BEHAVIORAL SCIENCE Flashcards
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
WHat does incincidence look at?
NEW CASES (INCIDENTS)
Prevalance formulas
Prevalence =
# of existing cases
__________________
Population at risk
Prevalence ≈ incidence rate × average disease duration.
What does prevalance look at?
Prevalence looks at all current cases.
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 = ad / bc
Relative Risk (RR)
The proportion of risk reduction attributable to the intervention as compared to a control. RRR = 1 – RR (e.g., if 2% of patients who receive a flu shot develop flu, while 8% of unvaccinated patients develop the flu, then RR = 2/8 = 0.25, and RRR = 1 – RR = 0.75).
Attributable Risk (AR)
The difference in risk between exposed and unexposed groups, or the proportion of disease occurrences that are attributable to the exposure
(e.g., if risk of lung cancer in smokers is 21% and risk in nonsmokers is 1%, then 20% (or .20) of the 21% risk of lung cancer in smokers is attributable to smoking).
AR Formula
AR = a/(a+b) - c/(c+d)
Absolute risk reduction (ARR)
The difference in risk (not the proportion) attributable to the intervention as compared to a control
(e.g., if 8% of people who receive a placebo vaccine develop flu vs. 2% of people who receive a flu vaccine, then ARR = 8% - 2% = 6% = .06).
(Risk factor +, Disease + = a)
(Risk factor +, Disease - = b)
(Risk factor - , Disease + = c)
(Risk factor -, Disease + = d)
needed to treat and how to calculae
Number of patients who need to be treated for 1 patient to benefit.
Calculated as 1/ARR.
Needed top harm and how to calculate
Number of patients who need to be exposed to a risk factor for 1 patient to be harmed.
Calculated as 1/AR.
Precision vs. Accuracy
Precision: The consistency and reproducibility of a test (reliability).
The absence of random variation in a test.
(more precision –> less standard deviation)
Accuracy: The trueness of test measurements (validity).
The absence of systematic error or bias in a test.
What reduces precision in a test?
Random error
What reduces accuracy in a test?
Systemic error
Selection bias: What is it? Examples? Strategy to reduce bias?
Nonrandom assignment to participate in a study group. Most commonly a sampling bias.
Examples include:
Berkson bias
A study looking only at inpatients
Loss to follow-up
Studying a disease with early mortality
Healthy worker and volunteer biases
Study populations are healthier than the general population
Reduce bias by:
Randomization
Ensure the choice of the right comparison/reference group
Recall Bias: What is it? Examples? How to reduce?
Awareness of disorder alters recall by subjects; common in retrospective studies.
Ex: Patients with disease recall exposure after learning of similar cases
Reduce by: Decrease time from exposure to follow-up
Measurement bias? What is it? Ex? Reduce by?
Information is gathered in a way that distorts it.
Ex: Hawthorne effect — groups who know they’re being studied behave differently than they would otherwise
Reduce by:Use of placebo control groups with blinding to reduce influence of participants and researchers on experimental procedures and interpretation of outcomes
Procedure bias…
Subjects in different groups are not treated the same.
Ex:Patients in treatment group spend more time in highly specialized hospital units
Reduce by:Use of placebo control groups with blinding to reduce influence of participants and researchers on experimental procedures and interpretation of outcomes
Observer-expectancy bias…
Researcher’s belief in the efficacy of a treatment changes the outcome of that treatment (aka Pygmalion effect; self-fulfilling prophecy).
Ex: If observer expects treatment group to show signs of recovery, then he is more likely to document positive outcomes
Reduce by:Use of placebo control groups with blinding to reduce influence of participants and researchers on experimental procedures and interpretation of outcomes
Confounding bias
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.
Ex: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 by: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
Early detection is confused with survival; seen with improved screening techniques.
Ex:Early detection makes it seem as though survival has increased, but the natural history of the disease has not changed
Reduce by: Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)
Mean
(sum of values)/(total number of values).
Median
middle value of a list of data sorted from least to greatest.
If there is an even number of values, the median will be the average of the middle two values
Mode
most common value.
Standard deviation
how much variability exists from the mean in a set of values.
σ = SD; n = sample size.
Standard error of the mean
= an estimation of how much variability exists between the sample mean and the true population mean
SEM = σ/√n.
SEM decreases as n increases.
Gaussian
bellhaped = normal distribution
mean=median=mode
Bimodal
nonnormal distribution
Suggests two different populations (e.g., metabolic polymorphism such as fast vs. slow acetylators; suicide rate by age).
Positive skew
Typically, mean > median > mode. Asymmetry with longer tail on right.
Negative skew
Typically, mean < median < mode. Asymmetry with longer tail on left.
Null (H0)
Hypothesis of no difference (e.g., there is no association between the disease and the risk factor in the population).
Alternative (H1)
Hypothesis of some difference (e.g., there is some association between the disease and the risk factor in the population).
Correct result of statistical hypothesis testing
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 - alfa = false - positive error
Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis).
α is the probability of making a type I error. p is judged against a preset α level of significance (usually < .05). If p < 0.05, then there is less than a 5% chance that the data will show something that is not really there.
α = you saw a difference that did not exist (e.g., convicting an innocent man).
Type II error - beta = false negative error
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 the probability of making a type II error.
b is related to statistical power (1 – b), which is the probability of rejecting the null hypothesis when it is false.
b = you were blind to a difference that did exist (e.g., setting a guilty man free). If you sample size, you power. There is power in numbers.
how to increase power and decrease (b-beta)
increase sample size (power in numbers)
increase expected effect size
increase precision of measurement
Meta-analysis
How is it limited?
Pools data and integrates results from several similar studies to reach an overall conclusion.
Limited by quality of individual studies or bias in study selection.
Confidence interval
Range of values in which a specified probability of the means of repeated samples would be expected to fall.
CI = range from [mean – Z(SEM)] to [mean + Z(SEM)]
.
CI values
The 95% CI (corresponding to p = .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
significant difference exists.
If the CIs between 2 groups overlap
usually no significant difference exists.
t-test
Checks differences between means of 2 groups
ANOVA
Checks differences between means of 3 or more groups
Chi-square
Checks difference between 2 or more percentages or proportions of categorical outcomes (not mean values).
Pearson correlation coefficient (r)
r is always between -1 and +1.
The closer the absolute value of r is to 1, the stronger the linear correlation between the 2 variables.
Positive r value positive correlation.
Negative r value negative correlation.
Coefficient of determination = r 2 (SQUARED = value that is usually reported).
Primary disease prevention
Prevent disease occurrence (e.g., HPV vaccination).
Secondary disease prevention
Screening early for disease (e.g., Pap smear)
Tertiary disease prevention
Screening early for disease (e.g., Pap smear)
Medicare vs. Medicaid
Medicare and Medicaid—federal programs that originated from amendments to the Social Security Act.
MedicarE (Elderly) is available to patients ≥ 65 years old, < 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.
Quaternary disease prevention
identifying patients at risk of unnecessary treatment, protecting from the harm of new interventions
What are the core ethical principles
Respect patient autonomy
Beneficence(over autonomy+ society)
Nonmaleficence (Do no harm)
Justice
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 (≥ 7 = good; 4–6 = assist and stimulate; < 4 = resuscitate). If Apgar score remains < 4 at later time points, there is an increased risk that the child will develop long-term neurological damage.
Low birth weight
definition, causes, associations, and complications
Defined as < 2500 g.
Caused by prematurity or intrauterine growth retardation (IUGR).
Associated with risk of SIDS, and with overall mortality. Other problems include impaired thermoregulation and immune function, hypoglycemia, polycythemia, and impaired neurocognitive/emotional development.
Complications include infections, respiratory distress syndrome, necrotizing enterocolitis, intraventricular hemorrhage, and persistent fetal circulation.
informed consent legally reuires what?
Disclosure: discussion of pertinent information
Understanding: ability to comprehend (assess)
Mental capacity: unless incompetent (a legal determination)
Voluntariness: freedom from coercion and manipulation
Exceptions to informed consen
Patient lacks decision-making capacity or is legally incompetent
Implied consent in an emergency
Therapeutic privilege—withholding information when disclosure would severely harm the patient or undermine informed decision-making capacity
Waiver—patient explicitly waives the right of informed consent
Situations in which parental consent is no required
parents can’t stop kids from getting treatment for:
Sex (contraception, STDs, pregnancy)
Drugs (addiction)
Rock and roll (emergency/trauma)
Components of decision making
Patient is ≥ 18 years old or otherwise legally emancipated
Patient makes and communicates a choice
Patient is informed (knows and understands)
Decision remains stable over time
Decision is consistent with patient’s values and goals, not clouded by a mood disorder
Decision is not a result of delusions or hallucinations
What are advance direcives and types?
Instructions given by a patient in anticipation of the need for a medical decision.
Oral advance directive Living will (written advance diretive)
Medical power of attorny
Priority on surrogate decision makers?
spouse, adult children, parents, adult siblings, other relatives.
Exceotions to confidentiality and examples
Potential physical harm to others is serious and imminent
Likelihood of harm to self is great
No alternative means exists to warn or to protect those at risk
Physicians can take steps to prevent harm
Reportable diseases (e.g., STDs, TB, hepatitis, food poisoning)—physicians may have a duty to warn public officials, who will then notify people at risk
The Tarasoff decision—California Supreme Court decision requiring physician to directly inform and protect potential victim from harm
Child and/or elder abuse
Impaired automobile drivers (e.g., epileptics)
Suicidal/homicidal patients
Infant 0-12mo milestones
Motor,
“Parents Start Observing”
Primitive reflexes disappear— Moro (by 3 mo), rooting (by 4 mo), palmar (by 6 mo), Babinski (by 12 mo)
Posture—lifts head up prone (by 1 mo), rolls and sits (by 6 mo), crawls (by 8 mo), stands (by 10 mo), walks (by 12–18 mo)
Picks—passes toys hand to hand (by 6 mo), Pincer grasp (by 10 mo)
Points to objects (by 12 mo)
infant social milesetones
Social smile (by 2 mo)
Stranger anxiety (by 6 mo)
Separation anxiety (by 9 mo)
infant verbal/cognitive milestones
Orients—first to voice (by 4 mo), then to name and gestures (by 9 mo)
Object permanence (by 9 mo)
Oratory—says “mama” and “dada” (by 10 mo)
Toddler (12-36months)
Motor milestones
“Child Rearing Working”
Climbs stairs (by 18 mo)
Cubes stacked—number = age (yr) × 3
Cultured—feeds self with fork and spoon (by 20 mo)
Kicks ball (by 24 mo)
Toddler Social milestones
Recreation—parallel play (by 12 mo)
Rapprochement—moves away from and returns to mother (by 24 mo)
Realization—core gender identity formed (by 36 mo)
Toddler Verbal milesones
Words—200 words by age 2 (2 zeros), 2-word sentences
Preschool (3-5yr) Moor milestones
“Dont Forget theyre still Learning”
Drive—tricycle (3 wheels at 3 yr)
Drawings—copies line or circle, stick figure (by 4 yr)
Dexterity—hops on one foot (by 4 yr), uses buttons or zippers, grooms self (by 5 yr)
Preschool Social milesones
Freedom—comfortably spends part of day away from mother (by 3 yr)
Friends—cooperative play, has imaginary friends (by 4 yr)
Preschool Verbal Milestones
Language—1000 words by age 3 (3 zeroes), uses complete sentences and prepositions (by 4 yr)
Legends—can tell detailed stories (by 4 yr
What are the changes in elderly?
Sexual changes:
Men—slower erection/ejaculation, longer refractory period
Women—vaginal shortening, thinning, and dryness
Sleep patterns:
decreased REM ;
increased sleep onset latency and increased early awakenings
increased suicide rate, fat
decreased vision, hearing, immune response, bladder control renal, pulmonary, GI function muscle mass,
Presbycusis
high-frequency hearing loss due to destruction of hair cells at the cochlear base (preserved low-frequency hearing at apex).
