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Vocational decision status and the effect of four types of occupational information on cognitive complexity
Journal of Vocational Behavior 25, 215-224 (1984)
Vocational Decision Status and the Effect of Four Types of Occupational Information on Cognitive Complexity JOAN
P.
University
CESARI
of Kansas
AND JANE L.
WINER
AND KATHLEEN
R.
PIPER
Texas Tech University
Because most vocational counseling interventions focus on giving occupational information, research investigating effects of information giving on cognitive processing styles has governed attention in the recent past. The present study was intended to determine some aspects of occupational information relevance while assessing differences in cognitive complexity between vocationally decided and undecided subjects. Two hundred eighty college student volunteers were assigned to eight groups based on their decision status (decided versus undecided) and random distribution of four types of occupational information packets. Cognitive complexity levels were measured, using the Cognitive Differentiation Grid, 48 hr after the packets were distributed. A 2 x 4 analysis of variance found no differences between decided and undecided subjects’ cognitive complexity scores as a function of type of occupational information received. There was a significant main effect for information received. There was a significant main effect for information across decision status in the positively and negatively toned information groups: the positive information was associated with relatively greater cognitive simplicity scores and the negative information was associated with relatively greater cognitive complexity scores. Implications of results and further necessary research is specified.
Vocational indecision in the college student population remains a potent issue for researchers and practitioners in the area of vocational counseling. College students have shown the most interest in career counseling interventions as opposed to other programs offered by university counseling centers (e.g., Camey, Savitz, & Weiskott, 1979), and researchers have This study is based on a doctoral dissertation completed by the first author under the supervision of the second author and submitted to the Department of Psychology at Texas Tech University. Address correspondence and requests for reprints to Joan P. Cesari, Counseling Department, 116 Bailey Hall, University of Kansas, Lawrence, KS 66045. 215 OOOl-8791/84$3.00 Copyright 0 1984 by Academic Press, Inc. All rights of reproduction in any form reserved.
216
CESARI,
WINER,
AND PIPER
responded to these requests by continuing their attempts to define, develop, and critically evaluate career counseling strategies which can be maximally effective (Fretz & Leong, 1982; Holland, Magoon, & Spokane, 1981). While there is still no universal definition of the vocational counseling process, the common denominator of many interventions involves the giving of some type of occupational information. This may include career requirements or education, career outlook, salary ranges, job descriptions, interest inventory results, and so forth. In an attempt to find vocational decision making variables which might facilitate and/or explain the impact of this occupational information giving, the cognitive complexity-simplicity dimension (Kelly, 1955) has generated research interest. Early work in this area focused on possible correlational relationships between cognitive complexity-simplicity and congruence of vocational choice (Bodden, 1970a, 1970b), vocational maturity (Winer, Cesari, Haase, & Bodden, 1979), and vocational preference (Winer, Haase, Glenn, Cesari, & Bodden, 1979). Other research has focused on the cognitive complexity-simplicity dimension and its relationship to the processing of occupational information. Bodden and James (1976) found that giving occupational information to subjects reduced their cognitive complexity scores, which suggests a reduction in the ability to make finer discriminations among occupations. They concluded that giving occupational information may only confuse the client or hamper his/her ability to come to a vocational decision resolution due to the reduction in discrimination. It would appear to be desirable to be cognitively complex while making a career decision so that finer discriminations among variables can be made (Bodden & James, 1976) and more information can be integrated. Haase, Reed, Winer, and Bodden (1979) hypothesized that the type of information presented to the subject would have differing effects on cognitive complexity. Using a sample that did not discriminate on the vocational decision status of their subjects, they found positively toned occupational information led to greater cognitive simplicity. Negatively and mixed toned information was found to reduce subjects’ trend toward cognitive simplicity. It would seem, then, that differential changes in cognitive complexity are at least partly a function of the type of information presented. Theories of cognitive complexity and information processing would support the notion that subjects who have completed a decision making task would differentially process incoming information when compared to subjects who have not completed the task (e.g., Sieber & Lanzetta, 1964). A replication of the Bodden and James (1976) study was conducted to determine whether vocationally undecided subjects would respond differently from vocationally decided subjects when presented with occupational information. Cesari, Winer, Zychlinski, and Laird (1982) found that the two groups did not differ from one another on cognitive complexity scores after exposure to neutral occupational information. However,
VOCATIONAL
DECISION STATUS
217
neither did the subjects become more cognitively simple as a result of the information presented when compared to the no-information control condition. Thus, the Bodden and James (1976) results were not replicated. It is possible that the Cesari et al. (1982) results neither followed the hypothesized direction nor replicated the Bodden and James (1976) work because the information provided was not relevant to the vocational task. Relevant information is that information “to which a meaningful task-oriented response is possible” (Streufert, 1973, p. 224); neutral information may not allow a meaningful response by any subject or it may be redundant for a vocationally decided individual to respond in a taskoriented way to vocational exploration information. Haase et al. (1979) showed that different types of occupational information differentially affected cognitive complexity levels. Giving neutral information to subjects, as in Cesari et al. (1982), may involve merely exposing subjects to “information load” as opposed to “information relevance” (Streufert, 1973). The present study was intended to determine some aspects of information relevance in the vocational information area while assessing differences in cognitive complexity between decided and undecided subjects. The hypothesis predicted that there would be a difference between vocationally decided and undecided subjects’ cognitive complexity scores as a function of the four types of occupational information provided. Magnitude and direction of differences were not predicted. METHODS Subjects A total of 280 subjects participated in this study, 113 males and 167 females. Subjects volunteered from several sections of an introductory psychology course at a large Southwestern university as one of several ways to earn extra course credit. The mean age of the sample was 19.5 years. The numbers of freshmen, sophomores, juniors, and seniors were 170, 83, 19, and 8, respectively. The mean grade point average for the sample was 2.93 on a 4.0 scale. A total of 57 different college majors were represented (including the undecided category), and these majors reflected all six undergraduate college divisions at the university. Instrumentation This study used one dependent measure, the Cognitive Differentiation Grid (Grid), developed by Bodden (197Oa). The Career Decision Scale (CDS; Osipow, Carney, Winer, Yanico, & Koschier, 1976) was used to assign subjects to decided or undecided groups. Subjects also completed a demographic questionnaire concerning age, sex, classification, grade point average, and self-report decision status via declared or undeclared college major. The CDS is designed to identify barriers which prevent people from
218
CESARI, WINER, AND PIPER
making an occupational choice. The respondent employs a 4-point Likert scale to answer 18 statements about career choice; item 19 is an openended question. Vocationally undecided students are designated by their responses to the first two items on the scale: “I have decided on a career and feel comfortable with it. I also know how to go about implementing my choice.” And the second “I have decided on a college major and feel comfortable with it. I also know how to go about implementing my choice.” Osipow (1979) delineates vocationally undecided respondents as those whose response for either item on the 4-point scale is 2 (“Only slightly like me”) or 1 (“Not at all like me”). Because it has been argued that college major decidedness is not the equivalent of vocational decidedness (Hawkins, Bradley, & White, 1977),and because it was desirable to set a stricter criterion of vocational decidedness, only the first item of the CDS, the one concerning career choice, was employed, using Ospiow’s criterion. The subsequent decision status was then compared with the self-report decision status item on the demographic questionnaire. Only those subjects whose CDS score and self-report indicated vocational indecision were included in the undecided sample. The Grid uses a modification of Kelly’s (1955) Repertory Grid Technique to assess cognitive complexity-simplicity. The instrument uses a grid format with 12 occupational titles (e.g., farmer, physicist) across the top of the grid and 12 vocationally relevant, bipolar construct dimensions (e.g., white collar vs blue collar) along the right-hand side. Subjects are asked to rate each occupation on each of the 12 construct dimensions utilizing a 6-point Likert scale (Bodden 8z James, 1976.) Scoring the vocational complexity grid is accomplished by comparing each rating in a row with the rating below it in the other rows of the matrix. In comparing any two construct rows, a score of 1 [is] given for every exact agreement or rating for any one occupational title. This comparison procedure [is] done for all possible comparisons, and scores for each comparison [are] added to yield a total score. Since there are 66 possible row combinations in a 12 x 12 matrix, the highest possible score [is] 792 (i.e., 12 x 66). The higher the score, the lower the complexity level. (Bodden, 1970b, p. 365)
Bodden provides a test-retest reliability correlation of .82 for an interval of 2 weeks, and the average total complexity score of college students has been reported in the 270-290 range (Bodden, 1970b). Materials
For the positive, negative, and mixed information groups, the vocational information was presented in packets which contained occupational summaries abstracted from information in the Occupational Outlook Handbook (U.S. Department of Labor, 1977) for the 12 occupational titles used in the Grid. In the positive information group, all references to salary, future
VOCATIONAL
DECISION STATUS
219
of the occupation, necessary training, etc., were presented in positive form and favorable testimonials from people in each occupation were included. The negative information group received the same information but in a negative form, and testimonials were included from dissatisfied persons in those occupations. The mixed information condition used a combination of the positively and negatively toned descriptions and the testimonials for each occupation. The fourth type of information was the no-information control condition. Subjects in this condition received an identical-looking packet which included only a list of addresses where the subject could write for more information about each of the 12 occupations. All addresses were distant locations to preclude the possibility of subjects’ actually obtaining relevant information from these sources within the 4%hr testing interval. Procedure Subjects were initially screened on the CDS to determine their vocational decidedness status. Once assigned to decided or undecided status, each subject was randomly assigned to one of the four treatment-information groups. Subject selection continued until there were 35 subjects in each of the eight experimental groups. These groups were: decided-positive information, decided-negative information, decided-mixed information, decided-control, undecided-positive information, undecided-negative information, undecided-mixed information, and undecided-control. Each subject was asked to complete the brief demographic data questionnaire and was provided with an information packet according to his/ her respective assigned information condition, To ensure exposure to the material contained within, subjects were required to read the material in the presence of the experimenter, to review the information prior to the second session, and to be prepared to answer a questionnaire pertaining to the usefulness of the material. They were cautioned not to discuss their packets with other subjects. When the subjects returned for the second session 2 days later, they were asked to complete the Grid and a brief questionnaire on the material contained in the packet. The subjects were then debriefed concerning the nature of the study. Confidentiality and anonymity of the data were protected. RESULTS
Using a 2 x 4 factorial design with two levels of decidedness and four levels of occupational information, eight independent treatment groups were formed. A summary of descriptive statistics for each group on the dependent variable, cognitive complexity, can be found in Table 1. The major hypothesis of this study was tested using a 2 x 4 analysis of variance between decision status and type of occupational information
220
CESARI, WINER, AND PIPER TABLE 1 Summary Statistics of Cognitive Complexity Scores across Treatment Groups
x
SD
35 35 35 35 35 35 35 35
282.89 256.00 257.27 264.94 267.94 251.06 272.66 251.23
45.53 47.09 40.46 51.12 so.79 36.96 54.31 41.51
280
263.15
46.31
Treatment group
N
Decided-positive information Decided-negative information Decided-mixed information Decided-control Undecided-positive information Undecided-negative information Undecided-mixed information Undecided-control Total
presented. A summary of that analysis is presented in Table 2. No significant differences were found between vocationally decided and undecided subjects’ cognitive complexity scores as a function of the type of occupational information that they were given. The main effect for decision status was not significant. However, there was a significant main effect for type of information, F(3, 272) = 2.71, p < .05. Collapsing across decision status and using Duncan’s multiple range method, a significant difference in cognitive complexity scores was found between subjects who received the positive information packet and subjects who received the negative information packet. The subjects in the positive information groups had significantly higher scores on the Grid (greater cognitive simplicity) than those in the negative information group. Table 3 presents a summary of the mean comparisons for the Duncan multiple range test. DISCUSSION The analysis of variance did not support the hypothesis that there would be a significant between vocational decision status and the type TABLE 2 Analysis of Variance of Cognitive Complexity Scores by Decision Status and Information Type Source
ss
df
MS
F
Information type Decision status Information type x decision status Residual
17,438.64 654.23 8,857.23 593,404.69
3 1 3 272
5812.88 654.23 295.41 2144.87
2.71* .31 1.38
Total
610,354.81
279
2187.65
* p < .05.
VOCATIONAL
221
DECISION STATUS
TABLE 3 Summary of Duncan’s Multiple Range Mean Comparisons for Information Type Subgroups”
Negative group Control group Mixed group Positive group
xz X4 x3 x,
= = = =
253.53 261.09 264.97 275.41
-
7.56 -
11.44 3.89 -
21.89* 14.33 10.64 -
a n = 70 per group. * p < .05.
of occupational information received when assessing subjects’ cognitive complexity scores. There was a significant main effect for type of occupational information, but there were no differences in cognitive complexity according to the decision status of the subjects. The significant main effect for the type of occupational information received by the subjects serves as a replication of the Haase et al. (1979) results on differential effects of occupational information tone. Further analysis of the present results revealed one significant pair-wise comparison among the means for the four information treatment groups. This indicated that the positive information condition was associated with relatively greater cognitive simplicity (higher scores on the Grid) when compared to the negative information condition. The negative information treatment was associated with relatively greater cognitive complexity (lower scores on the Grid) when compared with the positive information condition. This finding partially replicated the earlier results of Haase et al. (1979) who found that positive information produced more change in Grid scores toward greater simplicity relative to negative or mixed information. The present results and the comparable Haase et al. (1979) results were observed regardless of the decision status of the subjects. Although nonsignificant, an interesting trend toward greater cognitive simplicity in undecided subjects was found in the mixed information condition when compared with decided subjects in the same treatment. While there appears to be at least one dimension of occupational information (tone of information) which leads subjects to cognitively process that material in nonuniform ways, no significant differences could be found across decision status of subjects. Cesari et al. (1982) also found no differences in cognitive complexity scores between decided and undecided subjects. There does not appear to be an explanation in the realm of cognitive complexity theories which could explain the results in these two studies as reflecting a homogeneity among subjects across the cognitive complexity-simplicity construct, if there is differential processing between those who have and have not completed a decision
222
CESARI,
WINER,
AND PIPER
making task (Siber & Lanzetta, 1964). An alternate explanation of the results lies in the characteristics of the treatment variable. It is possible that the information used in the treatment was not relevant to the two decision types being studied. The results of the “usefulness quiz” given to the subjects (originally as a measure to avoid deception in the instructions) indicated that 60.7% of the respondents thought that information about occupations not in the packets would have been useful to them. These subjective report data lend some support to a hypothesis that undecided subjects may have found the information packets irrelevant to their career choice processes. It is possible that real difference in cognitive complexity between decided and undecided subjects were masked by the consideration of undecided subjects as a homogeneous group. Subjects with different reasons for being undecided may respond differentially to the material provided as do they respond differentially to various career counseling interventions (Barak & Friedkes, 1982). Such subtype responses could effectively mask the responses of other subtypes who process in other ways. Thus, researchers in this field could erroneously conclude that vocational information is processed in the same way by all vocationally undecided subjects. As research continues on the cognitive complexity-simplicity dimension with respect to vocational indecision, a serious look must be taken at one of the underlying assumptions involved in these efforts. As noted earlier, Bodden (1970b) and Haase et al. (1979) implied that cognitive complexity is more desirable than cognitive simplicity in making a vocational decision. At this point, there is no empirical support for this statement. The present study did not attempt to provide support or disproof for that position, but future research in the area might well be addressed to this question. Winer, Warren, Dailey, and Heisberger (1980) postulated that the Bodden (1970b) and Haase et al. (1979) subjects may have become more simple by making a vocational decision or at least by restricting their acceptable alternatives in the course of their participation in the research. A pre- and postexamination of decision status or acceptable vocational alternatives while simultaneously assessing complexity changes could prove useful in understanding subjects’ trend toward cognitive simplicity after exposure to certain types of occupational information. Future research which is directed at determining relevant occupational information for undecided individuals is certainly warranted. With respect to cognitive processing (complexity-simplicity), however, the logical progression in research endeavors might be to determine the relative merit of complexity-simplicity first. The results of the present study serve as a case in point. In studying the tone of occupational information, one of the results showed that negatively toned occupational information was associated with cognitive complexity in subjects. Earlier work (Bodden
VOCATIONAL
DECISION STATUS
223
& Klein, 1973; Haase et al., 1979; Winer et al., 1980) contended that occupations which are viewed negatively or as threatening to the subject are processed in a more complex manner than occupations which are viewed positively. Hence, the present study supported previous knowledge about subjects’ cognitive complexity-simplicity responses to information tone. It appears to be time for research to address the issue of merit of cognitive complexity-simplicity in vocational decision making. In other words, now that it is known how subjects will respond to positive and negative occupational information, which responses would be more desirable for effective vocational decision making? Further, would different types of vocationally undecided subjects benefit from differential cognitive complexity-simplicity responses? How might the researcher (and, subsequently, the vocational counselor) adapt relevant occupational information to suit the needs of subjects (and clients) to maximize effective career choices? In an era of increased emphasis on the accountability of psychologists, finding answers to these questions should be of interest to researchers in counseling psychology. REFERENCES Barak, A., & Friedkes, R. (1982). The mediating effects of career indecision subtypes on career-counseling effectiveness. Journal of Vocational Behavior, 20, 120-128. Bodden, J. L. (197Oa). Cognitive complexity as a factor in appropriate vocational choice (Doctoral dissertation, Ohio State University, 1%9). Dissertation Abstracts International, 30, 33080B. Bodden, J. L. (1970b). Cognitive complexity as a factor in appropriate vocational choice. Journal
of Counseling
Psychology,
17, 364-368.
Bodden, J. L., & James L. E. (1976). Influence of occupational information giving on cognitive complexity. Journal of Counseling Psychology, 23, 280-282. Bodden, J. L., & Klein, A. J. (1973). Cognitive differentiation and affective stimulus value in vocational judgments. Journal of Vocational Behavior, 3, 75-79. Camey, C. G., Savitz, C. J., & Weiskott, G. N. (1979). Students’ evaluations of a university counseling center and their intentions to use its programs. Journal of Counseling Psychology,
26, 242-249.
Cesari, J. P., Winer, J. L., Zychlinski, F., & Laird, I. 0. (1982).Influence of occupational information giving on cognitive complexity in decided versus undecided students. Journal
of Vocational
Behavior,
21, 224-230.
Fretz, B. R., & Leong, F. T. L. (1982). Vocational behavior and career development, 1981: A review. Journal of Vocational Behavior, 21, 123-163. Haase, R. F., Reed, C. F., Winer, J. L., & Bodden, J. L. (1979). Effect of positive, negative, and mixed occupational information on cognitive and affective complexity. Journal
of Vocational
Behavior,
15, 294-302.
Hawkins, J. G., Bradley, R. W., & White, G. W. (1977). Anxiety and the process of deciding about a major and vocation. Journal of Counseling Psychology, 24,398-403. Holland, J. L., Magoon, T. M., & Spokane, A. R. (1981). Counseling psychology: Career interventions, research, and theory. Annual Review of Psychology, 32, 279-305. Kelly, G. A. (1955). The psychology of personal constructs (2 ~01s.). New York: Norton. Osipow, S. H. (1979). A preliminary manual for the Career Decision Scale. Columbus, OH: Marathon Consulting & Press.
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Osipow, S. H., Camey, C. G., Winer, J. L., Yanico, B., & Koschier, M. (1976). Career Decision Scale (3rd rev.). Columbus, OH: Marathon Consulting 62 Press. Sieber, J. E., & Lanzetta, J. T. (1964). Conflict and conceptual structure as determinants of decision making behavior. Journal of Personality, 32, 622-641. Streufert, S. C. (1973). Effects of information relevance in decision making in complex environments. Memory & Cognition, 1, 224-228. U.S. Department of Labor (1977). Occupational outlook handbook. Washington, DC. Winer, J. L., Cesari, J., Haase, R. F., & Bodden, J. L. (1979). Cognitive complexity and career maturity among college students. Journal of Vocational Behavior, 15, 186-192. Winer, J. L., Haase, R. F., Glenn, C. M., Cesari, J., & Bodden, J. (1979, April). Cognitive complexity and vocational preference among college students. Paper presented at the meeting of Southwestern Psychological Association, San Antonio, TX. Winer, J. L., Warren, G. D., Dailey, K. C., & Hiesberger, J. (1980). Complexity of judgment of occupational titles among Holland types. Vocational Guidance Quarterly, 29, 12-24. Received: September 23, 1983.
Vocational Decision Status and the Effect of Four Types of Occupational Information on Cognitive Complexity JOAN
P.
University
CESARI
of Kansas
AND JANE L.
WINER
AND KATHLEEN
R.
PIPER
Texas Tech University
Because most vocational counseling interventions focus on giving occupational information, research investigating effects of information giving on cognitive processing styles has governed attention in the recent past. The present study was intended to determine some aspects of occupational information relevance while assessing differences in cognitive complexity between vocationally decided and undecided subjects. Two hundred eighty college student volunteers were assigned to eight groups based on their decision status (decided versus undecided) and random distribution of four types of occupational information packets. Cognitive complexity levels were measured, using the Cognitive Differentiation Grid, 48 hr after the packets were distributed. A 2 x 4 analysis of variance found no differences between decided and undecided subjects’ cognitive complexity scores as a function of type of occupational information received. There was a significant main effect for information received. There was a significant main effect for information across decision status in the positively and negatively toned information groups: the positive information was associated with relatively greater cognitive simplicity scores and the negative information was associated with relatively greater cognitive complexity scores. Implications of results and further necessary research is specified.
Vocational indecision in the college student population remains a potent issue for researchers and practitioners in the area of vocational counseling. College students have shown the most interest in career counseling interventions as opposed to other programs offered by university counseling centers (e.g., Camey, Savitz, & Weiskott, 1979), and researchers have This study is based on a doctoral dissertation completed by the first author under the supervision of the second author and submitted to the Department of Psychology at Texas Tech University. Address correspondence and requests for reprints to Joan P. Cesari, Counseling Department, 116 Bailey Hall, University of Kansas, Lawrence, KS 66045. 215 OOOl-8791/84$3.00 Copyright 0 1984 by Academic Press, Inc. All rights of reproduction in any form reserved.
216
CESARI,
WINER,
AND PIPER
responded to these requests by continuing their attempts to define, develop, and critically evaluate career counseling strategies which can be maximally effective (Fretz & Leong, 1982; Holland, Magoon, & Spokane, 1981). While there is still no universal definition of the vocational counseling process, the common denominator of many interventions involves the giving of some type of occupational information. This may include career requirements or education, career outlook, salary ranges, job descriptions, interest inventory results, and so forth. In an attempt to find vocational decision making variables which might facilitate and/or explain the impact of this occupational information giving, the cognitive complexity-simplicity dimension (Kelly, 1955) has generated research interest. Early work in this area focused on possible correlational relationships between cognitive complexity-simplicity and congruence of vocational choice (Bodden, 1970a, 1970b), vocational maturity (Winer, Cesari, Haase, & Bodden, 1979), and vocational preference (Winer, Haase, Glenn, Cesari, & Bodden, 1979). Other research has focused on the cognitive complexity-simplicity dimension and its relationship to the processing of occupational information. Bodden and James (1976) found that giving occupational information to subjects reduced their cognitive complexity scores, which suggests a reduction in the ability to make finer discriminations among occupations. They concluded that giving occupational information may only confuse the client or hamper his/her ability to come to a vocational decision resolution due to the reduction in discrimination. It would appear to be desirable to be cognitively complex while making a career decision so that finer discriminations among variables can be made (Bodden & James, 1976) and more information can be integrated. Haase, Reed, Winer, and Bodden (1979) hypothesized that the type of information presented to the subject would have differing effects on cognitive complexity. Using a sample that did not discriminate on the vocational decision status of their subjects, they found positively toned occupational information led to greater cognitive simplicity. Negatively and mixed toned information was found to reduce subjects’ trend toward cognitive simplicity. It would seem, then, that differential changes in cognitive complexity are at least partly a function of the type of information presented. Theories of cognitive complexity and information processing would support the notion that subjects who have completed a decision making task would differentially process incoming information when compared to subjects who have not completed the task (e.g., Sieber & Lanzetta, 1964). A replication of the Bodden and James (1976) study was conducted to determine whether vocationally undecided subjects would respond differently from vocationally decided subjects when presented with occupational information. Cesari, Winer, Zychlinski, and Laird (1982) found that the two groups did not differ from one another on cognitive complexity scores after exposure to neutral occupational information. However,
VOCATIONAL
DECISION STATUS
217
neither did the subjects become more cognitively simple as a result of the information presented when compared to the no-information control condition. Thus, the Bodden and James (1976) results were not replicated. It is possible that the Cesari et al. (1982) results neither followed the hypothesized direction nor replicated the Bodden and James (1976) work because the information provided was not relevant to the vocational task. Relevant information is that information “to which a meaningful task-oriented response is possible” (Streufert, 1973, p. 224); neutral information may not allow a meaningful response by any subject or it may be redundant for a vocationally decided individual to respond in a taskoriented way to vocational exploration information. Haase et al. (1979) showed that different types of occupational information differentially affected cognitive complexity levels. Giving neutral information to subjects, as in Cesari et al. (1982), may involve merely exposing subjects to “information load” as opposed to “information relevance” (Streufert, 1973). The present study was intended to determine some aspects of information relevance in the vocational information area while assessing differences in cognitive complexity between decided and undecided subjects. The hypothesis predicted that there would be a difference between vocationally decided and undecided subjects’ cognitive complexity scores as a function of the four types of occupational information provided. Magnitude and direction of differences were not predicted. METHODS Subjects A total of 280 subjects participated in this study, 113 males and 167 females. Subjects volunteered from several sections of an introductory psychology course at a large Southwestern university as one of several ways to earn extra course credit. The mean age of the sample was 19.5 years. The numbers of freshmen, sophomores, juniors, and seniors were 170, 83, 19, and 8, respectively. The mean grade point average for the sample was 2.93 on a 4.0 scale. A total of 57 different college majors were represented (including the undecided category), and these majors reflected all six undergraduate college divisions at the university. Instrumentation This study used one dependent measure, the Cognitive Differentiation Grid (Grid), developed by Bodden (197Oa). The Career Decision Scale (CDS; Osipow, Carney, Winer, Yanico, & Koschier, 1976) was used to assign subjects to decided or undecided groups. Subjects also completed a demographic questionnaire concerning age, sex, classification, grade point average, and self-report decision status via declared or undeclared college major. The CDS is designed to identify barriers which prevent people from
218
CESARI, WINER, AND PIPER
making an occupational choice. The respondent employs a 4-point Likert scale to answer 18 statements about career choice; item 19 is an openended question. Vocationally undecided students are designated by their responses to the first two items on the scale: “I have decided on a career and feel comfortable with it. I also know how to go about implementing my choice.” And the second “I have decided on a college major and feel comfortable with it. I also know how to go about implementing my choice.” Osipow (1979) delineates vocationally undecided respondents as those whose response for either item on the 4-point scale is 2 (“Only slightly like me”) or 1 (“Not at all like me”). Because it has been argued that college major decidedness is not the equivalent of vocational decidedness (Hawkins, Bradley, & White, 1977),and because it was desirable to set a stricter criterion of vocational decidedness, only the first item of the CDS, the one concerning career choice, was employed, using Ospiow’s criterion. The subsequent decision status was then compared with the self-report decision status item on the demographic questionnaire. Only those subjects whose CDS score and self-report indicated vocational indecision were included in the undecided sample. The Grid uses a modification of Kelly’s (1955) Repertory Grid Technique to assess cognitive complexity-simplicity. The instrument uses a grid format with 12 occupational titles (e.g., farmer, physicist) across the top of the grid and 12 vocationally relevant, bipolar construct dimensions (e.g., white collar vs blue collar) along the right-hand side. Subjects are asked to rate each occupation on each of the 12 construct dimensions utilizing a 6-point Likert scale (Bodden 8z James, 1976.) Scoring the vocational complexity grid is accomplished by comparing each rating in a row with the rating below it in the other rows of the matrix. In comparing any two construct rows, a score of 1 [is] given for every exact agreement or rating for any one occupational title. This comparison procedure [is] done for all possible comparisons, and scores for each comparison [are] added to yield a total score. Since there are 66 possible row combinations in a 12 x 12 matrix, the highest possible score [is] 792 (i.e., 12 x 66). The higher the score, the lower the complexity level. (Bodden, 1970b, p. 365)
Bodden provides a test-retest reliability correlation of .82 for an interval of 2 weeks, and the average total complexity score of college students has been reported in the 270-290 range (Bodden, 1970b). Materials
For the positive, negative, and mixed information groups, the vocational information was presented in packets which contained occupational summaries abstracted from information in the Occupational Outlook Handbook (U.S. Department of Labor, 1977) for the 12 occupational titles used in the Grid. In the positive information group, all references to salary, future
VOCATIONAL
DECISION STATUS
219
of the occupation, necessary training, etc., were presented in positive form and favorable testimonials from people in each occupation were included. The negative information group received the same information but in a negative form, and testimonials were included from dissatisfied persons in those occupations. The mixed information condition used a combination of the positively and negatively toned descriptions and the testimonials for each occupation. The fourth type of information was the no-information control condition. Subjects in this condition received an identical-looking packet which included only a list of addresses where the subject could write for more information about each of the 12 occupations. All addresses were distant locations to preclude the possibility of subjects’ actually obtaining relevant information from these sources within the 4%hr testing interval. Procedure Subjects were initially screened on the CDS to determine their vocational decidedness status. Once assigned to decided or undecided status, each subject was randomly assigned to one of the four treatment-information groups. Subject selection continued until there were 35 subjects in each of the eight experimental groups. These groups were: decided-positive information, decided-negative information, decided-mixed information, decided-control, undecided-positive information, undecided-negative information, undecided-mixed information, and undecided-control. Each subject was asked to complete the brief demographic data questionnaire and was provided with an information packet according to his/ her respective assigned information condition, To ensure exposure to the material contained within, subjects were required to read the material in the presence of the experimenter, to review the information prior to the second session, and to be prepared to answer a questionnaire pertaining to the usefulness of the material. They were cautioned not to discuss their packets with other subjects. When the subjects returned for the second session 2 days later, they were asked to complete the Grid and a brief questionnaire on the material contained in the packet. The subjects were then debriefed concerning the nature of the study. Confidentiality and anonymity of the data were protected. RESULTS
Using a 2 x 4 factorial design with two levels of decidedness and four levels of occupational information, eight independent treatment groups were formed. A summary of descriptive statistics for each group on the dependent variable, cognitive complexity, can be found in Table 1. The major hypothesis of this study was tested using a 2 x 4 analysis of variance between decision status and type of occupational information
220
CESARI, WINER, AND PIPER TABLE 1 Summary Statistics of Cognitive Complexity Scores across Treatment Groups
x
SD
35 35 35 35 35 35 35 35
282.89 256.00 257.27 264.94 267.94 251.06 272.66 251.23
45.53 47.09 40.46 51.12 so.79 36.96 54.31 41.51
280
263.15
46.31
Treatment group
N
Decided-positive information Decided-negative information Decided-mixed information Decided-control Undecided-positive information Undecided-negative information Undecided-mixed information Undecided-control Total
presented. A summary of that analysis is presented in Table 2. No significant differences were found between vocationally decided and undecided subjects’ cognitive complexity scores as a function of the type of occupational information that they were given. The main effect for decision status was not significant. However, there was a significant main effect for type of information, F(3, 272) = 2.71, p < .05. Collapsing across decision status and using Duncan’s multiple range method, a significant difference in cognitive complexity scores was found between subjects who received the positive information packet and subjects who received the negative information packet. The subjects in the positive information groups had significantly higher scores on the Grid (greater cognitive simplicity) than those in the negative information group. Table 3 presents a summary of the mean comparisons for the Duncan multiple range test. DISCUSSION The analysis of variance did not support the hypothesis that there would be a significant between vocational decision status and the type TABLE 2 Analysis of Variance of Cognitive Complexity Scores by Decision Status and Information Type Source
ss
df
MS
F
Information type Decision status Information type x decision status Residual
17,438.64 654.23 8,857.23 593,404.69
3 1 3 272
5812.88 654.23 295.41 2144.87
2.71* .31 1.38
Total
610,354.81
279
2187.65
* p < .05.
VOCATIONAL
221
DECISION STATUS
TABLE 3 Summary of Duncan’s Multiple Range Mean Comparisons for Information Type Subgroups”
Negative group Control group Mixed group Positive group
xz X4 x3 x,
= = = =
253.53 261.09 264.97 275.41
-
7.56 -
11.44 3.89 -
21.89* 14.33 10.64 -
a n = 70 per group. * p < .05.
of occupational information received when assessing subjects’ cognitive complexity scores. There was a significant main effect for type of occupational information, but there were no differences in cognitive complexity according to the decision status of the subjects. The significant main effect for the type of occupational information received by the subjects serves as a replication of the Haase et al. (1979) results on differential effects of occupational information tone. Further analysis of the present results revealed one significant pair-wise comparison among the means for the four information treatment groups. This indicated that the positive information condition was associated with relatively greater cognitive simplicity (higher scores on the Grid) when compared to the negative information condition. The negative information treatment was associated with relatively greater cognitive complexity (lower scores on the Grid) when compared with the positive information condition. This finding partially replicated the earlier results of Haase et al. (1979) who found that positive information produced more change in Grid scores toward greater simplicity relative to negative or mixed information. The present results and the comparable Haase et al. (1979) results were observed regardless of the decision status of the subjects. Although nonsignificant, an interesting trend toward greater cognitive simplicity in undecided subjects was found in the mixed information condition when compared with decided subjects in the same treatment. While there appears to be at least one dimension of occupational information (tone of information) which leads subjects to cognitively process that material in nonuniform ways, no significant differences could be found across decision status of subjects. Cesari et al. (1982) also found no differences in cognitive complexity scores between decided and undecided subjects. There does not appear to be an explanation in the realm of cognitive complexity theories which could explain the results in these two studies as reflecting a homogeneity among subjects across the cognitive complexity-simplicity construct, if there is differential processing between those who have and have not completed a decision
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CESARI,
WINER,
AND PIPER
making task (Siber & Lanzetta, 1964). An alternate explanation of the results lies in the characteristics of the treatment variable. It is possible that the information used in the treatment was not relevant to the two decision types being studied. The results of the “usefulness quiz” given to the subjects (originally as a measure to avoid deception in the instructions) indicated that 60.7% of the respondents thought that information about occupations not in the packets would have been useful to them. These subjective report data lend some support to a hypothesis that undecided subjects may have found the information packets irrelevant to their career choice processes. It is possible that real difference in cognitive complexity between decided and undecided subjects were masked by the consideration of undecided subjects as a homogeneous group. Subjects with different reasons for being undecided may respond differentially to the material provided as do they respond differentially to various career counseling interventions (Barak & Friedkes, 1982). Such subtype responses could effectively mask the responses of other subtypes who process in other ways. Thus, researchers in this field could erroneously conclude that vocational information is processed in the same way by all vocationally undecided subjects. As research continues on the cognitive complexity-simplicity dimension with respect to vocational indecision, a serious look must be taken at one of the underlying assumptions involved in these efforts. As noted earlier, Bodden (1970b) and Haase et al. (1979) implied that cognitive complexity is more desirable than cognitive simplicity in making a vocational decision. At this point, there is no empirical support for this statement. The present study did not attempt to provide support or disproof for that position, but future research in the area might well be addressed to this question. Winer, Warren, Dailey, and Heisberger (1980) postulated that the Bodden (1970b) and Haase et al. (1979) subjects may have become more simple by making a vocational decision or at least by restricting their acceptable alternatives in the course of their participation in the research. A pre- and postexamination of decision status or acceptable vocational alternatives while simultaneously assessing complexity changes could prove useful in understanding subjects’ trend toward cognitive simplicity after exposure to certain types of occupational information. Future research which is directed at determining relevant occupational information for undecided individuals is certainly warranted. With respect to cognitive processing (complexity-simplicity), however, the logical progression in research endeavors might be to determine the relative merit of complexity-simplicity first. The results of the present study serve as a case in point. In studying the tone of occupational information, one of the results showed that negatively toned occupational information was associated with cognitive complexity in subjects. Earlier work (Bodden
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& Klein, 1973; Haase et al., 1979; Winer et al., 1980) contended that occupations which are viewed negatively or as threatening to the subject are processed in a more complex manner than occupations which are viewed positively. Hence, the present study supported previous knowledge about subjects’ cognitive complexity-simplicity responses to information tone. It appears to be time for research to address the issue of merit of cognitive complexity-simplicity in vocational decision making. In other words, now that it is known how subjects will respond to positive and negative occupational information, which responses would be more desirable for effective vocational decision making? Further, would different types of vocationally undecided subjects benefit from differential cognitive complexity-simplicity responses? How might the researcher (and, subsequently, the vocational counselor) adapt relevant occupational information to suit the needs of subjects (and clients) to maximize effective career choices? In an era of increased emphasis on the accountability of psychologists, finding answers to these questions should be of interest to researchers in counseling psychology. REFERENCES Barak, A., & Friedkes, R. (1982). The mediating effects of career indecision subtypes on career-counseling effectiveness. Journal of Vocational Behavior, 20, 120-128. Bodden, J. L. (197Oa). Cognitive complexity as a factor in appropriate vocational choice (Doctoral dissertation, Ohio State University, 1%9). Dissertation Abstracts International, 30, 33080B. Bodden, J. L. (1970b). Cognitive complexity as a factor in appropriate vocational choice. Journal
of Counseling
Psychology,
17, 364-368.
Bodden, J. L., & James L. E. (1976). Influence of occupational information giving on cognitive complexity. Journal of Counseling Psychology, 23, 280-282. Bodden, J. L., & Klein, A. J. (1973). Cognitive differentiation and affective stimulus value in vocational judgments. Journal of Vocational Behavior, 3, 75-79. Camey, C. G., Savitz, C. J., & Weiskott, G. N. (1979). Students’ evaluations of a university counseling center and their intentions to use its programs. Journal of Counseling Psychology,
26, 242-249.
Cesari, J. P., Winer, J. L., Zychlinski, F., & Laird, I. 0. (1982).Influence of occupational information giving on cognitive complexity in decided versus undecided students. Journal
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Fretz, B. R., & Leong, F. T. L. (1982). Vocational behavior and career development, 1981: A review. Journal of Vocational Behavior, 21, 123-163. Haase, R. F., Reed, C. F., Winer, J. L., & Bodden, J. L. (1979). Effect of positive, negative, and mixed occupational information on cognitive and affective complexity. Journal
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Hawkins, J. G., Bradley, R. W., & White, G. W. (1977). Anxiety and the process of deciding about a major and vocation. Journal of Counseling Psychology, 24,398-403. Holland, J. L., Magoon, T. M., & Spokane, A. R. (1981). Counseling psychology: Career interventions, research, and theory. Annual Review of Psychology, 32, 279-305. Kelly, G. A. (1955). The psychology of personal constructs (2 ~01s.). New York: Norton. Osipow, S. H. (1979). A preliminary manual for the Career Decision Scale. Columbus, OH: Marathon Consulting & Press.
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Osipow, S. H., Camey, C. G., Winer, J. L., Yanico, B., & Koschier, M. (1976). Career Decision Scale (3rd rev.). Columbus, OH: Marathon Consulting 62 Press. Sieber, J. E., & Lanzetta, J. T. (1964). Conflict and conceptual structure as determinants of decision making behavior. Journal of Personality, 32, 622-641. Streufert, S. C. (1973). Effects of information relevance in decision making in complex environments. Memory & Cognition, 1, 224-228. U.S. Department of Labor (1977). Occupational outlook handbook. Washington, DC. Winer, J. L., Cesari, J., Haase, R. F., & Bodden, J. L. (1979). Cognitive complexity and career maturity among college students. Journal of Vocational Behavior, 15, 186-192. Winer, J. L., Haase, R. F., Glenn, C. M., Cesari, J., & Bodden, J. (1979, April). Cognitive complexity and vocational preference among college students. Paper presented at the meeting of Southwestern Psychological Association, San Antonio, TX. Winer, J. L., Warren, G. D., Dailey, K. C., & Hiesberger, J. (1980). Complexity of judgment of occupational titles among Holland types. Vocational Guidance Quarterly, 29, 12-24. Received: September 23, 1983.