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Causality in Medicine and Its Relationship with the Role of Statistics

Received: 17 January 2017     Accepted: 4 February 2017     Published: 24 February 2017
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Abstract

The general goal of this work is the clarification of the use of concepts of causality in medicine and its relationship with the role of statistics. The value of an association is the evidence of causality. The Bradford Hill considerations on causality are the criteria commonly used to infer causality. Statistics help to know the role of chance in the working medical hypotheses but does not prevent other common mistakes made during clinical research, such as biases. Man has found a procedure that removes the most of all subjectivities and external factors: the scientific method, this does not mean that scientific studies are infallible. There are many factors influencing the cure or improvement of a disease that would be take in account: spontaneous resolution, regression to the mean, the Forer effect, placebo effect and other. The subjective observation of these phenomena is often insufficient when it comes to analyzing the effectiveness of therapies, medications, diets, homeopathy, cosmetics and natural therapies. It is very difficult to establish causality in health sciences but not impossible, the principles of this establishement can be resumed as Temporality, Strength, Consistency, Biology, Plausibility, Specificity, Analogy, Experiment and Coherence.

Published in Biomedical Statistics and Informatics (Volume 2, Issue 2)
DOI 10.11648/j.bsi.20170202.14
Page(s) 61-68
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Statistics, Causality, Medicine, Mathematics, Epidemiology

References
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  • APA Style

    Antonio Monleon-Getino, Jaume Canela-Soler. (2017). Causality in Medicine and Its Relationship with the Role of Statistics. Biomedical Statistics and Informatics, 2(2), 61-68. https://doi.org/10.11648/j.bsi.20170202.14

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    ACS Style

    Antonio Monleon-Getino; Jaume Canela-Soler. Causality in Medicine and Its Relationship with the Role of Statistics. Biomed. Stat. Inform. 2017, 2(2), 61-68. doi: 10.11648/j.bsi.20170202.14

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    AMA Style

    Antonio Monleon-Getino, Jaume Canela-Soler. Causality in Medicine and Its Relationship with the Role of Statistics. Biomed Stat Inform. 2017;2(2):61-68. doi: 10.11648/j.bsi.20170202.14

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  • @article{10.11648/j.bsi.20170202.14,
      author = {Antonio Monleon-Getino and Jaume Canela-Soler},
      title = {Causality in Medicine and Its Relationship with the Role of Statistics},
      journal = {Biomedical Statistics and Informatics},
      volume = {2},
      number = {2},
      pages = {61-68},
      doi = {10.11648/j.bsi.20170202.14},
      url = {https://doi.org/10.11648/j.bsi.20170202.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20170202.14},
      abstract = {The general goal of this work is the clarification of the use of concepts of causality in medicine and its relationship with the role of statistics. The value of an association is the evidence of causality. The Bradford Hill considerations on causality are the criteria commonly used to infer causality. Statistics help to know the role of chance in the working medical hypotheses but does not prevent other common mistakes made during clinical research, such as biases. Man has found a procedure that removes the most of all subjectivities and external factors: the scientific method, this does not mean that scientific studies are infallible. There are many factors influencing the cure or improvement of a disease that would be take in account: spontaneous resolution, regression to the mean, the Forer effect, placebo effect and other. The subjective observation of these phenomena is often insufficient when it comes to analyzing the effectiveness of therapies, medications, diets, homeopathy, cosmetics and natural therapies. It is very difficult to establish causality in health sciences but not impossible, the principles of this establishement can be resumed as Temporality, Strength, Consistency, Biology, Plausibility, Specificity, Analogy, Experiment and Coherence.},
     year = {2017}
    }
    

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    AB  - The general goal of this work is the clarification of the use of concepts of causality in medicine and its relationship with the role of statistics. The value of an association is the evidence of causality. The Bradford Hill considerations on causality are the criteria commonly used to infer causality. Statistics help to know the role of chance in the working medical hypotheses but does not prevent other common mistakes made during clinical research, such as biases. Man has found a procedure that removes the most of all subjectivities and external factors: the scientific method, this does not mean that scientific studies are infallible. There are many factors influencing the cure or improvement of a disease that would be take in account: spontaneous resolution, regression to the mean, the Forer effect, placebo effect and other. The subjective observation of these phenomena is often insufficient when it comes to analyzing the effectiveness of therapies, medications, diets, homeopathy, cosmetics and natural therapies. It is very difficult to establish causality in health sciences but not impossible, the principles of this establishement can be resumed as Temporality, Strength, Consistency, Biology, Plausibility, Specificity, Analogy, Experiment and Coherence.
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Author Information
  • Section of Statistics, Departament of Genetics, Microbiology and Statistics, Faculty of Biology, Univeristy of Barcelona, Barcelona, Spain

  • Department of Public Health, School of Medicine, Univeristy of Barcelona, Barcelona, Spain

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