An exploratory study of ageing women's perception on access to health informatics via a mobile phone-based intervention

Xue, Lishan; Yen, Ching Chiuan; Chang, Leanne; Chan, Hock Chuan; Tai, Bee Choo; Tan, Say Beng; Duh, Henry Been-Lirn; Choolani, Mahesh

doi:10.1016/j.ijmedinf.2012.04.008

Cited by 132 publications

(101 citation statements)

References 42 publications

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“…Also, this study empirically shows that PEOU is significantly correlated with PU (H3: β=0.409, p<0.001). This result conforms with prior findings (Mohamed, 2011;Wu et al, 2011;Hung and Jen, 2012;Xue et al, 2012). The current result implies that if the individuals feel that the m-healthcare is easy to use and effortless to manage they will tend to perceive it as useful.…”

Section: Wwwccsenetorg/ibrsupporting

confidence: 91%

“…8, No. 9; Similar findings were reported by information technology adoption studies implemented in the context of different healthcare domains (Lin, 2011;Mohamed, 2011;Hung & Jen, 2012;Xue et al, 2012;Jaradat & Smadi, 2013;Kuo et al, 2013). In fact, the strength of PU and BI relationship is obviously comparable to prior studies in the field, however the strength of the relationship between PEOU and BI is much stronger than what concluded by previous studies.…”

Section: Wwwccsenetorg/ibrsupporting

confidence: 78%

“…Further analysis has also reported that PEOU and PU were statistically significant in determining the BI to adopt m-technology (Hung & Jen, 2012;Xue et al, 2012;Kuo et al, 2013). Also, PEOU has been identified to strongly affect PU in the context of m-healthcare innovation adoption (Hung & Jen, 2012;Xue et al, 2012). Therefore, based on these discussions, the subsequent hypotheses are suggested.…”

Section: Tam-related Hypothesesmentioning

confidence: 87%

“…More, an empirical analysis was set to investigate the determinants affecting consumers" intention towards m-healthcare (Lin, 2011) and Lin"s analysis has revealed that PEOU and PU had potential impact on BI to use m-healthcare technology. Further analysis has also reported that PEOU and PU were statistically significant in determining the BI to adopt m-technology (Hung & Jen, 2012;Xue et al, 2012;Kuo et al, 2013). Also, PEOU has been identified to strongly affect PU in the context of m-healthcare innovation adoption (Hung & Jen, 2012;Xue et al, 2012).…”

Section: Tam-related Hypothesesmentioning

confidence: 89%

“…In addition, a study has concluded that SI can have certain level of influence on BI to use m-technologies in healthcare (Wu et al, 2011). More, a number of studies documented that SI had influence on intentions to adopt and use m-healthcare (Xue et al, 2012;Jaradat & Smadi, 2013;Zhang et al, 2014).…”

Section: External Variables: Social Influence Trust Security/privacmentioning

confidence: 99%

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Mobile Healthcare Adoption among Patients in a Developing Country Environment: Exploring the Influence of Age and Gender Differences

Faqih¹,

Jaradat²

2015

IBR

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This research was motivated by two considerations: (1) Mobile-based technologies have the potential to improve the delivery process of healthcare services, and (2) limited research has been implemented worldwide to focus on patients" perceptions towards the adoption of mobile healthcare, particularly in developing country environment. This research proposes an extended TAM model as a research framework to better understand the adoption process of mobile healthcare among patients. To serve the objectives of this study, a paper questionnaire was employed to collect data. Previously validated set of measurement items were used to develop the survey instrument. The proposed research model was validated using the PLS-SEM approach (WarpPLS 4.0) with a sample of 366 respondents. The results of the current study have provided adequate statistical support for the extended TAM model. With the exception of cost, all external variables incorporated in this model (including perceived ease of use, perceived usefulness, social influence, trust, and security/privacy) are found influential in shaping the patients" perceptions towards the adoption of mobile-healthcare technology. In addition, the current study demonstrates that demographic variables of age and gender have considerable moderating influence on the adoption of mobile technologies in healthcare systems in Jordan. The current research model can serve as a blueprint for future expansion of research in this vital field of study. Theoretical contributions, practical implications and future research directions of the study are also addressed.

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Section: Wwwccsenetorg/ibrsupporting

confidence: 91%

Section: Wwwccsenetorg/ibrsupporting

confidence: 78%

Section: Tam-related Hypothesesmentioning

confidence: 87%

Section: Tam-related Hypothesesmentioning

confidence: 89%

Section: External Variables: Social Influence Trust Security/privacmentioning

confidence: 99%

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Mobile Healthcare Adoption among Patients in a Developing Country Environment: Exploring the Influence of Age and Gender Differences

Faqih¹,

Jaradat²

2015

IBR

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Tools supporting polypharmacy management in Italy: Factors determining digital technologies' intention to use in clinical practice

Catrini

Ferrario

Mazzone

et al. 2022

Health Science Reports

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Background and Aims: INTERCheckWEB is one of the most outstanding digital technologies, that could be implemented at the hospital level, supporting the clinicians in the evaluation of the therapy appropriateness, reducing the potentially inappropriate prescriptions, for the improvement of the clinical decision-making process. The paper aims at investigating the relationship between clinicians' behaviors towards digital decision support system in therapy appropriateness for elderly patients in polytherapy in medical departments, defining the factors that could influence clinicians to use INTERCheckWEB, for supporting drugs' prescription. Methods: A questionnaire was administered to 70 clinicians referring to Internal Medicine wards, of four Italian hospitals. The authors assessed how perceived usefulness, perceived ease of use, image, and output quality, would affect INTERCheckWeb intention to use. Inferential statistics, by means of a regression analysis, were conducted to define the main aspects useful to understand the factors impacting on such digital technology adoption in clinical practice. Results:The regression analysis reported that image, perceived ease of use and perceived usefulness, as well as the moderator effect of the voluntary use between the perceived usefulness and the intention to use, are the factors that most influence the use of INTERCheckWEB (adjusted R 2 = 0.870).Conclusions: Results demonstrated that clinicians would use INTERCheckWEB, when available, to identify all the information on situations that could be dangerous for the patients, thus limiting the drug-drug interactions, optimizing the overall patient's clinical pathway. Furthermore, the implementation of INTERCheckWEB could also contribute to the proper management of COVID-19 patients, since both hospitalized and symptomatic COVID-19 patients are frequently older, with comorbidities.

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Mobile health services and the elderly: Assessing the determinants of technology adoption readiness in Pakistan

Khan

Azhar

et al. 2021

Journal of Public Affairs

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Technological innovations changed people's daily lives. Wireless technologies, such as mobile phones and other portable gadgets, are becoming an essential part of each generation. With the increasing size of the elderly population around the world, opportunities for the older generation to use wireless technologies, such as gerontechnologies, are increasing. Older adults can use mobile health (mHealth) to receive healthcare at their doorstep. This study uses the UTAUT theoretical framework, extended to perceived ubiquity (PU), perceived trust (PT), and technology anxiety (TA), to investigate the elderly's intention to adopt mobile phone technology for healthcare (i.e., mHealth) in the socioeconomic environment of Pakistan. This study surveys 286 respondents from Islamabad, Pakistan. Structural equation modeling (SPSS version 25 and AMOS version 24) is used to analyze the data. Outcomes show that performance expectancy (PE), effort expectancy, social influence (SI), facilitating conditions, PU, and PT have a positive significant relationship with mHealth adoption intention (AI). However, the results do not indicate the negative relation of TA with mHealth AI. Moreover, gender significantly moderates the relationship between PE and SI and mHealth AI. This study contributes comprehensive knowledge to the existing literature on gerontechnology adoption in the socioeconomic context of a developing economy.

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An exploratory study of ageing women's perception on access to health informatics via a mobile phone-based intervention

Cited by 132 publications

References 42 publications

Mobile Healthcare Adoption among Patients in a Developing Country Environment: Exploring the Influence of Age and Gender Differences

Mobile Healthcare Adoption among Patients in a Developing Country Environment: Exploring the Influence of Age and Gender Differences

Tools supporting polypharmacy management in Italy: Factors determining digital technologies' intention to use in clinical practice

Mobile health services and the elderly: Assessing the determinants of technology adoption readiness in Pakistan

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