We have just completed two large systematic reviews looking at the difference between consenters and non-consenters. The review considered clinical trials and observational studies with primary data collection and secondary use of existing databases. For the clinical trials there were already many systematic reviews done, so this was a systematic review of systematic reviews.
The main question was whether the participants who agree to be part of a research study differ in any systematic way than those who refuse to participate. There was compelling evidence that requiring explicit consent for participation in different forms of health research can negatively impact the process and outcomes of the research itself: a) recruitment rates decline significantly when individuals are asked to consent (opt-in vs. opt-out consent, or explicit consent vs. implied consent), (b) in the context of explicit consent, those who consent tend to be different from those who decline consent on a number of variables (age, sex, race/ethnicity, marital status, rural versus urban locations, education level, socio-economic status and employment, physical and mental functioning, language, religiosity, lifestyle factors, level of social support, and health/disease factors such as diagnosis, disease stage/severity, and mortality) hence potentially introducing bias in the results, (c) consent requirements increase the cost of conducting the research and often these additional costs are not covered, and (d) the research projects take longer to complete (because of the additional time and effort needed to obtain consent, as well as taking longer to reach recruitment targets due to the impact on recruitment rates).
The review itself is here: http://jamia.bmj.com/content/suppl/2009/11/20/16.5.670.DC1/El_Emam_M3144R1_data_supplement_Appendix_A.pdf
This was an appendix to the following article, which provides the citation as well: http://jamia.bmj.com/content/16/5/670.short
In practice this means that ethics boards need to consider bias as another factor in deciding whether it is appropriate to waive consent. Even if it is possible to obtain consent, would the impact on study quality be sufficient to allow a consent waiver? For example, if we are looking at a syndromic surveillance study of H1N1 influenza, a bias against say, pregnant women would be devastating because they are an important group of patients who are affected.
In the context of secondary use or database studies, one option that should then be considered is to de-identify the data if consent is waived. There is no regulatory requirement to obtain consent for de-identified data and many research ethics boards will not require consent if the data is appropriately de-identified.
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