ArticleFrontiers in public health2022
Predicting the Mass Adoption of eDoctor Apps During COVID-19 in China Using Hybrid SEM-Neural Network Analysis.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 29 citations in OpenAlex.
- Investigating Continuance Intention for Telehealth Visits in Children's Hospitals: Survey-Based Study.Journal of medical Internet research · 2025Article
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- Willingness to use smart fetal heart rate monitoring devices among pregnant women: an extension of the technology acceptance model.Frontiers in psychology · 2024Article
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- How health motivation moderates the effect of intention and usage of wearable medical devices? An empirical study in Malaysia.Frontiers in public health · 2022Article
- Predicting the intention to adopt wearable payment devices in China: The use of hybrid SEM-Neural network approach.PloS one · 2022Article
- Modeling the Intention and Adoption of Wearable Fitness Devices: A Study Using SEM-PLS Analysis.Frontiers in public health · 2022Article
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Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technology plays an increasingly important role in our daily lives. The use of technology-based healthcare apps facilitates and empowers users to use such apps and saves the burden on the public healthcare system during COVID-19. Through technology-based healthcare apps, patients can be virtually connected to doctors for medical services. This study explored users' intention and adoption of eDoctor apps in relation to their health behaviors and healthcare technology attributes among Chinese adults. Cross-sectional data were collected through social media, resulting in a total of 961 valid responses for analysis. The hybrid analysis technique of partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) analysis was applied. The obtained results revealed the significant influence of eDoctor apps in terms of usefulness, compatibility, accuracy, and privacy on users' intention to use eDoctor apps. Intention and product value were also found to suggestively promote the adoption of eDoctor apps. This study offered practical recommendations for the suppliers and developers of eHealth apps to make every attempt of informing and building awareness to nurture users' intention and usage of healthcare technology. Users' weak health consciousness and motivation are notable barriers that restrict their intention and adoption of the apps. Mass adoption of eDoctor apps can also be achieved through the integration of the right technology features that build the product value and adoption of eDoctor apps. The limitations of the current study and recommendations for future research are presented at the end of this paper.
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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.