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A cross-sectional study assessing determinants of the attitude to the introduction of eHealth services among patients suffering from chronic conditions

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2015
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Title
A cross-sectional study assessing determinants of the attitude to the introduction of eHealth services among patients suffering from chronic conditions
Published in
BMC Medical Informatics and Decision Making, April 2015
DOI 10.1186/s12911-015-0157-3
Pubmed ID
Authors

Mariusz Duplaga

Abstract

Provision of care to patients with chronic diseases remains a great challenge for modern health care systems. eHealth is indicated as one of the strategies which could improve care delivery to this group of patients. The main objective of this study was to assess determinants of the acceptance of the Internet use for provision of chosen health care services remaining in the scope of current nationwide eHealth initiative in Poland. The survey was carried out among patients with diagnosed chronic conditions who were treated in three health care facilities in Krakow, Poland. Survey data was used to develop univariate and multivariate logistic regression models for six outcome variables originating from the items assessing the acceptance of specific types of eHealth applications. The variables used as predictors were related to the sociodemographic characteristics of respondents, burden related to chronic disease, and the use of the Internet and its perceived usefulness in making personal health-related decisions. Among 395 respondents, there were 60.3% of Internet users. Univariate logistic regression models developed for six types of eHealth solutions demonstrated their higher acceptance among younger respondents, living in urban areas, who have attained a higher level of education, used the Internet on their own, and were more confident about its usefulness in making health-related decisions. Furthermore, the duration of chronic disease and hospitalization due to chronic disease predicted the acceptance of some of eHealth applications. However, when combined in multivariate models, only the belief in the usefulness of the Internet (five of six models), level of education (four of six models), and previous hospitalization due to chronic disease (three of six models) maintained the effect on the independent variables. The perception of the usefulness of the Internet in making health-related decision is a key determinant of the acceptance of provision of health care services online among patients with chronic diseases. Among sociodemographic factors, only the level of education demonstrates a consistent impact on the level of acceptance. Interestingly, a greater burden of chronic disease related to previous hospitalizations leads to lower acceptance of eHealth solutions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 15%
Student > Bachelor 15 14%
Researcher 13 12%
Student > Ph. D. Student 11 10%
Student > Doctoral Student 4 4%
Other 19 17%
Unknown 31 28%
Readers by discipline Count As %
Nursing and Health Professions 15 14%
Medicine and Dentistry 14 13%
Psychology 10 9%
Social Sciences 7 6%
Business, Management and Accounting 6 5%
Other 18 16%
Unknown 40 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 April 2015.
All research outputs
#14,221,392
of 22,800,560 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,100
of 1,987 outputs
Outputs of similar age
#139,420
of 265,270 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#22
of 37 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,987 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 39th percentile – i.e., 39% 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 265,270 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 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.