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Responses to hypothetical health scenarios overestimate healthcare utilization for common infectious syndromes: a cross-sectional survey, South Africa, 2012

Overview of attention for article published in BMC Infectious Diseases, July 2018
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Title
Responses to hypothetical health scenarios overestimate healthcare utilization for common infectious syndromes: a cross-sectional survey, South Africa, 2012
Published in
BMC Infectious Diseases, July 2018
DOI 10.1186/s12879-018-3252-0
Pubmed ID
Authors

Karen K. Wong, Adam L. Cohen, Neil A. Martinson, Shane A. Norris, Stefano Tempia, Claire von Mollendorf, Sibongile Walaza, Shabir A. Madhi, Meredith L. McMorrow, Cheryl Cohen

Abstract

Asking people how they would seek healthcare in a hypothetical situation can be an efficient way to estimate healthcare utilization, but it is unclear how intended healthcare use corresponds to actual healthcare use. We performed a cross-sectional survey between August and September 2012 among households in Soweto and Klerksdorp, South Africa, to compare healthcare seeking behaviors intended for hypothetical common infectious syndromes (pneumonia, influenza-like illness [ILI], chronic respiratory illness, meningitis in persons of any age, and diarrhea in a child < 5 years old) with the self-reported healthcare use among patients with those syndromes. For most syndromes, the proportion of respondents who intended to seek healthcare at any facility or provider (99-100%) in a hypothetical scenario exceeded the proportion that did seek care (78-100%). More people intended to seek care for a child < 5 years old with diarrhea (186/188 [99%]) than actually did seek care (32/41 [78%], P < 0.01). Although most people faced with hypothetical scenarios intended to seek care with licensed medical providers such as hospitals and clinics (97-100%), patients who were ill reported lower use of licensed medical providers (55-95%). People overestimated their intended healthcare utilization, especially with licensed medical providers, compared with reported healthcare utilization among patients with these illnesses. Studies that measure intended healthcare utilization should consider that actual use of healthcare facilities may be lower than intended use.

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The data shown below were collected from the profile of 1 X user 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 21%
Student > Master 4 14%
Student > Bachelor 2 7%
Student > Ph. D. Student 2 7%
Other 2 7%
Other 3 11%
Unknown 9 32%
Readers by discipline Count As %
Medicine and Dentistry 7 25%
Nursing and Health Professions 2 7%
Agricultural and Biological Sciences 2 7%
Biochemistry, Genetics and Molecular Biology 1 4%
Immunology and Microbiology 1 4%
Other 3 11%
Unknown 12 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 August 2018.
All research outputs
#20,529,173
of 23,098,660 outputs
Outputs from BMC Infectious Diseases
#6,542
of 7,751 outputs
Outputs of similar age
#288,659
of 330,303 outputs
Outputs of similar age from BMC Infectious Diseases
#127
of 165 outputs
Altmetric has tracked 23,098,660 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,751 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 1st percentile – i.e., 1% 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 330,303 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.