008; Leuty & Hansen, 2013; Smith & Campbell, 2009). Our results found that the value of Altruism was higher for the Socials, Leisurites, and Enthusiasts groups. This partially confirms that those with higher Social profiles place more importance on altruistic values.

Differences in personality traits across the seven profile groups also were consistent with previous bivariate relationships. For instance, Openness has been found to relate to Artistic (Mount, Barrick, Scullen, & Rounds, 2005) and cultural leisure interests (Wilkinson & Hansen, 2006) and was supported in the current results. As predicted from previous studies (Courneya & Hellsten, 1998; Eysenck et al., 1982; Hills & Argyle, 1998; Sale et al., 2000; Wilkinson & Hansen, 2006), Extraversion was highest for profiles with dominate Social (e.g., Socials), Enterprising (Competitive Business), or overall high interests (Enthusiasts).

Relations between profiles and personality only partially replicate McLarnon and colleagues’ (2014) results, however. Both the current study and McLaron et al. found that group typified by higher Enterprising interests (i.e., Competitive Business) reported higher Extraversion, relative to other personality traits, and the profiles with dominant Artistic interests from both studies did report higher Openness and Neuroticism than most other groups. Finally, both studies found a group characterized by overall low interests. However, we found this profile to have lower Openness and higher Neuroticism, but this was not found by McLaron et al. It may be that differences in measurement, as different measures of personality and interests were utilized in each study, may have resulted in slightly different results in this regard. Additionally, assessment of leisure interests also may have affected these results. Further replication is needed to clarify these relationships.

Sample demographics may limit the generalizability of the results, as the sample was predominately White, although a number of researchers have documented little meaningful differences in interests across ethnic groups (Fouad, 2002; Fouad & Mohler, 2004). Nonetheless, research with more ethnically diverse samples is needed to confirm that profiles do not differ across ethnicity. Although there is support for the appropriateness of the current sample size, given the number of high-quality indicators (Wurpts & Geiser, 2014), replication with larger samples is suggested.

Theoretical Implications

The robustness of the four profiles of interests that were found by both McLarnon et al. (2014) and the current study inform theory about vocational interests. Despite Holland’s (1997) assumption that individuals’ profiles are likely dominated by one particular RIASEC theme, the current results only support profiles dominated by Social, Artistic, and Enterprising themes. The Enthusiasts group did report high Realistic interests relative to other areas of vocational interests but reported even higher leisure interests. No profiles emerged that replicated Holland’s remaining areas of interest (Conventional and Investigative). Additionally, profiles partially supported Prediger’s (1982) bipolar dimensions of People versus Things and Data versus Ideas, as support was found for individuals with high interests in People but lower in Things (Socials), and higher interests in either Ideas (Artists) or Data (Competitive Business). However, profiles that endorsed higher interests in Things, with low interest in People, were not found. In contrast, the remaining profiles supported Tay et al.’s (2011) research that Prediger’s dimensions may be unipolar, where Tay and colleagues examined clusters of individuals, given their interest in Realistic or Social themes, finding some individuals endorsed higher interests in both dimensions of People and Things or equal endorsement of both People and Things, as was found in the current study (Enthusiasts and Flat profiles, respectively).

Current findings also inform theory on leisure interests. Research by Hansen and Scullard (2002) and Hansen, Dik, and Zhou (2008) on the structure of leisure interests found that leisure interests may be bipolar, with one dimension reflecting an expressive instrumental dimension (e.g., LIQ Arts vs. LIQ Competitive). Examining the variations in the LIQ scales across profile groups partially supports this. For example, the LIQ Arts scale appeared to be higher when lower LIQ Competitive interests were reported and vice versa (e.g., Artists and Competitive Business profiles). Hansen and colleagues (2008) suggested a second dimension captured in LIQ scales that reflects interest in affiliative versus nonaffiliative activities. Modest support was found for this dimension, where interests were higher in either LIQ Social (i.e., affiliative) or LIQ Athletic or Competitive (nonaffiliative) areas. Our results suggest that, for some, all leisure themes are endorsed as being interesting (Leisurites profile) or uninteresting (Defined Business profile). Given the infancy of research on leisure interests, further examination of patterns of leisure interests are needed to inform theory in this area.

More importantly, the current results inform theory on individual differences. Findings suggest that some individuals endorse narrow areas of interest in similar activities, despite the context being work or nonwork, such as was found for socials and artists profiles. Additionally, results suggest that profiles may be most closely aligned to personality traits of Openness, Agreeableness, and Neuroticism. Research by Ackerman and Heggestad (1997) has furthered understanding of how people may vary on traits in a somewhat predictable fashion by providing evidence of four specific trait complexes, given their analysis and review of existing data. They found that Realistic and Investigative interests, along with math reasoning and visual perceptions abilities, form the science/math trait complex, whereas interests in Social and Enterprising themes, coupled with the personality traits of extraversion, social potency, and well-being, form a Social trait complex. Ackerman (2000) found support for three of these trait complexes—Social, Science/Math, and Intellectual/Cultural among a sample of college graduates, suggesting that there may be a common source that influences the development of individuals’ abilities, personality, and interests (Ackerman & Heggestad, 1997). Furthermore, Ackerman and Beier (2003) used Ackerman’s (2000) data to illustrate that these trait complexes varied as predicted with individuals’ reported college majors, such that Physical Science majors were highest on the Science/Math complex, whereas Arts and Humanities majors were highest on the Intellectual/Cultural complex, illustrating that these trait complexes have implications for career choice and development. Additional profile-level research, that ties together understanding on these trait complexes, may further inform theory on the relations between these constructs that support the validity of these trait complexes and their impact on life events, such as career choice.

Implications for Practice

Information about different profiles, comprised of both vocational and leisure interests, may enhance the ability of counselors to offer a more dynamic and holistic interpretation of clients’ interest patterns. This may also facilitate provision of more detailed feedback and assist with better identifying areas for further career and life planning interventions consistent with suggestions for interpreting interest assessment results (Hansen, 2000). For example, the profiles with clearly defined interests in Social, Artistic, and Business interests suggest these individuals have likely solidified their interests in these areas as their interests appear to be consistent across contexts. Despite this, career counseling may be helpful in identifying the particular opportunities, both vocationally and avocationally, which can provide satisfying experiences. Individuals presenting with these profiles who are not satisfied with their jobs may be counseled to find satisfaction through engagement in similar leisure activities (Melamed & Meir, 1981; Melamed et al., 1995).

The four remaining profiles, with less clearly defined interests, warrant further investigation. The Leisurite group, placed the most importance on the value of Achievement relative to other groups, endorsed that the role of work was of central importance more so than other groups and was highest on Conscientiousness, Extraversion, and Openness. It may be that this profile group is comprised of individuals who espouse a “work hard, play hard” attitude, and despite their increased interest in leisure activities over vocational activities, may be highly motivated to succeed in their careers. Research by Munson and Savickas (1998) supports this idea, finding that college students with higher leisure participation also reported higher career decision making. These individuals may need assistance with identifying occupations that meet their vocational interests but also allow time to pursue their leisure interests.

In contrast, the Defined Business profile group reported mostly low interests but endorsed the value of Achievement as the most important value compared to other values. Ironically, this group also attributed less importance of role of work yet had very low leisure interests and also endorsed higher amounts of Neuroticism and lower Openness. Researchers have shown that low profile elevation, similar to that of the Defined Business group, is related to increased depressive traits and Neuroticism and lower Extraversion and Openness (Bullock & Reardon, 2008). While not examined in the current study, in light of this previous research, a reasonable hypothesis is that individuals in the Defined Business group may experience more difficulty in the career development process, given their lowered interests and increased negative emotionality in contrast to other groups. These individuals may benefit from career interventions that incorporate leisure activities. Engaging these individuals in leisure activities may be a pathway to provide opportunities to solidify individuals’ identities (Hendel & Harrold, 2004) and be more open to exploring different career options. Moreover, given that Achievement was high for this group, having these individuals identify what types of tasks produce feelings of achievement may lead to identifying areas for further leisure and career exploration.

The Enthusiasts reported higher interests in most vocational and leisure activities, producing an overall elevated profile. Opposite of findings with low profiles, high profiles have been shown to relate to increased Openness and Conscientiousness (Bullock & Reardon, 2008), which was partially found in the current study and lower depressive thinking (Fuller, Holland, & Johnston, 1999). Swanson and Hansen (1986) found that college students with elevated profiles, although flat with respect to differences in the magnitude of scales, reported higher college grade point averages and greater persistence in college. Given their high interests in many areas, these individuals may need career assistance with solidifying a career choice, as they likely have considered a number of different options. Integrating information about this group’s top work values (Achievement, Altruism, and Safety) into counseling may be helpful in narrowing career options to occupations that may match both their interests and their values.

Finally, the Flat profile group may signal individuals who need more assistance with identifying educational and career options in college. In a longitudinal study by Sackett and Hansen (1995), they found that women with flat vocational interest profiles, measured at their freshman year in college, reported less certainty about selecting a college major and a career choice at the time. However, reassessment of career certainty 12 years later suggested similar levels of certainty about one’s career choice between individuals with flat profiles and women with more differentiated profiles as well as similar levels of job satisfaction between both groups. Additionally, men in their sample with flat profiles reported higher job satisfaction than men with more differentiated profiles, suggesting having many interests at a similar magnitude may allow for greater flexibility in selecting a career that is congruent with one’s interests. In light of their endorsement of low Conscientiousness and lower desire for Achievement relative to other groups, individuals in the Flat group may be more likely to not have made career plans. Thus, individuals in this group may need more assistance with immediate career choices, such as selecting a major rather than articulating long-term career goals. Discussing and encouraging leisure participation with these individuals, particularly in more competitive or solitary activities, may provide opportunities for these individuals to further explore their interests.

In sum, provision of more profile data on interests and their relation to relevant career constructs can facilitate more meaningful conceptualizations of clients. Additional research that examines other characteristics that may relate to each unique profile, such as career decision-making or job or leisure satisfaction, may provide important information about career development issues particular to each profile group.

	Number of Groups
Entropy	.81	.85	.84	.86	.89	.91	.91	.91	.92
Loglikelihood	−6,706.99	−6,660.10	−6,624.18	−6,588.01	−6,558.80	−6,525.34	−6,507.09	−6,488.71	−6,470.49
AIC	13,495.98	13,424.20	13,374.35	13,324.02	13,287.60	13,242.67	13,228.17	13,213.41	13,198.99
BIC	13,628.67	13,592.50	13,578.25	13,563.52	13,562.69	13,553.37	13,574.47	13,595.31	13,616.49
Adjusted BIC	13,498.81	13,427.79	13,378.70	13,329.13	13,293.46	13,249.29	13,235.55	13,221.55	13,207.88
BLRT	−6,783.31	−6,706.99	−6,660.10	−6,624.18	−6,588.01	−6,558.80	−6,525.34	−6,507.09	−6,488.71
BLRT p value	.00	.00	.00	.00	.00	.00	.02	.02	.01

	Group
1	.92	.01	.02	.01	.00	.02	.02
2	.01	.96	.00	.00	.02	.00	.01
3	.02	.00	.95	.01	.00	.00	.02
4	.02	.01	.00	.94	.02	.00	.01
5	.00	.00	.00	.05	.94	.00	.01
6	.03	.02	.01	.00	.00	.93	.01
7	.01	.00	.02	.02	.02	.00	.94

	Socials	Competitive Business	Artists	Leisurites	Enthusiasts	Defined Business	Flat
Realistic	35.34	47.98	36.26	41.99	59.18	32.60	48.70
Investigative	43.55	44.80	42.28	49.06	55.32	38.80	50.43
Artistic	38.96	35.16	56.41	52.07	51.45	32.82	50.62
Social	52.88	46.31	49.31	50.64	53.26	44.34	50.49
Enterprising	45.91	56.32	45.90	45.34	52.24	50.04	47.86
Conventional	45.71	55.22	40.81	45.39	56.21	49.93	51.63
LIQ Arts	47.79	37.51	56.14	58.91	55.29	41.34	47.39
LIQ Competitive	42.13	56.47	40.79	57.12	65.21	40.14	51.52
LIQ Social	53.17	51.45	46.62	57.42	54.59	40.46	40.84
LIQ Athletic	51.49	53.65	44.76	58.48	56.09	31.09	45.38
Achievement	1.47^a	1.20^a,b	1.38^a,b	1.64^a	1.37^a,b	1.35^a,b	1.10^b	12.24
Comfort	.62	.47	.43	.74	.74	.66	.50	9.10
Status	.78^a,b	.95^a	.68^a,b	.89^a,b	.74^a,b	.84^a,b	.54^b	5.29
Altruism	1.28^a,c	.78^b	1.11^a,b,c	1.44^a	1.28^a,c	.98^a,b,c	.95^b,c	25.49*
Safety	.84	.69	.68	1.05	1.01	.82	.69	10.82
Autonomy	.81	.73	.67	1.08	.84	.58	.61	7.97
Work Centrality	34.42^a,b	34.23^a,b	31.35^a	38.93^b	34.63^a,b	33.01^a,b	36.86^b	15.84
Conscientiousness	75.52^b	73.09^a,b	73.37^a,b	75.64^b	72.46^a,b	72.36^a,b	67.41^a	6.99
Neuroticism	48.17^b,c	44.47^b,c	56.73^a	44.38^b	49.47^a,b,c	57.20^a,c	52.58^a,c	20.73*
Extraversion	76.33^a	77.60^a	73.96^a,b	78.51^a	73.81^a,b	70.24^a,b	67.96^b	7.68
Openness	65.64^a,d	62.88^d	80.65^b	76.77^b,c	73.99^b,c	63.87^a	71.46^a,c	74.45*
Agreeableness	80.03^a	70.32^b	79.22^a,c	77.92^a,d	71.88^b,c,d	71.27^a,b,c	71.03^b	18.67*

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

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	Group
	1	2	3	4	5	6	7
1	.92	.01	.02	.01	.00	.02	.02
2	.01	.96	.00	.00	.02	.00	.01
3	.02	.00	.95	.01	.00	.00	.02
4	.02	.01	.00	.94	.02	.00	.01
5	.00	.00	.00	.05	.94	.00	.01
6	.03	.02	.01	.00	.00	.93	.01
7	.01	.00	.02	.02	.02	.00	.94

	Socials	Competitive Business	Artists	Leisurites	Enthusiasts	Defined Business	Flat
% Women, % Men	n = 44	n = 22	n = 29	n = 30	n = 21	n = 13	n = 29
% Women, % Men	84.1, 15.9	0, 100	96.6, 3.4	76.7, 23.3	28.6, 71.4	69.2, 30.8	37.9, 62.1	Global Wald’s χ²
Realistic	35.34	47.98	36.26	41.99	59.18	32.60	48.70
Investigative	43.55	44.80	42.28	49.06	55.32	38.80	50.43
Artistic	38.96	35.16	56.41	52.07	51.45	32.82	50.62
Social	52.88	46.31	49.31	50.64	53.26	44.34	50.49
Enterprising	45.91	56.32	45.90	45.34	52.24	50.04	47.86
Conventional	45.71	55.22	40.81	45.39	56.21	49.93	51.63
LIQ Arts	47.79	37.51	56.14	58.91	55.29	41.34	47.39
LIQ Competitive	42.13	56.47	40.79	57.12	65.21	40.14	51.52
LIQ Social	53.17	51.45	46.62	57.42	54.59	40.46	40.84
LIQ Athletic	51.49	53.65	44.76	58.48	56.09	31.09	45.38
Achievement	1.47^a	1.20^a,b	1.38^a,b	1.64^a	1.37^a,b	1.35^a,b	1.10^b	12.24
Comfort	.62	.47	.43	.74	.74	.66	.50	9.10
Status	.78^a,b	.95^a	.68^a,b	.89^a,b	.74^a,b	.84^a,b	.54^b	5.29
Altruism	1.28^a,c	.78^b	1.11^a,b,c	1.44^a	1.28^a,c	.98^a,b,c	.95^b,c	25.49*
Safety	.84	.69	.68	1.05	1.01	.82	.69	10.82
Autonomy	.81	.73	.67	1.08	.84	.58	.61	7.97
Work Centrality	34.42^a,b	34.23^a,b	31.35^a	38.93^b	34.63^a,b	33.01^a,b	36.86^b	15.84
Conscientiousness	75.52^b	73.09^a,b	73.37^a,b	75.64^b	72.46^a,b	72.36^a,b	67.41^a	6.99
Neuroticism	48.17^b,c	44.47^b,c	56.73^a	44.38^b	49.47^a,b,c	57.20^a,c	52.58^a,c	20.73*
Extraversion	76.33^a	77.60^a	73.96^a,b	78.51^a	73.81^a,b	70.24^a,b	67.96^b	7.68
Openness	65.64^a,d	62.88^d	80.65^b	76.77^b,c	73.99^b,c	63.87^a	71.46^a,c	74.45*
Agreeableness	80.03^a	70.32^b	79.22^a,c	77.92^a,d	71.88^b,c,d	71.27^a,b,c	71.03^b	18.67*

	Group
	1	2	3	4	5	6	7
1	.92	.01	.02	.01	.00	.02	.02
2	.01	.96	.00	.00	.02	.00	.01
3	.02	.00	.95	.01	.00	.00	.02
4	.02	.01	.00	.94	.02	.00	.01
5	.00	.00	.00	.05	.94	.00	.01
6	.03	.02	.01	.00	.00	.93	.01
7	.01	.00	.02	.02	.02	.00	.94

	Group
	1	2	3	4	5	6	7
1	.92	.01	.02	.01	.00	.02	.02
2	.01	.96	.00	.00	.02	.00	.01
3	.02	.00	.95	.01	.00	.00	.02
4	.02	.01	.00	.94	.02	.00	.01
5	.00	.00	.00	.05	.94	.00	.01
6	.03	.02	.01	.00	.00	.93	.01
7	.01	.00	.02	.02	.02	.00	.94