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Wenbin Liang, taking master of public health Curtin University of Technology
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Dear editor, Patients, who are with cardiovascular functional impairment, may have more difficulties to deal with their daily life. They may consider writing a reply letter or ring up someone who is not familiar as a burden/great ”personal sacrifices”, and they would be less willing to make such an effort to become participants. However to answer a phone and “say yes” would be much more easier for these people, and therefore more people, who were in poorer health, were recruited by the “opt-out” method in this study. [1] Given this explanation is correct, the “opt-out” strategy may not be better than the “opt-in” strategy to recruit patients with higher risk, if the risk does not associate with functional impairments which are” barriers” for active response. For example: to recruit women for breast cancer prevention research, “opt-out” method may not be able to obtain a sample with a bigger proportion of women who are at higher risk, than the “opt-in” method. Reference 1. Junghans Cornelia, Feder Gene, Hemingway Harry, Timmis Adam , Jones Melvyn, Recruiting patients to medical research: double blind randomised trial of “opt-in” versus “opt-out” strategies. BMJ, doi:10.1136/bmj.38583.625613.AE (published 12 September 2005) Competing interests: None declared |
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David S Millson, GP Principal & Visiting Professor of Medicines Management (Keele University) Leek Health Centre, Fountain Street, Leek ST13 6JB
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We recently published a method to determine if consenters to population surveys are representative of the target study population [1]. Recently introduced data protection legislation has changed research practice in the UK, although uncertainties about the interpretation of the legislation remain [2]. Methods such as searching general practice records to investigate whether non-responders are different to responders, are no longer acceptable as they use information about identifiable individuals without their consent.An alternative approach to estimating the effect of non-response is to reformulate the problem as the extent to which responders are representative of the total target population. Since anonymised data may be obtained and used for the target population as a whole, this represents an indirect way of assessing the impact of non- response on representativeness. We compared consultation rates for some common conditions among responders to a headache survey [3] who had consented to the use of their practice records for research with anonymised rates derived from the practice populations from which they were sampled. We found that the adjusted consultation rates were similar but generally higher in the consenters group compared with the population group. This suggests that consenters have more morbidity than those who do not participate, not only with respect to the topic of the survey (headache) but for other conditions also. However, the differences were not large and suggest that non-response bias is unlikely to be substantial with respect to the extent and pattern of ill health. The alternative method which we described offers one potential approach to determine whether respondents to a study are representative of the population from which they were sampled with respect to a particular set of characteristics, namely their morbidity as measured by consultation with a general practitioner, and as such can be used as one measure of the representativeness of the responding sample. 1.Strobl J, Cave E, Walley T. Data protection legislation: interpretation and barriers to research. BMJ 2000;321:890-892. 2.Helen F. Boardman, Elaine Thomas, Helen Ogden, Peter R. Croft, and David S. Millson A method to determine if consenters to population surveys are representative of the target study population J. Public Health Med., Jun 2005; 27: 212 - 214. 3.Boardman HF, Thomas E, Croft PR, Millson DS. Epidemiology of headache in an English district. Cephalalgia 2003;23:129-137. Competing interests: None declared |
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BM Hegde, Retired Vice Chancellor Mangalore 575004, India
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Dear Editor, I am talking of statistics. What are we comparing in a controlled study? It is only a few phenotypic features. Those phentotypic features, by themselves, can not predict the future time evolution. The latter depends on the knowledge of the total initial state of the organism (patient or control)for any controlled study. Randomisation does not help either. That being the case what good are the controlled studies, in the first place? Be that as it may, the new "avatar" of clinical drug trial research in the third world countries involves a new breed of CROs (clinical research organisations) that work like the middlemen in any business! Less said about their authenticity the better. Where are we headed in medical research? Yours ever, bmhegde Competing interests: None declared |
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