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3rd Year - FoPC > 1.2. Population Data - Types of Studies, Trials, Bias, Interpreting Factors, and Confounding Factors > Flashcards

1.2. Population Data - Types of Studies, Trials, Bias, Interpreting Factors, and Confounding Factors Flashcards

1
Q

What are the Types of Epidemiological Studies?

A
  1. Descriptive Epidemiological Studies
  2. Cross-Sectional Analytical Epidemiological Studies
  3. Case Control Analytical Epidemiological Studies
  4. Cohort Analytical Epidemiological Studies
  5. Randomized Controlled Trial
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2
Q

What is the purpose of “Descriptive Epidemiological Studies”?

A

To describe the amount and distribution of a disease in a given population, for:

  1. Gaining an insight into the aetiology of the condition
  2. Planning Health Services to meet the Clinical Need
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3
Q

Do “Descriptive Epidemiological Studies” only look at the disease alone?

A
  1. They can

2. They can also examine one or more factors (exposures) thought to be linked to the aetiology

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4
Q

Do “Descriptive Epidemiological Studies” provide definite conclusions about disease causation?

A

No

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5
Q

What do “Descriptive Epidemiological Studies” give clues about?

A
  1. Possible Risk Factors

2. Candidate Aetiologies

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6
Q

What framework do “Descriptive Epidemiological Studies” follow?

A
  1. Time
  2. Place
  3. Person
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7
Q

What are “Descriptive Epidemiological Studies” useful in?

A
  1. Identifying emerging public health problems, through monitoring surveillance of a disease
  2. Signalling the presence of effects worthy of further investigation
  3. Assessing the effectiveness of measures of prevention and control (e.g. screening programs)
  4. Assessing need for Health Services and Service Planning
  5. Generating Hypotheses about Disease Aetiology
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8
Q

What are the advantages of “Descriptive Epidemiological Studies”?

A
  1. They are quick
  2. They are cheap
  3. They give valuable initial overview of the problem
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9
Q

What are the disadvantages of “Descriptive Epidemiological Studies”?

A
  1. They do not provide evidence about the causes of disease

2. They do not test hypotheses

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10
Q

When are observations made in “Cross-Sectional Analytical Epidemiological Studies”?

A

At a single point in time

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11
Q

What are conclusions drawn about in “Cross-Sectional Analytical Epidemiological Studies”?

A

The relationship between diseases (or other health-related characteristics) and other variables of interest in a defined population

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12
Q

What are the advantages of “Cross-Sectional Analytical Epidemiological Studies”?

A

They provide results quickly

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13
Q

What are the disadvantages of “Cross-Sectional Analytical Epidemiological Studies”?

A

It is usually impossible to infer causation

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14
Q

What is compared in “Case Control Analytical Epidemiological Studies”?

A

2 groups of people

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15
Q

What are the 2 groups of people compared in “Case Control Analytical Epidemiological Studies”?

A
  1. A group of individuals who have the disease of interest (Cases)
  2. A group of individuals who do not have the disease of interest (Controls)
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16
Q

What happens to the individuals selected in “Case Control Analytical Epidemiological Studies”?

A

Data is gathered on each individual to determine whether or not they have been exposed to suspected aetiological factors

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17
Q

How is the data gathered on individuals selected for “Case Control Analytical Epidemiological Studies” used?

A

The average exposure in the 2 groups ( Cases and Controls) is compared to identify significant differences, which give clues to factors which elevate/reduce risk of the disease under investigation

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18
Q

How are the results from “Case Control Analytical Epidemiological Studies” expressed?

A
  1. Odd Ratio’s

2. Relative Risks

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19
Q

What is presented as a guide to whether the result was a chance finding?

A

Confidence intervals; or “P values”

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20
Q

What information is collected in “Cohort Analytical Epidemiological Studies”?

A

Baseline data on exposure from a group of people who do not have the disease under study

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21
Q

What happens to the individuals who have data gathered for “Cohort Analytical Epidemiological Studies”?

A

They are followed through time, until a sufficient number have developed the disease to allow for analysis

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22
Q

What happens to the original group in “Cohort Analytical Epidemiological Studies” during analysis?

A

They are separated into subgroups according to original exposure status

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23
Q

What happens to the subgroups during analysis in “Cohort Analytical Epidemiological Studies”?

A

They are compared to determine the incidence of disease according to the exposure

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24
Q

What do “Cohort Analytical Epidemiological Studies” allow the calculation of?

A

Cumulative incidence, allowing for differences in follow up time

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25
Q

How are results of “Cohort Analytical Epidemiological Studies” usually expressed?

A

Relative Risks, with confidence intervals (or P values)

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26
Q

What are trials?

A
  1. Experiments used to test ideas about aetiology

2. Experiments used to evaluate interventions

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27
Q

What is the definitive method of assessing any new treatment in medicine?

A

The Randomized Control Trial

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28
Q

What happens in a “Randomized Controlled Trial”?

A
  1. 2 groups at risk of developing a disease are assembled (Intervention and Control)
  2. An alteration is made to the “Intervention” group (e.g. suspected causative factor is removed) with no change to the “Control Group”
  3. Data on subsequent outcomes (e.g. disease incidence) are collected in the same way for both groups
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29
Q

What is calculated from the results of “Randomized Controlled Trials”?

A

The Relative Risk for both groups

30
Q

What is the aim of “Randomized Controlled Trials”?

A

To determine whether the modification of the factor (removing, reducing, or increasing exposure) alters the incidence of the disease

31
Q

How can “Randomized Controlled Trials” be used in the trial of a new treatment?

A
  1. a) The “Intervention” group receives the new therapy
  2. b) The “Control” group receives the current (standard) therapy or a placebo
  3. The treatment outcomes (e.g. reduction in symptoms) are compared between the 2 groups
32
Q

What are 6 factors to consider when interpreting results?

A
  1. Standardization
  2. Standardized Mortality Ratio (SMR)
  3. Quality of data
  4. Case Definition
  5. Coding and Classification
  6. Ascertainment
33
Q

What is “Standardization”?

A

A set of techniques used to remove (or adjust for) the effects of differences in age or other confounding variables when comparing 2 or more populations

34
Q

What does an “Age-Sex Standardized Rate” represent?

A

What the Unstandardized (Crude) rate would have been in the study population - if that population had the same proportion of: Males and Females; and People in different age groups; as the standard population

35
Q

Can rates be standardized for any other relevant confounding factor?

A

Yes (E.g. Social Class)

36
Q

What comparisons should always be based on standardized rates, and never on crude rates?

A
  1. Incidence or mortality rates in a population over time
  2. Between 2 different populations
  3. Between population subgroups
37
Q

What is the “Standardized Mortality Ratio (SMR)”?

A

A special kind of Standardization:

It is a standardized death rate converted into a ratio for easy comparison

38
Q

What is the figure for a standard reference population (e.g. Scotland), used in a “Standardized Mortality Ratio (SMR)”?

A

100

39
Q

In “Standardized Mortality Ratio (SMR)”, What is the figure for the comparison (study) populations expressed as?

A

As a proportion of the 100 (Standard Reference Population)

E.g. the standardized death rates of Grampian in Scotland will be expressed as a proportion of the 100

40
Q

In “Standardized Mortality Ratio (SMR)”, what does a figure below 100 mean?

A

Fewer than expected deaths
E.g. an SMR of 80 means that 20% less deaths occurred than expected in the study population, allowing for the differences in the Age and Sex structure of the standard and study populations

41
Q

In “Standardized Mortality Ratio (SMR)”, what does a figure above 100 mean?

A

More than expected deaths
E.g. an SMR of 120 means that 20% more deaths occurred than expected in the study population, allowing for the differences in the Age and Sex structure of the standard and study populations

42
Q

What is meant by “Quality of Data” as a factor to consider when interpreting results?

A

Must ensure that the data is trustworthy

43
Q

What is the purpose of “Case Definition”?

A

To decide whether an individual has the condition of interest or not

44
Q

Why is “Case Definition” important?

A

Not all doctors or investigators mean the same thing when they use medical terms - differences in incidence of disease over time or in different populations may be artifact, due to differences in case definition rather than differences in true incidence

45
Q

What is “Coding and Classification” related to?

A

Case Definition

46
Q

What normally happens when data is being collected routinely?

A

Diseases are converted into sets of codes to assess in data storage and analysis

47
Q

Why does “Coding and Classification” need to be considered when interpreting results?

A

The rules used to dictate how clinical information is converted into code can change - disease can seem more / less common because its not under a new heading

48
Q

What does “Ascertainment” mean, in relation to it being a factor to be considered when interpreting results?

A

If the data is complete - if researchers are looking harder in one place than another then the incidence rate will be higher

49
Q

What is Bias?

A

Any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically different from the truth

50
Q

What are the 4 important types of Bias?

A
  1. Selection Bias
  2. Information Bias
  3. Follow-up Bias
  4. Systematic Error
51
Q

When does Selection Bias arise?

A

When the study sample is not truly representative of the whole study population, about which conclusions are going to be drawn
E.g. In a randomized controlled drug trial, one of the groups has more old/ill folk than the other and so the results are skewed

52
Q

Why does Information Bias arise?

A

Due to systematic errors in measuring exposure or disease:
E.g. In a case control study, a researcher who was aware of whether the interviewee was a case or control, may influence the researchers enthusiasm

53
Q

Why does Follow-up Bias arise?

A

When one of the group of subjects is followed up more assiduously than another, to measure disease incidence or other relevant outcome.
E.g. In cohort studies, subjects can move address or fail to reply to questionnaires sent out

54
Q

What is Systematic Error?

A

A form of Measurement Bias, where there is a tendency for measurements to always fall on one side of the true value

55
Q

Why might Systematic Error occur?

A
  1. The instrument is calibrated wrongly (e.g. a blood pressure machine)
  2. The way a person uses a instrument is wrong
    Note - this can also occur with questionnaires
56
Q

What is a “Confounding Factor”?

A

A factor which is associated independently with both:

  1. The disease
  2. The exposure under investigation
57
Q

What can “Confounding Factors” do to results?

A

They distort the relationship between exposure under investigation and the disease
Note - in some cases the confounding factor may be the true casual factor, and not the exposure, that is under consideration

58
Q

What are common “Confounding Factors”?

A
  1. Age
  2. Sex
  3. Social Class
59
Q

How are “Confounding Factors” dealt with in study design?

A
  1. In trials - The process of randomization
  2. Restriction of Eligibility Criteria
  3. Subjects in different groups can be matched for likely confounding factors
  4. Results can be stratified according to confounding factors
  5. Results can be adjusted to take account of confounding factors
60
Q

What are the Criteria for Causality?

A
  1. Strength of Association
  2. Consistency
  3. Specificity
  4. Temporality
  5. Biological Gradient
  6. Biological Plausibility
  7. Coherence
  8. Analogy
  9. Experiment
61
Q

In relation to the Criteria of Causality, what is “Strength of Association” measured by?

A

Relative Risk or Odds Ratio

62
Q

In relation to the Criteria of Causality, what is “Consistency”?

A

Repeated observation of an association, in different populations, under different circumstances

63
Q

In relation to the Criteria of Causality, what is “Specificity”?

A

A single exposure leading to a single disease

64
Q

In relation to the Criteria of Causality, what is “Temporality”?

A

The exposure comes before the disease

Note - This is the only absolute Criterion

65
Q

In relation to the Criteria of Causality, what is the “Biological Gradient”?

A

The dose-response relationship - as the exposure increases so does the risk of disease

66
Q

In relation to the Criteria of Causality, what is “Biological Plausibility”?

A

The association agrees with what is known about the biology of the disease

67
Q

In relation to the Criteria of Causality, what is “Coherence”?

A

The association does not conflict with what is known about the biology if the disease

68
Q

In relation to the Criteria of Causality, what is “Analogy”?

A

Another exposure-disease relationship exists which can act as a model for the one under investigation
E.g. it is known that certain drugs can cross the placenta and cause birth defects - it might be possible for viruses to do the same

69
Q

In relation to the Criteria of Causality, what is the “Experiment”?

A

A suitably controlled experiment is needed to probe the association as causal - very uncommon in human populations

70
Q

What is the only Absolute Criterion for the Criteria of Causality?

A

Temporality

71
Q

Does failing to fulfill any of the Criteria of Causality (other than Temporality) rule out Causality?

A

No

3rd Year - FoPC (4 decks)

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