Select and read one of the following articles, located in the Topic 4 materials:

• The Role of Faculty Mentors in the Research Training of Counseling Psychology Doctoral Students
• The Career Development of Mexican American Adolescent Women: A Test of Social Cognitive Career Theory

Write a 500-750-word analysis of your selected article. Include the following in your analysis:

• What are the key differences between qualitative and quantitative research?
• What are the strengths and weaknesses of qualitative research designs?
• What are the essential components that should be considered when applying qualitative methods to counseling outcomes?

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.

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Course Code	Class Code	Assignment Title	Total Points
CNL-540	CNL-540-O500	Article Review (Obj. 4.2 and 4.4)	60.0
Criteria	Percentage	Unsatisfactory (0.00%)	Less Than Satisfactory (74.00%)	Satisfactory (79.00%)	Good (87.00%)	Excellent (100.00%)	Comments	Points Earned
Content	70.0%
Qualitative and Quantitative Research	30.0%	Essay omits or incompletely describes the key differences between qualitative and quantitative research. Essay does not demonstrate understanding of the topic.	Essay inadequately describes the key differences between qualitative and quantitative research and/or the discussion is not accurate. Essay demonstrates poor understanding of the topic.	Essay adequately describes the key differences between qualitative and quantitative research, but description is limited and lacks some evidence to support claims.Essay demonstrates a basic understanding of the topic.	Essay clearly describes the key differences between qualitative and quantitative research, and description is strong with sound analysis and some evidence to support claims.Essay demonstrates understanding that extends beyond the surface the topic.	Essay expertly describes the key differences between qualitative and quantitative research, and description is comprehensive and insightful with relevant evidence to support claims.Essay demonstrates an exceptional understanding of the topic.
Qualitative Research Design			20.0%	Essay omits or incompletely describes the strengths and weaknesses of qualitative research design. Essay does not demonstrate understanding of the topic.	Essay inadequately describes the strengths and weaknesses of qualitative research design and/or the discussion is not accurate. Essay demonstrates poor understanding of the topic.	Essay adequately describes the strengths and weaknesses of qualitative research design, but description is limited and lacks some evidence to support claims.Essay demonstrates a basic understanding of the topic.	Essay clearly describes the strengths and weaknesses of qualitative research design, and description is strong with sound analysis and some evidence to support claims.Essay demonstrates understanding that extends beyond the surface the topic.	Essay expertly describes the strengths and weaknesses of qualitative research design, and description is comprehensive and insightful with relevant evidence to support claims.Essay demonstrates an exceptional understanding of the topic.
Applying Qualitative Methods to Counseling Outcomes	Essay omits or incompletely describes the essential components that should be considered when applying qualitative methods to counseling outcomes. Essay does not demonstrate understanding of the topic.	Essay inadequately describes the essential components that should be considered when applying qualitative methods to counseling outcomes and/or the discussion is not accurate. Essay demonstrates poor understanding of the topic.	Essay adequately describes the essential components that should be considered when applying qualitative methods to counseling outcomes, but description is limited and lacks some evidence to support claims.Essay demonstrates a basic understanding of the topic.	Essay clearly describes the essential components that should be considered when applying qualitative methods to counseling outcomes, and description is strong with sound analysis and some evidence to support claims.Essay demonstrates understanding that extends beyond the surface the topic.	Essay expertly describes the essential components that should be considered when applying qualitative methods to counseling outcomes, and description is comprehensive and insightful with relevant evidence to support claims.Essay demonstrates an exceptional understanding of the topic.
Organization and Effectiveness
Thesis Development and Purpose	7.0%	Paper lacks any discernible overall purpose or organizing claim.	Thesis and/or main claim are insufficiently developed and/or vague; purpose is not clear.	Thesis and/or main claim are apparent and appropriate to purpose.	Thesis and/or main claim are clear and forecast the development of the paper. It is descriptive and reflective of the arguments and appropriate to the purpose.	Thesis and/or main claim are comprehensive. The essence of the paper is contained within the thesis. Thesis statement makes the purpose of the paper clear.
Argument Logic and Construction	8.0%	Statement of purpose is not justified by the conclusion. The conclusion does not support the claim made. Argument is incoherent and uses noncredible sources.	Sufficient justification of claims is lacking. Argument lacks consistent unity. There are obvious flaws in the logic. Some sources have questionable credibility.	Argument is orderly, but may have a few inconsistencies. The argument presents minimal justification of claims. Argument logically, but not thoroughly, supports the purpose. Sources used are credible. Introduction and conclusion bracket the thesis.	Argument shows logical progressions. Techniques of argumentation are evident. There is a smooth progression of claims from introduction to conclusion. Most sources are authoritative.	Clear and convincing argument that presents a persuasive claim in a distinctive and compelling manner. All sources are authoritative.
Mechanics of Writing (includes spelling, punctuation, grammar, language use)			5.0%	Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice and/or sentence construction are used.	Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) and/or word choice are present. Sentence structure is correct but not varied.	Some mechanical errors or typos are present, but are not overly distracting to the reader. Correct and varied sentence structure and audience-appropriate language are employed.	Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech.	Writer is clearly in command of standard, written, academic English.
10.0%
Paper Format (use of appropriate style for the major and assignment)	Template is not used appropriately or documentation format is rarely followed correctly.	Appropriate template is used, but some elements are missing or mistaken. A lack of control with formatting is apparent.	Appropriate template is used. Formatting is correct, although some minor errors may be present.	Appropriate template is fully used. There are virtually no errors in formatting style.	All format elements are correct.
Documentation of Sources (citations, footnotes, references, bibliography, etc., as appropriate to assignment and style)	Sources are not documented.	Documentation of sources is inconsistent or incorrect, as appropriate to assignment and style, with numerous formatting errors.	Sources are documented, as appropriate to assignment and style, although some formatting errors may be present.	Sources are documented, as appropriate to assignment and style, and format is mostly correct.	Sources are completely and correctly documented, as appropriate to assignment and style, and format is free of error.
Total Weightage	100%

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Record: 1

The role of faculty mentors in the research training of counseling
psychology doctoral students.
Hollingsworth, Merris A.. U Maryland, Counseling & Personnel
Services, MD, US, merrish@udel.edu
Fassinger, Ruth E.. U Maryland, Counseling & Personnel Services,
MD, US
Hollingsworth, Merris A., U Delaware, Ctr for Counseling & Student
Development, 261 Perkins Student Center, Newark, DE, US,
19716, merrish@udel.edu
Journal of Counseling Psychology, Vol 49(3), Jul, 2002. pp. 324-
330.
J Couns Psychol
US : American Psychological Association
US : Wm. C. Brown Co.
0022-0167 (Print)
1939-2168 (Electronic)
English
faculty mentors, research training, counseling psychology, doctoral
students, productivity, self-efficacy
This study investigated research mentoring experiences of
counseling psychology doctoral students as predictors of students’
research productivity. The authors also assessed the research
training environment and research self-efficacy as influences on
research productivity. Participants were 194 third- and fourth-year
counseling psychology doctoral students. Results indicated that the
research training environment predicted students’ research
mentoring experiences and their research self-efficacy. Both
research mentoring experiences and research self-efficacy
mediated the effect of the research training environment on
research productivity. Analyses showed no significant differences in
these relationships by student gender or scientific stature of training
programs. (PsycINFO Database Record (c) 2016 APA, all rights
reserved)
Journal Article
*Counseling Psychology; *Educational Program
Evaluation; *Mentor; *Postgraduate Training; *Teacher Student
Interaction; Counselor Education; Experimentation; Postgraduate

PsycINFO Classification:
Population:

Age Group:

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Format Covered:
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Release Date:
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Database:

Students; Self-Efficacy
Classroom Dynamics & Student Adjustment & Attitudes (3560)
Human
Male
Female
Adulthood (18 yrs & older)
Young Adulthood (18-29 yrs)
Thirties (30-39 yrs)
Middle Age (40-64 yrs)
Empirical Study
Print
Journal; Peer Reviewed Journal
Accepted: Oct 3, 2001; Revised: Oct 1, 2001; First Submitted: Nov
1, 2000
20060710
American Psychological Association. 2002
http://dx.doi.org.lopes.idm.oclc.org/10.1037/0022-0167.49.3.324
cou-49-3-324
2002-01965-005
36
APA PsycArticles

The Role of Faculty Mentors in the Research Training of Counseling Psychology Doctoral
Students

By: Merris A. Hollingsworth
Counseling and Personnel Services, University of Maryland;
Ruth E. Fassinger
Counseling and Personnel Services, University of Maryland
Acknowledgement: The data were collected by Merris A. Hollingsworth as part of her doctoral
dissertation.

Research training of counseling psychology doctoral students has received increased scrutiny in the last
2 decades. This scrutiny stems, in part, from the observation that few counseling psychologists conduct
research after completing their doctoral requirements despite training in a scientist-practitioner model
(Brems, Johnson, & Gallucci, 1996). Although research suggests that individual factors, such as
personality and interests, play a major role in research attitudes and productivity (e.g., Kahn & Scott,
1997; Krebs, Smither, & Hurley, 1991; Mallinckrodt, Gelso, & Royalty, 1990), theorists have also
proposed that the research training environment plays an influential role in shaping counseling
psychologists’ perceptions of research (Gelso, 1997).

To describe the role of the research training environment, Gelso (1997) has proposed and empirically
tested a model. The research training environment model hypothesizes nine themes central to research
training, which include (a) teaching students that all research is flawed, (b) teaching students to look
inward for research ideas, (c) helping students understand the connection between science and practice,
(d) teaching varied methodologies, (e) teaching statistics in ways that are relevant to research
applications, (f) faculty modeling of appropriate scientific behavior and attitudes, (g) providing positive
reinforcement of scientific activity, (h) involving students in research activities early in graduate training,
and (i) viewing participation in science as a partially social activity. A number of empirical studies have
indicated that the research training environment model describes critical elements that differentiate
between research training programs (Gelso, Mallinckrodt, & Judge, 1996; Kahn & Scott, 1997; Royalty,
Gelso, Mallinckrodt, & Garrett, 1986).

Studies also consistently show positive relationships between the research training environment,
students’ research self-efficacy, and students’ research productivity. For example, Krebs et al. (1991)
found a positive relationship between students’ perceptions of the research training environment and
subsequent research productivity. Investigations also supported positive relationships between the
research training environment and students’ research self-efficacy (Bishop & Bieschke, 1998; Phillips &
Russell, 1994). Further analyses suggested that research self-efficacy mediates the relationship between
the research training environment and students’ research productivity; that is, the training environment
affects productivity indirectly, through the influence of the training environment on students’ research self-
efficacy (Brown, Lent, Ryan, & McPartland, 1996; Kahn & Scott, 1997).

In addition, previous research suggests that student gender moderates the research training
environment, self-efficacy, and productivity relationship, with significantly different relationships existing
between these variables for men and for women. Specifically, Brown et al. (1996) found that research
self-efficacy had a significantly stronger effect on research productivity for male students than for female
students; in contrast, the research training environment had a greater direct effect on productivity for
female than for male students. Evidence from Kahn and Scott (1997) also supports student gender as a
possible moderator, with males reporting higher research self-efficacy than females.

The literature also supports expressed interest in research as a predictor of research productivity (Kahn &
Scott, 1997; Parker & Detterman, 1988; Royalty & Magoon, 1985). Although the research training
environment and research self-efficacy appear to influence students’ interest in research (Bishop &
Bieschke, 1998; Kahn & Scott, 1997), students also have had interest and experiences with scientific
inquiry that they developed prior to their doctoral program training (Gelso, 1997). Varied levels of prior
research interest reflect individual differences that students bring to their doctoral programs. Although
data have supported the effects of the research training environment in changing students’ level of
research interest (Mallinckrodt et al., 1990; Royalty et al., 1986), the extent to which prior levels of
research interest may influence students’ later research productivity is unclear.

Although mentoring is not a specific focus of the research training environment literature, faculty
mentoring emerges as a consistently important undercurrent in the research training environment. For

example, Gelso (1993) outlined specific faculty behaviors associated with good research-related
mentoring. In this description, faculty offer interpersonal reinforcement for research activity, express
enthusiasm for science and research, acknowledge the inevitability of flaws in research, expose students
to a variety of research methods, model a balance of science and practice, and use relationship skills that
communicate empathy, positive regard, and genuineness to students.

However, some researchers have critiqued research training environment theory in regard to mentoring,
suggesting that faculty mentoring should be a more explicit element of the research training environment.
For example, Hill (1997) compared the role of the faculty-student mentoring relationship in research
training to that of the working alliance between the counselor and the client, which prompted her
suggestion that the faculty-student mentoring relationship itself may be an essential ingredient in the
research training environment. Similarly, Mallinckrodt (1997) recommended a systemic perspective, in
which each advisor-student relationship is considered as a “micro-environment” that exists within the
larger contexts of a department and institution.

Other researchers have voiced similar support for the important role of mentors in research training,
although not within the specific context of the research training environment. For example, Royalty and
Reising’s (1986) data indicated that research activities involving interaction with role models or an advisor
were among the strongest positive influences on interest in research. O’Brien (1995) and Gelso (1997)
both noted that student responses to open-ended questions about critical incidents in their research
training often focused on their relationships with faculty members. Several studies suggest that faculty
modeling or mentoring in research activities corresponds with higher rates of research involvement and
productivity among psychology students and recent graduates (Cronan-Hillix, Gensheimer, Cronan-Hillix,
& Davidson, 1986; Galassi, Brooks, Stoltz, & Trexler, 1986; Krebs et al., 1991).

Despite these associations, no studies could be identified that focused specifically on research-related
mentoring in counseling psychology. The literature suggests that graduate students believe that having a
mentor is a critical component of graduate training (Atkinson, Neville, & Casas, 1991; Lark & Croteau,
1998; Luna & Cullen, 1998). Many psychology graduate students also appear to have mentors during
their training; two studies among this population found that more than half of respondents reported having
a mentor during their graduate work (Cronan-Hillix et al., 1986; Mintz, Bartels, & Rideout, 1995).
Furthermore, Atkinson et al. (1991) surveyed ethnic minority psychologists and found that respondents
recalled their faculty mentors’ encouragement related to research involvement as important and useful.

A few studies have investigated outcomes associated with research-related mentoring in other academic
disciplines. Green and Bauer’s (1995) study of doctoral students in the physical sciences showed little
relationship between research mentoring and students’ research productivity after controlling for
participants’ research interest prior to graduate school. In contrast, Cronan-Hillix et al. (1986) found a
significant relationship between receipt of mentoring and several measures of research productivity. The
lack of additional studies in academic settings that explore outcomes associated with mentoring contrasts
sharply with studies of mentoring in business settings, where measures such as rate of promotion, salary
increases, and job satisfaction are consistently correlated with receipt of mentoring (e.g., Bahniuk,

Dobos, & Kogler Hill, 1990; Bowen, 1985; Turban & Dougherty, 1994; for a more complete review of this
literature, see Noe, 1988a).

The current study extended the investigation of research training in counseling psychology by exploring
the role that faculty research mentoring plays in predicting student research productivity, above and
beyond the contributions of the research training environment, students’ research self-efficacy, and
students’ past research attitudes. Five research questions guided our work:

1. Does the research training environment predict students’ research mentoring experiences, their research self-
efficacy, or their research productivity?

2. Do students’ research mentoring experiences mediate the relationship between the research training
environment and productivity?

3. Do students’ self-efficacy beliefs mediate the influence of the research training environment on research
productivity?

4. Does controlling for students’ past attitudes toward research significantly change the relationships between
research training environment, self-efficacy, research mentoring, and research productivity?

5. Are relationships between these variables moderated by students’ gender or by the scientific stature of their
training program?

Method

Participants
Participants were 194 (135 women and 59 men) third- or fourth-year students enrolled in 25 APA-
approved counseling psychology programs. Only students working toward a PhD participated in the
study, and the response rate was 70%. The majority of the participants identified themselves as
European American (71%), and 12% identified as African American/Black, 5% as Hispanic/Latino/Latina,
4% biracial, 3.5% Asian American, 2% international students, and 1.5% unspecified. Ninety-five percent
of the respondents categorized themselves as third- or fourth-year doctoral students, whereas the
remaining 5% included second-, fifth-, and sixth-year students. The ages of the participants ranged from
23 to 58 years (M = 31.08 years, SD = 6.36 years). Participants from high and medium research
productivity programs comprised the majority of the sample (38% and 36%, respectively), with 26%
coming from low research productivity programs. More than half of the respondents (57.5%) indicated
that they currently participated in an active research team, and 72% considered themselves as currently
having a research mentor. Students who did not have a research mentor were instructed to “consider the
faculty relationship that has been most important in your research training while in your current doctoral
program” when answering questions.

Instruments
Independent variables

The research training environment was assessed by a modified version of the Research Training

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Environment Scale—Revised (RTES-R; Gelso et al., 1996). The original instrument contains nine
subscales measuring the following: teaching relevant statistics, facilitating students “looking inward” for
research ideas, teaching that all experiments are flawed and limited, focusing on varied investigative
styles, wedding science and clinical practice, faculty modeling of appropriate scientific behavior, faculty
reinforcement of student research, students’ early involvement in research, and science as a partly social
experience. Items ask students to rate their doctoral program in each of these areas. Test-retest
reliabilities for each subscale range from .74 to .94, and the subscales consistently correlate with
changes in research attitudes during graduate training and with research self-efficacy (Gelso et al.,
1996). The current study used a modified 16-item version of the RTES-R. First, the three items with the
highest factor loading on each subscale were selected for this study on the basis of factor analyses
conducted by Kahn and Gelso (1997), in which all items were forced to load on one of the nine
subscales. This step yielded an abbreviated version with 27 items. To avoid a potential problem of item
overlap between this instrument and the Research Mentoring scale (described below), we omitted 11
additional items from the RTE measure because they addressed the role of the faculty advisor (e.g., “I
feel that my faculty advisor expects too much from my research projects”). Participants responded on a 5-
point Likert scale ranging from 1 to 5, with higher numbers indicating a greater level of agreement with
each statement. Responses were added to yield a total score, with potential scores ranging from 16 to
80. Cronbach’s alpha for the RTE measure was .87 in the current study.

We measured research mentoring experiences with the Research Mentoring Experiences Scale (RMES),
a measure created for this study that is based on comparable instruments developed for business
settings (e.g., Noe, 1988b; Ragins & McFarlin, 1990). The RME included two subscales. The first
subscale, Psychosocial Mentoring, includes 13 items that explored the affective aspects of research
training, focusing on the personal elements of the relationship between faculty member and student.
Participants indicated the extent to which a specific faculty member expressed emotional support,
communicated respect and personal regard, and modeled positive attitudes toward research. The second
subscale, Career Mentoring, investigated faculty members’ efforts to help students acquire specific
information necessary to complete research tasks successfully. The 16 items on this subscale explored
faculty members’ teaching of research skills, giving advice, and providing research opportunities. For both
psychosocial and career mentoring, instructions asked respondents to rate their relationship with the
faculty member whom they considered most important in their current doctoral research training. Possible
responses ranged from 1 (faculty member pays very little attention to …) to 5 (faculty member pays a
great deal of attention to …). Responses to items were added and divided by the number of items to
generate a total score. Possible scores ranged from 1 to 5. The RMES was initially tested and revised in
a pilot study (n = 25); Cronbach’s alpha in the current study was .74.

Research self-efficacy, hypothesized as a second mediating variable, was measured by a shortened
version of the Self-Efficacy in Research Measure (SERM; Phillips & Russell, 1994). As previously
adapted by Kahn and Scott (1997), the shortened version of Phillips and Russell’s measure includes 12
items asking doctoral students to describe their confidence in applying four types of research-related
skills: research design, practical research skills, quantitative and computer skills, and writing skills. In this
study, participants indicated their responses on a 5-point Likert scale, ranging from 1 (no confidence) to 5

(total confidence). Each response was added to yield a total score, with potential scores ranging from 12
to 60. This instrument yielded high internal consistency (.90) in previous research (Kahn & Scott, 1997)
and in the current study (α = .87).

Past attitudes toward research was measured by the four items constructed by Royalty et al. (1986).
These items measured counseling psychology students’ recalled interest in conducting research prior to
their enrollment in the doctoral program. The items included the following: (a) “I would have preferred to
have the option of completing my doctoral training without being required to complete research projects”
(Preference), (b) “I had a strong interest in doing research” (Interest), (c) “I placed a high value on the
place of research in my future career” (Value), and (d) “Participating in research activities after graduation
was not a major priority for me” (Priority). Participants rated their level of agreement with each item, using
a 5-point Likert scale, which ranged from 1 (strongly disagree) to 5 (strongly agree), and the first and last
items were reverse-scored. Responses were added, then divided by the number of items to produce a
final score, with a potential range from 1 to 5. Previous research shows good internal consistency for the
scale, with alpha ranging from .87 to .90 (Gelso et al., 1996; Kahn & Scott, 1997; Royalty et al., 1986),
and the test-retest correlation for this measure was .93 (Royalty et al., 1986). Cronbach’s alpha in the
current study was .89.

Dependent variable

The dependent variable, research productivity, was assessed using Kahn and Scott’s (1997) 8-item
measure. These items provided a broad measure of students’ involvement in research-related activities,
including collection and analysis of data, development of manuscripts, participation in public
presentations, and attendance at research conventions (Kahn & Scott, 1997). Students responded to
each item by providing a number indicating the number of projects for which they are currently collecting
or analyzing data, the number of manuscripts they have completed or are now working on, and so forth.
Responses were summed to obtain a total number, with potential scores ranging from zero to infinity. The
current study yielded responses ranging from zero to 40, with a modal score of 6. Internal consistency
coefficients (K-R 20) for this scale ranged from .59 to .72 (Kahn & Scott, 1997), and in the current study
Cronbach’s alpha was .75 for this measure.

A demographic data form requested information about participants’ gender, race, year in doctoral
program, and age. Additional items asked if students were currently part of an active research team and if
they currently had a research mentor.

Procedure
The instruments for this study included a demographic form and a survey booklet with the scales
administered in the following sequence: Attitudes Toward Research, Research Productivity, Research
Training Environment, Research Self-Efficacy, and Research Mentoring Experiences. To incorporate
participants from training programs with varying levels of emphasis on research, the 63 currently active,
APA-accredited counseling psychology programs were stratified into three groups on the basis of their
scientific stature: high, medium, or low. An evaluation of counseling psychology doctoral programs based
on faculty research production (Hanish, et al., 1995) served as a guideline for each training program’s

designation within a category. Nine programs were selected from each category (high, medium, or low
scientific stature), with attention to geographical and institutional diversity. The researchers’ home
university was omitted from the participant pool to avoid potential bias. Three program directors declined
to participate, and only one replacement program could be identified on short notice, resulting in a
sample representing 25 programs: 9 high, 9 medium, and 7 low scientific stature training programs.

To identify participants, counseling psychology program directors were asked to provide names and
mailing addresses of third- and fourth-year doctoral students in the spring of 1998. Potential participants
(N = 278) received an advance postcard inviting their participation, followed by a mailed survey packet
and personalized cover letter 1 week later, accompanied by a stamped return envelope. Each survey
packet was numerically coded to permit accurate follow-up. As an incentive to participate, we included a
pencil with each test packet. To maximize the return rate, potential participants who had not yet returned
their survey received a reminder postcard 10 days after the mailing of the original survey, and a follow-up
letter and additional survey packet 2 weeks after the mailing of the reminder postcard. Nonrespondents
received one final request for participation by mail 2 weeks after the mailing of the second survey packet.
In addition, survey packets were distributed anonymously by two program directors who were unable to
release student names. No follow-up mailings were sent to these two sites. Overall, 200 students
responded. Data from 6 surveys were incomplete and could not be used; thus, the final number of
participants was 194.

Results

In preliminary analyses, we noticed strong positive skew on the Research Productivity scale. To manage
this difficulty, we used a logarithmic transformation to adjust each score, which yielded a more normal
distribution. The data in Table 1 and all subsequent analyses used the transformed productivity scores.
Means, standard deviations, and zero-order correlations for the five variables are indicated in Table 1.

Zero-Order Correlations, Means, and Standard Deviations of Variables

Multiple regression analyses were used to investigate the research questions. We used hierarchical
regression to investigate research mentoring experiences as a mediator of the research training
environment’s influence on students’ research productivity. According to Baron and Kenny (1986), several

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conditions are needed to support mediation: (a) the independent variable (training environment) must be
related to the mediator (mentoring), and (b) the independent variable (training environment) must be
related to the dependent variable (productivity). In addition, when the mediator (mentoring) and the
independent variable (training environment) are added, in subsequent steps, to a regression equation
predicting the dependent variable (research productivity), the regression coefficient for the independent
variable (training environment) should decrease when the effects of the mediator (mentoring) are
partialed out. Research mentoring would be considered a “perfect” mediator if the training environment
had no effect on productivity when mentoring is controlled (Baron & Kenny, 1986). The first two conditions
were supported by correlation coefficients (see Table 1), so we proceeded with a regression equation in
which research mentoring experiences was added in the first step, followed by research training
environment in the second step. This analysis supported research mentoring experiences as a mediator
(β = .45, p < .001) because the research training environment became a nonsignificant predictor of research productivity (β = −.03, p > .60).

Similarly, hierarchical regression was used to analyze research self-efficacy for a mediating effect
between the research training environment and research productivity. As above, the two preliminary
conditions were satisfied by correlation coefficients (i.e., training environment and self-efficacy were
related, and training environment and productivity were related). Regression supported the mediational
hypothesis: Research self-efficacy predicted research productivity (β = .36, p < .001), whereas the research training environment coefficient decreased (β = .07, p > .30) after self-efficacy was partialed out.

In a third analysis, we explored the role of research mentoring experiences and research self-efficacy
when we controlled for students’ past attitudes toward research. Past research attitudes was entered in
the first step of the hierarchical regression. Past research attitudes emerged and remained a significant
predictor of research productivity (β = .38, p < .001) despite the addition of research training environment, research mentoring experiences, and research self-efficacy to the regression equation. Although past research attitudes explained an additional 10% of students' research productivity, research mentoring experiences and research self-efficacy remained significant predictors (β = .38, p < .001, and β = .28, p < .001, respectively) of research productivity.

We tested student gender as a potential moderating variable of the relationships noted earlier with
additional regression equations. In the first hierarchical regression, we entered gender as a dummy
variable, followed by entry of the research training environment and research mentoring experiences in
subsequent steps. We then analyzed the two- and three-way interactions among these variables. A
significant interaction term would suggest that student gender acts as a moderator, affecting the strength
and/or direction of the relationship between the independent variables (Baron & Kenny, 1986). As Table 2
indicates, student gender was not a significant predictor of research productivity, and the two- and three-
way interaction terms with mentoring and the training environment also were not significant. We
completed a similar regression analysis with student gender, research self-efficacy, and the research
training environment and found no significant interaction effects. Similar analyses showed no significant
differences based on scientific stature of students’ programs (high, medium, or low) in the relationships
among research training environment, research mentoring, and research self-efficacy. Results are

reported in Table 2.

Summary of Hierarchical Regression Analyses Predicting Research Productivity

Discussion

This study built on previous research describing the research training environment and its effects on
counseling psychology doctoral students by addressing fundamental questions about students’ research
mentoring experiences as a potentially important addition to the research training environment. Previous
research supports the research training environment, research self-efficacy, and students’ past research
attitudes as predictors of students’ research productivity. The current study incorporated these
established variables and investigated research mentoring experiences as an additional influence on
productivity. Consistent with previous research, analyses supported the role of the research training
environment, research self-efficacy, and past research attitudes as direct predictors of productivity.

The data also suggested that students’ mentoring experiences serve as an important predictor of
research productivity, mediating the relationship between the research training environment and research
productivity. This finding supports recent assertions that faculty mentoring is a critical component within
the research training environment as a whole (e.g., Gelso & Lent, 2000; Hill, 1997) and provides
additional evidence that students’ experiences with faculty research mentors are important to students’

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development as researchers. The strong correlation between the research training environment and
research mentoring experiences supports the logical proposition that a strong research training
environment is most likely to promote strong research mentoring relationships. However, the mediating
role of research mentoring in the prediction of research productivity suggests that a research mentoring
relationship is the vehicle through which the training environment has greatest impact on individual
students’ research production. If this is the case, then working to improve student-faculty research
mentoring may be an important step toward promoting greater research productivity among counseling
psychology doctoral students.

Students’ research self-efficacy served as another mediator between the research training environment
and research productivity. This result supports earlier findings by Brown et al. (1996) that the training
environment influences productivity indirectly through its effects on students’ self-efficacy.

When we controlled for students’ past attitudes toward research, students’ mentoring experiences and
research self-efficacy remained as influential predictors of research productivity. Although this finding
supports the importance of individual differences that students bring to their doctoral programs, it also
underscores the effects of environmental and interpersonal factors, such as mentoring relationships and
research self-efficacy, during doctoral training. Although one may argue that students who enter a training
program with high research interest are more likely to seek research mentoring and to develop research
self-efficacy, these data suggest that environmental interventions to support research mentoring and
development of students’ research self-efficacy have effects exceeding those associated solely with
students’ past level of interest. This result supports earlier suggestions (e.g., Gelso, 1997) that
environmental interventions may play a decisive part in promoting student research activity.

Participants’ gender did not significantly influence these relationships among the variables of interest.
This outcome diverges from results of previous research, which showed male students experiencing
research self-efficacy as a greater influence on research productivity than their female peers (e.g., Brown
et al., 1996). The absence of significant findings by gender for research self-efficacy in the current study
may reflect restricted range in participants’ responses because we used a 5-point scale for research self-
efficacy responses, compared with the 10-point scale used in the earlier studies (Brown et al., 1996;
Kahn & Scott, 1997). Our results also showed no difference by gender in the effects of the research
training environment on productivity, contrasting with a previous study (Brown et al., 1996). Although the
abbreviated version of the research training environment measure used in our study was based on earlier
work (Gelso et al., 1996; Kahn & Gelso, 1997) and showed internal consistency comparable to the full
scale, perhaps the smaller number of items limited the range of participant responses, leading to no
effects by gender. However, the lack of significant effects by gender in our study also may reflect changes
that have occurred in many counseling psychology training programs because the data for Brown et al.’s
analyses were collected in the early 1990s. As many training programs have experienced an influx of
female students, perhaps the research training environments have shifted, leading to fewer differences in
the research training experiences of men and women. Because not many published studies have
analyzed participant gender and our findings conflict with earlier work, these results highlight the critical
need for investigation of potential differences and similarities by gender in future research.

Our analyses also showed no differences between male and female students in the effects of research
mentoring on productivity. This result suggests that mentoring plays an equally important role for
students, regardless of gender; however, this finding should be interpreted cautiously given the absence
of prior work in this area. As above, we note the importance of further research, with attention to possible
differences in the relationships between variables as a function of student gender.

We also investigated potential differences in the effects of the training environment, mentoring, and
research self-efficacy on research productivity by the scientific stature of participants’ training programs.
The absence of significant differences suggests that these variables function similarly to support research
productivity in all counseling psychology doctoral programs, regardless of the scientific stature of the
program. This result should be considered preliminary because other studies have not used a
comparable stratification system in selecting programs to sample. However, if supported by further study,
this finding lends support to the universality of the research training environment, research mentoring,
and research self-efficacy as constructs that are fundamental components of the research training
process.

Strengths and Limitations
This study has several strengths that underscore its value to counseling psychology. This work provides a
conceptual bridge linking two areas—the research training environment and mentoring relationships—
that had not yet been combined empirically. The research demonstrates that linking these two areas is
critically important in understanding the research training process. The extent of the sampling and the
high return rate support the generalizability of these findings to upper level doctoral students in
counseling psychology. Our study also generates numerous questions for further research.

Several limitations also must be considered in interpreting these results. First, the data collected were
cross-sectional and correlational. Thus, perceptions of past research interest were based on participants’
recollections, which easily may be blurred by current experiences. In addition, mentoring relationships,
like most relationships, are likely to change over time. For example, a student in the early stages of
developing a mentoring relationship is likely to have a different perspective than when the relationship is
well established. Similarly, a student who has a long history with a specific mentor may find their
relationship becoming more collegial as the student approaches the status of a professional peer. Relying
on cross-sectional data provides only a brief snapshot of students’ experiences, which may result in
omission of important information. A future study that incorporated a longitudinal design could address
some of these concerns.

Second, the measures relied solely on self-report by student participants. The data did not corroborate
students’ perceptions of their research training environment, research productivity, or their mentoring
relationships from additional sources. Additional research would greatly benefit from study of paired
observations regarding these variables, for example, comparisons of student and faculty mentor
responses. Furthermore, the study design and accompanying analyses assume independence among
respondents. Despite random sampling of training programs, clusters of respondents were enrolled in the
same doctoral program and shared the same research training environment. Consequently, one might

find some homogeneity within clusters, based on students having met similar admission criteria and
selecting the same research training program environment (Kish, 1965). Lack of independence may
magnify the relationships between variables. This problem could be corrected by conducting analyses at
the program level; however, the sample size in this study was insufficient to support this level of analysis.

Finally, the absence of established measures to explore mentoring relationships prompted use of a new,
unproven instrument to assess psychosocial mentoring in this study. Although the measure was revised
on the basis of pilot study data and achieved an adequate measure of reliability in this study, the data
should be regarded with some caution given the lack of established reliability and validity evidence for
this instrument. This limitation points clearly to the need for more instrument development in the study of
academic mentoring relationships. In addition, the research training environment measure was greatly
abbreviated from Gelso et al.’s (1996) original version. Although an adequate reliability coefficient was
obtained for the measure used in this study, results should be interpreted with the awareness that this
abbreviated version is not an established use of this scale.

Implications for Research and Practice
This study suggests a number of avenues for further research. Additional research is warranted to
explore the role of faculty mentoring within the research training environment and as a contributor to
students’ research productivity. Consistent with this suggestion, further efforts to develop and refine
instruments to assess faculty mentoring are particularly needed. Several well-established instruments to
describe mentoring exist in business settings, but few attempts have been made to create comparable
measures for academic settings. This study focused exclusively on dyadic mentoring relationships
between faculty and students. Additional research could investigate the effects of group mentoring, such
as that received through research team experiences or peer mentoring by research-oriented classmates.
In addition, specific models of mentoring, such as feminist mentoring (Fassinger, 1997), could be
explored to investigate aspects of mentoring approaches, such as traditional, hierarchical approaches
versus more collaborative styles. It is also important to note that methodological diversity is needed in
both the research training environment and mentoring literatures, incorporating methods that permit
longitudinal assessment of change. Methodological diversity should include a wider range of perspectives
than self-report by students and use both quantitative and qualitative approaches. Further exploration of
potential similarities and differences in the research training environment and students’ research self-
efficacy by gender are also needed, particularly as training programs begin to reflect greater numbers of
female faculty and female students.

Because this study applies specifically to the interactions of doctoral students and faculty, the implications
for practical application are tailored to those who learn and teach in doctoral training programs. For
prospective doctoral students, the results suggest that students who value research training should
explore the research training environment of programs they are considering because the overall research
training environment influences individual research mentoring relationships and development of research
self-efficacy beliefs. At the same time, students also need to consider the person variables (e.g., past
level of research interest) that they bring to their research training as a way to dispel possible
expectations that the “right” mentor can create high levels of research interest, self-efficacy, or

productivity. For faculty, the results offer some encouragement that efforts to mentor students’ research
development are associated with greater research productivity among students. At a more systemic level,
the data invite consideration of the research training environment and mentoring activities at the program
and departmental level. Training programs that value research may benefit from discussion about the
extent to which faculty feel supported in their efforts to be research mentors. Faculty discussions of
mentoring may also encourage sharing of strategies or collaborative efforts, which may decrease the
likelihood that some faculty will bear a disproportionate burden for research mentoring of students. This
type of discussion may also encourage faculty to explore ways that they can manage elements of the
mentoring relationships that seem particularly burdensome. Because the research training environment
contributes to students’ research self-efficacy, faculty in training programs may also wish to consider
specific ways in which they, individually and collectively, nurture research self-efficacy among their
students. Faculty also may wish to help their own students who plan on careers in academe develop their
own skills as research mentors. For example, helping advanced doctoral students organize and direct
their own research team, composed of undergraduate students and graduate peers, provides an
opportunity to develop research self-efficacy, receive research mentoring, and begin developing skills as
a future research mentor.

In summary, this study suggests that research mentoring experiences make a notable contribution to
students’ research productivity. We encourage further innovation, collaboration, and evaluation in this
area to promote continued development of scientist-practitioners in counseling psychology.

References
Atkinson, D. R., Neville, H., & Casas, A. (1991). The mentorship of ethnic minorities in professional
psychology. Professional Psychology: Research and Practice, 22, 336–338.

Bahniuk, M. H., Dobos, J., & Kogler Hill, S. E. (1990). The impact of mentoring, collegial support, and
information adequacy on career success: A replication. Journal of Social Behavior and Personality, 5,
431–451.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological
research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social
Psychology, 51, 1173–1182.

Bishop, R. M., & Bieschke, K. J. (1998). Applying social cognitive theory to interest in research among
counseling psychology doctoral students: A path analysis. Journal of Counseling Psychology, 45, 182–
188.

Bowen, D. D. (1985). Were men meant to mentor women?Training and Development Journal, 39, 31–34.

Brems, C., Johnson, M. E., & Gallucci, P. (1996). Publication productivity of clinical and counseling
psychologists. Journal of Clinical Psychology, 52, 723–725.

Brown, S. D., Lent, R. W., Ryan, N. E., & McPartland, E. B. (1996). Self-efficacy as an intervening

https://web-a-ebscohost-com.lopes.idm.oclc.org/ehost/delivery?sid=af34111b-b0a3-49e6-bb92-f7a196cf33ff@sessionmgr4008&vid=2&ReturnUrl=https://web.a.ebscohost.com/ehost/pdfviewer/pdfviewer?vid=1&sid=af34111b-b0a3-49e6-bb92-f7a196cf33ff%2540sessionmgr4008%23toc

mechanism between research training environments and scholarly production: A theoretical and
methodological extension. Counseling Psychologist, 24, 535–544.

Cronan-Hillix, T., Gensheimer, L. K., Cronan-Hillix, W. A., & Davidson, W. S. (1986). Students’ view of
mentors in psychology graduate training. Teaching of Psychology, 13(3), 123–127.

Fassinger, R. E. (1997, August). Dangerous liasions: Reflections on feminist mentoring.Paper presented
at the 105th Annual Convention of the American Psychological Association, Chicago, IL.

Galassi, J. P., Brooks, L., Stoltz, R. F., & Trexler, K. A. (1986). Research training environments and
student productivity: An exploratory study. Counseling Psychologist, 14, 31–36.

Gelso, C. J. (1993). On the making of a scientist-practitioner: A theory of research training in professional
psychology. Professional Psychology: Research and Practice, 24, 468–476.

Gelso, C. J. (1997). The making of a scientist in applied psychology: An attribute by treatment
conception. Counseling Psychologist, 25, 307–320.

Gelso, C. J., & Lent, R. W. (2000). Scientific training and scholarly productivity: The person, the training
environment, and their interaction. In S.D Brown & R. W.Lent (Eds.), Handbook of counseling psychology
(3rd ed., (pp. 109–139). New York: Wiley.

Gelso, C. J., Mallinckrodt, B., & Judge, A. B. (1996). Research training environment, attitudes towards
research, and research self-efficacy: The Revised Research Training Environment Scale. Counseling
Psychologist, 24, 304–322.

Green, S. G., & Bauer, T. N. (1995). Supervisory mentoring by advisers: Relationships with doctoral
student potential, productivity, and commitment. Personnel Psychology, 48, 537–561.

Hanish, C., Horan, J. J., Keen, B., St. Peter, C. C., Ceperich, S. D., & Beasley, J. F. (1995). The scientific
stature of counseling psychology training programs: A still picture of a shifting scene. Counseling
Psychologist, 23, 82–101.

Hill, C. E. (1997). The effects of my research training environment: Where are my students now?
Counseling Psychologist, 25, 74–81.

Kahn, J. H., & Gelso, C. G. (1997). Factor structure of the Research Training Environment Scale—
Revised: Implications for research training in applied psychology. Counseling Psychologist, 25, 22–37.

Kahn, J. H., & Scott, N. A. (1997). Predictors of research productivity and science-related career goals
among counseling psychology doctoral students: A structural equation analysis. Counseling Psychologist,
25, 38–67.

Kish, L. (1965). Survey sampling. New York: Wiley.

Krebs, P. J., Smither, J. W., & Hurley, R. B. (1991). Relationship of vocational personality and research
training environment to research productivity of counseling psychologists. Professional Psychology:
Research and Practice, 22, 362–367.

Lark, J. S., & Croteau, J. M. (1998). Lesbian, gay, and bisexual doctoral students’ mentoring relationships
with faculty in counseling psychology: A qualitative study. Counseling Psychologist, 20, 754–777.

Luna, G., & Cullen, D. (1998). Do graduate students need mentors?College Student Journal, 32, 322–
331.

Mallinckrodt, B. (1997). Discovering research training environments that fit the students we select: The
challenge of providing for diverse needs. Counseling Psychologist, 25, 68–73.

Mallinckrodt, B., Gelso, C. J., & Royalty, G. M. (1990). Impact of the research training environment and
counseling psychology students’ Holland personality type on interest in research. Professional
Psychology: Research and Practice, 21, 26–32.

Mintz, L. B., Bartels, K. M., & Rideout, C. A. (1995). Training in counseling ethnic minorities and race-
based availability of graduate school resources. Professional Psychology: Research and Practice, 26,
316–321.

Noe, R. A. (1988a). Women and mentoring: A review and research agenda. Academy of Management
Review, 13, 65–78.

Noe, R. A. (1988b). An investigation of the determinants of successful assigned mentoring relationships.
Personnel Psychology, 41, 457–479.

O’Brien, K. M. (1995). Enhancing research training for counseling students: Interuniversity collaborative
research teams. Counselor Education and Supervision, 34, 187–198.

Parker, L. E., & Detterman, D. K. (1988). The balance between clinical and research interests among
Boulder model graduate students. Professional Psychology: Research and Practice, 19, 342–344.

Phillips, J. C., & Russell, R. K. (1994). Research self-efficacy, the research training environment, and
research productivity among graduate students in counseling psychology. Counseling Psychologist, 22,
628–641.

Ragins, B. R., & McFarlin, D. G. (1990). Perceptions of mentor roles in cross-gender mentoring
relationships. Journal of Vocational Behavior, 37, 321–339.

Royalty, G. M., Gelso, C. J., Mallinckrodt, B., & Garrett, K. (1986). The environment and the student in
counseling psychology: Does the research training environment influence graduate students’ attitudes
towards research?Counseling Psychologist, 14, 9–30.

Royalty, G. M., & Magoon, T. M. (1985). Correlates of scholarly productivity among counseling

psychologists. Journal of Counseling Psychology, 32, 458–461.

Royalty, G. M., & Reising, G. N. (1986). The research training of counseling psychologists: What the
professionals say. Counseling Psychologist, 14, 49–60.

Turban, D. B., & Dougherty, T. W. (1994). Role of protege personality in receipts of mentoring and career
success. Academy of Management Journal, 37, 688–702.

Submitted: November 1, 2000 Revised: October 1, 2001 Accepted: October 3, 2001

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Source: Journal of Counseling Psychology. Vol. 49. (3), Jul, 2002 pp. 324-330)
Accession Number: 2002-01965-005
Digital Object Identifier: 10.1037/0022-0167.49.3.324

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Record: 1

The career development of Mexican American adolescent women:
A test of social cognitive career theory.
Flores, Lisa Y.. Ohio State U, Dept of Psychology, Columbus, OH,
US, flores.60@osu.edu
O’Brien, Karen M.
Flores, Lisa Y., Ohio State U, Dept of Psychology, 1885 Neil Avenue
Mall, Columbus, OH, US, 43

2

10-1222, flores.60@osu.edu
Journal of Counseling Psychology, Vol 49(1), Jan, 2002. pp. 14-27.
J Couns Psychol
US : American Psychological Association
US : Wm. C. Brown Co.
0022-0167 (Print)
1939-2168 (Electronic)
English
career choice model, Mexican American adolescent women,
contextual variables, social cognitive variables, career aspiration,
prestige, traditionality, feminist attitudes, predictors
This study tested R. W. Lent, S. D. Brown, and G. Hackett’s (1994)
model of career choice with 364 Mexican American adolescent
women. Path analyses were run to determine the influence of
contextual and social cognitive variables on career aspiration,
career choice prestige, and traditionality. Partial support for the
model was evidenced as nontraditional career self-efficacy, parental
support, barriers, acculturation, and feminist attitudes predicted
career choice prestige. Acculturation, feminist attitudes, and
nontraditional career self-efficacy predicted career choice
traditionality. Feminist attitudes and parental support predicted
career aspiration. The paths between nontraditional career interests
and the 3 outcome variables were not supported. Finally, none of
the background contextual variables in this study predicted
nontraditional career self-efficacy. Implications of the results and
suggestions for future research are discussed. (PsycINFO
Database Record (c) 2016 APA, all rights reserved)
Journal Article
*Mexican Americans; *Occupational Aspirations; *Occupational
Choice; *Occupational Success Prediction; *Sociocultural
Factors; Models

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Population:

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Occupational Interests & Guidance (3610)
Human
Female
US
Adolescence (13-17 yrs)
Empirical Study
Print
Journal; Peer Reviewed Journal
Accepted: Mar 21, 2001; Revised: Mar 19, 2001; First Submitted:
Feb 2, 2000
20060710
American Psychological Association. 200

2

http://dx.doi.org.lopes.idm.oclc.org/10.1037/0022-0167.49.1.14
cou-49-1-14
2001-05923-002
APA PsycArticles

The Career Development of Mexican American Adolescent Women: A Test of Social
Cognitive Career Theory

By: Lisa Y. Flores
Department of Psychology, The Ohio State University;
Karen M. O’Brien
Department of Psychology, University of Maryland, College Park
Acknowledgement: This study was based on the doctoral dissertation of Lisa Y. Flores, which was
conducted under the direction of Michael J. Patton. An earlier version of this article was presented at the
108th Annual Convention of the American Psychological Association, Washington, DC, August 2000.

We thank Nancy Betz, Mary Heppner, and Fred Leong for helpful feedback on earlier versions of this
article; Kristopher Preacher and Robert MacCallum for statistical consultation; Jamilla Griffin and Jason
Quarantillo for assistance with coding data; and the students, teachers, counselors, and administrators of
the participating schools.

Mexican American women constitute a significant portion of the American population (U.S. Bureau of the
Census, 1996), are underrepresented at all levels of education (Carter & Wilson, 1993; Lango, 1995;
McNeill et al., 2001; U.S. Bureau of the Census, 1991), and are overrepresented in low-paying
occupations traditionally occupied by women (Arbona, 1989; Arbona & Novy, 1991; Ortiz, 1995).
Relatively little empirical research has been conducted to identify the variables that contribute to the
educational and occupational underachievement of Mexican American women. Indeed, researchers have
noted that the career development of Hispanics has received only slight consideration in the counseling

and vocational literature (Arbona, 1990; Fouad, 1995; Hoyt, 1989; McNeill et al., 2001), and they have
questioned the generalizability of career development theories to Hispanics (Arbona, 1990, 1995;
Fitzgerald & Betz, 1994; Hackett, Lent, & Greenhaus, 1991). The purpose of this study was to investigate
the applicability of a current model of career choice to the experiences of Mexican American adolescent
women and to extend the current model to incorporate variables that are hypothesized to be salient to this
population.

It is well documented that Hispanics are the least educated when compared with other major racial/ethnic
groups in the United States and that, among Hispanics, Mexican Americans have the lowest high school
and college completion rates (47% and 6.5%, respectively; U.S. Bureau of the Census, 1996). Mexican
American women are less likely to graduate from college than their male counterparts (Ortiz, 1995;
Tinajero, Gonzalez, & Dick, 1991), and their representation in higher education decreases significantly at
each successive level (Carter & Wilson, 1993). Moreover, those Mexican American women who pursue
higher education confront many stressors and may experience psychological distress as they seek to
reconcile their career aspirations with their familial and cultural values (Niemann, 2001).

Education is related to occupational status, and thus, the restricted employment status among Mexican
American women is not surprising given their low educational attainment. Arbona (1989) reported that,
occupationally, Hispanic women were concentrated in low and mid-level technical, service-oriented, and
clerical type jobs. According to Ortiz (1995), Mexican American women were less likely to be
professionals or private business owners and earned less money when compared with women from other
racial/ethnic groups and Mexican American men. Moreover, Mexican American women who were in
professional occupations were more likely to choose traditional and low-status occupations (Ortiz, 1995).

A review of the literature on Mexican American women revealed inconsistencies between their
educational and vocational achievements and aspirations. For example, Arbona and Novy (1991)
reported that the majority of Mexican American college women in their study aspired to investigative and
enterprising type jobs. It is interesting that the percentage of women who expected to enter these fields
was smaller than the percentage of women who aspired to these careers, whereas the opposite was true
of those who aspired and expected to enter fields that have typically represented traditional career
options for women. Other studies revealed that Mexican American girls aspired to careers that required a
college degree and to obtaining a postsecondary education (Hernandez, Vargas-Lew, & Martinez, 1994;
Valenzuela, 1993). Reyes, Kobus, and Gillock’s (1999) study indicated that 87% of the girls in a sample of
predominantly Mexican American 10th-grade students aspired to nontraditional or male-dominated
careers. Clearly, a difference exists between Mexican American women’s educational and vocational
aspirations and their actual achievements, suggesting that these women may not be realizing their
educational and career potential.

Prior studies on the career development of Hispanics have focused primarily on their educational and
career aspirations (Arbona & Novy, 1991; Hernandez et al., 1994; Reyes et al., 1999) and the factors
postulated to be related to their educational success (Cardoza, 1991; Fisher & Padmawidjaja, 1999;
Gandara, 1982; Gillock & Reyes, 1999; Hess & D’Amato, 1996; Keith & Lichtman, 1994; Lango, 1995;

Ramos & Sanchez, 1995; Rodriguez, 1996; Valenzuela, 1993; Vasquez, 1982; Wycoff, 1996). Other
studies have examined the barriers that Hispanic students anticipate in their educational and career
endeavors (Luzzo, 1992; McWhirter, 1997). The research to date provides insight into the career
development of Hispanic individuals but contains limitations that restrict its use.

First, several studies are descriptive in nature, and while helpful in understanding patterns of behavior
with this group, they do not further knowledge regarding the salient predictors of career behaviors.
Second, several studies included racially/ethnically diverse samples (in which the number of Hispanics
were disproportionately small) or failed to report the ethnic background of Hispanic participants. Because
of the educational and occupational differences between racial/ethnic groups and among Hispanics,
investigating ethnically diverse subgroups individually seems warranted (Arbona, 1995). Another
limitation of the existing studies is that many included both women and men. Given differences in Mexican
American women’s and men’s educational attainment, occupational status, and socialization within the
culture, women and men should be investigated separately to understand the effects of cultural and
gender role socialization on career decisions. Finally, few studies have assessed the influence of cultural
variables, such as acculturation, on Hispanics’ career-related behaviors (Arbona, 1995).

One notable exception to the research described above was a study investigating the educational plans
and career expectations of Mexican American high school girls (McWhirter, Hackett, & Bandalos, 1998).
McWhirter and her colleagues studied the utility of Farmer’s (1985) model of career commitment and
aspirations in explaining the educational planning and career expectations of Mexican American
adolescent women. They extended Farmer’s model by including acculturation and perceived barriers in
their theoretical models. The results of this study indicated that their models described the educational
and career plans of a sample of Mexican American girls; however, only a modest amount of variance was
accounted for by the models. Thus, McWhirter et al. encouraged researchers to include additional
variables when developing future models of the career development of Mexican American adolescent
women. Moreover, McWhirter et al. suggested that Lent, Brown, and Hackett’s (1994) social cognitive
career theory had promise for advancing knowledge regarding the career development of Mexican
American women.

Lent and his colleagues (Lent et al., 1994) extended Bandura’s (1986) social cognitive theory and Hackett
and Betz’s (1981) career self-efficacy theory to develop a social cognitive career theory (SCCT) that
hypothesized the influence of personal, contextual, and social cognitive factors on interest formation,
career goals, and performance. Of interest in this study are the propositions of SCCT that background
contextual variables exert an influence on career self-efficacy, which in turn directly influences career
interests. In addition, Lent et al. posited that career interests directly influence career goals and that
career self-efficacy both directly and indirectly (through career interests) influences career goals. Finally,
proximal contextual variables were hypothesized to exert direct effects on career goals (see Figure 1).
Lent and his colleagues suggested that SCCT may be used to guide inquiry on the career development of
women and racial/ethnic minorities, and they recently advocated for more research to test the hypotheses
related to the contextual variables in their model (Lent, Brown, & Hackett, 2000). Recent studies provided
partial support for the model with racially diverse middle school students (Fouad & Smith, 1996) as well

as Asian American (Tang, Fouad, & Smith, 1999) and Black college students (Gainor & Lent, 1998);
however, no studies to date have investigated the validity of SCCT with Mexican American adolescent
women.

Figure 1. Portions of Lent, Brown, and Hackett’s (1994) model of career choice tested in the present study

To test this theory, when operationalizing the constructs advanced by Lent et al. (1994), we selected
variables that were hypothesized to be salient for racial/ethnic minorities or women. Specifically, in our
model, we operationalized background contextual variables to include acculturation level, feminist
attitudes, and mothers’ modeling through educational attainment and occupation. Multicultural
researchers have identified the importance of examining within-group differences of racial and ethnic
subgroups, and Casas and Pytluk (1995) discussed acculturation as one variable that differentiates
Hispanic subgroups or individuals within a subgroup. Moreover, McWhirter et al. (1998) noted that
acculturation was the only variable that they added to Farmer’s (1985) model that accounted for
significant variance in the educational aspirations of Mexican American girls. Other researchers also
documented that acculturation was positively related to educational aspirations (Ramos & Sanchez,
1995), in addition to interest in nontraditional careers (Reyes et al., 1999), college attendance (Hurtado &
Gauvain, 1997), and achievement styles (Gomez & Fassinger, 1994) among Hispanic students.

Other variables, specifically feminist and gender role attitudes, have been shown to relate to the career
choices of young women (Betz, 1994; O’Brien & Fassinger, 1993), such that women with traditional
gender role attitudes exhibited lower levels of career orientation and aspiration than women holding
liberal gender role attitudes. Among Mexican American girls, nontraditional gender role attitudes were
positively related to higher levels of educational and career expectations (McWhirter et al., 1998) and
academic achievement (Valenzuela, 1993; Vasquez-Nuttal, Romero-Garcia, & De Leon, 1987). For
Mexican American women, cultural expectations about gender roles may result in traditional gender role
attitudes or nonfeminist attitudes (Ginorio, Gutierrez, Cauce, & Acosta, 1995; Reid, Haritos, Kelly, &
Holland, 1995), which in turn may contribute to lower levels of career achievement.

In addition, parental factors, such as occupation and educational level, were found to relate to academic
achievement and parental involvement in Mexican American students’ educational and career planning

(Keith & Lichtman, 1994). With regard to the influence of mothers, having a mother who attended college
was predictive of college attendance and persistence among Latinas (Cardoza, 1991). However, other
studies that assessed the role of parents’ educational or occupational attainment in children’s educational
and career aspirations reported no relation (Fisher & Padmawidjaja, 1999; Hernandez et al., 1994; Hess
& D’Amato, 1996; Lango, 1995; Reyes et al., 1999), possibly because of the highly skewed number of
parents with lower educational and occupational levels in these samples. The influence of mothers’
educational level and occupational traditionality were included in the present study to determine their
influence on daughters’ career development.

According to SCCT, these background variables were hypothesized to influence nontraditional career
self-efficacy or confidence in pursuing nontraditional career-related tasks for women (Lent et al., 1994). In
turn, nontraditional career self-efficacy should exert a direct effect on both nontraditional career interests
and career goals (i.e., career choice prestige, career choice traditionality, and career aspirations). Indeed,
these relations have been supported in prior studies, which reported that career self-efficacy was related
to career interests and careers considered among Hispanic students (Bores-Rangel, Church, Szendre, &
Reeves, 1990; Church, Teresa, Rosebrook, & Szendre, 1992; Lauver & Jones, 1991). In addition,
research has shown that career interests were related to careers considered among Hispanic students
(Bores-Rangel et al., 1990; Church et al., 1992). These findings were consistent with SCCT, which
posited a direct link between career interests and career goals.

We also hypothesized, in accordance with SCCT (Lent et al., 1994), that the proximal contextual variables
of perceived support from parents and perceptions of barriers will influence career choice prestige,
traditionality, and career aspirations. Among Latinas, encouragement and emotional support from families
have been found to be predictive of educational achievement (Hernandez et al., 1994; Keith & Lichtman,
1994; Ramos & Sanchez, 1995) and college attendance (Vasquez, 1982; Wycoff, 1996). With regard to
perceived barriers, Hispanic students reported experiencing more barriers to education than students
from other racial/ethnic groups (Luzzo, 1992; McWhirter, 1997), and Mexican American women who
experienced negative family attitudes related to their college attendance were more likely to attend
college close to home (Wycoff, 1996). McWhirter et al. (1998) found no relation among perceived barriers
and Mexican American girls’ educational or career plans. However, they suggested that the influence of
perceived barriers on academic and vocational goals be further tested with additional samples. It is
possible that Mexican American adolescent women’s increased levels of perceived barriers to their
educational or career goals may alter their decision making, such that they plan to pursue careers that
present the least resistance.

In summary, this study was designed to test several tenets of SCCT (Lent et al., 1994) with a sample of
Mexican American adolescent women. Specifically, we explored the influence of background contextual
variables, namely, acculturation level, feminist attitudes, mother’s educational level, and mother’s
occupational traditionality on nontraditional career self-efficacy. Additionally, we investigated the
contributions of nontraditional career self-efficacy, nontraditional career interests, parental support, and
perceived barriers to career choice prestige, career choice traditionality, and career aspirations. These
dependent variables were selected because of their importance to women’s career development

(Fitzgerald, Fassinger, & Betz, 1995; O’Brien & Fassinger, 1993). A secondary purpose of this study was
to obtain descriptive information regarding participants’ demographic characteristics, career choices,
plans following high school graduation, choice of colleges/universities, and reasons for choosing these
schools, given the lack of data regarding this population and their career plans.

Method

Participants
Participants were Mexican American adolescent women enrolled in their senior year of high school. At the
same time, Mexican American adolescent men were surveyed for a later study. Participants were drawn
from two large public high schools in a mid-sized town (a population of approximately 30,000) in south
Texas. The community is close to the United States–Mexican border and is heavily influenced by the
Mexican culture. A high percentage of U.S. citizens who are of Mexican descent live in this area, and this
is reflected in the student population at the high schools, in which almost 95% of the students are
Mexican American.

A total of 931 surveys were distributed to students; 831 were returned (450 female, 381 male), resulting in
an 89% overall return rate. Women who were in their senior year of high school and who identified as
Mexican American were included in this study (n = 377). Of these women, 13 were dropped from the
study because of incomplete data, resulting in a total sample of 364. Participants ranged in age from 16
to 21 years with a mean age of 17.47 (SD = 0.70). The average number of people living at home was
4.83 (SD = 1.71; range = 2 to 13).

Eighteen percent of the students (n = 65) reported that they were first-generation Mexican American, with
37.9% (n = 138) second generation, 11.3% (n = 41) third generation, 19.2% (n = 70) fourth generation,
and 10.7% (n = 39) fifth generation. With regard to acculturation level, 17% (n = 61) were categorized as
“very Mexican oriented,” 38% (n = 138) “Mexican oriented to approximately balanced bicultural,” 34% (n =
123) “slightly Anglo oriented bicultural,” 10% (n = 37) “strongly Anglo oriented,” and 1% (n = 5) “very
assimilated, Anglicized.”

The educational level of the female and male head of household, respectively, was as follows: completed
elementary school, 24% and 21%; attended high school, 25% and 23%; high school graduate, 19% and
21%; attended college/university, 14% and 12%; college/university graduate, 10% and 12%; and graduate
or professional degree, 2% and 1%.

Eighty-seven percent (n = 317) of the students planned to attend a 2- or 4-year college/university
following their high school graduation, with the remaining students indicating plans to attend technical
school (5.5%), work (3.2%), enlist in the military (2.1%), and marry or stay at home (0.5%). Among
students with intentions to continue their education at a 2- or 4-year college/university, almost half (43.2%,
n = 137) reported that they would work either full time (1.9%, n = 6) or part time (41.3%, n = 131). Over a
third (39.1%, n = 124) planned to attend the local 4-year university, and 19.2% (n = 61) planned to attend
the local 2-year community college. The most often cited reasons for choosing to attend the college or
university of their choice were because it was close to home and family (36.5%, n = 116), had a good

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program of study (10.7%, n = 34), was a good college/university (6.9%, n = 22), and was affordable or
inexpensive to attend (4.1%, n = 13). Sixty-eight percent (n = 214) indicated that they would rely on
financial aid (e.g., loans, grants, and work study) to finance their education, whereas 31.5% (n = 100)
hoped to earn scholarships, 26.5% (n = 84) planned to receive financial support from their parents or
other family members, and 25% (n = 78) planned to work.

Procedure
Data collection occurred during the fall semester of the school year. Student participation was solicited
through English IV classes because every senior was required to enroll in this class. Data collection
occurred across 4 days, and Lisa Y. Flores met with every English IV section (n = 46) at both schools.
English teachers escorted their students to a central room at the beginning of the class period and stayed
to monitor students’ behaviors.

Packets containing an informed-assent form, an entry form for cash prizes, and the research instruments
were distributed to students as they entered the room. The questionnaires were counterbalanced to avoid
order effects from fatigue. Participants were told that the investigator was interested in studying the career
development of Mexican American adolescents. Students were told that it would take them most, if not
all, of the class period to complete the questionnaires and were encouraged to work quickly. The
investigator told the students that two of the surveys looked very similar (each listed the same
occupations and educational programs), but these surveys asked students to rate either interests or skills.
Students were informed of a possible follow-up study and were invited to participate in future studies. As
an incentive to participate in the study, students who completed and returned the surveys were eligible for
a random drawing for cash prizes (10 prizes for $20 and 1 prize for $50).

Instruments
Acculturation level

The Acculturation Rating Scale for Mexican Americans (ARSMA–II; Cuellar, Arnold, & Maldonado, 1995)
was a 30-item scale that assessed association with and identity with the Mexican and Anglo cultures on
two independent subscales. Participants responded to the items using a 5-point scale ranging from not at
all (1) to extremely often or almost always (5). An acculturation score was calculated by subtracting the
mean score for items on the Anglo Orientation Subscale (AOS) from the mean score for items on the
Mexican Orientation Subscale (MOS). On the basis of their acculturation score, participants were
categorized into one of the five acculturation levels described by Cuellar et al. (1995). Levels range from
very Mexican oriented (1) to very assimilated (5). Middle categories represented bicultural individuals.
Thus, high scores were indicative of a strong orientation toward the Anglo culture.

The ARSMA–II, as well as prior to its revision, the ARSMA, is one of the most widely used measures to
assess acculturation among Mexican Americans, and evidence suggests that it is a reliable and valid
instrument. Adequate internal consistency coefficients have been reported for the two subscales with
multiple samples (range from .79 to .83 for the AOS and .87 to .91 for the MOS; Cuellar et al., 1995;
Cuellar & Roberts, 1997; Lessenger, 1997). Reliability coefficients of .77 for the AOS and .91 for the MOS
were obtained in the present study.

Cuellar and his colleagues also reported a test–retest reliability estimate for the AOS and MOS over a 2-
week interval of .94 and .96, respectively. Concurrent validity was assessed by comparing scores on the
ARSMA–II with scores on the ARSMA and yielded a correlation coefficient of .89. Concurrent validity for
the ARSMA–II was further supported when its two subscales correlated in the expected direction with the
dominant group and ethnic group subscales of the Stephenson Multigroup Acculturation Scale
(Stephenson, 2000). Lessenger (1997) provided additional support for concurrent validity when she
reported that acculturation scores on the ARSMA–II correlated positively with other acculturation
measures. Construct validity was supported when acculturation scores on the ARSMA–II were compared
across generations, and differences were found between generation levels in the expected directions
(Cuellar et al., 1995; Lessenger, 1997).

Feminist attitudes

The Attitudes Toward Feminism and the Women’s Movement Scale (FWM; Fassinger, 1994) was used to
measure feminist attitudes. The FWM is a 10-item scale that assessed attitudes about the feminist
movement. Participants rated their agreement with the items along a 5-point scale ranging from strongly
disagree (1) to strongly agree (5). Scale scores were obtained by averaging the items; high scores reflect
profeminist attitudes.

Fassinger (1994) reported that the FWM had high internal consistency (α = .89), and O’Brien and
Fassinger (1993) reported an internal reliability coefficient of .82 for the FWM with a sample of adolescent
women. Cronbach’s alpha for this sample was .68. Enns and Hackett (1990) reported a 2-week test–
retest reliability coefficient of .81 with female college students. Convergent validity for the FWM was
supported when the FWM was positively correlated with measures assessing attitudes toward women,
gender roles, and feminism (Enns & Hackett, 1990; Fassinger, 1994). In addition, the FWM correlated
positively with items assessing feminist identification and favorability toward the women’s movement
(Fassinger, 1994). Finally, Enns and Hackett (1990) reported that the FWM correlated in the expected
directions with both interest and involvement in feminist activities. Divergent validity estimates revealed
that the FWM was not measuring gender role characteristics, dogmatism, and social desirability
(Fassinger, 1994).

Mother’s level of education

A single item asked participants to indicate the highest level of education completed by their mother.
Options ranged from elementary school to graduate/professional school. High scores represented high
levels of education.

Mother’s occupational traditionality

An item asked participants to indicate their mother’s occupation, which was later categorized according to
traditionality. Traditionality of mother’s career was computed on the basis of the percentage of women
employed in a given career and was obtained through the Statistical Abstract of the United States (1998),
a publication of the U.S. Bureau of the Census. The U.S. Census Bureau relies on information from the

U.S. Bureau of Labor Statistics and Employment and Earnings to report these data. Scores ranged from 6
to 99, with high scores representing careers with high concentrations of women. This indicator of career
orientation has been used in previous studies of women’s career development (O’Brien, 1996; O’Brien &
Fassinger, 1993; O’Brien, Friedman, Tipton, & Linn, 2000).

Nontraditional career self-efficacy

Self-efficacy expectations with regard to nontraditional occupations were assessed using a short form of
the occupational self-efficacy questionnaire used by Church et al. (1992). The self-efficacy questionnaire
used in this study was comparable with career self-efficacy measures used by Betz and Hackett (1981)
and Lauver and Jones (1991). The original occupational questionnaire contained a total of 31 occupations
for which participants rated their confidence in their ability to successfully learn to perform the job. The
nontraditional career self-efficacy scale used for this study was modified to include seven male-dominated
occupations (e.g., electronic equipment repairer, police officer, mechanical engineer). Occupations were
categorized according to the percentage of women in the occupation according to U.S. census data (U.S.
Bureau of the Census, 1998). A brief description of the occupation was provided for each job title.

Participants were asked to rate their confidence in their ability and skills to successfully learn to do the
jobs. Participants responded to the items using a scale ranging from very unsure (1) to very sure (4).
Although studies typically use 5-point scales to measure strength of self-efficacy, we followed the
reasoning of Bores-Rangel et al. (1990), whose sample predominantly consisted of Hispanic students,
that students may dependably and meaningfully discriminate these four bipolar levels. Occupational self-
efficacy scores for male-dominated occupations were obtained by averaging the responses to the items.
High scores reflected strong levels of nontraditional career self-efficacy.

Church et al. (1992) reported an internal consistency reliability of .95 for the 31-item self-efficacy scale
with a sample of predominantly Hispanic racial/ethnic minority high school students. Convergent validity
was supported with a sample of Mexican American boys when nontraditional career self-efficacy was
positively related to nontraditional career interests, consideration of nontraditional careers, and selection
of careers dominated by men (Flores, 2000). Divergent validity estimates indicated that nontraditional
career self-efficacy was not related to acculturation or feminist attitudes (Flores, 2000). Church et al.
reported that the self-efficacy scale was not measuring aptitude. An alpha coefficient of .81 for the short
version of the nontraditional self-efficacy scale was obtained in the present study.

Nontraditional career interests

Students’ nontraditional occupational interests were assessed using the same male-dominated
occupations on the nontraditional career self-efficacy scale. Participants were asked to indicate their
interest in the jobs listed on a scale ranging from dislike (1) to like (3); this scale is similar to ones used in
other career interest inventories. Scoring the nontraditional career interests scale consisted of summing
the items and dividing by the number of items to obtain a mean score. High scores reflected strong levels
of interest for the nontraditional or male-dominated occupations.

Church et al. (1992) reported an internal consistency reliability of .86 for the 31-item interest scale with a
sample comprising mainly Hispanic students. Construct validity was supported when the original scale
correlated positively with another interest measure (Church et al., 1992). In addition, among a group of
Mexican American boys, it correlated positively with nontraditional career self-efficacy, consideration of
nontraditional careers, and choice of nontraditional careers, providing support for convergent validity
(Flores, 2000). It was not related to feminist attitudes (Flores, 2000). Cronbach’s alpha was .74 for the
present study.

Parental support

The Career Support Scale (CSS; Binen, Franta, & Thye, 1995) was used to assess the amount of
perceived support and encouragement that participants received in their career pursuits from their
parents. The CSS was adapted by assessing support from both parents concurrently rather than
individually and by reducing the number of items (10 items that were cross-listed on both Mother and
Father subscales were retained). Sample items included “My parents agree with my career goals” and
“My parents and I often discuss my career plans.” Participants responded to the 10 items using a 5-point
scale ranging from almost never (1) to almost always (5). Scale scores were obtained by averaging the
items. High scores reflected strong levels of perceived support from parents.

Reliability estimates were .87 for the 22-item Mother–CSS and .90 for the 18-item Father–CSS (Binen et
al., 1995). Internal consistency for the modified CCS used in the present study was .76. Discriminant
validity estimates indicated that the Mother and Father subscales were not significantly correlated with
social desirability (Binen et al., 1995).

Perceived occupational barriers

The Perceptions of Barriers scale (POB; McWhirter, 1997) was a 24-item scale that assessed ethnic and
gender-related occupational and educational barriers. Because the present study assessed career choice
goals, only those items of the POB that measured participants’ job-related barriers were included. Eight
items, which assessed anticipated future gender and ethnic discrimination in the workplace, were used for
this study. Individuals responded to the items using a scale ranging from strongly agree (1) to strongly
disagree (5). Scale scores were derived by averaging the responses. High scores reflected low
anticipation of gender or ethnic discrimination in a career.

McWhirter (1997) reported an alpha coefficient of .89 for the job discrimination items, and a reliability
estimate of .91 was obtained with the present sample. Construct validity was supported when McWhirter
(1997) found significant differences in anticipated job discrimination between Mexican American and
European American students, boys and girls, and Mexican American girls and European American girls in
the expected directions.

Career choice prestige and traditionality

Participants were asked to list their top three career choices. The traditionality rating of the top career
choice was obtained with the same procedure for mothers’ occupational traditionality.

Career choice prestige was determined on the basis of Stevens and Featherman’s (1981) socioeconomic
index of occupational status. Scores ranged from 13 to 89, with high scores indicating prestigious
careers. This indicator of career choice has been used in previous studies of women’s and racial/ethnic
minorities’ career development (O’Brien, 1996; O’Brien & Fassinger, 1993; O’Brien et al., 2000; Tang et
al., 1999).

Career aspiration

The Career Aspiration Scale (CAS; O’Brien, 1992) contained 10 items that assessed participants’ goals
and plans within their career field. Example items included “I plan on developing as an expert in my
career field” and “I do not plan on devoting energy in getting promoted in the organization or business I
am working in.” Participants indicated whether the items applied to them by using a 5-point scale ranging
from not at all true of me (0) to very true of me (4). Scale scores were derived by calculating the mean
score for the items. High scores indicated strong aspirations in one’s career pursuits.

Internal consistency of the CAS has been reported as .76 (O’Brien & Fassinger, 1993) with female high
school students and .77 (Dukstein & O’Brien, 1994) and .80 (Nauta, Epperson, & Kahn, 1998) with female
undergraduate students. In the present study, a reliability coefficient of .61 was obtained. Convergent
validity for the CAS was supported by relations with multiple role self-efficacy, career decision-making
self-efficacy, and career salience (O’Brien, Gray, Tourajdi, & Eigenbrode, 1996). Discriminant validity was
demonstrated through the absence of relations between the CAS and social desirability, as well as a
negative relation between the CAS and a measure of the relative importance of career versus family
(O’Brien et al., 1996).

Demographic information

A demographic information survey was included to obtain age, gender, race/ethnicity, grade level, number
of people living at home, family income, plans following high school graduation, parents’ level of
education, and parents’ occupations. If participants were planning to continue their education following
high school, information regarding their major of study, choice of college/university to attend, sources of
financial support for education, and reasons for choosing the college/university was obtained.

Results

The means, standard deviations, ranges, and reliability coefficients for each of the measured variables,
along with a correlation matrix, are presented for the full sample in Table 1.

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Means, Standard Deviations, Ranges, Reliability Coefficients, and Correlations Among the Measured
Variables

Model Predicting Mexican American Adolescent Women’s Career Choice Prestige
The original sample of 364 Mexican American young women was randomly split into two samples. A
sample consisting of 262 women was used to test the original models, and a validation sample consisting
of 102 women was set aside for confirmation purposes in the case that any of the models were revised. A
path analysis was conducted using the EQS (Version 5.7) statistical package (Bentler & Wu, 1995).

The hypothesized model predicting career choice prestige tested the paths from acculturation level,
feminist attitudes, mothers’ educational level, and mothers’ occupational traditionality to nontraditional
career self-efficacy; nontraditional career self-efficacy to nontraditional career interests; and nontraditional
career self-efficacy, nontraditional career interests, parental support, and perceived future barriers to
career choice prestige. The exogenous variables, which included the background and proximal contextual
variables, in the model were allowed to covary.

Adequacy of model fit was determined by using a variety of goodness-of-fit measures, including the chi-
square test, the comparative fit index (CFI), the goodness-of-fit index (GFI), the root-mean-square error of
approximation (RMSEA), and the standardized root-mean-squared residual (SRMR). The CFI and
RMSEA goodness-of-fit measures are preferred indexes by which to assess model fit (Loehlin, 1998).

If a model provides adequate fit, a small chi-square value and a nonsignificant p value are expected.
Values for the CFI and GFI indexes range from 0 to 1; models with values above .90 have traditionally
been considered models with good fit (Loehlin, 1998); however, values of .95 and higher are suggested
today as the baseline to assess model fit. Models with RMSEA and SRMR values around or below .05
(“close fit”) are considered acceptable models (Loehlin, 1998). To further test the adequacy of the model,
Hu and Bentler (1999) recommended joint criteria to minimize the dual threats of rejecting the right model
and retaining the wrong model. Specifically, a model can be retained if the CFI is .96 and the SRMR is
≤.10, or the RMSEA is ≤.06 and SRMR is ≤.10. See Table 2 for a summary of the goodness-of-fit indices
for the career prestige model.

Summary of Model-Fit Statistics

The chi-square statistic for the model predicting career choice prestige was significant, suggesting a poor
fit. However, given that the chi-square statistic is overly stringent in its evaluation of exact fit (Quintana &
Maxwell, 1999), other indexes were studied. Examination of the CFI, RMSEA, and SRMR indexes implied
that the data fit the model poorly, indicating that the fit between the data and model could be improved.
Thus, the model was rejected.

We attempted to identify modifications to the model to improve the fit of the model and followed the
suggestions of MacCallum, Roznowski, and Necowitz (1992) that changes be made only when they are
theoretically meaningful. The Lagrange multiplier test suggested that the model could be improved by
adding paths from acculturation level and feminist attitudes to career choice prestige. The influence of
acculturation level on career choice prestige was consistent with prior research, which indicated that
among racial/ethnic minorities in the United States, levels of acculturation can directly and indirectly
influence career choice and career expectations (Leong & Chou, 1994; McWhirter et al., 1998; Tang et
al., 1999). Adding the path from feminist attitudes to career choice prestige was justified on the basis of
prior research that supported the relation between feminist attitudes (Fassinger, 1990; O’Brien &
Fassinger, 1993) and career outcomes, such as educational achievement or career choices.

The model was rerun with these changes, and the fit indexes indicated a superior fit to the data (see
Table 2 for a summary of the fit indexes for the initial and revised model predicting career choice
prestige). Comparing the chi-square statistic for the initial and the revised models allows a determination
of whether the modifications resulted in significant improvement in the model’s fit (Quintana & Maxwell,
1999). The revised model was a significant improvement over the initial model, χ difference(2, N = 262) =
39.94, p < .01.

Because revisions were made to the original model and because modifications were based on data from
the calibration sample, it was necessary to validate the revised model using the second sample. The
modified model was run with the validation sample, and the fit indexes with this group were satisfactory

2

(see Table 2). To determine whether the corresponding paths had the same values across both groups,
we performed a multiple group analysis with Group 1 as the calibration sample (n = 262) and Group 2 as
the validation sample (n = 102). This analysis runs the model simultaneously for both groups and follows
a two-step procedure. First, the revised model was tested and the path values were estimated for each
group. Next, we tested the revised model again with all paths constrained to have equal values across
both groups. A comparison of the chi-square statistic for the multiple group analysis with no constraints
and the multiple group analysis with constraints determines whether these models were significantly
different. If the chi-square difference between the constrained and nonconstrained models is significant,
the path coefficients differ across samples. The model predicting career prestige resulted in a
nonsignificant chi-square value, χ (11, N = 364) = 24.95, p > .05, indicating that the paths values were not
significantly different across the two groups. Thus, the modified model was replicated satisfactorily with
the two samples of Mexican American adolescent women, providing support for the revised model. Table
3 presents the results of the multigroup comparisons for the model predicting career choice prestige.

Summary of Multigroup Analyses Between Split Sample of Mexican American Adolescent Women

The next step involved running the revised model using the combined sample of 364 Mexican American
adolescent women given that the model was replicated for both groups. See Table 2 for a summary of the
fit indexes. The squared multiple correlation coefficient (R ) was obtained by squaring the residual
coefficient of the criterion variable and subtracting that value by 1. The R for the model of career prestige
indicated that 8% of the variance in career choice prestige was accounted for by acculturation level,
feminist attitudes, nontraditional career self-efficacy, nontraditional career interests, parental support, and
perception of future barriers. See Figure 2 for the revised model predicting Mexican American girls’ career
choice prestige.

2
2
2

Figure 2. Respecified model predicting Mexican American adolescent women’s career choice prestige. *p
< .05

Model Predicting Mexican American Adolescent Women’s Career Choice Traditionality
The hypothesized model predicting career choice traditionality tested the same paths identified in the
career prestige model, except that career choice traditionality was used as the criterion variable. The
contextual variables in the model were allowed to covary.

The chi-square statistic for the model predicting career choice traditionality was significant, suggesting
that the model demonstrated poor fit. Examination of the CFI, RMSEA, and SRMR implied a poor fit with
the data; however, the GFI indicated an adequate fit. On the basis of Hu and Bentler’s (1999) criteria, the
model of career choice traditionality was rejected.

Again, attempts were made to identify modifications to the model based on suggestions that were
theoretically sound. Adding paths from acculturation level and feminist attitudes to career choice
traditionality were suggested by the Lagrange multiplier, and these additions were justified on the basis of
previous research (Fassinger, 1990; Leong & Chou, 1994; McWhirter et al., 1998; O’Brien & Fassinger,
1993; Tang et al., 1999) that found relations among acculturation levels, feminist attitudes, and career
choice.

The model was rerun with the modifications and the fit indices improved (see Table 2 for a summary of
the fit indexes for the initial and revised model predicting career choice traditionality). The values on the
CFI and GFI exceeded .95, and the RMSEA and SRMR values were less than .05. Further, the revised
model met Hu and Bentler’s (1999) recommended criteria for model acceptance. The chi-square
difference test indicated that the revised model was a significant improvement over the initial model, χ
difference(2, N = 262) = 25.04, p < .01.

Consistent with the previous method of analysis, the revised model predicting career choice traditionality
was tested on the validation sample. On the basis of the fit indexes (see Table 2), the revised model was
supported with this sample. We performed a multiple group analysis to determine if the path coefficients

2

in the modified model predicting career choice traditionality could be replicated in the second sample. The
chi-square difference between the constrained and nonconstrained models resulted in a nonsignificant
chi-square value, χ (11, N = 364) = 6.25, p > .05, indicating that the values for the paths were not
significantly different across the two groups. Thus, the revised model and the corresponding path values
were validated with the validation sample. Table 3 presents the results of the multiple group comparisons
for the model predicting career choice traditionality.

Because the model was replicated with an independent sample, the calibration and validation samples
were combined, and the revised model was run using the full sample. See Table 2 for a summary of the fit
indexes. The squared multiple correlation coefficient in the revised model of career traditionality indicated
that 11% of the variance in career choice traditionality was accounted for by acculturation level, feminist
attitudes, nontraditional career self-efficacy, nontraditional career interests, parental support, and
perception of future barriers. See Figure 3 for the revised model predicting Mexican American girls’ career
choice traditionality.

Figure 3. Respecified model predicting Mexican American adolescent women’s career choice
traditionality. *p < .05

Model Predicting Mexican American Adolescent Women’s Career Aspiration
The hypothesized model predicting career aspiration tested the same paths identified in the previous
models, except that career aspiration was used as the criterion variable. The exogenous variables in the
model were allowed to covary.

The chi-square statistic for the model predicting career aspirations was significant, suggesting that the
model demonstrated poor fit. Examination of the CFI, RMSEA, and SRMR fit indexes indicated a poor fit
with the data; however, the GFI indicated adequate fit. By using Hu and Bentler’s (1999) criteria, the
original model was rejected.

Respecifications to the model were suggested on the basis of the Lagrange multiplier modification index.
The addition of a path from feminist attitudes to career aspiration was suggested and was supported by

2

prior research (Fassinger, 1990; O’Brien & Fassinger, 1993).

The revised model was reestimated and the fit indices improved (see Table 2 for a summary of the fit
indexes for the initial and revised model predicting career aspiration). Examination of the chi-square
differences between the two models indicated that the revised model was an improvement over the initial
model, χ difference(1, N = 262) = 23.29, p < .01.

The revised model was estimated on the validation sample, and the fit indexes (see Table 2) suggested
that this model adequately fit the data. We performed a multiple group analysis to determine if the path
values in the modified model predicting career aspiration would generalize to other samples in the
population. The chi-square difference between the constrained and nonconstrained models resulted in a
nonsignificant chi-square value, χ (11, N = 364) = 8.60, p > .05, indicating that the values of the paths
were not significantly different across the two groups. Thus, the revised model and the path coefficients
were supported with the validation sample. Table 3 presents the results of the multiple group comparisons
for the model predicting career aspiration.

Again, both of the samples were combined, and a path analysis of the revised model was performed
using the full sample. See Table 2 for a summary of the fit indexes. The squared multiple correlation
coefficient for the model of career aspiration indicated that 13% of the variance in career aspiration was
accounted for by feminist attitudes, nontraditional career self-efficacy, nontraditional career interests,
parental support, and perception of future barriers. See Figure 4 for the revised model predicting Mexican
American girls’ career aspiration.

Figure 4. Respecified model predicting Mexican American adolescent women’s career aspirations. *p < .05

There were no significant paths between the background contextual variables of acculturation level,
feminist attitudes, mothers’ educational level, mothers’ occupational traditionality, and nontraditional
career self-efficacy. Nontraditional career self-efficacy predicted nontraditional career interests in all
models; however, nontraditional career interests did not predict any of the three criterion variables of

2
2

career choice prestige, career choice traditionality, or career aspiration. Acculturation, nontraditional
career self-efficacy, parental support, and perceived barriers had significant effects on career choice
prestige. Acculturation level and feminist attitudes had a significant positive effect, and nontraditional
career self-efficacy had a significant negative effect, on choice of traditional careers, but parental support
and perceived barriers had no significant effects. Finally, higher parental support and higher levels of
feminist attitudes were predictive of higher levels of career aspiration. Nontraditional career self-efficacy
and perceived barriers did not significantly predict Mexican American women’s career aspirations.

Descriptive Statistics
A wide range of careers, representing both traditional and nontraditional occupational fields, were
identified as potential careers for this sample. The top two occupations endorsed by these women were
traditionally female occupations (teacher = 16% and nurse = 11.3%). Eleven percent intended to be
doctors, and over 6% chose physical therapy as their future occupation. A total of 76 occupations were
reported. (Contact Lisa Y. Flores for a complete list.)

Discussion

This study was the first to test the validity of SCCT (Lent et al., 1994) in explaining the career-related
goals of Mexican American adolescent women. Consistent with SCCT, nontraditional career self-efficacy
predicted nontraditional career interests. In addition, nontraditional career self-efficacy had a positive
effect on career choice prestige and a negative effect on career choice traditionality. As hypothesized by
Lent et al., the proximal contextual variables of parental support and perceived future occupational
barriers directly predicted career choice prestige, and parental support was predictive of career
aspiration.

However, several SCCT (Lent et al., 1994) propositions were not supported by data from this sample of
Mexican American women. Specifically, relations did not emerge between the background contextual
variables (i.e., acculturation level, feminist attitudes, mothers’ educational level, and mothers’
occupational traditionality) and nontraditional career self-efficacy. Interestingly, nontraditional career
interests did not exert an influence on any of the outcome variables tested in this study. Moreover, the
proximal contextual variables did not influence career traditionality, and nontraditional career self-efficacy
did not predict career aspiration.

Finally, although not posited by SCCT, adding paths from acculturation level and feminist attitudes to
career choice prestige and career choice traditionality were suggested based on the data and increased
the amount of variance explained in each model. Also, the addition of the path from feminist attitudes to
career aspiration improved the model explaining Mexican American adolescent women’s career
aspirations.

Explication of potential reasons why several SCCT (Lent et al., 1994) propositions were not replicated in
this sample of Mexican American women seems warranted. First, support for the SCCT hypotheses
related to the formation of self-efficacy beliefs was not demonstrated by our models. Specifically, SCCT
hypothesized that background contextual variables would have an indirect effect on nontraditional career

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self-efficacy through learning activities. Although learning opportunities were not measured in this study,
contextual factors would be expected to exert an influence on career self-efficacy, assuming their
relationship to learning opportunities. However, acculturation level, feminist attitudes, mothers’
educational attainment, and mothers’ career traditionality did not predict nontraditional career self-
efficacy. These findings suggested that other contextual variables, not assessed in the present study, may
account for the variance in Mexican American women’s nontraditional career self-efficacy. Researchers
might investigate the contributions of related academic and social experiences, persuasion, and familial
expectations in future models to account for the role of learning experiences in the development of
Mexican American women’s nontraditional career self-efficacy.

With regard to acculturation and nontraditional self-efficacy, previous research demonstrated a relation
between these variables with another racial/ethnic minority group (Tang et al., 1999). The nonsignificant
relation with this sample may be due to defining acculturation level along a single continuum and the
distribution of the sample, which was overwhelmingly bicultural (n = 237). Future studies should conduct
multisample analyses on the basis of acculturation level to determine if differences are present among
nonacculturated, bicultural, and highly acculturated individuals.

Feminist attitudes also were not related to nontraditional career self-efficacy, a finding that has been
consistently reported in samples of predominantly White women (O’Brien, 1996; O’Brien & Fassinger,
1993). It is possible that the lack of variability in scores on the measure assessing feminist values made
detecting a relation with career self-efficacy difficult. Alternatively, feminist beliefs may not be salient for
this sample of Mexican American women, perhaps demonstrated by mean scores in the mid-range on
this instrument. At times, the feminist movement has been criticized for focusing on the needs and values
of White women (Espin, 1994). It is possible that moderate beliefs about feminism combined with little
variability in scores on this measure may have contributed to the lack of predictive validity of this variable
with regard to confidence in pursuing nontraditional occupations.

In addition to acculturation and feminist attitudes not predicting nontraditional career self-efficacy,
mothers’ educational level and mothers’ career traditionality did not influence confidence in pursuing
nontraditional occupations. There may be other factors in the mother–daughter relationship that influence
the strength of the relation to nontraditional career self-efficacy. Indeed, O’Brien et al. (1996) found that
high school girls’ relationships with their mothers often included conflictual feelings. These feelings could
affect mothers’ influence on their daughters’ career decision making. Future research studies should
assess the quality of mother–daughter relationships to ascertain the predictive ability of mothers’
influence on daughters’ career self-efficacy. Alternatively, these girls may have looked to their fathers for
career role modeling, a finding reported by O’Brien et al. (2000). Seeking other family members for career
role modeling may be common among Mexican American girls, especially because Mexican American
women tend to be employed in traditional career fields. Indeed, over a third of this sample reported that
their mothers were homemakers. Thus, we suggest that future studies also assess the influence of
additional role models beyond mothers, including fathers, aunts, uncles, grandparents, siblings, and
peers.

An additional SCCT (Lent et al., 1994) proposition that was not supported was the hypothesized relation
between nontraditional career self-efficacy and career aspiration. Although nontraditional career self-
efficacy appears to exert an influence on the types of careers Mexican American adolescent women
choose, this construct did not contribute to their aspiration or goals within a given career. Programs that
expose Mexican American women to nontraditional careers and provide opportunities for increased self-
efficacy in performing tasks associated with nontraditional occupations could enhance the relation
between self-efficacy and aspiration and perhaps increase the number of Mexican American adolescent
women who develop interests in and choose nontraditional, prestigious careers (see O’Brien, Dukstein,
Jackson, Tomlinson, & Kamatuka, 1999, for an example of a career intervention). Moreover, O’Brien and
her colleagues suggested that educational and career planning occur far in advance of graduation from
high school. Indeed, prior research recommended the implementation and evaluation of career-oriented
workshops, classes, or summer programs with middle school and high school students who are at risk for
educational and vocational underachievement (O’Brien et al., 1999; O’Brien et al., 2000). Fouad (1995)
noted the need for such interventions to focus specifically on Hispanic students. Programs that demystify
the college experience, improve decision-making skills, and assist participants in learning about
themselves, colleges/universities, and careers could enhance career self-efficacy.

Also, the SCCT (Lent et al., 1994) proposition that career interests influence career goals was not
supported by our data; a similar finding was reported with Asian American college students (Tang et al.,
1999). For this sample of Mexican American women, factors other than interests, such as confidence in
their abilities to carry out the duties of the career, had a stronger influence on career goals. Alternatively, it
is possible that Mexican American adolescent women may not have the luxury of choosing a career
based on their interests. If this finding is replicated in other samples, we recommend that Lent et al.
consider revising their proposition to reflect the lack of salience of interests in predicting the career paths
of women of color. Moreover, psychologists might reconsider the use of a traditional approach to career
counseling with Mexican American women, as other factors beyond matching interests and careers may
be stronger determinants to their career decisions. Counselors also need to assess if career choices are
consonant with interests, and if not, they should explore the obstacles that may be preventing them from
pursuing careers in which they have interests.

Finally, modifications to the model suggested that acculturation level significantly influenced the selection
of nontraditional, highly prestigious careers, and feminist attitudes was a significant predictor of career
traditionality and career aspiration. Women who were more oriented toward the Anglo culture tended to
choose less prestigious and more traditional careers. Also, women with higher levels of feminist attitudes
were more likely to choose traditional careers and have higher career aspiration. These relations were
contrary to prior research that suggested that nontraditional gender role attitudes were positively related
to Mexican American women’s educational and career choices (McWhirter et al., 1998; Valenzuela, 1993;
Vasquez-Nuttal et al., 1987). One possible explanation for these findings is that acculturated women may
be aware of the sociopolitical atmosphere for women in workplaces that are dominated by men and thus
may choose to avoid those careers. Results also indicated that women who ascribed to feminist beliefs
were more likely to be goal oriented within their chosen career. Indeed, O’Brien et al. (2000) reported this
same phenomenon among a sample of White college women and suggested that women may choose

nontraditional, less prestigious careers to balance personal and work demands, yet may desire to achieve
within their career. As such, it is reasonable to expect that these adolescents may perceive more
opportunities for advancement in traditional careers for women.

Several of Lent et al.’s (1994) propositions were supported by our data. First, nontraditional career self-
efficacy was found to have a direct influence on Mexican American women’s nontraditional career
interests, career prestige, and career traditionality. As nontraditional career self-efficacy increased,
nontraditional career interests also increased. Furthermore, higher levels of nontraditional career self-
efficacy were related to the selection of nontraditional and prestigious careers. These findings support the
SCCT propositions that people develop interests in areas in which they have a strong sense of agency,
and they select careers in which they feel confident about their ability to complete the tasks necessary for
the career.

Second, results of the present study provided empirical support for Lent et al.’s (1994) proposition that the
presence of support and few perceived barriers has a positive effect on career goals. Mexican American
adolescent women who perceived support from their parents for their career pursuits and who anticipated
fewer barriers chose prestigious careers, and women who perceived their parents to be supportive of
their career goals had stronger levels of career aspiration. This finding contradicts an earlier study that
found that perceptions of barriers were not predictive of the career expectations of Mexican American
girls (McWhirter et al., 1998) and replicates those studies that found that emotional support from the
family was predictive of educational plans and career expectations (Gandara, 1982; Hernandez et al.,
1994; Keith & Lichtman, 1994; Ramos & Sanchez, 1995; Vasquez, 1982; Wycoff, 1996).

These findings suggest that Mexican American adolescent women may choose highly prestigious careers
on the basis of the approval of others or their family obligations. Indeed, with the exception of feminist
attitudes, parental support contributed more to the prediction of Mexican American women’s selection of
prestigious careers than any other variable assessed in this study. These findings are important given the
emphasis placed on the family unit in the Mexican American culture and are consistent with vocational
decision-making behaviors among Asian Americans, a group who similarly place a high value on family
(Leong & Gim, 1995; Leong & Serafica, 1995). Mexican American women from traditional families may
not have the support to pursue nontraditional educational and vocational aspirations if they conflict with
cultural norms and family expectations. Counselors should address these factors when working with
Mexican American women.

These findings highlight the salience of addressing cultural and familial expectations when providing
career counseling to Mexican American women. Furthermore, counseling psychologists should be
encouraged to develop innovative career intervention programs for Mexican American adolescents that
involve parents and other family members. Parental involvement in vocational interventions could
facilitate the lines of communication between children and their parents about career development and
job requirements, which could assist students in planning for their future. Moreover, parents and children
could clarify the expectations and dreams that each holds regarding educational and career attainment.
Researching the effectiveness of these programs in students’ educational and career planning is strongly

recommended.

The importance of family also was reflected in the educational goals of these young women. Most of the
participants who planned to continue their education beyond high school indicated that they would enroll
in the local 2-year community college or 4-year state university. Indeed, students reported that the
proximity of the college/university to home was one of the most important factors in choosing a
college/university. Remaining geographically close to their families while attending college seems to be a
salient consideration in the educational planning of Mexican American women. It is unknown, however,
whether these young women choose to stay close to home because of familial expectations or personal
preferences. It is also unclear whether this choice provides needed support to pursue their educational
and career aspirations or if their future opportunities are limited by this decision. Research is needed to
understand how attending college in the same hometown facilitates or hinders attrition and graduation
rates as well as the career orientation of Mexican American women.

Future researchers should also consider incorporating additional variables not included in the SCCT (Lent
et al., 1994) model of career choice given that the hypothesized models only accounted for 8%, 11%, and
13% of the variance in the prediction of prestige, traditionality, and career aspiration, respectively.
Because the proximal contextual variable of support contributed to Mexican American women’s career
choice prestige and career aspirations, consideration of other contextual variables that may contribute to
their career goals is warranted. Indeed, analyses revealed that the background contextual variables of
acculturation level and feminist attitudes have a direct influence on the prestige level and traditionality of
Mexican American women’s career choices that are not represented in Lent et al.’s proposed model.
Furthermore, environmental factors related to the school (i.e., vocational guidance programs in the
school) are not included in Lent et al.’s model but should be investigated.

The reliability estimates for the scales used to assess feminist attitudes and career aspiration were
relatively low, and thus, the findings related to these constructs should be interpreted with caution. For
example, it is possible that significant path coefficients may emerge in the career aspiration model with a
more reliable scale. Given the paucity of research with Mexican Americans, future studies should attempt
to improve on the psychometric properties of the measures used in this study and to develop new
instruments for use in research with this population. Additional testing of the revised model with several
samples of Mexican American women is necessary to determine if these results can be generalized.
Research is also needed to evaluate the validity of Lent et al.’s (1994) model with Mexican American boys
and men.

As noted earlier, only a modest amount of variance in the criterion variables was accounted for by the
social cognitive and contextual variables assessed in this study. Additional variables that may contribute
to career goals should be considered in future studies with Mexican American women. For example,
researchers have suggested that socioeconomic status and student ability may be important variables to
assess among Mexican Americans and female participants (e.g., Fassinger, 1990; Lauver & Jones, 1991;
McWhirter et al., 1998). Moreover, given that teen pregnancy and marriage occur with some frequency in
this population, assessing pregnancy and marriage rates at this age could provide data regarding how

these events affect the educational and career aspirations of young women. Relatedly, although this study
included an assessment of several environmental influences on women’s career development, the focus
was on individual variables. Additional research is needed to investigate the ways in which the social
environment limits the educational and occupational opportunities of Mexican American women.

Finally, a longitudinal study that assesses the career orientation of Mexican American women at periodic
intervals following high school graduation is recommended. Such a study would provide information
regarding the factors that affect the vocational development of Mexican American women over the course
of their lives. A longitudinal study would also provide useful information regarding the factors that
contribute to college graduation among Mexican American women. Future studies could investigate the
barriers encountered by students who do not complete college and explore the characteristics shared by
those who successfully complete college. Counseling psychologists could then develop empirically based
interventions to optimize success in college.

In conclusion, the results of this study advanced knowledge regarding the explanatory power and
limitations of SCCT (Lent et al., 1994) in describing the career development of Mexican American
adolescent women. Because Mexican American women are largely underrepresented in higher education
and in nontraditional, high-prestige occupations, investigating their educational and career aspirations at
a critical decision-making time of their lives (in their senior year of high school) seems critically important.
Such information could inform counseling interventions aimed at this population to enable Mexican
American women to pursue academic and career opportunities that correspond with their ability and
maximize their potential for educational and vocational success.

References
Arbona, C. (1989). Hispanic employment and the Holland typology of work. Career Development
Quarterly, 37, 257–268.

Arbona, C. (1990). Career counseling research and Hispanics: A review of the literature. The Counseling
Psychologist, 18, 300–323.

Arbona, C. (1995). Theory and research on racial and ethnic minorities: Hispanic Americans. In F. T.
L.Leong (Ed.), Career development and vocational behavior of racial and ethnic minorities (pp. 37–66).
Mahwah, NJ: Erlbaum.

Arbona, C., & Novy, D. M. (1991). Career aspirations and expectations of Black, Mexican-American, and
White students. Career Development Quarterly, 39, 231–239.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs,
NJ: Prentice Hall.

Bentler, P. M., & Wu, E. J. C. (1995). EQS for Windows user’s guide: Version 5. Encino, CA: Multivariate
Software.

Betz, N. E. (1994). Basic issues and concepts in career counseling for women. In W. B.Walsh & S.

https://web-a-ebscohost-com.lopes.idm.oclc.org/ehost/delivery?sid=8040a7f5-faab-41ad-ba6c-ab4d04c9f1b5@sessionmgr4007&vid=2&ReturnUrl=https://web.a.ebscohost.com/ehost/pdfviewer/pdfviewer?vid=1&sid=8040a7f5-faab-41ad-ba6c-ab4d04c9f1b5%2540sessionmgr4007%23toc

H.Osipow (Eds.), Career counseling for women (pp. 1–41). Hillsdale, NJ: Erlbaum.

Betz, N. E., & Hackett, G. (1981). The relationship of career-related self-efficacy expectations to
perceived career options in college women and men. Journal of Counseling Psychology, 28, 399–410.

Binen, L. M., Franta, P. J., & Thye, R. (1995). Career Support Scale.Unpublished manuscript, University
of Missouri—Columbia.

Bores-Rangel, E., Church, A. T., Szendre, D., & Reeves, C. (1990). Self-efficacy in relation to
occupational consideration and academic performance in high school equivalency students. Journal of
Counseling Psychology, 37, 407–418.

Cardoza, D. (1991). College attendance and persistence among Hispanic women: An examination of
some contributing factors. Sex Roles, 24, 133–147.

Carter, D., & Wilson, R. (1993). Minorities in higher education: 1992 eleventh annual status report.
Washington, DC: American Council on Education.

Casas, J. M., & Pytluk, S. D. (1995). Hispanic identity development: Implications for research and
practice. In J. G.Ponterotto, J. M.Casas, L. A.Suzuki, & C. M.Alexander (Eds.), Handbook of multicultural
counseling (pp. 155–180). Thousand Oaks, CA: Sage.

Church, A. T., Teresa, J. S., Rosebrook, R., & Szendre, D. (1992). Self-efficacy for careers and
occupational consideration in minority high school equivalency students. Journal of Counseling
Psychology, 39, 498–508.

Cuellar, I., Arnold, B., & Maldonado, R. (1995). Acculturation Rating Scale for Mexican Americans—II: A
revision of the original ARSMA scale. Hispanic Journal of Behavioral Sciences, 17, 275–304.

Cuellar, I., & Roberts, R. E. (1997). Relations of depression, acculturation, and socioeconomic status in a
Latino sample. Hispanic Journal of Behavioral Sciences, 19, 230–238.

Dukstein, R. D., & O’Brien, K. M. (1994). The contribution of multiple role self-efficacy and gender role
attitudes to women’s career development.Unpublished manuscript, University of Kansas.

Enns, C. Z., & Hackett, G. (1990). Comparison of feminist and nonfeminist women’s reactions to variants
of nonsexist and feminist counseling. Journal of Counseling Psychology, 37, 33–40.

Espin, O. M. (1994). Feminist approaches. In L.Comas-Diaz & B.Greene (Eds.), Women of color:
Integrating ethnic and gender identities in psychotherapy (pp. 265–318). New York: Guilford Press.

Farmer, H. S. (1985). Model of career and achievement motivation for women and men. Journal of
Counseling Psychology, 32, 363–390.

Fassinger, R. E. (1990). Causal models of career choice in two samples of college women. Journal of

Vocational Behavior, 36, 225–248.

Fassinger, R. E. (1994). Development and testing of the Attitudes Toward Feminism and the Women’s
Movement (FWM) scale. Psychology of Women Quarterly, 18, 389–402.

Fisher, T. A., & Padmawidjaja, I. (1999). Parental influences on career development perceived by African
American and Mexican American college students. Journal of Multicultural Counseling and Development,
27, 136–152.

Fitzgerald, L. F., & Betz, N. E. (1994). Career development in cultural context: The role of gender, race,
class, and sexual orientation. In M. L.Savickas & R. W.Lent (Eds.), Convergence in career development
theories: Implications for science and practice (pp. 103–117). Palo Alto, CA: Consulting Psychologists
Press.

Fitzgerald, L. F., Fassinger, R. E., & Betz, N. E. (1995). Theoretical advances in the study of women’s
career development. In W. B.Walsh & S. H.Osipow (Eds.), Handbook of vocational psychology: Theory,
research, and practice (pp. 67–110). Mahwah, NJ: Erlbaum.

Flores, L. Y. (2000, August). Testing a model of career choice with Mexican American boys.Poster
presented at the 108th Annual Convention of the American Psychological Association, Washington, DC.

Fouad, N. A. (1995). Career behavior of Hispanics: Assessment and career intervention. In F. T. L.Leong
(Ed.), Career development and vocational behavior of racial and ethnic minorities (pp. 165–192).
Mahwah, NJ: Erlbaum.

Fouad, N. A., & Smith, P. L. (1996). A test of a social cognitive model for middle school students: Math
and science. Journal of Counseling Psychology, 43, 338–346.

Gainor, K. A., & Lent, R. W. (1998). Social cognitive expectations and racial identity attitudes in predicting
the math choice intentions of Black college students. Journal of Counseling Psychology, 45, 403–413.

Gandara, P. (1982). Passing through the eye of the needle: High-achieving Chicanas. Hispanic Journal of
Behavioral Sciences, 4, 167–179.

Gillock, K. L., & Reyes, O. (1999). Stress, support, and academic performance of urban, low-income,
Mexican-American adolescents. Journal of Youth and Adolescence, 28, 259–282.

Ginorio, A. B., Gutierrez, L., Cauce, A. M., & Acosta, M. (1995). Psychological issues for Latinas. In
H.Landrine (Ed.), Bringing cultural diversity to feminist psychology: Theory, research, and practice (pp.
241–263). Washington, DC: American Psychological Association.

Gomez, M. J., & Fassinger, R. E. (1994). An initial model of Latina achievement: Acculturation,
biculturalism, and achieving styles. Journal of Counseling Psychology, 41, 205–215.

Hackett, G., & Betz, N. E. (1981). A self-efficacy approach to the career development of women. Journal

of Vocational Behavior, 18, 326–339.

Hackett, G., Lent, R. W., & Greenhaus, J. H. (1991). Advances in vocational theory and research: A 20-
year retrospective. Journal of Vocational Behavior, 38, 3–38.

Hernandez, A., Vargas-Lew, L., & Martinez, C. L. (1994). Intergenerational academic aspirations of
Mexican-American females: An examination of mother, daughter, and grandmother triads. Hispanic
Journal of Behavioral Sciences, 16, 195–204.

Hess, R. S., & D’Amato, R. C. (1996). High school completion among Mexican American children:
Individual and family background variables. School Psychology Quarterly, 11, 353–368.

Hoyt, K. B. (1989). The career status of women and minority persons: A 20-year retrospective. Career
Development Quarterly, 37, 202–212.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional
criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55.

Hurtado, M. T., & Gauvain, M. (1997). Acculturation and planning for college among youth of Mexican
descent. Hispanic Journal of Behavioral Sciences, 19, 506–516.

Keith, P. B., & Lichtman, M. V. (1994). Does parental involvement influence the academic achievement of
Mexican-American eighth graders? Results from the National Educational Longitudinal Study. School
Psychology Quarterly, 9, 256–272.

Lango, D. R. (1995). Mexican American female enrollment in graduate programs: A study of
characteristics that may predict success. Hispanic Journal of Behavioral Sciences, 17, 33–48.

Lauver, P. J., & Jones, R. M. (1991). Factors associated with perceived career options in American Indian,
White, and Hispanic rural high school students. Journal of Counseling Psychology, 38, 159–166.

Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and
academic interest, choice, and performance. Journal of Vocational Behavior, 45, 79–122.

Lent, R. W., Brown, S. D., & Hackett, G. (2000). Contextual supports and barriers to career choice: A
social cognitive analysis. Journal of Counseling Psychology, 47, 36–49.

Leong, F. T. L., & Chou, E. L. (1994). The role of ethnic identity and acculturation in the vocational
behavior of Asian Americans: An integrative review. Journal of Vocational Behavior, 44, 155–172.

Leong, F. T. L., & Gim, R. H. C. (1995). Career assessment and intervention for Asian Americans. In F. T.
L.Leong (Ed.), Career development and vocational behavior of racial and ethnic minorities (pp. 193–226).
Mahwah, NJ: Lawrence Erlbaum.

Leong, F. T. L., & Serafica, F. C. (1995). Career development of Asian Americans: A research area in

need of a good theory. In F. T. L.Leong (Ed.), Career development and vocational behavior of racial and
ethnic minorities (pp. 67–102). Mahwah, NJ: Erlbaum.

Lessenger, L. H. (1997). Use of Acculturation Rating Scale for Mexican Americans—II with substance
abuse patients. Hispanic Journal of Behavioral Sciences, 19, 387–398.

Loehlin, J. C. (1998). Latent variable models: An introduction to factor, path, and structural analysis.
Mahwah, NJ: Erlbaum.

Luzzo, D. A. (1992). Ethnic group and social class differences in college students’ career development.
Career Development Quarterly, 41, 161–173.

MacCallum, R. C., Roznowski, M., & Necowitz, L. B. (1992). Model modifications in covariance structure
analysis: The problem of capitalization on chance. Psychological Bulletin, 111, 490–504.

McNeill, B. W., Prieto, L. R., Neimann, Y. F., Pizarro, M., Vera, E. M., & Gomez, S. P. (2001). Current
directions in Chicana/o psychology. The Counseling Psychologist, 29, 5–17.

McWhirter, E. H. (1997). Perceived barriers to education and career: Ethnic and gender differences.
Journal of Vocational Behavior, 50, 124–140.

McWhirter, E. H., Hackett, G., & Bandalos, D. L. (1998). A causal model of the educational plans and
career expectations of Mexican American high school girls. Journal of Counseling Psychology, 45, 166–
181.

Nauta, M. M., Epperson, D. L., & Kahn, J. H. (1998). A multiple-group analysis of predictors of higher
level career aspirations among women in mathematics, science, and engineering majors. Journal of
Counseling Psychology, 45, 483–496.

Niemann, Y. F. (2001). Stereotypes about Chicanas and Chicanos: Implications for counseling. The
Counseling Psychologist, 29, 55–90.

O’Brien, K. M. (1992). Career Aspiration Scale.(Available from K. M. O’Brien, Psychology Department,
University of Maryland, College Park, MD 20742)

O’Brien, K. M. (1996). The influence of psychological separation and parental attachment on the career
development of adolescent women. Journal of Vocational Behavior, 48, 257–274.

O’Brien, K. M., Bikos, L. H., Epstein, K. L., Flores, L. Y., Dukstein, R. D., & Kamatuka, N. A. (2000).
Enhancing the career decision-making self-efficacy of upward bound students. Journal of Career
Development, 26, 277–293.

O’Brien, K. M., Dukstein, R. D., Jackson, S. L., Tomlinson, M. J., & Kamatuka, N. A. (1999). Broadening
career horizons for students in at-risk environments. Career Development Quarterly, 47, 215–229.

O’Brien, K. M., & Fassinger, R. E. (1993). A causal model of the career orientation and career choice of
adolescent women. Journal of Counseling Psychology, 40, 456–469.

O’Brien, K. M., Friedman, S. M., Tipton, L. C., & Linn, S. G. (2000). Attachment, separation, and women’s
vocational development: A longitudinal analysis. Journal of Counseling Psychology, 47, 301–315.

O’Brien, K. M., Gray, M. P., Tourajdi, P. P., & Eigenbrode, S. P. (1996, August). The operationalization of
women’s career choices: The Career Aspiration Scale. In V. S.Solberg & K. M.O’Brien (Chairs),
Promoting women’s career development into the next millennium and beyond Symposium conducted at
the 104th Annual Convention of the American Psychological Association, Toronto, Ontario, Canada.

Ortiz, V. (1995). The diversity of Latino families. In R. E.Zambrana (Ed.), Understanding Latino families:
Scholarship, policy, and practice (pp. 18–39). Thousand Oaks, CA: Sage.

Quintana, S. M., & Maxwell, S. E. (1999). Implications of recent developments in structural equation
modeling for counseling psychology. The Counseling Psychologist, 27, 485–527.

Ramos, L., & Sanchez, A. R. (1995). Mexican-American high school students: Educational aspirations.
Journal of Multicultural Counseling and Development, 23, 212–221.

Reid, P. C., Haritos, C., Kelly, E., & Holland, N. E. (1995). Socialization of girls: Issues of ethnicity in
gender development. In H.Landrine (Ed.), Bringing cultural diversity to feminist psychology: Theory,
research, and practice (pp. 93–111). Washington, DC: American Psychological Association.

Reyes, O., Kobus, K., & Gillock, K. (1999). Career aspirations of urban, Mexican American adolescent
females. Hispanic Journal of Behavioral Sciences, 21, 366–382.

Rodriguez, N. (1996). Predicting the academic success of Mexican American and White college students.
Hispanic Journal of Behavioral Sciences, 18, 329–342.

Stephenson, M. (2000). Development and validation of the Stephenson Multigroup Acculturation Scale
(SMAS). Psychological Assessment, 12, 77–88.

Stevens, G., & Featherman, D. L. (1981). A revised socioeconomic index of occupational status. Social
Science Research, 10, 364–396.

Tang, M., Fouad, N. A., & Smith, P. L. (1999). Asian Americans’ career choices: A path model to examine
factors influencing their career choices. Journal of Vocational Behavior, 54, 142–157.

Tinajero, J., Gonzalez, J. L., & Dick, F. (1991). Raising career aspirations of Hispanic girls. Bloomington,
IN: Phi Delta Kappa Educational Foundation.

U.S. Bureau of the Census. (1991). The Hispanic population in the United States: March 1991. (Current
Population Report, Series P-20, No. 455). Washington, DC: U.S. Government Printing Office.

U.S. Bureau of the Census. (1996). Statistical abstract of the United States: 1996. (116th ed.).
Washington, DC: U.S. Government Printing Office.

U.S. Bureau of the Census. (1998). Statistical abstract of the United States: 1998. (118th ed.).
Washington, DC: U.S. Government Printing Office.

Valenzuela, A. (1993). Liberal gender role attitudes and academic achievement among Mexican-origin
adolescents in two Houston inner-city Catholic schools. Hispanic Journal of Behavioral Sciences, 15,
310–323.

Vasquez, M. J. T. (1982). Confronting barriers to the participation of Mexican-American women in higher
education. Hispanic Journal of Behavioral Sciences, 4, 147–165.

Vasquez-Nuttal, E., Romero-Garcia, I., & De Leon, B. (1987). Sex roles and perceptions of femininity and
masculinity of Hispanic women: A review of the literature. Psychology of Women Quarterly, 11, 409–425.

Wycoff, S. E. (1996). Academic performance of Mexican American women: Sources of support that serve
as motivating variables. Journal of Multicultural Counseling and Development, 24, 146–155.

Submitted: February 2, 2000 Revised: March 19, 2001 Accepted: March 21, 2001

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Source: Journal of Counseling Psychology. Vol. 49. (1), Jan, 2002 pp. 14-27)
Accession Number: 2001-05923-002
Digital Object Identifier: 10.1037/0022-0167.49.1.14