The Structure and Relationship of Work-Related Interests & Needs

Abstract

Measures of work-related interests (the Interest Inventory, Career Orientation Profile-Work Activity Preferences, and US Employment Services Questionnaire) and measures of needs (the Inventory of Work-Related Needs, Career Orientation Profile-Benefits and Opportunities, and Minnesota Importance Questionnaire) were used to clarify the nature of these domains. Mired with inconsistencies in terminology, this study explored each domain separately by a) inspecting measurement characteristics, b) examining the underlying structure of the recently developed Interest Inventory and the newly developed I-WRN, c) identifying the cross instrument within domain factor structures, and d) investigating convergent-divergent validity. Because there had been very little previous research addressing the relationship between interests and needs, the relationship between these two domains was explored through e) cross-domain structural analysis of all six instruments, f) canonical correlation analyses and g) multiple regression analyses. Data were collected from a sample of approximately 800 respondents drawn from the subject pool at North Carolina State University. The subject pool consisted of undergraduates and included students from 95 different curricular majors.

Internal consistency reliabilities from the various scales ranged from .28-.96 with the 68 percent of them ranging between .80-.90. Test-retest reliabilities for the I-WRN, Interest Inventory, and the CareerOp-Benefits and Opportunities ranged from .52-.89, and mean individual profile test retest correlations ranged from .66-.83. Factor analysis of the 42 individual items of the Interest Inventory resulted in an eight-factor solution. The eight interest factors were Technical Activities, Business Management, Animal & Plant Life, Health Related, Arts & Humanities, Security & Enforcement, Architectural Design, Human Development & Assistance, and Physical Performing. Factor analysis of the 10 Interest Inventory scales resulted in a five-factor solution: Technical Activities, Human & Animal Care, Business Management, Humanities, and Security, Enforcement & Physical Performing. These two factor solutions explained 52 and 48 percent of the variance respectively. An overall factor analysis of the three work-related interest questionnaires resulted in an eight-factor solution that accounted for 73 percent of the total variance. The eight factors were Technical & Hardware Related, Business Detail, Leadership, Health Related, Liberal Arts, Protection, Enforcement & Physical Performing, Caring for Plants & Animals, and Customer Sales & Service. The factor structures from the above mentioned analyses were comparable to results from previous research in this area. Convergent-discriminant correlational analyses of the Interest Inventory with more established measures provided evidence for the construct validity of the Interest Inventory.

Factor analysis of the Inventory of Work-Related Needs resulted in a five-factor solution accounting for 72 percent of the total variance. The factors were titled Responsibility & Recognition, Comfort, Self-Actualization, Enriched Working Environment, and Helping. This structure closely resembles existent theory including Maslow's need hierarchy. Analysis of all three work-related need instruments together produced an eight-factor solution that accounted for 67 percent of the variance. The resultant factors were stable across sub-samples. Convergent-discriminant correlational analyses of the I-WRN with more established measures provided evidence for the construct validity of the I-WRN.

In the investigation of cross-domain relationships an overall factor analysis was performed on all six interests and need questionnaires. This analysis produced a 14-factor solution accounting for 70 percent of the total variance. The factors were titled Responsibility & Recognition, Technical & Hardware Related, Business (low), Business (high), Humanitarian, Comfort, Artistic, Self-Actualization, Interpersonal Relations, Security & Physical Performing, Plants & Animals, Status, Autonomy, and Activity. This solution produced pure factors, in that the variables were grouped according to their domains, and only one mixed factor emerged that was marked by salient variables from both domains. In a second set of cross-domain analyses, canonical correlations revealed a number of statistically significant relationships. Across the three sets of equations there were eight statistically significant canonical correlation coefficients. However, correlations between the interest canonical variates and need variables were relatively low, suggesting that although some relationships existed between the interests and needs, these constructs fall into two distinct domains.

In a final set of cross domain analyses, multiple correlations again supported the conclusion that although needs and interests relate in a consistent way and appear to be components of the same motivational system they are distinct domains. In sum, the results emphasize the distinct nature of interests and needs and call for an expansion in the use of work-related needs in predicting outcomes such as vocational choice. Historically interests have been used to predict outcomes such as career choice and needs have been used as criterion variables (Dawis, 1991). However, needs are likely more meaningful than unfamiliar interest activities and easier to rate especially for students pursuing career exploration. Understanding the relationship between work-related interests and needs is critical for organizations today. They are increasingly faced with work role transitions due to attrition, mobility, de-layering activities and change in job functionality due to technological changes.