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# behav sci

### First Aid- Behavioral Sciences

Case control study observational and retrospective; compares group with ds to group w/o. Identifies risk factor, "what happened?" Uses Odds Ratio
Cohort study observational and prospective: compares group exposed to risk factor to group w/o exposure, "what will happen?" Uses Relative Risk
Cross sectional study observational: collects data at a particular point in time "what is happening?" uses disease prevalence
Clinical trial: Phase 1 is it safe? asseses toxicity and pharmockinetics
Clinical trial: Phase 2 Does it work? (efficacy) assesses optimal dosing, efficacy and adverse effects
Clinical trial: Phase 3 Does it work better? compares new tx to current standard of care
Clinical trial: Phase 4 Detects long term or rare adverse affects
Sensitivity Probability that a person with ds will test + SNOUT= rules in, =TP/TP+FN =1-FN rate
Specificity Probability that a person w/o ds will test - SPIN= r/o =TN/TN+FP =1-FP rate
Positive Predictive Value (PPV) proportion of postive test results that are TP =TP/TP+FP
Negative Predictive Value (NPV) proportion of negative test results that are true negative. =TN/FN+TN
Prevalence ~= to incidence x disease duration
Incidence = # of new cases
Odds ratio For case control studies: odds of having disease in exposed group divided by odds of having ds in unexposed gropu. = ad/bc
Relative risk for cohort studies RR= (a/(a+b)) / (c/ (c+d))
Attributable risk Difference in risk between exposed and unexposed. = ( a/(a+b)) - (c/(c+d))
Absolute Risk reduction same as attributable risk, except replacing risk by reduction of risk due to exposure to drug. (same eq. as attributable risk)
NNT- Number needed to treat 1/absolute risk reduction
NNH- number needed to harm 1/ attributable risk
Precision consistency and reproducability of a test
accuracy trueness of the test measurements
Selection bias non random assignment to study group, may include loss to follow- up includes berkson bias
Berkson's bias Using only hospital records as data
recall bias knowledge of presence of d/o alters recall by subjects
sampling bias subjects are not representative relative to general population; therefore results are not geralizable
late-look bias information gathered at an inappropriate time- eg. using a survey to study a fatal disease ( only those patients still alive will be able to answer the survey)
Procedure bias subjects in different groups are not treated the same. e.g., more attention is paid to treatment group, stimulating greater compliance
confounding bias occurs with 2 closely associated factors; the effect of 1 factor distorts or confuses the effects of another.
Lead-time bias early detection confused with increased survival; seen with improved screening (natural history of ds is not changed, but earl detection makes it seem as tho survival increased)
pygmalian effect occurs when a researchers belief in the efficacy of a treatment changes the outcome of that treatment
hawthorne effect occurs when the group being studied changes its behavior oweing to the knowledge of being studied.
effect modification is present when the effect of teh main exposure on teh outcome is modified by the presence of another variable. eg: effect of new estrogen receptor agonist on the incidence of DVT is modified by smoking status)
Normal Gaussian statistical distribution mean=median= mode
bimodal statistical distribution 2 humps (2 modal peaks)
positive skew mean > median > mode asymmetry with tail on the right
negative skew mean < median < mode asymmetry with tail on the left
Null hypothesis (H0) Usually opposes your hypothesis hypothesis of no difference (eg there is no association b/w the disease and the risk factor in the population).
alternative hypothesis (H1) hypothesis that there is some difference (eg there is some association b/w the ds and the risk factor in population)
Type 1 error (alpha) study shows something that is not reality states there is an effect when none exists. p= probability of making a type I error. False positive error
p < .05 p= probability of making type 1 error, should be less than .05
Type II error (beta) stating that there IS NOT an effect or difference when one does exist. False negative error
Power (1-beta) study shows something that's there or doesn't show what's not there
Percentage of population in 1 SD (standard deviation) 68%
Percentage of population in 2 SD 95.5%
percentage of population in 3 SD 99.7%
Confidence Interval range of values in which a specified probability of the means of repeated samples would be expected to fall.
Confidence Interval equation CI= range from (mean-Z(SEM) to (mean + Z (SEM)
Z in different Confidence intervals 95% CI, Z= 1.96 90% CI, Z= 1.645 99% CI, Z= 2.57
t-test checks the difference between the means of 2 groups
ANOVA ANOVA checks difference bw 3 OR MORE groups
chi squared test checks difference bw 2 or more percentages or proportions of categorical outcome (not mean values)
correlation coefficient (r) r is always between -1 and +1. the closer the absolute value of r is to 1, the stronger the correlation between the 2 variables
Coefficient of determination r squared, value that is usually reported
disease prevention primary- prevent disease occurrence secondary- early detection of ds tertiary- reduce disability from ds (eg chemo)
Reportable diseases (STD's) (HIV)/AIDS, syphilis, gonorrhea
Reportable diseases (Heps) Hep A, B, and (C)
Reportable diseases (kids) MMR: measles, mumps, rubella and chicken pox
Reportable diseases (diarrheals) Salmonella, Shigella
Leading cause of death in infants Congenital anomalies, SIDS, Respiratory distress syndrome
Leading cause of death ages 1-14 injuries, cancer, congenital anomalies
Leading cause of death ages 15-24 injuries, homicide, suicide
Leading cause of death ages 25-64 cancer, heart attack, injuries
Leading cause of death ages 65+ heart ds, cancer, stroke
Medicare medicarE is for Elderly part A= inpatient care part B= outpatient care part C= combo of A and B pard D= prescription drug coverage
medicaid MedicaiD is for the destitute is federal and statehealth assistance for people with very low income
APGAR score assess what? assesses health of a newborn at 1 and 5 minutes old Appearance, Pulse, Grimace, Activity, Respiration
Low birth weight (defined as) <2500g
Low birth weight complications infections, respiratory distress syndrome, necrotizing enterocolitis (due to feeding baby too fast), intraventricular hemorrhage, persistant fetal circulation
Created by: 16306496

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