Limitations are not properly acknowledged in the scientific literature is a research paper published in Journal of Clinical Epidemiology (2007). On theSindex it has a DataRank of 0.717. It has been cited 118 times.
Limitations are important to understand for placing research findings in context, interpreting the validity of the scientific work, and ascribing a credibility level to the conclusions of published research. This goes beyond listing the magnitude and direction of random and systematic errors and validity problems. Acknowledgment of limitations requires an interpretation of the meaning and influence of errors and validity problems on the published findings. An examination of the full-text files of the first 50 articles published in 2005 in the six most-cited research journals and in two recently launched leading open-access journals showed that only 67 articles (17%) used at least one word denoting limitations in the context of the presented scientific work. Only four articles (1%) used the word limitation in their abstract; none referred to limitations of the present work that materially affected conclusions. Only five articles had a separate section on limitations. Conversely, 243 articles (61%) used words detected by the roots error, valid, bias, reproducib, or false and 289 articles (72%) used words with the root importan. Among the 25 top-cited journals' instructions to the authors and editorial policies, only one encourages discussion of limitations; importance, novelty, and lack of error are typically encouraged. Limitations should be better covered and discussed in research articles. To facilitate this, journals should give better guidance and promote the discussion of limitations. Otherwise, we are facing an important loss of context for the scientific literature.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.717
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.