Modeling Patients' Acceptance of Provider-delivered E-health
2004
- 11Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
Objective: Health care providers are beginning to deliver a range of Internet-based services to patients; however, it is not clear which of these e-health services patients need or desire. The authors propose that patients' acceptance of provider-delivered e-health can be modeled in advance of application development by measuring the effects of several key antecedents to e-health use and applying models of acceptance developed in the information technology (IT) field. Design: This study tested three theoretical models of IT acceptance among patients who had recently registered for access to provider-delivered e-health. Measurements: An online questionnaire administered items measuring perceptual constructs from the IT acceptance models (intrinsic motivation, perceived ease of use, perceived usefulness/extrinsic motivation, and behavioral intention to use e-health) and five hypothesized antecedents (satisfaction with medical care, health care knowledge, Internet dependence, information-seeking preference, and health care need). Responses were collected and stored in a central database. Results: All tested IT acceptance models performed well in predicting patients' behavioral intention to use e-health. Antecedent factors of satisfaction with provider, information-seeking preference, and Internet dependence uniquely predicted constructs in the models. Conclusion: Information technology acceptance models provide a means to understand which aspects of e-health are valued by patients and how this may affect future use. In addition, antecedents to the models can be used to predict e-health acceptance in advance of system development.
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