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Medicine: Scholarship > Year 1 > Flashcards

Year 1 Flashcards

1
Q

Draw the picture

A
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2
Q

Case report case series

A

Quantitative
Observational
Descriptive

Detailed description to generate hypothesis
+ first clues of new diseases
- no proof no comparison

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3
Q

Cross sectional prevalence

A

Quantitative
Observational
Descriptive
Snapshot in time
+ quick and cheap
- cant confirm causation

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4
Q

Ecological

A

Compares exposure with another outcome
+ low cost
- ecological fallacy

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5
Q

Case control

A

Quantitative
Observational
Analytic

Compares cases with controls with history of exposure
+ investigates multiple causal exposures
- susceptible to bias

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6
Q

Cohort

A

Quantitative
Observational
Analytic

focuses on exposure then outcome
+ measures incidence
- expensive and time consuming

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7
Q

Cross sectional analytic

A

Quantitative
Observational
Analytic

Uses odds ratio, snapshot
+ quick and cheap
- single time point

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8
Q

Explanatory RCT

A

Quantitative
Experimental
randomised control trial

Highly controlled conditions, select participants, perfect
+ removes bias
- expensive and time consuming

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9
Q

Pragmatic RCT

A

Quantitative
Experimental
Randomised control trial

More flexible setting, real world
+ removes bias
- expensive and time consuming

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10
Q

Qualitative

A

Non numerical data
Splits into in depth interviews, focus groups and ethnographic studies

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11
Q

Descriptive

A

Case report
Case series
Cross sectional prevalence
Longitudinal
Ecological

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12
Q

Analytic

A

Case control
Cohort
Cross sectional analytic

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13
Q

Bradford hill criteria

A

Analogy
Coherent
Consistency
Experimental evidence
Plausibility
Temporal relationship
Susceptibility
Strength of association

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14
Q

Spurious

A

Variables correlated without relation

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15
Q

3rd variable problems

A

3rd problem linking other 2 variables

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16
Q

Anscombes quartet

A

Statistical relation doesn’t equal distribution

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17
Q

Colliders

A

Exposure and outcome independently influence 3RD variable
Can obscure real/reveal false associations

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18
Q

Selection bias

A

Over or under representation of groups of participants

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19
Q

Observation bias

A

Participants modify behaviour when they’re being watched

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20
Q

Confirmation bias

A

Look for specific outcome

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21
Q

Publication bias

A

P hacking
Number manipulation

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22
Q

Attrition

A

Unequal loss of participants

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23
Q

Ontology

A

What is there to know

24
Q

Epistemology

A

How can we know it

25
Methodology
What procedures to acquire
26
Sources
Which and from who
27
Epidemiology
Study of distributions and determinants of health related states/events and application to disease control
28
Incidence
New cases
29
Prevalence
All cases
30
Ecological fallacy
Failure in reasoning that arises when inference is made about individual based on aggregate data in a group
31
What makes a good question
Population Intervention Comparison/control Outcome
32
Variable tyoes
Dependent Independent Confounding Control
33
Dependent
We measure
34
Independent
We manipulate
35
Confounding
Have hidden effect on DV
36
Measurement scales
Nominal Ordinal Interval Ratio
37
Nominal
Discrete Mutually exclusive No intrinsic order
38
Ordinal
Discrete Intrinsic order
39
Interval
Discrete/ continuous Intrinsic order
40
Central tendency
Makes assumptions about nsture of data
41
Standard deviation
Measure of amount of variation of a set of values 68.27 in 1 95 in 2 99.73 in 3
42
What does sigma assume
Symmetrical data
43
Normal distribution
Symmetrical around the mean
44
Skewed
Loss of symmetry
45
Positive skew
Shifts to the left but the skew is to the right Median< mean
46
Negative skew
Left skew but moves right Mean < median
47
Leptokurtic
High peak at mean
48
Platykurtic
Low peak Flat distribution
49
Absolute risk
Prevalence and incidence rates now vs unit time
50
Attributable risk
Probability difference Exposed vs unexposed Positive intervention = AR reduction
51
Sensitivity
Probability of detecting true positive
52
Specificity
Probability of detecting true negative
53
Odds exposure
Association between outcome and exposure Number exposed/ non exposed cases
54
Odds ratio
Exposed x non exposed controls Divided by Non exposed x exposed controls
55
Odds ratio results
1 = exposure doesn’t affect outcome 1 < increased odds of outcome 1 > decreased odds of outcome

Medicine: Scholarship (1 decks)

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