MHS Revision

Question 0

Associations may be the result of…

Answer 0

Chance
Bias
Confounding
REAL ASSOCIATIONS

Question 1

What type of study is a cohort study?

Answer 1

An observational study.

Question 2

Alpha level is usually ____

Answer 2

0.05 (1 in 20)

Question 3

P value = ______

Answer 3

The estimated probability of seeing a difference of a result equal to or more extreme than that observed in a study occurring by chance.

Question 4

Confounding means _____

Answer 4

The effects of a proposed risk factor is mixed up with other risk factors.

Question 5

Doll and hill study 1952 Looked at what?

Answer 5

Lung cancer, with controls of no lung Cx in a hospital.

Question 6

Why is recall bias an issue?

Answer 6

People who have had the disease or illness tend to be able to recall more clearly.

Question 7

What methoda can you employ to deal with confounding?

Answer 7

1. ) In design, restrict the study to one stratum of the confounder, i.e. only study smokers or only non- smokers.
2. ) In study design, match for potential confounders.

Question 8

Residual confounding.

Answer 8

Occurs when all known confounders have been accounted for but there are other, unknown confounders that cannot be accounted for.

Question 9

Incidence

Answer 9

No. of NEW events, occuring during a period of time. I.e. 1000/year.

Question 10

Prevalance

Answer 10

Point prevalence - how many with a condition with a SNAPSHOT

Period prevalence - NO. of people with diabetes during a period of time - NOT just new cases.

Question 11

Incidence Density

Answer 11

Looking at incidence in individuals over varied lengths of time. This is because different individuals will be “at risk” for varied lengths of time.

Question 12

the standardised mortality ration is an example of ______ standardisation.

Answer 12

Indirect

Question 13

SMR = _____/_____

Answer 13

Observed No of deaths/Expected number of deaths.

Question 14

Define Sensitivity

Answer 14

How sensitive the test is to detect the presence of a disease, basically saying how likely it is the test will give positive result if a patient HAS the condition.

Question 15

Define Specificity:

Answer 15

Is a result POSITIVE to the target condition? In other words, how likely will someone WITHOUT condition give a NEGATIVE reponse.

Low specificity will lead to Type 2 error. (saying that there is no difference between condition and not when there is)

Question 16

Define POSITIVE PREDICTIVE VALUE.

Answer 16

How VALUABLE is a POSITIVE test result predicting a condition. AKA: how many of the people that tested positive actually HAVE the disease?

Calculated by (true positive/sum positive results)

Question 17

Define NEGATIVE PREDICTED VALUE.

Answer 17

What proportion of patients with negative values are TRULY FREE of the disease?

i.e. (true negative/sum negative)

Question 18

Type ____ error is usually considered the “worst” in research. Type ____ error is worse in medicine, as it will mean patients requiring treatment will not receive it.

Answer 18

1. ) Type 1

2. ) Type 2

Question 19

How do you calculate the efficiency of a test?

Answer 19

E = ((TP+TN)/(TP+FP+FN+TN))

Question 20

Predictive values are influenced by ______

Answer 20

The prevalence of the disorder in the population.

Question 21

Sensitivity and specificity are influenced by _____

Answer 21

The cut off point chosen for continuously distributed test parameters.

NOT influenced by prevalence.

Question 22

How would you calculate prevalence?

Answer 22

Total with/Sum total of pop

Question 23

If prevalence < the PPV _____ and the NPV ____.

Answer 23

Increases PPV

Decreases NPV

Question 24

how would you calculate absolute risk?

Answer 24

(No/(populationxyears)) x 1000 (if per 1000 in pop)

Question 25

How would you equate attributable risk?

Answer 25

Absolute risk (with drug/etc) - Absolute risk (without drug/etc)

Question 26

How do you calculate relative risk?

Answer 26

Absolute risk (with drug) / Absolute risk (without drug)