Understanding Research Articles

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Understanding Research Articles

• What the Heck
• are they
• Taking About?

Seminar I B. J. French, PhD, RN
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Reading References
Authors

• Hatch EE, Palmer JR, Titus-Ernstoff L, Noller KL,
  Kaufman RH, et al. Cancer risk in women exposed
  to diethylstilbestrol in utero. JAMA
  1998280(7)630-4.

Name of Article
Year Published
Journal (abbreviation)
Pages in journal
Volume (Issue )
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Lay Out of Articles

• Scientific articles in journals tend to be
  divided into sections
• Abstract
• Introduction (Background, Lit Review)
• Methods
• Results/Findings
• Discussion/Conclusion
• References

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Abstract

• At the very beginning of the article
• It is a brief review of the entire article
• Ask yourself these questions as you read it
• What was studied?
• Who participated in the study?
• How and where was the research done?
• What did the researchers find?

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Introduction

• Sometimes this is called "Background" or
  "Literature Review"
• Normally, the authors will describe what they're
  about to study and why it's important
• They also give lots of information on what is
  already known on the topic

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Methods

• This section is designed to explain
• who participated in the research
• how they were chosen
• the design of the research
• What kind of research was done?
• How was it done?
• Did it involve review of medical records?
• Does it measuring the effectiveness of a new drug
  or intervention?
• how the results were examined, analyzed
  statistically

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Methods Ask Yourself

• Who were the people who were studied?
• Where they live, age, ethnicity, etc.
• Did the authors pick participants in such a way
  that findings should matter to anyone else?
• (a) Randomness.
• Was the participants' selection pretty much by
  chance or are they just convenient
• (b) Inclusiveness.
• "All patients between 1997 to 2006"
• Are there phrases that imply the researcher tried
  to include a broad group of subjects.
• This isn't the same as randomness, but it does
  help with applicability

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Results

• This section tells you specifically what the
  authors found
• You're likely to find tables and graphs
• Key words to look for are "statistically
  significant," "significant," or "not significant"
  
• These words tell you whether the authors'
  findings may just be the result of chance, or
  whether they're likely to really mean something

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Results - Example

• If a new headache drug is being tested, and the
  author tells you that those who took the drug had
  "significantly less pain than those who did not
  take it"
• that means there's fairly strong evidence that
  the drug really works
• Sometimes "not significant" is important too
• If you read an article that studied whether
  living near electrical lines increases your risks
  of developing cancer, and the authors' results
  tell you that there was "no significant
  difference between people who lived near the
  lines and those who did not," that's good news!

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Discussion

• This section should interpret what the research
  findings mean and how they're relevant
• The authors should also describe the limitations
  of their research
• They should discuss what you can and can't
  conclude, what the research failed to find, and
  things that may affect how relevant the findings
  are to other people

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Mean

• Mean is just a fancy word for average
• It's the sum of all the values or scores, divided
  by the number, of people in the study or group

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Median

• The median is nothing more than the score or
  value that falls closest to the middle
• Half of the individual scores are higher than the
  median while the other half are lower

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Mean and Median

• If you have five numbers 0, 0, 5, 10, 30, the
  mean or average would be 9 (005103045
  45/59)
• The median, however, would be 5, for there are
  two scores above and two scores below

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Standard Deviation

• It tells you how spread out the data or
  information is
• For example, imagine that you're going to have a
  relatively new spinal surgery. You've been told
  that only five people have had this surgery at
  your hospital, and that their mean (average)
  length of stay was 24 days.
• Suppose the hospital stays for those five people
  were 22, 22, 24, 25 and 26 days.
• The mean length of stay is 24 days
• Suppose instead their hospital stays looked like
  this 6 days, 8 days, 10, days, 31 days, and 65
  days
• The mean is again 24 days.
• It is this spread between scores or values that
  the standard deviation describes

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Statistically Significant?

• Because health problems occur for a variety of
  reasons, including chance, researchers must
  determine if a health effect they are studying
  may have occurred in study participants as a
  result of chance alone

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Statistically Significant

• Specifically, "statistical significance" refers
  to a finding in a research study that is larger
  or smaller than would be expected by chance alone

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Stastically Significant

• Did people get cancer in a specific area of the
  country more than would be generally expected?
• Did people who took a certain drug have more
  heart problems than would be expected in the
  general population?

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Statistical Significance

• Researchers test their findings - those means and
  averages we talked about - for statistical
  significance
• They try to control for other factors outside of
  the ones they're studying

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Statistical Significance

• When researchers test for statistical
  significance, they compare different sets of
  values
• - such as bladder infections before and bladder
  infections after using a medication
• while taking into account
• how many people participated in the research
• how dramatic their findings seem to be
• what some of the characteristics were of the
  people they compared
• If the researcher finds that the probability
  value is low (usually less than 5, 1 or even
  1/10th of 1), they can conclude that the drug
  really does work

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Probability

• These probability values - called p values -
  represent percentages, but are typically
  represented as plt.05, plt.01, or plt.001, or more
  specifically, as p.023, p.0067
• For example, plt.01 means that there is a less
  than 1 chance that our bladder medication seemed
  to work because of chance alone
• If probabilities are low, researchers describe
  them as statistically significant

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Probability

• Remember the lower the p value, the smaller the
  percentage, the greater the significance and the
  less likely that something happened just because
  of chance

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What is Significant Enough?

• It depends on what's being studied, the potential
  benefit or harm of the findings, and the author's
  own standards
• Generally in medical and nursing literature you
  are looking for a significance level of plt.05
• or a less than 1 in 20 chance that it works,
  makes a difference, etc.

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Proof

• Researchers - especially in health related
  research - should not be telling you that they
  proved that one thing causes or leads to another
• Instead, the message should be that one thing is
  related to another

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Validity

• Did the instruments used measure what they were
  intending to measure?

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Peer Reviewed Journal

• Scientific journals require research articles to
  go through a process called "peer review"
• During peer review, scientific experts who were
  not connected to the study review the article and
  decide whether it was done properly and whether
  the findings have merit

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Credibility

• Health care providers trust and use research
  published in credible, peer-reviewed scientific
  journals
• Experts have reviewed studies published in these
  journals to make sure they are of high quality
• Some examples of credible, peer-reviewed journals
  are JAMA, the Journal of the National Cancer
  Institute, the New England Journal of Medicine,
  and Science

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Credibility

• What are authors credentials?
• Does article list where they work or did
  research?
• An email is often listed, so if you have a
  question you can contact author (or
  representative)

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Sources of Information

• http//www.craighospital.org/SCI/METS/articles.asp
  
• Hinton, P. R. (1998) Statistics Explained,
  Routledge Press, NY.