Examination of Influential Factors of Tablet PC Use - Application of Theory of Planned Behavior and Technology Acceptance Model -

Son, Hyunjung; Lee, Sang‐Won; Jin, Bumsub; 조문희,

doi:10.14696/jcs.2014.12.14.4.106

Cited by 5 publications

(3 citation statements)

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“…Furthermore, smartphone has been said to be a close substitute to tablets because of their many shared interfaces and functionality (Tofel, 2012). On the other hand, some studies at the individual level support the notion that tablets and smartphones have a complementary relationship (Son et al, 2014;Song & Lee, 2012). Two products are seen as complementary when, using together, one can add or enhance the value/functions of the other (Ha & Ganahl, 2004).…”

Section: Price Factor -Complementary Device V Substitutive Devicementioning

confidence: 99%

“…Complementarity encourages dual adoption/ownership. A recent consumer level study suggests that the relationship between tablet PCs and smartphones is complementary in terms of functionality for smart devices, at least in the market's initial stage (Son et al, 2014). Song and Lee (2012) also found that people show strong intention to own both a tablet and a smartphone.…”

Section: Price Factor -Complementary Device V Substitutive Devicementioning

confidence: 99%

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An empirical analysis of tablet PC diffusion

Lee

Chan‐Olmsted

2017

Telematics and Informatics

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Section: Price Factor -Complementary Device V Substitutive Devicementioning

confidence: 99%

Section: Price Factor -Complementary Device V Substitutive Devicementioning

confidence: 99%

An empirical analysis of tablet PC diffusion

Lee

Chan‐Olmsted

2017

Telematics and Informatics

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“…This key concept of the model suggests that the evaluation of the use of wearable health care devices (ie, when performance expectancy exceeds effort expectancy) would lead to a decision on device acceptance [ 17 ]. Similar to Son et al [ 39 ], we developed items to measure effort expectancy (ie, the degree of perceived ease of use). We hypothesized that effort expectancy would affect performance expectancy and the intention of continued use.…”

Section: Methodsmentioning

confidence: 99%

Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

Ha¹,

Park²,

Lee³

et al. 2023

JMIR Form Res

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Background Prevention of the risk factors for metabolic syndrome (MetS) in middle-aged individuals is an important public health issue. Technology-mediated interventions, such as wearable health devices, can aid in lifestyle modification, but they require habitual use to sustain healthy behavior. However, the underlying mechanisms and predictors of habitual use of wearable health devices among middle-aged individuals remain unclear. Objective We investigated the predictors of habitual use of wearable health devices among middle-aged individuals with risk factors for MetS. Methods We proposed a combined theoretical model based on the health belief model, the Unified Technology of Acceptance and Use of Technology 2, and perceived risk. We conducted a web-based survey of 300 middle-aged individuals with MetS between September 3 and 7, 2021. We validated the model using structural equation modeling. Results The model explained 86.6% of the variance in the habitual use of wearable health devices. The goodness-of-fit indices revealed that the proposed model has a desirable fit with the data. Performance expectancy was the core variable explaining the habitual use of wearable devices. The direct effect of the performance expectancy on habitual use of wearable devices was greater (β=.537, P<.001) than that of intention to continue use (β=.439, P<.001), and the total effect estimate of the performance expectancy was 0.909 (P<.001), including the indirect effect (β=.372, P=.03) on habitual use of wearable devices via intention to continue use. Furthermore, performance expectancy was influenced by health motivation (β=.497, P<.001), effort expectancy (β=.558, P<.001), and risk perception (β=.137, P=.02). Perceived vulnerability (β=.562, P<.001) and perceived severity (β=.243, P=.008) contributed to health motivation. Conclusions The results suggest the importance of the users’ performance expectations for wearable health devices for the intention of continued use for self-health management and habituation. Based on our results, developers and health care practitioners should find better ways to meet the performance expectations of middle-aged individuals with MetS risk factors. They also should generate device use easier and find a way to encourage users’ health motivation, thereby reducing users’ effort expectancy and resulting in a reasonable performance expectancy of the wearable health device, to induce users’ habitual use behaviors.

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Factors associated with Pneumococcal Vaccinations in Older Adults

Lee¹,

Lee²

2018

J Korean Gerontol Nurs

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Purpose:The purpose of this study was to confirm the current status of pneumococcal vaccination in adults over 65 years old and to identify factors related to pneumococcal vaccination. Methods: The research design was a descriptive survey design using convenience sampling. Data collection was conducted at senior citizen centers and schools for elders. A self-report questionnaire was completed by 131 older adults. Data collection period was from March 1 to 31, 2017. Data were analyzed using numbers, percentages, means, standard deviation, x 2 test, t-test, and logistic regression with the IBM SPSS Statistics 19.0 program. Results: Pneumococcal vaccination rate for older adults was 51.1%. Pneumococcal vaccination was associated with chronic disease (adjusted odds ratio [OR]=548.27, 95% CI: 26.67~999.99) and attitude toward pneumococcal vaccination (adjusted odds ratio [OR]=1.33 95% CI: 1.16~1.53). Conclusion: Pneumococcal vaccination rate for elders was about 50% and chronic disease positively affected the pneumococcal vaccination rate. To improve the pneumococcal vaccination rate for older adults, it is necessary to develop an intervention plan to define the role of nurses in vaccination for pneumococcal disease and to put the plan into action. An intervention program should be developed to promote a positive attitude toward pneumococcal vaccination in older people.

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Examination of Influential Factors of Tablet PC Use - Application of Theory of Planned Behavior and Technology Acceptance Model -

Cited by 5 publications

References 0 publications

An empirical analysis of tablet PC diffusion

An empirical analysis of tablet PC diffusion

Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

Factors associated with Pneumococcal Vaccinations in Older Adults

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