The adoption of "silver" e-Health technologies

Buccoliero, Luca; Bellio, Elena

doi:10.1145/2691195.2691303

Cited by 12 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Keränen et al [ 16 ] analyzed the differences in information and communication technologies use, attitudes, and reasons for nonuse among older adults categorized as physically frail, prefrail, and robust, and they found that older adults with frailty were less likely to use information and communication technologies than robust people. In addition, Buccoliero and Bellio [ 17 ] analyzed the factors that affect the adoption of technologies for health by older adults. Research showed that, in the case of health technologies, frailty negatively affects perceived ease of use (PEOU) and perceived usefulness (PU), PU positively affects behavioral intention to use health technologies, and PEOU negatively affects behavioral intention to use these technologies [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, Buccoliero and Bellio [ 17 ] analyzed the factors that affect the adoption of technologies for health by older adults. Research showed that, in the case of health technologies, frailty negatively affects perceived ease of use (PEOU) and perceived usefulness (PU), PU positively affects behavioral intention to use health technologies, and PEOU negatively affects behavioral intention to use these technologies [ 17 ]. Interestingly, Lee et al [ 18 ] found that adults with frailty were less likely to use web-based health resources than healthy adults, but adults with frailty who used the internet alone or with assistance were more likely to obtain web-based health information and advice.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comprehensive Senior Technology Acceptance Model of Daily Living Assistive Technology for Older Adults With Frailty: Cross-sectional Study

Shin¹,

Um²,

Yoon³

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

Background There are considerable gaps between the need for assistive technologies and the actual adoption of these technologies among older adults, although older adults are among the groups that most need assistive technologies. Consequently, research is needed in this area because older adults’ technology acceptance and influencing factors may differ depending on their level of frailty. Objective The objective of this study was to compare frail, prefrail, and robust groups of South Korean adults regarding their behavioral intention to use daily living assistive technologies and the affecting factors—namely, technological context factors, health contexts and abilities, and attitudinal factors—based on a comprehensive senior technology acceptance model. Methods A nationwide sample of 500 older South Korean adults (aged 55-92 years) was analyzed, and multivariate linear regression analyses of the robust, prefrail, and frail groups were performed. The independent and dependent variables consisted of 3 factors based on previous studies. First, technological context factors consisted of gerontechnology self-efficacy, gerontechnology anxiety, and facilitating conditions. Second, health contexts and abilities consisted of self-reported health conditions, cognitive ability, social relationships, psychological function, and physical function. Third and last, attitudinal factors consisted of behavioral intention to use assistive technologies, attitude toward use, perceived usefulness (PU), and perceived ease of use (PEOU). Results The results of the analyses showed that technological context factors such as gerontechnology self-efficacy, health contexts and abilities such as self-reported health conditions and psychological function, and attitudinal factors such as attitude toward use, PU, and PEOU had significant effects on behavioral intention to use daily living assistive technologies. In particular, gerontechnology self-efficacy had a significant relationship with behavioral intention to use these technologies in the robust (r=0.120; P=.03) and prefrail (r=0.331; P<.001) groups. Psychological function (life satisfaction) had a significant relationship with behavioral intention to use these technologies in the robust group (r=–0.040; P=.02). Self-reported health conditions had a significant relationship with behavioral intention to use these technologies in the prefrail group (r=–0.169; P=.01). Although each group had a different significant relationship with the variables, attitudinal factors such as attitude toward use affected all groups (robust group: r=0.190; P=.03; prefrail group: r=0.235; P=.006; and frail group: r=0.526; P=.002). In addition, PU and PEOU in the attitudinal factors had a significant relationship with behavioral intention to use assistive technologies in the robust (PU: r=0.160; P=.01; and PEOU: r=0.350; P<.001) and prefrail (PU: r=0.265; P<.001; and PEOU: r=0.120; P=.04) groups. Conclusions This study found that the comprehensive senior technology acceptance model of daily living assistive technologies had different associations according to the frailty group. These findings provided insights into the consideration of interventions with daily living assistive technologies for older adults with varying levels of frailty.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comprehensive Senior Technology Acceptance Model of Daily Living Assistive Technology for Older Adults With Frailty: Cross-sectional Study

Shin¹,

Um²,

Yoon³

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…Yet as Ling has argued in 2008, intimate personal network can act either as a supportive mechanism or a limiting one (Ling, 2008). This set of conditions and context affects ICT adoption in particular and perceptions of digital technologies in general (Buccoliero & Bellio, 2014). As other research indicates, personal values and interests change over the lifetime (B. L. Neugarten, 1996) and personal communication patterns and the use of media evolve as we grow old, as Ling, Bertel, & Sundsoy (2012) have demonstrated in analyzing differences in SMS use between different age groups.…”

Section: Introductionmentioning

confidence: 99%

Beyond WhatsApp: Older people and smartphones

Rosales

Fernández-Ardèvol

2016

Ro. Comm. & PR

View full text Add to dashboard Cite

<p>This paper analyzes how older people, living in Spain, use smartphones and smartphone applications. Using a mixed methods approach, we compare quantitative results obtained by tracking mobile app usage amongst different generational samples with qualitative, focus-group discussions with active smartphone users. A sample of Spanish smartphone users were tracked during one month in the winter of 2014 (238 individuals, aged 20 to 76 years-old). This was followed by three focus group sessions conducted in the spring of 2015, with 24 individuals aged 55 to 81. As we learned, WhatsApp is currently the most popular application used by people of all ages, including older adults. Smartphones increasingly are playing a central role in the life of older participants, although the frequency of app access is negatively correlated with age. On the other hand, as our data indicates, older adults also use a number of different types of apps that are distinct from that of younger users. Older participants access personal information manager apps (calendar, address book and notes) more often than other age groups. And comparatively, older participants use the smartphone less often in stable locations (home, office, relatives’ home) with Wifi than somewhere else and with mobile data. As we argue, differences in age seem to reflect the evolution in personal interests and communication patterns that change as we grow older. Our study captures new trends in smartphone usage amongst this cohort. It also indicates how a combination of methods may help to assess the validity of the log and qualitative data. We highlight the relevance of conducting careful generational studies in smartphone use and some of the potentials and limitations of making predictive studies of ICT use as we change throughout the life course. Finally, we assert the value of the inclusion of older representatives within research, which ultimately may influence public decisions and the design of new technologies.</p>

show abstract

“…Subjective norm had positively influenced the intention to use in eHealth studies (Alaiad and Zhou, 2014;Zhang et al, 2014;Chang et al, 2015;Jere et al, 2015;Hsieh, 2015aHsieh, , 2015bMalhotra and Galletta, 1999) and Schepers and Wetzels (2007) quantitative meta-analysis discovered that it had positive influence on attitude. A few other studies on eHealth adoption also exhibited positive relationship between subjective norm and perceived usefulness (An, 2005;Kim and Park, 2012;Buccoliero and Bellio, 2014;Ng et al, 2015). Hence, the following hypotheses were developed for this study:…”

Section: Literature Gapmentioning

confidence: 85%

“…People are more likely to accept and use PHR if they believe it to be simple to use PHR if they think it has an easy-to-use interface and is intuitive. In related eHealth studies, perceived ease of use has positive effect on the intention to use (Buccoliero and Bellio, 2014;Rho et al, 2014;Wang et al, 2014;Chang et al, 2015;de Veer et al, 2015;Jere et al, 2015). Furthermore, perceived ease of use boosted users' acceptance level through attitude besides using the mediating effect of perceived usefulness Predicting e-PHR acceptance (Davis et al, 1989;Davis, 1989;Venkatesh and Davis, 2000;An, 2005).…”

Section: Literature Gapmentioning

confidence: 99%

Predicting electronic personal health record (e-PHR) acceptance: evidence from emerging market

Khor,

Teoh,

Vafaei-Zadeh

et al. 2023

IJPHM

View full text Add to dashboard Cite

Purpose With the function to store individual’s data input, personal health record (PHR) enhanced the accessibility to personal health information. This study aims to assess the factors that impact the intention of Malaysian internet users to use PHR and create a modified technology acceptance model (TAM) for eHealth. Design/methodology/approach Multivariate statistical analysis was performed on a total of 216 responses using the partial least square technique based on the cross-sectional survey among Malaysian internet users. Findings Behavioral intention was positively associated to PHR. Subjective norm significantly influenced both attitude and intention to use, whereas trust and perceived usefulness significantly influenced attitude. There was no significant positive impact in the relationships between compatibility and perceived ease of use and intention to use; nevertheless, they positively influenced perceived usefulness. Attitude exhibited mediating influence between trust, perceived usefulness and subjective norm and intention to use. Nonetheless, perceived risk did not affect behavioral intention. Thus, PHR acceptance was well-justified by the modified TAM in evaluating eHealth acceptance. Practical implications The eHealth vendors can enhance their marketing and development strategies on related products. Originality/value Literatures and empirical evidence on eHealth are still scarce, especially in emerging markets. The role of attitude may not be well-researched in health-care context, therefore was included in this study’s modified TAM. Critical determinants, namely, trust and risk, were added to the model.

show abstract

The adoption of "silver" e-Health technologies

Cited by 12 publications

References 9 publications

Comprehensive Senior Technology Acceptance Model of Daily Living Assistive Technology for Older Adults With Frailty: Cross-sectional Study

Comprehensive Senior Technology Acceptance Model of Daily Living Assistive Technology for Older Adults With Frailty: Cross-sectional Study

Beyond WhatsApp: Older people and smartphones

Predicting electronic personal health record (e-PHR) acceptance: evidence from emerging market

Contact Info

Product

Resources

About