# data[].attributes.body
1. Reflection
2. Ask a clinical ?
3. Search for Evidence
4. Critically Appraise
5. Implement Evidence
6. Evaluate the change
7. Disseminate

# data[].attributes.body
perceptions, experiences, understanding, beliefs
Rich in depth data, important if nothing else is known.
Small  sample size, open to selection bias

# data[].attributes.body
Test an intervention, contains study arm (treatment/control)
Best to confound variables, best to control bias
Expensive, resource and time intensive, limited generalisability to the whole population

# data[].attributes.body
follow participant over time , can collect data of multiple points in time
Multiple endpoints, large sample sizes, reduced selection bias & allows more confidence in conclusions
Long time scale, expensive

# data[].attributes.body
association between 2 factors, data collected at a single point in time, surveys/questionnaires
Large sample size, fast and cheaper
Low response rate open to selection bias, silent majority is missed, self-reported data (participant needs to tell the truth)

# data[].attributes.body
1. Selection
2. Performance
3. Detection
4. Confirmation
5. Attrition
6. Reporting

# data[].attributes.body
- Allocation concealment (envelope)
-Randomisation (computer)

# data[].attributes.body
collates what is already known about a topic
can be meta analysis, narrative review, qualitative synthesis

# data[].attributes.body
CASP, JAMA, CONSORT, STROBE

# data[].attributes.body
1 - Right type of study
2 - Reliable study