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MED 106- RESEARCH METHODS AND ESSENTIAL MEDICAL STATISTICS > 32. INTERNAL VALIDITY > Flashcards

32. INTERNAL VALIDITY Flashcards

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USMLE® Step 1 flashcards
1
Q
  1. According to the World Health Organisation (WHO), how would we define Interpersonal Education (IPE)?
A

THIS KIND OF EDUCATION OCCURD WHEN:
- two or more professionals learn about, from and with
each other
- this enables effective collaboration
- it improves the health outcomes

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2
Q
  1. What does Clinical and Public Health work involve?
A
  • it involves a Multi-disciplinary team

THIS IS COMPOSED OF THE LIKES OF:
- doctors
- nurses
- psychologists
- environmental specialists
- legal representatives
- counsellors
- etc.

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3
Q
  1. Look at this study example.
    How do you know if this is a good study and if it applies to your Patient Population?
A
  • it adheres to the necessary ethical research guidelines
  • it has a long and constant follow-up period
  • hospital records and national cancer registries were
    used in this study
  • the sample used was made up of Health Professionals
  • this means that they have some knowledge on how to
    fill out a Questionnaire correctly and in an unbiased
    manner
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4
Q
  1. What is Internal Validity?
A

THIS RELATES TO:
- how well a study is conducted
- it looks at how the study is designed
- it looks at how the data is collected

IT LOOKS AT WHETHER THE STUDY RESULTS ARE VALID:
- in terms of whether the study has found the truth
about the specific source population

IT LOOKS AT IF:
- there is really an exposure-outcome association
- or if the results are explained by something else

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5
Q
  1. What is External Validity?
A

THIS RELATES TO:
- how applicable the findings are in the real world
- how applicable it is to your population or the
subgroup being analysed

IT LOOKS AT IF:
- the results can be generalised to the general
population
- or if there are other similar populations

IT LOOKS AT IF THE RESULTS CAN BE USED:
- for a broader group of patients

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6
Q
  1. How do we relate variables to Internal Validity?
A

INTERNAL VALIDITY IS THE MEASURED BY:
- the extent to which you are able to say that only the
independent variable has caused a change in the
dependent variable

THIS MEANS THAT:
- no other variable is responsible for this change

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7
Q
  1. In order to judge Validity, which three factors do we look at when it comes to their effect on the results?
A
  1. Chance
  2. Bias
  3. Confounding
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8
Q
  1. What is Chance?
A
  • this is a type of Random (Sampling) Error
  • it is due to the random nature of the sampling

THE ROLE THAT CHANCE PLAYS IN OUR RESULTS:
-is determined by the p-value
- and by the 95% Confidence Interval

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9
Q
  1. How do we determine if the Validity of our results has been affected by Chance?
A
  1. CHECK THE FINDINGS FOR STATISTICAL SIGNIFICANCE
    • this is based on the p-value result
    • it is also based on the Confidence Interval values
  2. IF THE EXPOSURE-OUTCOME ASSOCIATION IS
    STATISTICALLY SIGNIFICANT
    • we can conclude that our finding is not by CHANCE
    • there is in fact an exposure-outcome association in
      the population
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10
Q
  1. What is Bias?
A
  • this is a type of Systematic Error
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11
Q
  1. How do we minimise the influence of Chance in our findings?
A
  • we take a large Sample
  • this sample has to be representative of the Population
    as a whole

A LARGE SAMPLE:
- will reduce the Standard Error
- it increases the study power
- it gives more precise estimates

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12
Q
  1. In this study, what can be said about the presence of Chance (Random Error)?
A

THE 95% CONFIDENCE INTERVAL:
- does not include the value 1
- this is in the case of All-cause Mortality

THE RESULTS IN THIS STUDY:
- are statistically significant

WE CAN CONCLUDE WITH HIGH CERTAINTY:
- that the observed association between the
Mediterranean- Diet and Prostate Cancer is NOT due
to Chance

THE VALIDITY OF THIS STUDY:
- is not compromised by Random Error

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13
Q
  1. What are the two types of Bias?
A
  1. Selection Bias
  2. Information Bias
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14
Q
  1. Define Selection Bias.
A
  • these are errors
  • they happen in the process of sampling

THEY ARE A RESULT OF:
- selecting a non-representative sample
- this leads to any derived estimate having a high
likelihood of being biased

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15
Q
  1. Define Information Bias.
A
  • these are errors
  • they happen in the process of data collection

THIS IS A RESULT OF:
- inaccurately assessing the exposure or outcome
variables

EXAMPLE:
- taking specific measurements in a study that are
inaccurate
- they are non-representative of the sample
- this can be done without the researcher realising

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16
Q
  1. What are some examples of Information Bias?
A
  1. RECALL BIAS
    - this is when people struggle to remember information
    - this can alter the results of the study
  2. INTERVIEWER BIAS
    - the researcher unintentionally brings in Bias by asking
    questions in a specific way
17
Q
  1. How is Bias determined in a study?
A
  • this is not a straightforward process

THE RESEARCHER:
- needs to to be reflective and self-critical
- this is with regards to the appropriateness of the
sample they are choosing
- as well as with the measurements that they are taking

18
Q
  1. What kind of samples are always expected to have Bias in them?
A

SAMPLES COLLECTED USING:
- Convenience Sampling

MEASUREMENTS RESULTING FROM:
- participant self-reports

19
Q
  1. How do we minimise the influence of Bias in our findings?
A
  1. CHOOSING A SAMPLE:
    - that is representative of the Source Population that
    we want to investigate
    - this will minimise Selection Bias
  2. CHOOSING ASSESSMENT TOOLS
    - that have high accuracy
    - these tools need to be valid and reliable
    - this minimised Information Bias
  3. MAKING A THOROUGH INVESTIGATION
    - of the accuracy of the data collected
    - this should be done during the data collection process
    - it should also be done during the Data Analysis
  4. DATA CLEANING
    - this is an analysis of the data during Data Analysis
    - it removes any biased data
    - it does this by looking at abnormalities and outliers
    - makes the results more reliable
20
Q
  1. In this study, what can be said about the presence of Bias?
A
  1. THE STUDY SAMPLE IS LARGE
    - it is a Random Study of 47 867 individuals
    - it was collected randomly
    - this means that there is no Selection Bias
  2. THE STUDY INVOLVES SELF-REPORTING
    - this is done by the participants with regard to their
    Mediterranean diet food intake
    - Measurement Error (Bias) in the exposure assessment
    is very likely
  3. THE INFORMATION ABOUT THE PROSTATE CANCER
    - was taken through National Health Registries
    - and through Hospital Records
21
Q
  1. Define Confounding.
A
  • this is when there is a factor or combination of factors
  • these explain all (or part) of the association between
    an Exposure and Outcome
22
Q
  1. How does Confounding effect the study?
A
  • it can greatly compromise the validity of the study
  • it can distort the estimate of the potential association
  • it can mask a true association
  • it can make a false association appear
  • even if an association does not exist
23
Q
  1. How do we determine if our results are affected by Confounding?
A
  1. UNDER NON-EXPERIMENTAL CONDITIONS:
    - it should be expected that Confounding is present
    - it will affect the results to some degree
  2. IF THERE IS AN UNEXPECTED RESULT OBTAINED
    • based on previous evidence
    • we can assume that there is Confounding present
  3. IF THERE IS SOMETHING THAT DOES NOT MAKE
    SENSE BIOLOGICALLY
    - we can assume that there is confounding present
24
Q
  1. What is an example of a Non-Experimental Condition?
A
  • Observational studies
25
Q
  1. How do we minimise the influence of Confounders in our studies?
A
  1. MAKE A LIST OF POTENTIAL CONFOUNDERS
    - for a given exposure-outcome association
  2. ADJUST THE POTENTIAL CONFOUNDERS
    - this is done during Data Analysis
    - it will give Confounder-adjusted estimates
    - these are free from the confounding effects
  3. ALWAYS BE CAUTIOUS OF RESIDUAL CONFOUNDING
    - even after adjusting the data
26
Q
  1. In this study, what potential confounders did the Researchers adjust their results for?
A
  • age
  • BMI
  • physical activity
  • smoking status
  • ethnicity
  • height
  • diabetes
  • family history of PCa
  • vitamin supplement used
27
Q
  1. In this study, what can be said about the presence of the Confounders??
A
  1. THE MOST IMPORTANT POTENTIAL CONFOUNDERS
    - were identified and adjusted for
  2. RESIDUAL CONFOUNDING
    - could still be present
    - this is due to the unknown confounders
    - as well as any imprecise assessments that could have
    happened with regards to the existing confounders
  3. THE INTERNAL VALIDITY OF THE STUDY
    - could be compromised
    - by the possible presence of Residual Confounding
    - it is not compromised to a large extent

MED 106- RESEARCH METHODS AND ESSENTIAL MEDICAL STATISTICS (43 decks)

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