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PH 304 Midterm > Intro to Epi > Flashcards

Intro to Epi Flashcards

1
Q

What is the difference between general epidemiology and clinical epidemiology?

A

Clinical epi makes predictions about individual patients by analyzing clinical events in a group of similar patients.

General epidemiology is the study of diseases and their consequences in populations, without a focus on predicting individual outcomes or clinical decision making.

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2
Q

What is the key premise of epidemiology (and life in general)?

A

life is uncertain

OoOoOh AaAaAah

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3
Q

Name 4 uses of epidemiology.

A
  1. describe the distribution of disease
  2. test hypothesis
  3. Assess research reports
  4. Assess clinical and population data
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4
Q

What are the 4 D’s of treatment outcomes that are analyzed by epidemiological studies?

A

Death
Discomfort
Disability
Dissatisfaction

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5
Q

How do you best estimate the probability of an outcome in an individual patient?

A

by referring to past experiences with GROUPS of SIMILAR patients

i.e. not the last patient you saw, please and thank you

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6
Q

What is the best study design to eliminate selection bias?

A

randomized controlled trial

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7
Q

Describe a cohort/incidence study.

A

individuals in study population are classified into exposure categories.

Patients are followed and “outcome” is measured.

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8
Q

Are cohort studies retrospective or prospective?

A

Either!

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9
Q

When are cohort studies most useful?

A

when the outcome is common and an RCT is too expensive

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10
Q

What is the best study method for rare outcomes?

A

Case control study

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11
Q

What is the best study method for common outcomes?

A

cohort studies

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12
Q

Describe a case control study

A

Choose 2 samples of individuals with and without the outcomes, then assess the exposure status some time in the past.

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13
Q

Does the ‘case’ v. ‘control’ classification in a case control study refer to exposure or outcomes?

A

outcomes!

classically, a case control study is retrospective so start with your outcome of interest.

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14
Q

What is the only kind of case control study that is not retrospective?

A

a nested case control study, in which the case and control subjects are drawn from a cohort study

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15
Q

What is another term for a prevalence study?

A

a cross sectional study or survey

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16
Q

Describe a cross-sectional study

A

the exposure and outcome are assessed at the same time (to assess prevalence)

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17
Q

What is the least expensive kind of study?

A

a prevalence/cross sectional study

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18
Q

What is the main drawback of a cross sectional study?

A

because exposure and outcome are measured at the same time, there is no temporal relationship between the two

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19
Q

Are sensitivity and specificity useful in analyzing data from a diagnostic or risk factor association study?

A

diagnostic

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20
Q

Are relative risk, hazard ratios and odds ratios useful for analyzing data from a diagnostic or a risk factor association study?

A

risk factor association - these statistics tell you about the association between a given risk factor and the outcome

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21
Q

Name 3 sampling methods

A

random
stratified random
convenience

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22
Q

“the degree to which the results of a study are correct for the sample of patients being studied.”

Does this describe internal or external validity?

A

internal validity - is your study describing the “truth” for the patients enrolled?

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23
Q

“The degree to which the results of an observation hold true for patients who are not sampled.”

Does this describe internal or external validity?

A

External validity - is your study describing the “truth” for your patients who didn’t enroll?

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24
Q

What is the main threat to validity?

A

BIAS.

Is it just me or is the answer always bias?

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25
Q

What is the difference between bias and, for example, a single mistake made by a med student who stayed up late binge watching “pandemic”?

A

Bias is systematic - it undermines your entire data set in some kind of procedural way, not just the one data point.

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26
Q

Describe selection bias.

A

A systematic process which leads to the creation of a sample group which have other determinants for the outcome aside from the one you’re studying.

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27
Q

What kind of bias is particularly prone to creating confounding variables?

A

selection bias - you create a second factor that “travels with” your outcome of interest and distorts your data

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28
Q

Define measurement bias.

A

Measurements that are imprecise and/or methods of measurement that vary between study groups

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29
Q

Why do we measure things in patients?

A

to classify patients into different risk and outcome groups

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30
Q

Race: white, hispanic, afro american etc. would be an example of which of the following measurement scales:

  1. nominal
  2. ordinal
  3. interval
A

nominal

Can also be dichotomous ( x versus y)

nominal = nombre = names (yay spanish)

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31
Q

COVID positive v. COVID free is an example of which kind of measurement scale?

  1. nominal
  2. ordinal
  3. interval
A

this is an example of a dichotomous nominal scale

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32
Q

“Age 15 to 24, 25 to 34, etc.’
is an example of which kind of measurement scale?

  1. nominal
  2. ordinal
  3. interval
A

ordinal - there’s no inherent ranking or ordering

  • this is always confusing to me, because I think of age in years as being “ordered” since none of us just popped into the world at 25 years of age, but I think the idea is that none of these age categories create any kind of mathematical difference in your analysis - any participant could be in any category at the moment they enroll, and those categories do not need to be spanning the same number of years (e.g. age 65+ covers more years than 1 to 15, but we treat them the same way in our analysis) - it’s just a bucket to categorize people into. If I’m thinking about this wrong lmk.
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33
Q

“The ounces of wine Alba had last night” is an example of which measurement scale?

  1. nominal
  2. ordinal
  3. interval
A

interval - there’s an inherent order and the interval between each ounce is equal because that’s how physics works

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34
Q

What’s the difference between a continuous or discrete variable?

A

continuous: 1.1, 1.12, 1.13 etc
discrete: number of births (1, 2, 3, 4, etc). You can’t have 1.10 births (though we haven’t had repro-GU yet so idk for sure)

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35
Q

Central tendency and distribution can be applied to what kind of scale data?

  1. nominal
  2. interval
  3. ordinal
A

interval

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36
Q

How do we assess error due to bias?

A

validity/accuracy

(bias impacts validity, validity tells us about bias… validity = bias, bias = validity. You get the idea).

37
Q

How do we assess error due to random chance?

A

reliability

38
Q

Why do we compare things to our gold standard? (don’t overthink this)

A

to know if our data is VALID

39
Q

If you don’t have a gold standard, what are two other aspects of your data that you can assess for bias?

A

content validity

construct validity

40
Q

Define content validity

A

The extent to which the method of measurement includes all the relevant dimensions of a construct and nothing else.

I.e. does our measurement include everything that is important to know about our outcome of interest?

41
Q

Define construct validity

A

The extent to which the measurement predicts a directly observable phenomenon

i.e does our measurement actually measure what we think it measures?

42
Q

Does INTRArater reliability refers to the measurement instrument or the operator?

A

instrument

43
Q

Does INTERrater validity refer to the measurement instrument or its operator?

A

operator

44
Q

Define type I error

A

A false positive

45
Q

Define type II error

A

A false negative

46
Q

Define P value

A

estimates the probability that the observed effect IS due to chance, given the assumption that no association exists in your population

BIG p value = Random chance is right

47
Q

What is the difference between clinical and statistical significance?

A

Clinical significance is, essentially, a value judgment by providers and patients: What is WORTH accomplishing in a given intervention?

Statistical significance is just telling you if something is due to chance, and is heavily impacted by a study’s power.

48
Q

What is power directly proportional to? (4)

A
  1. sample size
  2. type I error probability
  3. size of effect
  4. proportion of patients experiencing the outcome
49
Q

What do confidence intervals assess?

A

the precision of an effect estimate

50
Q

If a confidence interval excludes the no effect value, what is always true of the effect?

A

it is statistically significant and the p value is 0.05 or less

51
Q

What is descriptive epidemiology?

A

exactly what it sounds like - it DESCRIBES who has what in which location at what time.

Descriptive should make you think of prevalence and incidence

52
Q

What is analytic epidemiology?

A

Epidemiology assessing the determinants of disease - think of cause and effect, risk factors, exposures, etc.

53
Q

What kind of study method lacks a comparison group?

A

case reports/series

54
Q

Define ecological fallacy.

A

When researchers reach conclusions on the relationship between an exposure and disease at the individual level based on ecological data, which is population based.

eg. sour cream consumption correlates with motorcycle collision deaths

55
Q

Is prevalence related to rates or proportions?

A

proportions - proportions compare subgroups to larger groups, without a component of time

56
Q

is incidence related to rates or proportions?

A

rates - rates compare change over time

57
Q

Give two (general) examples of a ratio.

A

a proportion and a rate

58
Q

In a ratio, are the numerator and denominator always drawn from the same group?

A

not necessarily - you are comparing the number or rate of things in one group versus things in another group.

A proportion and a rate are two specific examples of ratios in which the numerator is a sub group of the denominator

59
Q

in a proportion, are the numerator and denominator drawn from the same group?

A

Yes! the numerator is a subset of the denominator

60
Q

Is a ‘proportionate mortality ratio’ an example of a proportion or a rate?

A

A proportion: ex. 2020 COVID deaths in USA divided by all deaths in 2020 in the USA

61
Q

Is a ‘participant rate’ a proportion or a rate?

A

proportion - number of individuals enrolled out of a pool of eligible individuals. There is no “time” component to the measurement in this instance.

the lesson here should be that the name of the statistic is a LIE and cannot be trusted.

62
Q

Are proportions or rates a measure of risk?

A

rates!

63
Q

Is a mortality rate an example of a proportion or a rate?

A

A rate - it involves time

number of deaths divided by the population over a specific time period

64
Q

Define cumulative incidence

A

Number of new cases during specified period divided by size of population at start of time period

65
Q

Define incidence rate

A

number of new cases during specified time interval divided by summed person-years of observation

66
Q

What is different between incidence rate and cumulative incidence: the numerator or the denominator?

A

the denominator changes!

Denominator for IR is the sum of each person’s time under observation without disease, while in CI it is just the size of the population studied

67
Q

What is one big advantage of incidence rate calculations?

A

Because person-time is calculated for each subject, it can accommodate persons coming into and leaving the study. It allows enrollees to enter the study at different times.

68
Q

What is an important disadvantage in incidence rate calculations?

A

Person-time assumes that the probability of disease during the study period is constant, so that 10 persons followed for one year equals one person followed for 10 years. Because the risk of many chronic diseases increases with age, this assumption is often not valid.

69
Q

“What is the risk that an individual will develop the disease over a given time interval?”

does this describe incidence rate or cumulative incidence?

A

cumulative incidence

70
Q

“How quickly or frequently does a disease occur in a population?”

does this describe incidence rate or cumulative incidence?

A

incidence rate

71
Q

What are the 3 assumptions that must be met for “incidence x duration = prevalance”?

A
  1. incidence must be constant
  2. average duration of disease is constant
  3. prevalence in population is low
72
Q

What is the main difference between a crude/category specific rate and an adjusted rate?

A

Adjusted rates are comparisons between two populations and ARE NOT REAL NUMBERS

Crude rates describe actual cases and events in a population

73
Q

how are crude rates and category specific rates related?

A

Crude rates are a weighted average of the individual category-specific rates.
The weights are the proportion of the population in that category

74
Q

When do you use the direct method of age adjustment?

A

Use direct method when you know the age specific rates and a standard population is available

75
Q

When do you use indirect method for age adjustment?

A

Use indirect method when the age-specific rates are unknown or unstable (small numbers)

76
Q

How should external standards be used in age adjustment?

A

You need to use the same external standard on all the populations being studied so that you have a valid comparison point between the two

you should always report what your standard population is

77
Q

When should direct age adjustment NOT be used?

A

`. if the category specific rates are not available OR the number of cases is less than 20

78
Q

How do I calculate an indirect age adjustment?

A

Multiply my STANDARD age category rates by the people in each age category of my STUDY population = expected numbers in my study population

Then look at my actual study results - do they match the expected numbers i.e. what’s the standardized mortality ratio (SMR)

79
Q

How do I calculate direct age adjustment?

A

Multiply my STUDY age specific rates by the number of individuals in my STANDARD age categories = this tells me what my study results would have looked like in a population without a weighted average skewed by age

80
Q

What is the SMR?

A

number of observed deaths/number of expected deaths

Expected deaths are calculated by indirect age adjustment

81
Q

Does surveillance include controlling the problem?

A

nope - you’re just compiling information so that the people controlling the issue have good information as to what is happening

82
Q

Define syndromic surveillance

A

surveillance which focuses on less specific criteria (i.e. people with a self reported fever, as opposed to cases of clinically confirmed fevers)

83
Q

Define active notification in surveillance

A

Organization conducting surveillance initiates procedures to obtain reports of health event

84
Q

Define passive notification in surveillance

A

Organization conducting the surveillance does not contact reporters but rather leaves the initiative for reporting health event to providers

85
Q

Define sentinel notification in surveillance

A

Organization conducting surveillance relies on pre- arranged sample of reporters who agreed to report cases of health event

86
Q

Describe a point source outbreak with index case and limited spread

A

More and more people get infected then dies down after a peak

87
Q

Describe an index case with propagated spread

A

Index case or cases –> handful of cases –> then more –> then propagates as it goes on –> only goes away once you identify and control it (or can go away on its own when it loses its hosts)
(ie. COVID)

88
Q

What are two types of study methods that are used to formulate a hypothesis during an outbreak investigation?

A

cohort and case control studies

PH 304 Midterm (1 decks)

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