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Y1 Tp2 Pgh > 2. critical appraisal > Flashcards

2. critical appraisal Flashcards

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1
Q

Research definition

A

systematic and rigorous process of enquiry which aims to describe phenomena and to develop and test explanatory concepts and theories
- aims to contribute to a scientific body of knowledge

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2
Q

purpose of research

A

identify or test a theory/ hypothesis

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3
Q

what approach is taken for research

A

methodological approach

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4
Q

Audit

A

a count or measurement of current activity/ practice/ performance
- does not address a question or add substantial new knowledge

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5
Q

Evaluation

A

may involve research methods, or audits
examine either methods or activities
- may lead to new understanding

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6
Q

positivist approach

A

deductive, - testing through hypothesis development
testing theory - to give explanation, verification, prediction
objective reality - facts

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7
Q

interpretivist approach

A

inductive - build through empirical examples
developing theory- develop understanding
multiple interpretations of reality - observable symbolic meaning

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8
Q

approach

A

view of the researcher

overall perspective of the study

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9
Q

methodology

A

coherent and defined set of methods

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10
Q

methods

A

practical activity used to achieve the studys aim

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11
Q

scientific method

A 
approach = positivist 
methodology = quantitative, deductive 
methods = surveys, experiments, observations
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12
Q

understanding method ??

A 
approach = interpretivist
methodology = qualitative, inductive
methods = interviews, participants observation, focus groups, document study
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13
Q

healthcare research

A

focus on treatment

implementation
experience (acceptability, is it a good option)
efficiency - cost and equity
effectiveness - efficacy does it work well

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14
Q

how to find which interventions are effective

A

experimental design

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15
Q

how to find out what will happen (prognosis) lead to population studies

A

observational designs

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16
Q

how to find out how things occur or are experienced in a clinical setting

A

qualitative designs

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17
Q

4 characteristics of answerable questions

A

PICO

patient or population
intervention or exposure variable
comparison intervention or exposure variable
outcome

to give a testable hypothesis

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18
Q

hypothesis definition

A

an educated guess or proposition that attempts to explain a set of facts or natural phenomena

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19
Q

T - test

A

T-test compares the means between two samples of normally distributed data

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20
Q

ANOVA

A

• ANOVA compares the means between more than two samples of normally distributed data

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21
Q

odds ratio equation

Study These Flashcards
A

• Odds are calculated by calculating the number of times an event happens by the number of times it
does not happen
• Odds ratios are calculated by dividing the odds of exposure in cases by the odds of exposure in the
control group

Odds of exposure in
cases = a/c
Odds of exposure in
controls = b/d
Odds ratio =
(a/c) / (b/d)
22
Q

Odds ratio values

Study These Flashcards
A

OR of 1 = no difference in risk between the groups
OR > 1 = the rate of the event in experimental group is increased in people who
have been exposed to risk factor
OR < 1 = the rate of the event in experimental group is reduced in people who
have been exposed to risk factor
If confidence interval crosses 1 then the OR is not statistically significant

23
Q

risk ratios equation

Study These Flashcards
A

Risk itself is the probability that an event will happen i.e. divide the number of events by the number of
people at risk
• Risk ratio is calculated by dividing the risk in the treated or exposed group by the risk in the control or
unexposed group

24
Q

risk ratio value

Study These Flashcards
A

RR of 1 = no difference in risk between the groups
RR > 1 = the rate of the event in experimental group is greater than in control
group
RR < 1 = the rate of the event in experimental group is reduced compared to
control group
If confidence interval crosses 1 then the RR is not statistically significant

25
absolute risk reduction
Difference between the event rate in the treatment group to that in the control group. •ARR allows you to differentiate between something being statistically significant vs clinically significant.
26
number needed to treat
Used to find out how often a treatment works rather than just whether it works • Number of people who must be treated to result in benefit for one person Absolute Risk Reduction (undesirable) = Control Event Rate – Experimental Event Rate Absolute Risk Reduction (desirable) = Experimental Event Rate – Control Event Rate
27
mean
Definition: Sum of all the values, divided by the number of values
28
when to use the mean
If the spread of data is normally distributed i.e. fairly similar on either side of the mid-point.
29
median
Definition: The middle point in the dataset that has half the values above and half the values below
30
when to use median
It is used to represent the average when the data are skewed i.e. not symmetrical. Often given alongside interquartile range (more on this later)
31
mode
Definition: The most common value within a dataset
32
when to use the mode
If we need a label for the most frequently occurring event. Some papers make reference to a ‘bi-modal’ distribution i.e. where there are two peaks within the dataset
33
measures of dispersion/ variability - what do they show
❑ Refer to how spread out the data is within a distribution ❑ Can also be called measures of dispersion ❑ Different measures of variability relate to different measures of central tendency
34
measures of dispersion/ variability - 4 examples
Variance Standard Deviation Range InterquartileRange
35
Variance
• Definition: The average of the squared differences from the mean
36
when to use variance
Often as precursor to calculating the standard deviation (more on next slide) to give you an idea of how spread out your data is from the mean. ❑ Samples with low variance have data that is clustered closely about the mean. ❑ Samples with high variance have data that is clustered far from the mean. ❑ Variance is often used to compare the distribution of two data sets.
37
Standard Deviation
Definition: The standard deviation measures the spread of the data about the mean value. It is the square root of the variance.
38
when to use standard deviation
❑ SD is used for data which are normally distributed
39
calculating SD and variance
on the slide
40
Range
Definition: The difference between the maximum and minimum | values in a dataset
41
Interquartile Range (IQR)
Definition: The difference between the upper and lower quartiles
42
cohort studies and epidemiology
Cohort studies are of particular value in epidemiology, helping to build an understanding of what factors increase or decrease the likelihood of developing disease.
43
exposure outcome confounder
research q = is there a causal relationship btw exposure and outcome does confounder influence the outcome is the confounder associated with the exposure
44
Strengths of cohort studies
•Gather data regarding sequence of events; can assess causality. •Examine multiple outcomes for a given exposure. •Can calculate rates of disease in exposed and unexposed individuals over time (e.g. incidence, relative risk). •Observational by nature so participants are not manipulated in any way.
45
Weaknesses of cohort studies
You may have to follow large numbers of participants for a long time. •They can be very expensive and time consuming. •They are not good for rare diseases or diseases with a long latency. •Differential loss to follow up can introduce selection and attrition bias
46
Quantitative Research:
Deductive Objective Generalising
47
Qualitative Research:
Inductive Subjective Contextual
48
• CONVERGENT PARALLEL
1. quantitiative and qualitative Data Collection and Analysis 2. compare or relate 3. interpretation
49
• EXPLANATORY SEQUENTIAL
1. quantitiative data collection and analysis 2. data builds to qualitative data collection and analysis 3. interpretation
50
EMBEDDED
- Quant (or Qual) Design - Quant (or Qual) Data Collection and Analysis - Qual (or Quant) Data Collection and Analysis (before, during or after) = interpretation
51
MULTIPHASE
1. study 1 qualitative 2. informs study 2 quantitative 3. this informs a third study used mixed methods
52
4 mixed method study designs
• CONVERGENT PARALLEL - both data used at once • EXPLANATORY SEQUENTIAL - quant data informs qual data collection - interpretation * EMBEDDED * MULTIPHASE - qual deisgn then quant then mixed methods

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