Article

Vocational and Leisure Interests:A Profile-Level Approach toExamining Interests

Melanie E. Leuty1, Jo-Ida C. Hansen2, and Stormy Z. Speaks1

AbstractAlthough 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 incor-poration of leisure interests into career counseling, particularly for college students. Furthermore,research on the relations between leisure and vocational interests highlights that some leisureinterests are highly related to vocational interests, such as interests in Social, Artistic, and Realisticactivities. To advance understanding on interests and the relations between leisure and vocationalinterests, the current study used Latent Profile Analysis, a novel approach to examining interestprofiles that identifies groups of individuals with similar profiles. Support was found for seven dif-ferent interest profiles in a sample of college students. Additionally, a number of mean differences onwork values, work centrality, and personality traits among the seven profiles were examined.

Keywordsvocational 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, per-

sonality) as well as the relation of vocational interests to many career outcomes, such as job satis-

faction, 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. Sev-

eral studies by Melamed and Meir (Meir & Melamed, 1986; Melamed & Meir, 1981; Melamed,

1 Department of Psychology, University of Southern Mississippi, Hattiesburg, MS, USA2 University of Minnesota, Minneapolis, MN, USA

Corresponding Author:

Melanie E. Leuty, Department of Psychology, University of Southern Mississippi, 118 College Dr. #5025, Hattiesburg,

MS 39406, USA.

Email: melanie.leuty@usm.edu

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Meir, & Samson, 1995) examined individuals with incongruent vocational choices (i.e., voca-

tional 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 com-

pensatory 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 voca-

tional 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 per-

sonality 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 occu-

pational 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 compo-

nent 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 simul-

taneously 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 coun-

seling 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 vari-

ables rather than observed variables. In other words, like cluster analysis, LPA is a statistical pro-

cedure 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

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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 inter-

ests. 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 differ-

ences. 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 prefer-

ences 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 oth-

ers; 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 Conven-

tional 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 Rea-

listic 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. Rea-

listic), 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

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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 trans-

late to work activities and vice versa (Gaudron & Vautier, 2007; Hansen & Scullard, 2002). Anal-

ysis 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 Conven-

tional 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

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.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 voca-

tional 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 fit-

ting statistical analysis to determine the placement of leisure interests on Holland’s RIASEC hexa-

gon 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 voca-

tional 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 inter-

ests 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’ concep-

tualization 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 inter-

est 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, examina-

tion 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 impor-

tance 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

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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 satis-

faction (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 central-

ity 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 inter-

est profiles where vocational interests were higher overall than leisure interests and lower for pro-

files 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 per-

sonality. 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

(r ¼ .41), Extraversion and Enterprising (r ¼ .40), Extraversion and Social (r ¼ .29), and Open-

ness and Investigative (r ¼ .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 relation-

ships 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 psy-

chology course, for which they received partial class credit for their participation. The sample was

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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 parti-

cipants 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 partici-

pants was 19.11 years (SD ¼ 1.75 years), and the average number of years in college was 1.66

years (SD ¼ 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 activ-

ities (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 ¼ .85), estimated with Cronbach’s a, 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 Inter-

ests 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 evi-

dence of validity between the six types measured by the SII and six Vocational Preference Inven-

tory types (Holland, 1985) has been found, given the high median correlation (r ¼ .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 Expe-

rience, 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 ¼ very inaccurate and 5 ¼ very accurate) to

assess how accurately each statement describes them. Goldberg (1999) found acceptable evi-

dence of validity for IPIP scores, given significant correlations with the NEO-PI (Costa &

McCrae, 1985). Internal consistency estimates (Cronbach’s a) 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

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‘‘Life is only worth living when people get absorbed in work,’’ are endorsed on a 6-point scale (e.g.,

1 ¼ Strongly disagree to 6 ¼ Strongly agree), with higher scores reflecting more importance attrib-

uted to the role of work. Paulley et al. provide supportive evidence of internal consistency (a ¼ .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 (a ¼ .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 Achieve-

ment, Altruism, Autonomy Comfort, Safety, and Status for the current study. The MIQ is an instru-

ment 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 clas-

sifies 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 ath-

letic interests (e.g., adventure sports, camping and outdoors, and individual sports), and the last fac-

tor 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

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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 w2 distribution, to determine the number of groups or classes that provides the best solution

(Nylund, Asparouhov, & Muthen, 2007). However, as some have discussed, most models violate

a w2 distribution, making the significance of the LRT unreliable or inaccurate (Geiser, 2013; Nylund

et al., 2007). Therefore, Nylund, Asparouhov, and Muthen (2007) suggest use of the bootstrap like-

lihood 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 num-

ber 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 interpret-

ability 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 & Muthen,

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 condi-

tional 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

& Muthen, 2005) but is interpreted identically to traditional LPA models where a common factor, to

account for correlations between indicators, is not included.

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 w2 test of significance, which is based on the

assumption of equal means for each variable across group profiles (see Asparouhouv & Muthen,

2007 for more technical information on this procedure). Larger values for the Wald’s test (and sub-

sequently 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 ¼ 13,553.37). Significance values for the BLRT suggested a signif-

icant 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.

Leuty et al. 9

at UNIV OF SOUTHERN MISSISSIPPI on April 16, 2015jca.sagepub.comDownloaded from

Tab

le1.

Des

crip

tive

Dat

aon

Study

Var

iable

s.

12

34

56

78

910

11

12

13

14

15

16

17

18

19

20

21

22

1R

ealis

tic

2In

vest

igat

ive

.64

3A

rtis

tic

.33

.42

4So

cial

.28

.44

.36

5Ente

rpri

sing

.44

.35

.24

.50

6C

onve

ntional

.57

.45

.15

.46

.74

7LI

QA

rts

.15

.33

.71

.44

.17

.11

8LI

QC

om

pet

itiv

e.7

1.5

0.2

3.1

8.3

4.4

6.2

39

LIQ

Soci

al.1

4.3

2.1

9.5

1.3

8.2

7.3

8.3

610

LIQ

Ath

letic

.36

.38

.22

.32

.26

.20

.34

.50

.56

11

Ach

ieve

men

t�

.09

.11

.07

.01�

.04�

.09

.12�

.06

.13

.07

12

Com

fort

.01

.08

.03

.06

.06

.05

.10

.05

.10

.05

.56

13

Stat

us

�.0

4.0

3�

.05

.02

.19

.03�

.03

.03

.19

.00

.55

.66

14

Altru

ism

�.0

6.1

9.1

7.2

6�

.11�

.11

.24�

.02

.23

.14

.48

.43

.23

15

Safe

ty.0

8.2

1.1

2.1

3.1

4.1

4.2

1.1

1.2

3.1

6.4

4.6

4.4

3.4

616

Auto

nom

y.0

3.1

3.0

9.0

0.0

6.0

0.1

1.1

0.1

2.1

4.6

4.6

4.5

8.3

4.4

017

Work

Cen

tral

ity

.11

.12

.00

.10

.06

.19

.09

.18

.06

.05�

.03�

.01�

.03�

.02

.06

.02

18

Consc

ientiousn

ess�

.13�

.03�

.08�

.09

.02�

.02

.05

.03

.19

.13

.09�

.01

.01

.00

.00

.07

.18

19

Neu

rotici

sm�

.04�

.06

.08�

.01�

.06�

.04

.11�

.20�

.26�

.33

.00

.02

.07�

.04

.01�

.10�

.08�

.29

20

Extr

aver

sion

�.1

0�

.02

.05

.08

.16�

.05

.06

.01

.39

.29

.14

.07

.08

.15

.12

.08�

.06

.19�

.47

21

Open

nes

s.0

6.1

9.6

0�

.03�

.02�

.09

.49

.10

.08

.11

.15

.07

.00

.16

.08

.16�

.04

.16�

.02

.21

22

Agr

eeab

lenes

s�

.24�

.07

.09

.13�

.15�

.18

.17�

.21

.15

.11

.16

.01�

.13

.34

.11

.03�

.08

.33�

.40

.29

.14

Mea

n42.6

346.4

246.0

950.1

948.3

548.4

18.0

7�

5.4

928.1

719.5

11.3

7.5

9.7

61.1

5.8

3.7

834.9

673.0

949.8

974.4

671.1

575.4

7SD

10.3

69.0

011.1

410.4

511.0

311.3

933.1

918.9

316.1

617.0

1.6

3.5

3.7

0.6

6.5

8.6

88.0

510.7

913.2

212.8

511.9

410.5

4

Not

e.Fo

rco

rrel

atio

ns

above

.14,p

<.0

5,an

dfo

rco

rrel

atio

ns

above

.19,p

<.0

1.

10

at UNIV OF SOUTHERN MISSISSIPPI on April 16, 2015jca.sagepub.comDownloaded from

Tab

le2.

Fit

Indic

esofLP

AR

esults

for

2-

to10-G

roup

Model

s.

Num

ber

ofG

roups

23

45

67

89

10

Entr

opy

.81

.85

.84

.86

.89

.91

.91

.91

.92

Logl

ikel

ihood

�6,7

06.9

9�

6,6

60.1

0�

6,6

24.1

8�

6,5

88.0

1�

6,5

58.8

0�

6,5

25.3

4�

6,5

07.0

9�

6,4

88.7

1�

6,4

70.4

9A

IC13,4

95.9

813,4

24.2

013,3

74.3

513,3

24.0

213,2

87.6

013,2

42.6

713,2

28.1

713,2

13.4

113,1

98.9

9BIC

13,6

28.6

713,5

92.5

013,5

78.2

513,5

63.5

213,5

62.6

913,5

53.3

713,5

74.4

713,5

95.3

113,6

16.4

9A

dju

sted

BIC

13,4

98.8

113,4

27.7

913,3

78.7

013,3

29.1

313,2

93.4

613,2

49.2

913,2

35.5

513,2

21.5

513,2

07.8

8BLR

T�

6,7

83.3

1�

6,7

06.9

9�

6,6

60.1

0�

6,6

24.1

8�

6,5

88.0

1�

6,5

58.8

0�

6,5

25.3

4�

6,5

07.0

9�

6,4

88.7

1BLR

Tp

valu

e.0

0.0

0.0

0.0

0.0

0.0

0.0

2.0

2.0

1

Not

e.A

IC¼

Aka

ike’

sIn

form

atio

nC

rite

rion;BIC¼

Bay

esia

nIn

form

atio

nC

rite

rion;BLR

T¼

boots

trap

likel

ihood

test

;LI

Q¼

Leis

ure

Inte

rest

Ques

tionnai

re.

11

at UNIV OF SOUTHERN MISSISSIPPI on April 16, 2015jca.sagepub.comDownloaded from

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 pro-

files, 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 inter-

preting 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).

The first class was the largest (n ¼ 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 sec-

ond 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 ¼ 29, 96.6% women), Profile 3 was typified by higher SII Artis-

tic 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 ¼ 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 Com-

petitive leisure interests but also high Realistic vocational interests. Given this groups overall ele-

vated profile, they were labeled the Enthusiasts group. The sixth profile group was the smallest

class (n ¼ 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 ¼ 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.

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 .022 .01 .96 .00 .00 .02 .00 .013 .02 .00 .95 .01 .00 .00 .024 .02 .01 .00 .94 .02 .00 .015 .00 .00 .00 .05 .94 .00 .016 .03 .02 .01 .00 .00 .93 .017 .01 .00 .02 .02 .02 .00 .94

Note. Bold-faced values refer to average posterior probabilities for the group the individuals were assigned. Probabilities donot sum to 1 due to rounding.

12 Journal of Career Assessment

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303540455055606570

Soci

als

303540455055606570

Com

petit

ive

Bus

ines

s

303540455055606570

Arti

sts

303540455055606570

Leis

urite

s

303540455055606570

Enth

usia

sts

303540455055606570

Def

ined

Bus

ines

s

303540455055606570

Flat

Fig

ure

1.

Score

son

Stro

ng

Inte

rest

Inve

nto

ry(S

II)

and

Leis

ure

Inte

rest

Ques

tionnai

re(L

IQ)

scal

esfo

rth

ese

ven-p

rofil

egr

oups.

13

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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 w2¼ 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.

Differences in the overall importance of the work role in one’s life, or work centrality, were not

significant overall (Wald’s w2¼ 15.84, p > .01). However, interestingly, work centrality was high-

est 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 w2 ¼ 20.73, p < .01), Openness (Wald’s w2 ¼ 74.45, p < .01), and Agreeableness (Wald’s

w2 ¼ 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 Lei-

surites 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. Conscien-

tiousness 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 low-

est 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 person-

ality 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 partic-

ipation report greater career exploration (Munson & Savickas, 1998), suggests attention to leisure

participation may enhance career interventions. Thus, additional information that allows counse-

lors 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

14 Journal of Career Assessment

at UNIV OF SOUTHERN MISSISSIPPI on April 16, 2015jca.sagepub.comDownloaded from

Tab

le4.

Mea

ns

for

Eac

hofth

eSe

ven-P

rofil

eG

roups

on

Study

Var

iable

s.

Soci

als

Com

pet

itiv

eBusi

nes

sA

rtis

tsLe

isuri

tes

Enth

usi

asts

Def

ined

Busi

nes

sFl

at

%W

om

en,%

Men

n¼

44

n¼

22

n¼

29

n¼

30

n¼

21

n¼

13

n¼

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

Glo

bal

Wal

d’sw2

Rea

listic

35.3

447.9

836.2

641.9

959.1

832.6

048.7

0In

vest

igat

ive

43.5

544.8

042.2

849.0

655.3

238.8

050.4

3A

rtis

tic

38.9

635.1

656.4

152.0

751.4

532.8

250.6

2So

cial

52.8

846.3

149.3

150.6

453.2

644.3

450.4

9Ente

rpri

sing

45.9

156.3

245.9

045.3

452.2

450.0

447.8

6C

onve

ntional

45.7

155.2

240.8

145.3

956.2

149.9

351.6

3LI

QA

rts

47.7

937.5

156.1

458.9

155.2

941.3

447.3

9LI

QC

om

pet

itiv

e42.1

356.4

740.7

957.1

265.2

140.1

451.5

2LI

QSo

cial

53.1

751.4

546.6

257.4

254.5

940.4

640.8

4LI

QA

thle

tic

51.4

953.6

544.7

658.4

856.0

931.0

945.3

8A

chie

vem

ent

1.4

7a

1.2

0a,

b1.3

8a,

b1.6

4a

1.3

7a,

b1.3

5a,

b1.1

0b

12.2

4C

om

fort

.62

.47

.43

.74

.74

.66

.50

9.1

0St

atus

.78

a,b

.95

a.6

8a,

b.8

9a,

b.7

4a,

b.8

4a,

b.5

4b

5.2

9A

ltru

ism

1.2

8a,

c.7

8b

1.1

1a,

b,c

1.4

4a

1.2

8a,

c.9

8a,

b,c

.95

c25.4

9*

Safe

ty.8

4.6

9.6

81.0

51.0

1.8

2.6

910.8

2A

uto

nom

y.8

1.7

3.6

71.0

8.8

4.5

8.6

17.9

7W

ork

Cen

tral

ity

34.4

2a,

b34.2

3a,

b31.3

5a

38.9

3b

34.6

3a,

b33.0

1a,

b36.8

6b

15.8

4C

onsc

ientiousn

ess

75.5

2b

73.0

9a,

b73.3

7a,

b75.6

4b

72.4

6a,

b72.3

6a,

b67.4

1a

6.9

9N

euro

tici

sm48.1

7a

44.4

7a

56.7

3b,c

44.3

8a

49.4

7a,

c57.2

0a,

c52.5

8a,

c20.7

3*

Extr

aver

sion

76.3

3a

77.6

0a

73.9

6a,

b78.5

1a

73.8

1a,

b70.2

4a,

b67.9

6b

7.6

8O

pen

nes

s65.6

4a,

c62.8

8a

80.6

5b

76.7

7b,c

73.9

9b

63.8

7a

71.4

6c

74.4

5*

Agr

eeab

lenes

s80.0

3a

70.3

2b

79.2

2a,

c77.9

2a,

d71.8

8b,c

,d71.2

7a,

b,c

71.0

3b

18.6

7*

Not

e.M

eans

with

diff

eren

tsu

per

scri

pts

are

sign

ifica

ntly

diff

eren

t(p

<.0

1),

while

those

shar

ing

asu

per

scri

pt

do

not

sign

ifica

ntly

diff

er.In

tere

stsc

ore

sar

ere

port

edas

tsc

ore

s.*p

<.0

1.

15

at UNIV OF SOUTHERN MISSISSIPPI on April 16, 2015jca.sagepub.comDownloaded from

-1.0

0

-.80

-.60

-.40

-.20

.00

.20

.40

.60

.80

1.00

Soci

als

Com

p. B

usin

ess

Arti

sts

Leis

urei

tes

Enth

usia

sts

Def

. Bus

ines

sFl

at

Ach

eive

men

tC

omfo

rtSt

atus

Altr

uism

Safe

tyA

uton

omy

Wor

k C

entra

lity

Con

scie

ntio

usne

ssN

euro

ticis

mEx

trave

rsio

nO

penn

ess

Agr

eeab

lene

ss

Fig

ure

2.

Score

son

work

valu

es,w

ork

centr

ality,

and

per

sonal

ity

for

each

pro

file

group.N

ote.

Score

sw

ere

tran

sform

edto

z-sc

ore

sfo

rea

sier

inte

rpre

tation.

16

at UNIV OF SOUTHERN MISSISSIPPI on April 16, 2015jca.sagepub.comDownloaded from

in leisure activities may help build relationships with others, develop positive emotions, and

acquire knowledge, skills, and abilities (Brajsa-Zganec, Merkas, & Sverko, 2011), which may sub-

sequently lead to progress in identifying a career path (Bloland, 1984; Hendel & Harrold, 2004).

Others (Armstrong & Rounds, 2008; Hendel & Harrold, 2004) have proposed that career counsel-

ing 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 Com-

petitive 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 voca-

tional and leisure interests has found that leisure interests relate highest to Social, Artistic, and Rea-

listic vocational interests (Armstrong & Rounds, 2008) which supports the current findings.

Furthermore, research by Gaudron and Vautier (2007) found that individuals express less consis-

tency 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 Pro-

files. 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 Rea-

listic 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 understand-

ing 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 val-

ues, 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 con-

firmed 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,

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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 pre-

vious 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 (Compet-

itive 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 char-

acterized 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 measure-

ment, 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 predomi-

nately 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 (Conven-

tional and Investigative). Additionally, profiles partially supported Prediger’s (1982) bipolar dimen-

sions 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 individ-

uals, 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

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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 inter-

ests 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 lei-

sure 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 Neuroti-

cism. 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 com-

plexes, 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 high-

est 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 sup-

port 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.

Leuty et al. 19

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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 ele-

vation, 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 exam-

ined in the current study, in light of this previous research, a reasonable hypothesis is that individ-

uals 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 soli-

dify 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 individ-

uals 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 par-

tially 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 indi-

viduals 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 identify-

ing 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 differen-

tiated 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 articu-

lating long-term career goals. Discussing and encouraging leisure participation with these individ-

uals, 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

20 Journal of Career Assessment

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job or leisure satisfaction, may provide important information about career development issues

particular to each profile group.

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.

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