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A cross-sectional survey assessing the acceptability and feasibility of self-report electronic data collection about health risks from patients attending an Aboriginal Community Controlled Health…

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2014
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Title
A cross-sectional survey assessing the acceptability and feasibility of self-report electronic data collection about health risks from patients attending an Aboriginal Community Controlled Health Service
Published in
BMC Medical Informatics and Decision Making, April 2014
DOI 10.1186/1472-6947-14-34
Pubmed ID
Authors

Natasha E Noble, Christine L Paul, Mariko L Carey, Robert W Sanson-Fisher, Stephen V Blunden, Jessica M Stewart, Katherine M Conigrave

Abstract

Aboriginal Australians experience significantly worse health and a higher burden of chronic disease than non-Aboriginal Australians. Electronic self-report data collection is a systematic means of collecting data about health risk factors which could help to overcome screening barriers and assist in the provision of preventive health care. Yet this approach has not been tested in an Aboriginal health care setting. Therefore, the aim of this study was to examine the acceptability and feasibility of a health risk questionnaire administered on a touch screen laptop computer for patients attending an Aboriginal Community Controlled Health Service (ACCHS).

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 16%
Researcher 8 14%
Student > Ph. D. Student 8 14%
Other 5 9%
Student > Bachelor 4 7%
Other 10 17%
Unknown 14 24%
Readers by discipline Count As %
Medicine and Dentistry 12 21%
Nursing and Health Professions 8 14%
Psychology 6 10%
Agricultural and Biological Sciences 3 5%
Social Sciences 3 5%
Other 6 10%
Unknown 20 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 April 2014.
All research outputs
#14,194,875
of 22,753,345 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,100
of 1,985 outputs
Outputs of similar age
#107,726
of 203,744 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#15
of 28 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 38th percentile – i.e., 38% 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 203,744 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.