This study examined evidence of concurrent validity for the use of scores from the Campbell Interest and Skill Survey (CISS) with college student-athletes. Agreement between declared college major and interest scores on the CISS was calculated for male student-athletes and nonathletes. Difference between samples was nonsignificant.
Many student-athletes, especially those in sports such as basketball and football, expect to play professionally after completing their college eligibility. Even those who will never receive significant playing time in college seem to ignore the stiff competition for the relatively few professional positions that need to be filled annually. They often seem to attend college to satisfy their interest in athletic competition and to prepare for their athletic careers rather than to take advantage of the other educational opportunities that college offers (Martinelli, 2000).
Time and energy constraints experienced by student-athletes because of practice schedules, games, and team meetings may lead them to neglect academic- and career-planning activities that are a part of other students' college experiences. In some cases, this oversight occurs because the student-athlete firmly believes that she or he will make a smooth transition into professional athletics, making career planning a moot issue. In other cases, athletes find that there is little time in their schedules for academic planning after all other demands on them have been addressed, and vocational considerations are repeatedly postponed (Pearson & Petitpas, 1990). Moreover, college athletic programs often contribute to this effect by sheltering student-athletes from the hassles of everyday life in the interest of maintaining athletes' focus on their sports. For example, assistance frequently is provided in negotiating schedules, maintaining academic records, and ensuring academic eligibility so that achieving athletic goals can be a top priority.
One potential side effect of the sheltering and assistance that many student-athletes receive is that they focus exclusively on their athletic goals and pay little attention to developing other aspects of their identities. Erikson (1968) suggested that the major psychosocial challenge of adolescence is exploring and establishing one's identity. This is a challenge especially likely to be faced by college students as they seek to establish both social and vocational aspects of identity (A. L. Guerra & Braungart-Rieker, 1999). However, this process is dependent on students having the opportunity and inclination to explore their options fully. In an effort to provide this opportunity for student-athletes, several authors have suggested that career counseling programs should become a more structured part of college athletic programs (P. Guerra, 1998; Lefcourt & Hoben, 1998; Pearson & Petitpas, 1990). Most college career counseling programs incorporate assessment of interests as part of the exploration process. St udies have been conducted to demonstrate evidence of validity for instruments such as the Strong Interest Inventory (SII; Hansen & Tan, 1992), the Campbell Interest and Skill Survey (CISS; Hansen & Neuman, 1999), and the Self-Directed Search (Holland, 1985) to predict college majors for college students who are nonathletes. However, little work has been done to demonstrate the efficacy of interest inventories with student-athletes. One exception is a study by Hansen and Sackett (1993) in which the authors examined the predictive accuracy of the SII for college major selection of women who were Division I athletes and of women from the same university who were nonathletes. Their results indicated that the SII predicted college major choice at the same level of accuracy for both the student-athletes and nonathletes.
The CISS is used increasingly with college students to assist them in selecting college majors (Campbell, 1996). However, only one study has been done to examine the evidence of validity for use of scores from the CISS with college students (Hansen & Neuman, 1999), and that study did not include student-athletes in the sample. Research with males suggests that they are more likely than females to overidentify with athletics (Kennedy & Dimick, 1987; Wiechman & Williams, 1997) and that, therefore, it is important to examine the evidence of validity for the use of interest inventories with men who are studentathletes. The purpose of this study, then, was to examine the accuracy of one widely used interest inventory--the CISS--for concurrent prediction of college major choice for male student athletes enrolled in a large university and participating in Division I intercollegiate athletics. We hypothesized that because male student-athletes devote less attention to academic planning, they would show a poorer fit b etween their interests, as measured by the CISS, and their choices of academic majors than would male nonathlete college students. In other words, we hypothesized that the evidence of concurrent validity for the use of scores from the CISS with student-athletes would be less compelling than would the evidence for the use of scores from the CISS with nonathlete students.
Kennedy and Dimick (1987) studied the career attitude maturity of scholarship athletes in the revenue-generating sports of football and basketball and found that athletes in these sports showed significantly lower career maturity than did nonathlete students. A comparison of these results with those of Blann (1985), who studied student-athletes in both revenue-generating and non-revenue-generating sports, suggested that individuals who participate in revenue-generating sports such as football and basketball tended to be particularly overconfident about the probabilities that they would enter professional sports. Moreover, Blann found that athletes in revenue-generating sports scored significantly lower than did athletes in non-revenue-generating sports on measures of career maturity and vocational development. Therefore, we also hypothesized that student-athletes in sports such as basketball and football, who often have higher expectations about professional careers in athletics, would have a poorer match bet ween their declared college majors and their measured interests than would student-athletes in non-revenue-generating sports (i.e., track, gymnastics).
The results for the student-athlete sample used in this study were compared with a nonathlete student sample from the same institution.
Student-athlete sample. The student-athlete sample consisted of 82 men participating in Division I sports at a large midwestern university. With the assistance of the student services office of the intercollegiate athletic program, participants were drawn from both revenue-generating (football and basketball) and non-revenue-generating (baseball, swimming, golf, gymnastics, and cross country/track) sports.
Of the participants, 63% represented revenue-generating sports and 33% represented non-revenue-generating sports. Of the athletes, 73% were Caucasian, 26% were African American, and 1% were Hispanic. Their ages ranged from 18 to 23, with a mean of 19.9 years. Forty-nine percent of the sample were freshmen, 26% were sophomores, 13% were juniors, and 12% were seniors. The participants had declared majors in 33 fields (e.g., management, sociology of law, computer science). The largest number were in the College of Liberal Arts (33%), followed by Education and Human Development (2 1%), Management (11%), Institute of Technology (9%), Human Ecology (5%), and Agriculture (4%). Participants completed the CISS during Session 1. During Session 2, they received an interpretation of their test scores and information on ways in which to use the results to enhance their career planning.
Comparison sample. A nonathlete student sample, collected during the same time frame as the student-athlete sample, was used to provide comparative data for this study. The nonathlete student sample was composed of 55 men enrolled in an introductory psychology course at the same large midwestern university attended by the student-athletes. Their ages ranged from 18 to 23, with a mean of 19.6 years. The composition of the comparison sample was 74.5% Caucasian, 3.6% African American, 16.4% Asian, 3.6% Hispanic, and 1.8% other. By comparison, the general student population on this campus was 80.2% Caucasian, 4.0% African American, 8.3% Asian, 1.9% Hispanic, and 5.77% other. Approximately 50% of the sample were freshmen, 23.6% sophomores, 20% juniors, and 9% seniors. The nonathlete students completed the CISS and received extra credit for participating in the project; they did not receive an interpretation of their results. The nonathlete participants had declared majors in 29 fields. The largest number were in t he College of Management (29%), followed by Liberal Arts (27%), Institute of Technology (18%), Education and Human Development (9%), Human Ecology (5%), and Biological Sciences (5%). Among the general student population on this campus, enrollment was greatest in the College of Liberal Arts (52%), followed by the Institute of Technology (15%), College of Management (6%), Biological Sciences (4%), Agriculture (4%), Education and Human Development (2%), Natural Resources (2%), and Architecture (1%).
Data for each participant included his declared major and his profile of scores on the CISS. The CISS consists of 200 interest items and 120 skill items. An individual's responses to these items are used to compute scores on 7 Orientation Scales, 29 Basic Scales, and 58 Occupational Scales. Only the Occupational Scale interest scores were used for this study. Because the Occupational Scales are composed of heterogeneous items, examining the internal consistency of those scales is not an appropriate test of score reliability. However, an appropriate test of score stability (i.e., the median test-retest reliability coefficient over 90 days) for the interest component of the Occupational Scales has been reported as .87 (Campbell, Hyne, & Nilsen, 1992).
This study replicated the procedures used by Hansen and Newman (1999) to assess the level of agreement between assessed interests and declared college majors of undergraduates who had taken the CISS. First, student-athletes' declared college majors were determined by examining their official university transcripts. Then, students' majors were matched with related Occupational Scales on the CISS. A match was classified as "direct" if the college major was clearly represented by an Occupational Scale (e.g., marketing with the Marketing Director scale). A match was considered "indirect" if no specific Occupational Scale clearly represented the major (e.g., kinesiology was indirectly matched with the Athletic Trainer scale). Two raters used the matching list developed by Hansen and Newman (1999). Any disagreements between the raters were negotiated until 100% agreement was reached.
To be consistent with the published literature on the agreement between the choice of college major and Occupational Scale scores (Hansen & Neuman, 1999; Hansen & Sackett, 1993; Hansen & Tan, 1992), matches were further classified according to level of agreement as either "excellent," "moderate," or "poor" using a range of standard deviation scores for each Occupational Scale calculated by Hansen and Neuman (1999) in their CISS validation study. Each scale's cutoff score for categorization was calculated as 0.5 standard deviation above or below the mean for an excellent match, 0.6 to 1.0 standard deviation below the mean for a moderate hit, and more than 1.0 standard deviation below the mean for a poor hit. The concurrent validity hit rates were estimated by computing the percentage of students who scored high on a CISS Occupational Scale that matched their declared major.
The level of agreement for each student represents how well his chosen major matched the corresponding Occupational Scale score on the CISS. Percentages in each level of agreement (excellent, moderate, and poor) are shown in Table 1. In the student-athlete sample, 65.9% of the matches reached excellent or moderate levels of agreement. In comparison, the nonathlete sample showed that 70.9% of the matches were categorized as excellent or moderate. Although the nonathletes had a higher percentage of matches than did the athletes, the difference between the levels of agreement for the two groups was not statistically significant, [chi square] (1, N= 137) = 0.124, p < .05, w = 0.030. To test the hypothesis that evidence of concurrent validity for scores from the CISS would be strongest first for nonathletes, then for athletes in non-revenue-generating sports, and finally for athletes in revenue-generating sports, the levels of agreement for these three samples were compared. Among the athletes in revenue-generatin g sports, 63.4% of the matches were excellent or moderate, 74.1% of the athletes' matches in non-revenue-generating sports reached the same level of agreement, and, as reported above, 70.9% of the nonathlete samples had matches that were excellent or moderate. As expected, the athletes in revenue-generating sports had a lower percentage of matches than did either the athletes in non-revenue-generating sports or the nonathlete students, but here too the differences among the samples were not statistically significant, [chi square] (1, N 134) 0.36l, p < .05, w = 0.052.
Contrary to the results of researchers such as Petitpas and Champagne (1988); Murphy, Petitpas, and Brewer (1996); and Adler and Adler (1991), these results suggest that student-athletes were just as likely as nonathlete students to choose a major in accordance with their assessed interests. In their parallel study of the agreement between vocational interests and college major for female student-athletes and nonathlete students, Hansen and Sackett (1993) also found no statistically significant differences between the two groups. The combined excellent and good hit-rate percentages were in the same range for female student-athletes who completed the SII and for male student-athletes in this study who completed the CISS--62.7% and 65.9%, respectively.
Several programs for assisting student-athletes with career development tasks have been described in the vocational counseling literature. For example, the University of Kentucky (Sanders, 1992) has a program that includes assessment of interests, job shadowing with community professionals, and opportunities to learn job search strategies. Other programs (Street & Schroeder, 1996) work with SIGI-PLUS, a computer-assisted career guidance program. Still other programs have been organized as courses (Wooten & Hinkle, 1994) that include exploration, assessment, and job skills training or are presented as group career counseling (Nelson, 1982). All of these programs have career assessment in common as an integral component. Yet, little effort has been made to establish evidence of validity for the use of interest inventories with college student-athletes. The results from this study provide evidence for the validity of using scores from the CISS with both college student-athletes and nonathlete college students.
This study suggests the need for further research on a number of points. First, the two groups used in this study were demographically different from each other, particularly in terms of ethnicity and college enrollment. Although this more likely reflects a real difference between student-athletes and nonathlete students rather than sampling error, replication using larger numbers in both groups would reinforce the conclusions shown here. Further replication with female student-athletes and nonathlete students would also be advisable. Although Hansen and Sackett (1993) found no significant differences between these two groups of women using the 511, such evidence also needs to be collected for the use of CISS scores.
The next logical step in this research might be to follow the career progress of both student-athletes and nonathlete students. Although this study found no significant differences in the evidence of validity for use of scores from the CISS with nonathletes and athletes, this project did not address the congruence between measured interests and actual job selection. Future research might also be geared toward examining whether choice of a college major represents a logical step between expressed interests, as measured by an interest inventory, and eventual occupational selection. Such information might be valuable for the academic advising of college students and also in the vocational guidance offered to retiring professional or Olympic athletes as they make the transition from athletic careers to other fields.
TABLE 1 Level of Agreement Between College Major and CISS Occupational Scale Scores for Male Student-Athletes and Nonathlete Students Percent age of Student-Athletes Level of DM IM Total Agreement (n = 33) (n = 49) (N = 82) Excellent 57.6 53.1 54.9 Moderate 3.0 16.3 11.0 Poor 39.4 30.6 34.1 Percentage of Nonathlete Students Level of DM IM Total Agreement (n = 30) (n = 25) (N = 55) Excellent 43.3 56.0 49.1 Moderate 20.0 24.0 21.8 Poor 36.7 20.0 29.1 Note. CISS = Campbell Interest and Skill Survey; DM = percentage of participants with a direct match between CISS Occupational Scale scores and college major; IM = percentage of participants with an indirect match between CISS Occupational Scale scores and college major.
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Laura A. Pendergrass, Jo-Ida C. Hansen, and Jody L. Neuman, Department of Psychology University of Minnesota; Kevin J. Nutter, Department of Health Promotion and Preventive Services. University of Arizona. Correspondence concerning this article should be addressed to Jo-Ida C. Hansen, Department of Psychology, N556 Elliott Hall, University of Minnesota, Minneapolis, MN 55455 (e-mail: email@example.com).…