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RESS yr 1 > Term 1 > Flashcards

Term 1 Flashcards

1
Q

What does PICOT stand for

A

Patients / population - who will be participating
Intervention/interest (exposure) - what is being tested
Comparison - what is the comparison group
Outcome - what is the outcome or endpoint
time - when should outcome be measured

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2
Q

what are the two types of primary research designs

A

qualitative

quantitative

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3
Q

what are the three types of qualitative designs

A

interview
focus group
observational

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4
Q

what are the three types of quantitive studies

A

survey (closed)
observational analytic
experimental

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5
Q

what are the 3 subdivisions of observational analytic

A

cohort study
case-control study
cross sectional study

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6
Q

what are the two subdivisions of experimental studies

A

randomised control trials

non-randomised

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7
Q

what are secondary research designs

A

systematic review or meta analysis

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8
Q

what are the strengths of randomised controlled trials

A

provides evidence of causality

rigorous evaluation of single variable

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9
Q

what are the limitations of randomised controlled trials

A

resource intensive: costs time and money
needs a large number of participants - many studies underpowered
ethical challenges

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10
Q

what is the difference between a prospective and retrospective cohort study

A

In a retrospective cohort study, the group of interest already has the disease/outcome. In a prospective cohort study, the group does not have the disease/outcome,

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11
Q

what are the strengths of cohort studies

A

can establish population-based incidence
can study several outcomes for each exposure
can establish cause effect

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12
Q

what are the limitations of cohort studies

A

resource intensive: costs money and the
large number of people needed
loss to follow up
inefficient for rare conditions

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13
Q

what are the strengths of a case control study

A

small sample size needed

appropriate or studying rare conditions or those with long lag between exposure and outcome

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14
Q

what are the limitations of a case control study

A

exposure assessed after disease occurrence
reliance on records to determine exposure status
highly susceptible to selection bias

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15
Q

what is the purpose of cross sectional studies

A

document health status in specific population at a specific point

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16
Q

what are the strengths of cross sectional studies

A

provides estimates of prevalence of a disease
can identify population healthcare needs
easy fast and inexpensive
no follow up required

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17
Q

what are the limitations of cross sectional studies

A

cannot determine casual relationships
participants may provide social desirable answers
impractical for studying rare diseases

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18
Q

why would you use a qualitative study

A

useful for understanding patients experiences perspectives and views

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19
Q

what are the strengths and limitations of qualitative studies

A

strengths:
enables understanding of patients experiences, unpredictable and insightful findings
limitations:
difficult to generalise, sample selection based on certain experiences
small sample size

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20
Q

what are meta analysis / systematic reviews used for

A

answer a specific clinical question

combines results of previous studies to produce one overall measure of the effect of an intervention

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21
Q

what is the difference between descriptive statistics and inferential statistics

A

descriptive - techniques we use to describe the main features of a data
inferential - statistical inference is the process of using the value of a sample statistic to make an informal guess about the value of the population parameter

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22
Q

what is the difference between categorical and numeral data types

A

categorical - sex, blood type

number - age, weight, number of siblings

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23
Q

what are the two types of categorical data

A

nominal and ordinal

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24
Q

what are the two types of numerical data

A

continuous and discrete

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25
Q

what is the difference between nominal and ordinal

A

nominal - no natural ordering ie sex or blood type

ordinal are ordered in severity or disease stage

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26
Q

what is the difference between continuous and discrete data

A

continuous - no value limitation such as weight

discrete - whole values only such as hospital visits

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27
Q

what are some ways you can present categorical data

A

bar chart
pie chart
frequency distribution

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28
Q

what are ways you can present data that is numerical

A

histogram

box or whisker plot

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29
Q

what does a frequency distribution table show

A

the frequencies and percentages in each group or category

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30
Q

what do these plots/charts show:
bar chart/pie chart
scatterplot
box plots

A

box - display frequencies of categories (categorical data)
scatter - numerica data using two continuous variables
box plots - summary statistics for numeric data

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31
Q

what is positive / negative skew

A

Positive Skewness means when the tail on the right side of the distribution is longer or fatter. The mean and median will be greater than the mode
Negative Skewness is when the tail of the left side of the distribution is longer or fatter than the tail on the right side. The mean and median will be less than the mode.

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32
Q

what is the difference between the mean median and mode

A

mean = average
median - middle number
mode - most common number

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33
Q

what does the mean median and mode not tell us

A

the spread and range of data

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34
Q

what does the range do

A

indicates the extremes - min and max value

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35
Q

what is the standard deviation

A

average of values around a mean

the larger the SD the further away the values re from the mean ie greater spread of data

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36
Q

how do you calculate standard deviation

A 
Calculate the mean
Subtract the mean from every value
Square these new values, and add up
Divide this total by (n-1) = variance
Take the square root = sd
37
Q

what does the interquartile range do

A

summaries the spread of values around the mean

its a range from the lower quartile (25%) to upper quartile (75%0

38
Q

what values do you report for normally distributed data compared to discrete data

A

normal: report mean and standard deviation

skewed data: report median and interquartile range

39
Q

what values are not dependant on the distribution

A

mode and range

40
Q

what are the two types and sub types of research

A

observational - cohort and cross sectional survey

experimental - lab experiments and randomised clinical trials

41
Q

what are the two types of statistical inference

A

estimation - using summary statistics from collected sample to represent the population
hypothesis - making hypothesis and investigating whether there’s evidence against the hypothesis

42
Q

what is a confidence interval

A

gives us a plausible range of values (96% of the times) if we were to repeat the experiment

43
Q

what does correlation measure

A

strength of a linear relationship

44
Q

what are the different types of correlation

A

Ifr> 0 we have a positive correlation; implying that as one variable increases then so does the other.

Ifr< 0 we have a negative correlation; implying that as one variable increases then the other decreases.

Ifr= 0 we have no correlation; implying there is no association between the two variables.

If r=+1 there is a perfect positive correlation.

If r=-1 there is a perfect negative correlation.

45
Q

which correlation due you sue is data is not normally distributed

A

use spearman rank as it is less sensitive to strong outliers

46
Q

when do you not use correlation

A

when data is not liner or there are distinct sub groups

47
Q

which tests would you use for one numerical and one categorical association

A

indépendant staples t test - two sample t test

Mann-Whitney-U test

48
Q

what are the limits in a two-sample t test

A

-2 - +2

49
Q

what are the three assumptions of two sampled t tests

A

two independent groups
numerical variable is normally distributed
similar standard deviations

50
Q

how would you examine an association between two categorical values such as survival and treatment

A

proportional difference

51
Q

what are the three types of proportional differences for measuring two categorical associates

A

chi squared - standard
chi squared - yates correction
fishers exact test

52
Q

what are the assumptions for chi squared tests

A

two independent groups
number of expected values in each of four cells should be greater than 1
in three of four cells the expected value should be greater than 5

53
Q

what is the problem with using yates correction

A

For small sample sizes the chi-squared test is too likely to reject the null hypothesis. A continuity correction can be made to allow for this.

54
Q

what is wrong with using fishers exact test

A

If a contingency table fails to meet the conditions required for the chi-squared test then Fisher’s exact test can be used.

55
Q

what do inferential analyses do

A

draw conclusions about populations from staples of data drawn from the population

56
Q

what does a sample do

A

measurements are used to estimate population parameters

57
Q

what is standard error

A

represents the average distance between an estimate and its population parameter

58
Q

how do you calculate standard error

A

Calculate the mean (of all the samples’ means)
Subtract the overall mean from every sample’s mean
Square these new values, and add up
Divide this total by (n-1) = sampling variance
Take the square root = standard error (= standard deviation of the sampling distribution of the mean)

59
Q

how do you calculate the standard error of man and what does it tell us

A

SE = standard deviation / square root of number of samples
it will always be smaller than the standard deviation
the larger the sample size the smaller the standard error

60
Q

how does SE show us 95% confidence intervals

A

estimates the range that is most likely to occur - 95% of all sample means will fall between our sample mean value

61
Q

how would you calculate 95% confidence for the upper and lower interval

A

Using our example of n=10 GP surgeries, mean=4, SEM=0.79

The 95% confidence interval for the GP surgeries data is

4 - (1.96 x 0.79) = 4 -1.58 = 2.42 (Lower limit)
4 + (1.96 x 0.79) = 4 + 1.58 = 5.58 (Upper limit)

The interval from 2.42 to 5.58 is therefore called the 95% confidence interval (95% CI) for the mean

62
Q

what is null hypothesis

A

there is no difference between the two groups

63
Q

what does a p value do

A

significance level 0.05 - allows us to reject or accept null hypothesis

64
Q

what is the difference between a large and small p value

A

large p value: quite likely to see results by chance
cannot be sure of a difference in the target population
small p value:
unlikely to see results by chance
there may be a difference in the target population
cuts off point is arbitrary
if very unlikely then reject the null hypothesis

65
Q

what does p value greater than 0.05 mean

A

no statistical difference - accept the null hypothesis

66
Q

what is the relationship between p value and 95% CI

A

If 95% CI of a mean difference does not contain zero, reject the null hypothesis at statistical significance (p-value of 0.05) of 5%

67
Q

what are the different uses for p value and confidence interval

A 
p value: 
weight of evidence to reject null hypothesis
no clinical interpretation 
confidence interval: 
can be used in hypothesis testing 
clinical interpretation
68
Q

what is cares

A 
clinical 
assessment 
reasoning 
ethics 
safety
69
Q

what is qualitative research

A

collection and analysis of non-numerical information

why and how of population behaviours experiences etc

70
Q

what are the general differences between qualitative and quantitative data

A

quant - findings are generalisable

qualt - unique and insightful

71
Q

what are the types of qualitative research methods

A 
Content Analysis
Grounded Theory
Framework Analysis
Protocol Analysis
Ethnography
Phenomenology
Discourse Analysis
Conversation Analysis
Thematic analysis
Interpretative Phenomenological Analysis (IPA)
72
Q

what is a theme

A

themes are recurrent and distinctive features of participants accounts which the researcher sees as relevant to the research question
it can reflect a pattern of response which is determined by the researchers judgement

73
Q

what is the value of qualitative studies

A

enables understanding of patients choices and why they did this

74
Q

what is AnSWeR

A

antenatal screening web resource

75
Q

what are the limitations of findings in qualitative research

A

generalisability
sample selection based on certain experiences (not random)
sample size often small
reliability - findings based on interpretations by the researcher

76
Q

what are the strengths of qualitative findings

A

robust methodologies
offers in depth understanding of diverse perspectives
unpredictable and insightful
usually unobtainable using a quantitative approaches based on preconceived ideas

77
Q

what is a systematic review

A

uses systematic and explicit methods to identify, select and critically appraise relevant evidence
involves collection and analysis of data from the studies that are included in the review

78
Q

what is meta-analysis

A

stat technique which summarises the results of several studies into a single estimate

79
Q

what is the relationship between systematic reviews and meta analysis

A

systematic reviews often but not always include meta analysis

80
Q

why do we have systematic reviews

A 
information management 
reduction of subjectivity / bias 
increase power and precision 
identify gaps in research 
efficient use of resources
81
Q

what are the criteria for Mulrows review quality

A 
purpose 
data identification 
study selection criteria 
validity assessment 
qualitative/quantitative synthesis 
summary 
future directives
82
Q

what is cumulative meta analysis

A

repeated performance of meta analysis whence a new relevant trail becomes available for inclusion

83
Q

what are the key stages in a systematic review

A

define the question
look for all studies reliably addressing the question
sift the studies to select relevant ones
assess the quality fo the studies
calculate results for each study
interpret results

84
Q

what specifically makes a systematic review

A

was there a clear research question
was protocol developed
are the inclusion criteria clearly stated

85
Q

what is heterogeneity

A

between study differences: some random difference between studies is expected due to random variation

86
Q

what are the there types of heterogeneity

A

Clinical: different patient populations, interventions, follow-up times, choice and measurement of outcomes.
Methodological: different study designs, quality issues (e.g. not all trials described as RCTs may have adequately randomised patients)
Statistical: numerical variation in treatment effects

87
Q

what is publication bias

A

the selective bias of research evidence based upon the results of that research
positive studies more likely to be published than negative ones
english language, availability

88
Q

what are the four conclusion of systematic review

A

we now know for sure that it works
we now know for sure it doesn’t work is no better than..
the research is of such poor quality or is so biased that
there is no research

RESS yr 1 (1 decks)

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