Biomedical model vs. Biobehavioral model Biomedical model: idea that disease is caused by biology->germs, bacteria, etc.
Biobehavorial model: recognizes biological, psychological, and sociocultural forces in determining an individual's health and vulnerability to disease (ex. Framingham Heart S...
BBH 101 Final Exam Questions and
Correct Answers
Biomedical model vs. Biobehavioral model ✅Biomedical model: idea that disease is
caused by biology->germs, bacteria, etc.
Biobehavorial model: recognizes biological, psychological, and sociocultural forces in
determining an individual's health and vulnerability to disease (ex. Framingham Heart
Study)
Hypotheses vs. Theories ✅Hypotheses: educated guess, speculating
Theories: comprehensive explanation; tested over and over; more confident
P-value ✅-tells us what the probability is of obtaining our result if there really is no
relationship between the variables we are interested in
-a p-value of <0.05 is generally accepted as a significant figure
-correct interpretation of p-value of 0.03: there is approximately a 3% chance that
observed
-the lower the p-value the more likely it will be valid
Observational study ✅-independent variable not manipulated by experimenter, but still
is different between groups
-ex. one group smokes and the other does not
-sometimes it is unethical to conduct an experimental study
-find subjects that are already exposed
Prevalence ✅-how frequently something occurs, the current number of cases of
something
Incidence ✅-number of new cases
Case Study/ Case Series ✅-clinical description of a single patient
-usually describes an unusual feature or association between disease and some
exposure factor
-a case series can be valuable as an early indicator of disease or other health problems
-low explanatory capabilities- can't examine cause and effect
-case series is a collection of case studies
--involves a group of patients with similar characteristics
Cross-sectional Studies ✅-takes a "point-in-time" picture of health, health behaviors,
other exposure factors, etc.
, -there is no follow-up, measures are only taken once
-low explanatory capabilities-can't examine cause and effect
--describes population prevalence-> how many at a time
-can give an estimate of prevalence
-can use CORRELATION as a measure
--provides a measure of the relationship between 2 variables
---correlation coefficient (r) can indicate strength (ranges from 0-no relationship- to 1.00
or -1.00 -perfect correlation)
---and direction (if positive, as x inc, y inc- if negative, as x inc, y dec)
Case-control studies ✅-retrospective study
-people with outcome (cases) and without the outcome (controls) are selected
-research is done to see how many people in each group had exposure to some
variable of interest (cannot state whether something causes something else)
-the question to the answer is if a greater proportion of people in the case group
(compared to the control) were exposed to the independent variable
-measure often used is called the odds ratio, and it tells us how much more likely people
with exposure are to have the outcome, compared to people without the exposure
--higher the number, the greater the risk
Cohort studies ✅-prospective study
-people with certain exposure and without the exposure are selected, then followed for a
specific period of time to see if they develop the outcome of interest
-the question to answer is if a greater proportion of people with the exposure develop
the outcome than people without the exposure
-the measure often used is called relative risk or the risk ratio. It tells us how much
higher the risk of the outcome is in the exposed group compared to the unexposed
group.
--it is interpreted in a very similar way as odds ratio
-give us an estimate of incidence
-HIGHER explanatory capabilities-can examine cause and effect
--still generally need more evidence to verify a causal relationship
-start-> nobody has the outcome, 1/2 have had exposure
Experimental designs ✅-when designed properly, the gold standard for identifying
causal relationships
-experiment group vs. control group
-other than the intervention, the experimental and control group should be as similar as
possible!
--ways to make the groups similar include:
--random assignment
--blinding
--good placebo
Random assignment (completely) ✅-involves using a truly random method of
assigning participants to groups
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