Chapter 7 Flashcards

1
Q

observational research

A

naturally occurring variation observed to identify patterns and associations
natural history od disease

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2
Q

type of observational study

A
case series 
ecological
surveys and cross sectional 
case control 
cohort 
qualitative
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3
Q

experimental research

A

investigator controls 1 factor and measures variation in outcome
clinical trials
impact of preventative vaccines or behaviour change programs

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4
Q

type of experimental research

A

RCT
cluster RCT
cross over trials
factorial trials

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5
Q

modelling and stimulation research

A

development of theories
validity dependant on data used to set up model parameters
study disease transmission and empirical data

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6
Q

hierarchy of evidence

A
Systematic review and meta-analysis of trials.
• RCTs.
• Cohort studies.
• Case–control studies.
• Ecological studies.
• Cross-sectional studies.
• Case reports and case series.
• Expert opinion.
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7
Q

exposure

A

describe something that might affect an outcome
explanatory or independent variables
exposure of interest -= one in the hypothesis

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8
Q

outcome

A

response or dependant variables

can have more than 1 outcome per study

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9
Q

confoiunder

A

independantkly associated with the exposure and outcome of the study
can lead to bias
explanatory or independent variables

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10
Q

bias

A

deviation from the truth that occurs in studies

systematic error is different from random error - increasing the sample size can reduce random error but not bias

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11
Q

selection bias

A

recruit participants based on characteristic linked to exposure and outcome
occurs in allocation to intervention
non-responders different to responders - healthy participant effect

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12
Q

measurement bias

A

systematic errors in measurement including errors in allocation to different groups
systematically wrong - recall bias in case control

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13
Q

association

A

statistical dependence between 2 variables - indicates the degress to which the outcome is different in those with(out) exposure

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14
Q

chance

A

inference from samples
repeat in different sample and results would be different
use CI to determine likelihood of chance being a factor

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15
Q

observer bias

A

RCT

researxher aware of the treatment that the person is getting

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16
Q

information bias

A

difference in the way that the information is collected and so different qualities between groups of the study

17
Q

non-differential misclassification

A

chance of misclassification is the same regardless of the disease status/exposure
random misclassification
bias association towards null - masks true differences

18
Q

differential misclassification

A

probability of exposure being misclassified depends on the disease status/vice versa
can bias estimates in either direction

19
Q

confounding

A

false association because it distorts the observed association

20
Q

randomisation

A

adjust for confounding at the design stage

distribution of confounding factors should be the same in both groups

21
Q

matching

A

case control

select cases and controls so match on confounding factors

22
Q

adjusting for confounding at analysis stage

A

stratification
standardisation
multiple regression

23
Q

association/causation

A

exclude chance bias and confounding = true association - doesn’t necessarily mean causal

24
Q

Bradford hill criteria

A
strength of association
consistency of association 
specificity of association 
temporal sequence of association 
dose response relationship 
biological plausibility of association 
coherence 
reversibility 
analogy
25
strength
measured by RR | stronger = more likely causal
26
consistency
repeated demonstration in different populations and study designs
27
specificity
1:1 relationship between cause and outcome
28
temporal
risk factor before outcome
29
dose response
gradient of risk
30
plausibility
known biological mechanism
31
coherence
absence of conflict with other knowledge about the natural history and disease
32
reversibility
remove the risk factor prevent the outcome
33
analogy
analogy with other similar causal associations
34
causality and public health
absolute proof rarely attainable in empirical sciences
35
how important are causal relationships
knowledge of causal mechanism not essential for effective preventative strategies