Brainscape's Knowledge GenomeTM

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


See full index

RESS Term 1 Lectures and Tutorials > RESS Term 1 Lectures > Flashcards

RESS Term 1 Lectures Flashcards

1
Q

What is evidence based medicine?

A

The conscientious use of current best evidence in making decisions about patient care

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

What is a research question?

A

A question that directs and focuses your research

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

What is an acronym that can help you develop a research question?

A

PICOT
Patients/Population - who will be participating?
Interest - what is being tested?
Comparison - what is the comparison group?
Outcome - what is the outcome or endpoint?
Time - when should outcome be measured?

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

What is a non-randomised control trial?

A

An ‘uncontrolled’ study - no control group

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

What are the strengths of Randomised Clinical Trials? (RCTs)

A
  • provide evidence of causality- more chance of having ‘impact’
  • rigorous evaluation of a single variable
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What are the limitations of Randomised Clinical Trials? (RCTs)

A
  • resource intensive: costs, time and money
  • needs a large number of participants- many studies underpowered
  • ethical challenges
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is a cohort study?

A

Cohort studies are a type of medical research used to investigate the causes of disease and to establish links between risk factors and health outcomes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are the limitations of cohort studies?

A
  • resource intensive: costs time and money
  • needs a large number of participants
  • loss to follow up
  • inefficient for rare conditions
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a cross-sectional study?

A

A document health status in a specific population at a specific point
Provides a snapshot, patients not followed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
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
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What are the weaknesses of cross sectional studies?

A
  • Cannot determine causal relationships
  • Participants may provide socially desirable answers
  • Impractical for studying rare diseases
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What are the strengths of qualitative studies?

A
  • Enables an understanding of patients’ experiences/perspectives
  • Unpredictable and insightful findings
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What are the limitations of qualitative studies?

A
  • difficult to generalise
  • sample selection based on certain experiences
  • small sample size
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Which study design would you use to answer the following:

  1. How common is oestrogen treatment in women after menopause?
  2. What are women’s experiences of taking oestrogen treatment?
  3. Is taking oestrogen after menopause associated with a higher risk of breast cancer?
  4. Does drug X, hormone treatment , reduce the symptoms of menopause?
A
  1. Cross sectional - to assess prevalence of exposure
  2. Qualitative - to explore patient experiences
  3. Cohort study - to evaluate association of exposure and disease
  4. RTC - to establish the effect of this intervention
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
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
17
Q

What is statistical inference?

A

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
18
Q

What is a variable?

A

A particular characteristic being studied

19
Q

Explain the 2 main data types?

A
  1. Categorical - can only be assigned to a number of distinct categories e.g sex (male or female)
  2. Numerical - takes a numerical value e.g age, weight
20
Q

What can categorical data be divided into?

A
  1. Nominal - no natural ordering e.g sex, blood type

2. Ordinal- ordered categories e.g severity or disease stage

21
Q

What can numerical data be divided into?

A
  1. Continuous - no value limitation e.g weight 87.2345kg

2. Discrete - whole values only e.g number of hospital visits

22
Q

What type of data do bar charts and pie charts show?

A

Categorical

23
Q

What type of data do scattergraphs show?

A

Relationships within numeric data (using two continuous variables)

24
Q

What type of data do box plots show?

A

Summary statistics for numeric data

25
Q

What type of data do histograms show?

A

Numerical data

26
Q

How do you calculate the median?

A
  1. Sort observations in numerical order
  2. Find the mid point
  3. If two values lie at the mid point, average them
27
Q

What does the standard deviation tell us about the data?

A

Summarises the average spread of values around the mean

The larger the SD, the more spread out the values

28
Q

Which data values should you report for normally distributed data?

A

Report mean and SD

29
Q

Which data values should you report for skewed data?

A

Report median and inter-quartile range

30
Q

What is a parameter?

A

A particular characteristic of the population that we are interested in e.g the population mean

31
Q

What are the two common forms of statistical inference?

A
  1. Estimation - the process of using summary statistics from collected sample data to represent the population
  2. Hypothesis testing - making a hypothesis about a population and then collect sample data toes whether it gives evidence against the hypothesis
32
Q

What are the 5 steps for calculating standard deviation?

A
  1. Calculate the mean
  2. Subtract the 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
33
Q

What is the standard error?

A

The standard deviations of different estimates from repeated samples of a population
Standard error of the estimate represents the average distance between an estimate and its population parameter

34
Q

What is the frame work for hypothesis testing?

A
  • State the null and alternative hypothesis
  • Decide a level of significance (p-value cut-off)
  • Define and evaluate a test statistic
  • Calculate the p-value
  • Interpret the results
35
Q

What is the difference between estimation and hypothesis testing?

A
  • estimation is used to generate better understanding of the likely true value of a measurement and the degree of uncertainty surrounding this estimate
  • hypothesis testing evaluates whether our data provide confidence that our sample estimate is different from another “population” value
36
Q

What are the two types of research?

A
  1. Observational:
    - cohorts
    - cross sectional surveys
  2. Experimental:
    - lab experiments
    - randomised clinical trials
37
Q

What is correlation?

A

Correlation measures the strength of the linear relationship between two numerical variables

38
Q

When do we use spearman correlation coefficient?

A

When data is not normally distributed

39
Q

When do we use Pearson correlation coefficient?

A

to measure the association between two normally-distributed variables

40
Q

What is proportion difference?

A

Measures the strength of the relationship between two categorical variables

41
Q

When is chi squared used?

A
  • To work out association between two categorical variables (in two independent groups)
  • difference between two proportions
42
Q

Why is the chi squared test sometimes not accurate?

A
  1. Continuity correction (Yates’s correction)
    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.
  2. Fisher’s exact test
    If a contingency table fails to meet the conditions required for the chi-squared test then Fisher’s exact test can be used.
43
Q

What test do we use if theres one continuous variable and one binary variable?

A

T test

44
Q

Explain the structure of a research paper?

A
  1. Title - clearly describes content
  2. Abstract - brief summary of the paper
  3. Introduction - explains the problem
  4. Methods- describes what was done
  5. Results - describes the results obtained
  6. Discussion - interpretation and implications
  7. References

RESS Term 1 Lectures and Tutorials (1 decks)

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