Consumer choice of on-demand mHealth app services: Context and contents values using structural equation modeling

Lee, Euehun; Han, Saemee; Jo, Sang Hyun

doi:10.1016/j.ijmedinf.2016.10.016

Cited by 60 publications

(54 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[22], [24], [55], [56], [26], [12], [51], [39], [40], [49], [51], [13], [14], [10], [44], [52], [57], [53], [54], [58], [43], [36] Telemedicine Technologies for direct intervention of the clinician, such as a remote consultation with patients, remote collaboration between clinicians, including integrated care.…”

Section: Telecarementioning

confidence: 99%

“…[17], [62], [57], [45], [30] [47], [16], [17], [30] Observational / survey 7 [33], [23], [46], [26], [34], [56], [29] Published Protocol 6 [10], [13], [19], [18], [35], [40] Review article (non-systematic) 6 [15], [53], [22], [50], [49], [38] Review article (systematic) 3 [39], [43], [48] Forty-one studies explicitly described the study population under investigation, with 37 studies focused on older adults alone. Fourteen of these studies specified a specific age range to define older adults with the starting age for this category varying from 55 to 65.…”

Section: Article Type Number Of Articles Article Referencesmentioning

confidence: 99%

See 1 more Smart Citation

E-health for active ageing; A systematic review

2018

View full text Add to dashboard Cite

Enabling successful active ageing is an international priority to meet the challenges of increasing life expectancy. Digital strategies, such as telemedicine and e-health, offer the potential to deliver active ageing in a cost-effective manner at scale. This article aims to establish the extent to which the research literature considers e-health-based and telemedicine-based active ageing interventions. A systematic review was conducted according to PRISMA standards. Independently, two authors searched the Cochrane, EMBASE & CINAHL databases, with subsequent independent extraction and semi-quantitative analysis. We report a considerable breadth in digital active ageing research, which is truly international in its scope. There is a diverse range of both interventions and technologies, including a reassuring focus on community-based interventions. Whilst there are a number of quantitative studies, sample sizes are small, with a limited amount of statistical testing of the results. There is significant variation in the outcome measures reported and little consensus as to the most effective intervention strategies. Overall, whilst there is considerable breadth to the research published in the literature, there is a clear restriction in the depth of this research. There is little overall consensus. This lack of depth and consensus may be due to the need to recognize the important role of technical research elements alongside more traditional research methodologies, such as randomized controlled trials. Enabling both technical and clinical research methods to be recognized, in tandem, has enormous potential to support individuals, communities, clinicians and policy makers to make more informed decisions in relation to active ageing.

show abstract

Section: Telecarementioning

confidence: 99%

Section: Article Type Number Of Articles Article Referencesmentioning

confidence: 99%

E-health for active ageing; A systematic review

2018

View full text Add to dashboard Cite

show abstract

“…Theories, such as the technology acceptance model (TAM) as well as the unified theory of acceptance and use of technology (UTAUT) are frequently used as the theory framework [ 1 , 6 , 7 , 8 , 9 , 10 ]. A variety of influence factors, such as technical factors, personal traits, environment issues, facilitating issues were verified to affect elderly users’ mHealth usage [ 1 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. The prior research greatly enriched our understanding of elderly users’ mHealth usage.…”

Section: Introductionmentioning

confidence: 99%

Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective

Cao

Qin

et al. 2020

IJERPH

View full text Add to dashboard Cite

Aging has increased the burden of social medical care. Mobile health (mHealth) services provide an effective way to alleviate this pressure. However, the actual usage of mHealth services for elderly users is still very low. The extant studies mainly focused on elderly users’ mHealth adoption behavior, but resistance behavior has not been sufficiently explored by previous research. A present study tried to remedy this research gap by examining the effect of overload factors on the mHealth application resistance behavior based on the stimulus-organism-response (SOR) framework. The results indicated that information overload and system feature overload of an mHealth application increased the fatigue and technostress of the elderly user, which further increased their resistance behavior. Meanwhile, we integrated the intergeneration support with the SOR model to identify the buffer factor of the elderly user’s resistance behavior. The results showed that intergenerational support not only directly decrease the elderly user’s mHealth application resistance behavior, but also moderates (weaken) the effects of fatigue and technostress on resistance behavior. The present study also provided several valuable theoretical and practical implications.

show abstract

“…By integrating the Technology Acceptance Model (TAM) and Theory of Planned Behavior, it was found that perceived ease of use and perceived usefulness indirectly influenced people's intention to use mobile health services for their elderly family members through attitude towards technology [16]. Lee et al [17] explored context-and content-related factors affecting people's intention to use mHealth. Using responses from 313 South Koreans aged over 40, they reported that perceived usefulness and convenience significantly influenced people's intention to use mHealth.…”

Section: Introductionmentioning

confidence: 99%

What Motivates Chinese Young Adults to Use mHealth?

Lee

et al. 2019

Healthcare

View full text Add to dashboard Cite

mHealth is one of China’s national strategies that brings affordable, accessible, and convenient health care to its entire population, may they be in cities or rural areas. Although Chinese young adults are among the first to adopt mHealth, the factors influencing Chinese young adults to use mHealth are yet to be studied both empirically and in depth. This study explores the mechanism that determines Chinese young adults’ intention to use mHealth, based on an extended Technology Acceptance Model (TAM). The extended TAM was tested using responses from 486 Chinese young adults. The results showed that perceived usefulness strongly and significantly influenced people’s intention to use mHealth. Additionally, communication effectiveness, health consciousness, and perceived ease of use were found as significant factors influencing people’s intention to use mHealth through perceived usefulness. Distrust was not found to significantly influence people’s intention to use mHealth.

show abstract

Consumer choice of on-demand mHealth app services: Context and contents values using structural equation modeling

Cited by 60 publications

References 70 publications

E-health for active ageing; A systematic review

E-health for active ageing; A systematic review

Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective

What Motivates Chinese Young Adults to Use mHealth?

Contact Info

Product

Resources

About