| Title |
Mobile Health Systems for Community-Based Primary Care: Identifying Controls and Mitigating Privacy Threats
|
|---|---|
| Published in |
JMIR mHealth and uHealth, March 2019
|
| DOI | 10.2196/11642 |
| Pubmed ID | |
| Authors |
Leonardo Horn Iwaya, Simone Fischer-Hübner, Rose-Mharie Åhlfeldt, Leonardo A Martucci |
X Demographics
The data shown below were collected from the profiles of 5 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 | 2 | 40% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 115 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 17% |
| Student > Ph. D. Student | 12 | 10% |
| Student > Bachelor | 12 | 10% |
| Student > Postgraduate | 9 | 8% |
| Researcher | 8 | 7% |
| Other | 19 | 17% |
| Unknown | 36 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 15% |
| Nursing and Health Professions | 14 | 12% |
| Medicine and Dentistry | 12 | 10% |
| Social Sciences | 6 | 5% |
| Business, Management and Accounting | 4 | 3% |
| Other | 23 | 20% |
| Unknown | 39 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 March 2019.
All research outputs
#13,287,847
of 23,136,540 outputs
Outputs from JMIR mHealth and uHealth
#1,581
of 2,362 outputs
Outputs of similar age
#171,025
of 351,736 outputs
Outputs of similar age from JMIR mHealth and uHealth
#81
of 122 outputs
Altmetric has tracked 23,136,540 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,362 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one is in the 31st percentile – i.e., 31% 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 351,736 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 122 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.