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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
Q

Methodology

A

What procedures to acquire

26
Q

Sources

A

Which and from who

27
Q

Epidemiology

A

Study of distributions and determinants of health related states/events and application to disease control

28
Q

Incidence

A

New cases

29
Q

Prevalence

A

All cases

30
Q

Ecological fallacy

A

Failure in reasoning that arises when inference is made about individual based on aggregate data in a group

31
Q

What makes a good question

A

Population
Intervention
Comparison/control
Outcome

32
Q

Variable tyoes

A

Dependent
Independent
Confounding
Control

33
Q

Dependent

A

We measure

34
Q

Independent

A

We manipulate

35
Q

Confounding

A

Have hidden effect on DV

36
Q

Measurement scales

A

Nominal
Ordinal
Interval
Ratio

37
Q

Nominal

A

Discrete
Mutually exclusive
No intrinsic order

38
Q

Ordinal

A

Discrete
Intrinsic order

39
Q

Interval

A

Discrete/ continuous
Intrinsic order

40
Q

Central tendency

A

Makes assumptions about nsture of data

41
Q

Standard deviation

A

Measure of amount of variation of a set of values
68.27 in 1
95 in 2
99.73 in 3

42
Q

What does sigma assume

A

Symmetrical data

43
Q

Normal distribution

A

Symmetrical around the mean

44
Q

Skewed

A

Loss of symmetry

45
Q

Positive skew

A

Shifts to the left but the skew is to the right
Median< mean

46
Q

Negative skew

A

Left skew but moves right
Mean < median

47
Q

Leptokurtic

A

High peak at mean

48
Q

Platykurtic

A

Low peak
Flat distribution

49
Q

Absolute risk

A

Prevalence and incidence rates now vs unit time

50
Q

Attributable risk

A

Probability difference
Exposed vs unexposed
Positive intervention = AR reduction

51
Q

Sensitivity

A

Probability of detecting true positive

52
Q

Specificity

A

Probability of detecting true negative

53
Q

Odds exposure

A

Association between outcome and exposure
Number exposed/ non exposed cases

54
Q

Odds ratio

A

Exposed x non exposed controls
Divided by
Non exposed x exposed controls

55
Q

Odds ratio results

A

1 = exposure doesn’t affect outcome
1 < increased odds of outcome
1 > decreased odds of outcome

Medicine: Scholarship (1 decks)

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