Assessing the attentional demand: improvements to the experimental protocol and possible learning effects

Introduction: Attention control is a fundamental component of cognitive functioning and involves the ability to selectively process relevant stimuli, divide attention across tasks, and flexibly switch between attention demands. The present study describes the development and validation of the Attentional Demands Task (AD-Task), a new paradigm designed to measure selective attention, divided attention, and the cognitive costs associated with switching between these attentional processes. Based on and expanded upon the Switching Attentional Demands Task (SwAD-Task), the AD-Task introduces increased stimulus complexity, optimized temporal dynamics, and enhanced ecological validity. Methods: Forty-one healthy young adults (age: 21.0 ± 2.25; 33 F) completed the AD-Task along with established attentional paradigms (Oddball Task for selective attention, Dual-Task for divided attention). In a second experimental phase, the potential effects of practice were evaluated through an intensive training protocol involving 22 participants (age: 22.5 ± 2.89; 16 F). Results: Performance indices demonstrated strong convergent validity, with significant correlations in reaction times and accuracy measures across tasks. As expected, divided attention was associated with slower response times and reduced accuracy compared to selective attention, reflecting the increased cognitive load of processing multiple stimuli within a single modality. Analysis of switching costs revealed asymmetries, with selective attention displaying greater vulnerability to Task switching effects. No significant differences emerged between trained and untrained groups in overall task performance, aside from a modest improvement in target discrimination accuracy under switching conditions in the trained group. Discussion: These findings support the AD-Task as a sensitive, reliable, and repeatable measure of attentional control and flexibility. The AD-Task advances current methodologies by addressing previous limitations related to sensory modality interference and limited task complexity.