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REBP > L2&3 - Observational Health Research 1 & 2 > Flashcards

L2&3 - Observational Health Research 1 & 2 Flashcards

1
Q

What are the aims of health research?

A

Aim to answer/contribute:

  • better screening and diagnosis
  • better therapies and treatments
  • better prevention through the identification of risk factors and subsequent work in education
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2
Q

What is experimental research?

A

The researcher manipulates 1+ variables and observes the outcomes

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3
Q

What is observational research?

A

No manipulation of the situation, just observation of the outcome measures within pre-existing groups

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4
Q

How is the efficacy of intervention typically tested?

A

Experimental research design - RCT

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5
Q

How are risk factors for a disease typically investigated?

A

Observational research design.

Not the best but experimental design here would be unethical.

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6
Q

What is an association with variables?

A

A change in one variable causing a change in another

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7
Q

What are categorical variables?

A

Variables that take 1 value from a fixed selection. e.g. hair colour, favourite film, smoker/non smoker

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8
Q

What are non categorical variables?

A

Represented numerically e.g. height, weight, age, test score

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9
Q

How are associations between categorical variables shown?

A

Bar chart

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10
Q

How are associations between non-categorical variables shown?

A

Scattergrams

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11
Q

What does a positive correlation show?

A

When the value of one variable increases, the value of the other variable increases

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12
Q

What does a negative correlation show?

A

When the value of one variable increases, the value of the other variable decreases

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13
Q

What does no correlation look like?

A

The scatter is random and no line of best fit can be drawn

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14
Q

What is a non-linear association?

A

A random scatterplot with no line of best fit, showing no correlation between the variables

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15
Q

How is the strength of a correlation determined?

A
  • ‘Correlation coefficient r’ ranges from -1 to 1.
  • 0 means no correlation
  • -1 means perfect negative
  • 1 means perfect positive
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16
Q

How do we test for a correlation?

A

Pearson’s Correlation Coefficient tests the null hypothesis that there is no linear relationship

H0 >> r=0

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17
Q

What are the alternative terms for an exposure variable?

A
  • Risk factor
  • Predictor variable
  • Independent variable
  • Explanatory variable
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18
Q

What are the alternative terms for an outcome variable?

A
  • Predicted variable
  • Dependent variable
  • Response variable
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19
Q

What is a confounder?

A
  • A confounding variable is associated with both the exposure and outcome variables.
  • If not controlled for, the confounder can show an association between the outcome and exposure variables that is not causal.
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20
Q

What are some key confounders in health studies?

A
  • Age
  • Gender
  • Socio-economic Status
  • Anything evidenced in your lit. review
  • Anything that could plausibly be a confounder, even if the lit doesn’t mention it
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21
Q

How can confounders be controlled?

A
  • Use inclusion/exclusion criteria
  • Through statistical analysis
22
Q

What is the principle of fair subject selection?

A

Emanuel et al, 2000 – “groups of individuals should not be excluded from the opportunity to participate in research without a good scientific reason or susceptibility to risk that justifies their exclusion”

23
Q

What are some traditionally underrepresented groups in health studies?

A
  • Women
  • The elderly
  • People from ethnic minority groups
  • Children
  • ‘Real-world patients’ - those with co-morbidities
24
Q

What is a cross-sectional study?

A
  • Takes all data from one point in time
  • Samples participants blindly -
  • Simultaneously collects data about outcome and exposure variables
  • No follow up
  • Allows prevalence to be calculated
  • Observational Design
25
Q

What is a chi-squared test?

A

Chi-squared tests the null hypothesis that there is no association between 2 variables

26
Q

What are the requirements/assumptions for chi-squared?

A
  • Both variables must be categorical (nominal or ordinal)
  • Data points for each variable must be independent (i.e. only one measurement per variable per person)
  • Each cell must have at least 5 expected cases
27
Q

What is a cohort-study design?

A
  • Follow groups of people overtime, and compare how many develop the outcome of interest
28
Q

What does a cohort-study design look like?

A
29
Q

How do you calculate the risk of disease?

A

Risk of disease in the specified group = number of cases/total at risk x 100

30
Q

How do you calculate comparative risk?

A

Risk of disease in exposed group/risk of disease in the non-exposed group = x amount higher risk

31
Q

What is a case-control study design?

A

Identify the cases and the controls (with no disease), work out the exposure in both groups, then compare the exposed to non-exposed.

It is often used to investigate rare outcomes.

32
Q

What does a case-control study look like?

A
33
Q

What is a prospective cohort?

A

Both exposure and outcome variables are determined in the future, after the study has begun

34
Q

What is a retrospective cohort?

A

Both the exposure and outcome data were collected before the study began

35
Q

What is a combined retrospective and prospective cohort?

A

Exposure data is collected in the past, but outcome data is collected after the study has begun

36
Q

What are the advantages of prospective cohorts?

A
  • Establish temporal relationships
  • The research has better control over the data collection methods (as they do it theirself), meaning they have better control over confounders (when compared to a retrospective cohort).
37
Q

What are the disadvantages of a prospective cohort?

A
  • Outcome may take a long time to develop making the project very lengthy
  • If the outcome is rare, you may need to recruit a high number of participants
  • Very expensive
  • Hard to gain funding for
38
Q

What are the advantages of retrospective cohorts?

A
  • Can establish temporal relationships
  • Studies are shorter because they use existing data
  • Cheaper
  • Easier to win funding for
39
Q

What are the disadvantages of retrospective cohorts?

A
  • No control over the data collection methods
    • This means data for exposure and outcome variables can be incomplete
    • Data about confounders may be lacking
40
Q

What are 3 reasons for false results?

A
  • Chance through sampling
  • Confounding
  • Bias
41
Q

How can you control for confounding?

A
  • Widen exclusion criteria
  • Use statistical analysis (only if the confounder is known in advance)
    • Stratified analysis compares like with like
42
Q

What is bias?

A

Systematic error in the design, conduct or analysis of a study

43
Q

What are the two types of bias?

A
  • Selection Bias
  • Information Bias
44
Q

What is selection bias?

A

When cases and control patients are selected in a way that the association is observable in the study, but doesn’t exist in the real population

45
Q

What is information bias?

A

When the methods used for data collection are inadequate, leading to incorrect results about exposure and/or disease outcomes

46
Q

What is recall bias?

A

When the participant misremembers an event

47
Q

What does association but not causation show?

A

A pattern in the observed data

48
Q

What does chi-squared compare?

A

Patterns in the observed data with patterns in the expected data (the population)

49
Q

What does a P value/alpha value of <0.05 mean?

A

Significant because it shows the probability of finding those results due to chance is less than 5%.

The p value shows if the relationship is statistically relevant - if it exists within the population, not just the sample.

50
Q
A

REBP (5 decks)

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