Career Decision Making, Self-efficacy,

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Effect of Mode of Interest

Assessment on Clients CareerDecision-Making Self-Efficacy

Rachel A. UffelmanLinda Mezydlo SubichNathan M. DiegelmanKimberly S. WagnerRebekah J. Bardash

The University of Akron

To compare the effects of three different modes of interest assessment on careerdecision-making self-efficacy, 81 career-undecided college students participated inone of the following four conditions: an assessment intervention using the StrongInterest Inventory, an intervention using one of two methods of applying the Self-Directed Search, or a no-treatment control group. Change in career decision-making self-efficacy from pre- to posttest was assessed. Career decision-makingself-efficacy increased significantly for all three treatment groups, and in eachcase, pre-post differences for the treatment groups exceeded the pre-post differ-ence for the no-treatment control group. Differences in outcomes among thethree treatment groups were not observed.

Keywords: career decision making, self-efficacy, college students, assessment

Interest assessment traditionally has been an integral part of the career coun-seling done on college campuses. Often this assessment involves use of theStrong Interest Inventory (SII; Harmon, Hansen, Borgen, & Hammer, 1994) orthe Self-Directed Search (SDS; Holland, Fritzsche, & Powell, 1994), two of the

three most used interest measures (Watkins, Campbell, & Nieberding, 1994).Such interest assessments are used by counselors to inform clients career deci-sion making in the hope that the results may enhance the quality of clientscareer decisions (Brown & Lent, 1996). Yet, as Chartrand and Walsh (2001)pointed out, there is a pressing need to examine our assessment service deliverymodels (p. 249). In this study, we aimed to extend knowledge regarding the use

This research was supported by a grant from Commission VI of the American College Personnel Association.The authors wish to thank Susan I. Hardin for her contributions in developing the treatment protocols.Correspondence should be directed to the first author at [email protected].

JOURNAL OF CAREER ASSESSMENT, Vol. 12 No. 4, November 2004 366380DOI: 10.1177/1069072704266651 2004 Sage Publications

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Uffelman et al. / INTEREST ASSESSMENT AND DECISION-MAKING SELF-EFFICACY 367

of the SDS and SII in career counseling by comparing their effectiveness inincreasing college students career decision-making self-efficacy.

The construct of career decision-making self-efficacy derives from Banduras(1986) general self-efficacy theory. Self-efficacy is defined as a persons situation-specific beliefs that he or she can carry out the actions necessary to accomplishsuccessfully a given task. According to the theory, level of self-efficacy is a pri-mary determinant of various outcomes, including likelihood of undertaking atask, amount of effort expended in pursuing a goal, and degree of perseverancein responding to challenges or barriers to progress.

Career decision-making self-efficacy is especially relevant to the endeavor ofcareer counseling because persons with higher levels of career decision-makingself-efficacy report more confidence in their ability to make academic and occu-

pational choices (Taylor & Betz, 1983; Taylor & Popma, 1990). Importantly, thisconfidence has been associated positively with persons reported degree of voca-tional decidedness (Srsic & Walsh, 2001; Taylor & Popma, 1990). It also hasbeen associated positively with considering a greater range of occupations(Church, Teresa, Rosebrook, & Szendre, 1992), having a more stable career pat-tern (Gianakos, 1999), and using a more rational and a less dependent decision-making style (Mau, 2000). Thus, career decision-making self-efficacy may beconceptualized as an essential component of adaptive career exploration process-es and outcomes. Because a fundamental aim of career counseling is for coun-

selors to assist clients in making good academic and occupational decisions,knowledge of how to augment clients career decision-making self-efficacy maybe important.

The research literature however provides meager guidance with regard to howto increase effectively clients career decision-making self-efficacy. One of thefew available studies of how a career counseling intervention influences careerdecision-making self-efficacy is the work of Luzzo and Day (1999). They com-pared pre- and postintervention career decision-making self-efficacy scores offirst-year college students who took the SII and received group feedback, took theSII and received no feedback, or were part of a no-treatment control group. They

found that the college students who took the SII and received feedback in agroup interpretive session evidenced increases in their career decision-makingself-efficacy as compared to students who received no feedback on their SIIresults or who were members of the control group. Luzzo and Day suggested thattheir results are consistent with Banduras (1986) assertion that self-efficacy maybe increased via performance accomplishments and verbal persuasion as thesemechanisms were involved in the interpersonal group interpretation protocolused to provide their participants with SII feedback.

Another way to conceptualize Luzzo and Days (1999) findings however isfrom the framework of Brown and Krane (2000). These authors reported on aseries of meta-analyses of the career counseling outcome literature; the outcomesmeasured in the 62 studies included in their analyses varied but included careerdecision-making self-efficacy. Brown and Krane observed that the following five


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368 JOURNAL OF CAREER ASSESSMENT / November 2004

critical ingredients appeared most responsible for positive outcomes in extantcareer counseling outcome research: written exercises, individualized interpreta-

tions and feedback, world of work information, modeling opportunities, andattention to building support for choices within ones social network. More thanone of these ingredients seem relevant to the work of Luzzo and Day; Luzzo andDays description of their intervention clearly included the opportunity for indi-vidualized feedback (despite the group interpretation format) and world of workinformation. It may be that these elements of their assessment interventionaccounted for the significant increase observed in participants career decision-making self-efficacy.

If more general mechanisms (i.e., those implicated by Brown & Krane, 2000)underlie Luzzo and Days (1999) results, use of assessment instruments other

than the SII (e.g., the SDS) may result in similar client outcomes, but this hasnot yet been established. Given the practical and theoretical utility of Luzzo andDays findings, it seems important to extend their line of research to anotherinterest measurethe SDS. Such an extension is of interest not only because ofthe widespread use of the SDS (Watkins et al., 1994) but because it may shedlight on how the specifics of an assessment modality relate to increases in careerdecision-making self-efficacy. Indeed, career assessment with the SDS offersmore procedural flexibility than that with the SII as counselors may choose tohave clients complete the SDS alone and then meet to interpret results (much

like the typical use of SII) or to work through the SDS booklet together in ses-sion. These different approaches conceivably could involve different numbersand intensities of Brown and Kranes (2000) critical treatment ingredients.Indeed, Brown and Krane speculated that the effectiveness of self-directed careerinterventions (i.e., the SDS) could be enhanced by incorporation of additionaltreatment ingredients as their results indicated an additive effect on outcome ofincluding multiple critical treatment elements.

The present study therefore had two purposes. The first was to extend the lineof research of Luzzo and Day (1999) by investigating how two commonly usedassessment tools, the SII and SDS, compare in their ability to influence clients

career decision-making self-efficacy. It was hypothesized that administration andsubsequent interpretation of either instrument would result in an increase inclients career decision-making self-efficacy greater than that observed for the no-treatment control group.

The second purpose was to examine whether varying degrees of incorpo-ration of Brown and Kranes (2000) critical treatment ingredients in an assess-ment modality influence changes in career decision-making self-efficacy. Thisquestion was addressed by comparing the effects on career decision-making self-efficacy of alternate implementation methods for the SDS. Specifically, a col-laborative, process-oriented approach to delivering and interpreting the SDS wascompared to a more typical approach that involved the instrument being com-pleted independently by the client and then interpreted by the counselor in asecond session (similar to what is done typically with the SII). It was hypothesized


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that the process approach to the SDS would result in more change in careerdecision-making self-efficacy due to the greater opportunity for clients to receive

modeling, feedback, and relevant information from the counselor over the twosessions they worked together (compared to the single interpretive sessionapproach). Consequently, clients who experienced the process approach to theSDS were expected to demonstrate greater gains in career decision-making self-efficacy than were those who completed either the SDS or SII independentlyand subsequently received a SDS or SII interpretation. No differences werehypothesized between the latter groups.

METHOD

Participants

Participants were 81 college students who were recruited via introductorypsychology courses, ranging in age from 18 to 45 with a mean age of 23.67 years(SD = 6.61 years). Of the participants, 69% were women; 79% identified them-selves as White/Caucasian, 15% identified as Black/African American, 5% iden-tified as Asian American/Pacific Islander, and 1% identified as biracial. Partici-pants were most commonly first-year students (47%), consistent with the typical

college student seeking career counseling. The vast majority of participants(89%) had taken no other psychology classes beyond introduction to psychology.

Based on their responses to a demographic questionnaire administered as partof the study, it was seen that the following descriptors captured the majority ofparticipants previous and current job fields: food service (e.g., server, cook),sales/marketing (e.g., salesperson, cashier, telemarketer, customer service), cleri-cal (e.g., secretary), laborer (e.g., factory worker, landscaper), human and publicservices (e.g., teaching, camp counselor, police officer), business/informationtechnology (e.g., programmer, administrator), health care (e.g., nurse, aide), and

military. High-point Holland (1997) codes of the participants in the three treat-ment conditions (as determined by the interest assessments used in this research)were as follows: 3% realistic, 18% investigative, 17% artistic, 42% social, 12%enterprising, and 8% conventional (RIASEC). These distributions are compara-ble to those obtained for college student populations as published in the SDSmanual (Holland et al., 1994).

Instruments

College students reactions to two measures of interest assessment, the SII(Harmon et al., 1994) and the SDS (Holland et al., 1994), were examined. TheSII is a computer-scored inventory; the SDS is a hand-scored booklet. Both meas-ures assess interests as organized by Hollands (1997) six interest areas (i.e., real-


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istic, investigative, artistic, social, enterprising, and conventional), and both arerecognized as reliable and valid tools (Harmon et al., 1994; Holland et al., 1994).

Self-Directed Search. The SDS (Holland et al., 1994) is a self-administered,hand-scored assessment instrument that measures career interests. Items aregrouped according to Holland (1997) code and assess for interest in specific activ-ities, competencies, and occupations as well as ability self-estimates. Itemresponses are summed to obtain scores for each of Hollands RIASEC categories,with the top three generally comprising an individuals Holland code.

A wide range of research studies has demonstrated support for the reliabilityand validity of the SDS in assessing Holland code type (Holland et al., 1994;Spokane & Holland, 1995). For instance, Holland and Nafziger (1975) present-

ed correlational data supporting convergent validity of the SDS with a range ofother vocational assessment tools. Dumenci (1995) found support for convergentand discriminant validity of the SDS using hierarchically nested structural modeltests. Scores on the SDS also have been demonstrated to relate significantly toself-efficacy expectations (Feehan & Johnston, 1999).

Strong Interest Inventory. The SII (Harmon et al., 1994) is a computer-scoredinventory that assesses a wide range of vocational interests. The measure consistsof items corresponding to 211 occupational scales and 25 basic interest scales,grouped according to six general occupational themes based on the RIASECmodel (Holland, 1997). Empirical support for the concurrent validity, pre-dictive validity, and reliability of the occupational scales, basic interest scales,and general occupational themes is robust (Donnay & Borgen, 1996;Harmon et al., 1994).

Career Decision-Making Self-Efficacy Scale. Participants career decision-making self-efficacy was assessed with the Career Decision-Making Self-EfficacyScale (CDMSES; Betz & Taylor, 1994; Taylor & Betz, 1983), an often used andwell regarded measure. The CDMSES is a 50-item self-report instrument that

assesses self-efficacy expectations for completing a broad range of tasks related tocareer decision making. Respondents are asked to rate their perceived ability tocomplete the tasks on a scale from 0 (no confidence) to 5 (complete confidence).Item responses are summed to obtain an overall score. Prior investigations haveshown internal consistency to range from .93 to .97, and CDMSES scores havecorrelated in expected directions with measures of self-esteem, career decision-making attitudes, and career decidedness (Luzzo, 1996). Reliability and validityevidence were also provided by Luzzo (1993). For the current sample, internalconsistency reliability as measured by Cronbachs alpha was .94 for the pretestadministration and .96 for the posttest administration.

Demographic questionnaire. Basic demographic information (e.g., gender,age, race/ethnicity, year in school, self-reported grade point average [GPA], psy-chology courses taken, and recent work history) about the participants was gath-


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ered via a questionnaire designed for use in this study. Participants also reportedwhether they had declared a major and/or career path or what majors and careers

they were considering. Those who identified a chosen major and/or career alsorated their confidence that this choice would remain stable.

Procedure

Students were screened verbally prior to inclusion to verify that each was in astate of indecision about his or her career path. Specifically, students were askedprior to participation whether they had chosen a major and/or a career to whichthey aspired. Students who reported being fairly certain (i.e., greater than 60%

certain that they would not change their career plans) of a career path were notincluded so as to maximize the samples similarity to actual career counselingclients. Following this screening, participants were assigned randomly to one ofthe four experimental groups.

Because the SDS is flexible in its format and can be used as a counselor-freeapproach or as an adjunct to traditional career counseling (Holland et al., 1994),we examined two approaches to using the SDS. In one, the student completedthe SDS alone and in a subsequent session discussed it with the counselor; in theother, the student and counselor together worked through the SDS in a collabo-rative, process-oriented manner over two sessions. Therefore, the four experi-mental groups were (a) assessment with the SDS followed by an interpretive ses-sion with a counselor, (b) process-oriented assessment/interpretation of the SDSover two sessions, (c) assessment with the SII followed by an interpretive ses-sion with a counselor, and (d) the no-treatment control group (see Table 1).These groups were comprised of 22, 19, 21, and 19 participants, respec-tively, and were similar in terms of participants age, F(3, 77) = .62, p >.05;gender, 2(3) = 1.72, p > .05; race/ethnicity, 2 (9) = 8.27, p > .05; year in school,

2 (12) = 8.30, p > .05; and self-reported GPA range, 2 (12) = 10.03, p > .05.Four counselors delivered the various treatments. Counselors ranged in age

from 23 to 28, and three were women. They were all enrolled in a doctoral pro-gram in counseling psychology, and faculty in that program supervised their workdelivering the interventions. All counselors were experienced in the administra-tion and interpretation of the instruments.

To ensure a high degree of uniformity among the counseling interactions,standard protocols for the SII and SDS standard and the SDS process adminis-tration and interpretation were used. Consistent however with the nature ofcareer counseling, counselors were encouraged to individualize their discussionswith participants. The two sessions for the three treatment groups took place anaverage of 14.20 (SD = 3.01) days apart (range = 5 to 21 days) to accommodateindividuals schedules and mail-in scoring of the SII.

Table 1 summarizes the four treatment intervention protocols. In the first ses-sion, all participants regardless of treatment group met individually with an


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experimenter, were verbally screened for career indecision, gave informed con-sent, filled out a demographic form and the CDMSES pretest, and set up anappointment for a second session to take place approximately 2 weeks later. For

the three active treatment groups, counselors were available to answer questionsas needed. Postcards were sent or follow-up phone calls were made to all partic-ipants as a reminder about the second appointment. Of participants who attend-ed an initial session, 84% completed both sessions. There was no difference inpretest CDMSES scores between participants who completed both sessions andthose who completed only the first session, t(94) = .49, p >.05.

Control group. In the first session, participants in the no-treatment controlgroup were excused immediately following completion of the demographic formand CDMSES pretest. Upon returning for their second sessions, those in this

group filled out the CDMSES posttest. They then were debriefed and given acopy of the SDS and Occupations Finder to take with them for their personal usealong with information about receiving career counseling through the universitycounseling centers.

SII group. In the SII group, in the first session, participants completed theCDMSES and the entire SII after reading its instructions. In the second session,participants in this group received an interpretation of their computer-generatedSII profile. First, counselors attempted to establish rapport by going over thedemographic form with participants and getting some background informationabout them. Next, participants were given some background information aboutHollands theory and how it structures the SII assessment. Participants were givena description of the six types and were asked to self-rank their top three types.

Table 1Treatment Groups and Experimental Design

Session 1 Session 2

Group Pretest Session Session Posttest

SII CDMSES SII completed SII interpretation CDMSESalone with counselor

SDS standard CDMSES SDS started SDS completedalone and interpreted

with counselor CDMSES

SDS process CDMSES SDS started SDS completedwith counselor and interpreted

with counselor CDMSES

Control CDMSES CDMSES

Note. SII = Strong Interest Inventory; CDMSES = Career Decision-Making Self-Efficacy Scale;SDS = Self-Directed Search.


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Counselors explained the hexagon and how the types participants chose fit intothe hexagon. The codes identified by the SII were compared and contrasted with

participant-derived codes. Next, the General Occupational Themes, BasicInterest Scales, and Occupational Scales were interpreted. Occupations wereexamined in descending order of interest similarity, with counselors attemptingto summarize participants interest patterns based on what participants indicatedwas interesting or useful. Finally, Personal Style Scales were described and par-ticipants standings on each were discussed. Counselors explained that scores hadto do with how participants like to work rather than what participants like to door their abilities. Throughout the interpretation, counselors attempted to inte-grate information across different sections of the SII and checked in with partic-ipants to explore how results corresponded to or contrasted with participants

views of themselves. Counselors discussed with participants how they could usethe SII information in their career decision-making process and gave them thecompleted SII materials to take home. Finally, participants filled out the CDM-SES posttest and were debriefed.

Clients varied in their responses to these sessions, and lengths ranged from 16to 50 minutes (M = 31.00, SD = 9.39). One-way ANOVA revealed that these SIIinterpretation sessions varied in length depending on the counselor, F(3, 16) =3.29, p < .05, and post hoc analyses showed that one counselors session lengthsdiffered significantly from those of two other counselors. This counselors average

session length for SII participants was 40.60 minutes (SD = 8.79) as compared tomean lengths of 27.33 (SD = 5.05) and 27.29 (SD = 9.72) minutes for the othertwo counselors. This difference in session length however was unrelated statisti-cally to CDMSES score changes.

SDS standard group. In the standard SDS group, in the first session, partici-pants completed the CDMSES and the demographics form. They also complet-ed the SDS after reading its instructions but were instructed not to compile thethree-letter code on the Summary Code page and to leave the code boxes blankin the daydreams section of the SDS. This was an attempt to limit participants

awareness of the meaning of Holland codes prior to their second session to ensuresimilarity with the other treatment conditions. When these SDS participantsreturned for their second sessions, they were treated as were participants in theSII condition in that counselors attempted to establish rapport by going over thedemographic form and gathering background information. Next, counselorsexplained Hollands theory and how it structures the SDS assessment.Participants were given a description of the six types and were asked to self-rankthe top three. Counselors next explained the hexagon and how the three typesparticipants chose fit into the hexagon. Next counselors discussed participantsresponses in the various SDS sections and attempted to discern patterns in theparticipants responses. Counselors and participants discussed the participantsresponses in the Daydreams, Activities, Competencies, Occupations, and Self-Estimates sections, with counselors asking participants to share the experiences


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that formed the basis for their responses and noting patterns of interest. In theSelf-Estimates section, counselors noted patterns in participants answers and

asked participants to clarify with whom they were making comparisons and onwhat basis or evidence. Finally, the summary code was calculated and counselorsexplained the consistency of the code, the differentiation, and the various possi-ble permutations. The codes identified by the SDS were compared and con-trasted with participant-derived codes. The occupational titles corresponding tothe derived Holland code that were of interest to participants were noted andcompared/contrasted with those in the Daydreams section.

Throughout the process, similar to interpretations in other conditions, coun-selors asked participants whether the results made sense, if they had questions,how the findings fit with how participants thought about themselves, and if the

results seemed accurate. Counselors ended by summarizing the themes thatemerged from interpreting the SDS and linking these with background informa-tion previously obtained. Counselors addressed how participants could use theresults in the future and what plans the participant had for proceeding after thesession. Finally, participants were given the completed SDS materials to takewith them and completed the CDMSES posttest and were debriefed before leav-ing. These sessions ranged in length from 22 to 55 minutes (M = 32.95, SD =8.39). One-way ANOVA confirmed that session length for this group did not varyby counselor, F(3, 17) = .27, p > .05.

SDS process group. Subsequent to completing the CDMSES and demo-graphic form in the first session, participants in the SDS process condition com-pleted the first portion of the SDS in collaboration with the counselor. For thistreatment group, strategies for discussing results were taken and adapted fromHarmon et al.s (1994) general strategies for interpreting the SII. First, counselorsattempted to establish rapport by going over the demographic form with partici-pants and getting some background information about them. Next, participantsstarted to work on the SDS, beginning with the Daydreams section and continu-ing through the Activities and Competencies sections. Counselors and partici-

pants together discussed the significance of participants competency ratingresponses, with the counselor asking follow-up questions about the liked and dis-liked activities marked by participants. Counselors also commented on overallpatterns of liked and disliked activities. After completion of the first three SDSsections, the first session was ended. These first sessions ranged in length from 25to 45 minutes (M = 37.26, SD = 5.67). One-way ANOVA confirmed that first ses-sion length for this group did not vary by counselor, F(3, 15) = .86, p > .05.

When the participants in the SDS process condition returned for their secondsessions, counselors oriented them by briefly reviewing what had been discussedin first session. Then counselors and participants started where they had left offby completing the Occupations section (with counselors asking what about vari-ous occupational titles sounded interesting or not appealing), the Self-Estimatessection (with counselors clarifying with whom participants were making com-


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parisons), and the Summary Code page. Next, counselors introduced Hollandstheory and how it structures the SDS assessment, as in the SII and SDS standard

conditions. The codes derived from the SDS were compared and contrasted withparticipant-derived codes. Finally, the summary code was examined again andcounselors explained the consistency of the code, the differentiation, and thevarious possible permutations. The occupational titles that were of interest toparticipants were noted and compared/contrasted with those in the Daydreamssection.

Throughout the process, similar to interpretations in other conditions, coun-selors asked participants if the results made sense, if they had questions, how thefindings fit with how participants thought about themselves, and if the resultsseemed accurate. Counselors ended by summarizing the themes that emerged

from interpreting the SDS and linking these with background information pre-viously obtained. Counselors addressed how participants could use the results inthe future and what plans the participant had for proceeding after the session.Participants were given their SDS materials to take with them, and they com-pleted the CDMSES posttest and were debriefed before leaving. These secondsessions ranged in length from 18 to 42 minutes (M = 28.00, SD = 7.65). One-way ANOVA confirmed that session length for this group did not vary by coun-selor, F(3, 16) = 1.23, p > .05.

RESULTS

Preliminary analyses indicated that the four treatment groups (i.e., SII, SDSstandard, SDS process, and no-treatment control) did not differ in their pretestscores on the CDMSES, F(3, 75) = 1.49, p >.05. Furthermore, initial repeatedmeasures analyses of pre- and posttest CDMSES scores for the four counselorsindicated no counselor and no counselor by treatment group effects (all ps >.05).Thus, it was concluded that no significant group differences in career decision-

making self-efficacy were present at the outset and that data across counselorscould be aggregated.To test the hypothesized treatment effects, a repeated measures ANOVA with

pretest and posttest CDMSES scores as the within-subjects factor and treatmentgroup membership as the between-subjects factor was computed. Results of thisrepeated measures ANOVA indicated significant time, F(1, 77) = 74.00, p


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entire sample was 3.75 and at posttest it was 4.00. Yet when the groups areexamined separately, it can be seen that the mean CDMSES score for the no-

treatment control group was relatively stable from pre- to posttest (Mpretest = 3.80,Mposttest

= 3.87), but the mean CDMSES scores for the three treatment groupsincreased .24 to .37 points from pre- to posttest for the three active treatmentgroups. Indeed, post hoc analyses of these scores using paired t tests indicated sig-nificant (p < .05) increases from pre- to posttest for all three of the active treat-ment groups but no such increase for the no-treatment control group. Effect sizesfor the two SDS groups could be classified as medium-large to large (.68 for theSDS process group and .84 for the SDS standard group), and the SII group evi-denced a small to medium effect (.41) (Cohen, 1988).

DISCUSSION

The current study sought to increase understanding about the effects of threemodes of interest assessment on career clients career decision-making self-efficacy. Consistent with the underlying assumptions of and data regarding theeffective components of career counseling (Brown & Krane, 2000) and the find-ings of Luzzo and Day (1999), significant increases in career decision-makingself-efficacy were observed for participants in all three active treatment groups

(i.e., SII, SDS standard administration, and SDS process administration).Furthermore, students who received no career counseling intervention showedessentially no gains in career decision-making self-efficacy over a 2-week period,suggesting that interest assessment and interpretation in general is effective inenhancing self-efficacy about career decision making.

Contrary to our hypothesis however, pre-post changes in career decision-making self-efficacy did not differ reliably among the three active treatmentgroups. In particular, we expected that the greater counselor contact inherent inthe SDS process administration would lead to greater increases in CDMSES

scores due to greater opportunities for modeling and individualized interpreta-tion and feedback. Our results however suggest that varying levels of the criticalingredients identified by Brown and Krane (2000), at least as was operationalizedin the present research, did not differentially influence changes in career decision-making self-efficacy scores. It may be that the modest increase in counselor con-tact inherent in the SDS process group was insufficient to affect significantly par-ticipants scores. Future work that systematically controls and varies the dosageof certain critical treatment ingredients (per Brown & Krane, 2000) would helpclarify this issue. Perhaps a comparison between a truly counselor-free assessmentand an approach including counselor interaction and interpretation would clar-

ify this issue.The present lack of differences in career decision-making self-efficacy for the

three active treatment groups is consistent with the recent meta-analysis byWhiston, Brecheisen, and Stephens (2003). These researchers found few differ-


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ences in outcome across varied career counseling modalities, with only counselor-free approaches consistently producing poorer outcomes. The findings ofWhiston et al. bolster the interpretation that our failure to find group differencesreflects the true comparability of assessment modes. This is notable in that it sug-gests that all three of our assessment approaches are viable choices in careercounseling practice and all three intervention/assessment modes may be equallyeffective in increasing career decision-making self-efficacy. Given the researchsupporting the centrality of career decision-making self-efficacy to the careerexploration process (e.g., Church et al., 1992; Gianakos, 1999; Mau, 2000; Srsic& Walsh, 2001; Taylor & Betz, 1983; Taylor & Popma, 1990), this interpretationis encouraging as it offers practitioners support for their use of whichever interestassessment method best fits their style, clientele, or resources.

Alternatively, it is also possible that our three assessment modes do address dif-ferent needs or differentially complement diverse characteristics presented by

career clients. As such, the three modes may be differentially effective in enhanc-ing career decision-making self-efficacy for particular clients, but this may havebeen masked in the present research by our use of random assignment to thetreatment groups. That is, levels of relevant individual differences may have beendistributed equally among the treatment groups so we did not see group differ-ences in the dependent variable. Further research to identify individual differ-ence variables that may make certain forms of interest assessment more helpfulfor some clients seems warranted.

An especially interesting implication of the lack of differences between thethree active treatment groups concerns the difference in length of time spentwith a counselor. Participants in the SDS process group received roughlytwice as much individual contact with a counselor compared to participantsin the SII or SDS standard groups. Yet, the lack of difference in career decision-making self-efficacy changes among these groups suggests that increases in career

Table 2Career Decision-Making Self-Efficacy Scale (CDMSES)

Means and Standard Deviations for Treatment Groups at Pre- and Posttest

Pretest CDMSES Posttest CDMSES

Treatment Group n M SD M SD t

SII 22 3.82 .59 4.06 .58 3.29*

SDS standard 21 3.55 .46 3.92 .44 9.50**

SDS process 19 3.84 .41 4.14 .44 5.45*

Control 19 3.80 .44 3.87 .44 1.64

Total sample 81 3.75 .49 4.00 .49

Note. CDMSES mean scores could range from 1 to 5, with higher scores indicative of greater self-efficacy for career decision making. SII = Strong Interest Inventory; SDS = Self-Directed Search.

*p < .01. **p < .001.


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decision-making self-efficacy cannot be attributed simply to time spent individu-ally with a counselor. Again, further research into the manner in which time is

used in counseling could help clarify this issue.Finally, as the present work contributes to a body of knowledge that is rela-tively new and limited in scope (cf. Chartrand & Walsh, 2001), it seemed rea-sonable to consider further the descriptive pattern of the present results despitethe lack of statistically significant differences among the three active treatmentgroups. Consequently, we made a closer examination of the pre-post CDMSESscores across the three active treatment groups and noticed the SII group dis-played the smallest increase in CDMSES scores and the SDS standard groupexperienced the largest increase. Because the CDMSES taps confidence in onesown ability to make career-related decisions and because Bandura (1986) assert-

ed that performance accomplishments are the most effective manner of increas-ing self-efficacy, we speculate that this difference may be due to the amount ofindependent thinking required of clients using each tool. In other words, the SIIrequires relatively little independent thinking because the client responds toitems and receives a standardized printout of results that is then interpreted by acounselor. On the other hand, the SDS standard administration requires carefulconsideration by the client; he or she must navigate the process and consider theresults with less guidance by a counselor. Also, in this study, participants in theSDS process group were guided by a counselor throughout the experience; those

in the SDS standard condition navigated the instrument alone in the first session.It could be that those in the SDS standard group thus had greater opportunity toincrease their performance accomplishments because there was greater chancethat any learning would be attributed to the clients own effort. In addition, theSDS measures interests as well as self-rated abilities, and the SII taps only inter-ests; attention to a larger array of career-related self-constructs could account forthe slightly greater amount of observed change. As previously noted, this patterndoes not seem to be attributable to the amount of time spent with a counselor.Of course, the replicability of this pattern (including determination of whether itmight reach statistical significance with a larger sample) and the practical signif-

icance of the degree of pre- and posttest difference are open to question andrequire additional investigation.

Limitations

Although the present study used a relatively small sample of student clients,its attempt to isolate the effects of different modes of interest assessment on careerdecision-making self-efficacy is an offsetting strength. In addition, its use of acomparative methodology is an important extension of previous research.Furthermore, the limitations inherent in the use of student clients were at leastpartially minimized by screening individuals prior to the intervention to ensure abasic level of career indecision. The use of standard treatment protocols and fourdifferent counselors (cf. Luzzo & Day, 1999) for the three interventions and the


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failure to find counselor effects across treatment groups adds to our confidencethat the observed treatment effects are genuine. However, it is important to note

that interest assessment is only one aspect of career counseling and that manyother factors are likely important in assisting a client in making a career choice.In particular, it seems important in future work to look further at individual dif-ferences that may play a role in career counseling process and outcome. Finally,it should be noted that the sample was comprised mostly of White/Caucasianwomen, and this limits the generalizability of our findings.

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