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Exploring critical factors influencing physicians’ acceptance of mobile electronic medical records based on the dual-factor model: a validation in Taiwan

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2015
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2 tweeters

Citations

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33 Dimensions

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97 Mendeley
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Title
Exploring critical factors influencing physicians’ acceptance of mobile electronic medical records based on the dual-factor model: a validation in Taiwan
Published in
BMC Medical Informatics and Decision Making, February 2015
DOI 10.1186/s12911-014-0125-3
Pubmed ID
Authors

Chung-Feng Liu, Tain-Junn Cheng

Abstract

With respect to information management, most of the previous studies on the acceptance of healthcare information technologies were analyzed from "positive" perspectives. However, such acceptance is always influenced by both positive and negative factors and it is necessary to validate both in order to get a complete understanding. This study aims to explore physicians' acceptance of mobile electronic medical records based on the dual-factor model, which is comprised of inhibitors and enablers, to explain an individual's technology usage. Following an earlier healthcare study in the USA, the researchers conducted a similar survey for an Eastern country (Taiwan) to validate whether perceived threat to professional autonomy acts as a critical inhibitor. In addition, perceived mobility, which is regarded as a critical feature of mobile services, was also evaluated as a common antecedent variable in the model. Physicians from three branch hospitals of a medical group were invited to participate and complete questionnaires. Partial least squares, a structural equation modeling technique, was used to evaluate the proposed model for explanatory power and hypotheses testing. 158 valid questionnaires were collected, yielding a response rate of 33.40%. As expected, the inhibitor of perceived threat has a significant impact on the physicians' perceptions of usefulness as well as their intention to use. The enablers of perceived ease of use and perceived usefulness were also significant. In addition, as expected, perceived mobility was confirmed to have a significant impact on perceived ease of use, perceived usefulness and perceived threat. It was confirmed that the dual-factor model is a comprehensive method for exploring the acceptance of healthcare information technologies, both in Western and Eastern countries. Furthermore, perceived mobility was proven to be an effective antecedent variable in the model. The researchers believe that the results of this study will contribute to the research on the acceptance of healthcare information technologies, particularly with regards to mobile electronic medical records, based on the dual-factor viewpoints of academia and practice.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 96 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 26%
Student > Ph. D. Student 11 11%
Researcher 10 10%
Student > Doctoral Student 9 9%
Student > Bachelor 9 9%
Other 20 21%
Unknown 13 13%
Readers by discipline Count As %
Business, Management and Accounting 20 21%
Computer Science 16 16%
Medicine and Dentistry 13 13%
Nursing and Health Professions 9 9%
Social Sciences 9 9%
Other 14 14%
Unknown 16 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 April 2015.
All research outputs
#2,669,137
of 5,026,176 outputs
Outputs from BMC Medical Informatics and Decision Making
#550
of 812 outputs
Outputs of similar age
#94,253
of 178,991 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#12
of 18 outputs
Altmetric has tracked 5,026,176 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 812 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 178,991 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.