<p>Research indicates that behavior change interventions are more effective when tailored to an individual’s readiness to change. However, accurately assessing readiness remains challenging. This study proposes a novel method to detect uncertainty in decision-making by tracking cursor movements during the completion of an online readiness questionnaire. By aggregating cursor tracking data, adjustments can be made to self-reported scores based on the level of detected uncertainty, potentially leading to a more accurate assessment of an individual’s readiness to change. This feasibility study aims to evaluate the functionality and Likert-scale applicability of our newly developed cursor tracking software to assess readiness to change concerning health risk behaviors, specifically emotional eating, smoking, and vaping. Canadian adults <i>N</i> = 30 were recruited from the online platform Prolific. The University of Rhode Island Change Assessment Scale (URICA) was administered relevant to their specific health risk behavior with our integrated cursor tracking software. A one-sample <i>t</i>-test of data from 26 participants indicated that the absolute difference between cursor corrected and uncorrected URICA scores (<i>M</i> = 1.3, <i>SD</i> = 0.6) was significantly different from zero, <i>t</i>(25) = 11.76, <i>p</i> &lt; .001. The cursor tracking data confirmed that the software functioned properly by successfully generating cursor-corrected scores and demonstrated its applicability to Likert-type response scales. This study demonstrates the successful adaptation of cursor tracking technology for Likert scales in an online readiness questionnaire. These findings support the feasibility of the technology, laying the foundation for future studies to validate this approach to enhance readiness assessments to improve intervention matching.</p>