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Phase 1 > Critical numbers > Flashcards

Critical numbers Flashcards

1
Q

What is the difference between an experimental and observational study?

A

Experimental: researchers have intervened in some way
Observational: researchers haven’t intervened, just observed

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2
Q

What are 3 types of observational study?

A

Retrospective
Cross-sectional
Prospective

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3
Q

How do randomised controlled trials work?

A

Randomly allocate ptps to different interventions and follow up
Experimental
Prospective

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4
Q

What are some variations of RCT?

A

Cluster: ptps randomised in groups, not individually (e.g. a whole gp centre)
Crossover: ptps receive both interventions in a random order
Multi-arm: 2+ interventions evaluated in single study
Adaptive design trials: accruing info is used to inform planned design adaptations

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5
Q

Pros of RCTs

A

Gold standard
Reduced confounding potential
Reduce bias
Determine causal effects

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6
Q

Cons of RCT

A

Randomisations can be unfeasible or unethical
Require expert management and oversight
Expensive

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7
Q

How do cohort studies work?

A

Non-randomised
Observational
Typically prospective
Sample split into exposed/unexposed

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8
Q

Pros of cohort studies

A

Useful when random allocations not possible
Can work for rare exposures (select ptps exposed)
Can examine multiple outcomes

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9
Q

Cons of cohort studies

A

May require long follow up
Can be expensive
Not ideal for rare outcomes

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10
Q

How do case-control studies work?

A

Non-randomised
Observational
Retrospective
One group have condition already, other group don’t

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11
Q

Pros of case-control

A

Faster as use past data
Useful for rare outcomes- select ptps on basis of outcome
Cheaper

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12
Q

Cons of case-control

A

More prone to bias or poor quality data
Harder to show causal relationship
Not ideal for rare exposures

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13
Q

Features of cross-sectional studies?

A

Non-randomised
Observational
Single time point

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14
Q

Pros of cross-sectional studies

A

Relatively quick
Cheap
Can assess multiple exposures/outcomes

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15
Q

Cons of cross-sectional studies

A

Susceptible to bias
Cannot prove causality
Not ideal for rare exposures/outcomes

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16
Q

What are ecological studies, +pros and cons

A

Observational study of a group
Pros: large scale, can quantify geographical or temporal trends
Cons: ecological fallacy, can’t make inference at individual level

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17
Q

Types of categorical variables

A

Binary- 2 categories e.g. + or -
Ordinal- categories with natural order
Nominal- categories without order, e.g. blood group

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18
Q

Types of numeric variables

A

Discrete- only certain numerical values,e.g. number of children
Continuous- any value within a range, e.g. height

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19
Q

Define proportion

A

Number with a characteristic or outcome divided by total number
scale 0-1

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20
Q

Define odds

A

Number with an exposure or outcome divided by number without
Ratio of probability of event occurring vs not
probability divided by 1-probability

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21
Q

What is a rate?

A

Frequency per another unit of measurement, e.g. events per 100 people per year

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22
Q

Example of risk difference and risk ratio

A

risk of hypertension in aspirin group = 0.12
risk of hypertension in placebo group = 0.35
risk difference = 0.12 - 0.35 = 0.23, risk reduction 23%
risk ratio = 0.12/0.35 = 0.34, lower risk as less than 1

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23
Q

Example of odds ratio

A

odds of hypertension on aspirin = 0.13
odds of hypertension in placebo = 0.55
odds ratio = 0.13/0.55= 0.24

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24
Q

How to work out mean, median and mode

A

mean - sum the values divide by count, typically reported with st dev
median- order values then take midpoint, typically reported with range
mode- most common value, not used very often practically
if normal distribution, mean and median will be same

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25
Q

What is standard deviation?

A

Describes dispersion of values around the mean
x̄ = mean and sd = s when describing a sample
μ = mean and sd = σ when describing a population

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26
Q

What are range and interquartile range?

A

Range = lowest value and highest value
IQR = 25th-75th centile, central 50% range

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27
Q

What is right skewed distribution?

A

Positive
Median is less than mean
Tail on right hand side

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28
Q

What is left skewed distribution?

A

Negative
Mean less than median
Tail on left side

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29
Q

What % lie with 1sd, 2sd and 3sd of the mean (when symmetric)?

A

1sd = 68% of values
2sd = 95% of values
3sd= 99.7% of values

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30
Q

What is correlation?

A

A measure of linear relationships between variables
Quantified by correlation coefficient r
r between -1 and 1

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31
Q

What is statistical inference?

A

Use information from a sample to make inference about a population
Need to account for uncertainty
Derive estimates of population parameters and test hypotheses

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32
Q

What is central limit theorem?

A

the distribution of sample means approximates a normal distribution as the sample size gets larger, regardless of the population’s distribution

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33
Q

What is standard error?

A

Indicates how different a sample mean is likely to be from the population mean
Used for estimating
Tells us precision of estimation
Smaller standard error = more precise

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34
Q

Equation for standard error of the mean

A

SD divided by √n
bigger sd, bigger standard error
bigger the sample size, smaller standard error

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35
Q

What is a confidence interval?

A

a range around a measurement that conveys how precise the measurement is
gives plausible range

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36
Q

What factors affect confidence interval width?

A

Variability in the sample (SD)
Sample size (n)
The desired level of confidence
- typically we use 95% but it could be 90%, 99%, etc

37
Q

What does a probability of 1 mean?

A

Event is certain to happen

38
Q

What is the null hypothesis?

A

assume this hypothesis is true until we see sufficient evidence to the contrary
typically the theory we want to disprove

39
Q

What is the p value?

A

the probability of seeing an effect of the observed magnitude or greater if the null hypothesis were true

40
Q

What happens if p value is smaller than significance level?

A

Reject null hypothesis

41
Q

Features of regression

A

Allows one variable to be predicted from the other
Order matters (predict y from x)
Can handle multiple predictors
Variables don’t have to be numeric

42
Q

Features of correlations

A

Quantifies the linear association between two numeric variables
Variable order doesn’t matter (correlate x~y or y~x)

43
Q

What is regression?

A

a statistical technique that relates a dependent variable to one or more independent (explanatory) variables

44
Q

Advantages of multiple regression

A
  • Can include both numeric and categorical predictors
  • Explore relative strength of prediction
  • can adjust or control for confounding
  • reduce bias from chance covariate imbalance
  • explore interactions between predictors
  • make predictions based on combinations of risk factors
45
Q

What is multiple regression?

A

More than one predictor
e.g. a+b1height+ b2age +

46
Q

What is prognosis?

A

the forecast of future outcomes

47
Q

What is critical appraisal?

A

the process of assessing and interpreting evidence by systematically considering its validity, results and relevance to your own context

48
Q

Ways to reduce bias in RCTs?

A
  • Randomly allocating participants to receive an intervention or not
  • Blinding participants, investigators and assessors to the different treatments (where possible)
  • Including a control group to compare the intervention against
49
Q

What is a systematic review?

A

A research article in which existing evidence on a topic is systematically identified, appraised and summarised according to predetermined criteria

50
Q

What is a meta-analysis?

A

Statistical method for combining evidence from different sources

51
Q

What is heterogeniety?

A

a measure of variation between different studies

52
Q

What is sensitivity analysis?

A

analysis to test the robustness of the findings of primary analysis – looks at the effect of assumptions or variations in approach.

53
Q

What is sample bias?

A

sample does not represent population of interest

54
Q

What is recall bias?

A

inaccurate recall of past events/exposures/behaviours

55
Q

What is information bias?

A

incorrect measurement e.g. miscalibrated machine

56
Q

What is the Hawthorne effect?

A

participants change their behaviour when they know they are being observed

57
Q

What is attrition bias?

A

differential dropout from studies
e.g. sicker participants drop out so our outcome is only measured on healthier participants

58
Q

What does a confounding variable do?

A

obscure the real effect of an exposure on an outcome

59
Q

What does risk difference mean?

A

difference in proportions between groups
0 = no difference

60
Q

What is the risk ratio (aka relative risk)?

A

risk in one group divided by risk in the other, greater than 1= higher risk in groups of interest, less than 1= lower risk in group of interest

61
Q

What is the odds ratio?

A

odds in one group divided by odds in the other

62
Q

When will median and mean be the same?

A

When distribution is normal

63
Q

What does parametric mean?

A

make distributional assumptions

64
Q

Stages of hypothesis testing using stats

A

Define null and H1
Choose significance level
Perform appropriate stats test
Find p value

65
Q

What is regression?

A

a statistical technique that relates a dependent variable to one or more independent variable

66
Q

Regression general eqtn

A

y=a+bx
y variable being predicted
x variable predicting (independent)
a constant/intercept
b gradient/coefficient

67
Q

What is univariable regression?

A

One predictor

68
Q

What is used to establish causality in non randomised trials?

A

Strength of association
Consistency
Specificity
Temporality
Biological gradient
Plausibility
Coherence
Experiment
Analogy

69
Q

What is positivism based on?

A

objectivity
scientific method
Empiricism

70
Q

What does interpretivism believe?

A

social reality can only be understood through social constructions such as language, consciousness and shared meanings and understandings

71
Q

What is quantitative methodology?

A

Emphasises quantification in collection and analysis of data
Deductive approach – theory testing
Based on positivism
Views social reality as external and objective

72
Q

What is qualitative methodology?

A

Emphasising words, rather than numbers
Inductive approach – generating theories (does not claim ‘truth’ status)
Based on interpretivism – understanding the ways in which individuals and groups interpret their world

73
Q

Features of quantitative research

A

Deductive (theory testing)
Large, random samples
Generalisability, representativeness
‘Objective’ instruments (attitude/ outcome scales)
Results as number and statistics
Infer to population
‘Distance’ between researcher and subjects
Emphasis on following original research plan

74
Q

Features of qualitative research

A

Inductive (develop theory)
Small, purposive samples
May, or may not, be representative
Less structured instruments (interviews)
Results as words and concepts
Do not infer to population
Reflexivity and attention to individual participants
Flexibility of approach

75
Q

Examples of qualitative data

A

Interview transcripts
Focus groups transcripts
Field notes
Documents (reports, minutes, plans, blogs, social media posts)
Film, photographs, photo-elicitation.
Diary entries

76
Q

What is critical appraisal?

A

the process of assessing and interpreting evidence by systematically considering its validity, results and relevance to your own context

77
Q

What questions could be asked in critical appraisal?

A

Is the research question clear and focussed?
Is the study design appropriate?
What are the strengths/weaknesses?
Is there potential for bias? Has it been addressed?
Are the analysis methods appropriate?
Have the results been interpreted correctly?
Are the findings relevant to your practice?

78
Q

What does PICO stand for?

A

Population
Intervention
Comparator
Outcomes

79
Q

What does internal validity mean?

A

Accurately measuring those within the trial

80
Q

What does external validity mean?

A

Generalisable outside trial

81
Q

What is the CASP checklist?

A

Is the basic study design valid for a randomised controlled trial?
Was the study methodologically sound?
What are the results?
Will the results help locally?

82
Q

How do RCTs attempt to limit bias?

A

Randomly allocating participants to receive an intervention or not
Blinding participants, investigators and assessors to the different treatments (where possible)
Including a control group to compare the intervention against

83
Q

Features of a systematic review

A

Transparent, systematic methods make the process replicable
Bias is addressed by assessing each individual study for bias

84
Q

What are the steps of a systematic review?

A

Specify research question
Develop search strategy and inclusion/exclusion criteria
Identify relevant studies
Assess quality and risk of bias
Extract data from each study
Pool and interpret results
Answer research question

85
Q

What is a meta-analysis?

A

Statistical method for combining evidence from different sources

86
Q

What is a sensitivity analysis?

A

analysis to test the robustness of the findings of primary analysis – looks at the effect of assumptions or variations in approach

87
Q

What is heterogeniety?

A

a measure of variation between different studies

88
Q

What are the PRISMA guidelines for?

A

guidelines aimed to improve the reporting of systematic reviews

Phase 1 (18 decks)

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