ArticleInternational journal of environmental research and public health2022
The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 48 citations in OpenAlex.
- Adoption of Internet of Things in Health Care: Weighted and Meta-Analytical Review of Theoretical Frameworks and Predictors.Journal of medical Internet research · 2026Pooled it
- Determinants of Health Care Technology Adoption Using an Integrated Unified Theory of Acceptance and Use of Technology and Task Technology Fit Model: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Smart Home Advancements for Health Care and Beyond: Systematic Review of Two Decades of User-Centric Innovation.Journal of medical Internet research · 2025Pooled it
- Older Adults' Continued Use of Smart Healthcare Applications: An Integrated HBM-UTAUT Model with Technology Anxiety.Healthcare (Basel, Switzerland) · 2026Article
- The impact of DeepSeek's perceived interactivity on medical students' self-directed learning ability.Scientific reports · 2026Article
- Article
- Seniors' attitudes and intention toward IoT enabled healthcare devices in emerging economies.Scientific reports · 2025Article
- Exploring behavioral factors and emotional mechanisms underlying older adult users' adoption of smart health services: evidence from PLS-SEM and fsQCA.Frontiers in public health · 2025Article
- From Acceptance to Dependence: Exploring Influences of Smart Healthcare on Continuous Use Intention of Mobile Health Services Among Older Adults with Chronic Illnesses in China.Behavioral sciences (Basel, Switzerland) · 2024Article
- Exploring Technology Acceptance of Healthcare Devices: The Moderating Role of Device Type and Generation.Sensors (Basel, Switzerland) · 2024Article
- Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians' and Specialists' Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study.JMIR formative research · 2024Article
- Informing existing technology acceptance models: a qualitative study with older persons and caregivers.European journal of ageing · 2024Article
- From theory to practice: An integrated TTF-UTAUT study on electric vehicle adoption behavior.PloS one · 2024Article
- Social Media in Pregnancy Care: Exploring Adoption Factors and Digital Healthcare Information Utilization among Expectant Mothers in Ghana.Ethiopian journal of health sciences · 2024Article
- Understanding the factors of wearable devices among the patients with thyroid cancer: A modified UTAUT2 model.PloS one · 2024Article
- Article
- Evaluation of Smart Sensors for Subway Electric Motor Escalators through AHP-Gaussian Method.Sensors (Basel, Switzerland) · 2023Article
- Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model.Behavioral sciences (Basel, Switzerland) · 2023Article
- Home Health Care Problem with Synchronization Visits and Considering Samples Transferring Time: A Case Study in Tehran, Iran.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
With the COVID-19 pandemic, the importance of home health care to manage and monitor one's health status in a home environment became more crucial than ever. This change raised the need for smart home health care services (SHHSs) and their extension to everyday life. However, the factors influencing the acceptance behavior of SHHSs have been inadequately investigated and failed to address why users have the intention to use and adopt the services. This study aimed to analyze the influential factors and measure the behavioral acceptance of SHHSs in South Korea. This study adopted the integrated model of the unified theory of acceptance and use of technology (UTAUT) and task-technology fit (TTF) to understand the behavioral acceptance of SHHSs from users' perceptions and task-technology fit. Multiple-item scales were established based on validated previous measurement scales and adjusted in accordance with SHHS context. Data from 487 valid samples were analyzed statistically, applying partial least square structural equation modeling. The results indicated that the integrated acceptance model explained 55.2% of the variance in behavioral intention, 44.9% of adoption, and 62.5% of the continuous intention to use SHHSs, supporting 11 of the 13 proposed hypotheses. Behavioral intention was positively influenced by users' perceptions on performance expectancy, effort expectancy, social influence, and functional conditions. Task-technology fit significantly influenced performance expectancy and behavioral intention, validating the linkage between the two models. Meanwhile, task characteristics were insignificant to determine task-technology fit, which might stem from complex home health care needs due to the COVID-19 pandemic, but were not sufficiently resolved by current service technologies. The findings implied that the acceptance of SHHSs needs to be evaluated according to both the user perceptions of technologies and the matching fit of task and technology. Theoretically, this study supports the applicability of the integrated model of UTAUT and TTF to the domain of SHHS, and newly proposed the measurement items of TTF reflecting the domain specificity of SHHS, providing empirical evidence during the pandemic era in South Korea. Practically, the results could suggest to the planners and strategists of home health care services how to promote SHHS in one's health management.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.