Epidemiology Flashcards

1
Q

Define Selection Bias

A

The most worried about

Deals with how the researcher selects or acquires study subjects

Creates a systematic difference in the composition between groups

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2
Q

Define Self-Selection/Participant/Responder bias

A

Those that wish to participate/volunteer may be different in some way to those that don’t volunteer or self-select to participate

i.e. clipboard at the mall example

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3
Q

Define Recall/Reporting bias

A

Something done by the study subject

A differential level of accuracy/detail in provided info. b/w study groups

i.e. exposed or diseased subjects may have greater sensitivity for recalling their history or amplify their responses (exaggerate)

“Hawthorne Effect” - Individuals can report their “effects” of exposure, disease symptoms or treatment differently bc they are apart of the study; want to please the experimenter

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4
Q

Define Compliance bias

A

Groups being interventionally studied have different compliances

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5
Q

Define cause (association & causality)

A

A precursor event/condition/characteristic required for the occurrence of the disease

Associations are relationships b/w an exposure and an outcome = artifactual, non-causal, causal

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6
Q

What are the 5 Hill’s Criteria for causality?

A
  1. Strength
  2. Consistency
  3. Temporality
  4. Biologic Gradient
  5. Plausibility

The greater criteria that are met, the more likely that an association may be causal

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7
Q

Delineate between cohort, case-control, and cross-sectional observational studies

A

Case-control = ALWAYS RETROSPECTIVE; based on the presence of disease (case) and no disease (control)

Cohort = Group allocation based on exposure; BOTH prospective and retrospective (unable to randomize, exposure is rare, etc.)

Cross-sectional = NATIONAL; snapshot in time; quick and easy

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8
Q

What is the primary difference between simple and factorial study designs?

A

Simple contains only ONE act of randomization

In factorial you are testing multiple hypothesis at same time

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9
Q

What is the primary difference between parallel and cross-over study designs?

A

Parallel contains no switching of groups after the initial randomization

Cross-over contains switching between and within groups (such as wash-outs) after randomization

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10
Q

List the 3 forms of randomization

A
  1. Simple - ensures an equal probability during allocation within one of the study groups
  2. Blocked - ensures an equal # within each interventional group; researcher doesn’t know
  3. Stratified - ensures a balance within the known confounding variables; i.e. want population characteristics to be equal (race, gender, etc.)
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11
Q

What are the 3 ways in which researchers can handle lost to followups or drop outs?

A
  1. Include them anyway = INTENT TO TREAT
  2. Ignore them = PER-PROTOCOL/EFFICACY ANALYSIS; pre-defined compliance
  3. AS-TREATED; ignores group assignments
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12
Q

Benefits of intent to treat?

A

Most conservative decision; convert all subsequent yet missed assessments for a subject to a null-effect

Preserves randomization process, preserves baseline characteristics, maintains statistical power/original sample size

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13
Q

Benefits/Disadvantages of treating subjects as per-protocol in studies?

A

Biases estimates of effect

Reduces generalizability

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14
Q

What is the purpose of case-control studies and when might you use them?

A

(Observational)

Always RETROSPECTIVE

Dependent on disease status

Used when disease is rare, testing for multiple exposures compared to one outcome, time and cost effective, ethical issues and cannot use interventional study (randomize)

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15
Q

What is the purpose of cohort studies and when might you use them?

A

(Observational)

Studies done based on exposure and commonalities

Used for RARE EXPOSURES, can determine the risk ratio as a measure of association, when you cannot randomize

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16
Q

What is the purpose of cross-sectional studies and when might you use them?

A

(Observational)

Large population studies = SNAPSHOT in time; collects data simultaneously and seeks associations and generates and tests hypothesis

NATIONAL

17
Q

Define sensitivity; what is the calculation?

A

How well a test can detect disease presence when the disease is actually present; no prediction

A highly sensitive test can have a low false negative rate

Sensitivity = TP / (TP + FN;all disease) x 100%
S = A / A+C
18
Q

Define specificity; what is the calculation?

A

How well a test can detect the ABSENCE of disease when the disease is actually absent; no prediction

A highly specific test has a low false positive rate

Specificity = TN / (TN + FP) x 100%
Sp = B / B+D
19
Q

Define positive predictive value (PPV); what is the calculation?

A

How accurately a positive test PREDICTS the presence of disease

PPV = TP / (TP + FP) x 100%
ppv = TP / (all positive tests) x 100%
20
Q

Define negative predictive value (NPV); what is the calculation?

A

How accurately a negative test PREDICTS the absence of disease

NPV = TN / (TN + FN) x 100%
npv = TN / (all negative tests) x 100%
21
Q

Define diagnostic accuracy; what is the calculation?

A

Proportion of time that a patient is correctly identified as either having a disease or not having a disease with a positive or negative test.

DA = (TP + TN) / (TP+TN+FP+FN) x 100%
DA = (TP + TN) / (all patients) x 100%
= (A + D) / (A+B+C+D)

22
Q

What type of studies are CONSORT checklist is used for?

A

Interventional studies

23
Q

What type of studies are strOBe checklists used for?

A

Observational studies

24
Q

Nominal data characteristics

A

Dichotomous/Binary

No magnitude; No consistency of scale; No order

i.e. gender, hair color, eye color, chocolate preference, Low BP/High BP

25
Q

Ordinal data characteristics

A

Ranked; Non-equal distance

MAGNITUDE; No order

i.e. Normal BP, Hypertension, Chronic hypertension

26
Q

Interval data characteristics

A

ORDER AND MAGNITUDE

Continuous

i.e. BP 150/100 - 135/90; 134/89 - 120/80; 119/78 - 110/70