Neurological Outpatients Prefer EEG Home-Monitoring over Inpatient Monitoring—An Analysis Based on the UTAUT Model

Ulrike Baum, Frauke Kühn, Marcel Lichters, Anne-Katrin Baum, Renate Deike, Hermann Hinrichs and Thomas Neumann
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Ulrike Baum: Department of Neurology, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany
Frauke Kühn: Institute for Sensory and Innovation Research (ISI GmbH), Ascherberg 2, 37124 Rosdorf, Germany
Marcel Lichters: Chair of Marketing and Retailing, Faculty of Economics and Business Administration, Chemnitz University of Technology, Reichenhainer Straße 39, 09126 Chemnitz, Germany
Anne-Katrin Baum: Department of Neurology, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany
Renate Deike: Department of Neurology, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany
Hermann Hinrichs: Department of Neurology, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany

IJERPH, 2022, vol. 19, issue 20, 1-22

Abstract: Home monitoring examinations offer diagnostic and economic advantages compared to inpatient monitoring. In addition, these technical solutions support the preservation of health care in rural areas in the absence of local care providers. The acceptance of patients is crucial for the implementation of home monitoring concepts. The present research assesses the preference for a health service that is to be introduced, namely an EEG home-monitoring of neurological outpatients—using a mobile, dry-electrode EEG (electroencephalography) system—in comparison to the traditional long-time EEG examination in a hospital. Results of a representative study for Germany ( n = 421) reveal a preference for home monitoring. Importantly, this preference is partially driven by a video explaining the home monitoring system. We subsequently analyzed factors that influence the behavioral intention (BI) to use the new EEG system, drawing on an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. The strongest positive predictor of BI is the belief that EEG home-monitoring will improve health quality, while computer anxiety and effort expectancy represent the strongest barriers. Furthermore, we find the UTAUT model’s behavioral intention construct to predict the patients’ decision for or against home monitoring more strongly than any other patient’s characteristic such as gender, health condition, or age, underlying the model’s usefulness.

Keywords: home monitoring; electroencephalography (EEG); mobile EEG; partial least squares structural equation modelling (PLS-SEM); UTAUT (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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