(M) Validity of Epidemiologic Studies Flashcards

(45 cards)

1
Q

try to provide accurate answers to questions

A

Epidemiological studies

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2
Q

T or

Estimates ≠ Real Prevalence or Real Risk → Error

A

T

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3
Q

involves generating and testing hypothesis about factors that cause or prevent disease

A

Epidemiologic research

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4
Q

eliminate alternative explanations for his/her findings

A

major objective of every investigator who tests an etiologic hypothesis

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5
Q

one in which the observed association is not due to various sources of error (systematic and random errors)

A

valid study

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6
Q

from the poor design and/or conduct of the study
* Noncomparability of Groups
* Measurement Flaws

A

bias from systematic error

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7
Q

Underestimate or overestimate the true measure of association

A

bias from incorrect estimate of the measure of association

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8
Q

Results from procedures used to select subjects and factors that influence participation in the study

A

Selection Bias

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9
Q

Selection Bias

Groups being compared should be as similar as possible with respect to all other factors that may be related to the disease except the determinant under investigation

A

Principle in the Selection of Study Groups

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10
Q

Types of Selection Bias

A
  • Sampling Bias
  • Allocation Bias
  • Responder Bias
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11
Q

Systematically excluding or over-representing certain groups

A

Sampling Bias

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12
Q

E.g. A study to estimate the prevalence of smoking in a population, choosing a city center as location for study

A

Sampling Bias

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13
Q

Systematic differences in the way in which subjects are recruited into different groups for a study

A

Allocation Bias

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14
Q

E.g. A study may fail to do random sampling

First 20 patients who arrived at the clinic are allocated to a new treatment
Next 20 patients are allocated to an existing treatment
However, the patients who arrived early may be fitter or wealthier, OR alternatively the doctor may have asked to see the most seriously ill patients first

A

Allocation Bias

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15
Q

Missed responders or non-responders

A

Responder Bias

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16
Q

E.g. A study may send questionnaires to members of the control group. If these subjects are from a different social class to the cases, there may be differences in the proportion of responses that are received.

A

Responder Bias

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17
Q

AKA. measurement error, misclassification bias, observation bias

A

Information Bias

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18
Q

A flaw is measuring exposure or outcome variables that resultes in incorrect information between comparison group

A

Information Bias

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19
Q

Systematic differences in data collection, measurement or classification

A

Information Bias

20
Q

Types of information bias

A
  • Recall Bias
  • Social acceptability
  • Recording Bias
  • Interview Bias
  • Follow-up Bias
  • Misclassification Bias
21
Q

People suffering from a disease may have spent more time thinking of possible links between their past behavior and their disease than non-sufferers

22
Q

Cases may report more exposure to possible hazards

Common in case-control studies

23
Q

Some subjects may exaggerate or understate their responses, or deny that they engage in embarrassing or undesirable activities

Ex. cheating – they may deny this because it is not socially accepted

A

Social Acceptability Bias

24
Q

Medical records may contain more information on patients who are “cases”

A

Recording Bias

25
Interviewers may phrase questions differently for different subjects, or write down their own interpretations of what subjects have said | Question of phrasing is different from each group
Interviewer Bias
26
In studies that follow up at intervals, people from certain groups may tend to be lost to followup, or a disproportionate number of exposed subjects may be lost to follow-up compared with non-exposed subjects
Follow-up Bias
27
Patients may be systematically misclassified as either having disease or exposure
Misclassification Bias
28
E.g older people of lower social class may be less likely to express dissatisfaction with a health-related service
Some groups may give different responses
29
# T or F Investigators may look more closely at exposed patients, to try to find the presence of a disease, or they may be more attentive to certain types of subjects.
True
30
The mixing of effects between the exposure, The disease, and a third variable
Confounding
31
what is the third variable
Confounder
32
When present, the association between exposure and disease is distorted
The “third variable problem” | confounder
33
Have an effect on the independent variable, and have big effect on disease
The “third variable problem” | confounder
34
Occurs when a separate factor (or factors) influences the risk of developing a disease, other than the risk factor being studied.
Confounding (confounder)
35
the factor has to be related to the exposure, and it also has to be an independent risk factor for the disease being studied.
To be a confounder
36
common causes of confounding.
Age and Sex | wow naol
37
Confounding =
Spuriousness | (not genuine or authentic )
38
if u see this card
go over the example of confounding
39
# T or F Majority of study is PERFECTLY VALID
F - no study dumbass
40
fators that contributes to study why there is no perfectly valid
* Residual confounding * Unpredictable nature of chance * Complexity of bias
41
Eliminate Effect of Confounding in Studies
* Randomization * Matching * Stratified analysis
42
ensuring that samples are randomly selected
Randomization
43
In Case-Control study, controls are matched to cases at the start of the study according to particular characteristics which are known to be present in cases (e.g. age, sex, ethnic group, smoking, etc)
Matching
44
dividing subjects into groups at the analysis stage (e.g. by sex, age group, smoker/non-smoker) and analyzing on this basis.
Stratified Analysis
45
if u see this card
yey tapos kana | talon sa jeep