Behavioral Science Flashcards
study population in cohort study
Compares a group with a given exposure or risk factor to a group without such exposure.
Ruling in vs. out
Negative test in a highly sensitive test rules out disease. Highly specific test rules in disease. (SNOUT/SPINN)
Other expression for sensitivity
1- false-negative rate
Effect of lowering test cutoff
Increased sensitivity, decreased specificity, increased NPV, decreased PPV (just think about it as increasing the # of FP and decreasing the nuber of FNs)
Effect of raising test cutoff
Increased specificity, decreased sensitivity, increased PPV, decreased NPV (similarly just think of it as increasing the # of FNs and decreasing the # of FPs).
Attributable risk
Difference in risk between exposed and unexposed groups, or the proportion of disease occurrences that are attributable to the exposure (eg, if risk of lung cancer in smokers is 21% and risk in nonsmokers is 1%, then 20% of lung cancer risk in smokers is attributable to smoking).
If 21% of smokers develop lung cancer vs. 1% of nonsmokers, what is the relative risk?
21
absolute risk reduction
Difference in risk (NOT proportion) attributable to interention as compared to a control (eg, if 8% of people who receive a placebo vaccine develop the flu vs. 2% of people who receive a flu vaccine, then ARR = 8% - 2% = 6% = .06
Number needed to harm
Number of patients who need to be exposed to a risk factor for 1 patient to be harmed.
Relation between precision and statistical power
Increased precision, increased statistical power
Statistical power definition
1-beta
random error vs. systematic error
random error decreases precision in a test, systematic error decreases accuracy in a test.
Berkson bias
Study population selected from hospital is less healthy than general population.
Healthy worker effect
Study population is healthier than the general population
Non-response bias
Participating subjects differ from nonrespondents in meaningful ways.
Procedure bias
Subjects in different groups are not treated the same.
Observer-expectancy bias
Researcher’s belief in the efficacy of a treatment changes the outcome of that treatment.
pygmalion effect
observer-expectany bias. AKA self-fulfilling prophecy
Crossover study
Subjects act as their own controls.
Lead-time bias
early detection confused with increased survival
How do you mitigate lead-time bias?
Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis).
normal distribution
mean = median = mode
Variance definition
(SD)^2
Standard error of the mean (SEM)
Estimate of how much variability exists between the sample mean and the true population mean.
Definition of SEM
SD/sqr(n)
Relation between SEM and n
SEM decreases and n increases
positive skew
mean>median>mode (asymmetry with longer tail on right)
negative skew
mode > median > mean
alternative hypothesis
Hypothesis of some difference or relationship.
beta
Probability of making a type II error.
alpha
Probability of making a type I error.
You sAw an error that didn’t exist
False-positive error
Type I error (alpha)
Type I error
Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis).
What does a p value of 0.05 indicate?
There is less than a 5% chance that the data will show something that is not really there.
Type II error (beta)
False-negative error.
Type II error (beta)
stating that there is not an effect or difference when one exists (Null hypothesis is not rejected when it is in fact false). (beta, you were blind to the truth).
Statistical power
(1-beta). Probability of rejecting the null hypothesis when it is false.
How would you increase power and decrease beta?
1) increase sample size.
2) increase expected effect size.
3) increase precision of measurement.
Confidence interval
Range of values within which the true mean of the population is expected to fall, with a specified probability.
CI equation
CI = mean +/- Z(SEM)
Important points about CI
1) If the CI includes 0, there is no significant difference.
2) If the CI for odds ratio or relative risk includes 1, there is no significant difference.
3) If the CIs between 2 groups overlap, usually no significant difference exists. Conversely, if CIs between 2 groups do not overlap, statistically significant difference exists.
Pearson correlation coefficient (r)
r is always between -1 and +1. The closer the absolute value is to 1, the stronger the linear correlation between 2 variables.
Coefficient of determination
r^2
exceptions to informed consent
1) patient lacks decision-making capacity or is legally incompetent.
2) Implied in an emergency
3) therapeutic privilege
4) waiver (patient waives right)
Conditions for which a minor is legally emancipated
1) Married
2) self supporting
3) in the military
Situations in which parental consent is usually not required.
Sex (contraception, STIs, pregnancy), drugs (substance abuse), and rock and roll (emergency/trauma)
Oral advance directive
Incapacitated patient’s prior oral statements used as a guide for decision-making.
priority of surrogates
spouse>adult children>parents>adult siblings>other relatives.
answer to confidentiality questions
make an exception if its in the patient’s best interests.
Reportable diseases in which patient confidentiality is broken.
STIs, TB, hepatitis, food poisoning
Tarasoff decision
California Supreme Court decision requiring physician to directly inform and protect potential victim from harm.
nonintuitive exceptions to patient confidentiality
1) child and/or elder abuse
2) impaired automobile drivers
3) suicidal patients