Statistics on Medical Journal Articles Paper Example

Introduction

Statistical training across the field of medical education may not have advanced at the speed of statistical reporting in the medical literature; nevertheless, a complete indulgence of statistical concepts most frequently presented in the research currently is very important to the real practice of Evidence-Based Medicine. The aim of this analysis was to discuss various statistical methods used by a leading medical journal (JAMA) across a 20-year period, with a concentration on effects for medical education.

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Explanation of the Article

In 1990, 2000, and 2010, two issues of JAMA published each month were selected randomly out of these, 361 articles were reviewed. Statisticalcomponents, the primary focus and study design were examined by year of publication. The greatest frequently reported statistics over the 20 year period comprised of epidemiologic outcomes, mortality, morbidity and descriptive statistics. Never the less, between 1990 and 2010, there was a surge in reporting of more advanced ways for instance sensitivity analysis, multilevel modelling, and multivariable regression and survival analysis. In as much as this study was restricted by a focus on one specific journal, one of the advantages was that the journal in question is read widely by several clinical specialties. On the other hand, JAMA is considered a leading journal in the medical field thereby setting standards for published research.

Use of Statistical Information in the Article

In order to manage this analysis, random samples of journal issues recognized and articles published within these issues cross-checked for statistical content. The sample frame for the articles included all issues of JAMA published between 1990, 200, and 2010. In order to select two weekly issues of JAMA from each month, a random number generator was used. However, in cases where different theme edition was amongst the weekly issues randomly selected, other issues were ignored. All articles within those issues selected were then assessed for eligibility.

Due to the fact that medical education and standards for publication are constantly evolving, it is important to reexamine the issue of statistical reporting to see if finding from 1980 and 1990s are of importance today. In this manner, this study sheds some light to the literature as it backs the continuing use of more advanced statistical techniques and measures in the medical literature. Additionally, this study offers additional evidence to support revisiting of what the medical students are taught to acquaint them with ever-changing statistical methods.

To be precise, I observed that all studies published from 1990 to 2010 comprised of some form more complicated multivariable methods and statistical reporting. Additionally, there was a significant increase in the percentage of papers reporting multilevel modelling results, sensitivity analysis, survival analysis, and multivariable regression. In order to understand these higher level statistical methods, solid statistical understanding is required to interpret their application and the outcome presented.

These results offer information to be put into consideration as postgraduate training programs and medical schools revise and review statistical training components. In addition, for medical investigators and clinicians with interests in continuing their own education in statistics, there is a guide for the techniques that learners and faculty should put into consideration in order to critically and comprehensively use excellent literature as part of the practice of evidence-based medicine.

Since the of medical college admission test encourages students to gain foundational knowledge in statistics during their premedical education (Lambert et al, 2010) and since proposed changes to add a statistics course to the premedical requirement are debated undergraduate medical education will need to consider revisions to their pre-clinical and clinical curricula. Sequentially, this will affect graduate and postgraduate education. One of the limitations of this content analysis is the focus on one journal since it does not account for variation by specialty and it restricts generalization of findings. For instance, the ideal choice of data analysis and study design expectations may differ from those in psychiatry or pediatrics. Therefore, the developments in analytical techniques and study design presented here may differ from journals with more area of focus target audience.

One journal alone does not serve as a benchmark by which to judge medical education needs. Never the less, the journal chose for this study serves as a strength since the study concentrated on a leading medical journal with the exceedingly broad readership. The journal is read widely by clinicians in a variety of specialties and publishes across a range of clinically related issues. In this manner, understanding the statistical techniques and measures reported mostly by JAMA may serve as one source of evidence for generating discussions about guiding areas on which to focus the statistical characteristics of medical education.

In as much as others have presented on the use of statistics in specific disciplines, numerous studies are older in nature. According to Agrawal et al (1994), results from the New England Journal of Medicine suggests that almost 88% of the articles needed some statistical analysis beyond descriptive statistics. To evaluate the changes in the use of statistical methods in specialized journals and general medicine journals, I identified reviews of statistical methods used in journals. According to Goldin, Zhu, Sayre (1996), rheumatology journals tend to use simpler and fewer statistics than general medicine journals.Conclusions from this content analysis of JAMA articles over thirty years extends and supports trends in previous studies that point to the continued use of regression and multivariate modelling as complex statistical approaches in the medical literature. Although the findings do not directly suggest that medical education necessarily needs to be modified, the statistical reporting trends described may have consequences for medical education essentially needs to be modified.

Conclusion

At the moment, statistics is extensively recognized as a powerful tool in the scientific research process with a great increase in the use of statistical methods. However, several errors were in this article, for instance, incompatibility of statistical tests with the type of data and use of an inappropriate test for the hypothesis under investigation. In my opinion, this article is very accurate since it has proper use of statistical information and also offers extra evidence to back up a re-examination of medical students; residents are taught during the course of their training in order to acquaint them with developing statistical methods.

Works cited

DR, Lambert et al. Standardizing and Personalizing Science in Medical Education. Acad Med 85, 2010, pp. 356-362.

G, R. and SL, K. (2010). Physician numeracy as the basis for an evidence-based medicine Curriculum. 2nd ed. Acad Med 85, pp.1794-1799.

MH, Cardiel, and Goldsmith CH. Type of Statistical Techniques in Rheumatology and Internal Medicine Journals. 1996, pp. 197-201.

S, Agrawal et al. Use of Statistical Analysis in the New England Journal of Medicine. 3rd ed., John Wiley & Sons, 2009, pp. 41-49.