SPH1904 Midterms Flashcards

1
Q

Rank the following on the evidence pyramid :
- randomised controlled trials (RCTs)
- critically-appraised individual articles (article synopses)
- cohort studies
- case-controlled studies (case series/reports)
- background information/expert opinion
- systematic review
- critically-appraised topics (evidence syntheses)

A

From strongest to weakest evidence :
- systematic review
- critically-appraised topics (evidence syntheses)
- critically-appraised individual articles (article synopses)
- randomised controlled trials (RCTs)
- cohort studies
- case-controlled studies case series/reports
- background information/expert opinion

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2
Q

What does the PICO framework stand for?

A

P - Patient
I - Intervention
C - Comparison
O - Outcome

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3
Q

Rank the study designs for a Therapy/Prevention Question

A

RCT > Cohort > Case-control > Case series

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4
Q

Rank the study designs for a Etiology/Harm Question

A

RCT (rarely) > Cohort > Case-control > Cross-sectional

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5
Q

Rank the study designs for a Prognosis Question

A

Cohort > Case-control > Case series

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6
Q

Rank the study designs for a Diagnosis Question

A

Prospective, blind comparison to a gold standard

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7
Q

List the Boolean operators and how to perform a search

A
  • – Include all forms of the same word
    AND – Include words of different topics/concepts
    OR – Include words of similar topics/concepts
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8
Q

What does the CRAAP tool stand for?

A

C : Currency – timeliness of information
R : Relevance – importance of information for your needs
A : Authority – source of information
A : Accuracy – reliability, truthfulness and correctness of the content
P : Purpose – the reason the information exists

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9
Q

For each of the following study designs [Cross-sectional study, Case-control study, Cohort-study, RCT] , answer the following questions :
1. When are the exposure and outcome measured?
2. Are participants matched on the outcome?
3. Are participants randomised to the exposure?

A

Case-control : Outcome measured after the exposure ; Participants matched on the outcome ; Participants not randomised to the exposure
———-
Cohort study : Outcome measured after the exposure ; Participants are not matched on outcome ; Participants are not randomised to the exposure
———
RCT : Outcome measured after the exposure ; Participants are not matched on outcome ; Participants are randomised to the exposure

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10
Q

List the Bradford-Hill criteria.

A

TSBDECCSA
1. Strength: A larger effect size makes it more likely that the association is causal.
2. Temporality: Cause must precede effect
3. Consistency: Multiple studies showing the same findings increase the credibility
4. Biological Plausibility: A rationale or theoretical basis for the finding
5. Dose response relationship: Greater the amount of exposure, the greater amount of harm
6. Experimental Evidence: Experiments make a causal association more plausible
7. Coherence: Cause-effect relationship doesn’t conflict with what is known or has other competing hypotheses
8. Specificity: Effect has only one cause
9. Analogy: A commonly accepted phenomenon in one area can be applied to another area

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11
Q

Define prevalence.

A

The frequency/number of cases in a specific population who have a specific condition during a specified time region (e.g. all current cases within a specific time frame)

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12
Q

Define incidence.

A

Incidence is the frequency/occurrence of a new outcome of interest during the specified time period being examined.

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13
Q

Explain the characteristics, benefits and limitations of each of the following sampling methods (Non-probability sampling, Simple Random Sampling, Stratified Sampling, Cluster Sampling, Systematic Sampling)

A

Non-Probability Sampling :
- Characteristics – Selects samples based on non-random criteria like convenience or judgement
- Benefits – Easy, Quick and Cost-effective
- Limitations – Biased, not representative, findings cannot be generalised

Simple Random Sampling :
- Characteristics – Every member of the population has an equal chance of being selected
- Benefits – Unbiased, easy to understand, generalisable results
- Limitations - Challenging for large populations, potential to miss segments

Stratified Sampling :
- Characteristics – Divides population into subgroups ; samples from each subgroup
- Benefits – Represents all segments, more accurate, reduces sampling error
- Limitations – Requires population knowledge, complex, higher costs

Cluster sampling :
- Characteristics – Divides populations into clusters ; selects entire clusters randomly
- Benefits – Economical for large areas, reduces costs and logistical issues
- Limitations – Higher sampling error, less precision, clusters may vary internally

Systematic Sampling :
- Characteristics – Selects members at a fixed interval from a randomly chosen starting point
- Benefits – Simple, suitable for large populations
- Limitations – Risk of periodicity bias, not truly random, ordered list required

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14
Q

List the data type, numerical summary, graphical display (1 variable) and graphical display (2 variables) for categorical and numerical data respectively.

A

Categorical data :
[Data type] Nominal : Response categories with no order and Ordinal : Response categories with order
[Numerical summary] Frequency, n ; Percentage, %
[Graphical display (1 variable)] : Bar chart
[Graphical display (2 variables)] : Grouped Bar charts, Multiple boxplots (mixed data)

Numerical data :
[Data type] Continuous / Discrete
[Numerical summary] Normally distributed, Skewed division, Mean, Standard deviation, Median, Range median, IQR
[Graphical display (1 variable)] : Histogram/Boxplot ; Mean, Mode, Median
[Graphical display (2 variable)] :
Scatter plots, Pearson/Spearman Correlation Coefficient, Multiple boxplots (mixed data)

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15
Q

Define sensitivity.

A

Probability of correcting identifying persons with the disease.

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16
Q

Describe Specificity.

A

Probability of correctly identifying persons without the disease.

17
Q

Write down how sensitivity of the test is calculated and why it is important.

A
  • Sensitivity = True positives/Disease present
  • Higher sensitivity = Fewer false negatives (fewer people with disease who are missed by the test)
  • Important for screening tests
18
Q

Write down how specificity of the test is calculated and why it is important.

A
  • Specificity = True negatives/Disease absent
  • High specificity = Fewer false positives (Fewer people without the disease being incorrectly identified as positive by the test)
  • Important for confirmatory tests
19
Q

Explain the significance of ROC curves.

A

ROC curves are Receiver Operating Characteristic (ROC) curves which show sensitivity and specificity of a diagnostic test at various cut-off points.

20
Q

Explain the significance of the area under the ROC curve.

A

Area under the ROC curve is an indication of the overall accuracy of the test.

21
Q

Explain the significance of the positive predictive value.

A

The probability that a person with a positive test has the disease (post-test probability of the disease)

22
Q

Explain the significance of the Negative Predictive Value.

A

Probability that a person with a negative test does not have the disease (post-test probability of no disease)

23
Q

Describe ways to reduce systematic errors.

A

Conduct :
- Probability Sampling
- Calibration
- Standardisation
- Randomisation
- Statistical adjustments

24
Q

Describe ways to reduce random errors.

A

Conduct :
- Increase sample size

25
Q

What is the significance of the 95% Confidence Interval

A
  • We are 95% confident that the true parameter lies in the interval (x,y)
  • If we repeat the study 100 times with random samples of the same size, 95 of the 100 confidence intervals will contain the true parameter
  • 95% CI = Mean +/- level of confidence x standard error (SE)
26
Q

What is the test to be conducted if i have 2 groups of independent numerical data that is parametric?

A

Two-sample t-test

27
Q

What is the test to be conducted if i have 2 groups of independent numerical data that is non-parametric?

A

Mann-Whitney U test

28
Q

What is the test to be conducted if i have >2 groups of independent numerical data that is parametric?

A

One-way ANOVA

29
Q

What is the test to be conducted if i have >2 groups of independent numerical data that is NON-parametric?

A

Kruskal Wallis test

30
Q

What is the test to be conducted if i have 2 groups of independent categorical data?

A

Chi-squared test (cell count > 5) OR the Fisher’s exact test (if the cell count <5)

31
Q

Explain what is a Type I error.

A
  • Reject the null hypothesis when it is in fact true
  • Related to the significance level of the test
32
Q

Explain what is a Type II error.

A
  • Fail to reject the null hypothesis when it is false
  • Related to power of test