Collecting the Evidence Flashcards

1
Q

When constructing a clinical question, what factors need to be considered?

A
  • Patient/Problem,
  • Intervention,
  • Comparison to intervention (if any),
  • Outcome
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2
Q

Describe the anatomy of a good question?

A
  • Define precisely whom the question is about?
  • Define which option you are considering and a possible comparison.
  • Define desired/undesired outcome.
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3
Q

What are some of the information resources?

A
  • Systematic reviews/ meta analysis,
  • Clinical practice guidelines,
  • Original article containing primary research data
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4
Q

What are simple rules for navigating a clinical question?

A

1) Start with cochrane reviews, NICE and SIGN guidelines.

2) Then use MedLine (eg, PubMed)

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5
Q

What are the different type of hypothesis?

A

Null hypothesis - Where two data are from the same population and not different.
Alternative hypothesis - Two sets of data are from different populations and are different

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6
Q

What are the different types of quantitative data?

A

Discrete - Can only have certain numerical values.

Continuous - Do not have discrete steps (height and weight)

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7
Q

Describe nominal and ordinal variables?

A

(more data types)
Nominal - eg, alive/dead, blue or green etc.

Ordinal - Objective and subjective

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8
Q

What is the P value?

A

The probability that the null hypothesis is correct. When equal to one is means it is certain.

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9
Q

What does it mean if the P>0.05?

A

Weak evidence against the null hypothesis. Data is consistent with the null hypothesis

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10
Q

What does it mean if the P<0.05

A

Means there is moderate evidence against the null hypothesis in favour of the alternative. The smaller the value then the stronger the evidence

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11
Q

What is the Type 1 errors?

A

Rejecting the null hypothesis when it is true (false positive) meaning P is small.

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12
Q

what is a type 2 wrrors?

A

Not rejecting the null hypothesis when it is false (false negative) - meaning there is no effect when there is

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13
Q

What is power?

A

The power of a test is its ability to reject the null hypothesis when it is false. (Capacity to detect an effect if one is present)

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