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Step One Prep > Behavioral Science- Epidemiology/Biostatistics > Flashcards

Behavioral Science- Epidemiology/Biostatistics Flashcards

1
Q

Cross-sectional study

A

Observational. Collects data from a group of people to assess frequency of disease (an related risk factors) at a particular point in time. Measures disease prevalence. Can show risk factor association with disease, but does not establish causality

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2
Q

Case-control study

A

Observational and retrospective. Compares a group of people with disease to a group without disease. Looks for prior exposure or risk. Measures by odds ratio.

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3
Q

Cohort study

A

Observational and prospective or retrospective. Compares a group with a given exposure or risk factor to a group without such exposure. Looks to see if exposure increased the likelihood of disease. Relative risk

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4
Q

Twin Concordance Study

A

Compares the frequency with which both monozygotic twins or both dizygotic twins develop same disease. Measures heritability and influence of environmental factors

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5
Q

Adoption Study

A

Compares siblings raised by biological vs adoptive parents. Measures heritability and influence of environmental factora

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6
Q

Clinical trial

A

Experimental study involving humans. Compares therapeutic benefits of 2 or more treatments, or of treatment and placebo. Study quality improbes when study is randomized, controlled, and double-blinded

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7
Q

What is the difference between double-blinded and triple-blinded?

A

Double-blinded: neither patient nor doctor knows whether the patient is in the treatment or control group.

Triple-blinded: refers to the additional blinding of the researchers analyzing the data.

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8
Q

Define: Phase I Drug Trial

A

Small number of healthy volunteers. “Is it safe?” Assesses safety, toxicity, and pharmacokinetics

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9
Q

Define: Phase II Drug Trial

A

Small number of patients with disease of interest. “Does it work?” Assesses treatment efficacy, optinal dosing, and adverse effects.

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10
Q

Define: Phase III Drug Trials

A

Large number of patients randomly assigned with to the treatment under investigation or to the best available treatment (or placebo). “Is it as good or better?”

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11
Q

Define: Phase IV Drug Trials

A

Postmarketing surveillance trial of patients after approval. “Can it stay?” Detects rare or long-term adverse effects. Can result in drugs being withdrawn from market.

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12
Q

Define: Sensitivity

A

The proportion of people with disease who test positive for the disease. Used for screening in disease with low prevalence.

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13
Q

Give the equation for sensitivity

A

True-Positive / [(True-Positive) + (False-Negative)]

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14
Q

Define: Specificity

A

The proportion of all people without disease who test negative. High specificity test used for confirmation after a positive screening test.

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15
Q

Give the equation for specificity

A

True-Negative / [(True-Negative) + (False-Positive)]

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16
Q

Define: Positive Predictive Value (PPV)

A

Proportion of positive tests that are true positives

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17
Q

Give the equation for positive predictive value (PPV)

A

True-Positive/ [(True-Positive)+ (False-Positive)]

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18
Q

Define: Negative Predictive Value (NPV)

A

Proportion of negative tests that are true negatives

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19
Q

Give the equation for Negative Predictive Value (NPV)

A

True-Negative/ [(True-Negative) + (False-Negative)]

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20
Q

What is the difference between incidence and prevalence?

A

Incidence looks at new cases

Prevalence looks at all current cases

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21
Q

When are incidence and values similar? When are they different?

A

Similar- when the disease duration is short e.g. common cold

Different- when the disease is chronic
e.g. diabetes

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22
Q

Give the equation for incidence rate

A

Incidence Rate = (number of new cases in a specified time period) / (population at risk during same time period)

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23
Q

Give the equation for prevalence

A

Prevalence = (number of existing cases) / (Population at risk)

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24
Q

In what studies are odds ratios used?

A

OR are typically used in case-control studies.

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25
Q

Define: Odds Ratio (OR)

A

Odds that the group with the disease (cases) was exposed to a risk factor (a/c) divided by the odds that the group without the disease (controls) was exposed (b/d)

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26
Q

Give the equation for odds ratio

A

(a/c) / (b/d)

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27
Q

In what studies are relative risk used?

A

RR are typically used in cohort studies

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28
Q

Define: Relative Risk (RR)

A

Risk of developing disease in the exposed group divided by risk in the unexposed group.

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29
Q

Give the equation for relative risk (RR)

A

= [a/(a+b)] / [c/(c+d)]

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30
Q

At what point is the relative risk approximately equal to odds ratio?

A

When the prevalence is low

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31
Q

Define: Relative Risk Reduction (RRR)

A

The proportion of risk reduction attributable to the intervention as compared to a control

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32
Q

Give the equation for Relative Risk Reduction (RRR)

A

RRR = 1- RR

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33
Q

Define: Attributable Risk (AR)

A

The difference in risk between exposed and unexposed groups, or the proportion of disease occurrences that are attributable to the exposure (e.g. if risk of lung cancer in smokers is 21% and risk in nonsmokers is 1% the 20% of the 21% risk of lung cancer in smokers is attributable to smoking)

34
Q

Give the equation for Attributable Risk (AR)

A

AR = [a/(a +b)] - [c/(c+d)]

35
Q

Define: Absolute Risk Reduction (ARR)

A

The difference in risk (not the proportion) attributable to the intervention as compared to a control. E.g. if 8% of people who receive a placebo vaccine develop flu vs. 2% of people who receive a flu vaccine the ARR = 8% -2% = 6%

36
Q

Define: Number needed to treat

A

Number of patients who need to be treated for 1 patient to benefit .

37
Q

Give the equation for Number Need to Treat

A

1 / ARR

38
Q

Define: Number Needed to Harm

A

Number of patients who need to be exposed to a risk factor for 1 patient to be harmed.

39
Q

Give the equation for Number Needed to Harm

A

1 / AR

40
Q

Define: Precision

A

The consistency and reproducibility of a test (reliability)

41
Q

Define: Accuracy

A

The trueness of test measurements (validity). The absence of systematic error or bias in a test.

42
Q

Define: Selection Bias

A

Nonrandom assignment to participate in a study group. Most commonly a sampling bias.

43
Q

Name two ways to reduce selection bias.

A
  1. Randomization

2. Ensure the choice of the right comparison/reference group

44
Q

Name three examples of selection bias

A
  1. Berkson Bias- only study inpatient
  2. Loss of follow-up- Studying a disease with early mortality
  3. Healthy worker and volunteer biases- Study populations are healthier than the general public
45
Q

Name four biases that occur when performing a study.

A
  1. Recall bias
  2. Measurement bias
  3. Procedure bias
  4. Observer-expectancy bias
46
Q

Define: Recall Bias

A

Awareness of disorder alters recall by subjects; common in retrospective studies, Patients with disease recall exposure after learning of similar cases.

47
Q

How can you decrease recall bias?

A

Decrease time from exposure to follow-up

48
Q

Define: Measurement Bias

A

Information is gathered in a way that distort it

49
Q

Give an example of measurement bias

A

Hawthorne Effect- groups who know they’re being studied behave differently than they would otherwise

50
Q

How can you reduce measurement bias?

A

Use of placebo control groups with blinding to reduce influence of participants and researchers on experimental procedures and interpretation of outcomes

51
Q

Define: Procedure Bias

A

Subjects in different groups are not treated the same

52
Q

Define: Observer-Expectancy Bias

A

Researcher’s belief in the efficacy of a treatment changes the outcome of that treatment (aka Pygmalion effect; self-fulfilling prophecy)

53
Q

Name two biases that occur when interpreting results

A
  1. Confounding Bias

2. Lead-time Bias

54
Q

Define: Confounding bias

A

When a factor is related to both the exposure and outcome, but not on the causal pathway leading to factor distorts or confuses effect of exposure on outcome. Example: Pulmonary disease is more common in coal workers than the general population; however, people who work in coal mines also smoke more frequently than the general population

55
Q

Define: Lead-Time Bias

A

Early detection is confused with increased survival; seen with improved screening techniques. To reduce bias you can measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)

56
Q

Name three nonnormal distributions

A
  1. Bimodal
  2. Positive Skew
  3. Negative Skew
57
Q

Define: Bimodal Skew

A

Suggests two different populations. Example suicide rate by age

58
Q

Define: Positive skew

A

Typically mean > median > mode. asymmetry with long tail on the right

59
Q

Define: Negative Skew

A

Typically mean

60
Q

Define: Null Hypothesis

A

Hypothesis of no difference

61
Q

Define: Alternative Hypothesis

A

Hypothesis of some difference

62
Q

Name two incorrect results

A
  1. Type 1 Error (alpha)

2. Type 2 Error (beta)

63
Q

Define: Type I Error (alpha)

A

Stating that there is an effect or difference when none exits (null hypothesis incorrectly rejected in favor of alternative hypothesis). Alpha is the probability of making a type I error.

64
Q

What does it mean when p

A

There is less than a 5% chance that the data will show something that is not really there

65
Q

Define: Type II Error (beta)

A

Stating that there is not an effect or difference when one exists. Also known as a false-negative error

66
Q

What is beta?

A

The probability of making a type II error.

67
Q

What decreases beta and increases power?

A
  1. Increasing sample size
  2. Increasing expected effect size
  3. Increasing precision of measurement
68
Q

Define: Meta-analysis

A

Pools data and integrates results from several similar studies to reach an overall conclusion. Increases statistical power.

69
Q

Define: Confidence interval

A

Range of values in which a specified probability of the means of repeated samples would be expected to fall.

70
Q

Define: t-test

A

Checks differences between means of 2 groups

71
Q

Define: ANOVA

A

Checks differences among means of 3 or more groups

72
Q

Define: Chi-Square (x^2)

A

Checks difference between 2 or more percentages or proportions of categorical outcomes (not mean values)

73
Q

Pearson correlation coefficient (r) is between what two values?

A

-1 and +1

74
Q

What does a positive r tell you?

A

There is a positive correlation between 2 variables

75
Q

What does a negative r tell you?

A

There is a negative correlation between two variables

76
Q

Define: primary disease prevention

A

Prevent disease occurrence e.g. vaccines

77
Q

Define: secondary disease prevention

A

Screening early for disease (e.g. Pap smear)

78
Q

Define: tertiary disease prevention

A

Treatment to reduce disability from disease e.g. chemotherapy

79
Q

Define: Quaternary disease prevention

A

identifying patients at risk of unnecessary treatment, protecting from the harm of new interventions.

80
Q

Identify a similarity of medicare and medicaid

A

Both are federal programs that originate from amendments to the Social Security Act

81
Q

Who is eligible for medicare

A

Medicare- is available to patients greater than or equal to 65 years of age or

82
Q

Who is eligible for medicaid

A

Medicaid is a joint federal and state health assistance for people with very low income

Step One Prep (11 decks)

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