Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Dec 28, 2021)
Date Submitted: Sep 2, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
User experience and user acceptance of a speech recognition-based diagnostic management application: mobile health at point-of-care
ABSTRACT
Background:
In-patient management like ordering medical tests is time-consuming and burdens physicians on the ward with non-clinical tasks. We developed and implemented a smartphone-based mobile application (MA) that uses speech recognition for the ordering of radiological examinations. While we could show that the MA supported process was faster, its acceptance and usability remaines unknown.
Objective:
We examined the user experience (1), user acceptance (2) and the determinants of user acceptance (3) of a new mobile, speech recognition guided in-patient management MA.
Methods:
A comprehensive questionnaire based on the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and use of Technology (UTAUT) was given to all physicians at the Department of Trauma and Plastic Surgery at the University Hospital of Wuerzburg , Germany. The user experience with the new MA was compared to the usual desktop application (DA) workflow embedded in the clinical information system (i.s.h.med, Cerner Health Services Deutschland GmbH, Berlin, Germany). The domains of user experience consisted of overall attractiveness, pragmatic quality, and hedonic quality. For the determinants of the acceptance model, we employed hierarchical regression analysis.
Results:
Twenty-one out of 30 physicians (mean age 34±8 years, 62% male) completed the questionnaire (response rate 70%). Compared to the conventional DA workflow, the new MA showed superior overall attractiveness (mean difference +2.15±1.33), pragmatic quality (mean difference +1.90±1.16), hedonic quality (mean difference 2.41±1.62; all p<.001). The user acceptance measured by the UTAUT (mean 4.49, SD 0.41; min. 1, max. 5) was also high. Performance expectancy (beta=0.57, p=.02) and effort expectancy (beta=0.36, p=.04) were identified as predictors of acceptance explaining 65.4% of its variance.
Conclusions:
There is huge potential in reducing the physicians’ burden of administrative tasks by adopting innovative DHI like our speech recognition guided MA in daily ward routine. With this study, we could illustrate that physicians are more than willing to implement such innovative mobile health solutions.
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