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Assessing generalisability through the use of disease registers: findings from a diabetes cohort study

Overview of attention for article published in BMJ Open, August 2011
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3 X users
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1 peer review site

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Title
Assessing generalisability through the use of disease registers: findings from a diabetes cohort study
Published in
BMJ Open, August 2011
DOI 10.1136/bmjopen-2011-000078
Pubmed ID
Authors

Michael David, Robert Ware, Maria Donald, Rosa Alati

Abstract

Objectives Knowledge of a study population's similarity to the target population allows researchers to assess the generalisability of their results. Often generalisability is assessed through a comparison of baseline characteristics between individuals who did and did not respond to an invitation to participate in a study. In this prospective population-based cohort, we broadened this assessment by comparing participants with all individuals from a chronic disease register who satisfied the study eligibility criteria but for a number of reasons, such as the absence of consent to be approached for research purposes, did not participate. Methods Data are from the Living with Diabetes Study, a population-based cohort of individuals diagnosed with diabetes mellitus, which commenced in Queensland, Australia in 2008. Individuals were sampled from a federally-funded diabetes register. We compared the characteristics of 3951 study participants with 10 488 non-participants (individuals who were invited to participate but declined) and with 129 900 non-study individuals on the register who did not participate in the study. Results Study participants were more likely than non-study registrants to be male, aged 50-69, have type 2 diabetes non-insulin requiring, be recently registered and be non-indigenous Australians. Study participants were more likely than non-participants to be aged 50-69, have type 1 diabetes and be non-indigenous Australians. Conclusions The interpretation of a study's generalisability can alter depending on which non-participating group is compared with participants. When assessing generalisability, participants should be compared with the largest possible group of non-participating individuals. When sampling from a disease register, researchers should be wary of the influence of research consent procedures on the register's coverage.

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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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 18%
Student > Bachelor 3 18%
Student > Master 2 12%
Student > Doctoral Student 1 6%
Professor 1 6%
Other 4 24%
Unknown 3 18%
Readers by discipline Count As %
Medicine and Dentistry 5 29%
Nursing and Health Professions 3 18%
Biochemistry, Genetics and Molecular Biology 2 12%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Psychology 1 6%
Other 1 6%
Unknown 4 24%
Attention Score in Context

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 29 August 2011.
All research outputs
#13,122,371
of 22,651,245 outputs
Outputs from BMJ Open
#13,839
of 22,283 outputs
Outputs of similar age
#78,024
of 123,786 outputs
Outputs of similar age from BMJ Open
#26
of 51 outputs
Altmetric has tracked 22,651,245 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,283 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one is in the 36th percentile – i.e., 36% 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 123,786 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.