Reading Research Literature—Implementing the Study, Data Collection Methods
Numbers and Definitions
We continue our review of the steps of the research process. Earlier in the course, we discussed the following.
- Why the researcher believes the topic to be significant enough to warrant further investigation. The why is found in the Introduction and Literature review.
- What the researcher chooses to research. The what is identified in the research problem, research purpose, and research question.
- Who the researcher decides to study. Who is explained in the sampling strategy.
- Where the researcher opts to conduct the study. The where is described in the setting section.
- How is the theme this week as we concentrate on how the research data are measured and collected on the sample of the population. This information is usually found in the methods section of the research report.
In general, the researcher wishes to learn more about the characteristics of a population. Research questions may include the following.
- Are the characteristics of interest present in the population?
- Are there discernible relationships among the characteristics?
- Can predictions be made about one characteristic based on another? Data collected about the characteristics are usually represented by numbers.
Why use numbers? According to Houser (2018), numbers are objective, standardized, consistent, precise, statistically testable, and an accurate representation of attributes.
The researcher may work with numbers that can be calculated and have numerical value—for example, body temperature. At other times, the researcher assigns numbers to traits simply to classify them. These numbers are not quantifiable but, rather, serve to sort, organize, or group subjects according to traits. An example would be a rating based on perception, such as self-esteem. Reading Research Literature—Implementing the Study, Data Collection Methods
As you can see, not all numbers possess the same properties. The researcher must set up rules regarding how numbers are determined, collected, recorded, and analyzed. These rules are called the measurement strategy.
Part of the measurement strategy is to define the research variables.
- The conceptual definition may be offered in the conceptual or theoretical framework. This is understood, but is vague, and, therefore, does not lend itself to direct measurement.
- The researcher must translate the conceptual definition into an operational definition that spells out in specific, concrete terms how variables will be measured.
Example: The researcher may wish to study anxiety. The researcher offers a conceptual definition of anxiety as the emotional response to a perceived threat. The operational definition describes the emotional responses in concrete, measureable terms, such as sweating and rapid heart rate.
When you formulate clinical questions and identify PICO elements, your goal is to think like the researcher. Select key words to search that are similar to operational definitions the researcher may have chosen. Avoid searching on conceptual terms such as better health that are too vague to match. Operationalizing key terms will improve your chances of finding relevant research-based evidence. Reading Research Literature—Implementing the Study, Data Collection Methods
Levels of Measurement
Variables must be expressed as numbers in order to analyze them statistically, but different types of numbers have different levels of measurement.
Table 5.1 |
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Level of Measurement | Description | Examples | Implications for Statistical Testing |
Nominal | Variables are
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Subjects cannot be compared. Analysis may include frequencies in each category. Analyze with nonparametric statistics. |
Ordinal | Variables are
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Subjects can be compared. Analysis may include frequencies and percentiles. The median may be computed. Analyze with nonparametric statistics. Reading Research Literature—Implementing the Study, Data Collection Methods |
Interval | Variables are
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Values can be added and a mean computed. Analyze with parametric statistics.
Reading Research Literature—Implementing the Study, Data Collection Methods |
Ratio | Variables are
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Values can be added and a mean computed. Analyze with parametric statistics. |
Information adapted from Houser, 2018.
Errors
Errors may occur when collecting data. A measurement error is the difference between the true number and the number that the instrument reads.
Random error leads to readings that may be inaccurate for a variety of reasons. Some readings are accurate, whereas others are inaccurate; the occurrence of either type of reading is unpredictable and cannot be reproduced.
Systematic error happens consistently and can introduce bias into the readings. One example of a systematic error occurs when a poorly calibrated instrument produces readings that are all too high or too low, or a systematic error happens when an observer mistakes a behavior and marks it as one thing on the rating tool when the behavior should be marked as another. Reading Research Literature—Implementing the Study, Data Collection Methods.
Errors in measurement can ripple throughout the rest of the research process and lead to faulty findings.
Instruments
Instruments measure variables. Instruments must be reliable and valid in order to yield useful data.
Reliable instruments measure a variable with precision.
- Internal reliability occurs when the instrument produces the same results each time it is used. This indicates that the instrument is stable. Certain instruments may need to be calibrated in order to ensure reliable measurement.
- Inter-rater reliability indicates that the instrument produces the same results when different people use it. The raters are stable when this occurs. Inter-rater reliability is particularly important in studies where data are collected by more than one researcher. If there is a lack of reliability (as inter-rater stability is established), we conclude that any significant differences may be due to the inaccurate measurement of the instrument and not because of the variables themselves.
Valid instruments measure in a manner that is accurate and truthful. A valid instrument measures the correct thing.
An instrument may be reliable but not valid in that it may consistently measure something that is not accurate. Instruments must be reliable in order to be valid, and both attributes must exist in order to measure data in a way that inspires confidence in the research findings. Each method of data collection has its own strengths and weaknesses with respect to reliability and validity.
The measurements section of the research report describes the instruments that the researcher used to collect data. The researcher may describe the reliability and validity of the instrument. The existence of both attributes lends credibility to the claims that the researcher makes in the findings. Decide if the instruments actually measure the variables identified in the research question. If there is a mismatch, the findings should not be applied to your situation. Reading Research Literature—Implementing the Study, Data Collection Methods.
Data Collection
- Physiologic measures involve instruments that measure physiologic dimensions, such as blood gases, pulmonary function, and other diagnostic tests.
- Psychometric instruments include scales or surveys. The survey is the most common method to collect research data.
- Interviews and questionnaires collect subjective data, such as attitudes or descriptions of experiences provided by individuals or focus groups.
- Observation obtains objective data related to behavior that the subject may not be able to describe, such as activity during sleep or agitation in the person withdrawing from alcohol. Reading Research Literature—Implementing the Study, Data Collection Methods.
Secondary data may be collected from sources that were not created for the current research study. Typically, the researcher looks through records or “mines” the relevant data that pertains to the variables. Examples include but are not limited to
- patient charts;
- census reports; and
- public health records.
Q&A
A popular data collection instrument is the Likert scale. What is a Likert scale? What type of number does it measure?
The Likert scale is a 5- or 7-point scale that asks the subject to answer a question by indicating a number on the scale. Typically, the subject is asked to indicate the degree to which there is agreement or disagreement. The numbers represent ordinal data. The numbers can be ordered and ranked, but there is no fixed interval between the numbers. An example of a question using a Likert scale is, “Do all citizens have a right to healthcare regardless of their ability to pay?” Please choose a number between one and five that best indicates your answer to this question.
1 |
2 |
3 |
4 |
5 |
Strongly Agree |
Agree |
Neutral |
Disagree |
Strongly Disagree |
Review the interactive research report to discover where the data collection method is described.
The following research report contains descriptions of the various components that comprise most reports. The purpose of this interactive report is to help you learn where to find specific information.
Summary
The implementation of the research study is a crucial step of the research process. The way the researcher defines characteristics in the population leads to the selection of instruments to measure and collect data on the subjects that represent that population. The key terms that you choose to search for, research-based evidence, should try to match the way in which the researcher operationalizes the definitions of the variables. Reading Research Literature—Implementing the Study, Data Collection Methods.
It is important to remember that not all numbers have the same attributes. Some are merely for classification, whereas others can be quantified and analyzed statistically. Be sure that any instruments are reliable and valid and that they accurately collect data that will help the researcher to close the knowledge gap.
References
Garbage-in, garbage-out. (2010). Business Dictionary.com. Retrieved from http://www.businessdictionary.com/definition/garbage-in-garbage-out-GIGO.html
Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones and Bartlett. Reading Research Literature—Implementing the Study, Data Collection Methods.