EAB Flashcards

1
Q

How do you calculate incidence rate?

A

total no of new cases in given period/total population at risk

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2
Q

How do you calculate prevalence rate?

A

all new and exisiting cases/total population

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3
Q

How do you calculate attributable risk?

A

(incidence exposed - incidence unexposed to risk) / incidence

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4
Q

What are the main concerns of experimental study designs?

A

unethical and feasability

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5
Q

What are the main concerns of observational study designs?

A

confounding bias, selection bias and measurement errors

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6
Q

What are examples of selection bias?

A

self-selection, attrition, non-response

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7
Q

What are examples of information bias?

A

false positives/negatives,, reporting bias, error or omission of details

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8
Q

What is intention to treat?

A

in RCTs, always do analysis with patients in their original groups
- even if switched treatments or drop out

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9
Q

What are the features of case control studies?

A
  • observational

- retrospective

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10
Q

What are the pros and cons of case control studies?

A

Pros: quick, inexpensive
Cons: usually biased or data is incomplete

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11
Q

What are the features of cohort studies?

A
  • observational
  • moniters healthy indviduals over time for disease risk/rates
  • prospective
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12
Q

What are the pros and cons of cohort studies?

A

Pros: less bias than case control
Cons: long follow up, need large groups

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13
Q

What are the features of cross-sectional studies?

A
  • observational
  • data is collected at 1 point in time
  • useful for frequencies and attitudes
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14
Q

What are the 2 types of quantitative data?

A

continuous or discrete

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15
Q

What is dichotomous or binary data?

A

categorical data with only 2 categories

e.g. gender

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16
Q

What is categorical data with more than 2 categories?

A

Ordered/nominal - e.g. stages of cancer

Unordered - e.g. marital status

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17
Q

How is variance determined?

A

SD^2

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18
Q

How is standard deviation measured?

A

(value-mean)^2

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19
Q

What type of skew is normally seen in medicine?

A

positive skew (tail on right hand side)

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20
Q

What does normal distribution mean?

A
  • bell shaped curve
  • 95% of data lies within 2SD of mean
  • 68% of data lies within 1SD of mean
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21
Q

what does the confidence interval indicate?

A

range within the true mean is likely to lie

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22
Q

What is sampling error?

A

different samples will give different estimates of the mean

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23
Q

What does standard error indicate?

A

the extent of sampling error

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24
Q

How do you calculate sampling error?

A

SE = SD/√N

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25
Q

What does a 95% confidence interval mean?

A

that the true mean is expected to like within 1.96 SE of the estimated mean in 95% of calculation

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26
Q

What are the assumptions when calculating confidence intervals?

A
  • normal data
  • large population
  • randomly chosen samples
  • observations are independent of each other
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27
Q

What is the difference between statistical and clinical significance?

A

Statistical means that P<0.05 - i.e likely to be true difference
Clinically means that the difference is large enough to have a clinical impact

28
Q

What does a t test assess?

A

if there is a difference in means of 2 difference samples

29
Q

What is the difference between a paired and unpaired t-test?

A
paired = data is matched e.g. BP before and after treatment
unpaired = different samples e.g. mean height in boys and girls
30
Q

How is the t test calculated?

A

mean difference/SE

31
Q

What are the assumptions of a t test?

A
  • quantitative data
  • normally distributed
  • equal variances
  • randomly selected samples
  • observations are independent
32
Q

What does the Chi-squared test assess?

A

association between categorical variables

33
Q

How is degrees of freedom calculated in chi-square tests?

A

(no. of rows - 1 ) x (no. of columns - 1)

34
Q

What does the Chi-squared test calculate?

A

compares expected frequencies for no association against observed frequencies
- large difference indicates and an association

35
Q

What are the assumptions of the Chi-squared test?

A

large sample
use of frequencies (not percentage)
80% of expected frequencies are >5

36
Q

How do population pyramids differ for high and low income countries?

A

Low-income have high birth and death rates - lower percentage of older age groups

High income have more rectangular shapes with more elderly

37
Q

What is demographic transition:

A

Concept for population growth:

  • low income countries have high birth and death rates
  • in development, get initial reduction in death rates -> rapid growth
  • Birth rate will later decrease, giving stable population with lower birth:death rate equilibrium
38
Q

How often is the census conducted?

A

every 10 years

39
Q

How are areas divided up in census?

A

enumeration districts

40
Q

What groups are considered hard to reach?

A

disabled, elderly, students, migrants/non-english speakers, travellers

41
Q

What measures estimate populations inbetween censuses?

A

population estimates annually - cohort component method

population projections every 2 years

42
Q

What are the indicies of multiple deprivation (IMD)?

A
  • income
  • employment
  • health and disability
  • education, skills and training
  • barriers to housing and services
  • living environment
  • crime
43
Q

What are super-output areas?

A

areas divided to calculate the level of deprivation using IMD

44
Q

What is avoidable mortality?

A

deaths from causes that are considered avoidable with effective healthcare/public health

45
Q

What is the bradford-hill criteria?

A

the minimum conditions a study needs to provide adequate evidence of a causal relationship

46
Q

What are the components of the bradford-hill criteria?

A
  1. strength of association
  2. consistency
  3. specificity
  4. temporality
  5. dose-response relationship
  6. biological plausability
  7. coherence
  8. experimental evidence
  9. analogy
47
Q

What types of assoctions are case control studies good for?

A

rare outcomes and multiple risk factors

48
Q

What is non-response bias?

A

people who are more likely to respond are more likely e.g. to go for a test/check up

49
Q

What is recall bias?

A

cases remember exposure differently than controls

50
Q

what is an example diagnostic bias?

A

contraceptive pill use makes detection of uterine cancer more likely

51
Q

What is interviewer bias?

A

cases and controls are asked about exposure differently

52
Q

What is confounding?

A

there is an alternative factor that is contributing to/causing the disease e.g. age

53
Q

What are the criteria for a confounding factor?

A
  • is associated with the exposure and disease independently
  • is a causal risk factor
  • must not be an intermediate cause
54
Q

What is interaction?

A

when association differs according to the level of a third factor

55
Q

What are the assumptions of cohort studies?

A

representative
well defined absence of exposure
outcome comparability

56
Q

How do you calculate relative risk?

A

number of new cases/number at risk at start of period

57
Q

What are the values for relative risk?

A
1 = no association
>1 = positive association (risk factor)
<1 = negative association (protective factor)
58
Q

How do you calculate relative rate?

A

number of new cases/total person time at risk

59
Q

What is the rate ratio?

A

relative rate in expose/relative rate in unexposed

60
Q

What is equipose?

A

when there is no existing evidence that the intervention being tested is superior to existing treatment or effective

61
Q

What is the power of an RCT?

A

probability of a type II error (false negative)

- usually use power of 80-90%

62
Q

What is the significance of an RCT?

A

probability of a type I error (false positive)

- use significance of 5%

63
Q

What is the criteria for choosing a primary outcome?

A
  • clinically relevant
  • not subjective
  • easy and accurate to measure
  • independent of treatment
64
Q

How do you calculate absolute risk reduction (ARR)?

A

risk in control - risk in intervention

65
Q

How do you calculate relative risk reduction (RRR)?

A

ARR /risk in control

66
Q

How do you calculate number needed to treat?

A

1/ARR

67
Q

What is NNT (number needed to treat)?

A

the number of patients that would need to receive treatment to prevent an adverse event in 1 patient