The determinants of home healthcare robots adoption: An empirical investigation

Alaiad, Ahmad; Zhou, Lina

doi:10.1016/j.ijmedinf.2014.07.003

Cited by 259 publications

(223 citation statements)

References 38 publications

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“…Legal concern refers to the possibility of users worry caused by the shortage of law enforcement (Alaiad & Zhou, 2014). Previous research has also implied that perceived risk and privacy could effectively predict users' adoption intention and their trust (Alaiad & Zhou, 2014;Kim et al, 2008). This study argues that the more the perceived risk, the less trust and adoption intention of mobile health services.…”

Section: Perceived Riskmentioning

confidence: 82%

“…In this paper, we measure perceived risk through the following three variables, including privacy risk, performance risk, legal concern. The measurement of legal concern is enlighten by Alaiad and Zhou(2014). In their research, they explored the impact of privacy concern, ethical concern, and legal concern on the adoption intention of home medical robots (Alaiad & Zhou, 2014).…”

Section: Perceived Riskmentioning

confidence: 99%

“…The measurement of legal concern is enlighten by Alaiad and Zhou(2014). In their research, they explored the impact of privacy concern, ethical concern, and legal concern on the adoption intention of home medical robots (Alaiad & Zhou, 2014). In the mobile health context, privacy risk refers to the possibility of information abuse caused by the use of mobile health services, such as information theft, information leakage(N. Lim, 2003).…”

Section: Perceived Riskmentioning

confidence: 99%

“…Performance risk refers to the possibility of the match between desired outcomes and actual use from mobile health services(N. Lim, 2003). Legal concern refers to the possibility of users worry caused by the shortage of law enforcement (Alaiad & Zhou, 2014). Previous research has also implied that perceived risk and privacy could effectively predict users' adoption intention and their trust (Alaiad & Zhou, 2014;Kim et al, 2008).…”

Section: Perceived Riskmentioning

confidence: 99%

See 3 more Smart Citations

What Predicts Patients� Adoption Intention Toward mHealth Services in China: Empirical Study (Preprint)

Deng¹,

Hong²,

Ren³

et al. 2017

Preprint

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Background:With the increasing concern of Healthy China and the development of information technology, mobile health enables patients access health information and interacting with doctors anytime and anywhere. Since the success of mobile health would depend on the adoption of patients, examining patients' willingness to use it is considered critical. Objective:This study aims to explore the determinants of mobile health services adoption among Chinese patients by an extended TAM with trust and perceived risk. Method:We conducted a questionnaire-based survey in three large Chinese hospitals, and analyzed the data with structural equation model. Results:The results reveal that the proposed model fits well. Specifically, trust, perceived usefulness and perceived ease of use positively correlate with mobile health services adoption. While, privacy risk and performance risk negatively correlate with the patients' trust and adoption intention toward mobile health. In addition, age and chronic condition of patients could predict their trust level and adoption intention towards mobile health respectively. Conclusion:We conclude that TAM works for the context of mobile health adoption in general, though the significance has declined. Supplementary to technical factors, trust and perceived risk are critical in explaining mobile health services adoption among Chinese patients.

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Section: Perceived Riskmentioning

confidence: 82%

Section: Perceived Riskmentioning

confidence: 99%

Section: Perceived Riskmentioning

confidence: 99%

Section: Perceived Riskmentioning

confidence: 99%

See 2 more Smart Citations

What Predicts Patients� Adoption Intention Toward mHealth Services in China: Empirical Study (Preprint)

Deng¹,

Hong²,

Ren³

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…Alaiad and Zhou define privacy concerns as the stakeholders' lack of control over the collection and use of their personal information after they have adopted the system [1]. Despite the fact that robots are perceived as independent entities by their users, they generally communicate with many other systems.…”

Section: Robots As Information Hubsmentioning

confidence: 99%

Implementing an ethical approach to big data analytics in assistive robotics for elderly with dementia

Felzmann

Beyan

Ryan

et al. 2016

SIGCAS Comput. Soc.

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In this paper, we analyse the ethical relevance of emerging informational aspects in robotics for the area of care robotics. We identify specific informational characteristics of contemporary and emerging robots, especially the fact of their increasing informational connectedness. We then outline specific ethical considerations arising in the design process in the H2020 project MARIO which aims to develop a care robot for persons with mild to moderate dementia in home and residential care settings. Ethical considerations regarding specific functionalities of the proposed care robot are outlined.

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Nurse preferences of caring robots: A conjoint experiment to explore most valued robot features

et al. 2022

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Both the COVID epidemic and increasing innovation have led to the growing involvement of robotic caregivers in nursing services. With the potential revolution in the computational power of artificial intelligence, Metzler et al. (2016) and Locsin (2017) have envisioned a future in which robots could become true professional collaborators of nurses. However, one of the main criticisms of the development of such skilled robots is that nurses seem to have very limited (or no) say in the development of robots for nursing (Archibald and Barnard, 2018;Eriksson et al., 2017). This may be explained by the limited expertise of nurses and the limited research on robotics. Glasgow et al. (2018) argued that nurses are missing critical opportunities to be involved in the design and development of future technology that could dramatically improve patient care. Even though nurses have historically been excluded from high-level decision-making, Robert (2019) affirmed that nurse participation in the design and deployment of telehealth robots is critical for the best use of the technology. Studying nurses' attitudes towards nursing robots is key because understanding nurses' preferences

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The determinants of home healthcare robots adoption: An empirical investigation

Cited by 259 publications

References 38 publications

What Predicts Patients� Adoption Intention Toward mHealth Services in China: Empirical Study (Preprint)

What Predicts Patients� Adoption Intention Toward mHealth Services in China: Empirical Study (Preprint)

Implementing an ethical approach to big data analytics in assistive robotics for elderly with dementia

Nurse preferences of caring robots: A conjoint experiment to explore most valued robot features

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