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Indecisiveness and High School Students’ Career Decision-Making
Process: Longitudinal Associations and the Mediational Role of Anxiety
Veerle Germeijs, Karine Verschueren, and Bart Soenens
Katholieke Universiteit Leuven
This study examined how indecisiveness relates to adolescents’ process of choosing a study in higher
education, using a longitudinal design. A sample of 281 students participated at the beginning, middle,
and end of Grade 12. Findings show that indecisiveness was a risk factor for future levels of coping with
the career decisional tasks of broad and in-depth environmental exploration (amount of information and
exploratory behavior), amount of self-information, decisional status, and commitment. However, inde-
cisiveness did not relate to the degree of change in decisional tasks during Grade 12. Moreover, results
suggest that the linkage of indecisiveness with the amount of in-depth environmental information, the
amount of self-information, decisional status, and commitment was mediated by adolescents’ career
choice anxiety. Finally, stability data provided support for the conceptualization of indecisiveness as a
trait.
Keywords: decision-making process, decisional tasks, longitudinal, indecisiveness, career choice anxiety
In the past few decades, a great deal of research attention has
been paid to the definition of several types of career decision-
making problems (e.g., Campbell & Cellini, 1981; Gati, Krausz, &
Osipow, 1996; Jones & Chenery, 1980; Larson, Heppner, Ham, &
Dugan, 1988). One topic discussed in most typologies of career
decision-making problems is indecisiveness (Santos, 2001). Inde-
cisiveness has been defined as a chronic problem with making
decisions across different situations (Crites, 1969; Osipow, 1999).
In career psychology, authors have referred to indecisiveness as a
trait, contrasting it with career indecision, which refers to a normal
transitory phase in the process of making one particular decision
(Cooper, Fuqua, & Hartman, 1984; Osipow, 1999).
Indecisiveness is conceptualized as a problem already existing
before the start of a career decision-making process (Gati et al.,
1996) and having important negative consequences for this process
(e.g., Gaffner & Hazler, 2002; Gati & Asher, 2001; Gati et al.,
1996). However, the characterization of how indecisive people
make career decisions has resulted largely from the analysis of
clinical cases (Santos, 2001). On the basis of observations of
clients, indecisive people have been characterized as being unable
to make decisions even after a long series of counseling sessions.
Indecisive clients have been described as suffering from a range of
personal problems like high anxiety, low self-confidence, and
dependency on other persons for a clear sense of self (Heppner &
Hendricks, 1995; Salomone, 1982), features which are expected to
have negative consequences for making a decision. Some
questionnaire-based empirical studies found evidence for a rela-
tionship between indecisiveness and career decision-making prob-
lems, with indecisiveness being negatively related to career cer-
tainty (e.g., Cooper et al., 1984; Gayton, Clavin, Clavin, & Broida,
1994) and positively related to the need for information about the
alternatives (e.g., Germeijs & De Boeck, 2003). However, these
studies were cross-sectional, thereby preventing testing of indeci-
siveness as a risk factor for future career decision-making prob-
lems. Moreover, previous studies only focused on some aspects or
tasks in the career decision-making process. Therefore, the precise
impact of indecisiveness on the career decision-making process
still remains unclear. In addition to the lack of longitudinal studies
and the failure to relate indecisiveness to a comprehensive frame-
work of career decision-making tasks, no research attention has
been paid to possible mediators of the hypothesized link between
indecisiveness and career decision-making problems.
The aims of the present study were (a) to relate indecisiveness
to a comprehensive framework of career decisional tasks (which
allows determining with greater precision on which tasks indeci-
siveness has a negative effect), (b) to examine whether indecisive-
ness has an effect on adolescents’ developmental progress in
decisional tasks during the career decision-making process, and (c)
to look at career choice anxiety as a possible mediator of the
relationship between indecisiveness and adolescents’ career
decision-making process.
There are important practical reasons for examining indecisive-
ness in relation to the crucial tasks of the career decision-making
process. First, if indecisiveness is identified as a risk factor for
career decision-making difficulties, prevention workers and career
counselors may be stimulated to detect this risk factor early, in
order to decrease the likelihood of problems with making career
decisions in the future. Second, identifying the unique career
decision-making difficulties that prevent indecisive individuals
Veerle Germeijs, Karine Verschueren, and Bart Soenens, Department of
Psychology, Katholieke Universiteit Leuven, Leuven, Belgium.
The contribution of Bart Soenens was sponsored by the Fund for
Scientific Research Flanders (FWO-Vlaanderen).
Correspondence concerning this article should be addressed to
Veerle Germeijs, Department of Psychology, Katholieke Universiteit
Leuven, Tiensestraat 102, B-3000, Leuven, Belgium. E-mail:
veerle.germeijs@psy.kuleuven.be
Journal of Counseling Psychology Copyright 2006 by the American Psychological Association
2006, Vol. 53, No. 4, 397–410 0022-0167/06/$12.00 DOI: 10.1037/0022-0167.53.4.397
397
from making a decision may guide career counselors in providing
these clients with the specialized help they need. Although it is
hypothesized (Osipow, 1999; Serling & Betz, 1990; Slaney, 1988)
that indecisive people need intensive counseling interventions
dealing with personality problems like obsessional–compulsive
phenomena, maladaptive perfectionism, trait anxiety, and low self-
esteem (e.g., Frost & Shows, 1993; Rassin & Muris, 2005; Santos,
2001), paying attention to their problems with specific career
decisional tasks too may provide an accessible starting point for a
counseling process.
In the current study, the decision-making process concerning
one specific career decision, that is, adolescents’ choice of a study
in higher education (i.e., a major), was focused on. In Belgium,
different educational forms in high school are distinguished (i.e.,
education in the arts, general, technical and vocational education).
After successfully completing high school and receiving a certif-
icate, pupils from all educational forms have unrestricted access to
higher education. Hence, despite the early tracking into type of
education in high school, the choice of study in higher education
remains open until the end of high school. Most of the students
with a high school diploma start higher education (i.e., 77.3%;
Sonar, 2002). The current study focused on the career decision-
making process of those students who follow general education in
high school. This group has the largest percentage of students
starting higher education (i.e., 97.3%; Sonar, 2002). In Belgium,
all students have to declare their major at the time of enrollment in
higher education. Choosing a study in higher education is thus an
important career decision for almost all of these high school
students.
In this study, adolescents’ career decision-making process was
studied by examining their coping with the following six career
decisional tasks at different measurement times during the final
year in high school: (a) orientation to choice (i.e., awareness of the
need to make a decision and motivation to engage in the career
decision-making process), (b) self-exploration (i.e., gathering in-
formation about oneself), (c) broad exploration of the environment
(i.e., gathering general information about career alternatives), (d)
in-depth exploration of the environment (i.e., gathering detailed
information about a reduced set of career alternatives), (e) deci-
sional status (i.e., progress in choosing an alternative), and (f)
commitment (i.e., strength of confidence in and attachment to a
particular career alternative).
These six career decisional tasks have been distinguished by
Germeijs and Verschueren (in press, 2006) as core aspects of the
career decision-making process, based on taxonomies of career
decision-making problems (Campbell & Cellini, 1981; Gati et al.,
1996) and theories about the career decision-making process (e.g.,
Gati & Asher, 2001; Harren, 1979; Tiedeman & O’Hara, 1963). In
the current study and in line with the model of career exploration
of Stumpf, Colarelli, and Hartman (1983), for each of the three
exploration tasks, two dimensions were distinguished, namely the
frequency of exploratory behavior and the amount of information
acquired as reported by the students. In sum, in the current study,
the relationship of indecisiveness with six career decisional tasks
(conceptualized by nine aspects) was investigated because these
tasks are considered critical for a comprehensive description and
analysis of the career decision-making process.
Effect of Indecisiveness on Career Decision Making
The first purpose of the present study was to investigate the
differential effect of indecisiveness on the career decisional tasks.
The longitudinal design of the study allows investigating the effect
of indecisiveness on later levels of coping with the career deci-
sional tasks, ensuring temporal precedence of the risk factor (i.e.,
indecisiveness) to the outcomes (i.e., decisional tasks; Kazdin,
1999).
We hypothesized that indecisiveness would have a negative
effect on decisional status, commitment, and the perceived amount
of information about oneself and about career alternatives (broad
and in depth) but not necessarily on orientation and exploratory
behavior regarding oneself and the career alternatives (broad and
in depth; see Crites, 1969). The hypothesized negative association
of indecisiveness with decisional status is in line with definitions
of indecisiveness as the general inability to make decisions (e.g.,
Chartrand, Robbins, Morril, & Boggs, 1990; Crites, 1969; Dosnon,
Wach, Blanchard, & Lallemand, 1997; Osipow, 1999; Wanberg &
Muchinsky, 1992), which is expected to hinder one’s decision-
making competencies in specific situations. With regard to com-
mitment, it was expected that if indecisive people do make a career
decision, they will be less confident and more ambivalent about
their decision (Van Matre & Cooper, 1984) and thus less commit-
ted to their career choice. Finally, we expected that indecisiveness
would have negative consequences for the perceived amount of
information about career alternatives and the self, based on find-
ings from previous studies in which indecisiveness was positively
related to a need for career information and for self-knowledge
(e.g., Dickinson & Tokar, 2004; Germeijs & De Boeck, 2003). We
did not necessarily anticipate negative relations between indeci-
siveness, on the one hand, and orientation and exploratory behav-
ior (regarding the self and the environment), on the other hand,
because indecisive people may be motivated to engage in the
career decision-making process and may execute some exploratory
behavior, but they are unable to use these opportunities to solve the
choice problem (Crites, 1969).
In addition to studying the differential effect of indecisiveness
on adolescents’ future level of career decisional tasks, the current
study examined the effect of indecisiveness on the (rate of) devel-
opmental changes in career decisional tasks during adolescents’
decision-making process (i.e., the second research aim). The career
decision-making process is considered a developmental process
(Hall, 1992; Tinsley, 1992), and therefore changes over time with
regard to career decision making have to be investigated in order
to understand this developmental process more thoroughly (Wil-
lett, Singer, & Martin, 1998). Furthermore, Vondracek, Lerner,
and Schulenberg (1986) stressed that the study of individual dif-
ferences in intraindividual change is an important research topic in
the career domain. Accordingly, the current study examined
whether differences in indecisiveness explain interindividual dif-
ferences in intraindividual change with regard to career decisional
tasks. For example, indecisiveness may be related to less growth in
decisional status over time. Because our study is the first to
examine the effect of indecisiveness on change in career decisional
tasks, the analyses were largely explorative.
398 GERMEIJS, VERSCHUEREN, AND SOENENS
Mediational Role of Anxiety
The final purpose of the present study was to investigate a
possible mechanism through which the effect of indecisiveness on
the career decision-making process occurs. More specifically, the
role of career choice anxiety as an intervening variable was tested.
This is in line with Crites (1969) and Goodstein (1972), who
hypothesized that indecisive individuals suffer from anxiety with
regard to making a decision, which is in turn an important ante-
cedent of career decision-making problems.
Career choice anxiety has been defined as affective distress
associated with career decision making and has been conceptual-
ized as an important personal–emotional factor that may inhibit
the career decision-making process (Chartrand et al., 1990). Find-
ings from prior cross-sectional research support the hypothesized
positive relationship between indecisiveness and career choice
anxiety (Chartrand et al., 1990; Dickinson & Tokar, 2004). In
addition, empirical studies found that career choice anxiety was
negatively associated with career choice certainty and vocational
identity (Vidal-Brown & Thompson, 2001) and positively associ-
ated with the need for career information and self-knowledge
(Chartrand et al., 1990; Dickinson & Tokar, 2004), suggesting that
career choice anxiety may be related to problems with career
decisional tasks. However, the full mediational model (i.e., includ-
ing indecisiveness, career choice anxiety, and career decisional
tasks) has not been investigated yet and was tested in the current
study.
Method
Procedure and Participants
For this study, 748 adolescents were recruited from 25 high schools
1
in
Flanders, the Dutch-speaking part of Belgium. Nearly all students were
White. All students were in their 6th year in high school (last year or Grade
12) and followed the general education track. A three-wave short-term
longitudinal design was used, with students receiving the same two ques-
tionnaires at the beginning (September), middle (January), and end (May)
of the school year. The choice of the particular design used in the current
study was based on a combination of empirical, methodological, and
practical reasons. On the basis of prior cross-sectional findings (Germeijs
& Verschueren, in press), the final year in high school (i.e., Grade 12) was
defined as adequate for investigating the decision-making process of
choosing a study in higher education. The number of waves was deter-
mined by methodological reasons (i.e., no latent curve models can be
estimated with less than three waves) but also by practical reasons (i.e.,
more than three waves was not feasible). Finally, a design with equally
spaced intervals among measurement points was used, which makes anal-
yses less complicated.
The first questionnaire that the students received was aimed at assessing
students’ coping with career decisional tasks, and it was administered
during regular classes. The second questionnaire probed personality and
environmental characteristics of the students, including indecisiveness and
career choice anxiety. Participants were asked to fill out this questionnaire
at home. To control for order effects, we constructed two versions of each
questionnaire, with the scales in a reverse order. Each time, the participants
received at random one of both versions.
With regard to the questionnaire on career decisional tasks, we do not
have data for 213 students on all waves because of the timetable of lessons
and the absence of some students at one or two waves. The dropout rate for
the questionnaire on personality and environmental characteristics filled
out at home was much higher, with 458 students not returning the ques-
tionnaire on all waves. This resulted in a three-wave longitudinal sample of
281 students (108 boys and 173 girls), who answered both questionnaires
at all measurement times. Mean age for the longitudinal sample was 17
years 3 months (SD ⫽5.07 months) at the first wave.
Comparison of the longitudinal sample with those students who did not
complete all questionnaires at all measurement times revealed no differ-
ences in students’ mean age or mean scores on the scales probing career
decisional tasks. However, for career choice anxiety and indecisiveness,
some differences between the longitudinal sample and the dropout group
were found. With regard to career choice anxiety, students in the dropout
group scored significantly higher than students in the longitudinal sample
at the beginning of the school year, t(543) ⫽2.30, p⬍.05, Cohen’s d⫽
.20. With regard to the indecisiveness scale, differences in the same
direction were found between both groups at the beginning, t(541) ⫽2.26,
p⬍.05, d⫽.19, and at the end, t(411) ⫽2.33, p⬍.05, d⫽.24, of the
school year. In all three cases, effect sizes were small. Finally, there was a
significant difference in gender for dropping out of the study,
2
(1, N⫽
747) ⫽8.44, p⬍.01, indicating that more boys than girls dropped out. In
sum, some caution is warranted in generalizing the results of the longitu-
dinal sample to the original sample.
Measures
All except one measure used in this study were originally created in
Dutch. Only one scale, the Career Choice Anxiety scale of the Career
Factors Inventory (CFI; Chartrand et al., 1990), was translated into Dutch
by Veerle Germeijs. Another person translated the items back into English,
and a third person matched the original items and the items translated back
into English. All items were correctly matched.
Indecisiveness. To measure indecisiveness, we used the 22-item Inde-
cisiveness Scale of Germeijs and De Boeck (2002). The construction of the
Indecisiveness Scale was based on descriptors for difficulties in making
decisions in general (e.g., deciding takes a long time, finding it difficult to
make a decision, not knowing how to make a decision), which were
derived from existing scales of indecisiveness and the literature describing
indecisiveness. All items of this scale (e.g., “It is hard for me to come to
a decision”) were answered on a 7-point scale ranging from 0 (strongly
disagree)to6(strongly agree). Germeijs and De Boeck (2002) provided
support for the reliability and validity of the Indecisiveness Scale, showing
its differentiation with measures of career indecision and its relationship
with measures of decision-making problems in several situations. In the
current study, Cronbach’s alphas for the Indecisiveness Scale were .92, .93,
and .93 at the first, second, and third measurement times, respectively.
Career choice anxiety. In order to measure the degree of anxiety
related to the process of making a study choice, we used the Career Choice
Anxiety scale of the CFI (Chartrand et al., 1990). The six items were
adapted to the situation of choosing a study in higher education (e.g.,
“When I think about actually deciding for sure what I want to study, I feel
(1) frightened, (5) fearless”). Although the precise multidimensional struc-
ture of the CFI still needs further investigation (Dickinson & Tokar, 2004),
several studies (Chartrand et al., 1990; Dickinson & Tokar, 2004; Lewis &
Savickas, 1995) reported evidence for the original hypothesized four-factor
1
Unconditional multilevel models for change (Singer & Willett, 2003)
were fit (with measurement occasions at Level 1, students at Level 2, and
schools at Level 3) in order to explore the amount of variance in the
decisional tasks at the school level. These analyses indicate that the
percentage of the variance at the school level was very small at each
occasion (M⫽3.6%), suggesting that schools only had a minor impact on
students’ coping with the career decisional tasks. As a consequence, in the
analyses, the school level was not taken into account (Lee, 2000).
399
INDECISIVENESS AND CAREER DECISION-MAKING PROCESS
structure of the CFI. With regard to the Career Choice Anxiety scale,
evidence was offered for a 2-week test–retest reliability (.79; Chartrand et
al., 1990), for the discriminant validity of the scale (Chartrand et al., 1990),
and for the convergent validity by finding relationships with other mea-
sures of career decision-making anxiety and career commitment anxiety
(Vidal-Brown & Thompson, 2001). In the current study, the internal
consistency of this scale was .89, .89, and .91 for the first, second, and third
waves, respectively, which is comparable with the Cronbach’s alpha of .86
found by Chartrand et al. (1990) in a U.S. sample.
Orientation, exploratory behavior, decisional status, commitment. The
Study Choice Task Inventory (SCTI; Germeijs & Verschueren, in press)
was used to measure coping behaviors and attitudes that address the six
career decisional tasks described above, using six separate subscales. With
regard to the three exploration tasks, the SCTI only measures exploratory
behavior as reported by the students. The development of the SCTI was
based on taxonomies of career decision-making problems (Campbell &
Cellini, 1981; Gati et al., 1996) and on theories of the career decision-
making process (e.g., Harren, 1979; Tiedeman & O’Hara, 1963). Germeijs
and Verschueren (in press) found evidence for the hypothesized multidi-
mensional structure of the SCTI from confirmatory factor analyses. They
also offered evidence for the convergent validity of the SCTI by finding the
predicted connections with existing measures of career exploration (Career
Exploration Survey; Stumpf et al., 1983) and career decision-making
difficulties (Career Decision-Making Difficulties Questionnaire; Gati et al.,
1996). Finally, construct validity evidence was also provided by two
known-groups validation analyses, in which the expected grade differences
and differences between vocational identity statuses were found. Below,
each of the six subscales will be described.
The Orientation to Choice scale of the SCTI, a 12-item measure, is
aimed at assessing students’ awareness of the need to make a decision and
motivation to engage in the career decision process (e.g., “I am motivated
to make work of choosing a study”). All items are answered on a 9-point
scale ranging from 1 (does not describe me)to9(describes me well). In the
current study, the internal consistency of this scale was .87, .89, and .89 at
Times 1, 2, and 3, respectively.
The Self-Exploratory Behavior scale of the SCTI contains 20 items (e.g.,
“I have talked with my friends about my interests”), which are a combi-
nation of four relevant domains of self-exploration (interests, values,
abilities, and study strategies) with five relevant sources of information
(self, parents, friends, teachers, and others). Three response categories (i.e.,
never,sometimes, and often) are used to indicate the frequency of self-
exploratory behavior during the last and current school year, as reported by
the students. Cronbach’s alphas for the self-exploratory behavior scale
were .87, .88, and .89 at the three measurement times, respectively.
The Broad Exploratory Behavior scale of the SCTI is a 5-item scale
(e.g., “I glanced through general summaries about the structure of higher
education”). Before probing in-depth exploratory behavior, we first asked
students to give the names of the area of studies about which they had
collected information. Next the 10-item In-Depth Exploratory Behavior
scale has to be completed with regard to these studies (e.g., “I thoroughly
read a brochure about these studies”). Students who had not looked up
information about any study did not have to fill out the In-Depth Explor-
atory Behavior scale. For the Broad Exploratory Behavior scale as well as
the In-Depth Exploratory Behavior scale, three response categories (i.e.,
never,sometimes, and often) are used to indicate the frequency of envi-
ronmental exploratory behavior during the last and current school years.
For the Broad Exploratory Behavior scale, Cronbach’s alphas were .85,
.77, and .80, respectively, and for the In-Depth Exploratory Behavior scale,
they were .70, .63, and .76 at Times 1, 2, and 3, respectively.
Decisional Status is measured in the SCTI by two questions: (a) “List all
studies you are considering now” and (b) “Which study is your first choice
(if undecided, write undecided)?” Numerical values are given to four
possibilities in responding: 1 (no first choice and no alternatives), 2
(alternatives without a first choice),3(a first choice with alternatives), and
4(a first choice with no alternatives).
The Commitment scale of the SCTI is aimed at assessing the degree of
commitment to a study choice. Only students who indicated having a first
choice in the Decisional Status scale (i.e., score 3 or 4) were asked to fill
out this scale. The eight items (e.g., “Are you certain about this study?”)
are rated on a 6-point scale ranging from 1 (not at all)to6(yes, very). High
scores represent a high degree of commitment. Cronbach’s alphas for this
scale varied between .83 and .84.
Amount of information acquired. In order to measure the amount of
information acquired (i.e., about oneself, the career alternatives in general,
the career alternatives in detail) as reported by the adolescents, we used
three scales constructed by Germeijs and Verschueren (2004). The first
scale is the Amount of Self-Information Scale. It contains 10 items (e.g., “I
have a clear idea of my own needs and desires with respect to my future
educational career”) and is based on the Vocational Rating Scale (Barrett
& Tinsley, 1977). We retained only those items of the Vocational Rating
Scale referring to the knowledge of vocational attributes and characteris-
tics. Some items were adapted to the situation of choosing an area of study
in higher education. The second scale is the Amount of Broad Information
Scale, which probes students’ perceived knowledge about the general
structure of higher education and differences among different types of
higher education in Belgium. This scale consists of nine items (e.g., “I have
a good view on which majors exist in higher education”). Finally, the
15-item Amount of In-Depth Information Scale (e.g., “I’m aware of the
skills that are important in these studies”) was used to probe the perceived
amount of information about the studies taken into consideration by the
students (see In-Depth Exploratory Behavior scale of the SCTI). The items
of this scale were based on different aspects (e.g., skills needed in a study,
study length, fields of interest associated with a study) considered impor-
tant in characterizing a study in higher education.
All items of the three scales on the amount of information are answered
on a 5-point response scale ranging from 1 (completely false)to5(com-
pletely true). Germeijs and Verschueren (2004) provided evidence for the
validity of these scales by finding connections with existing measures of
career exploration (Career Exploration Survey; Stumpf et al., 1983) and
career decision-making difficulties (Career Decision-Making Difficulties
Questionnaire; Gati et al., 1996) and through a comparison of the scores
across different grades and across different vocational identity statuses.
The Cronbach’s alphas of the Amount of Self-Information Scale (.90, .89,
and .89 for the first, second, and third measurement times, respectively),
the Amount of Broad Information Scale (.83, .85, and .86 for the first,
second, and third measurement times, respectively), and the Amount of
In-Depth Information Scale (.90, .90, and .91 for the first, second, and third
measurement times, respectively) in the current study were comparable
with those found by Germeijs and Verschueren (2004).
Results
Descriptive Statistics
Table 1 shows the means, standard deviations, and intercorre-
lations among scores for the variables at the three waves. The
means suggest an overall increase in the execution of all career
decisional tasks and a decrease in indecisiveness and career choice
anxiety during Grade 12. As can be seen in Table 1, most corre-
lations among scores for different career decisional tasks were
positive and significant, suggesting a positive association among
career decisional tasks within the three measurement occasions.
Some correlations with exploratory behavior (i.e., self, in depth)
and amount of broad information were not significant only for
decisional status and commitment.
400 GERMEIJS, VERSCHUEREN, AND SOENENS
It was hypothesized that indecisiveness would relate negatively
to decisional status, commitment, and the perceived amount of
information but not necessarily to orientation and exploratory
behavior. As expected, indecisiveness had a negative association
with the amount of information acquired about oneself and about
the environment (broad, in depth), decisional status, and commit-
ment at the three measurement times. Correlations between inde-
cisiveness and exploratory behavior regarding the self and the
environment (broad, in depth) and orientation were generally neg-
ative too. However, in line with the expectations, these correlations
were less pronounced and less consistent across measurement
times than the correlations with the amount of information ac-
quired, decisional status, and commitment. The relationship of
career choice anxiety with the career decisional tasks had a similar
Table 1
Means, Standard Deviations, Stability Coefficients, and Intercorrelations Among Variables at the Three Measurement Times
Variable 1234567891011
Time 1 (n⫽174–281)
1. Orientation
2. Self-Exploratory Behavior .42**
3. Broad Exploratory Behavior .47** .40**
4. In-Depth Exploratory Behavior .41** .52** .48**
5. Amount of Self-Information .36** .31** .38** .37**
6. Amount of Broad Information .33** .23** .40** .44** .36**
7. Amount of In-Depth Information .33** .26** .38** .51** .60** .66**
8. Decisional Status .20** .21** .18** .14 .32** .19** .30**
9. Commitment .34** .15* .25** .19** .56** .14 .41** .24**
10. Indecisiveness ⫺.08 ⫺.14* ⫺.16** ⫺.20** ⫺.45** ⫺.20** ⫺.27** ⫺.17** ⫺.28**
11. Career Choice Anxiety ⫺.03 .00 ⫺.01 ⫺.03 ⫺.40** ⫺.16** ⫺.26** ⫺.08 ⫺.31** .47**
M6.43 0.91 0.56 0.62 2.37 1.72 2.32 2.70 4.16 2.58 2.53
SD 1.34 0.32 0.50 0.33 0.76 0.72 0.66 0.86 0.72 0.86 0.79
Time 2 (n⫽228–281)
1. Orientation
2. Self-Exploratory Behavior .34**
3. Broad Exploratory Behavior .45** .38**
4. In-Depth Exploratory Behavior .34** .54** .51**
5. Amount of Self-Information .23** .24** .19** .22**
6. Amount of Broad Information .28** .13* .34** .27** .39**
7. Amount of In-Depth Information .36** .31** .40** .46** .52** .60**
8. Decisional Status .19** .12** .14* .09 .34** .12* .24**
9. Commitment .32** .17** .23** .21** .56** .20** .45** .41**
10. Indecisiveness ⫺.11 ⫺.16** .00 ⫺.15* ⫺.48** ⫺.23** ⫺.30** ⫺.17** ⫺.43**
11. Career Choice Anxiety ⫺.03 ⫺.07 .05 .00 ⫺.52** ⫺.14* ⫺.27** ⫺.27** ⫺.52** .55**
M6.97 0.94 1.19 0.74 2.65 2.58 2.71 3.01 4.47 2.49 2.48
SD 1.22 0.34 0.45 0.30 0.67 0.66 0.59 0.68 0.66 0.91 0.79
Time 3 (n⫽253–281)
1. Orientation
2. Self-Exploratory Behavior .37**
3. Broad Exploratory Behavior .35** .43**
4. In-Depth Exploratory Behavior .45** .58** .60**
5. Amount of Self-Information .34** .25** .18** .28**
6. Amount of Broad Information .34** .16** .36** .35** .36**
7. Amount of In-Depth Information .38** .23** .33** .43** .56** .60**
8. Decisional Status .24** .07 .13* .18** .36** .09 .26**
9. Commitment .33** .07 .22** .23** .57** .30** .49** .51**
10. Indecisiveness ⫺.12* ⫺.04 ⫺.16** ⫺.18** ⫺.47** ⫺.28** ⫺.36** ⫺.24** ⫺.43**
11. Career Choice Anxiety ⫺.14* ⫺.04 ⫺.10 ⫺.11 ⫺.51** ⫺.19** ⫺.39** ⫺.33** ⫺.57** .56**
M7.12 1.04 1.21 0.97 2.84 2.83 3.07 3.46 4.78 2.43 2.36
SD 1.22 0.34 0.46 0.35 0.67 0.63 0.53 0.70 0.62 0.93 0.87
Stability
Time 1–Time 2 .53** .59** .35** .57** .68** .42** .54** .38** .61** .77** .60**
Time 2–Time 3 .63** .70** .56** .63** .65** .70** .65** .25** .71** .82** .68**
Time 1–Time 3 .38** .55** .32** .44** .54** .51** .28** .20** .53** .80** .57**
Note. Time 1 ⫽beginning of Grade 12; Time 2 ⫽middle of Grade 12; Time 3 ⫽end of Grade 12.
*p⬍.05. ** p⬍.01.
401
INDECISIVENESS AND CAREER DECISION-MAKING PROCESS
pattern, showing significant negative correlations with the three
aspects of amount of information acquired, decisional status, and
commitment but not with orientation and self- and environmental
(broad, in-depth) exploratory behavior. Finally, as expected, sig-
nificant positive correlations were obtained between indecisive-
ness and career choice anxiety.
As indicated by the correlations among indecisiveness scores
across measurement times, the stability coefficients for indecisive-
ness (ranging from .77 to .82) were high (Cohen, 1988). This
means that a student’s relative position in the group did not change
much across the three moments. With regard to the career deci-
sional tasks, stability was mostly moderate to high (Cohen, 1988).
The stability coefficients were small to moderate only for the task
decisional status (Cohen, 1988). Finally, for career choice anxiety,
stability coefficients were high but lower than for indecisiveness
(ranging from .57 to .68).
Effect of Indecisiveness on Career Decision Making
In order to address the research questions about the differential
effect of indecisiveness on the level of career decisional tasks and
on adolescents’ developmental change in career decisional tasks,
we used latent curve modeling (Duncan, Duncan, Strycker, Li, &
Alpert, 1999). All models were estimated with the LISREL 8.71
software (Jo¨reskog & So¨rbom, 2004) using maximum likelihood
estimation. Data screening of the observed variables indicated
partial data nonnormality, both at the univariate and the multivar-
iate levels. In order to correct for this, we used in addition to the
covariance matrix the asymptotic covariance matrix among all
indicators as input, and we inspected the Satorra–Bentler scaled
chi-square (
SBS
2
; Satorra & Bentler, 1999) as a measure of fit
(Jo¨reskog, So¨rbom, du Toit, & du Toit, 1999). In addition, we used
the standardized root-mean-square residual (SRMR), the root-
mean-square error of approximation (RMSEA), and the compara-
tive fit index (CFI) as measures of fit (Hu & Bentler, 1999). When
comparing nested alternative models, we used Satorra–Bentler
chi-square difference tests (Satorra & Bentler, 1999). It is impor-
tant to note is that not all students of the longitudinal sample filled
out the In-Depth Exploratory Behavior Scale, the Amount of
In-Depth Information Scale, and the Commitment Scale (see Mea-
sures). Because listwise deletion
2
was used in LISREL 8.71, the
analyses about in-depth exploration and amount of in-depth infor-
mation were only performed on the subgroup of students who had
already looked up information about some studies at the beginning
of Grade 12 (n⫽174) and the analyses about commitment only
were performed on the students who already had a first choice at
the beginning of Grade 12 (n⫽160).
3
Preliminary analyses. Before investigating the effect of inde-
cisiveness on career decision making, we had to identify models
that best describe changes in career decisional tasks during Grade
12. Therefore, two-factor latent curve models were used. For each
career decisional task, two latent factors were modeled, namely (a)
the intercept, reflecting the level of the career decisional tasks at a
fixed measurement time, and (b) the slope, which describes the
rate of change over time (Duncan et al., 1999). In the current study,
for all career decisional tasks, the slope factor at Time 3 was fixed
to 0 and the slope factor at Time 1 was fixed to –1. As a
consequence, the estimated intercept means indicated the expected
mean scores for the decisional tasks at the end of Grade 12 (Willett
& Sayer, 1994), whereas the estimated slope means showed the
mean rate of change between the beginning and the end of Grade
12. For each career decisional task, the fit of three models was
compared in order to select the model that best described the
changing curves: (a) an unspecified two-factor model, allowing
possible nonlinear trajectories (slope factor loadings at Time 1 and
Time 3 being fixed to –1 and 0, respectively, and the slope factor
loading at Time 2 being freely estimated); (b) a linear growth
model (slope factor loadings fixed at –1, –0.5, and 0 at Times 1,
2, and 3, respectively); and (c) a strict stability model (model
without slope factor). In the unspecified two-factor model, the
variances of the time-specific errors had to be set equal for iden-
tification purposes. As a consequence, this equality constraint was
also used in the linear growth model and in the strict stability
model.
Analyses revealed that for all career decisional tasks, the fit of
the strict stability model was significantly worse than the fit of the
unspecified two-factor baseline model. For four career decisional
tasks (i.e., orientation, broad exploratory behavior, amount of
broad information, amount of in-depth information), the unspeci-
fied two-factor model provided a significantly better fit than the
respective linear growth models, indicating that for these career
decisional tasks, growth was best described by a nonlinear trend.
For five decisional tasks (i.e., self-exploratory behavior, in-depth
exploratory behavior, amount of self-information, decisional sta-
tus, commitment), no significant differences in fit were found
between the unspecified two-factor model and the linear growth
model, suggesting that for these decisional tasks, growth was
adequately and most parsimoniously described by a linear pattern.
However, for decisional status and commitment, the linear growth
model provided an inadequate fit:
SBS
2
(3, N⫽267) ⫽12.91,
RMSEA ⫽.11, SRMR ⫽.08, CFI ⫽.84, for decisional status, and
SBS
2
(3, N⫽160) ⫽19.26, RMSEA ⫽.12, SRMR ⫽.05, CFI ⫽
.97, for commitment. Additional analyses revealed that this inad-
equate fit was due to the equality constraints of the error variances
of the measurements across the three waves, indicating that the
restriction of equal time-specific error variances were not reason-
able for the these tasks. Therefore, time-specific error variances
were not restricted to be equal in the final linear growth models of
decisional status and commitment (see Table 2).
Table 2 presents the fit indices and parameter estimates of the
final models, which indicate an adequate fit (Browne & Cudeck,
1993; Byrne, 1998; Hu & Bentler, 1999). The RMSEA value of
.10 indicated mediocre fit only for self-exploratory behavior
(Byrne, 1998). However, because the modification indices did not
2
Using the method of listwise deletion reduces the sample size, which
may lead to less power to detect significant effects and to better-looking
models. However, a reanalysis of the data using the full information
maximum likelihood option in LISREL to deal with missing data revealed
only one additional significant effect (i.e., an effect of indecisiveness on the
slope of amount of self-information, ⫽.17, p⬍.05). In addition, all
models still showed an adequate fit when using full information maximum
likelihood.
3
Although these sample sizes may seem rather small, similar sample
sizes turned out to be appropriate for latent curve modeling (e.g., Curran &
Bollen, 2001; Stoolmiller, 1994; Willett & Sayer, 1994).
402 GERMEIJS, VERSCHUEREN, AND SOENENS
suggest to change the model and the other fit measures indicated
an adequate fit, the model was not modified.
In Table 2, the estimated intercept means indicate the mean
scores for execution of the decisional tasks at the end of Grade 12.
For all career decisional tasks, the slope means were significant
and positive (Table 2), indicating that on average substantial
growth occurred during Grade 12. The significant variances for the
intercept and slopes of all career decisional tasks indicate that there
was substantial variability across high school students in the career
decisional tasks at the end of Grade 12 and in the rate of change.
No substantial differences in intraindividual change existed among
high school students only for decisional status.
Indecisiveness predicting latent curve parameters. To exam-
ine the contribution of indecisiveness to the execution of career
decisional tasks and to intraindividual change in career decisional
tasks, we investigated the effect of indecisiveness on the intercept
and slope factor (see Figure 1). In each final model of the respec-
tive career decisional tasks, a latent indecisiveness variable was
added, representing the level of indecisiveness at the beginning of
Grade 12.
4
The latent indecisiveness variable was identified by
three indicator variables, namely three item parcels for indecisive-
ness at Time 1. The first item of the Indecisiveness Scale was
assigned to the first parcel, the second item to the second parcel,
the third item to the third parcel, the fourth item to the first parcel,
and so forth. Because the intercept factor of the career decisional
tasks was defined at Time 3, temporal precedence of the predictor
(i.e., indecisiveness at Time 1) to the outcomes was ensured.
In Table 3, the results of these analyses are shown, presenting
the structural paths from indecisiveness to the intercept and slope.
As expected, indecisiveness had a significant negative effect on the
intercept of decisional status and degree of commitment, indicating
that adolescents with higher scores on indecisiveness at the begin-
ning of Grade 12 showed lower levels of decisional status and a
lower degree of commitment at the end of Grade 12. Furthermore,
higher levels of indecisiveness at the beginning of Grade 12 were
predictive of lower levels of the amount of information about
oneself and about the career alternatives (broad, in depth) at the
end of Grade 12. In contrast, indecisiveness was not related to the
intercept of orientation, self-exploratory behavior, and in-depth
exploratory behavior. The negative effect of indecisiveness on the
intercept of broad exploratory behavior was significant but small,
t(280) ⫽–2.00, p⫽.046. In sum, these findings indicate that
indecisiveness is a risk factor for future levels of some but not all
career decisional tasks.
With regard to the effect of indecisiveness on the rate of change
in career decisional tasks, no effects on the slopes of the career
decisional tasks were revealed. These findings indicate that inde-
cisiveness does not explain interindividual differences in intrain-
dividual change with regard to the career decisional tasks. Because
the changing curves of students with high and low indecisiveness
have the same slope and are therefore parallel, this result suggests
that the effect of indecisiveness on the level of the career deci-
sional task remains rather constant during the career decision-
making process.
Mediational Role of Anxiety
The final purpose of this study was to test the role of career
choice anxiety as a mediating variable through which indecisive-
ness influences career decision making. Because indecisiveness
did not have any effect on the slope of the career decisional tasks,
only the level of the career decisional tasks was used as a depen-
dent variable in the remainder of the analyses. As a consequence,
latent curve modeling was not needed anymore to model the career
decisional tasks, and therefore we used latent task variables rep-
resenting the level of the tasks at the end of Grade 12. Each latent
task variable was identified by three indicator variables (i.e., three
item parcels of a task at Time 3, created in the same way as for
indecisiveness). Only for decisional status, the latent task variable
was identified by fixing the path from the manifest variable to the
4
Latent curve analyses on the indecisiveness scores at the three mea-
surement times suggest that the Time 1 scores for indecisiveness are
appropriate to use in the structural models because indecisiveness shows a
uniform change during Grade 12 without individual variation (Chassin,
Curran, Hussong, & Colder, 1996).
Table 2
Results of Latent Curve Analyses on Career Decisional Tasks: Fit Indices and Parameter Estimates for the Final Models
Career decisional task Model
SBS
2
df RMSEA
(90% CI) SRMR CFI
Intercept Slope
MVariance MVariance
Orientation (N⫽279) Unspecified two factor 1.29 2 .00 (.00–.10) .03 1.00 7.14** 1.02** 0.71** 0.97**
Self-Exploratory Behavior (N⫽281) Linear growth 10.74 3 .10 (.04–.16) .04 0.98 1.03** 0.09** 0.13** 0.03*
Broad Exploratory Behavior (N⫽281) Unspecified two factor 0.32 2 .00 (.00–.06) .01 1.00 1.21** 0.12** 0.65** 0.13**
In-Depth Exploratory Behavior (N⫽174) Linear growth 5.00 3 .06 (.00–.15) .03 0.99 1.02** 0.08** 0.41** 0.06**
Amount of Self-Information (N⫽281) Linear growth 2.12 3 .00 (.00–.09) .01 1.00 2.85** 0.31** 0.46** 0.20**
Amount of Broad Information (N⫽281) Unspecified two factor 4.36 2 .06 (.00–.15) .05 0.99 2.82** 0.31** 1.11** 0.29**
Amount of In-Depth Information (N⫽173) Unspecified two factor 2.89 2 .05 (.00–.17) .06 0.99 3.16** 0.15** 0.85** 0.31**
Decisional Status
a
(N⫽267) Linear growth 2.11 1 .06 (.00–.19) .00 0.98 3.45** 0.22** 0.77** 0.13
Commitment
a
(N⫽160) Linear growth 0.04 1 .00 (.00–.12) .00 1.00 4.87** 0.34** 0.65** 0.22*
Note. SBS ⫽Satorra–Bentler scaled; RMSEA ⫽root-mean-square error of approximation; CI ⫽confidence interval; SRMR ⫽standardized
root-mean-square residual; CFI ⫽comparative fit index.
a
In these models, the restriction of equal time-specific error variances was left out.
*p⬍.05. ** p⬍.01.
403
INDECISIVENESS AND CAREER DECISION-MAKING PROCESS
latent variable to 1 and the error variance to 0, because only one
item measured decisional status.
In Table 4 (see Total effect model), the effect of the latent
indecisiveness variable (representing indecisiveness at Time 1) on
the latent task variables (representing the decisional tasks at Time
3) is shown. These results are similar to the results of the analyses
in which latent curve modeling was used (see effect of indecisive-
ness on the intercepts in Table 3). Only differences for in-depth
exploratory behavior were found between both analyses, with
indecisiveness having a significant negative effect on the latent
task variable (see Table 4) but not on the intercept (see Table 3).
5
The mediational effect of career choice anxiety was tested only
for the seven career decisional tasks on which indecisiveness had
a significant effect (see Total effect model in Table 4).
6
First, the
fit of the overall mediational model was tested (see Figure 2), with
indecisiveness having an effect on career choice anxiety, with
career choice anxiety having an effect on the decisional task at the
end of Grade 12, and with a direct path from indecisiveness to the
decisional task. If this model provided an adequate fit, the path
coefficients were then examined. The paths from indecisiveness to
career choice anxiety and from career choice anxiety to the deci-
sional task should be significant in the directions predicted (i.e.,
positive and negative, respectively). In a final step, using the Sobel
test for indirect effects in LISREL 8.71, we tested the statistical
significance of the mediational effect in order to investigate
whether the effect of indecisiveness via career choice anxiety to
the decisional task is significant. This test is equivalent to a test of
whether the reduction in the effect from indecisiveness to the
career decisional tasks is significant as a result of including the
mediator in the model (Holmbeck, 2002). Besides these steps for
testing the mediational role of career choice anxiety, we also
investigated whether the previously significant path between in-
decisiveness and the decisional task was reduced to nonsignifi-
cance after controlling for the mediator (Holmbeck, 1997). An
alternative model was tested, with the direct path from indecisive-
ness to the decisional task being fixed to zero. The difference in fit
between the overall model and the restricted model was investi-
gated. No significant difference between both models indicates
that the direct path from indecisiveness to the decisional task was
not significant anymore in the mediational model.
In all mediational models, career choice anxiety was modeled as
a latent factor (identified by three item parcels, created in the same
way as for indecisiveness) representing the level of career choice
anxiety in the middle of Grade 12. As a consequence, in all
mediational models, temporal precedence of indecisiveness to
anxiety and of anxiety to the career decisional tasks was ensured.
All models were estimated with the LISREL 8.71 software (Jo¨res-
kog&So¨rbom, 2004) using the covariance matrix, the asymptotic
covariance matrix, and maximum likelihood estimations.
5
One possible explanation for this finding is the different group on
which the analyses were performed. In the latent curve model, the intercept
of in-depth exploratory behavior was estimated only for the subgroup of
the longitudinal sample who had looked up information about some studies
at the beginning, the middle, and the end of Grade 12 (n⫽174), whereas
for the analyses on the latent task variable, all students of the longitudinal
sample who answered the In-Depth Exploration Scale at the end of Grade
12 were taken into account (n⫽274).
6
There is debate about whether a direct link needs to be established
between independent and dependent variables before testing for mediation.
The approach of Baron and Kenny (1986) and Holmbeck (1997), which is
followed in the current study, makes a conceptual distinction between
indirect and mediated models. According to these authors, mediation can
only be demonstrated when there is initially a significant link between
independent and dependent variables, whereas for an indirect effect, no
initial relationship between both variables is needed. Other authors (e.g.,
MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002) have argued that
in order to demonstrate the intervening role of a variable, one mainly needs
to establish whether the size of the indirect effect is significant.
ksatl
an
oisicedreeraC1tpecretnI
1e
miTssenevisicednI
Item parcel 1 Career decisional task 1 Time 1
ksa
tlanoisicedreeraCssenev
isiced
nI1em
iTssene
vis
icednI
2emiT
1emiT
2l
e
c
rapmetI
-1
Slope
ksatlanoisicedreeraCeerfro5.0-ksatlanoisicedreeraC1emiTssenevisicednI
3emiT03 lecra
pmet
I
Figure 1. Effect of indecisiveness on intercept and slope of career decisional tasks.
Table 3
Path Coefficients for the Effect of Indecisiveness on Intercept
and Slope in Latent Curve Models of Career Decisional Tasks:
Standardized Solution
Career decisional task Intercept Slope
Orientation ⫺.10 .00
Self-Exploratory Behavior ⫺.10 .11
Broad Exploratory Behavior ⫺.15* .09
In-Depth Exploratory Behavior ⫺.15 .09
Amount of Self-Information ⫺.53** .15
Amount of Broad Information ⫺.29** ⫺.02
Amount of In-Depth Information ⫺.27** .15
Decisional Status ⫺.19* .07
Commitment ⫺.31** .06
*p⬍.05. ** p⬍.01.
404 GERMEIJS, VERSCHUEREN, AND SOENENS
As can be seen in Table 5, all overall mediational models
showed an adequate fit, and therefore the path coefficients of all
seven models were inspected for significance (see Table 4). The
path from indecisiveness to career choice anxiety was significant
in the expected direction, with higher indecisiveness at Time 1
predicting a higher degree of career choice anxiety at Time 2.
Furthermore, for all except one career decisional task, the effect of
the career choice anxiety was significant. This path was not sig-
nificant only for the amount of broad information, thereby indi-
cating that career choice anxiety cannot be considered as a medi-
ating variable for this decisional task.
The results in Table 4 and Table 5 indicate that significant
mediation occurred for the amount of self-information, the amount
of in-depth information, decisional status, and commitment. For
these four career decisional tasks, the significant effect of career
choice anxiety in the mediational model was in the predicted
direction, with higher levels of career choice anxiety at Time 2
predicting lower levels of the tasks at Time 3 (see Table 4). As can
be seen from Table 4, the mediational effect of career choice
anxiety on the amount of self-information, amount of in-depth
information, decisional status, and commitment was significant
and negative, which implies that the drop in the effect of indeci-
Career choice anxiety Career choice anxiety Career choice anxiety
Time 2 Item parcel 1 Time 2 Item parcel 2 Time 2 Item parcel 3
Career choice anxiety
Time 2
ksa
tl
ano
i
sicedreeraCssen
ev
isic
ednI
1 lec
ra
pmetI3
e
m
i
T
1lecrap
metI1emiT
Indecisiveness Indecisiveness Career decisional task Career decisional task
Time 1 Item parcel 2 Time 1 Time 3
Time 3 Item parcel 2
ksatlanoisicedreeraCssenevisicednI
3
lecra
p
metI3e
m
iT3 le
cr
ap
m
et
I1
emi
T
Figure 2. Overall mediational model: Effect of indecisiveness on career decisional tasks, with career choice
anxiety as mediator.
Table 4
Path Coefficients in Total Effect Models and Overall Mediational Models, With Career Choice Anxiety as Mediator: Standardized
Solution
␥variable
Total effect model Overall mediational model
XT1 3YT3 (total effect) XT1 3MT2 MT2 3YT3 XT1 3YT3
(direct effect) XT1 3MT2 3YT3
(mediated effect)
Orientation ⫺.14
Self-Exploratory Behavior ⫺.10
Broad Exploratory Behavior ⫺.17* .55** .18* ⫺.26** .10*
In-Depth Exploratory Behavior ⫺.23** .55** .22* ⫺.34** .12*
Amount of Self-Information ⫺.45** .55** ⫺.34** ⫺.26** ⫺.18**
Amount of Broad Information ⫺.26** .55** .11 ⫺.32** .06
Amount of In-Depth Information ⫺.38** .55** ⫺.20* ⫺.26** ⫺.11*
Decisional Status ⫺.16* .54** ⫺.29** .00 ⫺.16**
Commitment ⫺.40** .53** ⫺.39** ⫺.20** ⫺.21**
Note. Total effect model, with indecisiveness at Time 1 (XT1) having an effect on the career decisional task at Time 3 (YT3); Mediational model, with
career choice anxiety at Time 2 (MT2) as mediator.
*p⬍.05. ** p⬍.01.
405
INDECISIVENESS AND CAREER DECISION-MAKING PROCESS
siveness on the career decisional task was significant as a result of
the inclusion of career choice anxiety as a mediator. In sum, the
results indicate mediation for the amount of self-information,
amount of in-depth information, decisional status, and
commitment.
As can be seen from Table 5, with regard to decisional status, no
significant difference in fit was found between the overall model
and the constrained model, indicating that the effect of indecisive-
ness on decisional status was not significant anymore after con-
trolling for career choice anxiety. For the other three tasks, the
overall mediational model had a significantly better fit than the
restricted model, thereby indicating that the direct effect of inde-
cisiveness still remained significant after controlling for career
choice anxiety.
For broad exploratory behavior and in-depth exploratory behav-
ior, the path from career choice anxiety was significant but posi-
tive, indicating that higher levels of career choice anxiety related
to higher levels of environmental exploratory behavior (i.e., broad
and in depth). By consequence, the mediational path was also
positive (s⫽.10 and .12 for broad and in-depth exploratory
behavior, respectively). In contrast, the direct effect of indecisive-
ness on these tasks had the opposite sign (s⫽–.26 and –.34,
respectively). As can be seen from Table 4, this resulted in a
negative total effect of indecisiveness on environmental explor-
atory behavior (s⫽–.17 and –.23, respectively), which was
smaller than the direct effect. In sum, although the total effect of
indecisiveness on exploratory behavior was negative, the media-
tional path had the opposite effect: Indecisiveness increased career
choice anxiety, which in turn led to more instead of less environ-
mental exploratory behavior. Thus, adding the mediational vari-
able led to an increase of the effect of the predictor variable on the
criterion. These results suggest inconsistent mediation or suppres-
sion for environmental exploratory behavior: The magnitude of the
effect of indecisiveness on environmental exploratory behavior
increased instead of decreased when career choice anxiety was
included (MacKinnon, Krull, & Lockwood, 2000).
Discussion
The current longitudinal study had three goals. The first goal
was to examine the effect of indecisiveness on high school stu-
dents’ future level of career decision-making tasks. The second
goal was to investigate the relation of indecisiveness with the rate
of change in career decisional tasks during Grade 12. The third
goal was to examine the mediating role of career choice anxiety in
the relationship between indecisiveness and high school students’
career decision-making process.
Effect of Indecisiveness on Career Decision Making
The results of this study show that indecisiveness may be
considered as a risk factor for future coping with several but not all
career decisional tasks. Higher levels of indecisiveness at the
beginning of Grade 12 predicted lower levels of the perceived
amount of information regarding oneself and the environment
(broad, in depth) and lower levels of decisional status at the end of
Grade 12. These results are in line with definitions of indecisive-
ness (e.g., Crites, 1969) and previous findings from cross-sectional
research (e.g., Cooper et al., 1984; Dickinson & Tokar, 2004;
Germeijs & De Boeck, 2003).
In addition and as expected, indecisiveness had a negative effect
on the degree of commitment with the chosen study at the end of
Grade 12. This finding highlights that even if indecisive people do
choose an alternative, they are less committed to their choice.
Because several authors (e.g., Blustein, Ellis, & Devenis, 1989;
Harren, 1979) have suggested that a lower degree of commitment
to a choice may forecast problems with the implementation of that
choice, it may be expected that indecisive students who did make
a choice for a major in higher education may encounter difficulties
during their studies (e.g., less choice satisfaction, lower perfor-
mance in the chosen option, less choice stability). However, ad-
ditional research is needed in order to investigate this hypothesis.
With regard to environmental exploratory behavior, the results
show that students with higher levels of indecisiveness at the
beginning of Grade 12 are at risk for showing lower levels of
environmental exploratory behavior (i.e., broad and in depth) at the
end of Grade 12. However, these relationships were smaller and
less robust than the associations with amount of information ac-
quired, decisional status, and commitment. Moreover, indecisive-
ness was not related to self-exploratory behavior. Some authors
have suggested that indecisive people do not have problems with
Table 5
Fit Indices for the Overall and Restricted Mediational Models, With Career Choice Anxiety as Mediator
Career decisional task
Overall mediational model Restricted mediational model
⌬
SBS
2
⌬df
SBS
2
df RMSEA
(90% CI) SRMR CFI
SBS
2
df RMSEA
(90% CI) SRMR CFI
Broad Exploratory Behavior (N⫽277) 28.29 24 .03 (.00–.06) .03 1.00 37.06 25 .04 (.00–.07) .06 0.99 11.47** 1
In-Depth Exploratory Behavior (N⫽274) 23.97 24 .00 (.00–.05) .04 1.00 38.65 25 .04 (.01–.07) .08 0.99 16.82** 1
Amount of Self-Information (N⫽277) 24.26 24 .01 (.00–.05) .02 1.00 36.50 25 .04 (.00–.07) .06 1.00 14.27** 1
Amount of Broad Information (N⫽277) 23.21 24 .00 (.00–.05) .02 1.00 37.44 25 .04 (.00–.07) .08 0.99 13.95** 1
Amount of In-Depth Information (N⫽274) 34.45 24 .04 (.00–.07) .03 1.00 44.52 25 .05 (.03–.08) .07 0.99 9.78** 1
Decisional Status (N⫽274) 18.03 12 .04 (.00–.08) .02 1.00 18.19 13 .04 (.00–.08) .02 1.00 1.54 1
Commitment (N⫽250) 27.35 24 .02 (.00–.06) .04 1.00 32.65 25 .04 (.00–.07) .04 1.00 5.25* 1
Note. Overall mediational models have three structural paths: from indecisiveness to career choice anxiety and to the career decisional task, and from
career choice anxiety to the career decisional task. In the restricted mediational models, the direct path from indecisiveness to the career decisional task
is fixed to zero. SBS ⫽Satorra–Bentler scaled; RMSEA ⫽root-mean-square error of approximation; CI ⫽confidence interval; SRMR ⫽standardized
root-mean-square residual; CFI ⫽comparative fit index; ⌬
SBS
2
⫽Satorra–Bentler chi-square difference test between overall and restricted model.
406 GERMEIJS, VERSCHUEREN, AND SOENENS
information gathering. For example, according to Crites (1969),
indecisive people “may have appropriate information for making a
choice” (p. 600). The findings from this study suggest that this
may especially be true for information about oneself. Interestingly,
although indecisiveness was not related to less self-exploratory
behavior, it was related to lower perceived amounts of information
about the self. These results highlight the importance of distin-
guishing between exploratory behavior and the amount of infor-
mation acquired, as was already stressed by Stumpf et al. (1983).
One possible explanation for this differential effect of indecisive-
ness may be the relationship of indecisiveness with maladaptive
perfectionism (Frost & Shows, 1993). Indecisive people may show
the same amount of self-exploratory behavior as other individuals,
but they may be so overly concerned with making mistakes that
they express doubt about having enough self-information. How-
ever, this possible explanation together with the reason for why
this differential effect was not found for environmental exploration
remain important topics for further investigation.
On a practical level, the results suggest that when counselors are
confronted with indecisive students who need to make a career
choice, providing information alone may not be sufficient, but
encouraging them to make use of the information they have
already acquired may be needed too. For example, the counselor
can help clients with the structuring and ordering of information,
which may in turn enhance clients’ confidence in having the
appropriate information. The results of the current study show that
this may especially be important for information related to the self.
In addition, the results suggest that indecisive clients may need
help with selecting an alternative. This can be facilitated for
instance by explaining to them a systematic method for comparing
alternatives (Gati & Asher, 2001). For example, Janis and Mann’s
(1977) balance sheet procedure in which career alternatives are
compared on favorable and unfavorable consequences (gains or
losses for self or significant others, approval or disapproval for self
or others) or Katz’s (1993) method of comparing career alterna-
tives on a list of attributes that characterize alternatives (e.g., skills
required, corresponding interests) may be used for this purpose.
Finally, because indecisiveness turned out to be a risk factor for
commitment to a choice, it seems important that indecisive people
still receive support and encouragement from their environment
after a decision is made, so that they learn to experience a sense of
certainty and identification with the choice they made.
Indecisiveness did not turn out to be a risk factor for students’
awareness of the need to make a decision and motivation to engage
in the career decision process. Thus, the problems indecisive
students have with making career decisions do not seem to stem
from a lack of motivation with regard to the career decision-
making process. This finding is in line with Crites’s (1969) defi-
nition of indecisiveness as the inability to make decisions “even
after all conditions for doing so, such as choice supply, incentive
[italics added] to make a choice, . . . are provided” (p. 600). It
should be noted that Gati, Osipow, Krausz, and Saka (2000) did
find a significant positive association between indecisiveness and
the lack of motivation to engage in the career decision-making
process. However, in contrast to our study, the correlations men-
tioned by Gati et al. (2000) were based on data from counselees
who applied for personal career counseling. Whether this differ-
ence in response group sufficiently explains the divergent findings
remains a topic for further investigation.
An additional aim of the present study was to examine the effect
of indecisiveness on the developmental progress in career de-
cisional tasks. However, we did not find any effect of indeci-
siveness on the slopes of the career decisional tasks. This result
indicates that indecisiveness cannot explain the interindividual
differences in intraindividual change in career decisional tasks
during Grade 12.
Mediational Role of Anxiety
In line with the hypothesis of Crites (1969) and Goodstein
(1972), we examined the mediational role of one variable, namely
career choice anxiety. Results revealed that the relation between
indecisiveness, on the one hand, and the amount of self-
information, amount of in-depth information, decisional status, and
commitment, on the other hand, were mediated by students’ career
choice anxiety. This finding indicates that high-indecisive students
tend to show lower levels of the perceived amount of self and
in-depth information, less progress in decisional status, and less
commitment, (partly) because indecisiveness is associated with
more anxiety about making a career choice, which in turn predicts
lower levels of these career decisional tasks. Although several
authors have stressed the important role that anxiety may play in
the relationship between indecisiveness and career decision-
making problems (e.g., Kaplan & Brown, 1987), empirical re-
search testing the mediational role of anxiety has been lacking. For
that reason, our study provides an important contribution to un-
derstanding the mechanisms through which indecisiveness affects
the career decision-making process.
It is important to note that with regard to the amount of self-
information, in-depth information, and commitment, the effect of
indecisiveness still remained significant after career choice anxiety
was taken into account. This finding indicates that career choice
anxiety cannot fully explain the association between indecisive-
ness and these career decisional tasks, leaving place for other
potential mediators. For example, the mediating effect of self-
esteem may be worth studying in future research, because previous
research has suggested that indecisiveness is related to lower
self-esteem (e.g., Germeijs & De Boeck, 2002; Santos, 2001) and
lower self-esteem is related to career indecision (e.g., Creed,
Prideaux, & Patton, 2005; Greenhaus, Hawkins, & Brenner, 1983).
In line with suggestions offered in the literature on career
counseling (e.g., Kaplan & Brown, 1987; Van Matre & Cooper,
1984), the findings of this study indicate that anxiety-management
counseling may help indecisive clients to overcome their problems
with the perceived amount of self- and in-depth information, with
making a career decision, and with feeling committed to their
career choice. However, taking into account the fact that career
choice anxiety could not fully explain the link between indecisive-
ness and these tasks, this study also shows that only paying
attention to anxiety may be not enough for indecisive clients.
Counselors may need to pay attention to other possible underlying
mechanisms including perfectionism and self-esteem, and they
may work on that level too. Clearly, intervention studies are
needed in order to investigate this issue further.
407
INDECISIVENESS AND CAREER DECISION-MAKING PROCESS
We found inconsistent mediation with regard to broad and
in-depth exploratory behavior. The direct effect of indecisiveness
on environmental exploratory behavior (i.e., broad and in depth)
was negative, whereas the mediational effect through career choice
anxiety was positive. The significant negative direct effect indi-
cates that if career choice anxiety is held constant, indecisiveness
is likely to lead to less environmental exploratory behavior. It is
interesting to note that the positive effect of career choice anxiety
on these tasks did not cancel out completely the negative effect of
indecisiveness, because the total effect of indecisiveness remained
negative and significant. As already discussed, the total effect of
indecisiveness on environmental exploratory behavior was rather
small and less robust. The suppression effect can explain why this
relationship between indecisiveness and environmental explor-
atory behavior was not very strong.
Hence, it appears that indecisiveness may relate to higher or
lower levels of exploratory behavior, depending on whether it is
associated with career choice anxiety. To the extent that indeci-
siveness gives rise to higher levels of career choice anxiety,
adolescents become more likely to engage in exploratory behavior.
However, to the extent that indecisiveness does not elicit career
choice anxiety, this characteristic relates to lower levels of explor-
atory behavior.
Although unexpected, these findings are consistent with find-
ings obtained in the broader literature on exploration and identity.
Specifically, the positive effect of career choice anxiety on explor-
atory behavior is consistent with the findings of other researchers
demonstrating positive relationships between environmental ex-
ploration and career anxiety (Vignoli, Croity-Belz, Chapeland, de
Fillipis, & Garcia, 2005) and anxiety expressed as stress associated
with decision making (Blustein & Phillips, 1988). In the identity
literature, it has also been shown that a tendency to experience
negative affects (including anxiety) elicits some exploration of
identity alternatives (e.g., Clancy & Dollinger, 1993; Luyckx,
Soenens, & Goossens, in press). However, this exploration pre-
sumably serves to cope with feelings of worry and stress and may
represent a process of rumination rather than a thorough evaluation
of identity alternatives (Luyckx et al., in press). Clearly, additional
research is needed in order to examine more in depth the role of
anxiety in coping with decisional tasks.
Stability of Indecisiveness Over Time
The results of the current study contribute to a clearer concep-
tualization of indecisiveness. Although it was not a central re-
search aim of this study, the longitudinal data on indecisiveness
made it possible to investigate the stability of indecisiveness over
time. Stability, meaning the invariance of relative standing of
people over time, is characteristic of a trait (Kenny & Zautra,
2001; Strelau, 2001). Although indecisiveness has repeatedly been
defined in the literature as a trait (e.g., Cooper et al., 1984;
Osipow, 1999; Van Matre & Cooper, 1984), longitudinal studies
investigating the stability of indecisiveness have surprisingly been
lacking. In the current study, the results show that, on average,
indecisiveness decreases during Grade 12. However, the high
correlations between indecisiveness across measurement times in-
dicate that students’ relative standing remains the same over time
and suggest that students’ rate of decrease in indecisiveness is
comparable, which provides evidence for the stability of indeci-
siveness. The results of the latent curve analyses further confirm
this idea by showing invariance of interindividual differences in
intraindividual change in indecisiveness. Our study thus provides
essential support for the conceptualization of indecisiveness as a
trait.
Limitations and Future Research
Although the results of the current study provide new insights
into the indecisiveness construct and its relation to the career
decision-making process, some limitations should be noted. First,
despite the longitudinal design, the results do not necessarily
indicate causal influences. For example, other variables not in-
cluded in the present study may have influenced indecisiveness,
the career decisional tasks, and career choice anxiety. Because we
did not control for these kind of variables, we cannot rule out the
possibility that the relations obtained here are due to confounding
influences. Future research should pay attention to the causality
issue by including more variables related to indecisiveness, the
career decisional tasks, and career choice anxiety. In addition,
investigating whether the effects we found are consistent across
samples and whether, for example, anxiety-management interven-
tions enhance coping with career tasks is needed in order to draw
causal inferences (Kazdin, 1999; Kraemer et al., 1997). A second
limitation is that we focused on one specific career decision,
namely the choice of a study in higher education. Furthermore, the
sample of this study only consisted of students who followed
general education in high school. Future studies could give an
indication about the generalizability of these findings to other
career decisions in other populations. In addition, given that the
sample in our study was European and racially homogeneous,
research is needed in order to investigate whether the mean scores
on the career decisional tasks and their relationship with other
variables are comparable across other cultures or ethnicity groups.
Third, the specific design used in a longitudinal study (i.e., mea-
surement interval, measurement occasions) may have conse-
quences for the research findings (e.g., Rueter & Conger, 1998).
Therefore, the results in this study may not be generalized beyond
the design used. Fourth, the career decision-making process was
studied by means of questionnaires assessing the decisional tasks.
For a greater depth of understanding of an individual’s career
decision-making process, one could complement this study with
studies using, for example, a diary-based approach or interviews.
Fifth, with regard to decisional status and commitment, model
modifications were used in order to find the adequate latent curve
models. Additional research with new data is needed to cross-
validate these modified models (Boomsma, 2000). Finally, in this
study, clear evidence was found for a negative effect of indeci-
siveness on several career decisional tasks. However, we did not
investigate whether this negative impact has implications for the
quality of the implementation of the study choice too. Several
authors have suggested that the way decisional tasks are executed
during the career decisional process may have consequences for
the implementation of that choice (e.g., Blustein et al., 1989;
Brisbin & Savickas, 1994; Gati & Asher, 2001; Harren, 1979;
Stumpf et al., 1983). Hence, further research on the interrelation-
ships among indecisiveness, career decisional tasks, and career
408 GERMEIJS, VERSCHUEREN, AND SOENENS
choice implementation will add to researchers’ understanding of
the impact of indecisiveness on making a career choice.
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Received October 26, 2005
Revision received March 25, 2006
Accepted March 28, 2006 䡲
410 GERMEIJS, VERSCHUEREN, AND SOENENS
