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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Personal health technology: A new era in cardiovascular disease prevention
|
|---|---|
| Published in |
Postgraduate Medicine, February 2015
|
| DOI | 10.1080/00325481.2015.1015396 |
| Pubmed ID | |
| Authors |
Nina C. Franklin, Carl J. Lavie, Ross A. Arena |
| Abstract |
Abstract Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide yet the majority of related risk factors are largely preventable (primary prevention [PP]) and effectively treatable (secondary prevention [SP]) with healthy lifestyle behaviors. The use of information and communication technology (ICT) offers a unique approach to personal health and CVD prevention, as these mediums are relatively affordable, approachable, and accessible. The purpose of this review is to provide an overview of ICT-driven personal health technologies and their potential role in promoting and supporting self-care behaviors for PP and SP of CVD. In this review, we focus on technological interventions that have been successful at supporting positive behavior change in order to determine which tools, resources, and methods are most appropriate for delivering interventions geared towards CVD prevention. We conducted a literature search from a range of sources including scholarly, peer-reviewed journal articles indexed in PubMed and CINAHL, gray literature, and reputable websites and other Internet-based media. A synthesis of existing literature indicates that the overall efficacy of ICT-driven personal health technologies is largely determined by: 1) the educational resources provided and the extent to which the relayed information is customized or individually tailored; and 2) the degree of self-monitoring and levels of personalized feedback or other interactions (e.g. interpersonal communications). We conclude that virtually all the technological tools and resources identified (e.g. Internet-based communications including websites, weblogs and wikis, mobile devices and applications, social media, and wearable monitors) can be strategically leveraged to enhance self-care behaviors for CVD risk reduction and SP but further research is needed to evaluate their efficacy, cost-effectiveness, and long-term maintainability. |
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 % |
|---|---|---|
| India | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 229 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| New Zealand | 1 | <1% |
| Netherlands | 1 | <1% |
| United States | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 225 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 48 | 21% |
| Student > Ph. D. Student | 34 | 15% |
| Researcher | 30 | 13% |
| Student > Bachelor | 19 | 8% |
| Other | 9 | 4% |
| Other | 34 | 15% |
| Unknown | 55 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 45 | 20% |
| Nursing and Health Professions | 42 | 18% |
| Social Sciences | 17 | 7% |
| Computer Science | 16 | 7% |
| Psychology | 12 | 5% |
| Other | 32 | 14% |
| Unknown | 65 | 28% |
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 November 2015.
All research outputs
#14,304,167
of 24,416,081 outputs
Outputs from Postgraduate Medicine
#804
of 1,367 outputs
Outputs of similar age
#124,010
of 259,239 outputs
Outputs of similar age from Postgraduate Medicine
#185
of 285 outputs
Altmetric has tracked 24,416,081 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,367 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 40th percentile – i.e., 40% 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 259,239 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 51% of its contemporaries.
We're also able to compare this research output to 285 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.