BEHAVIORAL SCIENCE Flashcards
(96 cards)
Cross-sectional study
Type, Design, Measures & Examples
Observaional
Design: Collects data from a group of people to assess frequency of disease (and related risk factors) at a particular point in time. Asks, “What is happening?”
Measures/Examples:
Disease Prevalance
Can show risk factor association with disease, but does not establish causality.
Case-control study
Type, Design, Measures & Examples
Observational and retrospective
Design: Compares a group of people with disease to a group without disease. Looks for prior exposure or risk factor. Asks, “What happened?”
Measures/Example:
Odds ratio (OR).
“Patients with COPD had higher odds of a history of smoking than those without COPD had.”
Cohort Study
Type, Design, Measures & Examples
Observaional and prospective or retrospective
Design: Compares a group with a given exposure or risk factor to a group without such exposure. Looks to see if exposure the likelihood of disease. Can be prospective (asks, “Who will develop disease?”) or retrospective (asks, “Who developed the disease [exposed vs. nonexposed]?”).
Measures/Example: Relative risk (RR). “Smokers had a higher risk of developing COPD than nonsmokers had.”
Twin concordance study
Design: Compares the frequency with which both monozygotic twins or both dizygotic twins develop same disease.
Measures/Examples:
Measures heritability and influence of environmental factors (“nature vs. nurture”).
Adoption study
Design: Compares siblings raised by biological vs. adoptive parents.
Measures/Example:
Mesures heritability and influence of environmental factors.
Clinical trial
Experimental study involving humans. Compares therapeutic benefits of 2 or more treatments, or of treatment and placebo.
How can one improve the quality of clinical trials?
Study quality improves when study is randomized, controlled, and double-blinded (i.e., neither patient nor doctor knows whether the patient is in the treatment or control group).
What is triple-blind?
Triple-blind refers to the additional blinding of the researchers analyzing the data.
Drug Trial Phases; study sample; and purpose
Phase I - Small number of healthy volunteers.
Purpose: “Is it safe?” Assesses safety, toxicity, and pharmacokinetics.
Phase II - Small number of patients with disease of interest.
Purpose: “Does it work?” Assesses treatment efficacy, optimal dosing, and adverse effects.
Phase III - Large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo).
Purpose: “Is it as good or better?” Compares the new treatment to the current standard of care
Phase IV - Postmarketing surveillance trial of patients after approval.
Purpose: “Can it stay?” Detects rare or long-term adverse effects. Can result in a drug being withdrawn from market.
Evaluation of diagnostic tests
Uses 2 × 2 table comparing test results with the actual presence of disease.
TP = true positive; (Test +, Disease +)
FP = false positive; (Tes+, Disease -)
TN = true negative;
FN = false negative.
Sensitivity and specificity are fixed properties of a test
Define Sensitivity
True-positive Rate
Proportion of all people with disease who test positive, or the probability that a test detects disease when disease is present.
What does a high sensitivy % indicate?
Value approaching 100% is desirable for ruling out disease and indicates a low false-negative rate.
what is high sensitivity test used for?
High sensitivity test used for screening in diseases with low prevalence.
Sensitivity formula
= TP / (TP + FN)
= 1 – false-negative rate
If sensitivity is 100%, TP / (TP + FN) = 1, FN = 0, and all negatives must be TNs
Define Specificiy
True-negative rate
Proportion of all people without disease who test negative, or the probability that a test indicates non-disease when disease is absent.
What does a high Specificity indicate and what is it used for?
Value approaching 100% is desirable for ruling in disease and indicates a low falsepositive rate.
High specificity test used for confirmation after a positive screening test.
Specificity formula
= TN / (TN + FP)
= 1 – false-positive rate
(SP-P-IN = highly SPecific test, when Positive, rules IN disease )
If specificity is 100%, TN / (TN + FP) = 1, FP = 0, and all positives must be TPs
Define Positive predictive value (PPV)
Proportion of positive test results that are true positive
. Probability that person actually has the disease given a positive test result.
PPV Formula
= TP/(TP+FP)
How does PPV relate with prevalance?
PPV varies directly with prevalence or pretest probability:
high pretest probability –> high PPV
Define Negative predictive value (NPV)
Proportion of negative test results that are true negative.
Probability that person actually is disease free given a negative test result.
NPV Formula
= TN/ (FN+TN)
How does NPV relate to prevalance?
NPV varies inversely with prevalence or pretest probability:
high pretest probability –> low NPV
Incidence Rate formula
Incidence rate =
of new cases in a specified time period
________________________________
Population at risk during same time period