Assessing generalisability through the use of disease registers: findings from a diabetes cohort study.
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.
School of Population Health, The University of Queensland, Herston, Queensland, Australia.
Michael
M
David
Robert
R
Ware
Maria
M
Donald
Rosa
R
Alati