Behavioral Science Flashcards
Cross-sectional study
Collects data from a group of people to assess frequency of disease (and related risk factors) at a particular point in time
What is happening?
Disease prevalence
Can show risk factor association with disease, but does not establish causality
Case-control study
“Retrospective”
Compares a group of people with disease to a group without disease
Looks for prior exposure or risk factor
What happened?
Odds Ratio
“Patients with COPD had higher odds of a Hx of smoking than those without COPD”
Cohort study
“Retrospective or Prospective”
Compares a group with a given exposure or risk factor to a group without such exposure
Looks to see if exposure increases the likelihood of disease
Can be prospective (asks, “Who will develop disease?”) or retrospective (asks, “Who developed the disease [exposed vs nonexposed]?”)
Relative Risk
“Smokers had a higher risk of developing COPD than nonsmokers”
Twin concordance study
Compares the frequency with which both monozygotic twins or both dizygotic twins develop the same disease
Measures heritability and influence of environmental factors (nature vs nurture)
Adoption study
Compares siblings raised by biological vs adoptive parents
Measures 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. Study quality improves when study is randomized, controlled, and double-blinded (neither patient nor doctor knows whether the patient is in the treatment or control group).
Triple blind refers to the additional blinding of the researchers analyzing the data
Phase 1 - small number of healthy volunteers. “Is it safe?” assesses safety, toxicity, pharmacokinetics, and pharmacodynamics.
Phase 2 - Small number of patients with disease of interest. “Does it work?” Assesses treatment efficacy, optimal dosing, and adverse effects.
Phase 3 - Large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo). “Is it good or better?” Compares the new treatment to the current standard of care
Phase 4 - Postmarketing surveillance of patients after treatment is approved. “Can it stay?” Detects rare or long-term adverse effects. Can result in treatment being withdrawn from market.
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.
Value approaching 100% is desirable for RULING OUT disease and indicates a LOW FALSE NEG rate. High sensitivity test used for screening in diseases with low prevalence.
= TP/ (TP + FN)
= 1 - FN rate
SN-N-OUT = highly SeNsitive test, when Negative, rules OUT disease.
If sensitivity is 100%, TP/(TP - FN) = 1, FN = 0, and all negatives must be TNs
Specificity
“True negative rate”
Proportion of all people without disease who test negative, or the probability that a test indicates no disease when disease is absent.
Value approaching 100% is desirable for RULING IN disease and indicates a LOW FALSE POSITIVE rate. High specificity tests used for confirmation after a positive screening test.
= TN/ (TN + FP)
= 1 - false positive rate
SP-P-IN - highly specific test when positive rules in a disease.
Positive predictive value (PPV)
Proportion of positive test results that are true positive.
Probability that a person actually has the disease given a positive test result
= TP/ (TP + FP)
PPV varies directly with prevalence or pretest probability; high pretest probability leads to high PPV
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
= TN/ (TN + FN)
NPV varies inversely with prevalence or pretest probability; high pretest probability leads to low NPV
Incidence vs prevalence
Incidence rate = # of new cases/# of people at risk (during a time period)
Prevalence = # of existing cases/# of people at risk (at a point in time)
Prevalence = incidence for short duration disease (common cold)
Incidence looks at new cases (incidents)
Prevalence looks at ALL current cases
Prevalence = pretest probability
Quantifying risk
Definitions and formulas are based on the classic 2x2 or contingency table.
Disease
(+) (-)
Risk factor/ (+) a b
intervention (-) c d
Odds Ratio (OR)
Typically used in case-control studies. Odds that the group with the disease (cases) was exposed to a risk factor (a/c) divided by the odds that the group without the disease (controls) was exposed (b/d)
OR = (a/c) / (b/d)
OR = ad/bc
Relative Risk (RR)
Typically used in cohort studies.
Risk of developing disease in the exposed group divided by risk in the unexposed group (if 21% of smokers develop lung cancer vs 1% of nonsmokers, then RR = 21). If prevalence is low, OR = RR
RR =[a/(a+b)] / [c/(c+d)]
Attributable risk (AR)
The difference in risk between exposed and unexposed groups, or the proportion of diseases occurrences that are attributable to the exposure (if risk of lung cancer in smokers is 21% and risk in nonsmokers is 1%, then 20% of the lung cancer risk in smokers is attributable to smoking)
AR = [a/(a+b)] - [c/(c+d)]
Relative risk reduction (RRR)
The proportion of risk reduction attributable to the intervention as compares to a control (if 2% of patients who receive a flu shot develop the flu, while 8% of unvaccinated patients develop the flu, then RR = 2/8 = 0.25, and RRR = 0.75)
RRR = 1 - RR
Absolute risk reduction (ARR)
The difference in risk (not the proportion) attributable to the intervention as compared to a control (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% = 0.06)
ARR = [c/(c+d)] - [a/(a+b)]
Number needed to treat (NNT)
Number of patients who need to be treated for 1 patient to benefit
NNT = 1/ARR
Number needed to harm (NNH)
Number of patients who need to be exposed to a risk factor for 1 patient to be harmed
NNH = 1/AR
Precision
The consistency and reproducibility of a test (reliability)
The absence of random variation in a test
Random error reduces precision in a test
Increased precision leads to lower standard deviation
Increased precision leads to higher statistical power (1-Beta)
Accuracy
The trueness of test measurements (validity).
The absence of systematic error or bias in a test
Systematic error reduces accuracy in a test
Selection bias
Bias in recruiting patients
Error in assigning subjects to a study group resulting in an unrepresentative sample. Most commonly a sampling bias.
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
Reduce it by:
Randomization
Ensure the choice of the right comparison/reference group
Recall bias
Bias while performing study
Awareness of disorder alters recall by subjects; common in retrospective studies
Patients with disease recall exposure after learning of similar cases
Reduce it by:
Decrease time from exposure to follow-up
Measurement bias
Bias while performing study
Info is gathered in a way that distorts it
Miscalibrated scale consistently overstates weights of subjects
Reduce it with:
Use standardized method of data collection
Procedure bias
Bias while performing study
Subjects in different groups are not treated the same
Patients in treatment group spend more time in highly specialized hospital units
Reduce it with:
Blinding and use of placebo reduce influence of participants and researchers on procedures and interpretation of outcomes as neither are aware of group allocation
Observer-expectancy bias
Bias while performing study
Researcher’s belief in the efficacy of a treatment changes the outcome of that treatment (aka Pygmalion effect; self-fulfilling prophecy)
If observer expects treatment group to show signs of recovery, then he is more likely to document positive outcomes
Reduce it with:
Blinding and use of placebo reduce influence of participants and researchers on procedures and interpretation of outcomes as neither are aware of group allocation
Confounding bias
Bias during result interpretation
When a factor is related to both the exposure and outcome, but not on the causal pathway - factor distorts or confuses effect of exposure on outcome
Pulmonary disease is more common in coal workers than the general population; however, people who work in coal mines also smoke more frequently than the general population
Reduce it with:
Multiple/repeated studies
Crossover studies (subjects act as their own controls)
Matching (patients with similar characteristics in both treatment and control groups)
Lead-time bias
Bias during results interpretation
Early detection is confused with increased survival
Early detection makes it seem as though survival has increased, but the natural history of the disease has not changed
Reduce it by:
Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)
Null hypothesis (H0)
Hypothesis of no difference or relationship (there is no association between the disease and the risk factor in the population)
Alternative hypothesis (H1)
Hypothesis of some difference or relationship (there is some association between the disease and the risk factor in the population)
Correct result
Stating that there is an effect or difference when one exists (null hypothesis rejected in favor of alternative hypothesis)
Stating that there is not an effect or difference when none exists (null hypothesis not rejected)
Type 1 error (alpha)
Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis)
Alpha is the probability of making a type 1 error. p is judged against a preset alpha level of significance (usually
type 2 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)
B is probability of making type 2 error. B is related to statistical power (1-B), which is the probability of rejecting the null hypothesis when it is false
Increase power and lower B by:
Increasing sample size
Increasing expected effect size
Increasing precision of measurement
Also know as false-negative error
B = you were Blind to the truth (setting a guilty man free)
Confidence interval
Range of values in which a specified probability of the means of repeated samples would be expected to fall
CI = mean +/- Z (SEM)
The 95% CI (corresponding to p = 0.05) is often used
For the 95% CI, Z = 1.96
For the 99% CI, Z = 2.58
If the 95% CI for a mean difference between 2 variables includes 0, then there is no significant difference and H0 is not rejected
If the 95% CI for odds ratio or relative risk includes 1, H0 is not rejected
If the CIs between 2 groups do not overlap - statistically significant difference exists.
If the CIs between 2 groups overlap - no significant difference exists.
t-test
Checks differences between means of 2 groups
Tea is meant for 2
Ex/ comparing the mean blood pressure between men and women
ANOVA
Checks differences between means of 3 or more groups
3 words. ANalysis Of VAriance.
Ex/ comparing the mean BP between members of 3 different ethnic groups
Chi-squared (X^2)
Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values)
Pronounce. Chi-tegorical
Ex/ comparing the percentage of members of 3 different ethnic groups who have essential hypertension
Pearson correlation coefficient (r)
r is always between -1 and 1. The close the absolute value of r is to 1, the stronger the linear correlation between the 2 variables.
Positive r value - positive correlation (as one variable increases the other one increases too)
Coefficient of determination = r ^ 2. (value that is usually reported)
Disease prevention
Primary - Prevent disease occurrence. (HPV vaccination)
Secondary - Screening early for disease (Pap smear)
Tertiary - Treatment to reduce disability from disease (Chemotherapy)
Quaternary - identifying patients at risk of unnecessary treatment, protecting from the harm of new intervention
Medicare and Medicaid
Medicare and Medicaid - federal programs that originated from amendments to the social security act.
Medicare is available to patients older than 65. Less than 65 with certain disabilities, and those with end-stage renal disease
Medicaid is joint federal and state health assistance for people with very low income.
4 parts of medicare:
A = hospital insurance
B = basic medical bills (doctor’s fees, diagnostic testing)
C = (parts A + B) delivered by approved private companies
D = prescription drugs
Autonomy
Obligation to respect patients as individuals (truth telling, confidentiality), to create conditions necessary for autonomous choice (informed consent), and to honor their preference in accepting or not accepting medical care
Beneficence
Physicians have a special ethical (fiduciary) duty to act in the patient’s best interest. May conflict with autonomy (an informed patient has the right to decide) or what is best for society (traditionally patient interest supersedes)
Nonmaleficence
“Do no harm”
Must be balanced against beneficence; if the benefits outweigh the risks; a patient may make an informed decision to proceed (most surgeries and medications fall into this category)
Justice
To treat persons fairly and equitably. This does not always imply equally (triage)
Apgar score
Assessment of newborn vital signs following labor via a 10 point scale evaluated at 1 minute and 5 minutes.
Apgar score is based on Appearance, Pulse, Grimace, Activity, and Respiration
At least 7 = good
4 - 6 = assist and stimulate
Low birth weight
Defined as
Infant developmental milestones
0-12 months
Motor:
1) Primitive reflexes disappear - Moro (by 3 months), rooting (by 4 months), palmar (by 6), Babinski (by 12)
2) Posture - lifts head up prone (by 1), rolls and sits (by 6), crawls (by 8), stands (by 10), walks (by 12-18)
3) Picks - passes toys hand to hand (by 6), Pincer grasp (by 10)
4) Points to objects (by 12)
Social
1) Social smile (by 2)
2) Stranger anxiety (by 6)
3) Separation anxiety (by 9)
Verbal/Cognitive
1) Orients - first to voice (by 4), then to name and gestures (by 9)
2) Object permanence (by 9)
3) Oratory - says “mama” and “dada” (by 10)
Toddler developmental milestones
12-36 months
Motor
1) Cruises, takes first steps (by 12)
2) Climbs stairs (by 18)
3) Cubes stacked - number = age (yr) x 3
4) Cultured - feeds self with fork and spoon (by 20)
5) Kicks ball (by 24)
Social
1) Recreation - parallel play (by 24-36)
2) Rapprochement - moves away from and returns to mother (by 24)
3) Realization - core gender identity formed (by 36)
Verbal/Cognitive
1) Words - 200 words by age 2, 2 word sentences
Preschool developmental milestones
3-5 yrs
Motor
1) Drive - tricycle (3 wheels at 3 yrs)
2) Drawing - copies line or circle, stick figure (by 4 yrs)
3) Dexterity - hops on one foot (by 4 yrs), uses buttons or zippers, grooms self (by 5 yrs)
Social
1) Freedom - comfortably spends part of day away from mother (by 3 yrs)
2) Friends - cooperative play, has imaginary friends (by 4 yrs)
Verbal/Cognitive
1) Language - 1000 words by age 3, uses complete sentences and prepositions (by age 4)
2) Legends - can tell detailed stories (by 4 yrs)
Changes in the elderly
1) Sexual changes
Men - slower erection/ejaculation, longer refractory period
Women - vaginal shortening, thinning, and dryness
2) Sleep patterns: reduced REM and slow-wave sleep; increased sleep onset latency and increased early awakenings
3) Increased suicide rate
4) Reduced vision, hearing, immune response, bladder control
5) Lower renal, pulmonary, GI function
6) Lower muscle mass, increased fat
Sexual interest doe NOT decrease
Intelligence does NOT decrease
Presbycusis - sensorineural hearing loss (often of higher frequencies) due to destruction of hair cells at the cochlear base (preserved low frequency hearing at apex)
Common causes of death (U.S.) by age
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