RESS Flashcards

1
Q

Incidence rate?

A

Incidence rate = Number of new cases in period / Number at risk in population in period

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2
Q

Prevalence rate?

A

Prevalence rate= No. of people with a disease at certain time / No. of people in the population at certain time

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3
Q

Case fatality rate?

A

Case fatality rate = No. of people who die from the disease in period / No. of people with disease in period

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4
Q

Mortality rate?

A

Mortality rate = No. of people who die from the disease in period / No. of people who die in period

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5
Q

How is adjustment done to better represent the crude rates? (eg age adjustment)

A

It is done by calculating the stratum specific rates. A stratum is a subgroup in the sample, eg) age or sex group

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6
Q

Risk of disease?

A

Risk = Number or new cases / Number at risk

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7
Q

What does risk ratio measure?

A

It measures relative risk (RR)

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8
Q

Risk ratio?

A

Those with disease and exposed to risk factor / All those exposed to risk factor
DIVIDED BY:
Those with disease and not exposed to risk factor / All those not exposed to risk factor

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9
Q

What does it mean if the relative risk is:
=1 ?
<1 ?
>1 ?

The further away the relative risk is from 1, the stronger the association

A

= 1 … the risk in the exposed group is the same as the risk in the unexposed group
<1 … the exposure is associated with a protective effect
>1 … the exposure is associated with harm

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10
Q

What is an Odds ratio?

A

A measure that represents the relative risk for a case-control study

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11
Q

What does it mean if the odds ratio = 1?

A

The probability of an event occuring is the same as the probability that the event does not occur (ie an event will occur half the time)

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12
Q

What is the Null hypothesis (H0)?

A

Assumes no effect (if the drug is tested, the H0 will be that the drug will have no effect)

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13
Q

What is the Alternative hypothesis (H1 or Ha)?

A

Assumes there is an effect, either beneficial or harmful, ie. two-sided.

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14
Q

What are the features of a hypothesis?

A

It must be:

  • Plausible
  • Falsifiable (able to be accepted or rejected),
  • Have direction
  • Be precise
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15
Q

What is the P value?

A

It is the probability of obtaining the results of the test given that the null hypothesis is true, (ie- how likely it is that the null hypothesis is correct)
So: the smaller the p value, the less likely the result is to have occurred by chance alone & thus more likely the result is due to exposure

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16
Q

What are the features of Survival data?

A
  • A person enters the study
  • The time the person leaves the study (therefore the event= failure)
  • Leaving the study before the event occurs, or entering after the start of the study (=censoring)
17
Q

How may survival data be either Right or Left censored?

A

Right censored= people in the study didn’t reach a failure before the end of the study (eg in new HIV drug trial, right censored data will occur if the study participants die of other non-AIDS causes)
Left censored= not certain what happened to the people before the time at which they entered the study (eg when they already have the disease of interest when the study starts)

18
Q

What is:

a) Survival function
b) Hazard function

A

a) =the chance of survival until a certain time

b) =the chance of instantaneous failure at any one time

19
Q

What does a Kaplan-Meier plot show?

A

It shows survival as a series of steps. It steps down every time a failure is observed.

20
Q

What is a Log rank test?

A

(to examine Surviving data) This compares the survival functions between the 2 groups.

21
Q

What is the Asch Experiment (1952)?

A

What others think can change our behaviour – everyone asked a question, rest of group answer wrong, participant agrees with the wrong answer.

22
Q

What is social marketing?

A

Might be used to address lack of knowledge, marketing an idea NOT a product, e.g. advertising the number of units in alcohol in order to lower people’s drinking

23
Q

What is the Social norms approach?

A

It is about adressing misperceptions of the norm, reflecting a positive behaviour fact about the population.
1.Understand the norm –>2.Understand what people believe is the norm –>2.Evidence of mismatch (misperception) –>4.Challenge misperceptions

24
Q

How are themes identified?

A
  • Immersing in the data
  • Coding transcripts
  • Organising codes into meaningful groups
  • Generating themes
25
Q

Why are themes different to categories?

A

Themes are broader and include interpretation about a phenomenon

26
Q

What is Sensitivity?

A

The proportion of people with the disease who are identified as having it by a positive test result.
Sensitivity = A/(A+C)

27
Q

What is Specificity?

A

The proportion of people without the disease who are correctly re-assured by a negative test result.
Specificity = D/(D+B)

28
Q

What is a positive predictive value?

A

The probability that a person with a positive test result actually has the disease
Positive predictive value = A/(A+B)

29
Q

What is a negative predictive value?

A

Probability that a person with a negative test result doesn’t have the disease
Negative predictive value = D/(C+D)

30
Q

What are some features of high sensitivity?

A
  • Maximises identification of diseased people in the screened population
  • Few false negatives
  • Lots of false positives
31
Q

When is high sensitivity desirable?

A

If the adverse consequences of missed diagnosis for the individual are worse than early diagnosis
-If serious consequences of missed diagnosis on society

32
Q

Features of high specificity?

A
  • Tends to detect only people with the disease
  • Relatively few false positives
  • Lots of false negatives
33
Q

When is high specificity desirable?

A
  • If the diagnosis is associated with anxiety or stigma

- Further investigations are time consuming/expensive