| Title |
Patients’ attitudes to the use of modern technologies in the treatment of diabetes
|
|---|---|
| Published in |
Patient preference and adherence, September 2016
|
| DOI | 10.2147/ppa.s118040 |
| Pubmed ID | |
| Authors |
Lucie Cerna, Petra Maresova |
| Abstract |
The incidence of diabetes is rising across the world. This global problem significantly affects the economic and social development in the 21st century. If the disease is diagnosed in time, the number of complications as well as the costs of therapy will be lower. Modern technologies permeate all spheres of medicine, and diabetes treatment is no exception. Therefore, the aim of this article is to analyze patients' attitudes to the use of modern technologies in the treatment of diabetes (type 1 diabetes mellitus [T1DM] and type 2 diabetes mellitus [T2DM]). A total of 313 respondents from the Czech Republic in the period from June 24, 2015, to July 24, 2015, participated in a questionnaire survey. The target group was diabetics regardless of the type of illness. Collected data were analyzed using descriptive statistical methods, Z-test, and test of independence (Pearson's chi-squared test). Although in other areas mobile applications are used to monitor patients' health condition in ~30% of cases, in the case of diabetes they are used by only 4% of respondents. Approximately 8% of participants use an application, but they do not like it. The rest of the respondents have never used any mobile application. These low figures are due to a lack of knowledge about the availability and possibilities of mobile applications. A positive correlation was proven between technical skills and methods of entering data. Gender and age show only a weak dependency of the method of writing data on their own health condition. Furthermore, the monitored parameters show that patients with T1DM control and know more about their health condition than patients with T2DM, which is reflected, for example, by more frequent blood glucose measurements or larger track of their physical activity. Conversely, the relationship between the associated complications and self-care activities has not been demonstrated. Despite the current fast development of modern technologies, these technologies are not frequently used in treating patients. The principal problem lies in patients' low technological knowledge and their higher age, which makes learning new skills, including the use of modern technologies, more difficult. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 75 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 23% |
| Student > Ph. D. Student | 11 | 15% |
| Student > Bachelor | 10 | 13% |
| Researcher | 5 | 7% |
| Student > Doctoral Student | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 18 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 17 | 23% |
| Medicine and Dentistry | 15 | 20% |
| Computer Science | 9 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Economics, Econometrics and Finance | 3 | 4% |
| Other | 8 | 11% |
| Unknown | 20 | 27% |
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 08 October 2016.
All research outputs
#16,183,746
of 25,576,275 outputs
Outputs from Patient preference and adherence
#918
of 1,769 outputs
Outputs of similar age
#208,362
of 348,941 outputs
Outputs of similar age from Patient preference and adherence
#46
of 75 outputs
Altmetric has tracked 25,576,275 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,769 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one is in the 44th percentile – i.e., 44% 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 348,941 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 75 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.