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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Development of mHealth system for supporting self-management and remote consultation of skincare
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2015
|
| DOI | 10.1186/s12911-015-0237-4 |
| Pubmed ID | |
| Authors |
Bambang Parmanto, Gede Pramana, Daihua X. Yu, Andrea D. Fairman, Brad E. Dicianno |
| Abstract |
Individuals with spina bifida (SB) are vulnerable to chronic skin complications such as wounds on the buttocks and lower extremities. Most of these complications can be prevented with adherence to self-care routines. We have developed a mobile health (mHealth) system for supporting self-care and management of skin problems called SkinCare as part of an mHealth suite called iMHere (interactive Mobile Health and Rehabilitation). The objective of this research is to develop an innovative mHealth system to support self-skincare tasks, skin condition monitoring, adherence to self-care regimens, skincare consultation, and secure two-way communications between patients and clinicians. In order to support self-skincare tasks, the SkinCare app requires three main functions: (1) self-care task schedule and reminders, (2) skin condition monitoring and communications that include imaging, information about the skin problem, and consultation with clinician, and (3) secure two-way messaging between the patient and clinician (wellness coordinator). The SkinCare system we have developed consists of the SkinCare app, a clinician portal, and a two-way communication protocol connecting the two. The SkinCare system is one component of a more comprehensive system to support a wellness program for individuals with SB. The SkinCare app has several features that include reminders to perform daily skin checks as well as the ability to report skin breakdown and injury, which uses a combination of skin images and descriptions. The SkinCare app provides reminders to visually inspect one's skin as a preventative measure, often termed a "skin check." The data is sent to the portal where clinicians can monitor patients' conditions. Using the two-way communication, clinicians can receive pictures of the skin conditions, track progress in healing over time, and provide instructions for how to best care for the wound. The system was capable of supporting self-care and adherence to regimen, monitoring adherence, and supporting clinician engagement with patients, as well as testing its feasibility in a long-term implementation. The study shows the feasibility of a long-term implementation of skincare mHealth systems to support self-care and two-way interactions between patients and clinicians. |
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 % |
|---|---|---|
| United States | 2 | 67% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 155 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 22 | 14% |
| Student > Ph. D. Student | 18 | 12% |
| Student > Master | 17 | 11% |
| Researcher | 16 | 10% |
| Student > Postgraduate | 8 | 5% |
| Other | 27 | 17% |
| Unknown | 48 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 26 | 17% |
| Nursing and Health Professions | 24 | 15% |
| Computer Science | 17 | 11% |
| Engineering | 7 | 4% |
| Psychology | 7 | 4% |
| Other | 21 | 13% |
| Unknown | 54 | 35% |
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 11 April 2018.
All research outputs
#12,746,370
of 22,836,570 outputs
Outputs from BMC Medical Informatics and Decision Making
#848
of 1,990 outputs
Outputs of similar age
#175,240
of 393,178 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#21
of 41 outputs
Altmetric has tracked 22,836,570 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,990 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 56% 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 393,178 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 55% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.