Grant A Pignatiello1, Emily Tsivitse2, Ronald L Hickman2. 1. Case Western Reserve University, Cleveland, OH, United States. Electronic address: gap54@case.edu. 2. Case Western Reserve University, Cleveland, OH, United States.
Abstract
AIM: The aim of this article is to report the psychometric properties of the eight-item cognitive load scale. BACKGROUND: According to cognitive load theory, the formatting and delivery of healthcare education influences the degree to which patients and/or family members can engage their working memory systems for learning. However, despite its relevance, cognitive load has not yet been evaluated among surrogate decision makers exposed to electronic decision support for healthcare decisions. To date, no psychometric analyses of instruments evaluating cognitive load have been reported within healthcare settings. METHODS: A convenience sample of 62 surrogate decision makers for critically ill patients were exposed to one of two healthcare decision support interventions were recruited from four intensive care units at a tertiary medical center in Northeast Ohio. Participants were administered a battery of psychosocial instruments and the eight-item cognitive load scale (CLS). RESULTS: The CLS demonstrated a bidimensional factor structure with acceptable discriminant validity and internal consistency reliability (Cronbach's α = 0.75 and 0.89). CONCLUSIONS: The CLS is a psychometrically sound instrument that may be used in the evaluation of decision support among surrogate decision makers of the critically ill. The authors recommend application of the cognitive load scale in the evaluation and development of healthcare education and interventions.
AIM: The aim of this article is to report the psychometric properties of the eight-item cognitive load scale. BACKGROUND: According to cognitive load theory, the formatting and delivery of healthcare education influences the degree to which patients and/or family members can engage their working memory systems for learning. However, despite its relevance, cognitive load has not yet been evaluated among surrogate decision makers exposed to electronic decision support for healthcare decisions. To date, no psychometric analyses of instruments evaluating cognitive load have been reported within healthcare settings. METHODS: A convenience sample of 62 surrogate decision makers for critically illpatients were exposed to one of two healthcare decision support interventions were recruited from four intensive care units at a tertiary medical center in Northeast Ohio. Participants were administered a battery of psychosocial instruments and the eight-item cognitive load scale (CLS). RESULTS: The CLS demonstrated a bidimensional factor structure with acceptable discriminant validity and internal consistency reliability (Cronbach's α = 0.75 and 0.89). CONCLUSIONS: The CLS is a psychometrically sound instrument that may be used in the evaluation of decision support among surrogate decision makers of the critically ill. The authors recommend application of the cognitive load scale in the evaluation and development of healthcare education and interventions.
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