Abstract
The present study investigated the psychometric properties of the Basic Interest Markers (BIM), a public-domain broadband measure of basic interests. Unlike broader general interest frameworks such as Holland’s RIASEC types, basic interests represent more specific content domains and provide a granular view of vocational preferences and inclinations. We used Item Response Theory (IRT) to perform item analysis to identify the most informative items in each BIM scale and, by extension, reduce scale lengths. In addition, we used confirmatory factor analysis to test model fit for the BIM scales and previously suggested higher-order clusters. Data were drawn from a total of 2,009 participants, comprising two samples of undergraduate college students ( N = 910 and N = 120) and samples of 164 university alumni and 815 adults recruited through Amazon Mechanical Turk. Our analysis demonstrated that latent trait estimates obtained from the BIM-343 were similar to those of our proposed modified BIM-181, with model fit favoring the latter. Overall, we provide support for the use of a modified version of the BIM inventory that more accurately captures the intended construct while simultaneously reducing test length by nearly 50%.
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