Interpreting medical literature Flashcards

0
Q

Follow Up

A

Pick a group without outcome, watch their behavior over time and watch for outcome

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1
Q

Case Control Design

A

Case: has outcome, Control: does not have outcome

Ask both groups about their past factors, and compare accordingly

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2
Q

Cross-Sectional design

A

Start with a large population, ask about outcome and factors in the immediate past (“slice in time”)

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3
Q

Retrospective study AKA

A

Case-Control

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4
Q

Cohort AKA

A

Follow-Up

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5
Q

Prospective AKA

A

Follow-Up

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6
Q

Retrospective study timeframe

A

Begin and end in the present, watch the past

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7
Q

Prospective study timeframe

A

Begin in the present and march forward, collecting data about a population whose outcome lies in the future

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8
Q

Retrospective follow-up AKA

A

Historical prospective, retrospective cohort

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9
Q

Retrospective follow-up, defined

A

Behaves like a follow-up, but uses data carefully collected in the past. (think alcohol and BP example from book)

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10
Q

diagnostic bias

A

patients with symptoms for the condition are diagnosed because of the recognized factor

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11
Q

reporting bias

A

doctor more likely to report a condition if it is associated with the popular factor

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12
Q

subject bias

A

people with diseases tend to have a distorted view of past events

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13
Q

nested case-control

A

draw your cases from an already existing group participating in a long-term study, gives you data from the past and possibly lab samples

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14
Q

voluntary response bias

A

subjects who think they have been exposed to a toxin are more likely to return a mailed in questionnaire

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15
Q

ecologic study

A

using data on groups instead of individuals, ex: california cigarette sales vs heart disease prevalence

16
Q

surveillance bias

A

scrutinizing one group more than another, see infant abuse highlight

17
Q

Internally valid

A

Thin the confines of the study, results appear to be accurate, and the interpretation of the investigators is supported

18
Q

External validity

A

Do results generalize to the real world? Think of studies where a majority of subjects are excluded

19
Q

Convenience allocation

A

Put everyone on the north side of the room in group A

20
Q

validity in data collection

A

the degree to which a measurement reflects a true value

21
Q

reliability in data measurement

A

reproducibility of measurements

22
Q

social desirability bias

A

patients and subjects want to answer in a way they perceive to be “right”

23
Q

Hawthorne effect

A

subjects behave differently when they know they are being watched

24
Q

inference

A

generalization made about a large group based on data from a sample population

25
Q

type one error

A

rejecting a true null hypothesis

26
Q

type two error

A

accepting a false null hypothesis

27
Q

Sensitivity

A

Ability of a test to single out people who have the disease

28
Q

Specificity

A

Ability of a test to classify people who do not have the illness as negative

29
Q

Predictive value

A

Frequency with which a positive test actually signifies disease

30
Q

Efficiency

A

Overall ability of a test to classify patients correctly

31
Q

Likelihood ratio

A

Ratio of true positives to false positives