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What makes poorer studies less informative is a decreased ability to distinguish between the causative, face-value interpretation of outcomes and the alternative interpretation that the results are spurious because of intrusion of factors not adequately eliminated as possible influences.
Campbell, et al. (2011) suggest that 'inclusion of poorer studies is unlikely to have a very distorting impact on qualitative synthesis' [ 2]:[45], and suggest that the time spent on quality appraisal might perhaps be better spent.
Thus, the rational and transparent way to down-weight poorer studies is to consider the impact of this ambiguity as one evaluates alternative interpretations of the data, using the patterns of concordance or lack thereof with other studies as part of the evaluation of the likelihood that the study in question has misled us or informed us.
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The best score possible depended on study design, with lower scores indicating poorer study quality.
However, the methodological deficiencies of these studies translated to poorer study quality scores and much lower PAD prevalence ranges of 0.01 0.5%.
In order to avoid that poor studies receive false credibility, readers need to evaluate the quality of the methods.
We did not make a register of the very poor studies that attempted to infer population prevalence from patient samples, although there were examples of this.
Methodological quality of our sample was poor; studies met roughly half of the applied criteria (mean ± sd, 54.7±18.4%).
Good reporting cannot make up for poor study design; however, it can facilitate the identification of poor studies.
The pretentiously named medical literature is shot through with poor studies.
It is clear that in this relatively new study area the knowledge space is already occupied by poor studies and potentially unreliable data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com