Interpreting medical literature Flashcards
(32 cards)
Follow Up
Pick a group without outcome, watch their behavior over time and watch for outcome
Case Control Design
Case: has outcome, Control: does not have outcome
Ask both groups about their past factors, and compare accordingly
Cross-Sectional design
Start with a large population, ask about outcome and factors in the immediate past (“slice in time”)
Retrospective study AKA
Case-Control
Cohort AKA
Follow-Up
Prospective AKA
Follow-Up
Retrospective study timeframe
Begin and end in the present, watch the past
Prospective study timeframe
Begin in the present and march forward, collecting data about a population whose outcome lies in the future
Retrospective follow-up AKA
Historical prospective, retrospective cohort
Retrospective follow-up, defined
Behaves like a follow-up, but uses data carefully collected in the past. (think alcohol and BP example from book)
diagnostic bias
patients with symptoms for the condition are diagnosed because of the recognized factor
reporting bias
doctor more likely to report a condition if it is associated with the popular factor
subject bias
people with diseases tend to have a distorted view of past events
nested case-control
draw your cases from an already existing group participating in a long-term study, gives you data from the past and possibly lab samples
voluntary response bias
subjects who think they have been exposed to a toxin are more likely to return a mailed in questionnaire
ecologic study
using data on groups instead of individuals, ex: california cigarette sales vs heart disease prevalence
surveillance bias
scrutinizing one group more than another, see infant abuse highlight
Internally valid
Thin the confines of the study, results appear to be accurate, and the interpretation of the investigators is supported
External validity
Do results generalize to the real world? Think of studies where a majority of subjects are excluded
Convenience allocation
Put everyone on the north side of the room in group A
validity in data collection
the degree to which a measurement reflects a true value
reliability in data measurement
reproducibility of measurements
social desirability bias
patients and subjects want to answer in a way they perceive to be “right”
Hawthorne effect
subjects behave differently when they know they are being watched