Assessing user acceptance towards automated and conventional sink use for hand decontamination using the technology acceptance model

Dawson, Carolyn; Mackrill, Jamie; Cain, Rebecca

doi:10.1080/00140139.2017.1316018

Cited by 15 publications

(10 citation statements)

References 31 publications

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“…TAM models have revealed their ability to explain the differences between technology usage and behaviour across different contexts (Al-Okaily et al 2020c;Baptista and Oliveira 2016;Chen et al 2019;Dawson et al 2017).…”

Section: Technology Acceptance Model (Tam)mentioning

confidence: 99%

Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis

Alsyouf

Masa’deh

Albugami

et al. 2021

Risks

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Although technology trends and acceptance have been considered crucial topics, limited research has examined stress-specific factors such as health anxiety in the context of the COVID-19 pandemic based on people’s attitudes toward a mobile health app using the Technology Acceptance Model (TAM). Accordingly, this study primarily highlights the psychological determinants stemming from the COVID-19 pandemic that affect the usage of a mobile health app. The study followed a cross-sectional design and adopted a snowball sampling technique to collect the data. The findings showed a significant association between perceived usefulness, perceived ease of use, and event-related fear and Tabaud App intention. The relationships between Tabaud App intention and COVID-19 anxiety on Tabaud App usage were also revealed. The study found a significant association between perceived ease of use and perceived usefulness. Additionally, the multi-group analysis showed that only two paths related to Tabaud App intention, perceived ease of use and perceived usefulness, differed significantly between males and females. Additionally, women experienced anxiety disorders more than men. The study contributes to the previous knowledge on the field by examining the psychological determinants resulting from the COVID-19 pandemic that influence using a mobile health app, namely, event-related fear and COVID-19 anxiety. The study results may help governments, health policymakers, and health organisations in Saudi Arabia contain the spread of the COVID-19 pandemic.

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Section: Technology Acceptance Model (Tam)mentioning

confidence: 99%

Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis

Alsyouf

Masa’deh

Albugami

et al. 2021

Risks

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“…TAM models are consistently shown to be able to explain a large amount of variance in technology usage and acceptance behavior across varied contexts. 31–36 While the models have been widely tested, validated and extended in health informatics applications used by medical professionals, 37–39 they have seldom been applied to the modeling of consumer acceptance of health informatics applications. 15,40,41 In fact, consumers’ acceptance may be different from that of professionals, 42 as consumers are more likely to encounter difficulties in using health informatics applications due to their lack of self-efficacy and usability issues.…”

Section: Theoretical Background and Research Hypothesesmentioning

confidence: 99%

Integrating usability and social cognitive theories with the technology acceptance model to understand young users’ acceptance of a health information portal

Tao¹,

Shao²,

Wang

et al. 2019

Health Informatics J

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The past decade has seen the proliferation of health information portals; however, consumer acceptance of the portals has proven difficult and rate of use has been limited. This study developed a consumer acceptance model by integrating usability and social cognitive theories with the technology acceptance model to explain young Internet users’ acceptance of health information portals. Participants (n = 201) completed a self-report questionnaire measuring model constructs after attending a usability testing with a typical health information portal. Results showed that the hypothesized model accounted for 56 percent of the variance in behavioral intention to use the portal and explained consumer acceptance well. Both subjective usability and application-specific self-efficacy served as significant antecedents in the model, while application-specific self-efficacy also moderated the effect of subjective usability on perceived ease of use. The findings can help practitioners with the design and implementation of health information portals and other health informatics applications in support of consumer acceptance.

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“…Ghazizadeh, et al [52] proposed an automation acceptance model (AAM) which included trust as a crucial contributor to explain user acceptance of automation technology. Previous studies have used trust to explain technology acceptance related to automation such as automated sinks for hand decontamination [53]. In the context of AV acceptance, the AAM was embraced by Körber, et al [54] who suggested that trust in AVs is a vital precondition for facilitating the acceptance AVs to take advantage of benefits such as human error reduction.…”

Section: ) Trustmentioning

confidence: 99%

Critical Factors Influencing Acceptance of Automated Vehicles by Hong Kong Drivers

et al. 2020

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This study aimed to identify critical factors that influence acceptance of automated vehicles among drivers. The focus of this study was on automated vehicles (AVs) of level 3 (conditional driving automation) as defined by the Society of Automotive Engineers. A research model was proposed here by using the technology acceptance model (TAM) with trust, risk perception (perceived safety risk and perceived privacy risk), compatibility, and system quality. A cross-sectional structured questionnaire survey was used to collect quantitative data from 237 drivers in Hong Kong. The data were analyzed to test the proposed research model by structural equation modeling. The proposed research model was found to explain 68% of the variance in intention to use AVs. In contrast with the TAM constructs of perceived usefulness and perceived ease of use, the results of this study indicated that trust was the most important factor in shaping a positive attitude towards using AVs, which affected driver intention to use AVs. Also, trust was found to be influenced by perceived safety risk, compatibility, and system quality. This study is the first attempt to consider technological factors related to AVs (compatibility and system quality) in explaining AV acceptance among drivers and highlighted the importance of the technological factors in the context of driver acceptance of AVs. Based on the findings of this study, several recommendations are discussed to help AV developers and governments to improve driver attitudes towards adoption of AVs.

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Assessing user acceptance towards automated and conventional sink use for hand decontamination using the technology acceptance model

Cited by 15 publications

References 31 publications

Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis

Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis

Integrating usability and social cognitive theories with the technology acceptance model to understand young users’ acceptance of a health information portal

Critical Factors Influencing Acceptance of Automated Vehicles by Hong Kong Drivers

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