Determinants of Adoption of Smartphone Health Apps among College Students

Cho, Jaehee; Quinlan, Margaret M.; Park, Dong-Jin; Noh, Ghee-Young

doi:10.5993/ajhb.38.6.8

Cited by 95 publications

(62 citation statements)

References 35 publications

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“…The following figure7 shows that most of the studies used an integrated model to identify the factors influencing the adoption of mHealth services. The TAM has, however, been used in quantitative and qualitative studies of healthcare services to determine the factors affecting the acceptance of mobile technology by physicians and medical students respectively, and in health studies on subjects such as the adoption of mHealth services (Cho, 2014).…”

Section: Models/theoriesmentioning

confidence: 99%

Understanding the insight of factors affecting mHealth adoption

Kaium

Bao²,

Alam³

et al. 2019

IJRBS

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Numerous studies have addressed the different context of mHealth services among diverse user groups. But due to a lack of understanding the insight of factors affecting the mHealth adoption, it’s crucial need to conduct a systematic review on this issue. The objective of this study was to synthesize the present understanding of the influential factors of mHealth adoption. We performed a systematic literature search on eight electronically reputed scientific databases from 2010 to March 2019, such as Science Direct, Springer, IEEE Xplore, JMIR, Taylor & Francis, Emerald, Mary Ann Liebert and Google Scholar. This was accomplished by gathering data including authors, countries, years, target population, sample size, models/theories, and key influential factors. Primarily, a total of 2969 potentially relatable papers were found, of which 50 met the inclusion criteria. It was found that cross-sectional approach, survey methods and structural equation modeling (SEM) were the most explored research methodologies whereas PLS-SEM was found to be the largest used analysis tools. From the analysis, a total of ninety-four influential factors were clearly recognized and the findings represent that the following 15 factors appeared most recurrently and significantly; perceived usefulness, perceived ease of use, social-influence, subjective norms, self-efficacy, trust, facilitating conditions, technology anxiety, performance expectancy, effort expectancy, cost, attitude, resistance to change, perceived privacy and security, and perceived behavioral control. The research results have significant theoretical and practical implications for mHealth services providers, researchers and policy makers with regards to the Sustainable Development Goals (SDGs) allied to healthcare.

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Section: Models/theoriesmentioning

confidence: 99%

Understanding the insight of factors affecting mHealth adoption

Kaium

Bao²,

Alam³

et al. 2019

IJRBS

View full text Add to dashboard Cite

show abstract

“…Cho et al [27] developed a theoretical model of the adoption of health-related mobile applications. They reported that consciousness, health information orientation, eHealth literacy, Internet health information use efficacy and subjective norms all play a significant role in influencing the intention to use health applications.…”

Section: Related Workmentioning

confidence: 99%

“…Contextual: perceived usefulness [21,17,27], perceived ease of use [17,27], security [30], cost [19,20], required effort [21], gender and interest in new technologies [29].…”

Section: Related Workmentioning

confidence: 99%

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Why Do People Adopt, or Reject, Smartphone Password Managers?

Alkaldi¹,

Renaud²

2016

Proceedings 1st European Workshop on Usable Security

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Abstract-People use weak passwords for a variety of reasons, the most prescient of these being memory load and inconvenience. The motivation to choose weak passwords is even more compelling on Smartphones because entering complex passwords is particularly time consuming and arduous on small devices. Many of the memory-and inconvenience-related issues can be ameliorated by using a password manager app. Such an app can generate, remember and automatically supply passwords to websites and other apps on the phone. Given this potential, it is unfortunate that these applications have not enjoyed widespread adoption. We carried out a study to find out why this was so, to investigate factors that impeded or encouraged password manager adoption. We found that a number of factors mediated during all three phases of adoption: searching, deciding and trialling. The study's findings will help us to market these tools more effectively in order to encourage future adoption of password managers.

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“…Regarding PEOU's diminished role, previous research has found that the PEOU of health apps does not directly predict the behavioral intention to use those new apps. 10 Therefore, this study mainly focused on the role of the PU of diet/fitness apps in influencing one's intention to use them.…”

Section: Perceived Usefulness Of Diet/fitness Appsmentioning

confidence: 99%

Effects of Body Image on College Students' Attitudes Toward Diet/Fitness Apps on Smartphones

Cho

Lee

Park

2015

Cyberpsychology, Behavior, and Social Networking

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Considering the increasing use of diet/fitness apps, this study aimed to investigate how four factors related to body image-evaluations of and orientations toward both appearance and fitness-impact college students' perception of the usefulness of such apps. Based on the Technology Acceptance Model, this study tested a path model examining the relationships among the four body-image-oriented factors, perceived usefulness (PU) of diet/fitness apps, and behavioral intention to use such apps. Results from a path analysis revealed that while college students' evaluation of appearance and fitness decreased the PU of diet/fitness apps, their orientation toward fitness increased the same outcome variable.

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Determinants of Adoption of Smartphone Health Apps among College Students

Abstract: Study findings provide scholars and practitioners with an empirical model of explaining the cognitive and micro-mechanisms of determining the adoption of health apps, especially among younger populations.

Cited by 95 publications

References 35 publications

Understanding the insight of factors affecting mHealth adoption

Understanding the insight of factors affecting mHealth adoption

Why Do People Adopt, or Reject, Smartphone Password Managers?

Effects of Body Image on College Students' Attitudes Toward Diet/Fitness Apps on Smartphones

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