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<p>Vocational interests are one of the most widely studied individual difference constructs in psychology, education, and management. Despite their widespread importance and use, scholars have yet to determine the optimal way to measure vocational interests and match people’s interests to careers. Empirical-keyed occupational scales tend to have the highest predictive validity and closest alignment with recommendations of specific jobs; however, they are costly and difficult to develop, and interpretation of results can be unclear because the items may not directly relate to occupations. As a result, broader theoretical interest scales tend to be more widely used. In the present work, we investigated a new method of interest assessment using occupational task statements from the Occupational Information Network (O*NET). In study 1, we established the construct validity of task items for measuring occupational interests. Results provided clear evidence that task-based interest scores converged with empirically keyed interest scores from the Strong Interest Inventory. In study 2, results indicated that the task-based interest measure was a better predictor of work outcomes measured 2&#xa0;weeks later—including turnover intentions, job satisfaction, perceived person-job fit, and innovative performance—than RIASEC interest scores from the O*NET interest profiler. Taken together, this paper provides a compelling case for using open-source task statements from O*NET to measure people’s interest in specific occupations. This method has widespread and immediate applications for research, education, counseling, and human resource management.</p>

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Interest in Context: Using Work Tasks to Measure Occupational Interests

  • 期刊论文

  • 发表日期：

    2025年5月30日

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  • Alexis Hanna,
  • Kevin A. Hoff,
  • James Rounds

摘要

Vocational interests are one of the most widely studied individual difference constructs in psychology, education, and management. Despite their widespread importance and use, scholars have yet to determine the optimal way to measure vocational interests and match people’s interests to careers. Empirical-keyed occupational scales tend to have the highest predictive validity and closest alignment with recommendations of specific jobs; however, they are costly and difficult to develop, and interpretation of results can be unclear because the items may not directly relate to occupations. As a result, broader theoretical interest scales tend to be more widely used. In the present work, we investigated a new method of interest assessment using occupational task statements from the Occupational Information Network (O*NET). In study 1, we established the construct validity of task items for measuring occupational interests. Results provided clear evidence that task-based interest scores converged with empirically keyed interest scores from the Strong Interest Inventory. In study 2, results indicated that the task-based interest measure was a better predictor of work outcomes measured 2 weeks later—including turnover intentions, job satisfaction, perceived person-job fit, and innovative performance—than RIASEC interest scores from the O*NET interest profiler. Taken together, this paper provides a compelling case for using open-source task statements from O*NET to measure people’s interest in specific occupations. This method has widespread and immediate applications for research, education, counseling, and human resource management.