TY - JOUR
T1 - Factors Affecting Compliance with Alerts in the Context of Healthcare-related Emergencies
AU - Kumar, Manasvi
AU - Leroy, Gondy
N1 - Funding Information:
We would like to thank Prof. Philip Harber from the University of Arizona for his ideas and suggestions while designing the scenarios for the study. We would also like to thank the AIS-TRR reviewers for their thoughtful suggestions in revisions to our manuscript. Finally, we would also like to thank Dr. Susan Brown for her encouragement and guidance. This research was supported by the National Library of Medicine of the National Institutes of Health under Award Number R01LM011975. All content reported is solely the responsibility of the authors.
Funding Information:
Gondy Leroy, PhD, is Professor in MIS at the University of Arizona. Her research focuses on natural language processing and applied machine learning. She has won grants from NIH, AHRQ, NSF, Microsoft Research and several foundations, totaling more than $2.4M as principal investigator. She earned a combined BS and MS (1996) in cognitive, experimental psychology from the Catholic University of Leuven, (1996) and a MIS (1999) and PhD (2003) in management information systems from the University of Arizona. She serves on the editorial board of the Journal of Database Management, International Journal of Social and Organizational Dynamics in IT, Health Systems, Journal of Business Analytics, and co-chairs several sessions, tracks, workshops, and conferences focusing on design science and healthcare IT. She is the author of the book “Designing User Studies in Informatics (Springer, 2011). Finally, she is an active contributor to increasing the diversity and inclusion in computing and founded and leads the “Tomorrow’s Leaders Equipped for Diversity” program at the University of Arizona’s Eller School of Management.
Publisher Copyright:
© 2021 by the Association for Information Systems.
PY - 2021
Y1 - 2021
N2 - This study is a conceptual replication of the study by Han et al. (2015) in which the authors evaluated factors affecting students’ compliance with emergency instructions during campus emergencies. The current study focused on broader public health-related emergencies using eight scenarios evaluated by Amazon Mechanical Turk (AMT) participants. Analysis on the aggregated data showed that subjective norm and trust in information quality positively affected intention to comply with instructions, consistent with the original study. Three follow up analyses provide more nuanced results. First, an abridged dataset was created by filtering out participants whose reasons for non-immediate compliance weren't related to verifying information and then complying. Analysis on this dataset showed that subjective norm no longer positively affected intention to comply. Second, scenarios used in the study were grouped by characteristics such as development speed, frequency, and area affected, and the analysis was redone. Factors affecting intention to comply immediately changed based on the characteristic, with subjective norm positively affected intention to comply in slow-developing scenarios, scenarios that affect at a limited area, and commonly occurring scenarios, while trust in information quality affects the other scenarios. Third, recall of information from the notification was collected from participants and analyzed. Results show that participants who chose to comply immediately recalled more information than others. Our replication study shows some support for the original conclusions; however, the broader setting and more nuanced analyses show also differences between both studies.
AB - This study is a conceptual replication of the study by Han et al. (2015) in which the authors evaluated factors affecting students’ compliance with emergency instructions during campus emergencies. The current study focused on broader public health-related emergencies using eight scenarios evaluated by Amazon Mechanical Turk (AMT) participants. Analysis on the aggregated data showed that subjective norm and trust in information quality positively affected intention to comply with instructions, consistent with the original study. Three follow up analyses provide more nuanced results. First, an abridged dataset was created by filtering out participants whose reasons for non-immediate compliance weren't related to verifying information and then complying. Analysis on this dataset showed that subjective norm no longer positively affected intention to comply. Second, scenarios used in the study were grouped by characteristics such as development speed, frequency, and area affected, and the analysis was redone. Factors affecting intention to comply immediately changed based on the characteristic, with subjective norm positively affected intention to comply in slow-developing scenarios, scenarios that affect at a limited area, and commonly occurring scenarios, while trust in information quality affects the other scenarios. Third, recall of information from the notification was collected from participants and analyzed. Results show that participants who chose to comply immediately recalled more information than others. Our replication study shows some support for the original conclusions; however, the broader setting and more nuanced analyses show also differences between both studies.
KW - Analytical modeling
KW - Computer-mediated communication
KW - Surveys
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U2 - 10.17705/1atrr.00068
DO - 10.17705/1atrr.00068
M3 - Article
AN - SCOPUS:85123541376
SN - 2473-3458
VL - 7
JO - AIS Transactions on Replication Research
JF - AIS Transactions on Replication Research
ER -