When you have a heaping plate of research, inspect it carefully before swallowing

May 1, 1997
Research shows us many things: Sugar is cariogenic. Cigarettes stunt lung growth. Periodontal disease is multifactorial. It also shows that edentulous people who eat shark cartilage grow new teeth, and fluoride causes AIDS.

Heidi Emmerling, RDH, BS

Research shows us many things: Sugar is cariogenic. Cigarettes stunt lung growth. Periodontal disease is multifactorial. It also shows that edentulous people who eat shark cartilage grow new teeth, and fluoride causes AIDS.

Research is absolutely necessary to advance the art and science of our profession. While we love our statistics and prize those double-blind studies, we still know that we must be critical consumers of professional research. First, we need to keep in mind what type of literature to expect from specific publications.

RDH is not a scientific journal. It gives us practical advice in a lively, informal tone. It entertains us, challenges us to think about political issues, and informs us of the latest trends in dental hygiene.

You will not find this format in the Journal of Dental Hygiene or the Journal of Periodontology. These are written in a more formal tone. These are not "fun" lively reads. Some would venture to say that they are the ultimate cures for insomnia. It is tempting to want to skim the abstract and conclusion and skip all the "details." Let`s just cut to the chase...Do oral irrigators really lead to reduced bleeding on probing? Are ultrasonic scalers more effective than hand scalers?

Details, details, details

But we need the details. Without them, all we get is the researcher`s interpretation of the data. We leave ourselves vulnerable to swallowing such nonsense as "fluoride causes AIDS."

There are two types of research. First, we have the "hard" quantitative research that measures and counts things like pocket depths, bleeding indicies, and strains of bacteria. Next, we have the descriptive, qualitative research that explores such effects as patient attitude toward oral hygiene instruction or job satisfaction of hygienists.

Few researchers dispute that descriptive research is more subjective than the experimental research. This does not mean that the quantitative research is objective. No writing is ever totally objective. And published research is writing. Although we prize numerical-type scientific research because it tends to be more valid and more reliable, I would argue that even quantitative, experimental, scientific research can include elements of subjectivity. While we may visualize experimental researchers as detached, objective, emotionless, unbiased, and disinterested, we must remember that they are people too. Even though they may wear white coats and spend time in a laboratory, these researchers came up with the hypothesis in the first place. That in itself is a bias. Something compelled them to spend lots of time and money to find an answer.

Are they objective when tenure is on the line?

Researchers need tenure. Researchers need grants. Researchers need publication credit. Researchers form hypotheses and will probably utilize measuring instruments that will prove their hypotheses correct.

Remember the adage: numbers don`t lie but statisticians do. Well, researchers hire statisticians. If need be, researchers will more than likely hunt for something significant in their study to justify doing the research in the first place. This is not malevolent and does not mean that research is unimportant or useless. On the contrary.

Subjectivity is an intrinsic characteristic of research and writing. We need to acknowledge it and know it is there. We have no way of knowing whether a particular study is worthwhile or not until we are able to be critical consumers of research and spot a researcher`s bias as well as our own.

The use of central tendency illustrates this point. Let`s say you make $600 a week and want a raise. You conduct a salary survey of hygienists in Small Town, USA, and the following numbers come back: $600, $700, $700, $800, $900, $1,000, and $2,500.

You tell your employer that you deserve to earn the median, or average salary, which is $1,288.71. Your employer counters by saying that most hygienists make $700 which is represented by the mode (the most common response). Someone else says that you should be making the median salary ... not too high, and not too low ... just the number located right in the middle, which is $800.

All three responses to the data are correct - yet all responses are different. At least two of the three have a vested interest in using the instrument that they chose. You use the instrument which yields you the highest salary increase; the employer uses that which yields the lowest. With just a cursory look at the numbers without analyzing which direction the presenter of the numbers is trying to persuade us, we make ourselves vulnerable to their subjectivity.

Other questions to ponder when analyzing quantitative, experimental research are:

- "Would the researcher have gotten this result by chance?" If so, then the results are not significant. Much quantitative research is designed to examine correlations between variables. Careful researchers will not infer causation; rather they will infer correlations and then test their inferences statistically.

- "How are the subjects selected?" If the subjects are volunteers, be somewhat suspicious of the results. Although the results may be interesting and be worthy of discussion, keep in mind that people who voluntarily agree to be part of a project or mail in surveys tend to be different from the general population.

- "Are the subjects selected randomly?" For quantitative, experimental, and empirical scientific research, random selection is preferred. Random does not mean haphazard selection.

To obtain a random sample of hygienists, for example, a researcher would acquire a list of all hygienists and number them. Then the researcher would refer to a table of random numbers to select the subjects. This allows for an equal and independent chance of being selected. Many statisticians and researchers say that for a sample to be representative, there should be about 275 subjects for every 1000 people.

- "What is the inter-rater reliability?" This asks how closely the different "raters" or examiners are calibrated to interpret the data. Dental hygiene examiners calibrate during clinical boards. They strive for consistency. If one examiner probes a 5 millimeter pocket, so should the next examiner. Researchers advocate inter-rater reliabilities should be no less than .73. The closer to 1.0 the better.

- "Is the research valid?" This asks if the researchers are answering the research question they present. If the research question is, "Do irrigators result in decreased bleeding indices?" and the researchers conclude that "floss removes plaque" then the research is not valid because they did not answer the question about the irrigators.

- "Is the research reliable?" This asks if other examiners could perform the same research and come up with similar results. If one researcher finds that treating contaminated instruments with dry heat results in sterilization, and numerous other researchers repeat this experiment yielding the same results, the research is said to be reliable.

Researchers are not deliberate propagandists in some malevolent sense. But their knowledge is not immune from subjectivity, and their results can be misunderstood. Some of the responsibility for any misunderstanding belongs to the researchers for their attempt to obscure the inherent subjectivity. Just as much responsibility probably goes to the consumers for their naivete.

Questions of intent and culpability aside, the fact remains that the nature of quantitative research, its form and seeming objectivity, makes control over its uses and abuses nearly impossible.

Heidi Emmerling, RDH, BS, is a consulting editor for RDH, a writer, speaker, and clinician from Sparks, Nevada. Her e-mail address is [email protected]