Research Chapter 10
systematic measurement error
Variation in measurement values from the calculated average is primarily in the same direction. For example, most of the variation may be higher or lower than the average that was calculated. Systematic error occurs because something else is being measured in addition to the concept When measuring subjects' weights, a scale that shows weights that are 2 pounds over the true weights will give measures with systematic error. All the measured weights will be high, and as a result the mean will be higher than if an accurate weight scale were used
measurement error
is the difference between the true measure and what is actually measured For example, a weight scale may be inaccurate for 0.5 pound, precisely calibrated BP equipment might decrease in precision with use, or a tape measure may not be held at exactly the same tension in measuring the waist of each patient. A subject in a study may be 65 years old but may write illegibly on the demographic form. As a result, the age may be entered inaccurately into the study database
visual analogue scale
is typically used to measure strength, magnitude, or intensity of individuals' subjective feelings, sensations, or attitudes about symptoms or situations. Subjects are asked to place a mark through the line to indicate the intensity of the sensation or feeling. Then researchers use a ruler to measure the distance between the left end of the line (on a horizontal scale) and the subject's mark. This measure is the value of the sensation.
nominal
lowest of the four. It is used when data can be organized into categories of a defined property but the categories cannot be rank-ordered. ex: name, hair color, address Data such as gender, race and ethnicity, marital status, and diagnoses are examples of nominal data.
ordinal
data are assigned to categories that can be ranked To rank data, one category is judged to be (or is ranked) higher or lower, or better or worse, than another category For example, if you are measuring intensity of pain, you may identify different levels of pain. You probably will develop categories that rank these different levels of pain, such as excruciating, severe, moderate, mild, and no pain. However, in using categories of ordinal measurement, you cannot know with certainty that the intervals between the ranked categories are equal. A greater difference may exist between mild and moderate pain, for example, than between excruciating and severe pain. Therefore ordinal data are considered to have unequal intervals.
primary data
data collected for a particular study
secondary data
data collected from previous research and stored in a database & used by other researchers to address their study purposes
Levels of Measurement
from low to high, nominal, ordinal, interval, & ratio
interval
have equal numerical distances between intervals interval scale lacks a zero point. Temperature is the most commonly used example of an interval scale. The difference between the temperatures of 70 F and 80 F is 10 F and is the same as the difference between the temperatures of 30 F and 40 F. Changes in temperature can be measured precisely However, a temperature of 0 F does not indicate the absence of temperature
indirect measures
not a concrete object but an abstract idea, characteristic, or concept such as pain, stress, caring, coping, depression, anxiety, adherence Therefore multiple measurement methods or indicators are needed, and even then they cannot be expected to measure all elements of an abstract concept. For example, multiple measurement methods might be used to describe pain in a study, which decreases the measurement error and increases the understanding of pain. The measurement methods of pain might include the FACES Pain Scale, observation (rubbing and/or guarding the area that hurts, facial grimacing, and crying), and physiological measures, such as pulse and blood pressure.
ratio
highest form, has absolute zero Weight, length, and volume are commonly used as examples of ratio scales. All three have absolute zeros, at which a value of zero indicates the absence of the property being measured; zero weight means the absence of weight. Because of the absolute zero point
structured interview
in which the content is similar to that of a questionnaire, with the possible responses to questions carefully designed by the researcher researchers use strategies to control the content of the interview. Usually, researchers ask specific questions and enter the participant's responses onto a rating scale researchers use strategies to control the content of the interview. Usually, researchers ask specific questions and enter the participant's responses onto a rating scale or paper and pencil instrument during the interview.
direct measures
involve determining the value of concrete factors such as weight, waist circumference, temperature, heart rate, BP, respiration
focus groups
obtain participants perceptions of narrow subject in a group interview session
interviews
verbal communication between researcher and subject, during which information is provided to the researcher
rating scales
Crudest form of measure involving scaling techniques. Rating scales are commonly used by the general public. In conversations, one can hear statements such as "On a scale of 1 to 10, I would rank that. ..." . For example, the FACES Pain Scale is a commonly used rating scale to assess the pain of children in clinical practice and has proven to be valid and reliable over the years
Likert Scale
Designed to determine the opinions or attitudes of study subjects. This scale contains a number of declarative statements, with a scale after each statement ex pain scale with faces
Reliability Testing
Measure of the amount of random error in the measurement technique.
Reliability
consistency of measurement
unstructured interview
content is controlled by study participant
random measurement error
the difference between the measured value and the true value is without pattern or direction (random) In one measurement, the actual value obtained may be lower than the true value, whereas in the next measurement, the actual value obtained may be higher than the true value For example, the person taking the measurements may not use the same procedure every time, a subject completing a paper and pencil scale may accidentally mark the wrong column, or the person entering the data into a computer may punch the wrong key