Journal of Adolescence 34 (2011) 853–871

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Journal of Adolescence

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A multi-dimensional measure of vocational identity status

Erik J. Porfeli a,*, Bora Lee b, Fred W. Vondracek b, Ingrid K. Weigold c

aDepartment of Behavioral and Community Health Sciences, Northeastern Ohio Universities College of Medicine and Pharmacy, Rootstown, OH 44272, USAbDepartment of Human Development and Family Studies, The Pennsylvania State University, USAcDepartment of Counseling, The University of Akron, USA

Keywords:Identity statusVocationCareerAdolescenceYoung adulthoodMeasurement

* Corresponding author. Tel.: þ1 330 325 6114.E-mail address: eporfeli@neoucom.edu (E.J. Porf

0140-1971/$ – see front matter � 2011 The Foundadoi:10.1016/j.adolescence.2011.02.001

a b s t r a c t

Establishing a worker identity is among the most central aspects of the transition fromadolescence to adulthood. Despite its importance, few measures with acceptablepsychometric and conceptual characteristics exist to assess vocational identity statuses.This study reports the development and evaluation of the Vocational Identity StatusAssessment (VISA), which is derived from established conceptual models and includescareer exploration, commitment, and reconsideration dimensions. Results show that theVISA exhibited metric invariance across a high school and university sample. Clusteranalyses demonstrated that the VISA consistently resolved six identity statuses across thetwo samples, supporting the previously established achieved, moratorium, foreclosed, anddiffused statuses along with two additional statuses termed searching moratorium andundifferentiated. The identity statuses predicted differences in participants’ work valencesand well-being with the achieved and diffused statuses respectively exhibiting the mostand least favorable characteristics. Implications, limitations, and suggestions for futureresearch based upon these findings are offered.� 2011 The Foundation for Professionals in Services for Adolescents. Published by Elsevier

Ltd. All rights reserved.

The present study describes the development and tests the psychometric characteristics of the Vocational Identity StatusAssessment (VISA) for adolescents and young adults. This measure is based on Marcia’s (1966) conceptualization of fouridentity statuses (i.e., achieved, moratorium, foreclosed, and diffused), as well as more recent extensions of the identity statusmodel.

The relationship of vocational identity to other identity domains has received little attention in the empirical literature, inpart because of the absence of valid and reliable domain-specific measures of identity. Nevertheless, in spite of measurementlimitations, some interesting findings have been reported that suggest that Erikson was correct in assigning a leading role tovocational identity development in the overall process of identity formation. For example, Skorikov and Vondracek (1998),while confirming earlier results that found that vocational identity was positively related to overall identity (Kroger, 1986,1988), reported that advancement toward vocational identity achievement did not depend on prior advancement towardoverall identity achievement. In fact, vocational identity development appeared to lead identity development in otherdomains. Another noteworthy finding was that the developmental progression in identity development proposed byGrotevant (1987) was confirmed for the vocational domain in a number of studies (e.g., Archer, 1989; Dellas & Jernigan, 1987;Kroger, 1988; Meeus, 1993; Skorikov & Vondracek, 1998).

Few measures exist to assess the vocational identity statuses, and those that do tend to have conceptual or psychometriclimitations (Skorikov & Vondracek, 2007b). While the Extended Objective Measure of Ego Identity Status (EOM-EIS; Adams,

eli).

tion for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

E.J. Porfeli et al. / Journal of Adolescence 34 (2011) 853–871854

Bennion, & Huh, 1989) faithfully applies Marcia’s model, a subscale created to measure vocational identity status demon-strated marginal psychometric properties, primarily due to the low number of items in this subscale (Skorikov & Vondracek,1998). On the contrary, the vocational identity subscale of My Vocational Situation (MVS) instrument exhibits excellentpsychometric characteristics (Holland, Johnston, & Asama, 1993; Lucas, Gysbers, Buescher, & Heppner, 1988), but it isessentially a measure of career commitment and omits career exploration almost entirely. The centrality of work, coupledwith the limitations in existing measures of vocational identity, suggests that the time is ripe for a new and improvedmeasure.

Background

Rationale for development of a domain-specific (vocational) identity measure

Most established identity status measures (e.g., Adams et al., 1989) are global in the sense that they involve items per-taining to many life domains (e.g., work, family, religion, and politics) and are based upon Marcia’s (1966, 1993) two-dimensional model of identity status, which includes dichotomized (i.e., high and low) exploration and commitment, yieldingfour identity statuses. The four statuses are identity achieved (high exploration and commitment), foreclosed (low explo-ration and high commitment), moratorium (high exploration and low commitment), and diffused (low exploration andcommitment). Marcia’s model presumes that most, if not all people begin in the diffused status and move toward the otherthree during the periods spanning childhood and adulthood. Recent research supports such a progression (Klimstra, Hale,Raaijmakers, Branje, & Meeus, 2010; Kroger, Martinussen, & Marcia, 2010) while other research argues against it(Berzonsky, 2003). The achieved status is thought to be the most advanced and preferred identity status because it describespeople who are committed to roles that they have thoroughly explored. The moratorium status is believed to be a transitorystatus that most often leads to increased commitment and the achieved status. The foreclosed status is not preferable in mostcircumstances because it assumes commitment, often sourcing from external forces (e.g., the will of family members), in theabsence of adequate exploration. This configuration of low exploration and high commitment presumably increases theprobability that one’s premature commitments will not suit one’s identity as determined sometime later. Finally, diffusion ischaracterized by minimal exploration and commitment and can be characterized as a disengaged or drifting state. Pro-gressing through identity statuses and toward the achieved status is associated with positive psychological adjustment(Balistreri, Busch-Rossnagel, & Geisinger, 1995; Chen, Sousa, & West, 2005; Marcia, 1980, 1993).

There has not been complete agreement on the nature or number and kind of identity domains (e.g., work, family, religion,race, ethnicity, gender, and politics) contributing to one’s global sense of identity, but almost all conceptualizations includethe vocational domain. Erikson (1959), for example, insisted that the development of an occupational (vocational) identitywas the most troublesome and difficult aspect of identity formation during the transition from adolescence to adulthood.Indeed, half-a-century after Erikson’s observation, establishing a worker identity and choosing a career are paramount tasksas youths make the transition to adulthood (Blustein, 1994; Blustein, Devenis, & Kidney, 1989; Blustein & Noumair, 1996;Vondracek, 1992). Various researchers have commented on the asynchronous nature of identity development acrossdomains (e.g., Grotevant, 1987, 1993; Kroger, 1988; Kroger & Haslett, 1991; Lavoie, 1994; Skorikov & Vondracek, 1998;Waterman, 1985). For example, Waterman (1985) compiled a composite cross-sectional analysis of identity studies pub-lished in the 1970s and early 1980s and reported that the development of identity appeared to proceed at different ratesacross identity domains. Moreover, some identity domains, like ethnic identity, may be highly significant for some individualsand completely unimportant for others, highlighting the importance of the self in context in determining the salience ofvarious identity domains (Vondracek, 1995). The importance of vocational identity development likely varies across contextsbetween and within societies, but in the context of industrialized countries, vocational development and acquiring a voca-tional (occupational) identity has been recognized as the most important task of adolescents and young adults. For example,Kroger (1993) reported that various cohorts of students in New Zealand considered their occupational choice to be centrallyimportant in their identity formation. Similar results have been reported in the United States (Schulenberg, Bachman,Johnston, & O’Malley, 1994) and in Germany (Förster & Friedrich, 1996). Perhaps even more impressive is the observationthat adults report that their vocation was the most important factor in their identity development and the arena of the mostsignificant and earliest identity status transitions (Kroger & Haslett, 1991). In sum, there is support for the notion thatvocational identity plays a key role in overall identity development in industrialized countries.

Exploration and commitment are deemed to be the two central processes involved in progress through the (vocational)identity statuses (Marcia, 1966, 1993) and toward a career choice (Super, Savickas, & Super, 1996). Career exploration (Flum &Blustein, 2000; Jordaan, 1963, pp. 42–78; Patton & Porfeli, 2007) and career commitment (Blustein, Ellis, & Devenis, 1989;Creed & Patton, 2003; Diemer & Blustein, 2007; Germeijs & Verschueren, 2006) are generally perceived as favorableprocesses promoting the transition from the student to the worker role in most industrialized countries. Adolescents developtheir vocational identity as they explore themselves and theworking world and get ready to make commitments to both (e.g.,crystallizing work choices and personal values and interests). Doing so is believed to improve the chances of establishinga suitable match between the person and the occupation and help the person remain committed to the process of preparingfor the worker role despite the challenges or setbacks that may be faced during the preparation period (Super et al., 1996).

The vocational identity literature indicates that establishing an achieved identity status is associated with enhanced self-esteem, adjustment, life satisfaction, competence, academic adjustment, and performance (Meeus Iedema, Helsen,

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Vollebergh, 1999; Skorikov & Vondracek, 2007b; Vondracek, 1994). This pattern is also found in the global identity statusliterature (e.g., Meeus, 1996; Waterman, 2007). Vocational identity statuses may also be associated with one’s generalemotional, experiential, andmotivational valence towardwork. Previous research demonstrated that participants as young asthe grade-school years exhibit distinct positive and negative emotional and experiential valences towardwork (Porfeli, Wang,& Hartung, 2008). To the extent that adolescents perceive work as offering favorable experiences and emotions, they may bemore or less willing to explore and commit to an occupational role and remain more or less doubtful and flexible about theirchoices.

Contemporary models of identity status

Recent empirical studies of global identity status have implications for the development of a new measure of vocationalidentity. Two specific avenues of advancement have occurred and are summarized in Table 1. The first avenue is termed hereas the Luyckx model (Luyckx, Goossens, Beyers, & Soenens, 2006; Luyckx, Goossens, Soenens, & Beyers, 2006; Luyckx,Goossens, Soenens, Beyers, & Vansteenkiste, 2005). This model includes two dimensions of exploration (in-breadth andin-depth) and commitment (commitment making and identification with commitment), consistently resolving five statusesincluding the achieved, foreclosed, andmoratorium statuses proposed byMarcia. This work also has led to a refinement of thediffused status into two statuses termed diffused diffusion and carefree diffusion. A subset of studies employing this model hasalso found a sixth status characterized as undifferentiated,with all exploration and commitment subscale scores at or near themean (Luyckx et al., 2008; Luyckx, Vansteenkiste, Goossens, & Duriez, 2009). This work demonstrates that a new measure ofidentity status could benefit from refining Marcia’s two dimensions of identity status into two subscales of exploration andtwo subscales of commitment, yielding five or six statuses.

The second avenue, termed here as the Meeus and Crocetti model (Crocetti, Klimstra, Keijsers, Hale, & Meeus, 2009;Crocetti, Rubini, Luyckx, & Meeus, 2008; Crocetti, Rubini, & Meeus, 2008; Crocetti, Schwartz, Fermani, & Meeus, 2010;Meeus, 1996), suggests that identity statuses are defined by three dimensions including commitment (akin to identifica-tion with commitment in the Luyckx model), exploration (akin to in-depth exploration in the Luyckx model), and recon-sideration of commitment. Reconsideration, according to the Meeus and Crocetti model, involves releasing currentcommitments, comparing and contrasting alternative commitments, and a willingness to conduct in-breadth exploration.The research employing the Meeus and Crocetti model with mainly early and middle adolescent samples found thatreconsideration contributed to the identification of Marcia’s (1966) achieved, foreclosed, and diffused statuses (Crocetti,Rubini, Luyckx, et al., 2008). It also led to a refinement of the moratorium status into moratorium and searching morato-rium statuses. The searching moratorium status reflected participants with elevated commitment, in-depth exploration, andreconsideration and was compared to the moratorium-achievement-moratorium-achievement (MAMA) cycle (Stephen,Fraser, & Marcia, 1992), which characterizes individuals who vacillate between the moratorium and achievement statuseswhile establishing and refining their identity. Including reconsideration as a third dimension of the Marcia (1966) model mayaid in resolving an identity status akin to the MAMA cycle.

Age-based implications

More than a decade ago, Meeus et al. (Meeus, 1996; Meeus et al., 1999) examined the empirical literature on identitystatuses across adolescence and young adulthood and arrived at conclusions pertinent to the present study. First, many in thefield had incorrectly assumed that the majority of identity development occurred in the years immediately following highschool (i.e., the college years). Meeus (1996) urged researchers to focus their efforts on the high school years in light ofevidence suggesting that identity development begins during that period. A related and important finding was thata significant fraction of the field, at least tacitly, endorsed the position that identity statuses could be identified during theearly to middle adolescent period (Meeus, 1996; Meeus et al., 1999) despite statements (e.g., Marcia, 1980) suggesting thatidentity crises did not typically occur until late adolescence or early adulthood (see Meeus et al., 1999, p. 422, for a review ofthis literature).

A new measure of vocational identity status should have the capacity to assess developmental change if it aims to beapplicable across the adolescent and young adult periods, given that previous research has found these to be very activeperiods for identity development. Such a measure should be sensitive enough to find the regular progression of increasingfractions of adolescents in the moratorium status up to about an age of 19 years, followed by a steady decline thereafter,coupled with increasing fractions of those in the achieved status and decreasing fractions of those in the foreclosed anddiffused statuses across the adolescent and young adult periods (Klimstra et al., 2010; Kroger, Martinussen, &Marcia, 2010). Inbrief, a measure of vocational identity status should be capable of assessing theoretically predictable status differences as wellas developmental change.

A seemingly contradictory requirement is that a measure of vocational identity status should also demonstratemeasurement invariance with age. The common classification of measurement invariance is configural, metric, and scalar(Vandenberg & Lance, 2000). If configural invariance is achieved, the number of factors and the items loading on the factors ofa measure are invariant across age periods (e.g., data from adolescents and young adults would demonstrate a similar factorstructure). Metric invariance is achieved when configural invariance exists, and the size of the factor loadings is invariantacross age. Finally, if scalar invariance is achieved, then metric invariance is established, and in addition, the means of the

Table 1Summary of the identity status literature and the VISA.

Model Dimensions Identity statuses Measures

Global identity status models Marcia(Marcia, 1966, 1993)

� ExplorationB LowB High

� CommitmentB LowB High

AchievedForeclosedMoratoriumDiffused

Objective measure of egoidentity status (Adams,Bennion, & Huh, 1989)

Luyckx(Luyckx et al., 2005;Luyckx, Goossens, Beyers, et al., 2006;Luyckx, Goossens, Soenens, et al., 2006)

� ExplorationB In-breadthB In-depth

� CommitmentB Commitment makingB Identification with commitment

AchievedForeclosedMoratoriumDiffused diffusionCarefree diffusionUndifferentiated

Ego Identity ProcessQuestionnaire (EIPQ;Balistreri et al., 1995)Utrecht-Groningen IdentityDevelopment Scale (U-GIDS; Meeus& Dekovic, 1995)

Meeus and Crocetti(Crocetti et al., 2009;Crocetti, Rubini, Luyckx, et al., 2008;Crocetti, Rubini, & Meeus, 2008;Crocetti et al., 2010; Meeus, 1996)

� ExplorationB In-depth

� CommitmentB Identification with commitment

� Reconsideration of commitment

AchievedForeclosedMoratoriumSearching moratoriumDiffused

Utrecht-Management ofIdentity CommitmentsScale (U-MICS; Meeus, 2001)

Vocational identity status Present study � Career explorationB In-breadth career explorationB In-depth career exploration

� Career commitment

B Commitment makingB Identification with commitment

� Career reconsideration

B Career self-doubtB Career flexibility

To be explored in thepresent paper

Vocational IdentityStatus Assessment (Porfeli, 2009)

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factors are invariant (e.g., adolescents and young adults exhibit the same factor structure and loadings and they do not exhibitmean differences on the factors). Previous research and theory suggests that a sound measure of vocational identity statuswould exhibit configural invariance. We expect the two groups (adolescents and young adults) to demonstrate the samefactor structure given that the proposed measure includes identity processes that are known to be active for both groups. Wewould not expect, however, that such a measure would also exhibit scalar invariance, because this would lead to theexpectation that adolescents as a group would not exhibit mean-level differences in identity processes relative to youngadults. Previous research reviewed above clearly shows that career exploration and commitment tend to increase from theadolescence to young adulthood. We would thus expect an effective measure of vocational identity status to exhibit no morethan metric invariance across the adolescent and young adult years. In addition, we would expect that the measure woulddemonstrate invariance in the number and type of statuses for adolescents and young adults so that the measure could thenbe used to demonstrate the regular progression in identity statuses discussed above In sum, if we succeed in constructinga measure with these characteristics, it would have the capacity to detect the regular developmental change leading to anincreased likelihood of vocational exploration and commitment and decreased likelihood of vocational reconsideration,which could be used to translate into the language of identity statuses.

Initial development of the VISA

The VISA (Porfeli, 2009) was initially developed to assess the original identity status dimensions (career exploration andcommitment), the two subscales of those dimensions reported by Luyckx, and the reconsideration dimension offered byMeeus and Crocetti. This work also was based on a more differentiated conceptualization of career exploration (in-breadthand in-depth) based on recently reported research (Gati & Asher, 2001; Patton & Porfeli, 2007; Porfeli, 2008; Porfeli &Skorikov, 2010). The original measurement model demonstrated adequate fit according to established criteria (Hu &Bentler, 1999). The internal consistency reliabilities of the original subscales ranged from .72 (career self-doubt) to .88(specific career exploration). The initial test of the model demonstrated that using just the constructs from the Luyckx modelyielded a two-cluster solution distinguishing those participants who were or were not exploring and committing to careers.When career self-doubt (an indicator of reconsideration from the Meeus and Crocetti model) was added to the cluster model,the solution reflected either two or four statuses with the two status solution suggesting that being more or less engaged inexploring and committing was associated with being less or more doubtful, respectively, and the four status solutionreflecting the exploration and commitment pattern proposed by Marcia (1966), with self-doubt being elevated in themoratorium and diffused statuses. The four identity statuses predicted meaningful differences across several indicators ofcareer development and adjustment, thereby supporting the validity of the measures and the four identity statuses derivedfrom them. While the VISA showed a promising start, the inability of the measure to convincingly resolve more than twoidentity statuses signaled potential conceptual and/or methodological limitations that needed to be addressed.

To address possible conceptual limitations, the construct of career reconsideration was expanded. This dimension ofidentity status is conceived here to be composed of at least two aspects. The first aspect is career self-doubt. Career self-doubtis characterized by doubt, uneasiness, and worry about one’s current career choice and a sense that others share the samefeelings and ideas. Self-doubt is a possible negative consequence of the process of working toward a career commitment, andit may hinder in-depth exploration and making and identifying with career commitments. Research has shown thatadolescents who are actively experiencing an identity crisis exhibited increased doubt, confusion, and conflicts with others(Kidwell, Dunham, Bacho, Pastorino, & Portes, 1995), and those in the moratorium status (Hunsberger, Pratt, & Pancer, 2001;Porfeli, 2009) and the diffused status (Porfeli, 2009) experienced elevated doubt relative to the other two statuses. Moreover,personality characteristics associated with self-doubt, such as emotional instability (i.e., neuroticism), have been shown tointerferewith career decisionmaking (Jin, Watkins, & Yuen, 2009; Lounsbury, Hutchens, & Loveland, 2005; Lounsbury, Tatum,Chambers, Owens, & Gibson, 1999). Based upon past findings, individuals in the moratorium and diffused statuses areexpected to exhibit elevated levels of doubt relative to the other three statuses.

The second aspect of career reconsideration is career commitment flexibility, which is most aligned with the originalconceptualization of reconsideration offered by the Meeus and Crocetti model (Crocetti, Rubini, Luyckx, et al., 2008). Careercommitment flexibility is defined here as an active and ongoing consideration of alternatives and a recognition and accep-tance that one’s career choice, interests, and valuesmight change in the future as a consequence of learning and experience. Inthe context of adults aged 18–40 years typically changing jobs 10 times and a large proportion of these jobs ending withina year (U.S. Department of Labor, 2004), a flexible approach to identity formation may be adaptive (Savickas, 1997, 2002).Career commitment flexibility may be more prevalent and active for those who perceive themselves as being relatively earlyin the decision-making process. Adolescents who exhibit career flexibility may acknowledge that they still havemuch to learnand experience and are open to doing so. While career self-doubt centers on the negative consequences of working towarda career commitment and presumably contributes to a more reticent attitude toward work choices, career commitmentflexibility connotes a more positive rationale for remaining uncommitted to a career. Career commitment flexibility is pre-dicted to be positively associated with in-breadth career exploration and career self-doubt, and negatively associated withidentification with career commitment making and identification with those commitments.

The inability of the VISA to discern multiple identity statuses may also be partly due to methodological considerations. Inthe previous research on the VISA, the SPSS two-step procedure was used to identify an appropriate number of identitystatuses (Porfeli, 2009). Some believe that use of the SPSS two-step procedure should be avoided in favor of using a k-means

E.J. Porfeli et al. / Journal of Adolescence 34 (2011) 853–871858

method (Clatworthy, Hankins, Buick, Weinman, & Horne, 2007). Others have outlined (Gore, 2000) and applied (e.g., Crocetti,Rubini, Luyckx, et al., 2008; Luyckx et al., 2005) a more elaborate approach to clustering that involves a determination of theappropriate number of clusters employing an iterative hierarchical and k-means procedure. This method yields an estimate ofthe reliability of the cluster solution across randomly split halves of the sample. We extended this method here to estimatereliability of cluster assignment across a high school and college sample, which supports our aim to construct a measure thatis suitable for adolescents and young adults who are still preparing for an occupation.

Aims and hypotheses of the present study

The present study represents an effort to unify the identity status models of Luyckx and of Meeus and Crocetti throughthe further development and testing of the VISA. The specific aim was to construct a measure that could discern Marcia’s(1966) predicted four vocational identity statuses and possibly refined moratorium and diffused statuses as well as anundifferentiated status on the basis of unique configurations of career exploration, commitment, and reconsideration. Thisaim was supported by three goals, including (a) testing the measurement model of the VISA, (b) determining the appro-priate number of statuses resolved by the VISA through cluster analyses, and (c) assessing the validity of the identitystatuses resolved by the VISA.

We expected the sample to exhibit configural invariance and not scalar invariance across age groups because we expectedthat the university sample would exhibit more career commitment and exploration, but less career reconsideration, than thehigh school sample given the mounting societal pressure to establish an identity during the young adult years (Meeus, 1996).In a consistent manner, we predicted that the factors resulting from the measurement model could be used to establisha consistent set of identity statuses (i.e., clusters) across the two groups. Aligned with previous research on status progres-sions with age, we predicted that distribution of participants within the statuses would differ across the high school anduniversity samples in a manner consistent with the university sample being more advanced in their identity development. Itwas predicted that a greater fraction of high school students would be assigned to the diffusion status, and a greater fractionof university students to the achieved status.

In an effort to further validate the identity statuses derived from the VISA, and in light of the extensive literaturedemonstrating links between identity statuses and well-being (Waterman, 2007), mean differences in core self-evaluations(Judge, Erez, Bono, & Thoresen, 2003), depression, anxiety, and stress (Lovibond & Lovibond, 1995) across vocational identitystatuses were examined. Positive core self-evaluations have been found to be associated with favorable work performanceand attitudes (Judge, Bono, Erez, & Locke, 2005), and mental health indicators like depression have been associated withpoorer career development (Saunders, Peterson, Sampson, & Reardon, 2000; Skorikov & Vondracek, 2007a). We predictedthat adolescents and young adults occupying the achieved and diffused statuses will exhibit the largest mean differences intheir core self-evaluations, depression, anxiety, and stress, with the achieved status exhibiting the most favorable profileacross these four indicators of well-being and the diffused status exhibiting the least favorable profile.

Previous research with the first version of the VISA found that those participants in the achieved identity status exhibitedamore favorablework valence relative to those in the diffused/disengaged status (Porfeli, 2009).Work valence is composed ofbelief about one’s future work as it will be experienced on emotional and behavioral levels. Luyckx et al. (2010) assessed therelationships between global identity statuses and indicators of work engagement and burnout and found that identityachieved and diffused diffusion groups, respectively, demonstrated the most and least favorable profiles. The present studywill explore possible differences in adolescents’ experiential and emotional valences toward work across the identity statusesidentified with the revised version of the VISA. Adolescents in the achieved identity status are predicted to exhibit the mostfavorable work valence while their peers in the diffused identity status are predicted to exhibit the least favorable workvalence. Differences among the other statuses revealed by the VISAwill be assessed frommore of an exploratory frame giventhat the number and nature of the statuses were not known a priori.

Method

Participants

Participants were composed of two samples. One sample included 540 tenth and eleventh grade students who wererandomly sampled from amix of seven suburban and urban high schools in the Midwest. Of the high school participants whovolunteered, 432 provided complete and usable data for the target measures in this study (M age¼ 16.5 years, SD ¼ .99). Thesample was 55% female, 20% African American, 72% Caucasian, 2% Asian, and approximately 6% were another race or biracial.The other sample included 402 students attending a university in Northeastern Ohio. Of this total, 343 students providedcomplete and usable data (M age ¼ 21.7 years, SD ¼ 4.68). Of the 343 students, 74.6% were women (reflecting that thestudents were sampled mainly from psychology courses), 7.7% African American, 86.4% Caucasian, 1.7% Asian, and approxi-mately 6% were another race or biracial. The university maintains a policy of open enrollment that permits any student witha high school degree to gain admittance; hence, the relative degree of cultural, economic, and academic achievementdiversity of this sample may be greater than (or at least differ from) the diversity of students from universities that do notmaintain such a policy.

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Measures

Vocational Identity Status Assessment (VISA)The VISA was created and employed in previous research (Porfeli, 2009; Porfeli, Lee, & Vondracek, 2010). The items were

constructed on the basis of conceptual and empirical work distinguishing career exploration in-depth (i.e., specific careerexploration) and in-breadth (i.e., diversive career exploration) (Gati & Asher, 2001; Patton & Porfeli, 2007; Porfeli, 2008;Porfeli & Skorikov, 2010) and the two broad forms of commitment, namely commitment making and identification withcommitment (Luyckx et al., 2005; Luyckx, Goossens, Beyers, et al., 2006; Luyckx, Goossens, Soenens, et al., 2006). The VISAwas originally developed by the first author to include 66 items, reviewed and edited by five experts in identity statusresearch, and piloted on a sample of adolescents. Using these items, the VISA was constructed to consist of four subscalesaligning with the exploration and commitment dimensions proposed by Luyckx and colleagues, but exclusively focusing onexploring and committing to work. The original version of the VISA also included one indicator of reconsideration, namelycareer self-doubt (Porfeli, 2009). The result of the analytic work on the original version led to the newest iteration of theVISA employed here (see Table 2), which includes some revised items across the five subscales and includes an additionalsubscale of reconsideration termed career flexibility (Porfeli et al., 2010). The VISA, therefore, contains thirty items, with 10items for each of the three dimensions of career exploration, commitment, and reconsideration, and five items for each ofthe two subscales per dimension. All VISA subscales employed a five-point Likert scale ranging from 1 (strongly disagree) to5 (strongly agree). The subscales and validation measures are described in greater detail below.

Table 2VISA Constructs, Items, Parcel Assignment, and Factor Loadings

Construct Items Parcel Std. Loading

Career ExplorationIn-Breadth Career Exploration

1. casually learning about careers that are unfamiliar tome in order to find a few to explore further. 1 .662. trying to have many different experiences so that I can find several jobs that might suit me. 1 .683. thinking about how I could fit into many different careers. 2 .754. learning about various jobs that I might like. 2 .705. keeping my options open as I learn about many different careers. 2 .69

In-Depth Career Exploration1. identifying my strongest talents as I think about careers. 1 .652. learning as much as I can about the particular educational requirements of the career that

interests me the most.1 .70

3. learning what I can do to improve my chances of getting into my chosen career. 2 .684. trying to find people that share my career interests. 2 .545. thinking about all the aspects of working that are important to me. 2 .66

Career CommitmentCareer Commitment Making

1. I know what kind of work is best for me. 1 .652. No other career is as appealing to me as the one I expect to enter. 1 .723. I have known for a long time what career is best for me. 1 .694. No one will change my mind about the career I have chosen. 2 .745. I have invested a lot of energy into preparing for my chosen career. 2 .70

Identification with Career Commitment1. My career will help me satisfy deeply personal goals. 1 .652. My family feels confident that I will enter my chosen career. 1 .673. Becoming a worker in my chosen career will allow me to become

the person I dream to be.2 .75

4. I chose a career that will allow me to remain true to my values. 2 .675. My career choice will permit me to have the kind of family life I wish to have. 2 .48

Career ReconsiderationCareer Self-Doubt1. Thinking about choosing a career makes me feel uneasy. 1 .582. When I tell other people about my career plans, I feel like I am being

a little dishonest.1 .78

3. People who really know me seem doubtful when I share mycareer plans with them.

2 .66

4. I doubt I will find a career that suits me. 2 .785. I may not be able to get the job I really want. 2 .55

Career Flexibility (Newly added in the present study)1. My work interests are likely to change in the future 1 .812. What I look for in a job will change in the future. 1 .613. I will probably change my career goals. 2 .804. My career choice might turn out to be different than I expect. 2 .605. I need to learn a lot more before I can make a career choice. 2 .65

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The career exploration dimension

In-breadth and in-depth career exploration. These subscales include 10 items assessing two dimensions of career exploration,namely career exploration in-breadth and in-depth. Each set of items begins with, “When you explore careers, to what extentdo you agree with the following statements? Right now I am.” Higher scores indicate greater levels of in-breadth and in-depth exploration, respectively.

The career commitment dimension

Career commitment making and identification with a career commitment. These subscales include 10 items, which assess twodimensions of commitment. The first dimension is an indication of the extent to which participants had committed to anoccupation, and the second reflects the degree of their identification with that commitment. Higher scores indicate greaterlevels of commitment and identification, respectively.

The career reconsideration dimension

Career self-doubt. This subscale includes 5 items and was inspired by identity status research suggesting that doubt is animportant indicator of experiencing an identity crisis, particularly for those participants in the moratorium status. The scaleassesses the extent to which participants are uncertain about their career choice and about becoming a worker, with higherscores reflecting greater self-doubt.

Career commitment flexibility. This new subscale of the reconsideration dimension has 5 items that assess the degree to whicha participant expects and is open to changes in themselves and their career choice in the future. Higher scores reflect greaterflexibility.

Validation measures

Core self-evaluations (high school sample only). This construct was assessedwith ameasure of “a basic, fundamental appraisal ofone’s worthiness, effectiveness, and capability as a person” (Judge et al., 2005, p. 304). Core self-evaluations are defined asa composite of self-esteem, generalized self-efficacy, neuroticism, and locus of control (Judge et al., 2003). The wording of theitemswas slightlymodified to bemore appropriate to the age range of participants in this study (e.g., “Sometimes, I do not feelin control of my work”was changed to be “Sometimes, I do not feel in control of my life”). Participants responded to the itemson a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Judge et al. (2005) reported acceptable internalconsistency estimates (a was between .83 and .87 across several samples).

Depression, anxiety, and stress (university sample only). These aspects of adjustment were assessed with the Depression,Anxiety, and Stress Scales (DASS; Lovibond & Lovibond, 1995). This forty-two-item version of the measure includesdepression, physical arousal, and distress subscales. Participants were asked to respond to the series of items considering howmuch they applied to them over the past week. The Likert scale ranges from 0 (did not apply to me at all) to 3 (applied to mevery much, or most of the time). This measure has received extensive support in the literature as a valid measure of the targetconstructs with internal consistency estimates of .97, .92, and .95 for the three scales respectively (e.g., Antony, Bieling, Cox,Enns, & Swinson, 1998), but appears to be limited for use on adult samples only (Patrick, Dyck, & Bramston, 2010).

Work valence: positive and negative work affectivity and experiences. These scales are revised and expanded versions of scalesemployed with grade-school children to assess their work valences (Porfeli et al., 2008). The six positive and seven negativeaffectivity items begin with “When you are an adult doing your job, how often do you think you will feel .” Each item is anemotion that was identified by the emotion literature to be pertinent to the work context. Example positive affectivity itemsare “happy” and “proud,” and example negative affectivity items are “disgusted” and “defeated.” The 8 positive and 8 negativework experience items begin with “When you are an adult doing your job, how often do you think you will.” Each itemreflects a common experience within the work context. Example positive work experience items are “succeed at work” and“get really interested in your work,” and example negative work experience items are “get really tired at work” and “beassigned too many work tasks.”Participants responded to the items on a Likert scale ranging from 1 (never) to 5 (always) andtotal scale scores were computed as an average of the item scores. The internal consistency across both samples for thepositive and negative affectivity (a ¼ .80 and a ¼ .86, respectively) and positive and negative experience items (a ¼ .78 anda ¼ .75, respectively) in the current study were acceptable.

Analytic plan

The present study is a test of the psychometric characteristics of the VISA. The aim of the analytic plan was to (a)test the factor structure of the VISA and its invariance across age, (b) determine the appropriate number of statuses

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resolved by the VISA and the stability of this solution across age groups, and (c) test the validity of the identity statusesresolved by the VISA across age groups. The analytic method is partly based on a protocol employed to test the Meeusand Crocetti (Crocetti, Rubini, Luyckx, et al., 2008; Crocetti, Rubini, & Meeus, 2008; Meeus, 1996) and the Luyckx(Luyckx, Goossens, Beyers, et al., 2006; Luyckx, Goossens, Soenens, et al., 2006; Luyckx et al., 2005) models. This analyticmethod is enhanced by employing item and parcel approaches to confirmatory factor analysis (CFA) and a morecontemporary means of assessing measurement invariance in CFA models. The overall analytic plan is divided intoassessments of (a) the measurement model of the VISA, (b) the appropriate number of statuses resolved by the VISAthrough cluster analyses, and (c) the validity of the identity statuses resolved by the VISA.

Results

The measurement model: assessing fit and invariance across age

Multivariate outliers (about 1% of the sample) were identified via Mahalanobis distance estimates and removed. Absentoutliers, descriptive univariate statistics and bivariate correlations were computed for all of the VISA items and parcels(available upon request) separately for the high school and university samples and suggested that the items and parcelsexhibited an approximate normal distribution. The item and parcel correlations were generally in the expected directions,stronger within than between constructs, and those within constructs were statistically significant and of a meaningfulmagnitude. In sum, this pattern of associations generally supported the hypothesized structure of each scale and the inter-relationships among the scales.

We then proceeded to test the measurement model of the VISA and its invariance across age. To conduct these tests, wecomputed CFA models for the VISA using item and parcel approaches (Atlas & Overall, 1994) and then we tested themeasurement invariance across the high school and university samples. We employed item parcels in order to facilitatea comparison between the results here to those reported in previous research using the same method (e.g., Crocetti, Rubini,Luyckx, et al., 2008; Crocetti, Rubini, & Meeus, 2008; Luyckx et al., 2005). Employing item parcels (i.e., combining a set ofitems into a smaller subset of parcels) with CFA is known to yield more stable factor loadings, diminished measurementerror terms, and improved normality relative to items (Marsh, Hau, Balla, & Grayson, 1998), and simulations suggest that,under the condition that a set of items represents one underlying factor, items and parcels behave similarly in a CFA model(Alhija & Wisenbaker, 2006). On the contrary, other research finds that parceling may be inappropriate for use with itemsthat may be best modeled as multi-dimensional because parceling this set of items may yield overinflated fit indices,thereby obscuring the true number of factors represented by the items (Bandalos, 2002) and falsely suggesting measure-ment invariance across groups (Meade & Kroustalis, 2006). Computing the item and parcel models permitted a comparisonof the measurement model fit employing a conventional approach and an approach used in relatively recent identity statusresearch.

The item and parceled measurement models were examined with CFA and multi-group CFA (Jöreskog, 1971) using AMOS16. The first block in Table 3, termed Six Factor Vocational Identity, begins with the results from the item-level CFA, whichinvolved modeling the data for all the participants. The combination of the Comparative Fit Index (CFI), Root Mean SquareError of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR) suggests that the measurementmodel fits the data in an adequate fashion, particularly given that the model involves 30 indicators and 6 factors. Thisconclusion is partly supported by simulation studies demonstrating a known bias toward diminished fit in CFA models thatinvolve a larger number of indicators (Nasser & Wisenbaker, 2003).

Table 3Fit indices for multi-group confirmatory factor model of career commitment, exploration, and reconsideration.

Model c2 df CFI RMSEA SRMR Δc2 (Δdf) ΔCFI ΔRMSEA

Six factor vocational identitya. Combined groupa 1132.2** 390 .919 .050 .0533b. Multi-groupb unconstrained 1607.0** 780 .911 .037 .0601c. Multi-group configural invariance 1644.0** 804 .910 .037 .0599 37.0* (24) �.001c .000c

d. Multi-group metric invariance 1700.5** 825 .906 .037 .0676 93.5** (45) �.005c .000c

e. Multi-group scalar invariance 1825.8** 855 .896 .038 .0691 218.9** (75) �.015 .001c

Parceled six factor vocational identitya. Combined groupa 81.4** 39 .991 .038 .0253b. Multi-groupb unconstrained 129.3** 78 .989 .029 .0297c. Multi-group configural invariance 135.9** 84 .989 .028 .0304 6.6 (6) .000c .001c

d. Multi-group metric invariance 192.4** 105 .981 .033 .0531 63.1** (27) .008c �.004c

e. Multi-group scalar invariance 234.2** 117 .974 .036 .0568 104.9** (39) .015 �.007c

Note. CFI ¼ Comparative Fit Index; RMSEA ¼ Root Mean Square Error of Approximation; SRMR ¼ Standardized Root Mean Square Residual.* p < .05; ** p < .001.

a N of combined group ¼ 775.b N of high school sample ¼ 432; N of university sample ¼ 343.c ΔCFI and ΔRMSEA less than cutoffs (��.01 and <.05, respectively) suggested by Cheung and Rensvold (2002).

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Following the fit of the combinedmodel within the first block in Table 3, results from a series of tests employing themulti-group CFA models are reported. These tests are aligned with the commonly used terms configural, metric, and scalarinvariance (Vandenberg & Lance, 2000). The degree of invariance was assessed with two approaches. The first involved thechanges in chi-square (Δc2) as a consequence of increasing constraints on the measurement model and whether or not thosechanges were statistically significant (French & Finch, 2006). These results are included given that they are considered themost typical test of measurement invariance. More recent research on the validity of this test suggests that it may be too strict(Byrne, 2010). The second approach to testingmeasurement invariance involved computing the change in the Comparative FitIndex (ΔCFI) and the change in the Root Mean Square Error of Approximation (ΔRMSEA). The results of these tests arecontained in the last two columns in Table 3. The full explanation and rationale behind this approach is beyond the scope ofthis paper, so the reader is referred towork by Cheung and Rensvold (2002). This work suggests that ΔCFI��.01 and ΔRMSEA�.05 reflects an equivalent measurement model across groups at a ¼ .01 (Cheung & Rensvold, 2002). While we report bothtypes of tests to permit the reader to consider the results from the traditional test, wewill base our conclusions on the resultsfrom the more recently developed tests employing ΔCFI and ΔRMSEA. The results of the traditional tests (see column entitledΔc2 (Δdf)) suggest that the measurement model does not exhibit configural invariance across the high school and universitysamples at even the minimal level. Applying the more recent criteria (see columns entitled ΔCFI and ΔRMSEA) leads to theconclusion that the VISA exhibits metric invariance but does not exhibit scalar invariance across age. This means that thepattern and the magnitude of factor loadings are equivalent across the high school and university samples, but the meansdiffer as expected across these two groups.

The second block in Table 3, termed Parceled Six Factor Vocational Identity, replicates the approach used in the first block,but now all analyses are conducted on item parcels to be consistent with previous identity status research (e.g., Crocetti,Rubini, & Meeus, 2008; Luyckx et al., 2005). Whereas the previous analysis employed thirty items with five items perfactor, this approach involves randomly combining the five items into two parcels (three items in one and two in the other)and then computing all the models outlined above for the item-level multi-group measurement models. In other words, theparcel approach substantially diminishes the number of estimates computed, and as a consequence, it has the effect ofincreasing the probability that the model fit will be improved relative to the item approach (Nasser & Wisenbaker, 2003). Inthis case, the fit of the measurement model employing all the participants and, as indicated by the CFI, RMSEA, and SRMR, isquite good and improved relative to the item-level approach reported above. Moreover, the multi-group CFA results suggestthat the high school and university samples exhibit equivalent measurement weights using the traditional (Δc2) and morerecent criteria discussed above (ΔCFI and ΔRMSEA). Finally, the high school and college samples exhibited metric invariancebut not scalar invariance.

The net of the results reported in Table 3 suggest that the measurement model adequately fits the data for the entiresample and exhibits metric invariance across the high school and university samples. The fit indices from the parcel approachalso compare well to those reported in previous identity status research using the same approach (Crocetti, Rubini, & Meeus,2008; Luyckx, Goossens, Beyers, et al., 2006). Table 2 contains the item factor loadings for the final model. The VISA itemsappear to assess six underlying constructs representing subscales of the career commitment, exploration, and reconsiderationdimensions, and the configuration of these items relative to the factors and the metric of the loadings appears to remaininvariant across the high school and university years.

The six subscale scores were created by computing the mean response from the set of item indicators so that subscalescores could be interpreted on the basis of the original scale of the items. The descriptive statistics by age group are reportedin Table 4 and reveal that both age groups tend to exhibit commitment, exploration, and self-doubt at levels above themidpoint of the Likert scales around “agree and disagree” and trending toward “agree” and commitment flexibility below the

Table 4Correlations between indicators of identity statuses by age group.

M SD a 2 3 4 5 6

High school sampleCommitment 1. Commitment making 3.35 .81 .84 .56* .48* .10 �.11* �.39*

2. Commitment identification 3.84 .62 .76 .64* .33* �.28* �.16*Exploration 3. In-depth exploration 3.90 .60 .77 .53* �.21* �.08

4. In-breath exploration 3.69 .69 .83 .09 .35*Reconsideration 5. Self-doubt 2.51 .80 .79 .49*

6. Commitment flexibility 3.18 .79 .83

University sampleCommitment 1. Commitment making 3.45 .83 .82 .60* .49* �.08 �.38* �.39*

2. Commitment identification 3.98 .64 .79 .63* .09 �.45* �.29*Exploration 3. In-depth exploration 4.06 .62 .79 .31* �.30* �.15*

4. In-breath exploration 3.48 .78 .82 .15* .43*Reconsideration 5. Self-doubt 2.37 .78 .81 .61*

6. Commitment flexibility 2.98 .78 .81

Note: High school sample, N ¼ 432; University sample, N ¼ 343.*p < .05.

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midpoint and trending toward “disagree”. The correlation matrices suggest that constructs within the three dimensionsgenerally exhibit stronger correlations than do constructs between dimensions, lending more credibility to the overallconceptual model. The exception to this trend is that commitment making, commitment identification, and in-depthexploration exhibit a cluster of moderately sized correlations (Kline, 2004), which suggests that in-depth exploration may bestrongly tied to the process of committing to a career (Crocetti, Rubini, & Meeus, 2008). There is also a consistent pattern ofweak to moderate negative correlations between the reconsideration subscales and the commitment and explorationsubscales. This suggests that increased reconsideration may thwart identity development and/or vice versa. The results inTable 4 also demonstrate that the university sample generally demonstrates slightly stronger correlations than does the highschool sample.

The means of the six subscales were compared across the high school and college samples via ANOVA to ascertain theextent of the difference between the two groups. Taking a developmental perspective would suggest that the universitysample would exhibit more commitment making, commitment identification, and in-depth exploration and less in-breadthexploration, flexibility, and doubt than the high school sample given their closer proximity to the agewhen adolescents makethe transition to adulthood and establish work roles. This hypothesis was confirmed for all of the constructs exceptcommitment making (results not tabled, but available upon request). The eta-squared estimates revealed, however, that thedifferences were generally quite small to the point of being almost trivial given that nomore than 2% of the variance in the sixsubscales was explained by age group.

The cluster model: Identifying identity statuses and invariance in statuses across age

With the measurement model of the six subscales established for the entire sample, the model exhibiting metricinvariance across the high school and university samples, and the differences between the means of the two samples being inthe predicted directions, statistically significant but small, the next step was to ascertain the appropriate number of clusters(or identity statuses) to characterize the six subscales. While there are many different approaches toward conductingexploratory cluster analysis, the approach espoused by Gore (2000) has been used in the identity status literature recently(e.g., Crocetti, Rubini, Luyckx, et al., 2008; Luyckx et al., 2005). This approach involves multiple steps and iterations withinsteps, and is, therefore, complex and computationally intensive. The cluster models were conducted on the entire sample andthen were conducted using a multi-group approach to discern cluster model consistency across and within the high schooland university samples. We also assessed the relative frequencies of participants occupying the clusters by the high schooland university samples to satisfy the age-based hypotheses.

In the first step, subscale scores were standardized (M ¼ 0, SD ¼ 1), and these transformed items were subjected tohierarchical cluster analyses employing Ward’s method and Euclidean distances. Gore (2000), Crocetti, Rubini, Luyckx, et al.(2008), and Crocetti, Rubini, & Meeus (2008) suggest choosing a solution that is most consistent with a priori theoreticalpredictions (e.g., number of clusters and pattern of subscale scores within clusters), parsimony of the cluster solution (i.e.,choosing solutions with a minimum number of clusters), and the capacity of the cluster to explain the variance in thevariables used in the cluster solutionwith 50% explained variance for each variable being the target. We examined the resultsfrom the hierarchical cluster analyses for the combined sample and for the high school and college samples independentlyand concluded that solutions ranging from four to nine clusters were more or less satisfactory for the whole sample andacross the high school and college groups.

The range of solutions from the first step was then subjected to a second set of tests involving an iterative k-means clusteranalysis. This procedure begins by randomly assigning the sample into two groups. The cluster centers of each group from thefirst step are used as initial cluster centers for a series of k-means analyses that assign participants to clusters ranging fromfour to nine. Then, another set of k-means analyses are computed for each group, but in this case, the cluster centers from theopposite group are used to assign participants to the clusters. The two sets of k-means yield two sets of cluster assignmentsper group. The sets within a group are then compared via Cohen’s kappa (Cohen, 1960) to determine the reliability of clusterassignment, or in other words, the degree towhich participants in each group are assigned to the same cluster given differentinitial cluster centers. This entire second set of tests also was conducted by comparing the high school and universityparticipants. The net of these results is depicted in Fig. 1.

As the number of clusters increases from four to nine, the mean explained variance of the items used to define the clustersincreases from 47% to 64%. Cohen’s kappa, as computed by the random split groups and high school versus university splitgroups (see thinner lines in Fig. 1), tends to increase from four to six clusters and then declines beyond this point. The meankappa for the random and school split approaches was computed and is depicted as a thicker line in Fig. 1. The trend depictedby the mean kappa line reveals that the maximummean kappa of the random and school-level splits is 65% and is reached atsix clusters. The six-cluster solution typically explains about 58% of the variance in the variables used to define the clusters.These results suggest substantial agreement across the random split and school-level samples (Fleiss, 1981; Landis & Koch,1977) and demonstrate that the six-cluster solution explains an adequate amount of variance in the variables used tocompose the clusters (e.g., >50% of the variance explained; see Crocetti, Rubini, Luyckx, et al., 2008). These results led us toconclude that the six-cluster solution was the most satisfactory solution, which leads to the inference that the threedimensions as indicated by six subscales can be used to identify six identity statuses.

The means of the six subscales of the career commitment, exploration, and reconsideration dimensions by clustermembership for the entire sample and for the high school and university samples are depicted in Fig. 2. This figure also

Fig. 1. Cohen’s kappa and explained variance across a range of cluster solutions.

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includes identity status labels suggesting thatMarcia’s four identity statuses are confirmed alongwith two additional statusesentitled searching moratorium and undifferentiated. The searchingmoratorium pattern is most like a pattern of the same namediscovered within the Meeus and Crocetti model and is composed of participants who exhibited a pattern of morecommitment and exploration and elevated reconsideration. We interpret this pattern to be reflective of adolescents andyoung adults who may be vacillating between the achieved and moratorium statuses in a manner akin to the moratorium-achievement-moratorium-achievement (MAMA) cycle proposed by Marcia (1993). The second additional group is charac-terized as undifferentiated and represents more than 20% of the sample. This group is most like the undifferentiated patterndiscoveredwithin the Luyckxmodel and exhibits a profile of scores across the six subscales that vacillate around themean forthe entire sample, but the shape of the pattern is most reflective of the achieved pattern. Relative to the achieved pattern,undifferentiated participants score closer to the mean on commitment, exploration and reconsideration; hence, their profile

Fig. 2. Patterns of career commitment, exploration, and reconsideration for the six identity cluster solution.

E.J. Porfeli et al. / Journal of Adolescence 34 (2011) 853–871 865

also can be considered less differentiated and more normative. Thinking in terms of the classic 2 � 2 identity status tablereflecting high and low levels of commitment and exploration that yield the classic four identity statuses, this group would besituated in the center of this table but leaning more toward the achieved status. This status is supported by a few studiesemploying the Luyckx model that have found a similar pattern termed undifferentiated (Luyckx et al., 2008, 2009).

A chi-square was computed to discern differences in the frequency of the identity statuses across the high school anduniversity samples. Similar to the developmental hypothesis pertaining to the six subscale scores, with the universitystudents expected to be more advanced than the high school students, we predicted that the university students would bemore likely to occupy the achieved and diffused statuses when compared with the high school students. The results sup-ported this hypothesis, c2 (5, N ¼ 775) ¼ 28.46, p < .001. These results also demonstrated that a greater fraction of universitystudents occupied the foreclosed status and a smaller fraction occupied the searching moratorium status relative to the highschool sample. In other words, university students disproportionately occupied the statuses exhibiting higher levels ofcommitment and lower levels of reconsideration relative to the high school students.

Validation tests: Relationships between identity statuses and validation measures

Predictive validity tests were conducted by employing the six identity statuses as predictors of participants’work valencesalong affective and experiential dimensions and indicators of well-being. The general hypothesis was that identity achievedparticipants would exhibit a more positive and less negative work valence and identity diffused participants would exhibitthe reverse pattern. Results consistent with this hypothesis would support the validity of the VISA.

The four ANOVAmodels that were computed suggested that identity statuses are associated with mean differences acrossall four of the work valence variables, with achieved and diffused participants exhibiting the largest differences (Table 5 andFig. 3). Post-hoc contrasts (employing Bonferroni and Tukey estimates) demonstrated that the largest and statisticallysignificant mean differences were exhibited between the achieved and diffused groups, the foreclosed and diffused groups,and the achieved and searching moratorium groups (available upon request). The pattern of the means of the work valencevariables by the identity statuses suggested that the achieved participants generally have a more favorable and less unfa-vorable view of their future work lives while the reverse was observed of the diffused participants. The foreclosed group wasmost like the achieved group. The moratorium, searching moratorium, and undifferentiated identity status groups exhibita similar pattern of work valences with the positive aspects generally hovering around the grand mean.

TheANOVAmodels forwell-beingdemonstrated that the achievedgroupexhibited themost favorable characteristics, and thesearchingmoratoriumanddiffusedgroupsexhibitedthe least favorablewell-being. It shouldbeunderscoredthat the indicatorsofwell-being differed for the high school and university samples. The high school students completed an assessment of their coreself-evaluations, and the university sample completed the DASS, which provides indications of participants’ depression, anxiety,and distress. The results are, therefore, reported separately for the two samples, and the expected direction of effects is reversedgiven that core self-evaluations are scaled such that higher scores reflect increasing favorability and the DASS is scaled in anunfavorable direction (Table 5 and Fig. 3). All the indicators of well-being, except stress, exhibited statistically significantdifferences across the identity status groups. The post-hoc contrasts (employing Bonferroni and Tukey estimates) suggested thatwell-beingdifferedmostbetween theachievedanddiffusedgroupsandbetweentheachievedandsearchingmoratoriumgroups.

Discussion

This study supports an elaboration of Marcia’s (1966) two-dimensional model of global identity status by confirming thatcareer exploration, commitment, and reconsideration, derived from the Luyckx (Luyckx et al., 2005; Luyckx, Goossens, Beyers,et al., 2006; Luyckx, Goossens, Soenens, et al., 2006) and Meeus and Crocetti models (Crocetti, Rubini, Luyckx, et al., 2008;

Table 5Predictive validity of the VISA: means (standard deviations in parentheses) and ANOVA results.

Positive workaffectivity

Negative workaffectivity

Positive workexperiences

Negative workexperiences

Core self-evaluationsa

Depressionb Anxietyb Stressb

Achieved 4.53 (.45) 1.68 (.49) 4.50 (.46) 2.62 (.67) 3.95 (.58) .56 (.79) .53 (.58) .90 (.80)Searching

moratorium4.29 (.56) 2.13 (.68) 4.06 (.57) 3.00 (.64) 3.35 (.55) .80 (.95) .74 (.77) 1.17 (.99)

Moratorium 4.08 (.48) 2.03 (.60) 4.16 (.41) 2.75 (.57) 3.64 (.61) .64 (.62) .60 (.63) .86 (.69)Foreclosed 4.36 (.42) 1.80 (.56) 4.37 (.39) 2.60 (.52) 3.83 (.50) .47 (.57) .49 (.48) .84 (.61)Diffused 3.78 (.54) 2.29 (.71) 3.75 (.57) 2.83 (.50) 3.21 (.50) .79 (.69) .79 (.73) 1.00 (.66)Undifferentiated 4.16 (.46) 1.94 (.52) 4.14 (.46) 2.72 (.47) 3.57 (.60) .37 (.40) .34 (.38) .70 (.53)Grand mean 4.14 (.54) 2.00 (.63) 4.13 (.53) 2.75 (.56) 3.57 (.60) .56 (.64) .55 (.59) .86 (.68)

F 33.22* 15.47* 34.36* 5.18* 18.93** 4.13** 5.08** 2.44h2 .19 .10 .20 .04 .19 .06 .07 .04N 703 703 703 703 401 324 332 328

*p < .05, **p < .01.a High school sample only.b University sample only.

Fig. 3. Patterns of anticipated work valences and well-being by identity status. The positive affectivity and experiences lines almost entirely overlap as do thedepression and anxiety lines.

E.J. Porfeli et al. / Journal of Adolescence 34 (2011) 853–871866

Crocetti, Rubini, & Meeus, 2008; Meeus, 1996), aid in identifying multiple vocational identity statuses. Participants who wereassigned to the resulting vocational identity statuses exhibited predictable differences in work valences and well-being. Thesefindings support work toward unifying Luyckx and Meeus and Crocetti models into one measurement model of identity status.

The correlational and multi-group confirmatory factor analyses employing the six constructs across the high school anduniversity samples support the conclusion that the VISAmeasures two distinct manifestations of exploration, commitment andreconsideration. The cluster analyses of the VISA suggested that it can reliably identify six groups reflectingMarcia’s four identitystatuses plus two other statuses termed searching moratorium and undifferentiated (see Fig. 4). While the members of thesearchingmoratorium status expressed levels of exploration and commitment akin to those in the achieved status, they differedfrommembers of the achieved status in that they expressed the highest levels of career self-doubt and flexibility. This status ismost consistent with the MAMA cycle (Stephen et al., 1992) and the searching moratorium status found within the Meeus andCrocetti model (Crocetti, Rubini, Luyckx, et al., 2008). This status is depicted as a double-headed arrow in Fig. 4 to reflect itspresumed dynamic nature. Members of the undifferentiated status group differed from the others because their pattern wasalmost completely normative (i.e., at or around the mean) for all six indicators and is most consistent with the undifferentiatedstatus identifiedwithin the Luyckxmodel (Luyckx et al., 2008; 2009). Those participants classified as belonging in the achieved,moratorium, foreclosed, anddiffusedstatusesexhibitedcareerexploration, commitment, andreconsiderationpatternsconsistentwithMarcia’s identity status frameworkandpreviousempiricalworkwithin the LuyckxandMeeusandCrocettimodels.Of all thepatterns, the achieved and undifferentiated patterns were most similar, but the achieved group expressed commitment,exploration, and reconsideration at levels that were less attenuated than the undifferentiated group.

The results from the CFAs, combinedwith the cluster analyses, suggested that identifying andmeasuring distinct dimensionsof commitment, exploration, and reconsideration may aid in refining the vocational identity status framework. The addition ofsearchingmoratoriumandundifferentiatedvocational identitystatuses couldbetteralignvocational identity status researchwithinnovationsoccurringwithin theglobal identity status literature. Thepsychometric results also suggest that theVISAmaybeusedtoenhance future studiesaiming toemployoneormoreof thecareerexploration, commitment, and reconsiderationconstructsas

Achieved Moratorium

Foreclosed Diffused

Commitment

More Less

Exploration

More

Less

Searching

Undifferentiated

Fig. 4. Identity status model: An elaboration.

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predictors and outcomes rather than components of identity statuses (e.g., Porfeli & Skorikov, 2010). These results also largelyconfirm the original two-dimensional model proposed by Marcia and elaborate it by suggesting the existence of two additionalstatuses thatfitwithin theoriginal framework. Thefirstnewstatus isanundifferentiatedpattern that is situatedat themidpointofexploration and commitment. The second new status involves tentative commitments and is an intermediate status situatedbetween the conceptual spaces previously determined to be the achieved andmoratorium statuses.While the conceptualmodelprincipally includes twodimensions, this andother researchhas consistently demonstrated thatmore than two indictors of theseprocesses are needed along with a reconsideration aspect to reliably detect these statuses. Bridging the two predominantelaborations of theMarciamodel (i.e., the Luckyx andMeeus&Crocettimodels) seems like a fruitful avenue that shouldbe furtherexplored in the global and domain-specific identity status literatures.

Comparing the three dimensions of identity status and the frequency of identity statuses across the high school anduniversity samples hinted at the presence of a developmental trend leading from statuses involving less to more commit-ment. Recent longitudinal research identified two typical progressions in global identity statuses in support of thecommitment trend, which included a pattern leading from diffused to foreclosed, moratorium, and finally achieved status,and another pattern progressing from diffused to foreclosed, achieved, and finally moratorium status (Al-Owidha, Green, &Kroger, 2009). Findings of the present study are consistent with these patterns to the extent that the university sampleexhibited a greater proportion of participants within statuses reflecting higher commitment and lower doubt than did thehigh school sample. Future research could better test the validity of this finding with longitudinal data spanning the middleadolescent to young adult years, given the known limitations of making developmental assertions on the basis of data fromdifferent cohorts (Smith, 2008).

The results from the validation tests of the VISA support the well-established finding that identity statuses are distin-guished by differences in well-being (Waterman, 2007). The achieved group exhibited the most favorable pattern of identityprogress, work valences, and well-being. The foreclosed group exhibited a pattern most like the achieved group, with themain exception being that they have arrived at what looks to be a premature career commitment. The diffused groupexhibited the least favorable pattern of identity progress, work valence, and well-being. These three groups, therefore, exhibitclearly unique patterns.

The patterns expressed by themoratorium and undifferentiated groups are clearly different from the achieved, foreclosed,and diffused groups in that they reflect a more nuanced view of work. The moratorium and undifferentiated groups perceivetheir future work as neither categorically favorable nor unfavorable; rather, they expect their work to include favorable andunfavorable aspects at moderate to high levels of each. They also exhibited normative levels of well-being. While themoratorium and undifferentiated groups are similar, they are most distinguished by their pattern of career exploration,commitment, and reconsideration, with the moratorium group being much more focused on exploration than the undif-ferentiated group.

While the searching moratorium group shared relatively balanced positive and negative work valences, like their peers inthe moratorium and undifferentiated groups, they exhibited some of the poorest levels of well-being, expected to experiencenegative aspects of work at levels that rivaled the diffused group, and the most amount of career self-doubt and flexibility.The searching moratorium group may be a snapshot of those participants caught in a MAMA cycle (Stephen et al., 1992).Occupying the searching moratorium status or vacillating between the achieved and moratorium statuses appears to bedifficult. While this group has made much progress toward exploring and committing to a career, this group still expressesa unique combination of elevated career self-doubt and flexibility. These findings for the searching moratorium group inrelationship to the others suggest that the act of reconsideration involves favorable (flexibility) and unfavorable (doubt)elements that may yield different consequences to one’s well-being. The apparently unfavorable form of reconsideration,coupled to the belief that work choices will lead to a world that will bring many negative experiences and emotions, couldtake a toll on the well-being of those in the searching moratorium group and feel like a barrier preventing them from fullyachieving a worker identity. On the contrary, reconsideration marked by less of each aspect and particularly a lot less self-doubt, may be felt as a means of making progress for those in the moratorium and undifferentiated statuses. Another pointabout the searching moratorium status should be made. High school students occupied this group and all the lowercommitment groups disproportionately more than did university students, suggesting that high school is a critical periodduring which commitments are being developed. When high school students disproportionately occupied a high commit-ment status group, as in the case of the searching moratorium status, their commitments were more frequently paired withelevated career reconsideration and, particularly, with self-doubt. The searching moratorium group presents a uniquepattern occurring more during the adolescent years and underscores the potential value of expanding the career recon-sideration construct to include favorable and unfavorable aspects (Crocetti, Rubini, Luyckx, et al., 2008; Crocetti, Rubini, &Meeus, 2008).

The results from all of the analyses can be distilled further to suggest that relationships among identity processes, workvalences, and well-being can be categorized into four variable patterns or fields including a pattern of (1) advanced identityprogress, an optimistic if not Pollyannawork valence, and higher levels of well-being (achieved and foreclosed); (2) moderateidentity progress, balanced positive and negative work valences, and normative levels of well-being (moratorium andundifferentiated); (3) delayed identity progress, a pessimistic or gloomywork valence, and low levels of well-being (diffused);and (4) mixed identity progressmarked by elevated commitment and exploration, paradoxically coupledwith higher levels ofreconsideration and particularly self-doubt, a work valence marked by higher levels of the unfavorable aspects, and poorlevels of well-being (searching moratorium).

E.J. Porfeli et al. / Journal of Adolescence 34 (2011) 853–871868

Conclusions

Measures designed to assess global identity statuses have generally relied upon items pertaining to multiple (e.g., reli-gious, vocational, and political) roles. They often failed, however, to reliably yield role-specific identity statuses when dividedinto role-specific scales (Skorikov & Vondracek, 2007b). Theory and research suggest that a vocational identity may emergeduring adolescence (Erikson, 1968) and in advance of other role-specific identities (Skorikov & Vondracek, 1998). Thus,domain-specific measures like the VISA are needed as researchers explore the contribution of vocational identity develop-ment to global identity development and to adjustment and the transition from school to work.

While the original conceptual model presented by Marcia included two dimensions, recent empirical research, includingthis study, has demonstrated that amore refined identity status frameworkmaymore adequately account for adolescents andyoung adults who are in an undifferentiated status and those who are vacillating between the achieved and moratoriumstatuses over time. Based on the CFAs and the cluster analyses, a reconsideration dimensionwas added to the exploration andcommitment dimensions identified by Marcia. This resulted in the addition of two identity statuses named searchingmoratorium (as in the Meeus & Crocetti model) and undifferentiated (as in the Luyckx, et al. model). The clear convergence ofresults from the present study and the empirically derived global identity status models named above bodes well for a muchneeded alignment of vocational identity status research with innovations occurring within the global identity statusliterature.

The predictive validity results obtained with the VISA are consistent with other identity status studies pointing todifferences in well-being and adjustment across statuses (Meeus et al., 1999; Skorikov & Vondracek, 2007a; Vondracek,1994). They also suggest that vocational identity statuses can aid in identifying a pattern of work valences and well-being that could place certain adolescents in a more or less advantaged position as they become increasingly engaged in theworld of work. The identity status literature posits a developmental progression from the diffused status and tendingtoward the moratorium and achieved statuses (Al-Owidha et al., 2009), and this study, in part, supports such a progression.The present findings add to our understanding by demonstrating that the statuses may be associated with work valence andwell-being patterns that could be fairly stable over time. Thus, it is likely that the VISA could serve as an importantinstrument in developmental and behavioral research devoted to understanding the role of work in the lives of adolescentsand young adults.

Some important limitations of the present research should be noted. First, the study is limited by its reliance onexploratory methods (e.g., cluster analysis) that can be strongly influenced by inherent biases in the sample and that fail tooffer a definitive means of assessing model fit or statistical significance. Second, the study relies upon a small to moderatecross-section of middle adolescents attending several high schools and young adults attending one university in Ohio. Giventhe sample and the sampling frame, generalizations to adolescents and young adults outside the geographic and socio-demographic boundaries of the sample must be done with great caution. Evenmore caution must be exhibited when makingdevelopmental assertions. Generalizing this study to adolescents and young adults and making inferences about develop-ment spanning these periods must, therefore, be done with great caution.

Finally, the criterion variables used to assess the validity of the VISAwere deemed to be correlates of identity status ratherthan antecedents or outcomes. Longitudinal data would permit a more direct test of the causality of the statuses and criterionvariables by assessing their longitudinal relationships. These limitations call for ongoing efforts to specifically assess andimprove the VISA, and to more broadly explore the existence, antecedents, and outcomes of vocational identity statusesacross the adolescent and young adulthood periods. As a consequence of these limitations, replication of the principalfindings of this study with other samples, and preferably longitudinal data, is clearly needed.

Acknowledgment

We would like to thank Kay Vincent and her colleagues at Excel TECC for their work in collecting the data used in thisproject.

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