Development and initial investigation of the school counseling program evaluation scale.

This article evaluates the initial psychometric qualities of the School Counseling Program Evaluation Survey (SCOPES). SCOPES is a 64-item instrument designed to correspond to The National Standards for School Counseling Programs (Campbell & Dahir, 1997). Coefficient alphas on the overall score and the three subscales (i.e., Academic, Career, and Personal/Social Development) were all above. 90. All items had significant factor loadings with the specified subscales. The loadings for Academic Development were .38 to . 79; for Career Development, .42 to .78; and for Personal/Social Development, .36 to. 70. The indexes of goodness-of-fit supported a three-factor instrument. Additionally, students with more contacts with their school counselor reported more career competencies than did students who had never met with a counselor.

**********

Consistent with other professions within education, there have been calls for increased accountability within the field of school counseling (Erford, 2007; Stone & Dahir, 2007). This trend is represented in the ASCA National Model[R] developed by the American School Counselor Association (2005), in which counselors are encouraged to collect data regarding the effectiveness of their school counseling programs. This is often a difficult process as there are very few "off-the-shelf" instruments that assess outcomes relevant to school counseling programs (Studer, Oberman, & Womack, 2006).

In the past 20 years, school counselors have moved from providing services to individual students to providing a comprehensive program that delivers services to all students (Gysbers & Henderson, 2006). A comprehensive guidance and counseling model involves the implementation of a structured, sequential, and organized program in a school district with students from kindergarten through high school graduation. Hence, there is a guidance curriculum that is part of the educational experiences of each student within a school district (Gysbers, Lapan, & Jones, 2000). This movement toward comprehensive developmental guidance programs resulted in ASCA publishing The National Standards for School Counseling Programs (Campbell & Dahir, 1997). These standards explicate the competencies that students should acquire as a result of a comprehensive developmental guidance program provided by trained school counselors.

Although the field of school counseling has adopted the comprehensive developmental guidance approach, there has been very little research evaluating the effectiveness of this model (Whiston, 2007; Whiston & Sexton, 1998). Whiston (2002) argued that more research concerning the effects of school counseling programs is needed, but she contended that a major impediment to conducting both research and evaluation studies in school counseling is the lack of sound outcome assessments. Whiston, Eder, Tai, and Rahardja (2005) found in a meta-analysis of school counseling interventions that researchers often used instruments with limited psychometric support. For example, they found that in their meta-analysis of 117 studies that evaluated school counseling interventions, reliability information was available for less than 39% of the measures and validation evidence was reported less frequently. Hence, there appears to be a substantial need for a psychometrically sound evaluation instrument that could assess the effectiveness of school counseling programs.

In addition to the need for instruments to be used in school counseling research, there is a need for additional measurement tools to assist school counselors in responding to the calls for development of comprehensive school counseling programs that are data driven (Dimmitt, 2003; Isaacs, 2003; Stone & Dahir, 2007). The need for school counselors to collect data to inform their decision-making is particularly evident in the ASCA National Model (2005), in which school counselors are directed to evaluate their school counseling programs. Although some school districts have developed surveys and indicators related to the goals and objectives of comprehensive school counseling programs, many of these instruments only have been used once and their psychometric qualities have not been evaluated.

In other areas of education, assessments are often structured to correspond to the academic standards developed at either the state or national levels; hence, it seems appropriate to design a school counseling assessment that would correspond to the competencies described in the National Standards for School Counseling Programs (Campbell & Dahir, 1997). This article describes the process of developing the School Counseling Program Evaluation Survey (SCOPES) and the initial exploration of the psychometric qualities of this measure. The National Standards for School Counseling Programs were established with the expectation that students would learn and be able to demonstrate these competencies as a result of a K-12 program (Dahir, Sheldon, & Valiga, 1998). Although some competencies may be achieved by many students who participate in school counseling programs in elementary and middle school, SCOPES was designed to be inclusive of all standards and, therefore, is intended for high school students.

SCOPES is a 64-item instrument that was designed to correspond to the school counseling standards concerning Academic Development, Career Development, and Personal/Social Development. Kahn (2006) contended that there has been widespread use of factor analysis in scale development research. This study explored the reliability and the factor structure of the instrument. In this study, confirmatory factor analysis was used because SCOPES was designed to correspond directly to the Academic Development, Career Development, and Personal/Social Development standards of the National Standards for School Counseling Programs (Campbell & Dahir, 1997). SCOPES was developed to assist school counselors and researchers in gathering evaluative data, and the intent of this study is to begin to evaluate its psychometric characteristics.

METHOD

Participants

Participants in this study were 529 high school students (200 males and 329 females) in Texas and Connecticut. Participants came from two high schools in Texas (405 students) and four high schools in Connecticut (124 students). The age of the students ranged from 13 to 19 (M = 16.10, SD = 1.36). Students self-identified their ethnic/racial backgrounds as follows: 30% Caucasian (n = 158), 28% Asian (n = 147), 18% African American (n = 95), 13% Hispanic (n = 70), .5% Native American (n = 4), .5% biracial (n = 3), and 10% indicated "other" (n = 52). In addition, 21% of the participants were freshmen (n = 111), 52% sophomores (n = 274), 15% juniors (n = 77), and 13% seniors (n = 67).

Instruments

Demographic questionnaire. Respondents were asked to indicate their age, gender, race or ethnicity, grade level, name of school, and number of times they had met with their school counselor.

School Counseling Program Evaluation Survey.

SCoPES was developed to correspond to the National Standards for School Counseling Programs (Campbell & Dahir, 1997), and items were developed by a counselor educator with the assistance of school counseling students. In the three domains of Academic Development, Career Development, and Personal/Social Development there are standards, competencies, and indicators. The first attempt at instrument development, producing 120 items, was to write an item for each indicator. Three noted scholars in the field of school counseling reviewed the resulting instrument and found it to be too lengthy and cumbersome.

The second attempt was to develop items related to each of the three standards that are within each of the domains of Academic, Career, and Personal/ Social Development. This revision of the instrument was reviewed by 2 guidance directors, 3 counselor educators, and 10 school counselors in which the reviewers had to indicate whether the items reflected the pertinent competencies. Their suggestions were incorporated into a version that included 64 items, with the Academic Development Scale including 24 items, the Career Development Scale having 24 items, and the Personal/Social Development Scale having 16 items. In scoring SCOPES, items 1 through 24 were written to measure Academic Development, items 25 through 48 concerned Career Development, and items 49 through 64 were designed to assess Personal/Social Development. Each item was then reviewed and revised in order to ensure that the reading level was appropriate for high school students. The current version of SCOPES (see Appendix A) has an overall reading level of fourth grade-third month (4.3).

Each of the standards within the National Standards for School Counseling Programs (Campbell & Dahir, 1997) begins with the phrase "Students will." Hence, in developing an instrument to correspond to these standards, the development team determined to ask students their perceptions of their capabilities. SCOPES is not intended to be used in isolation as there are many other pertinent indicators of the effectiveness of standards-based professional school counseling programs (e.g., grades, disciplinary incidents, parents' and teachers' views). As the goal of SCOPES is to assess students' perceptions of their level of competencies, the instrument development team determined that a Likert scale rather than a dichotomous answer (i.e., yes or no) could provide information on progression toward mastering a competency.

In taking SCOPES, students respond to each item using a Likert scale that specifies the degree to which that competency-based statement applies to them. The Likert scale is (1) all of the time, (2) most of the time, (3) occasionally, (4) hardly ever, and (5) never. In scoring SCOPES, there are three subscales: Academic Development (score range 24 to 120), Career Development (score range 24 to 120), and Personal/ Social Development (score range 16 to 80). Professional school counselors also can obtain a full-scale score that could range from 64 to 320.

Procedure

The data collected in the two Texas schools were gathered by a graduate student. High school students who volunteered and had parental permission completed the demographic questionnaire and SCOPES during their English classes. In Connecticut, the instruments were administered by school counselors prior to beginning a classroom guidance unit.

RESULTS

As the purpose of this study was to explore some of the initial psychometric qualities of SCOPES, coefficient alphas were calculated. The coefficient for the full scale was [alpha] =.97, and for the subscales the estimates of reliability were [alpha] = .93 for Academic Development, [alpha] = .94 for Career Development, and [alpha] = .91 for Personal/Social Development. The means and standard deviations for the scales are provided in Table 1. The number of participants (N) varies among the scales as a few participants did not answer every question within a scale and they were not included in calculating the reliability coefficients.

In order to begin gathering validation evidence, an analysis of the factor structure of SCOPES was conducted using confirmatory factor analysis in AMOS 6. As the items were developed to correspond to the standards related to Academic Development, Career Development, and Personal/ Social Development, confirmatory factor analysis was selected over exploratory methods. Like exploratory factor analysis (EFA), the purpose of confirmatory factor analysis (CFA) is to identify latent factors that account for the variation and covariation among a set of indicators. However, while EFA is generally a descriptive or exploratory procedure, in CFA the researcher must prespecify all aspects of the factor model (Brown, 2006). In the analysis, Academic Development, Career Development, and Personal/Social Development were taken as unobserved constructs. Brown recommended using root mean square error of approximation (RMSEA) as one of the better indicators of goodness-of-fit, and the RMSEA for the three-factor solution was .070. Browne and Cudeck (1993) proposed, as a rule of thumb, that RMSEA values between .05 and 0.08 suggest fair model fit and values above .10 suggest poor fit; hence, the three-factor solution fit the data fairly well. The Comparative Fit Index of .74 also indicates a moderate fit of the data to the model.

In Table 2, a straight arrow between factors and variables represents hypotheses that a pattern coefficient is significantly different from zero. As reflected in Table 2, all variables (i.e., items) have significant factor loadings at p < .001, with the factor loadings for Academic Development being between .35 and .79, for Career Development between .42 and .78, and for Personal/Social Development between .36 and .70. According to Tabachnick and Fidell (2001), minimum factor loadings should be .32 in factor analysis. Also, the standardized regression weights can be interpreted as a correlation between the observed variable and the corresponding common factor (DeCoster, 1998). The two items with the lowest loadings or standardized regression weights were item 4 (.35) and item 63 (.36). In addition, the [R.sup.2] corresponding to all observed variables indicated that the respective factors explained a respectable portion of the variance (15%-62% for Academic Development, 18%-61% for Career Development, and 13%-53% for Personal/Social Development). In addition, the intercorrelations among the three factors were high (i.e., .82 to .87).

In order to explore another type of possible validation evidence of SCOPES, the relationship between students' scores on the SCOPES subscales and the number of times they had talked with their high school counselor was examined. A multivariate analysis of variance (MANOVA) was conducted to examine if there were differences among those who (a) never saw the counselor (n = 26), (b) saw the counselor 1 to 5 times (n = 309), (c) saw the counselor 6 to 10 times (n = 73), (d) saw the counselor 11 to 15 times (n = 17), or (e) saw the counselor more than 15 times (n = 28)--and Wilks' A = .94, F (12, 1,180) = 1.83, p < .05. One-way analysis of variance (ANOVA) results revealed a significant difference among the number of times students had seen their counselor and their scores on the Career Development subscale, F (4, 448) = 2.59, p < .05. Tukey honestly significant difference (HSD) pairwise comparisons reflected that significant differences were between those who never spoke to the counselor and those who met 1 to 5 times and, secondly, between those who never spoke to the counselor and those who met 6 to 10 times with their school counselor. As reflected in Table 3, in both cases participants' scores on SCOPES indicated that those who never met with their counselors reported fewer career competencies.

Another MANOVA was conducted that examined both grade and gender differences. The main effect for grade was significant--Wilks' A = .96, F (9, 1,080) = 2.15, p < .05. The ANOVA results revealed a significant difference related to Personal/Social Development, F (3,446) = 3.96, p < .05. The means, however, for grade level did not correspond to the anticipated linear increases in competencies from 9th grade through 12th grade, as signified by the Tukey HSD pairwise comparisons in which the only significant difference was between sophomores and seniors with sophomores reporting more competencies than seniors. There was not a significant main effect for gender nor was the interaction between gender and grade level significant.

DISCUSSION

School counselors are increasingly being asked to provide accountability data, but it is often difficult to provide evidence of the effectiveness of school counseling (Brigman, 2006). SCOPES was designed to assist with these efforts by providing an instrument that corresponds to the standards of the profession (Campbell & Dahir, 1997). SCOPES was developed for use by school counselors in providing information to administrators, school boards, and other pertinent shareholders. In addition, it was constructed to provide researchers and evaluators with a psychometrically sound instrument that could be used with other outcome measures to evaluate the effectiveness of interventions and comprehensive school counseling programs.

In the current educational environment, there frequently are references to scientifically based research that relies on measurement instruments that provide reliable and valid data (Carey & Dimmitt, 2006). Currently there are very few instruments that practitioners or researchers can use that specifically address school counselors' duties and responsibilities. The results of this study indicate some initial support for SCOPES, and the psychometric qualities related to the instrument are encouraging. The instrument, however, should be used with caution as these are preliminary results and the findings from the confirmatory factor analysis are positive but not conclusive. The reliability coefficients generated in this study were quite positive with coefficient alphas for the full scale on SCOPES being .97, and the coefficients for the subscales Academic Development, Career Development, and Personal/Social Development being .93, .94, and .91, respectively.

Tabachnick and Fidell (2001) asserted that confirmatory factor analysis is a much more sophisticated technique than exploratory factor analysis, and the results of this study generally support the three subscales and the relationship of the items to the three latent factors. The results of this study indicate that all of the items on SCOPES had significant loadings on the specified factors. In fact, 45 of the items had loadings above .60, which is a comparatively high threshold and indicates substantial relationships of the items to the latent factors. The goodness-of-fit indexes support the model but these results were not conclusive and indicate that additional research is warranted. If SCOPES were to be revised, the results of this study would indicate that item 13 in the Academic Development subscale (i.e., I am motivated to learn) and item 63 in the Personal/ Social subscale (i.e., I cope well with stress) should be examined, because these items had comparatively low loadings (.38 and .36). It should be noted, however, that these items were significantly related to the latent factor at the .001 level; thus, there is support for using all 64 items of SCOPES, which are listed in Table 2. Furthermore, the intercorrelations among the latent variables (i.e., Academic Development, Career Development, and Personal/Social Development) provide some support for using the overall score of SCOPES.

The finding that those who met with their school counselor 1 to 5 times and 6 to 10 times had more career competencies than those who never met with a counselor also provides some indication of validity of the Career Development subscale. Meeting with students may be particularly important in the career or vocational area as Whiston, Brecheisen, and Stephens (2003) found that career interventions that did not involve concurrent counseling were significantly less effective than career interventions that did. For example, they found that using a computerized career guidance system was more effective if counseling accompanied the computerized program as compared to using the computerized program in isolation. It is not particularly surprising that there were no differences on the Academic or Personal/ Social subscales between those who had talked with a school counselor and those who had not. Many of the interventions designed to facilitate these competencies may be delivered in classroom activities, which often are provided by classroom teachers or school counselors. Hence, the students may not consider a classroom presentation as actually conversing with their counselor.

Limitations of the Study and Suggestions for Future Research

There are a number of limitations with this initial study of the psychometric qualities of SCoPES. One of the primary limitations was the size and the restricted nature of the sample. The sample used in this study consisted of a disproportionately large number of Asian American students. The large number of Asian American students is because one of the schools in Texas was in a neighborhood in Dallas that had a particularly large Southeast Asian population. Therefore, there is a need for additional research that would expand the normative group of SCOPES so that it could be used with greater confidence in diverse schools. In particular, future researchers may want to consider selecting broad participant samples that represent a diverse range of race or ethnicity, geography, population density (i.e., urban and rural), and socioeconomic status.

SCoPES is designed to measure the effectiveness of school counseling programs and future research should focus on investigating the degree to which the instrument assesses the competencies expressed in the National Standards for School Counseling Programs (Campbell & Dahir, 1997). For example, it might be interesting to explore whether SCOPES scores could discriminate between high schools with clearly articulated and implemented guidance programs and schools that have yet to implement a comprehensive school counseling program. School counselors also could investigate whether students are mastering more competencies as they matriculate and are exposed to more programmatic school guidance interventions (e.g., do students report greater competencies their sophomore year as compared to their freshman year?). Intervention studies also would contribute to the construct validation evidence of SCoPES (see Anastasi & Urbina, 1997). An example of an intervention study would be to administer SCoPES before a guidance curriculum intervention designed to increase academic self-efficacy is conducted and then use it again as a posttest following the intervention to see if there are intended increases in academic development.

Conclusions

SCoPES was developed for two primary reasons: (a) to assist school counselors in gathering data regarding the effectiveness of their school counseling programs, and (b) to provide an outcome assessment instrument that could be used in research concerning school counseling. Positive results were obtained in this preliminary investigation of SCoPES's psychometric qualities. In particular, the results from this study that support using SCoPES are the reliability coefficients and the confirmatory factor analysis that found the 64 items of SCoPES correspond with the intended subscales of Academic, Career, and Personal/Social Development. Nevertheless, more research is needed to determine if SCOPES is a reliable measure that adequately assesses student competencies as articulated by ASCA (2005) and Campbell and Dahir (1997).

APPENDIX A

School Counseling Program Evaluation Survey Items

1. I feel I am a capable learner.

2. I like to learn.

3. I accept that making mistakes is a part of learning.

4. I take pride in my achievements.

5. I manage my time well to get my schoolwork done on time.

6. I put effort into my schoolwork to do my best.

7. If I don't get something right the first time, I keep trying until I do.

8. I ask for help in school as soon as I need it.

9. I think I am responsible for my actions.

10. I am productive and I get things done.

11. I learn by myself as well as with other students.

12. I can begin a task without being told to do so.

13. I am motivated to learn.

14. I use the study skills needed to be successful at school.

15. I can learn without help from others.

16. I use my learning style to do my best in school.

17. I set academic goals to get the grades I want.

18. I keep an eye on my schoolwork and solve problems before I get in trouble.

19. I make good decisions that help me progress in school.

20. I control my behaviors in class in order to succeed in school.

21. I seek outside activities, such as sports and school clubs, because I think they will help me.

22. I try to be successful in school in order to have a better future.

23. I plan on learning throughout my life in order to achieve my goals.

24. I am able to balance my time among school, family, and free time.

25. I use knowledge about myself when planning a career.

26. I am good at making decisions and setting goals.

27. I think about what I like when making decisions and setting goals.

28. I work to develop skills in the areas I am interested in.

29. I manage my time well.

30. I am a hard worker.

31. I enjoy working.

32. I respect people who are unique.

33. I use good sources of information in making career plans.

34. I work to find accurate job information

35. I use the Internet to get job information.

36. I try to learn about different job categories.

37. I set realistic career goals.

38. I make decisions about school based on what I need to achieve my goals.

39. I would change my educational plans to support my career goals.

40. I keep my career planning information in an organized way.

41. I think about the link between school and career success.

42. I think about how my career will affect the lifestyle I want to live.

43. My career plans involve work that I will find satisfying.

44. I plan on learning new skills during my career.

45. I use my interests and knowledge to achieve goals.

46. I use conflict management skills with peers.

47. I work well with other members of a team.

48. I use conflict management skills with adults.

49. I believe I am a unique and valuable person.

50. I have control of my behavior.

51. I know the differences between right and wrong.

52. I can express my feelings,

53. I respect the rights that every person has.

54. I respect people from different backgrounds.

55. I use good communication skills.

56. I make and keep good relationships with friends.

57. I am good at making personal decisions to solve problems

58. I resolve conflicts when they occur.

59. I force myself to keep learning new information and skills.

60. I use a plan to achieve goals.

61. I make choices that keep me healthy and safe.

62. I let people know when physical contact is okay.

63. I cope well with stress.

64. I am able to cope with peer pressure.

References

American School Counselor Association. (2005). The ASCA national model: A framework for school counseling programs (2nd ed.). Alexandria, VA: Author.

Anastasi, A., & Urbina, S. (1997). Psychological testing (7th ed.). Upper Saddle, NJ: Prentice Hall.

Brigman, G. (2006). Research methods in school counseling: A summary for the practitioner. Professional School Counseling, 9, 421-425.

Brown, T. A. (2006). Confirmatory factor analysis: For applied research. New York: Guilford.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-161). Newbury Park, CA: Sage.

Campbell, C. A., & Dahir, C. A. (1997). The national standards for school counseling programs. Alexandria, VA: American School Counselor Association.

Carey, J. C., & Dimmitt, C. (2006). Resources for school counselors and counselor educators: The Center for School Counseling Outcome Research. Professional School Counseling, 9, 416-420.

Dahir, C. A., Sheldon, C. B., & Valiga, M. J. (1998). Implementing the national standards for school counseling programs. Alexandria, VA: American School Counselor Association.

DeCoster, J. (1998). Overview of factor analysis. Retrieved October 19, 2006, from http://www.stat-help.com/notes. html

Dimmitt, C. (2003).Transforming school counseling practice through collaboration and the use of data: A study of academic failure in high school. Professional School Counseling, 6, 340-349.

Erford, B.T. (2007). Accountability. In B.T. Erford (Ed.), Transforming the school counseling profession (2nd ed., pp. 236-278). Upper Saddle River, NJ: Pearson.

Gysbers, N. C., & Henderson, P. (2006). Developing and managing your school guidance program. Alexandria, VA: American Counseling Association.

Gysbers, N.C., Lapan, R.T., & Jones, B. A. (2000). School board policies for guidance and counseling: A call to action. Professional School Counseling, 3, 349-355.

Isaacs, M. L. (2003). Data-driven decision making:The engine of accountability. Professional School Counseling, 6, 288-295.

Kahn, J. H. (2006). Factor analysis in counseling psychology research, training, and practice: Principles, advances, and applications. Journal of Counseling Psychology, 34, 684-718.

Stone, C. B., & Dahir, C. A. (2007). School counselor accountability: A measure of student success. Upper Saddle River, NJ: Pearson.

Studer, J. R., Oberman, A. H., & Womack, R. H. (2006). Producing evidence to show counseling effectiveness in schools. Professional School Counseling, 9, 385-391.

Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Boston: Allyn and Bacon.

Whiston, S. C. (2002). Response to the past, present, and future of school counseling: Raising some issues. Professional School Counseling, 5, 148-157.

Whiston, S. C. (2007). Outcome research on school counseling interventions and programs. In B.T. Erford (Ed.), Transforming the school counseling profession (2nd ed., pp. 39-50). Upper Saddle River, NJ: Pearson.

Whiston, S. C., Brecheisen, B. K., & Stephens, J. (2003). Does treatment modality affect career counseling effectiveness? Journal of Vocational Behavior, 62, 390-410.

Whiston, S. C., Eder, K., Tai, W. L., & Rahardja, D. (2005, June). Research supporting school counseling: Comprehensive findings. Paper presented at the annual meeting of the American School Counselor Association, Orlando, FL.

Whiston, S. C., & Sexton, T. L. (1998). A review of school counseling outcome research: Implications for practice. Journal of Counseling and Development, 76, 412-426.

Susan C. Whiston, Ph.D., is a professor at Indiana University, Bloomington. E-mail: [e-mail]

O. Tolga Aricak, Ph.D., is a visiting assistant professor at Tulane University, New Orleans, LA.

Table 1. Descriptive Statistics for the SCoPES Scale and Subscales

                                N       M        SD      [alpha]

Academic Development           495     49.98    14.32      .93
Career Development             492     51.74    15.58      .94
Personal/Social Development    513     31.30    10.63      .91
SCoPES Total                   454    132.40    37.61      .97

Note. [alpha] represents coefficient alpha.

Table 2. Results of Confirmatory Factor Analysis

Academic

Loading                       Item     Error

.61         [right arrow]       1      (.38)
.62         [right arrow]       2      (.38)
.45         [right arrow]       3      (.20)
.35         [right arrow]       4      (.35)
.62         [right arrow]       5      (.47)
.69         [right arrow]       6      (.39)
.63         [right arrow]       7      (.22)
.47         [right arrow]       8      (.37)
.61         [right arrow]       9      (.50)
.71         [right arrow]      10      (.36)
.60         [right arrow]      11      (.15)
.38         [right arrow]      12      (.45)
.67         [right arrow]      13      (.47)
.69         [right arrow]      14      (.19)
.44         [right arrow]      15      (.53)
.73         [right arrow]      16      (.53)
.72         [right arrow]      17      (.53)
.71         [right arrow]      18      (.50)
.73         [right arrow]      19      (.53)
.63         [right arrow]      20      (.39)
.44         [right arrow]      21      (.19)
.79         [right arrow]      22      (.62)
.67         [right arrow]      23      (.45)
.60         [right arrow]      24      (.36)

Career

Loading                       Item     Error

.75         [right arrow]      25      (.56)
.69         [right arrow]      26      (.48)
.68         [right arrow]      27      (.46)
.68         [right arrow]      28      (.23)
.48         [right arrow]      29      (.35)
.59         [right arrow]      30      (.23)
.49         [right arrow]      31      (.24)
.60         [right arrow]      32      (.36)
.78         [right arrow]      33      (.61)
.63         [right arrow]      34      (.40)
.42         [right arrow]      35      (.18)
.54         [right arrow]      36      (.29)
.68         [right arrow]      37      (.46)
.75         [right arrow]      38      (.57)
.58         [right arrow]      39      (.33)
.60         [right arrow]      40      (.36)
.66         [right arrow]      41      (.44)
.69         [right arrow]      42      (.48)
.68         [right arrow]      43      (.46)
.70         [right arrow]      44      (.48)
.72         [right arrow]      45      (.52)
.52         [right arrow]      46      (.27)
.57         [right arrow]      47      (.32)
.48         [right arrow]      48      (.23)

Personal/Social

Loading                       Item     Error

.68         [right arrow]      49      (.46)
.66         [right arrow]      50      (.43)
.70         [right arrow]      51      (.49)
.55         [right arrow]      52      (.30)
.70         [right arrow]      53      (.49)
.47         [right arrow]      54      (.47)
.67         [right arrow]      55      (.45)
.73         [right arrow]      56      (.53)
.70         [right arrow]      57      (.49)
.66         [right arrow]      58      (.43)
.57         [right arrow]      59      (.33)
.63         [right arrow]      60      (.39)
.66         [right arrow]      61      (.44)
.62         [right arrow]      62      (.36)
.36         [right arrow]      63      (.13)
.58         [right arrow]      64      (.34)

Table 3. Times Spoken with Counselor and Scores on Subscales
Spoken with

Spoken with                       Academic           Career
Counselor                       Development       Development

                                 M       SD        M       SD

Never (n = 32)                 55.89    15.10    59.07    18.52
1 to 5 times (n = 355)         49.62    13.32    51.69    14.64
6 to 10 times (n = 32)         48.52    15.27    50.13    15.78
11 to 15 times (n = 32)        49.65    13.82    49.67    14.79
More than 15 times (n = 32)    51.23    20.91    49.73    20.11

                                 Personal/
Spoken with                        Social
Counselor                       Development

                                 M       SD

Never (n = 32)                 35.50    14.11
1 to 5 times (n = 355)         30.60     9.29
6 to 10 times (n = 32)         31.64    10.60
11 to 15 times (n = 32)        33.70    11.67
More than 15 times (n = 32)    32.09    14.31

Note. Lower scores are associated with increased competencies.