The use of image-based testing to assess individual differences has increased substantially in recent years, with proponents arguing that they offer a more engaging alternative to text-based psychometric tests. Yet research examining the validity of these tests is near to non-existent. Traditional image-based formats have been little more than an adaptation of self-reports, with images replacing questions but not response options. The current study develops a novel image-based creativity measure, where images replace conventional response scales, and scores on the measures are obtained using a linear regression scoring algorithm to predict three self-reported creativity measures. Using sequential forward selection on a set of 77 image-based items, an optimal solution of 14 items that were valid predictors of self-reported creativity scores were identified. The image-based measure had good test-retest reliability. Implications are discussed in terms of the usefulness of image-based testing for practitioners seeking engaging and short test formats.

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