EVIDENCE BASED MEDICINE Flashcards
What are the steps in Evidence Based Psychiatry?
5 A’s
Ask - a relavent question about the patient
Access - database of available research
Appraise - look through research and appraise articles
Apply - apply what you’ve learned to your patient
Assess - evaluate your performance
How do you formulate a clinical question?
PICO
Patient/problem
Intervention
Comparison
Outcome
When would you use a case report/case series?
For some rare disease, that you want to do cheaply and quickly. But you cannot draw meaningful conclusions about cause and effect.
When would you use a Cross Sectional Study?
To determine prevelance. You can demonstrate cause and effect also.
Unfortunately you can get something called Prevelance-Incidence Bias - a risk factor appears to have caused a disease when it could just be something that alters duration or prognosis.
When do you use Cohort Studies?
Take 2 groups (defined by whether or not they were exposed to a risk factor). Compare who develops a disease with who doesn’t in both groups to give you an idea of whether exposure results in development of the disease.
PROSPECTIVE
What is Central Tendency and how is it measured?
- It is a description of a data set using a single value that represents the centre of a data set.*
- Mean, Median, Mode*
Mean?
Sum of all measurements divided by the number of elements.
Best for normally distributed data.
Painfully skewed by Outliers.
Median?
Middle value in a data set. Not affected by outliers (therefore can be used with NON NORMAL or skewed distributions). Okay when dealing with ordinal data.
Mode?
Most often occuring data.
What is Dispersion and how is it measured?
Dispersion is the spread about the mean. Measured by :
- SD (which is the square root of variance)
- Standard Error of the Mean
- Quartiles
- Percentile
- Range
Skewness and Kurtosis
Skewness - a measure of assymetry
Kurtosis - refers to the degree of the presence of outliers (spread wide or thin tailed).
Variance
Statistical measure of variations
Standard Deviation
Measure of spread about the mean.
Parametric vs Non Parametric
Parametric - makes assumptions about the distribution of the population from which the data was taken. The assumption is usually that the data is NORMALLY DISTRIBUTED.
Non parametric - does not make assumptions about the distribution. Better used to non normally distributed data or when making the assumption of normallity is worrisome (small sample size).