the relation of self-efficacy and interests: a meta-analysis of 60 samples

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The relation of self-efficacy and interests: A meta-analysis of 60 samples q Patrick J. Rottinghaus, * Lisa M. Larson, and Fred H. Borgen Department of Psychology, Iowa State University, Ames, IA 50011-3180, USA Received 18 April 2002 Abstract This study empirically synthesizes and evaluates studies that have examined the relation between vocationally relevant domains of self-efficacy and interests. We conducted a meta-an- alytic review of 60 empirical independent samples (N ¼ 39,154) in which relations between self- efficacy and interests had been examined. Fifty-three of these samples (N ¼ 37,829) included parallel measures of the constructs. Relations between parallel measures of HollandÕs RIASEC themes, the specific dimensions of art, math, science and math/science combined, and tradi- tionally female and male occupations are also presented. Results demonstrated that self-effi- cacy and interests are independent constructs that correlate moderately. Differences by sex, measure, and age group are noted. Future directions for research regarding links between self-efficacy and interests are discussed. Ó 2003 Elsevier Science (USA). All rights reserved. Keywords: Vocational interests; Self-efficacy; Social cognitive career theory; Meta-analysis 1. Introduction This article examines the current status of relations between vocationally relevant domains of self-efficacy and interests, building on Lent, Brown, and HackettÕs (1994) meta-analysis of 13 studies that yielded an average weighted effect size of .53. Since Journal of Vocational Behavior 62 (2003) 221–236 www.elsevier.com/locate/jvb q A version of this article was presented at the 110th Annual Convention of the American Psychological Association, August 2002, Chicago, IL, USA. * Corresponding author. Fax: 1-515-294-6424. E-mail address: [email protected] (P.J. Rottinghaus). 0001-8791/03/$ - see front matter Ó 2003 Elsevier Science (USA). All rights reserved. doi:10.1016/S0001-8791(02)00039-8

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The relation of self-efficacy and interests: Ameta-analysis of 60 samplesq

Patrick J. Rottinghaus,* Lisa M. Larson, and Fred H. Borgen

Department of Psychology, Iowa State University, Ames, IA 50011-3180, USA

Received 18 April 2002

Abstract

This study empirically synthesizes and evaluates studies that have examined the relation

between vocationally relevant domains of self-efficacy and interests. We conducted a meta-an-

alytic review of 60 empirical independent samples (N¼ 39,154) in which relations between self-

efficacy and interests had been examined. Fifty-three of these samples (N¼ 37,829) included

parallel measures of the constructs. Relations between parallel measures of Holland�s RIASEC

themes, the specific dimensions of art, math, science and math/science combined, and tradi-

tionally female and male occupations are also presented. Results demonstrated that self-effi-

cacy and interests are independent constructs that correlate moderately. Differences by sex,

measure, and age group are noted. Future directions for research regarding links between

self-efficacy and interests are discussed.

� 2003 Elsevier Science (USA). All rights reserved.

Keywords: Vocational interests; Self-efficacy; Social cognitive career theory; Meta-analysis

1. Introduction

This article examines the current status of relations between vocationally relevant

domains of self-efficacy and interests, building on Lent, Brown, and Hackett�s (1994)meta-analysis of 13 studies that yielded an average weighted effect size of .53. Since

Journal of Vocational Behavior 62 (2003) 221–236

www.elsevier.com/locate/jvb

qA version of this article was presented at the 110th Annual Convention of the American

Psychological Association, August 2002, Chicago, IL, USA.*Corresponding author. Fax: 1-515-294-6424.

E-mail address: [email protected] (P.J. Rottinghaus).

0001-8791/03/$ - see front matter � 2003 Elsevier Science (USA). All rights reserved.

doi:10.1016/S0001-8791(02)00039-8

1994, numerous empirical and conceptual articles have examined the self-efficacy/in-

terest linkage across more diverse aspects of vocational behavior. The present inves-

tigation integrates this literature by first describing methodological issues and then

presenting a meta-analytic review of 53 parallel empirical samples that examined re-

lations between self-efficacy and interests.A critical question in social cognitive career theory involves the overlap of self-

efficacy and interest within a similar content area (e.g., science self-efficacy with

science interests): Does either construct help explain a particular criterion such as

occupational membership above and beyond the other? In addition to its theoretical

import, answering this question has implications for practice. On one hand, the joint

assessment of science self-efficacy and interests is recommended if these constructs

are sufficiently distinct and provide incremental explanation of variance in selecting

a college major, for example. On the other hand, the joint assessment is notwarranted if the constructs are redundant with one another and explain the same

variance in selecting a major.

The question of independence has drawn a considerable amount of attention.

Lapan and Jingeleski (1992) concluded that the constructs of self-efficacy, interests,

and outcome expectations were not sufficiently distinct to be labeled different con-

structs. Tracey (1997) supported this conclusion, based upon his analysis that

showed a similar structure for interests and self-efficacy. In contrast, others including

Swanson (1993), Isaacs, Borgen, Donnay, and Hansen (1997), Donnay and Borgen(1999), Tracey and Hopkins (2001), and Rottinghaus, Lindley, Green, and Borgen

(2002) have argued that although interests, skills confidence, and self-rated abilities

are related, they are sufficiently distinct to be considered separate constructs.

It is notable that most of the early studies examining these relationships involved

expressed interests in science or math and used diverse measures of self-efficacy. Al-

though a few studies have investigated the relation between self-efficacy and interests

in additional areas such as English, art, and social studies (cf. Smith & Fouad, 1999),

very little is known about non-Investigative career areas. Within the past decade,several instruments have been introduced to assess self-efficacy, or skills confidence,

across the six Holland themes (Betz, Borgen, & Harmon, 1996; Campbell, Hyne, &

Nilsen, 1992; Lucas, Wanberg, & Zytowski, 1997).

Research on domain-specific self-efficacy instruments in conjunction with their

corresponding interest measures has allowed for a more thorough examination of

the links between self-efficacy and interests. The burgeoning literature in this area

now enables the investigation of relationships between these constructs at multiple

levels including Holland themes or more specific content (i.e., Sales), across occupa-tional domains. Examining multiple levels of specificity, consistent with Bandura�s(1986) self-efficacy construct, will advance understanding of career outcomes.

2. Methodological issues

Before reporting the meta-analyses, a brief overview of several instruments

used across the studies included in our meta-analysis is presented. Only prominent

222 P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236

instruments used in multiple studies will be addressed in this section, not unique

measures used to address specific research hypotheses in a single study.

2.1. Self-efficacy/interest linkages of Holland’s six RIASEC dimensions

Two parallel measures of self-efficacy and interests are the Skills Confidence In-

ventory (SCI; Betz et al., 1996), in conjunction with the Strong Interest Inventory

(SII; Harmon, Hansen, Borgen, & Hammer, 1994), and the Campbell Interest and

Skills Survey (CISS; Campbell et al., 1992). Both measures have reported excellent

estimates of reliability and validity.

The SCI (Betz et al., 1996) is a 60-item instrument with six scales entitled General

Confidence Themes (GCT) and was used in 10 of the studies. The six GCTs corre-

spond to the six Holland types and measure participants� perceived level of confidencein each of these six areas. Scores on the GCTs range from 1.0 (‘‘No Confidence’’) to

5.0 (‘‘Complete Confidence’’) and are computed by summing the responses for the 10

items composing each scale and dividing by the number of completed items.

The CISS (Campbell et al., 1992) is a 320-item instrument and was used in three

studies. Respondents indicate their degree of interest in 200 academic and occupa-

tional topics on a six-point scale ranging from 1 (‘‘Strongly Like’’) to 6 (‘‘Strongly

Dislike’’). A parallel set of 120 items addressing specific occupational activities mea-

sures respondent�s self-reported degree of skill on a six-point scale ranging from 1(‘‘Expert: Widely recognized as expert in this area’’) to 6 (‘‘None: Have no skills in

this area’’). Standardized scores are provided for interests and skills confidence across

three levels of specificity. There are seven Orientation Scales: Influencing, Organizing,

Helping, Creating, Analyzing, Producing, and Adventuring; 29 Basic Scales (e.g., Art,

Law/Politics, Mathematics, Science); and 60 Occupational Scales (e.g., Engineer,

Guidance Counselor). The Orientation Scales resemble the six Holland themes,

except the CISS composes two Realistic scales (Producing and Adventuring).

2.2. Self-efficacy/interest linkages of basic dimensions

In addition to the CISS, several additional measures assess self-efficacy and inter-

ests for the basic dimensions of art, math, and science self-efficacy. Betz and Hack-

ett�s (1983) Mathematics Self-Efficacy Scale (MSES) is the most common measure

for math. Participants rate their confidence in receiving a grade of ‘‘B or better’’

on a scale of 0–9 for 15 math-related courses. The math scale of the MSES has high

internal consistency with an a coefficient of .93 (Betz & Hackett, 1983). Numerousresearchers slightly modified this scale to match local course offerings or to be con-

sistent with age groups. Likewise, parallel composites of math and science self-

efficacy and interests were also featured in four studies herein.

Finally, all studies examining self-efficacy and interests for traditionally female or

male domains used Betz and Hackett�s (1981) initial instrument as a prototype. Their

original measure included 20 well-known occupations spanning the six Holland

themes in which each was represented by over 70% females or males according to

the USWomen�s Bureau (1975). Two 10-item scales representing traditionally female

P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236 223

and male occupations were established for both self-efficacy level and strength (or

confidence), and degree of interest in the occupations. A 10-point scale was used

for confidence ratings, whereas a three-point ‘‘like,’’ ‘‘indifferent,’’ or ‘‘dislike’’ for-

mat was used for interests. Layton (1984) reported excellent internal consistency

for the MSES, with reliability estimates of .91 and .92 for traditionally female andmale occupations, respectively.

3. Method

3.1. Literature review

A literature search was conducted to identify published and unpublished studiesthat measured vocational interests and occupationally relevant self-efficacy. Several

strategies were used to search the relevant literature. First, a computer search was

done through PsychLIT databases using the keywords ‘‘interest(s)’’ and ‘‘self-effica-

cy.’’ Second, in an effort to discover potentially overlooked articles, a manual search

of the following journals was conducted: Journal of Vocational Behavior, Journal of

Career Assessment, Journal of Counseling Psychology, and Measurement and Evalu-

ation in Counseling and Development. Third, we investigated additional sources cited

in references from articles, dissertations, and books.Since this study addresses the relationships between parallel measures of interests

and self-efficacy for vocational interest areas, we did not include studies examining

research self-efficacy or career decision-making self-efficacy. We also did not include

studies examining non-parallel measures of self-efficacy and interest in the overall

analysis (e.g., math self-efficacy and Investigative interests). However, for purposes

of comparison we did include a separate analysis of the seven non-parallel samples

(N¼ 1,325) that examined the relationships between math self-efficacy and math/sci-

ence interests. Finally, we eliminated samples included in more than one publicationto ensure the independence assumption.

A total of 60 independent samples (N¼ 39,154) was retained for the present study.

Since seven samples included non-parallel results only, the remaining 53 parallel

samples (N¼ 37,829) comprise the core analyses. Of the 49 sources, 38 were pub-

lished and 11 were unpublished. Table 1 lists these samples identified for inclusion,

including information on measures, age groups, and content domains examined in

each study. Because self-efficacy is domain specific, different vocational domains

were examined across the studies. At the most general level, 18 of the studies exam-ined parallel RIASEC self-efficacy/interest linkages. Additional studies examined art

(k¼ 2), math (k¼ 7), science (k¼ 3), math/science (k¼ 4), traditionally female

(k¼ 7), or traditionally male (k¼ 8) self-efficacy/interest linkages.

3.2. Computation of effect sizes

Mean effect sizes for correlations were calculated with standard meta-analytic

methods (Hedges & Olkin, 1985; Wang & Bushman, 1999). First, we computed effect

224 P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236

sizes for the average weighted pairwise cross-correlations between parallel measures

of interests and self-efficacy across all parallel samples (N¼ 37,829 across 53 sam-

ples). Second, we conducted a more detailed analysis of parallel content domains or-

ganized by Holland�s RIASEC themes and specific content domains of art, math,

science, math/science combined, and traditionally female and male occupations.We also calculated these effect sizes separately for subgroups of the sample, such

as sex, measures used, and age group.

Obtaining the means for correlations required first transforming the correlations

to a Fisher�s Z, next calculating the mean for the Zs, and then transforming the mean

Z back to a mean r. In performing these calculations, means were weighted by the

sample size of each study. Thus, results for larger sample sizes were weighted more

than results for smaller samples. A 95% confidence interval was also calculated for

each study and for the final effect size.

4. Results

The meta-analyses will be presented from the global to the more specific domains

of vocational activity. An overall average weighted correlation across all domains is

presented first, primarily as a means of comparison with Lent et al.�s (1994) earlierfindings. Second, the average weighted correlations for each of the GOTs are pre-sented, followed by the average weighted correlations for the more narrow domains

of art, math, science, math/science combined, and traditionally female and male oc-

cupations. The final section examines the moderators of sex, measures used, and age

group to see if they alter overall findings.

4.1. Overall average weighted mean correlation across domains

Because many recent studies reported a full correlation matrix for self-efficacy andinterests among multiple content domains (e.g., RIASEC), we computed the average

effect size among parallel measures for inclusion in the overall average weighted

mean effect statistic. Based on the overall population of 37,829 participants across

53 samples, the average weighted mean effect size for the correlation between self-ef-

ficacy and interests is .59 with a 95% confidence interval ranging from .58 to .59. This

effect size is slightly stronger than Lent et al.�s (1994) results (.53).

4.2. Meta-analyses by Holland themes, basic domains, and traditionally female and

male occupations

Table 2 reports effect sizes and confidence intervals for parallel measures of Hol-

land�s RIASEC, and the more specific basic dimensions of art, math, science, math/

science, and traditionally female and male occupations. Among RIASEC dimen-

sions, Investigative yielded the strongest effect (r¼ .68), followed by Realistic

(r¼ .67), Artistic (r¼ .64), Social (r¼ .54), Conventional (r¼ .53), and Enterprising

(r¼ .50). For basic domains, math yielded the strongest effect (r¼ .73), followed

P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236 225

Table 1

Listing of the samples included in the meta-analyses by year, sample size, measure used, age group, and vocational domain

Reference n Self-

efficacy

measure

Interest

measure

Age

group

RIASEC Art Math Science Math/

Science

Trad.

female

Trad.

male

Mean

only

Non-

parallel

Betz and Hackett (1981) 235 Unique Unique College � �Campbell and Hackett (1986) 120 �84 HB �84 HB College �Hackett and Campbell (1987) 92 �84 HB �84 HB College �Rotberg, Brown, and Ware (1987) 152 Unique Unique College � �Barak, Librowsky, and Shiloh

(1989)—Study #1a96 Unique Unique College �

Barak et al. (1989)—Study #2a 223 Unique Unique W. Adult �Lapan, Boggs, and Morrill (1989) 144 Unique �81 SCII College �Lent, Larkin, and Brown (1989) 70 Unique �81 SCII College �Bores-Rangel, Church, Szendre,

and Reeves (1990)

35 Unique USESII W. Adult �

Hackett, Betz, O�Halloran,

and Romac (1990)

149 MSES Unique College �

Bieschke (1991) 289 MSES Unique Adolescent �Lauver and Jones (1991)b 893 Unique Unique Adolescent � �Lent, Lopez, and Bieschke (1991) 138 MSES MSIN College �Campbell et al. (1992) 88 CISS CISS Adolescent �Campbell et al. (1992) 157 CISS CISS College �Campbell et al. (1992) 5391 CISS CISS W. Adult � � � �Church, Teresa, Rosebrook,

and Szendre (1992)

85 Unique USESII W. Adult �

Hackett, Betz, Casas,

and Rocha-Singh (1992)

197 Unique Unique College �

Lopez and Lent (1992) 50 Unique Unique Adolescent �Lent, Lopez, and Bieschke (1993) 166 MSES MSIN College �Swanson (1993) 112 Unique �85 SII College �Lenox and Subich (1994)c 180 Unique �85 SII College �Betz et al. (1996)—Study #1 110 SCI �94 SII College �Betz et al. (1996)—Study #2a 248 SCI �85 SII College �Fouad and Smith (1996) 380 MSES Unique Adolescent �

226

P.J.Rottinghausetal./JournalofVocationalBehavior62(2003)221–236

Lapan, Shaughnessy,

and Boggs (1996)

101 MSES �85 SII College �

Isaacs et al. (1997) 912 SCI �94 SII College �Lopez, Lent, Brown,

and Gore (1997)—Study #1

145 Unique Unique Adolescent �

Lopez et al. (1997)—Study #2 151 Unique Unique Adolescent �Vondracek and Skorikov (1997) 642 Unique Unique Adolescent �Gainor and Lent (1998)b 164 MSES Unique College �Smith-Weber (1998)b ;d 157 Unique Unique Adolescent � �Witherspoon (1998)b 129 Unique Unique College �Cronen (1999)d 134 Unique Unique College �Donnay and Borgen (1999) 1105 SCI �94 SII W. Adult �Luzzo, Hasper, Albert, Bibby,

and Martinelli (1999)

94 MSES Unique College �

O�Brien, Martinez-Pons,

and Kopala (1999)

415 MSES �77 JVIS Adolescent �

Panagos and DuBois (1999) 96 COPS COPS Adolescent �Smith and Fouad (1999) 952 Unique Unique College � �Strychasz (1999) 101 MSES Unique Adolescent �Tang, Fouad, and Smith (1999)b 187 SCI �94 SII College �Blaisdell (2000) 211 Unique Unique College �Brown, Lent, and Gore (2000) 229 Unique �85 SII College �Ferry, Fouad, and Smith (2000) 791 MSES Unique College �Richardson (2000)b 103 SCI Unique College � �Rottinghaus, Day,

and Borgen (2000)

141 SCI �94 SII College �

Chartrand, Borgen, Betz, and

Donnay (2002)—Study #1

13069 SCI �94 SII College �

Chartrand et al. (2002)—Study #2 7371 SCI �94 SII W. Adult �Diegelman and Subich (2002) 85 Unique Unique College �Lent et al. (2001) 111 MSES Unique College �

P.J.Rottinghausetal./JournalofVocationalBehavior62(2003)221–236

227

Table 1 (continued)

Reference n Self-

efficacy

measure

Interest

measure

Age

group

RIASEC Art Math Science Math/

Science

Trad.

female

Trad.

male

Mean

only

Non-

parallel

Lindley (2001) 311 SCI �94 SII College �Flores and O�Brien (2002) b ;d 364 Unique Unique Adolescent �Nauta, Kahn, Angell,

and Cantarelli (2002)

104 SCI �94 SII College �

Rottinghaus and Borgen (2002) 508 SCI �94 SII College �Rottinghaus et al. (2002) 471 SCI �94 SII College �

Note. Non-parallel¼ studies examining Math self-efficacy and Math/Science interests; COPS¼California Occupational Preference System (Knapp &

Knapp, 1982); HB¼Hackett and Betz (1984) measure; MSES¼Math Self-Efficacy Scale (Betz & Hackett, 1983); SCII¼Strong-Campbell Interest Inventory;

USESII¼United States Employment Service Interest Inventory; SII¼Strong Interest Inventory; JVIS¼ Jackson Vocational Interest Survey.aReported correlations for women and men separately and not for the total sample.bRacial and ethnic minority samples. Lauver and Jones (1991) reported correlations for White, Hispanic, and American Indian samples separately.c Lenox and Subich (1994) reported correlations for Realistic, Investigative, and Enterprising only.d Study included correlations for females only.

228

P.J.Rottinghausetal./JournalofVocationalBehavior62(2003)221–236

by science (r¼ .69), and art (r¼ .62). The broader math/science (r¼ . 51), tradition-

ally female (r¼ .40), and male (r¼ .47) occupational domains yielded weaker effects.

An analysis of seven non-parallel relationships between math self-efficacy and math/

science interests also yielded a relatively weaker correlation of .43.

4.3. Meta-analyses by the moderators

Sex. Table 3 presents the average weighted mean RIASEC self-efficacy and inter-est correlations, as measured by the SCI and SII. To control for the number of com-

parisons, a Bonferroni adjustment was made (.05/12), resulting in a critical p-value of

.005 to detect significant differences between the self-efficacy/interest correlations for

women and men. As shown in Table 3, men showed significantly stronger associa-

tions than women for the following dimensions: Realistic, Social, and Conventional.

However, the magnitudes of the differences were small, ranging from 3 to 7% of the

variance. For example, the Social self-efficacy and Social interest overlapped 28% for

men but only 21% for women.Measure. Table 4 presents the mean average weighted RIASEC self-efficacy and

interest correlations and their corresponding confidence intervals by measure. All

six correlations were significantly stronger when measured by the CISS compared

to the SII/SCI. As seen by Table 4, the larger differences are for Social, Enterprising,

and Conventional domains. The largest difference was with the Enterprising domain,

with an overlap of 18% when measured by the SII/SCI but 58% when measured by

Table 2

Mean effect size estimates and confidence intervals for the correlations between parallel measures of self-

efficacy and interests

Domains ka r 95% CI

Realisticb 18 .67 .67 to .68

Investigative 18 .68 .68 to .69

Artistic 17 .64 .64 to .65

Social 17 .54 .54 to .55

Enterprising 18 .50 .49 to .51

Conventional 17 .53 .52 to .53

Art 2 .62 .60 to .63

Math 7 .73 .72 to .74

Science 3 .69 .68 to .71

Math/Science 4 .51 .47 to .54

Trad. Female Occ. 7 .40 .36 to .44

Trad. Male Occ. 8 .47 .45 to .51

Note. N¼ 30,590 for Realistic, Investigative, and Enterprising; N¼ 30,410 for Artistic, Social, and

Conventional; N¼ 6,343 for Art; N¼ 6,166 for Math; N¼ 5,672 for Science; N ¼ 2,217 for Math/Science;

N¼ 1,540 for Traditionally Female; and N¼ 1,904 for Traditionally Male. k¼Number of samples.

r¼ average weighted mean correlation; CI¼ confidence interval.aAlthough the number of samples is reported for each domain, the actual number of participants

across all samples within each domain is used in the meta-analysis formula.b The authors included the Producing instead of the Adventuring Orientation Scale for the three studies

using the CISS because it better reflects Holland�s Realistic type.

P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236 229

the CISS. Likewise, though not as large, the Conventional self-efficacy and interest

overlap was 23% when measured by the SII/SCI, but 45% for the CISS. Finally, the

Social self-efficacy and interest overlap was 26% when measured by the SII/SCI and

44% when measured by the CISS. Clearly, the self-efficacy and interest correspon-

dence across the RIASEC domains varies meaningfully depending on the measures

used. Also, the stronger effects for Realistic, Investigative, and Artistic domains com-

pared to Social, Enterprising, and Conventional domains were present only for the

SII/SCI and not the CISS.Age group. Analyses were also conducted based on the sample type, either adoles-

cent (k¼ 11; N¼ 2,932), college students (k¼ 35; N¼ 20,687), or working adults

(k¼ 7; N¼ 14,210). Because there were too few studies available to conduct more

specific analyses, only overall effect sizes are available for each of the three sample

types. The effect size was smallest for adolescents (r¼ .50), followed by college stu-

dents (r¼ .57), and working adults (r¼ .62).

Table 3

Mean effect size estimates and confidence intervals for the correlations between parallel measures of self-

efficacy and interests in the SII/SCI by sex

Measure Women Men

r 95% CI r 95% CI

Realistica .58 .57 to .59 .64 .63 to .65

Investigative .65 .64 to .66 .65 .64 to .66

Artistic .62 .61 to .63 .63 .62 to .64

Sociala .46 .44 to .47 .53 .52 to .54

Enterprising .41 .39 to .42 .43 .41 to .44

Conventionala .50 .49 to .51 .47 .45 to .48

Note. N¼ 17,585 for women and N¼ 11,597 for men across eight samples. r¼ average weighted mean

correlation; CI¼ confidence interval.a There were sex differences in the magnitude of r at the p < :005 level for these domains.

Table 4

Mean effect size estimates and confidence intervals for the correlations between parallel measures of self-

efficacy and interests by Strong Interest Inventory/Skills Confidence Inventory (SII/SCI) and Campbell In-

terest and Skill Survey (CISS)

Measure SII/SCI CISS

r 95% CI r 95% CI

Realistic .66 .65 to .67 .73 .72 to .74

Investigative .67 .66 to .67 .75 .74 to .76

Artistic .63 .62 to .64 .68 .67 to .69

Social .51 .50 to .52 .66 .65 to .67

Enterprising .42 .41 to .43 .76 .74 to .77

Conventional .48 .47 to .49 .67 .66 to .69

Note. N¼ 24,289 for SII/SCI across 11 samples; N¼ 5,636 for CISS across three samples. r¼ average

weighted mean correlation; CI¼ confidence interval. All comparisons were significant at the p < :005 level.

230 P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236

5. Discussion

This study corroborates and adds specificity to our understanding of the overlap

between the domains of vocational self-efficacy and interests. It replicates what Lent

et al. (1994) reported nine years ago, namely that there appears to be a moderate re-lationship between self-efficacy and interests. Overall, self-efficacy and vocational in-

terests share approximately one-third of their variance. However, this study goes

beyond those findings to examine the specifics. First, it appears that the self-

efficacy/interest linkage is consistently strong across the RIASEC domains, ranging

from 25 to 46% of variance shared, as shown in Table 2. The overlap is clearly

substantial though small enough to illustrate the distinctiveness of these constructs.

After correcting for attenuation, the strongest effect size was for the CISS Artistic

scales, which results in 26% unshared variance. Second, it appears that the self-efficacy/interest overlap is somewhat less when a composite of female and male dom-

inated occupations are examined compared to when more basic domains are studied,

namely art, math, or science. The shared variance in the former is 16–22%, compared

to 38–53% for the latter. This may mean that the linkage is stronger when the

domain is more narrowly defined. However, this does not explain why the overlap

for the broad domain of Investigative is similar in strength (43%) to the more narrow

domains of math (53%) or science (49%). Likewise, the self-efficacy/interest link for

the broad Artistic Holland theme is virtually identical to the narrow art domain(41% vs 38%). Clearly, more research is needed to clarify if specificity of the domain

results in a stronger relationship.

We also examined the role of possible moderators including sex, measure used,

and age group. Although some differences were found by sex across the RIASEC do-

mains, the differences were not substantial, ranging from 0 to 7%. However, future

researchers may want to examine sex differences in specific instances where theory

suggests the possibility of gender-role socialization. For example, contextual barriers

could be posited to attenuate the relationship for women, but not for men.The one moderator that clearly matters is instrumentation. The development of

the SCI and the CISS have generated large data sets that have been used to validate

two new measures of confidence for the RIASEC domains. Based on this work, it

seems that the overlap varies considerably for the Social, Enterprising, and Conven-

tional domains depending on the measure used. Specifically, the SII/SCI linkage is

stronger for Realistic, Investigative, and Artistic domains than for the Social, Enter-

prising, and Conventional. However, for the CISS, the overlap between self-efficacy

and interest is more consistent across the hexagon. It is especially notable that theself-efficacy/interest relationships between the RIASEC domains are significantly

stronger when measured by the CISS compared to the SII/SCI. Differences in item

content, rating scales, and instructions between the CISS and SII/SCI may explain

these differences. Although the CISS is a measure of skills confidence, its response

scale and scoring procedures reflect external normative judgments. In contrast, the

SCI emphasizes internal perceptions.

The magnitude of the correspondence between self-efficacy and interests varied

across Holland�s hexagon for the SII/SCI, ranging from .42 for Enterprising to .67

P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236 231

for Investigative. Future research should explore why the relationships are stronger

for RIA compared to SEC. Likewise, consistent with Lent and Hackett�s (1987) hy-pothesis, the more specific content of math yielded a stronger effect (r¼ .73) com-

pared to the more diverse content of math/science (r¼ .51). Since self-efficacy

expectations are intended to be domain specific, results pertaining to parallel mea-sures of Holland�s RIASEC and basic interest dimensions are especially noteworthy.

Additionally, age group may moderate the self-efficacy/interest linkage. Collaps-

ing across the domains, the relationship was strongest for working adults (r¼ .62)

followed by college students (r¼ .57) and adolescents (r¼ .50). These results should

be interpreted with caution for at least two reasons. First, most of the adolescent

samples examined traditionally female and/or male domains whose correlations were

weaker, whereas most of the working adult samples measured RIASEC or basic do-

mains whose correlations were stronger. Thus, age group differences were con-founded by domains (and measures) under investigation. Second, one study

(Campbell et al., 1992) reported correlations for all three age groups and showed

minimal differences across the age groups. Future research will need to separate do-

main from age group.

A point should also be made regarding ethnicity. The studies to date do not typ-

ically report correlations separately by ethnicity, with a notable exception (Lauver &

Jones, 1991), although six additional samples did exclusively sample racial and

ethnic minorities. More racial and ethnic samples are needed and more studies needto report correlations by ethnicity whenever possible.

In addition to more studies using diverse participants, we need more studies that

emphasize the nature of the linkages between self-efficacy and interests. Although

different studies might yield similar effect sizes, understanding the causal direction

and potentially interactive process among these constructs enhances their utility.

For example, the proportion of participants with low confidence/high interest versus

high confidence/low interest could vary greatly across studies without affecting the

strength of the correlation. The examination of more dynamic processes (e.g., thresh-old effect and causality) would require an experimental approach.

The process of this transfer from belief about one�s abilities to an active interest has

received some speculation. Bandura and Schunk (1981) hypothesized that a temporal

lag exists between recently acquired self-efficacy and engagement of interest in neutral

or disliked activities. After a time delay, self-efficacy promotes interest via satisfaction

derived from mastery experiences. Bandura (1986) also hypothesized a threshold

effect regarding the relationship between self-efficacy and interest: ‘‘At least moderate

self-efficacy may be required to generate and sustain interest in an activity but addi-tional increases in self-efficacy above the threshold level do not produce further gains

in interest’’ (p. 242). This proposition of the non-linear relationship between self-

efficacy and interests apparently has been ignored by all studies but one (Lenox &

Subich, 1994). Lenox and Subich (1994) found that mean interest scores remained

stable at lower levels of self-efficacy, and then increased linearly at higher levels. These

results ran counter to Bandura�s (1986) hypothesis that interests would lessen at

higher levels of self-efficacy. It is notable that a base level of self-efficacy was required

for interests to increase, supporting Bandura�s threshold effect hypothesis.

232 P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236

Almost all of the research to date has used correlational analyses to explain the

influence of self-efficacy on interest development. The lack of experimental or longi-

tudinal designs has limited the process of supporting or revising social cognitive ca-

reer theory. However, recent studies (Nauta et al., 2002; Tracey, 2002) are beginning

to address the possibility that self-efficacy and interests have reciprocal effects uponeach other. In summary, this meta-analysis demonstrates that the magnitude of the

overall relationship between self-efficacy and interests is moderate. However, instru-

mentation appears to moderate this correspondence. Finally, because of the incon-

clusive nature of the results reported herein, additional studies are required to

examine the possibility that factors such as specificity of the domain measured

and age group also moderate these relationships.

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Further reading

*Betz, N. E., Harmon, L. W., & Borgen, F. H. (1996). The relationship of self-efficacy for the Holland

themes to gender, occupational group membership, and vocational interests. Journal of Counseling

Psychology, 43, 90–98.

236 P.J. Rottinghaus et al. / Journal of Vocational Behavior 62 (2003) 221–236