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BEHAVIORAL SCIENCE > BEHAVIORAL SCIENCE- Epidemiology/Biostatistics > Flashcards

BEHAVIORAL SCIENCE- Epidemiology/Biostatistics Flashcards

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1
Q

Types of studies

A 
Cross sectional study
Case control study
Cohort study
Twin concordance study
Adoption study
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2
Q

Which kind of study is Cross sectional study?

A

Observational

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3
Q

Collects data from a group of people to asses frequency of disease (and related risk factors) at a particular point in time

A

Cross sectional study

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4
Q

What does Cross sectional study ask?

A

What is happening?

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5
Q

What does Cross sectional study measure?

A

Disease prevalence

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6
Q

Can show risk factor association with disease, but doesn’t establish casuality

A

Cross sectional study

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7
Q

Which kind of study is Case control study?

A

Observational and retrospective

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8
Q

Compares a group of people with disease to a group without disease

A

Case control study

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9
Q

What does Case control study look for?

A

Look for prior exposure or risk factor

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10
Q

What does Case control study ask?

A

What happened?

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11
Q

This type of study measures Odds ratio (OR)

A

Case control study

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12
Q

An example of this study is “Patients with COPD had higher odds of a history of smoking than those without COPD had”

A

Case control study

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13
Q

What type of study is Cohort study?

A

Observational prospective or retrospective

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14
Q

Compares a group with a given exposure or risk factor to a group without such exposure

A

Cohort study

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15
Q

What does Cohort study look for?

A

Looks to see if exposure increases the likelihood of disease

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16
Q

If Cohort study is prospective, what does it ask?

A

Who will develop disease?

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17
Q

If Cohort study is retrospective, what does it ask?

A

Who devellop the disease? (exposed vs nonexposed)

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18
Q

What is measure by Cohort study?

A

Relative risk

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19
Q

It’s an example of which study: “Smokers had a higher risk of developing COPD than non smokers had”

A

Cohort study

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20
Q

Compares the frequency with which both monozygotic twins or both dyzigotic twins develop same disease

A

Twin concordance study

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21
Q

What does Twin concordance study measure?

A

Heritability and influence of enviromental factors (“nature vs nurture”)

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22
Q

Compares siblings raised by biological vs adoptive parents

A

Adoption study

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23
Q

What does Adoption study measure?

A

Heritability and influence of enviromental factors

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24
Q

Experimental study involving humans

A

Clinical trial

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25
Q

Compares therapeutic benefits of 2 or more treatments, or of treatment and placebo

A

Clinical trial

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26
Q

When does the study quality of a Clinical trial improve?

A

When study is randomized, controlled, and double-blinded

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27
Q

What is a double blinded Clinical trial?

A

Neither patinet nor doctor knows wheter the patient is in the treatment or control group

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28
Q

What is a triple blind Clinical trial?

A

Refers to additional blinding of the researches analyzing the data

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29
Q

In which people is Phase I drug trial done?

A

Small number of healthy volunteers

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30
Q

What is the purpose of Phase I drug?

A

Assesses safety, toxicitym and pharmacokinetics

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31
Q

What does Phase I drug look for?

A

Is it safe?

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32
Q

In which patients is Phase II drug trial done?

A

Small number of patients with disease of interest

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33
Q

What does Phase II drug look for?

A

Does it work?

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34
Q

What is the purpose of Phase II drug?

A

Assesses treatment efficacy, optimal dosing, and adverse effects

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35
Q

In which patients is Phase III drug trial done?

A

Large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo)

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36
Q

What does Phase III drug look for?

A

Is it as good or better?

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37
Q

What is the purpose of Phase III drug?

A

Compares the new treatment to the current standard of care

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38
Q

In which patients is Phase IV drug trial done?

A

Postmarketing surveillance trial of patients after approval

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39
Q

What does Phase IV drug look for?

A

Can it stay?

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40
Q

What is the purpose of Phase IV drug?

A

Detects rare or long term adverse effects

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41
Q

What can Phase IV drug result?

A

In a drug being withdrawn from market

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42
Q

What do Evaluation of diagnostic tests use?

A

Use 2 x 2 table comparing test results with the actual presence of disease

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43
Q

Which are the parameters taken in Evaluation of diagnostic test?

A 
TP= True positive
FP= False positive
FN= False negative
FP= False negative
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44
Q

What does Evaluation of diagnostic test determine?

A

Sensitivity and specificity are mixed properties of a test (vs PPV and NPV)

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45
Q

What does Sensitive evaluates?

A

True positive rate

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46
Q

Proportion of all people with disease who test positive, or the probability that a test detects disease when disease is present

A

Sensitivity

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47
Q

What is the purpose of Sensitivity?

A

Value approaching 100% is desirable for ruling out disease and indicates a low false negative rate

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48
Q

What is the importance of high Sensitivity?

A

High sensitiity test used for screening in disease with low prevalance

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49
Q

Formula to determine Sensitivity

A

= TP/ (TP+FN)

= 1 - false negative fate

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50
Q

What does Specificity evaluate?

A

True negative rate

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51
Q

Proportion of all people without disease who test negative, or the probability that a test indicates non-disease when disease is absent

A

Specificity

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52
Q

What is the purpose of Specificity?

A

Value approaching 100% is desirable for ruling in disease and indicates a low false positive rate

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53
Q

What is the importance of high Specificity?

A

= TN/ (TN+ FP)

=1 - false positve rate

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54
Q

Proportion of positive test results that are true positive

A

Positive predictive value

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55
Q

What is the purpose of Positive predictive value?

A

Probability that actually has a the disease given a positive test result

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56
Q

Formula for Positive predictive value

A

= TP/ (TP+FP)

57
Q

How does Positive predictive value varies?

A

Varies directly with prevalence or pretest probability: high pretest probability → high PPV

58
Q

Proportion of negative test results that are true negative

A

Negative predictive value

59
Q

What is the purpose of Negative predictive value?

A

Probability that a person actually is disease free given a negative test result

60
Q

Formula for Negative predictive value

A

= TN / (TN+FN)

61
Q

How does Negative predictive value varies?

A

Varies inversely with prevalence or pretest probability: high pretest probability → low NPV

62
Q

Formula to determine Incidence rate

A

of new cases in a specified time period
Incidence rate= ———————————————————-
Population at risk during same time period

63
Q

What does Incidence determine?

A

Looks at new cases

64
Q

Formula of Prevalence

A

of existing cases
Prevalence = ——————————-
Population at risk

65
Q

What does Prevalence determines?

A

Looks at all current cases

66
Q

How else is prevalence determine?

A

Prevalence = (Incidence Rate) x (Average Duration of Disease)

67
Q

Types of Quantifyng risk

A 
Odds ratio
Relative risk
Relative risk reduction
Attributable risk
Absolute risk reduction
68
Q

When is Odds ratio typically used?

A

In case control studies

69
Q

What is the purpose of Odds ratio?

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)

70
Q

Formula for Odds ratio

A

OR= ad/ bc

71
Q

When is Relative risk typically used?

A

In cohort studies

72
Q

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

A

Relative risk

73
Q

Example of Relative risk

A

If 21% of smokers develop lung cancer vs 1% of nonsmokers, RR= 21/1 = 1

74
Q

Formula for Relative risk

A

a/(a+b)
RR= ———–
c/(c+d)

75
Q

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

A

Relative risk reduction

76
Q

Formula to determine Relative risk reduction

A

RRR= 1 - RR

77
Q

Example of Relative risk reduction

A

If 2% of a patients who receive a flu shot develop flu, while 8% of unvaccinated patients develop the flu, then RR = 2/8 = 0.25, and RRR= 1- RR = 0.75

78
Q

The difference in risk between exposed and unexposed groups, or the proportion of disease of disease ocurrences that are attributable to the exposure

A

Attributable risk

79
Q

Example of Attributable risk

A

If risk of lung cancer in smokers is 21% and risk in nonsmokers is 1% then 20% (or .20) of the 21% risk of lung cancer in smokers is attributable to smoking

80
Q

How is Attibutable risk calculated?

A

a c
AR= —— - ———–
a+ b c+ d

81
Q

The difference in risk (not the proportion) attributable to the intervention as compared to a control

A

Absolute risk reduction

82
Q

Example of Absolute risk reduction

A

If 8% of people who receive a placebo vaccine develop flu vs 2% of people who receive a flu vaccine, then ARR= 8%- 2%= 6% = .06

83
Q

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

A

Number needed to treat

84
Q

How is Number needed to treat calculated?

A

1/ARR

85
Q

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

A

Number needed to harm

86
Q

How is Number needed to harm calculated?

A

1/AR

87
Q

Characteristics of Precision

A

The consistency and reproducibility of a test (reliability)

The abscence of random variation in a test

88
Q

What reduces precision in a test?

A

Random error

89
Q

What is the effect Increased precision?

A

Decreases standard deviation

90
Q

Characteristics of Accuracy

A

The trueness of test measurements (validaty)

The absence of systematic error or bias in a test

91
Q

What reduces accuracy in a test?

A

Systematic error

92
Q

Bias nad study errors

A

Recruiting participants
Perfoming study
Interpreting results

93
Q

What is including in Recruiting participants?

A

Selection bias

94
Q

Nonrandom assignment to parcipate in a study group

A

Selection bias

95
Q

What is the most common selection vias?

A

A sampling bias

96
Q

Examples of selection bias

A

Berkson bias
Loss of follow up
Healthy worker and volunteer biases

97
Q

Selection bias type that study looking only at inmpatients

A

Berkson bias

98
Q

Selection bias type Studying a disease with early mortality

A

Loss of follow up

99
Q

Selection bias type that study populations healthier than the general population

A

Healthy worker and volunteer biases

100
Q

How is Selection bias reduced?

A

Randomization

Ensure the choice of the right comparision/reference group

101
Q

Perfoming study types

A

Recall bias
Measurement bias
Procedure bias
Observer expectancy bias

102
Q

Definition of Recall bias

A

Awareness of disorder alters recall by subjects

103
Q

In which studies is common Recall bias?

A

Retrospective studies

104
Q

Which perfoming study has patients with disease recall exposure after learning of similar cases?

A

Recal bias

105
Q

Strategy to reduce Recall bias

A

Decrease time from exposure to follow up

106
Q

Definition of Measurement bias

A

Information is gathered in a way that distorts it

107
Q

Example of Measurement bias

A

Hawthourne effect- groups who know they’re beingstudied behave differently than they would otherwise

108
Q

Strategy to reduce Measurment bias

A

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

109
Q

Definition of Procedure bias

A

Subjects in different groups are not treated the same

110
Q

Patients in treatment group spend more time in highly specialized hospital units… it is an example or this bias and study error

A

Procedure bias

111
Q

Definition of 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)

112
Q

If observer expects treatment group to show signs of recovery, then he is more likely to document positive outcomes, which type of Perfoming study is?

A

Observer expectacy bias

113
Q

Types of Interpreting results

A

Confunding bias

Lead bias

114
Q

Definition of Confunding bias

A

When a factor is related to both the exposure and outcome, but not on the casual way → factor distorts of confuses effect of exposure on outcome

115
Q

Example of Confunding bias

A

Pulmonary disease is more common in coal workers than the general population; however people who work in coal mines also smoke more frequently than general population

116
Q

Strategy to reduce Confunding bias

A 
Multiple/repeated studies
Crossover studies (subjects act as their own controls)
Matching (patients with similar charateristics in both treatment and control groups)
117
Q

Definition of Lead time bias

A

Early detectionis confused with increased survival; seen with improved screening techniques

118
Q

Example of Lead time bias

A

Early detection makes it seem as though survival has increased, but the natural history of the disease has not changed

119
Q

Strategy to reduce Lead time bias

A

Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)

120
Q

Statistical distributions

A

Measures of central tendency
Measures of dispersion
Normal distribution

121
Q

Measures of central tendency

A

Mean
Median
Mode

122
Q

How is Mean calculated?

A

Mean= (sum of values)/ (total number of values)

123
Q

What is Median?

A

Middle value of a list of data sorted from least to greatest

If there is an even number of values, the median will be the average of the middle two values

124
Q

Most common value

A

Mode

125
Q

Measures of dispersion

A

Standard deviation

Standard error of the mean

126
Q

What is Standard deviation?

A

How much variability exists from the mean in a set of values

127
Q

What is Standard error of the mean?

A

An estimation of how much variability exists between the sample mean and the true population mean

128
Q

Characteristics of Normal distribution

A

Gaussian, also called bell shapped

Mean= median= mode

129
Q

Nonnormal distributions

A

Bimodal
Positive skew
Negative skew

130
Q

What does Bimodal distribution suggests?

A

Two different populations

131
Q

Example of Bimodal distribution

A

Metabolic polymorphosm such as fast vs low acetylators; suicide rate by age

132
Q

Characteristics of Positive skew distribution

A

Typically, mean > median > mode

Asymmetry with longer tail on right

133
Q

Characteristics of Negative skew distribution

A

Typically, mean

134
Q

Statustical hypotheses

A

Null (H0)

Alternative (H1)

135
Q

Hypothesis of no difference

A

Null hypothesis

136
Q

There is no association between the disease and the risk factor in the population

A

Null (H0) hypothesis

137
Q

Hypothesis of some difference

A

Alternative (H1) hypothesis

138
Q

There is some association between the disease and the risk factor in the population

A

Alternative (H1) hypothesis

139
Q

Outcomes of statistical hypothesis testing

A

Correct result

Incorrect result

BEHAVIORAL SCIENCE (1 decks)

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