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.

中文翻译：

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学习者，任务和教学环境的功能，可预测患者交接期间的认知负荷类型：对教学的影响

我们使用了用于交接的认知负荷清单（CLIH）来确定患者交接期间认知负荷类型的预测因素，以识别改善教学的机会。2019年，在24医院卫生系统中的1,807名居民和研究人员中，有693名（38.4％）在患者交接后完成了CLIH。多变量回归产生每种认知负荷类型的预测因子。与学习者的特征（疲劳成正相关）和任务（复杂性较高的临床环境，患者人数和移交长度成正相关）的内在负荷相关。与学习者相关的外来负载（正相关的疲劳，与口头协议中训练的次数负相关）和任务设计（正相关的书面信息来源的数量）。与学习者相关的日耳曼语负荷（培训水平负相关，疲劳水平正相关）和教学环境（中断负相关，形式反馈正相关）。探索对教学设计的影响。