Brainscape's Knowledge GenomeTM


Top Flashcards (Certified)
All Flashcards

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What are 3 types of observational study?

A

Retrospective
Cross-sectional
Prospective

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

How do randomised controlled trials work?

A

Randomly allocate ptps to different interventions and follow up
Experimental
Prospective

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Pros of RCTs

A

Gold standard
Reduced confounding potential
Reduce bias
Determine causal effects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Cons of RCT

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

How do cohort studies work?

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Cons of cohort studies

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

How do case-control studies work?

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Pros of case-control

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Features of cross-sectional studies?

A

Non-randomised
Observational
Single time point

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Pros of cross-sectional studies

A

Relatively quick
Cheap
Can assess multiple exposures/outcomes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Cons of cross-sectional studies

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Define proportion

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

What is a rate?

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
What is standard deviation?
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
26
What are range and interquartile range?
Range = lowest value and highest value IQR = 25th-75th centile, central 50% range
27
What is right skewed distribution?
Positive Median is less than mean Tail on right hand side
28
What is left skewed distribution?
Negative Mean less than median Tail on left side
29
What % lie with 1sd, 2sd and 3sd of the mean (when symmetric)?
1sd = 68% of values 2sd = 95% of values 3sd= 99.7% of values
30
What is correlation?
A measure of linear relationships between variables Quantified by correlation coefficient r r between -1 and 1
31
What is statistical inference?
Use information from a sample to make inference about a population Need to account for uncertainty Derive estimates of population parameters and test hypotheses
32
What is central limit theorem?
the distribution of sample means approximates a normal distribution as the sample size gets larger, regardless of the population's distribution
33
What is standard error?
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
34
Equation for standard error of the mean
SD divided by √n bigger sd, bigger standard error bigger the sample size, smaller standard error
35
What is a confidence interval?
a range around a measurement that conveys how precise the measurement is gives plausible range
36
What factors affect confidence interval width?
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
What does a probability of 1 mean?
Event is certain to happen
38
What is the null hypothesis?
assume this hypothesis is true until we see sufficient evidence to the contrary typically the theory we want to disprove
39
What is the p value?
the probability of seeing an effect of the observed magnitude or greater if the null hypothesis were true
40
What happens if p value is smaller than significance level?
Reject null hypothesis
41
Features of regression
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
Features of correlations
Quantifies the linear association between two numeric variables Variable order doesn’t matter (correlate x~y or y~x)
43
What is regression?
a statistical technique that relates a dependent variable to one or more independent (explanatory) variables
44
Advantages of multiple regression
- 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
What is multiple regression?
More than one predictor e.g. a+b1height+ b2age +
46
What is prognosis?
the forecast of future outcomes
47
What is critical appraisal?
the process of assessing and interpreting evidence by systematically considering its validity, results and relevance to your own context
48
Ways to reduce bias in RCTs?
- 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
What is a systematic review?
A research article in which existing evidence on a topic is systematically identified, appraised and summarised according to predetermined criteria
50
What is a meta-analysis?
Statistical method for combining evidence from different sources
51
What is heterogeniety?
a measure of variation between different studies
52
What is sensitivity analysis?
analysis to test the robustness of the findings of primary analysis – looks at the effect of assumptions or variations in approach.
53
What is sample bias?
sample does not represent population of interest
54
What is recall bias?
inaccurate recall of past events/exposures/behaviours
55
What is information bias?
incorrect measurement e.g. miscalibrated machine
56
What is the Hawthorne effect?
participants change their behaviour when they know they are being observed
57
What is attrition bias?
differential dropout from studies e.g. sicker participants drop out so our outcome is only measured on healthier participants
58
What does a confounding variable do?
obscure the real effect of an exposure on an outcome
59
What does risk difference mean?
difference in proportions between groups 0 = no difference
60
What is the risk ratio (aka relative risk)?
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
What is the odds ratio?
odds in one group divided by odds in the other
62
When will median and mean be the same?
When distribution is normal
63
What does parametric mean?
make distributional assumptions
64
Stages of hypothesis testing using stats
Define null and H1 Choose significance level Perform appropriate stats test Find p value
65
What is regression?
a statistical technique that relates a dependent variable to one or more independent variable
66
Regression general eqtn
y=a+bx y variable being predicted x variable predicting (independent) a constant/intercept b gradient/coefficient
67
What is univariable regression?
One predictor
68
What is used to establish causality in non randomised trials?
Strength of association Consistency Specificity Temporality Biological gradient Plausibility Coherence Experiment Analogy
69
What is positivism based on?
objectivity scientific method Empiricism
70
What does interpretivism believe?
social reality can only be understood through social constructions such as language, consciousness and shared meanings and understandings
71
What is quantitative methodology?
Emphasises quantification in collection and analysis of data Deductive approach – theory testing Based on positivism Views social reality as external and objective
72
What is qualitative methodology?
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
Features of quantitative research
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
Features of qualitative research
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
Examples of qualitative data
Interview transcripts Focus groups transcripts Field notes Documents (reports, minutes, plans, blogs, social media posts) Film, photographs, photo-elicitation. Diary entries
76
What is critical appraisal?
the process of assessing and interpreting evidence by systematically considering its validity, results and relevance to your own context
77
What questions could be asked in critical appraisal?
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
What does PICO stand for?
Population Intervention Comparator Outcomes
79
What does internal validity mean?
Accurately measuring those within the trial
80
What does external validity mean?
Generalisable outside trial
81
What is the CASP checklist?
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
How do RCTs attempt to limit bias?
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
Features of a systematic review
Transparent, systematic methods make the process replicable Bias is addressed by assessing each individual study for bias
84
What are the steps of a systematic review?
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
What is a meta-analysis?
Statistical method for combining evidence from different sources
86
What is a sensitivity analysis?
analysis to test the robustness of the findings of primary analysis – looks at the effect of assumptions or variations in approach
87
What is heterogeniety?
a measure of variation between different studies
88
What are the PRISMA guidelines for?
guidelines aimed to improve the reporting of systematic reviews

Phase 1 (18 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions