Module 1 Flashcards

1
Q

what does GATE stand for

A

Graphic Approach to epidemiology

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2
Q

PECOT

A

P - population of participants
E - exposure groups
C - comparison group
O - outcomes
T - time

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3
Q

CGO

A

Comparison group occurrence B/CG/t

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4
Q

EGO

A

exposure group occurrence A/EG/t

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5
Q

Features of a Cohort study

A
  • long-term follow-up
  • allocation by observation
  • time going down
  • common confounding
  • can measure incidents and prevalence
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6
Q

Incidence

A

Measure of the onset of a disease. e.g deaths, may be hard to measure

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7
Q

Prevalence

A

measure how much disease is in the population

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8
Q

What is an issue with measuring prevalence

A

That prevalence is a dirty measure as it has the cure and death rate involved with the calculation. not good for temporary events e.g asthma attack

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9
Q

What is one way to measure prevalence

A

Go back in time e.g during the past year have you xyz

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9
Q

RCT

A

Randomized control trial - best if ethical and practical

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10
Q

Why cannot do an RCT

A

if the intervention may be harmful, we cannot get people to do it as it may compromise health. only if the potential benefit to health.

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10
Q

How is an RCT conducted

A

By random allocation of individuals or groups

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10
Q

What is ethical around harmful exposures

A

It is not ethical to intervene but it is ethical to observe

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11
Q

Why are long term RCT hard to do

A

Many people do not remain in their groups long-term
Ethical errors
often hard to recruit pop that are representative

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12
Q

RD

A

EGO - CGO
It is the absolute difference
Has units

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13
Q

RR

A

EGO/CGO
No units
Relative difference

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14
Q

No Effect line RD

A

0

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15
Q

No Effect line RR

A

1

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16
Q

RRI

A

relative risk increase
If RR is over 1 can go RR/1 to get percentage increase

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17
Q

RRD

A

If RR less than 1. Can go 1-RR/1 to get percentage decrease

18
Q

Maintenance Error

A

Loss to follow up
Did they change groups

19
Q

Blind or Objective measures

A

Subjective vs Objective
Double Blind
How were outcomes measured

20
Q

Ecological studies

A

Allocation of populations to EG or CG
very common confounding
cheap to do
can be cross sect, cohort or RCT

21
Q

Cross Sectional

A

Measure done at one point in time
reverse causality
Cheaper
Measuring prevalence

22
Meta Analysis
Can combine multiple studies to one large study. increases sample size and decreases the random error
23
narrow definition of health
the absence of death, disease or disability
24
broad definition of health
the capacity to do what matters most to you
25
study validity
a study with only a small amount of random or non-random error is considered to be a valid study
26
recruitment error
are the participants a representative sample from a known population?
27
layers of the triangle
setting, eligible population, actual participants
28
confounding
when the exposure is mixed with another factor that is also associated with the outcome
29
stratified analysis
dividing the study into sub-studies (strata) so participants with the confounder are all in one sub-study
30
regression to the mean
repeating measurements or studies with extreme results multiple times usually gives less extreme results
31
random sampling errors
the smaller the sample, the greater the chance the sample will be different from the whole population
32
95% CI
there is about a 95% chance that the true value in a population lies within the 95% confidence interval
33
bradford hill criteria: [7]
- temporality - strength of association - reversibility - biological gradient (dose-response) - biological plausibility - consistency of association - specificity
34
temporality (BH)
- first the cause then the disease - essential to establish a causal relation
35
strength of association (BH)
the stronger the association, the more likely to be causal in absence of known biases
36
reversibility (BH)
the demonstration that under controlled conditions, a change in exposure results in a change in the outcome
37
biological gradient (BH)
incremental change in disease rates in conjunction with corresponding changes in exposure
38
biological plausibility of association (BH)
does the association make sense biologically?
39
consistency of association (BH)
replication of the findings by different investigators, at different times, in different places, with different methods
40
specificity of association
a cause leads to a single effect and an effect has a single cause
41
the epidemiological triad
host, environment and agent
42
a cause of a disease
an event, condition, characteristic (or combination of these factors) which play an essential role in producing the disease
43
sufficient cause
the whole pie a minimum set of conditions - without any one component disease would not occur
44
component cause
each factor/slice is a component cause
45
necessary cause
a factor (or component cause) that must be present for a specific dis-ease to occur
46
problems with the causal pie model
assumes all causes are deterministic and fails to capture dose-response relations as a continuum