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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Health figures: an open source JavaScript library for health data visualization
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, March 2016
|
| DOI | 10.1186/s12911-016-0275-6 |
| Pubmed ID | |
| Authors |
Andres Ledesma, Mohammed Al-Musawi, Hannu Nieminen |
| Abstract |
The way we look at data has a great impact on how we can understand it, particularly when the data is related to health and wellness. Due to the increased use of self-tracking devices and the ongoing shift towards preventive medicine, better understanding of our health data is an important part of improving the general welfare of the citizens. Electronic Health Records, self-tracking devices and mobile applications provide a rich variety of data but it often becomes difficult to understand. We implemented the hFigures library inspired on the hGraph visualization with additional improvements. The purpose of the library is to provide a visual representation of the evolution of health measurements in a complete and useful manner. We researched the usefulness and usability of the library by building an application for health data visualization in a health coaching program. We performed a user evaluation with Heuristic Evaluation, Controlled User Testing and Usability Questionnaires. In the Heuristics Evaluation the average response was 6.3 out of 7 points and the Cognitive Walkthrough done by usability experts indicated no design or mismatch errors. In the CSUQ usability test the system obtained an average score of 6.13 out of 7, and in the ASQ usability test the overall satisfaction score was 6.64 out of 7. We developed hFigures, an open source library for visualizing a complete, accurate and normalized graphical representation of health data. The idea is based on the concept of the hGraph but it provides additional key features, including a comparison of multiple health measurements over time. We conducted a usability evaluation of the library as a key component of an application for health and wellness monitoring. The results indicate that the data visualization library was helpful in assisting users in understanding health data and its evolution over time. |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 63% |
| Australia | 1 | 6% |
| France | 1 | 6% |
| Unknown | 4 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 75% |
| Practitioners (doctors, other healthcare professionals) | 2 | 13% |
| Scientists | 2 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Argentina | 1 | <1% |
| Canada | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 133 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 28 | 20% |
| Student > Ph. D. Student | 22 | 16% |
| Researcher | 18 | 13% |
| Student > Bachelor | 11 | 8% |
| Student > Doctoral Student | 6 | 4% |
| Other | 25 | 18% |
| Unknown | 27 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 42 | 31% |
| Medicine and Dentistry | 21 | 15% |
| Social Sciences | 9 | 7% |
| Nursing and Health Professions | 5 | 4% |
| Business, Management and Accounting | 5 | 4% |
| Other | 21 | 15% |
| Unknown | 34 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 21 February 2017.
All research outputs
#2,947,978
of 22,858,915 outputs
Outputs from BMC Medical Informatics and Decision Making
#240
of 1,992 outputs
Outputs of similar age
#49,673
of 300,114 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 27 outputs
Altmetric has tracked 22,858,915 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,992 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 87% of its peers.
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 300,114 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.