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Evaluating FOCUS-2's effectiveness in enhancing first-year college students' social cognitive career development.

This study examined the effectiveness of the computer-assisted career guidance system, FOCUS-2, on 1st-year college students' social cognitive career development. Specifically, the authors assessed career decision self-efficacy (CDSE) and assessment of attributions for career decision making (AACDM) using repeated measures analyses of variance with a sample of 1st-year college students (N = 420). Effectiveness was measured as a change in participants' CDSE and AACDM scores from pretest to posttest. Results demonstrated that participants' interaction with FOCUS-2 was associated with increases in participants' CDSE and alteration to a less optimistic style for AACDM. Gender, race, academic major status, and the amount of time using FOCUS-2 were also considered. Implications for practice are explored.

Keywords: FOCUS, computer-assisted career guidance system, social cognitive career

Career services at colleges and universities generally encompass individual and group career counseling, career workshops, and the administration and interpretation of various career-related assessments. Because traditional-age college students are increasingly oriented toward using computers and the Internet as tools for research, recreation, and decision making (Robinson, Meyer, Prince, McLean, & Low, 2000), it is prudent that academic institutions and university career centers offer services congruent with their students' lifestyles and practices. Evaluating the effectiveness of vocational resources that use technology and are accessible online is not only critical in ensuring effective transmission of well-founded career resources to college students but is also an ethical duty of counselors and psychologists (Davidson, 2001).

Computer-Assisted Career Guidance Systems

Within the past 40 years, computer-assisted career guidance (CACG) systems have supported career counselors and university career centers providing high-tech career guidance to interested clients. A meta-analysis of career intervention research by Whiston, Sexton, and Lasoff (1998) revealed that CACG systems are cost-effective interventions. However, a meta-analysis by Whiston, Brecheisen, and Stephens (2003) highlighted how completely self-directed interventions were not nearly as effective as other types of career interventions (e.g., individual, group career counseling). Specifically, Whiston and colleagues found that it was not until a counselor was involved in part of the process that there were better outcomes in comparison with self-directed interventions (including CACG systems). Nevertheless, CACG systems have served consumers since the 1960s (Harris-Bowlsbey & Sampson, 2001; Watts, 1993) and continue to be an important area of focus for vocational research and career development.

CACG systems are always evolving because of theoretical and technological advances, changing consumer needs, and market competition (Sampson et al., 1990). CACG system users can autonomously engage in tasks designed for career-related self-discovery and exploration at their own time, location, and pace. Other advantages of CACG systems include a centralized location for career information (Davidson, 2001) and an interactive, visually pleasing career-planning experience (Robinson et al., 2000).

Previous limitations identified within the existing CACG system literature include (a) a focus on user satisfaction over career-related gains; (b) failure to examine potential differential effects of CACG systems associated with gender, ethnicity, and socioeconomic status; and (c) reliance on small, convenient samples (Fowkes & McWhirter, 2007). Hinkelman and Luzzo (1997) urged researchers to gather more diverse samples and consider important multicultural variables (e.g., gender, race). Another glaring omission from the existing CACG system literature is an examination of how the amount of time spent using a system affects the user (Cairo, 1983). In Taber and Luzzo's (1999) review of one CACG system (i.e., DISCOVER), researchers were found to be inconsistently reporting which modules within the CACG system were used by participants. Taber and Luzzo suggested that researchers account for exposure to additional career services, such as talking with a career counselor prior to, concurrent with, or subsequent to using a CACG system. Without consideration of the contextual data, it is a fallacy to directly attribute changes in vocational outcomes solely to a CACG system.

A significant amount of research on CACG systems has focused on DISCOVER (Rayman & Harris-Bowlsbey, 1977) and SIGI (Katz, 1973). Various web-based career assessments from the Kuder Career Planning System (Kuder, Inc., 2011) have also surfaced over the years with upgrades and modifications over time. More recently, researchers have begun to consider other CACG systems commonly used among college career centers (e.g., Betz & Borgen, 2009), such as the CACG system FOCUS (Career Dimensions Inc., 2007), and other Internet-based self-help career assessments (e.g., Gati & Asufin-Peretz, 2011).

FOCUS-2 (Career Dimensions, Inc., 2009, 2010) is an updated version of FOCUS (Career Dimensions, Inc., 2007), which was a modified version of the original CACG system, the Education and Career Exploration System (ECES; Myers, Lindeman, Thompson, & Patrick, 1975). ECES was initially developed by the IBM Corporation and designed with consultation with Donald Super, Roger Myers, David Tiedeman, David Campbell, and Frank Minor (Career Dimensions, Inc., 2010). Betz and Borgen (2009) published findings on an earlier version of FOCUS, and thus research on the revised version, FOCUS-2, remains vacant among the published vocational psychology literature.

FOCUS-2 enables its users to utilize a variety of career-related features, including self-assessment and exploration of various career options. FOCUS-2 users are able to complete separate assessments involving their interests, personality, self-reported skills, values, and leisure activities (Career Dimensions, Inc., 2009). The results of these assessments are ultimately linked to corresponding occupations. FOCUS-2 users are also able to research more than 1,200 occupations by name or industry, perform a search about various academic majors, and view important characteristics (e.g., salary, skills, educational requirements) of two occupations side by side (Career Dimensions, Inc., 2009). In addition, over 500 brief (1-2 minute) video clips that depict various work tasks are easily accessible. To date, FOCUS-2 is a popular CACG system used at several different colleges and universities across the United States (Career Dimensions, Inc., 2009).

CACG systems, like FOCUS-2, hold promise to offer users an individualized experience by which they have the opportunity to be in personal command of career-related tasks linked to their career development. Maples and Luzzo (2005), in their evaluation of DISCOVER, posited that comparable CACG systems may grant a rewarding experience, providing a sense of personal achievement and empowerment concerning future activities that support career decision making. However, interaction with a CACG system might also give rise to users' vocational confusion or feeling overwhelmed by the vast array of career information presented within the system. Typically, individuals offer explanations related to events in their lives based on a set of general personal beliefs and an assessment of particular circumstances (Bell-Dolan & Anderson, 1999). For that reason, it is likely that 1st-year college students who use FOCUS-2 may begin to consider their personal attributions toward career decision making.

Assessment of Attributions for Career Decision Making (AACDM)

The process of making a career decision is likely to be a new occurrence for many college students, particularly 1st-year college students. According to Weiner's (1979, 1985, 1986) attribution theory, individuals are likely to offer explanations about various outcomes and events in their lives that are perceived as significant or novel. These causal attributions (i.e., explanations) are hypothesized to directly influence individuals' subsequent cognitions and emotions (Perry, Hechter, Menec, & Weinberg, 1993). Perry et al. (1993) noted that the defined properties of an attribution are considered to influence individuals' motivation and behavior related to future events. An individual's attributional style toward making career decisions can be measured with the AACDM (Luzzo & Jenkins-Smith, 1998). According to Maples and Luzzo's (2005) application of attribution theory to career decision making, someone who believes that career decision making is susceptible to internal, dynamic, and controllable forces is likely to believe that career-related events and decisions are due to internal factors within his or her control that can be changed with varying degrees of effort (i.e., optimistic attributional style). Maples and Luzzo reported that individuals who used the CACG system, DISCOVER, were more effective in enhancing one component of an attributional style (i.e., sense of control regarding the career decision-making process) compared with individuals who did not use the CACG system. To date, no other study has evaluated the effectiveness of other CACG systems as an intervention for modifying one's attributional style.

Career Decision Self-Efficacy (CDSE)

Closely related to attributional style is another social cognitive component of career decision making--namely, CDSE--which refers to how confident an individual is that he or she can perform various career-related tasks (Betz & Taylor, 2005). Taylor and Popma (1990) reported a moderate negative relationship between locus of control and CDSE (i.e., the more external a person's locus of control, the less confident he or she will be in performing career decision-making tasks). A person's level of self-efficacy about making career decisions is an important precursor to the likelihood of engaging in favorable career-related behaviors. By understanding a person's assurance in relation to various tasks, career counselors can more effectively understand whether the person is likely to approach or avoid certain career-related behaviors (Maples & Luzzo, 2005), which in turn affect the likelihood of engaging in new experiences and learning opportunities to develop career interests (Betz & Borgen, 2000).

CACG systems have also been studied in relation to CDSE. For instance, Fukuyama, Probert, Neimeyer, Nevill, and Metzler (1988) found that DISCOVER had a positive effect on participants' career self-efficacy and career decision making. Chapman, Katz, Norris, and Pears (1977) found that SIGI had a positive impact on numerous dimensions of career decision making (e.g., better understanding of values and career goals, more knowledge about sources of satisfaction from a job, more detail and accurate information about occupations, more definite overall career plans, and more confidence in their decision making). More recently, Betz and Borgen (2009) compared the effectiveness of two distinct CACG systems--FOCUS and CAPA--and found that both systems led to significant increases in CDSE.

Purpose of Study

The purpose of this study was to examine the influence of a recently revised CACG system (i.e., FOCUS-2) on the CDSE and AACDM of 1st-year college students. Specifically, CDSE and AACDM were assessed pre- and postcompletion of the FOCUS-2 intervention. The goal of this study was to assess the effectiveness of FOCUS-2 on these social cognitive career variables. This study was also designed to assess the impact of gender, race, and the status of selection of an academic major on potential differences in changes in CDSE and AACDM scores from pretest to posttest. The relationship between the self-reported amount of time spent using FOCUS-2 and changes in CDSE and AACDM scores was also appraised. Lastly, this study collected descriptive data regarding other career-related tasks and interventions (e.g., contact with family or friends about careers, an appointment at the university career center) that took place in conjunction with the completion of FOCUS-2 to provide additional information about the sample.

Method

Participants

Participants included 420 male (40%) and female (60%) 1st-year college students (mean age = 18.08 years, SD = 0.31, range = 18-21). Participants' race comprised 63.8% European American/White, 13.3% Hispanic American/Latino/Latina, 11.9% African American/Black, and 11.0% Asian American participants. All participants were enrolled as 1st-year students at a small, 4-year, private Catholic university in the Northeast. In terms of self-reported academic major status, 262 (62.4%) identified as "declared," 64 (15.2%) identified as "undecided," 48 (11.4%) identified as "declared but uncertain," and 46 (11.0%) identified as "tracking a major." Participants who selected "tracking a major" have intention to declare a certain academic major but have not yet been admitted to the specific program (e.g., wanting to declare a major as nursing but have not yet been accepted to the College of Nursing). Considering the total population (N= 1,119) of 1st-year students at the university who were 18 years or older at the beginning of the study, all students were invited to participate, and the response rate for this study was 37.5%.

Measures

Demographic questionnaires. Participants completed two demographics questionnaires, one during the pretest and one during the posttest administration of this study. On the pretest demographic questionnaire, questions included information about age, gender, year in college (student status), self-reported academic major status, and race. The demographic questionnaire for the posttest included specific questions concerning the self-reported amount of time (e.g., 30 minutes, 1 hour, 2 hours, 3 hours) each participant spent using FOCUS-2, as well as other career-related activities performed between the time of completing FOCUS-2 and when participants completed the posttest measures.

AACDM. The AACDM (Luzzo & Jenkins-Smith, 1998) was used to measure participants' attributional style toward making career decisions. The AACDM is a nine-item questionnaire with a factor structure consistent with Weiner's (1979, 1985, 1986) three-dimensional taxonomy for classifying attributions: causality, stability, and controllability. Luzzo and Jenkins-Smith (1998) reported that internal reliability estimates ranged from .64 (stability) to .89 (causality). There are three items per dimension, and each item was answered on a score continuum of 1 to 5; scores on each dimension range from 3 to 15, with higher scores indicating more internal, controllable, and stable perceptions of attributions for career decision making (i.e., optimistic attributional style for career decision making). The AACDM total score ranges from 9 to 45, with higher scores reflecting an optimistic attributional style for career decision making.

CDSE--Short Form. The CDSE--Short Form (CDSE-SF; Betz, Klein, & Taylor, 1996) was used to measure self-efficacy expectations for successfully completing tasks requisite to making good career decisions. The CDSE-SF contains five subscales comprising 25 items measuring the five career choice competencies of Crites's (1978) career maturity model: Self-Appraisal, Gathering Occupational Information, Goal Selection, Planning, and Problem Solving. Items are rated on a 5-point scale ranging from 1 (no confidence at all) to 5 (complete confidence). Research (Betz et al., 1996; Betz & Luzzo, 1996) has shown that the 25-item CDSE-SF is nearly as reliable and as valid as the original and lengthier Career Decision-Making Self-Efficacy Scale (Taylor & Betz, 1983). A total score is computed by summing scores for the 25 items and dividing that number by 25; higher scores (e.g., 5) indicate greater levels of CDSE.

Procedure

The dean of freshman studies at a private, Catholic northeastern university granted us permission to investigate 1st-year college students. This study was also approved by the institutional review board of the university. A promotional flyer was electronically posted within a 1st-year experience course in which all 1st-year undergraduate students were enrolled on Blackboard, an online database that includes information pertinent to corresponding academic courses. The course's overarching goal is to provide 1st-year students with academic and personal success. Students are familiarized with various campus resources that aid in academic and personal success. The promotional flyer included detailed information about the study, instructions for participation, as well as hyperlinks to access the pretest survey, FOCUS-2, and the posttest survey. First-year students were encouraged to complete the FOCUS-2 assessment at their own pace and to complete all modules within FOCUS-2. Only the detailed flyer was used to promote the study; no additional reminders were sent to students.

The promotional flyer was posted to Blackboard at the beginning of the fall 2010 semester (mid-September), and the survey concluded the 1st week of November. Because the end of the fall semester (last week of November) is dedicated to discussions surrounding career decision making, the timing of the class did not influence the results of the study since the career-focus discussions were held after all data were collected. Participants completed both the CDSE-SF and AACDM before and after using FOCUS-2. Based on self-report, participants indicated that on average they spent 1.80 hours (SD = 0.91) using FOCUS-2, with a range of 0.5 to 7.0 hours. All potential participants had the option to voluntarily take part in the study. There was no penalty or coercion for not completing the study, and the decision to participate or not was completely voluntary, without any incentive.

Results

Means and standard deviations across the CDSE-SF and AACDM for the pretest and posttest are presented in Table 1. We conducted a one-way repeated measures analysis of variance (ANOVA) to assess whether participants demonstrated significant changes in total CDSE score after using FOCUS-2. The results for the repeated measures ANOVA indicated a significant effect for total CDSE, Wilks's [lambda] = .96, F(1, 419) = 19.12, p < .0005, partial [[eta].sup.2] = 0.044. Effect size was calculated using partial [[eta].sup.2], which is an estimate of effect size (Gravetter & Wallnau, 2013). In addition to participants' overall confidence in their abilities to make career decisions, participants demonstrated significant changes from pretest to posttest on four of the five subscales of the CDSE-SF: Self-Appraisal, F(1, 419) = 38.64, p < .0005, partial [[eta].sup.2] = 0.084; Goal Selection, F(1, 419) = 34.21, p < .0005, partial [[eta].sup.2] = 0.075; Planning, F(1, 419) = 19.55, p < .0005, partial [[eta].sup.2] = 0.045; and Problem Solving, F(1, 419) = 58.79, p < .0005, partial [[eta].sup.2] = 0.123.
Table 1 Means and Standard Deviations for Total Pre-
and Career Decision Self-Efficacy (CDSE) and Assessment
of Attributes for Career Decision Making (AACDM) Scores

 Pretest Posttesl

Measure M SD M SD

CDSE total score 3.44 0.62 3.56 0.69

Self-appraisal 20.00 3.00 20.72 3.21

Occupational information 20.26 3.03 20.50 3.47

Goal selection 19.72 3.30 20.47 3.52

Planning 19.10 3.50 19.62 3.65

Problem solving 18.68 3.25 19.68 3.56

AACDM composite score 36.58 3.45 36.18 4.00

Controllability 13.35 1.80 13.08 1.97

Stability 9.91 2.12 10.01 2.12

Causality 13.32 1.58 13.09 1.86


The results for the repeated measures one-way ANOVA assessing whether participants demonstrated significant changes in AACDM from pretest to posttest after using FOCUS-2 also indicated a significant effect for the composite AACDM score, Wilks's [lambda] = .99, F(1, 419) = 5.97, p = .015, partial [[eta].sup.2] = 0.014. However, scores from pretest to posttest demonstrated a significant decrease in AACDM. The subscale results were as follows: Controllability, F(1, 419) = 10.01, p = .002, partial [[eta].sup.2] = 0.023; Causality, F(1, 419) = 8.29, p = .004, partial [[eta].sup.2] = 0.019; and Stability, F(1, 419) = 0.894, p = .345.

The participants' self-reported amount of time spent between pretest and posttest was, on average, 3.67 days (SD = 8.96). There was no stringent stipulation placed on participants for this study, because the flexible pretest and posttest dates were intended to allow participants the autonomy to spend as much time as they desired within FOCUS-2. The correlation between the amount of time spent using FOCUS-2 and the change in AACDM scores from pretest to posttest was not statistically significant, r(418) =-.012, p = .802. In addition, the correlation between the amount of time spent using FOCUS-2 and the change in CDSE scores from pretest to posttest was not statistically significant, r(418) =-.073, p = .133.

Table 2 outlines both the CDSE and AACDM pre- and posttest scores for the other variables of interest (i.e., gender, race, academic major) in this study. Several ANOVAs were conducted to evaluate the relationship among race, gender, and the status of selection of an academic major with the difference in AACDM scores from pre- to posttest after using FOCUS-2. The ANOVA for race and change in AACDM from pre- to posttest was not significant, Wilks's [lambda] = .99, F(3, 416) = 1.55, p = .20. The ANOVA for status of selection of an academic major and change in AACDM from pre- to posttest also was not significant, Wilks's [lambda] = .90, F(3, 416) = 1.39, p = .24. However, the ANOVA for gender and change in AACDM from pre- to posttest was significant, Wilks's [lambda] = .99, F(1, 418) = 5.67, p = .018, partial [[eta].sup.2] = .02, whereby men (-.879) adopted a less optimistic attributional style for career decision making compared with women (-.086) after using FOCUS-2.
TABLE 2 Means and Standard Deviations for Career Decision
Self-Efficacy (CDSE) and Assessment of Attributes for Career
Decision Making (AACDM) Scores by Gender, Race, and Academic
Major

 CDSE AACDM
 (a) (b)

 Pretest Posttest Pretest

Variable M SD M SD M SD

 Gender

Men (n = 166) 3.42 0.67 3.53 0.69 36.10 3.56

Women (n = 254) 3.46 0.58 3.58 0.69 36.89 3.35

 Race

European 3.41 0.62 3.54 0.69 36.67 3.35
American/White (n
= 268)

Asian 3.33 0.59 3.37 0.74 35.43 3.83
American/Asian (n
= 46)

Hispanic 3.54 0.57 3.63 0.68 36.18 3.47
American/
Latino/Latina (n
= 56)

African 3.60 0.64 3.78 0.65 37.58 3.38
American/Black (n
= 50)

 Academic
 Major

Declared major (n 3.55 0.62 3.68 0.66 36.72 3.53
= 262)

Declared major, 3.10 0.47 3.25 0.56 36.19 3.66
but uncertain (n
= 48)

Tracking a 3.43 0.58 3.48 0.66 36.91 2.81
major (n = 46)

Undecided (n = 3.25 0.62 3.34 0.80 36.05 3.38
64)

Total (N = 420) 3.44 0.62 3.56 0.69 36.58 3.45

 Posttest

Variable M SD

Men (n = 166) 35.22 3.90

Women (n = 254) 36.80 3.95

European 36.18 3.98
American/White (n
= 268)

Asian 35.04 4.29
American/Asian (n
= 46)

Hispanic 36.62 3.68
American/
Latino/Latina (n
= 56)

African 36.74 4.14
American/Black (n
= 50)

Declared major (n 36.52 3.92
= 262)

Declared major, 35.44 4.12
but uncertain (n
= 48)

Tracking a 35.70 4.27
major(n = 46)

Undecided (n = 35.69 4.00
64)

Total (N = 420) 36.18 4.01

(a) Total score.

(b) Composite score.


We also conducted several ANOVAs to evaluate the relationship among race, gender, and status of selection of an academic major and the change in CDSE scores from pretest to posttest after using FOCUS-2. The ANOVA for race and change in CDSE scores from pre- to posttest was not significant, Wilks's [lambda] = .99, F(3,416) = 0.56, p = .65. The ANOVA for status of selection of an academic major and change in CDSE scores from pre- to posttest also was not significant, Wilks's [lambda] = .99, F(3,416) = 0.41, p = .75. Lastly, the ANOVA for gender and change in CDSE from pre- to posttest was not significant, Wilks's [lambda] = 1.0, F(l,418) = 0.06, p = .80.

Data were collected on the proportion of participants who completed specific assessments and modules within FOCUS-2. The majority of participants (98.2%) completed all five of the available assessments within FOCUS-2; however, only 19% of participants reported exploring career occupations on their own accord within the FOCUS-2 system. Furthermore, participants were more inclined to search more general modules within FOCUS-2, for example, "What can I do with a major in ... ?" (90%) and "Search by industry" (82%), compared with more specific and presumably more sophisticated modules, for example, "Compare 2 occupations side by side" (8%) and "Search by occupation name" (25%).

We also collected data for the external activities that participants completed in between the pretest and the posttest to provide descriptive information concerning other activities participants took part in near their engagement with the FOCUS-2 system. The majority of the sample (n = 289, 69%) did not perform any external vocational activities in between the completion of the pre- and posttest measures. Of the 131 participants (31%) who took part in distinct activities between completion of the pre- and posttest, 23% spoke with a faculty, friend, or family member about careers; 19% researched careers and academic majors outside of FOCUS-2, and 3% or less attended an individual, group, or workshop appointment at the university career center. Participants were able to select as many activities as applicable.

Discussion

Results of the present study reveal that FOCUS-2, as a career intervention, was associated with statistically significant gains in CDSE from pretest to posttest for 1st-year college students at a small, private university in the Northeast. In terms of practical significance, these gains, however, were modest, with small effect sizes except for the gain on the CDSE-SF Problem Solving subscale, where changes were moderate (medium effect size). The findings of this study replicate previous research studies (Betz & Borgen, 2009; Fukuyama et al., 1988; Maples & Luzzo, 2005) that demonstrated increased confidence in engaging in career decision-making activities after using other CACG systems (i.e., CAPA, DISCOVER, FOCUS). Results of this study can now place FOCUS-2 in a comparable category with other CACG systems supported by major testing companies (e.g., DISCOVER, SIGI), as increases in 1st-year college students' CDSE were associated with participation in the FOCUS-2 CACG system.

An unexpected finding, dissimilar to Maples and Luzzo's (2005) study, was that participation in the FOCUS-2 system was associated with an adoption of a more pessimistic style of career decision making for 1st-year college students in our study (i.e., participants believed that career decision making was less under their control and influenced by external factors). It is prudent to consider the economic recession and the challenging vocational landscape of the United States during the time of this study. FOCUS-2 allows participants to acquire information on occupational salary, projected outlook, and the capability for job advancement. Thus, a cohort effect may have occurred in which less assurance and less controllability were perceived by FOCUS-2 users, who believed less that career decisions are a direct result of their efforts because of a greater awareness of the recession and other uncontrollable factors (e.g., the economy).

It is also likely that FOCUS-2 users may have felt overwhelmed or puzzled after using the CACG system. For instance, once career self-assessments are completed, FOCUS-2 does not rank order specific occupations compared with other well-established vocational assessments (e.g., the Strong Interest Inventory; Harmon, Hansen, Borgen, & Hammer, 1994). Instead, several corresponding careers are provided in alphabetical order for the user to peruse independently. This notion is related to Gelatt's (1989) stance that when too much information is gathered during one's decision-making process, individuals may have difficulty processing it all effectively. The happenstance learning theory (Krumboltz, 2009) is yet another possible explanation for the adoption of a "pessimistic" attributional style for career decision making after using FOCUS-2. This theory posits that it is implausible to foretell the destiny of individuals' careers because it is a by-product of both planned and unplanned events.

Further consideration for participants adapting a less optimistic attributional style after using FOCUS-2 includes the necessity to approach AACDM with a multiculturally sensitive lens. For example, 40 years ago, MacDonald (1971) considered powerlessness and external locus of control to be one and the same. However, we know that individuals from different cultural backgrounds may actually operate from a different locus of control. For instance, Hamid (1994) found that individuals from a collectivist society (e.g., Taiwan) are more likely to possess an external locus of control compared with individuals from an individualistic society (e.g., the United States). Individuals from a collectivistic culture tend to place more emphasis on the goals of the group and to define the self in relation to others (Triandis, 1995). These findings suggest that an external locus of control may be more commonplace in different cultures and is not necessarily a sign of pessimism.

In terms of time spent using FOCUS-2, the average time in this study (1.80 hours) was similar to the 2-hour modal average of Taber and Luzzo's (1999) study assessing DISCOVER. There was no significant relationship between the amount of time spent using FOCUS-2 in relation to CDSE and AACDM. These findings are similar to the findings of Reardon, Peterson, Sampson, Ryan-Jones, and Shahnasarian (1992). Although it is possible that no relationship exists between time spent using a CACG system and relevant outcomes, it is also possible that students inaccurately (i.e., over- or under-) reported the amount of time they spent using the CACG system. Furthermore, with the tendency for college students to multitask on the computer (e.g., checking Facebook and e-mail), it is possible that these activities may have contributed to inaccurate perceptions of time spent using FOCUS-2.

This study assessed for changes in participants' CDSE and AACDM scores from pre- to posttest with regard to their race, gender, and the status of selection of an academic major after using FOCUS-2. No significant differences were found, except for the gender difference in how participants responded to FOCUS-2. Specifically, compared with women, men adopted a less optimistic attributional style for career decision making from pretest to posttest. One possible explanation is the gender-role stereotype of men and how this may have been amplified when they were in distress (e.g., Greenhaus & Parasuraman, 1999). In traditional male gender roles, men are expected to solve problems independently and rely less on forms of assistance (Stokes & Wilson, 1984). Thus, men may have experienced some frustration for reliance on the assistance of a CACG system like FOCUS-2. Another possible explanation is that FOCUS-2 may have received such a multitude of results from both the career assessments and the exploration of various occupations that it shifted men's beliefs toward the notion that career-related events and decisions are due to external factors outside of their control because of an expansion of their existing schemas about possible career options.

A possible explanation for not finding significance for Other variables of interest in this study (race, gender, selection of academic major) is that participants' cultural identity or level of acculturation to which individuals identified with their particular racial group was not comprehensively considered. Duffy and Klingaman (2009) found a relationship between higher levels of ethnic identity achievement and career decidedness, choice comfort, indecisiveness, and choice importance among students of color. Concerning selection of an academic major, Tillar and Hutchins (1979) stated that the majority of college students, particularly 1st- and 2nd-year students, typically lack the knowledge and experience required to proficiently execute a decision concerning their choice of major. Thus, the different categorical levels used in this study for selection of an academic major (i.e., declared, declared but uncertain, tracking a major, and undecided) may not yet be as clearly defined among the population of 1st-year college students.

It is important to discuss briefly the role of effect size and practical significance in the present study. Effect sizes in this study were relatively small (ranging from 0.01 to 0.12), suggesting that FOCUS-2 did not have a large effect on the constructs of interest (i.e., CDSE and AACDM). However, the fairly large sample size in this study may have resulted in a level of statistical power in which small and practically negligible change could be found to be statistically significant. At the same time, as Campbell (2005) highlighted, although effect sizes can inform practical significance, they are not inherent indices of the meaningfulness of results.

Limitations of the Study

The following are limitations of the present study. First, the measures are all self-report, and all participants are volunteers. Second, this study did not use random assignment and did not include a control group to authenticate whether the changes observed in career decision and attributional style are due to FOCUS-2's activities or the students' maturation process. Third, the sample consisted of a convenience sample of 1st-year students at a single private university, which limits the generalizability of the results. The sample also excluded other undergraduate students and transfer students who are in their 2nd, 3rd, and 4th year of undergraduate studies; thus, this study is not fully generalizable to all undergraduate college students.

It is important to consider the brief amount of time that passed between completion of the pretest and posttest measures. Specifically, an average of 3.67 days (SD= 8.96) elapsed between completion of the pretest and posttest in this study. Although this relatively short time span may have been useful to create a brief window to focus on the impact of FOCUS-2, it simultaneously may have affected other aspects of the study, which is analogous to Gelso's (1979) bubble hypothesis. Furthermore, the brief time between pre- and posttest may have also influenced the low percentage of participants who engaged in other career-related activities outside of FOCUS-2 (e.g., only 12 participants sought formal career assistance at the university career center). It may have been more useful to assess future intentions to access services within this study.

Implications for Practice

Because of the ethical concerns with the use of CACG systems (e.g., Barak, 2003; Davidson, 2001), we strongly recommend that counseling and career professionals offer feedback sessions to further discuss the results of the FOCUS-2 assessment. Within this study, the university career center had offered several workshops to focus on interpretation of the results after collecting data on the pretest and posttest, the majority occurring at the end of the fall semester. As Whiston et at. (2003) documented, having a counselor involved in the process has been shown to increase the effectiveness of CACG systems. Future possibilities for practice may include supplementing additional resources to CACG systems, including videoconferences, podcasts, or an on-call counselor to discuss results or address concerns. Clients should also be encouraged to seek follow-up with the information that they gain from CACG systems (e.g., Brown et al., 2003), such as the workshops that were made available by the university career center in the fall semester within this study.

Future Directions for Research

The results of this study give credence to the need to examine the usefulness of FOCUS-2 with other populations (e.g., advanced undergraduate students, graduate students, community college students). For instance, advanced undergraduate students are likely to be actively seeking employment and working toward crystallizing their occupational choice, which may align well with FOCUS-2's modules that emphasize specific occupations rather than academic majors. As previously noted, future studies may want to assess participants' intentions to access career-related services as opposed to whether or not they received services within a fixed time period, as in this study. Furthermore, it is necessary to monitor the lasting effects of CDSE and AACDM for longer term follow-up studies or assess the effectiveness of FOCUS-2 with other vocational constructs, particularly compared to a time frame with a better economy and improved vocational landscape.

Received 12/05/11

Revised 05/27/12

Accepted 05/28/12

DOI: 10.1002/j.2161-0045.2013.00041.x

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David M. Tirpak and Lewis Z. Schlosser, Department of Professional Psychology and Family Therapy, Seton Hall University. David M. Tirpak is now at Counseling and Psychological Services, Lehigh University. Lewis Z. Schlosser is now at Institute for Forensic Psychology, Oakland, New Jersey. We are grateful to Pamela Foley, Peggy Brady-Amoon, Tracy Gottlieb, Nancy Borkowski, Jacquline Chaffin, and Sepideh Soheilian for their helpful contributions to the study and the article. Correspondence concerning this article should be addressed to David M. Tirpak, Counseling and Psychological Services, Lehigh University, 36 University Drive, Johnson Hall, 4th Floor, Bethlehem, PA 18015 (e-mail: davidtirpak@gmail.com).
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Author:Tirpak, David M.; Schlosser, Lewis Z.
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Date:Jun 1, 2013
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