Psychometric evaluation of the Smartphone for Clinical Work Scale to measure nurses’ use of smartphones for work purposes
Bautista, John Robert
Lin, Trisha Tsui-Chuan
Date of Issue2018
Wee Kim Wee School of Communication and Information
Objective: This study reports the development and psychometric evaluation of the Smartphone for Clinical Work Scale (SCWS) to measure nurses’ use of smartphones for work purposes. Materials and Methods: Items were developed based on literature review and a preliminary study. After expert consultations and pilot testing, a 20-item scale was administered in January-June 2017 to 517 staff nurses from 19 tertiary-level general hospitals in Metro Manila, Philippines. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to evaluate construct validity. Structural equation modeling (SEM) was used to test the predictive validity of SCWS on perceived work productivity. Results: EFA results show that 15 out of 20 items loaded on five factors: communication with clinicians via call and text, communication with doctors via instant messaging, information seeking, communication with nurses via instant messaging, and communication with patients via call and text. CFA results suggest that the five factors that form SCWS have adequate fit to the data, thus supporting construct validity. SEM results suggest predictive validity since SCWS was positively associated with perceived work productivity. Discussion: This study shows that nurses use their smartphones in various ways to satisfy communication and information seeking needs. In general, such usage can enhance their work productivity. These findings can have implications when developing policies on healthcare professionals’ use smartphones use in clinical settings. Conclusion: The 15-item SCWS showed satisfactory psychometric properties for use in future studies. These studies can focus on identifying factors associated with nurses’ use of smartphones for work purposes.
Journal of the American Medical Informatics Association
© 2018 The Author(s). All rights reserved. This paper was published by Oxford University Press in Journal of the American Medical Informatics Association and is made available with permission of The Author(s).