RESS flashcards for summative

Question 1

what is a health related state

Answer 1

Outcome or dependant variable

e.g death, disease

Question 2

What is a determinant

Answer 2

A definite cause

Question 3

Exposure

Answer 3

Independent variable - potential cause

e.g smoking, age``

Question 4

Incidence

Answer 4

Probability that a disease occurs/is contracted in population within a period of time
Equation: the number of new cases in the period / the number at risk over the period

Question 5

Prevalence

Answer 5

the number of cases of disease at a particular time point

Question 6

Mortality

Answer 6

Proportion of people dying from the disease compared to the rest of the population
Equation: number dying in period from disease / number in population

Question 7

Case fatality rate

Answer 7

Proportion of people who die from a specified disease among all individuals diagnosed with the disease over a certain period of time
Equation: number dying in period from disease / number with the disease in period

Question 8

The scientific method

Answer 8

1 - Observe
2- Propose/modify a hypothesis
3 - Test the hypothesis
4 - Reject/do not reject
5 - If reject, modify hypothesis, If don't reject - Test again

Question 9

Case series

Answer 9

Describes a sample of cases with the same disease, not doing any analysis just describing

Question 10

Cross-sectional study

Answer 10

Studies a group of people at a single point in time

Question 11

Cohort study

Answer 11

Examines disease development in groups of people over time

Question 12

Case-control study

Answer 12

Examines history of groups of people with / without a disease

Question 13

Ecological study (our projects)

Answer 13

Examines variations between geographical areas

Question 14

3 types of health outcomes

Answer 14

• Record based
• Biological/clinical
• Clinician/patient-reported

Question 15

Validity

Answer 15

• Measures accurately what it is meant to measure

- E.g. using BMI rather than weight as a measure of obesity

Question 16

Reliability

Answer 16

• Give the same result on retesting

- E.g. Weight on a bathroom scale is reliable within around ½ a pound

Question 17

Responsiveness

Answer 17

• Can detect real changes when they occur
• Death is unresponsive because once you’re dead you’re dead, it cant change.
• E.g. continuous QoL scale rather than categorical

Question 18

Person-time

Answer 18

• Used as incidence denominator

- a way of determining how many people are at risk

Question 19

Considering a common, short duration disease such as influenza, which of the following would you expect to see?

• Low incidence, low prevalence
• High incidence, low prevalence
• High incidence, High prevalence
• Low incidence, high prevalence

Answer 19

High incidence, low prevalence. Lots of people get it, but they’re cured quickly so fewer people have it at a single point in time.

Question 20

Relative risk (or odds ratio)

Answer 20

risk in exposed group / risk in unexposed group

Question 21

Interpretation of relative risk

Answer 21

• =1 means risk in exposed = risk in unexposed. No benefit or harm
• <1 means risk in exposed < risk in unexposed. Exposure is protective
• > 1 means risk in exposed > risk in unexposed. Exposure is harmful

Question 22

Truncation:

Answer 22

E.g. anorexi* = anorexia, anorexic,

Question 23

Adjacency searching:

Answer 23

E.g. eating adj2 disorder = eating disorder, eating related disorder

Question 24

Wildcards:

Answer 24

• ? #

- E.g. behavio?ral = behavioural, behavioral (one character, or none)

Question 25

The three Boolean operators 

Answer 25

AND - both concepts together OR - both concepts individually NOT - One concept where the other is not present

Question 26

Likert scale

Answer 26

a scale used to represent people's attitudes to a topic.

Question 27

Continuous data

Answer 27

Numerical value, no limitation on values e.g. weight. Even if recorded in whole units.

Question 28

Discrete data

Answer 28

Numerical value, limitation on values e.g. number of hospital appointments

Question 29

Ordinal data

Answer 29

Ordered category e.g. Likert scale, stage of disease. You categorise things and count the number of things in that category.

Question 30

Nominal data

Answer 30

Non-ordered category e.g. sex, blood group

Question 31

Normally distributed data analysis

Answer 31

Mean and standard deviation

Question 32

Skewed data analysis

Answer 32

Median and interquartile range (IQR)

Question 33

How would you check on the distribution of a continuous variable?

Answer 33

Histogram

Question 34

Histograms

Answer 34

The area of a bar in a histogram is proportional to the frequency (frequency histogram), so height is proportional to class width. Histograms are plotted for continuous variables.

Question 35

Bar chart

Answer 35

is a measure of the frequency of each item of a categorical variable

Question 36

Boxplot

Answer 36

displays the median, interquartile range and outlier values

Question 37

Scatterplot

Answer 37

looks at how 2 variables are related to each other. So a great way to see if there is a linear relationship between the two. But not to check the distribution

Question 38

Single categorical exposure & categorical outcome

Answer 38

- calculate risk or odds. | Use risk, risk ratio, odds, odds ratio etc

Question 39

Single categorical exposure & continuous outcome

Answer 39

Use t-test (or non-parametric equivalent)

Question 40

Single continuous exposure & continuous outcome

Answer 40

Use correlation (association)

Question 41

Multiple exposures & continuous outcome

Answer 41

Use linear regression (effect size)

Question 42

Multiple exposures & categorical outcome

Answer 42

Use logistic regression

Question 43

What does the p-value measure

Answer 43

Probability of a result | - So p=0.05 means a 1 in 20 (5%) chance of an event happening

Question 44

Random error

Answer 44

- Error due to random factors - Measurement error - Error from chance fluctuations in the profile of our sample

Question 45

Systematic error

Answer 45

- Error due to non-random factors | - Measurement bias, confounding bias etc.

Question 46

A distortion of an association between 2 variables due to a common shared cause is called

Answer 46

Confounding bias

Question 47

A systematic difference between patients chosen vs. not chosen for a study is called:

Answer 47

Selection bias

Question 48

Confounding bias

Answer 48

Distortion of association due to a common shared cause (confounder) Accommodate through conditioning

Question 49

Experimenter bias

Answer 49

Due to the behaviours and actions of the experimenter

Question 50

Information bias

Answer 50

Due to systematic error in reporting, measurement or recording of information

Question 51

Selection bias

Answer 51

Occurs through a systematic difference between those selected into a study sample and those not selected

Question 52

Standard deviation

Answer 52

Measure of spread

Question 53

Standard error

Answer 53

Measure of precision