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Making Sense of Pain Research

Making sense of research for pain practice can be difficult, so articles in this section provide answers for practitioners and patients. Medical research can be a messy endeavor in which nothing is actually proved and no absolute, irrevocable truths are discovered. Healthcare professionals, and most certainly patients, usually have had little if any specific training in evaluating research. This series of UPDATES articles exclusively from Pain-Topics helps to close the education gap, teaching readers how to understand and interpret the often mysterious and complex language of research to assess its validity. Meanwhile, the most prudent approach is for consumers of pain research to develop a healthy skepticism about everything they read in the journals, or hear at conferences, or see on the nightly news.

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Entire Series: Making Sense of Pain Research [MS Word Doc File]

This Microsoft® Word® document file* contains all UPDATES articles in this series to date for easy viewing and printing. Plus, all links in the document are active for easy access to additional resources. The document will be updated as more articles are added to this series, so check back occasionally for the latest edition. Contents are copyrighted © by Pain Treatment Topics / Stewart B. Leavitt, MA, PhD. However, this document may be copied and freely distributed for educational purposes. Any commercial use, including distribution for sale in printed or electronic format — eg, via CD, blog, website — requires prior notification and permission.   Also see PTCalcs below for an easy-to-use statistical calculator [Click Here].

Download Doc file here: http://pain-topics.org/docs/UnderstandingPainResearch.doc

*If you do not have MS Word installed on your computer you can still view, print, and copy this document with Microsoft’s free Word Viewer. Any version of Windows is required. Download Viewer Here>

Individual Articles...

Part 1: How to Make Practical Sense of Pain Research

Getting Started; Stewart B. Leavitt, MA, PhD; March 18, 2011.

Understanding research reports and articles, and translating their results into better patient care, has never been more difficult. Starting here, this series of UPDATES articles teaches readers the secrets of distinguishing good research from bad and how to decode the sometimes mystifying language of researchers and their statisticians.
 

Go to article: http://updates.pain-topics.org/2011/03/how-to-make-practical-sense-of-pain.html

Part 2: Pain Research – All That Glitters is Not Gold

A Hierarchy of Evidence; Stewart B. Leavitt, MA, PhD; March 25, 2011.

Just because a pain research study is published does not mean it is accurate, unbiased, valid, or useful for any clinical or decision making purpose. The truth is that much pain-related research literature is simply not worth reading, and sifting out the golden nuggets of worthwhile research from fool’s gold can be a challenging task. This article tells how.
 

Go to article: http://updates.pain-topics.org/2011/03/pain-research-all-that-glitters-is-not.html

Part 3: Validity, Reliability, & Bias in Pain Research

When Bad Things Happen to Good Research; Stewart B. Leavitt, MA, PhD; April 1, 2011.

Many wrong, or at least unreliable and invalid, therapeutic answers are being generated due to biased studies that are poorly designed and use inappropriate analyses. The pain field is no exception, and understanding potential sources of bias in pain research is vital for assessing reliability and validity of the outcomes.
 

Go to article: http://updates.pain-topics.org/2011/04/validity-reliability-bias-in-pain.html

Part 4: Pain Research – Insignificance of “Significance”

The Problem with P-Values; Stewart B. Leavitt, MA, PhD; April 15, 2011.

There is a common misperception that “statistical significance” as denoted by low P-values signifies the strength and importance of research results, and is the hallmark of a “good” study. However, this is far from the truth and, in fact, many allegedly worthwhile research studies with statistically significant findings actually depict small differences or effects that are trivial or have little relevance for pain practice.
 

Go to article: http://updates.pain-topics.org/2011/04/pain-research-insignificance-of.html

Part 5: Pain Research – Confidence in "Confidence Intervals"

Helping to Determine Clinical Significance; Stewart B. Leavitt, MA, PhD; May 1, 2011.

Whether or not outcomes of pain research studies are found to be statistically significant tells only small part of the story. What healthcare providers and their patients really need to know is whether the outcomes have importance for improving pain practice. And, for determining such clinical significance, understanding a statistical concept called the “Confidence Interval” can be critically helpful.
 

Go to article: http://updates.pain-topics.org/2011/05/pain-research-confidence-in-confidence.html

Part 6: Risks of Misinterpreting “Risk” in Pain Research

Understanding RR, RRR, ARR, & NNT; Stewart B. Leavitt, MA, PhD; May 20,2011.

An understanding of outcomes presented in pain research studies as “risk statistics,” which are special estimates of effect, is central to evidence-based medicine approaches. Yet, this can be confusing, since authors often do not portray or discuss study results involving these measures in everyday terms that can be applied in pain practice. Therefore, being able to interpret risk effects — denoted as RR, RRR, ARR, or NNT — is vital for making sense of pain research.
 

Go to article: http://updates.pain-topics.org/2011/05/risks-of-misinterpreting-risk-in-pain.html

Part 7: At Odds with “Odds Ratios” in Pain Research

Beware of Odds Posing as Risks; Stewart B. Leavitt, MA, PhD; June 7,2011,

While the presentation of data as odds and Odds Ratios is favored by gamblers and some statisticians, many authorities on evidence-based medicine disparage their use in pain research reports as being unhelpful and potentially misleading for clinical decision-making purposes. This article discusses how odds and Odds Ratios relate to risks and Risk Ratios and the misunderstandings that can occur.
 
Go to article: http://updates.pain-topics.org/2011/06/at-odds-with-odds-ratios-in-pain.html

Part 8: The ‘Big Esses’ of Pain Research: SD, SEM, SMD

Precision, Accuracy, & Significance of Mean Values; Stewart B. Leavitt, MA, PhD; July 22, 2011

Research outcomes are commonly reported as average, or mean, values; however, averages can be misleading, so it is important that they are examined from perspectives of their precision and accuracy. And, better understandings of statistical measures such as the Standard Deviation (SD), Standard Error of the Mean (SEM), and Standardized Mean Difference (SMD) are essential for assessing the validity and clinical significance of pain research data.
 

Go to article: http://updates.pain-topics.org/2011/07/big-esses-of-pain-research-sd-sem-smd.html

Part 9: Promises & Perils of Power in Pain Research

Why Size Really Does Matter; Stewart B. Leavitt, MA, PhD; August 10, 2011

A common failing of clinical research studies in the pain management field is having too few subjects enrolled and/or insufficient effect sizes to yield significant and valid results. An antidote to this is called “power analysis,” performed during study design. An understanding of statistical power, and its limitations, can help consumers of research appreciate why small-scale studies are often of little value for clinical decision-making purposes.
 

Go to article: http://updates.pain-topics.org/2011/08/promises-perils-of-power-in-pain.html

Part 10: Pain Research – Differences That Make a Difference

Interpreting Effect Sizes in Research Data; Stewart B. Leavitt, MA, PhD; December 17, 2011, updated Feb. 2012

One of the greatest and most frequent problems in pain research studies is authors presenting outcome results, and the statistical significance of these, but not assessing the clinical significance of the findings. This is especially vexing when pain therapies are compared with each other or against placebo and there are differences between groups, as is commonly the case. What do the differences, when considered as effect sizes, mean for patients?
 

Go to article: http://updates.pain-topics.org/2011/12/pain-research-differences-that-make.html

Part 11: “Proof” in Pain Research: How Much is Enough?

Weighing Evidence in Law and Medicine; Stewart B. Leavitt, MA, PhD; February 24, 2012.

Just as “Where’s the beef?!” was the exhortation in a once-popular hamburger commercial, healthcare providers and patients should be demanding “Where’s the proof?!” when it comes to research in the pain management field. This article examines parallels in law and medicine regarding several critical questions: What qualifies as evidence? What are requirements of evidence as proof? How much proof is needed for reaching valid and just clinical decisions?

Go to article: http://updates.pain-topics.org/2012/02/proof-in-pain-research-how-much-is.html

Part 12: Fallacies in Pain Research

How Critical Thinking Goes Awry; Stewart B. Leavitt, MA, PhD; May 2, 2012.

The greatest mistake that consumers of pain research can make is to blindly accept that published results and conclusions, or narrative arguments of some sort, are undoubtedly reasonable and true. We can either become wise or be fooled by commonplace fallacies in the pain literature. Although uncertainty and doubt are inherent in all scientific endeavors, where there is doubt there also can be understanding.

Go to article: http://updates.pain-topics.org/2012/05/fallacies-of-evidence-in-pain-research.html

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Easily Calculate Effect Sizes & More with PTCalcs

A key requirement for assessing the validity of pain research is knowing the clinical significance of study outcomes represented as effect sizes. This is discussed in Part 10 of this Series [above]. However, many times authors do not provide effect sizes for their data and readers are left to perform that statistical task on their own. But, how?

PTCalcs from Pain Treatment Topics is a free, online MicroSoft® Excel® spreadsheet that makes the task easy. This multipart program calculates effect sizes and other vital parameters by merely plugging-in outcomes data commonly found in published research reports. There are 11 easy-to-use statistical calculator worksheets...
 

• Effect Size for a Difference between 2 Means with SDs – Cohen's d.
• Effect Size and SD from a Mean Difference with Confidence Interval (CI).
• Effect Size and Standard Deviations (SDs) from 2 Means with CIs
• Effect Size for a Difference between 2 Proportions – h Statistic.
• Effect Size comparing 2 Correlation Coefficients – q Statistic.
• Effect Size for Chi-Square – w Statistic.
• Effect Size, CI, SD from P-value for a Difference between Means or Proportions.
• Convert between Effect Sizes – r, d, f, Odds Ratio, eta-squared, AUC.
• Obtain P-value from CI for Difference between Means, Proportions, or Ratio.
• Obtain CI from a P-value for Difference between Means, Proportions, or Ratio.
• Plot CIs when Point Estimate and Upper & Lower Limits are known.
  

These statistical calculators are intended only as an aid for assessing the quality and validity of research outcomes. Results are approximate and should not be used for inclusion in research papers submitted for publication.

Download PTCalcs here: http://pain-topics.org/docs/PTCalcs.xls

(requires any version of Microsoft® Excel®)

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