>When we measure something, we want to make sure our measurement is credible and trustworthy. This is particularly true in healthcare, where health and well-being may vitally depend on it!
>This key quality of good measurement is known as validity. Are we really measuring what we think we are measuring? Or might we accidentally be picking something else (other than what we intended) in our measurements?
>Here’s an example from psychology. If we have a test intended to measure depression, is this what we are really measuring? Or might we accidentally be picking up anxiety instead?
>>**We will be working with this concept of validity and how we can assess it in our measurement instruments.In order to qualify for full participation points, you are asked to post your own thoughts on each topic.*******
>>**Here’s a resource that will be very helpful to you in understanding validity and reliability in research:
1. Illness Prevalence:
The number of cases of illness in a population is referred to as its prevalence. Comment on what a high illness prevalence does to the positive predictive value (PPV). What about a low illness prevalence?
2. Study Feasibility:
In your research involving the BMI of fifth grade boys in the U.S., you will not only be collecting information on a child’s BMI, but also on his TV viewing habits, his eating habits, and his extracurricular activities. You would like to make contact through the school systems to gather your information. Discuss at least one factor that might affect the feasibility of this study.