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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2012
|
| DOI | 10.1186/1472-6947-12-144 |
| Pubmed ID | |
| Authors |
Anne M Walsh, Melissa K Hyde, Kyra Hamilton, Katherine M White |
| Abstract |
The quantum increases in home Internet access and available online health information with limited control over information quality highlight the necessity of exploring decision making processes in accessing and using online information, specifically in relation to children who do not make their health decisions. The aim of this study was to understand the processes explaining parents' decisions to use online health information for child health care. |
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 Kingdom | 1 | 20% |
| Canada | 1 | 20% |
| India | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 1 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Netherlands | 1 | <1% |
| Switzerland | 1 | <1% |
| Spain | 1 | <1% |
| United Kingdom | 1 | <1% |
| Unknown | 122 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 26 | 20% |
| Student > Ph. D. Student | 20 | 16% |
| Researcher | 15 | 12% |
| Student > Bachelor | 13 | 10% |
| Student > Postgraduate | 9 | 7% |
| Other | 24 | 19% |
| Unknown | 21 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 29 | 23% |
| Nursing and Health Professions | 21 | 16% |
| Social Sciences | 17 | 13% |
| Psychology | 14 | 11% |
| Computer Science | 7 | 5% |
| Other | 16 | 13% |
| Unknown | 24 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 14 December 2012.
All research outputs
#6,252,135
of 22,689,790 outputs
Outputs from BMC Medical Informatics and Decision Making
#584
of 1,980 outputs
Outputs of similar age
#65,907
of 278,728 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#22
of 47 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,980 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 69% 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 278,728 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 76% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.