Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

RESS > Term 1 (Esme) > Flashcards

Term 1 (Esme) Flashcards

1
Q

What is PICOT? What does it stand for?

A

A framework for evidence-based research questions P - Patients / population - who will be participating I - Intervention/interest (exposure) - what is being tested C - Comparison - what is the comparison group O - Outcome - what is the outcome or endpoint T -Time - when should outcome be measured

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

What are the possible outcomes investigated using PICOT?

A
  • Mortality/morbidity - Quality of life - Change in behaviour
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Example of PICOT in clinical scenario: You are concerned about the growing number of overweight and obese patients seen in your clinical practice. You want to know if introducing dietary advice within consultations would effect change.

A

P - Adults who are obese/overweight I - Dietary advice (behavioural) C - Current practice (no dietary advice) O - Decrease in weight obesity T - After 1, 3 and 6 months Outcome question –> Is dietary advice more effective than no dietary advice in decreasing weight in overweight/ obese patients?

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

What are the stages of practising evidence based medicine (EBM)?

A
  1. Formulating clinical question 2. Searching for evidence 3. Appraising evidence 4. Applying evidence to practice 5. Evaluating evidence use
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Why is EBM important?

A

Clinical judgement Relevant scientific evidence Patients values and preferences

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

What does RESS stand for?

A

Research, Evaluation and Special Skills

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

What are the 2 types of primary research designs?

A
  1. Analytic 2. Descriptive
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What are the 2 types of analytic research?

A
  1. Experimental 2. Observational analytic
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are the 2 branches of experimental analytic research?

A
  1. Randomised control trials 2. Non-randomised control trials
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What are the 3 branches of observational analytic research?

A
  1. Cohort study 2. Cross sectional 3. Case-control study
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What are the 2 types of descriptive research?

A
  1. Survey (cross-sectional) 2. Qualitative
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What are the 3 types of qualitative study?

A
  1. Interview study 2. Focus group study 3. Observational study
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is a 2ary research design?

A

Systematic review / meta analysis

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

What did Swift et al. find in his 2009 study about the usefulness of probability and statistics?

A

90% of respondents in their survey of 130 doctors

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

Does GMC require new doctors to have statistical skills?

A

Yes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What are the stages of data analysis?

A
  1. Collect 2. Organise 3. Present 4. Analyse 5. Interpret 6. Conclusion
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Statistics refers to a group of scientific methods used to…

A
  1. Collect data 2. Analyse and interpret data 3. Make conclusions or inferences
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What are descriptive statistics?

A

Techniques we use to describe the main features of a data

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

What are inferential statistics?

A

Statistical inference is the process of using the value of a sample statistic to make an informed guess about the value of a population parameter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What is purpose of analysing data?

A

Raw data may not be easy to understand Simplify large amounts of data Reduce lots of data into a simpler summary Show the patterns in the data, Enable comparison of groups

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

What is a variable?

A

A particular characteristic being studied. It is called a variable because it may vary from patient to patient (or by other units of measurement) (age, sex, status etc)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

What does a data set contain?

A

Variables (columns) and observations (rows)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

What does choosing appropriate descriptive statistics depend on?

A

Data type for variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

What are the 2 main groups that data can fall into?

A

Categorial and Numerical

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

What is ‘categorical’ data?

A

Can only be assigned to a number of distinct categories E.g: - Sex (male or female) - Blood type (A, B, AB or O0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

What is numerical data?

A

Takes a numerical value (can be categorised if appropriate) E.g: - Age - Weight - Number of siblings

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

What are the 2 types of categorical data?

A

Nominal and ordinal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

What is nominal data?

A

No natural ordering (e.g. sex, blood type)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

What is ordinal data?

A

Ordered categories (e.g severity, disease stage)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

What are the 2 types of numerical data?

A

Continuous and discrete

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

What is continuous data?

A

No value limitation (e.g. weight –> 87.234568kg)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

What is discrete data?

A

Whole values (e.g. number of hospital visits)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

Data types and where to start: Do I have numbers or text?

A
  1. Numbers –> continuous or discrete data Text –> nominal or ordinal categories
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

When can weight (continuous) be ‘ordinal’ instead?

A

Low, normal, high

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

Data types examples: 1. Weight (87.2 kg) 2. Sex (male) 3. Number of children (4) 4. Symptoms (mild, moderate severe) 5. Disease stage (I, II, III) 6. BMI (23.2) 7. BMI (normal) 8. Pain (absent, mild etc)

A
  1. Continuous 2. Nominal 3. Discrete 4. Ordinal 5. Ordinal 6. Continuous 7. Ordinal 8. Ordinal
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
36
Q

What is quantitative data?

A

Essentially numbers –> measurements made with instruments such as rulers, balances, beakers, thermometers etc These results are measurable

37
Q

What is metric data?

A

Numerical, quantitative (i.e. numbers)

38
Q

What is qualitative data?

A

Not numbers

39
Q

What is interval/ratio data?

A
  • Both numeric, both have known meaningful increments - Interval data do not have a true zero - Continuous, using our definitions
40
Q

What type of data would you use a frequency distribution table to present?

A

Categorical data - shows the frequencies and percentages in each group or category

41
Q

What type of data would you use a bar chart to present?

A

Categorical data –> displays the frequencies of categories

42
Q

How are bar charts made?

A

A bar is drawn for each category, with length proportional to the frequency in that category

43
Q

How do bar charts differ from histograms?

A

Bars are separated by gaps (unlike histograms) - indicates variable is categorical

44
Q

What type of data would a pie chart be used to present?

A

Categorical data –> displays frequencies of categories

45
Q

How are pie charts made?

A

The area of each section is proportional to the frequency of the category

46
Q

What type of data are histograms used to present?

A

Numerical data

47
Q

What can histograms also present?

A

The distribution of numerical data

48
Q

Positive skew on histogram

A

Right

49
Q

Negative skew on histogram

A

Left

50
Q

Describe shape of normal distribution on histogram

A
  • ‘Bell shaped curve’ - Symmetric
51
Q

What type of data are scatterplots used to present?

A

Display relationships with numeric data (using 2 continuous variables)

52
Q

What type of data are box plots used to present?

A

Displays summary statistics for numeric data

53
Q

E.g. weight and height; expect taller people to weigh more. Which is the dependent/independent variable?

A

Height is the explanatory variable (independent) Weight is the outcome variable (dependent)

54
Q

What are the strengths of randomised controlled trials?

A

Provides evidence of causality rigorous evaluation of single variable

55
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
56
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

57
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
58
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
59
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
60
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
61
Q

What is the purpose of cross sectional studies?

A
  • Document health status in specific population at a specific point
62
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
63
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
64
Q

Why would you use a qualitative study?

A

Useful for understanding patients experiences perspectives and views

65
Q

What are the strengths of qualitative studies?

A
  • Enables understanding of patients experiences - Unpredictable and insightful findings
66
Q

What are the limitations of qualitative studies?

A
  • Difficult to generalise - Sample selection based on certain experiences - Small sample size
67
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
68
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

69
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.

70
Q

What is the mean?

A

The sum of all the values divided by the total number of values

71
Q

What is the median?

A

Mid-point - the value about and below which 50% of the measurements lie If 2 values lie at the mid point, average them

72
Q

What is the mode

A

Most common value (can have more than one)

73
Q

What does the mean, median and mode not tell us?

A

The spread and range of the data

74
Q

What are the 4 measurements of dispersion of data?

A
  1. Variance 2. Standard deviation 3. Range 4. Inter-quartile range
75
Q

What is range? How is it calculated?

A

Indicates extremes within which all measurements lie 1. Sort observations in numerical order 2. Express the range as the minimum to the maximum value

76
Q

What is standard deviation?

A

Summarises the average spread of values around the mean

77
Q

What does a larger standard deviation imply?

A

The more spread out the values are (further away from the mean)

78
Q

How is the standard deviation calculated?

A
  1. Calculate mean 2. Subtract mean from every value 3. Square these new values and add up 4. Divide this total by (n-1) = variance 5. Take the square root = SD
79
Q

What is the interquartile range?

A

Summarises the spread of values around the median. A range from the lower quartlie (25%) to upper quartile (75%)

80
Q

How is the IQR calculated?

A
  1. Order the data
  2. Divide into 2 halves using the median (exclude median)
  3. Lower quartile = median of lower half
  4. Upper quartlie = median of upper half
81
Q

How is IQR calculated if we start with an odd number of observations?

A
82
Q

Which measures would you report for normally distributed data?

A

Report mean and SD

83
Q

What measures should be reported for skewed (or discrete) data?

A

Median and IQR

84
Q

Which data measurements are not dependent on distribution?

A

Mode and range

85
Q

What are boxplots graphical representations of?

A

The average, spread and extreme volumes.

They display the:

  • Median
  • IQR
  • Range

If data are normally distributed then median = mean

86
Q

Boxplot for when:

  • Median = 3.5
  • IQR = 2 to 6
  • Range = 1 to 9
A
87
Q

Descriptive statistics in research papers

A

Manning et al. 1998:

  • Means and standard errors are reported as measures of central tendency and dispersion.
  • Standard errors

Austin et al 2001:

  • Descriptive statistics used to describe participants characteristics
  • “The mean age of the males was 20.1 years (standard deviation 1.1 years) and the mean age of the females was 20.6 years (standard deviation 2.5 years)”.
88
Q
A

RESS (2 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions