Features of the learner, task, and instructional environment that predict cognitive load types during patient handoffs: Implications for instruction

We used the cognitive load inventory for handoffs (CLIH) to identify predictors of cognitive load types during patient handoffs in order to identify opportunities to improve instruction. In 2019, out of a total of 1,807 residents and fellows within a 24-hospital health system, 693 (38.4%) completed the CLIH after a patient handoff. Multivariable regression yielded predictors for each cognitive load type. Intrinsic load associated with features of the learner (fatigue positively associated) and task (higher complexity clinical setting, number of patients, and handoff length positively associated). Extraneous load associated with learner (fatigue positively associated, and number of times trained in the verbal protocol negatively associated) and task design (number of sources of written information positively associated). Germane load associated with learner (level of training negatively associated, and fatigue positively associated) and instructional environment (interruptions negatively associated and formal feedback positively associated). Implications for instructional design are explored.

Automated summary

The study utilized CLIH to identify predictors of cognitive load types during patient handoffs, highlighting the impact of learner and task characteristics on cognitive load types. The findings provide insights for improving instructional design.