BIOL 437 Week Ten p.2 (Causality) Flashcards
1
Q
direct causal association
A
- no intermediate factor
- more obvious
- elminating exposure will eliminate the adverse health outcome
ex. a trauma to the skin
2
Q
indirect causal association
A
- involves one or more intervening factors
- often more complicated
ex. poor diet and stress may cause high BP, which can cause heart disease
3
Q
factors of causation
A
- predisposing factors
- enabling factors
- precipitating factors
- reinforcing factors
4
Q
predisposing factors
A
- factors already present that produce a susceptibility or diposition in the host to a disease or condition without actually causing it
ex. age, immune status, knowledge, beleifs
5
Q
reinforcing factors
A
-help aggravate and perpetuate behaviours, disease, conditions, disability or death
6
Q
positive reinforcing factors
A
- social support
- health education
- economic assistance
7
Q
negative reinforcing factors
A
- negative peer influence
- poor economic conditions
8
Q
enabling factors
A
- antecedants to behaviours, disease, conditions, disability or death
ex. services, living conditions, programs - can also be a result of lack of services or medical programs
9
Q
precipitating factors
A
- essential to the development of diseases, conditions, injuries, disabilities and death
ex. infectious agent, lack of seat belt use, drinnking and driving, lack of helmet
10
Q
evidence for causal relationship (Henle and Koch postulates)
A
- Organisms is always found with the disease
- Organism is not found in those without the disease
- Organism when isolated from one who has the disease and is cultured, produces the disease
11
Q
direct observation
A
-lot of knowledge gained in this manner
12
Q
inference
A
-essential to scientific acitivty
>not everything can be observed
13
Q
latency
A
ex. long period between exposure to cigarettes and onset of lung cancer
14
Q
induction
A
Example:
- 2-week long induction period of measles and its infectiousness: barrier to understanding transmission
- confoudned seasonality link
15
Q
Test of operational hypothesis
A
- design study and collect data
- analyze data and make conclusions about study hypothesis
- modify hypotheses if needed
16
Q
type 1 error
A
-when hypotheis is rejected but is actually true
17
Q
type 2 error
A
-when hypothesis is not rejected but is actually false
18
Q
falsification of a hypothesis (Karl popper)
A
-more informative than corroboration of a hypothesis
>a single counter example forces modification
>studies should attempt to refute rather than confirm hypothesis
-problematic in epidemiology
19
Q
Karl Popper falsification process
A
- requres a large body of knowledge
- negative result often cannot refute orignail hypothesis due to many sources of bias that can mask underlying associations
- makes it hard to refute an epidemiolgoical hypothesis which limitis the application of Popper’s model
20
Q
common sense
A
- alternative model of scientific progress
- judgement under uncertainty that characterizes human experts and computer-based expert systems
- a blatant violation of of logic theory but is often how we actually operate
21
Q
what is causal inference?
A
- a conclusion about the presence of a health-realted event and reasons for its existence
- provide scientific basis for medical and public health action
- made with methods comprising lists of criteria applied to the results of scientific studies
22
Q
what is statistical inference?
A
- draws a conclusion about a population based on information from sampled data
- probability is used to indicate level of reliability
- possibility that chance, bias or confounding explain a statistical association should always be considered
23
Q
statistical inference
A
-used in evaluating the data for use in causal inference
24
Q
possilbe non-causal reasons for an association
A
- characteristic of study group
- problems with measuring disease or exposure
- another factor affecting disease and putative cause
25
causal inference overall
-attempt to eliminate all possible non-causal reasons for an observed association
26
causal inference is a reasoning process based on
- what is believed to be true
- the previaling concepts of disease
- knowledge at the time
- erroneous and potentially ignorant beleifs
27
Viral diseases
-do not follow Koch's postulates
1. disease production may need co-factors
2. Cannot be cultured as they need living cells to grow
3. Pathogenic virusus can be prsent without clinical disease
>subclinical infections, carrier states
28
true association?
-if controls have been selected in a mannor that favours non-exposure then the association of exposure to disease may be false, due to study design alone
29
if it is real, is it causal?
-is there a confounding factor that links the exposure to the disease?
>YES=then it is not a causal association
30
3 methods of hypthesis formulation in disease etiology
- method of difference
- method of agreement
- method of concomitant variation
31
method of difference
-frequency of disease occurence is extremely different under different situations or conditions
-if a risk factor can be identified in one condition and not in a second, it may be that factor
>or the absence of it that causes the disease
32
method of agreement
- if risk factors are common to a variety of different circumstances
- risk factors have been positively associated with a disease
* probability of that factor being the cause is extremely high
33
method of concomitant variation
-the frequency or strength of risk factor varies with the frequency of the disease or condition
>increased numbers of children not immunized causes the incidence rate to go up (Ex. measles)
34
strength of association
- excess of disease associated with exposure
| - magnitude of ratio of incidence in exposed to incidence in the unexposed
35
consistency
-assocation has been repeatedly observed:
>by different people
>in different places
>in different circumstances
>at different times
-guards against associations due to error or artifact
-not necessarily free of bias
36
specificity
- relationship between exposure and disease is specific in various ways
- specific types of exposures are more effective
- one agent can still contribute to multiple diseases
37
temporality
-first expsoure, then disease
-not always possibile to document sequence
>long lag periods
>subclinical disease
38
biological gradient
- dose-response relationship consistent with the hypothesized conceptual model
- incremental change is disease rates in conjunction with corresponding changes in exposure
- consider threshold and saturation effects
39
plausibility
- does it make biological sense?
| - common sense
40
coherence
- does it fit with known facts
| - include knowlege about distributions of exposure and disease and lab experiment results
41
experimental evidence
-some designs give more convincing evidence
-intervention studies can give the strongest support
-demonstrating under controlled conditions that changing the exposure causes a change in the outcome
>not always possible though, especially when dealing with humans
42
analogy
-accept causal inferences that resemble others already accepted
43
the role of chance
-characteritics of subjects may vary from sample to sample
>as a result, an association between an exposure and outcome may be from chance
-sample size directly related to chance
-increase sample size to decrease chance
44
web of causation
-complex sets of events or conditions caused by many activiites connected to a common core or experince or event
45
search for cause vs decision-making
- all scientific work is incomplete wheter it is observational or experimental
- sometimes we have to work with what we know in the moment
