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FND I - Summative III > EBPS > Flashcards

EBPS Flashcards

1
Q

p-value

A

determines the strength of evidence against a null hypothesis

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2
Q

null hypothesis (H0)

A

assumption that there is no significant difference, effect, or relationship between two or more groups or variables being studied

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3
Q

Alternative Hypothesis (Ha)

A

It usually suggests the presence of a significant effect, difference, or relationship.

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4
Q

hyperlipidemia

A

elevated levels of lipids in the bloodstream, including cholesterol and triglycerides, which can increase the risk of cardiovascular diseases

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5
Q

Normal blood pressure for adults is

A

120/80 or lower

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6
Q

Retrospective Study

A

looks at past data or events to examine the relationships between variables to draw conclusions about potential associations or outcomes.

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7
Q

Prospective Study

A

gathers data from participants moving forward in time, starting from the present and following them into the future to observe and measure outcomes as they occur, often through the design of cohort studies or clinical trials.

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8
Q

Cohort studies

A

follow a group of individuals, known as a cohort, and track their experiences and health outcomes over an extended period

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9
Q

confidence interval

A

a range of values that is calculated from sample data and is used to estimate the range within which a population parameter, such as a mean or proportion, is likely to fall with a certain level of confidence.

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10
Q

Epidemiology

A
  • the study of the distribution and determinants of disease frequency in human populations
  • the application of this study to control health problems and improve public health
  • understand and to control its causes
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11
Q

Biostatistics

A

concerns with analysis and summarization of raw data in interpretable messages related to human health

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12
Q

Evidence-based medicine (EBM)

A

using the current best evidence in decision making in medicine in conjunction (together) with expertise of the decision-makers and
expectations and values of the patients/people

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13
Q

clinical research

A
  • studying groups of people who are ill
  • studies humans in clinical facilities such as outpatient clinics or inpatient facilities
  • the interventions are often about therapy in sick people
  • experimental design
  • small to moderate size
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14
Q

epidemiological studies

A
  • study people in communities
  • preventive interventions
  • observational studies
  • large sample size
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15
Q

the “Big 6”

A
  • description
  • causation
  • attribution
  • mediation
  • interaction
  • prediction
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16
Q

Description

A

addresses how frequent or common are various risk factors, exposure, conditions, or diseases

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17
Q

Causation

A

addresses establishing causal relationships among biological, behavioral, environmental and other factors within humans.

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18
Q

Attribution

A

addresses what fraction or how many cases of disease Y can be eliminated if a causal exposure X is eliminated or reduced?

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19
Q

Mediation

A
  • addresses the mechanisms of causal relationships
  • Given that X does cause Y, how does X cause Y? What is the mechanism?
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20
Q

Interaction

A
  • addresses when and for whom does X cause/predict Y?
  • closely related to causation
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21
Q

Prediction

A

addresses as to whether some feature A or a combination of features A, B, and C predict the concurrent presence or future occurrence of Y?

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22
Q

How could we determine causes of diseases?

A

Conduct population studies using epidemiological methods

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23
Q

Why should pharmacists care about Epidemiology?

A
  • practice evidenced based medicine (EBM)
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24
Q

randomized controlled trials (RCTs)

A
  • scientific experiments in which participants are randomly assigned to receive different interventions or treatments
  • assess the efficacy and safety of these interventions while minimizing bias
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25
Q

Case-control studies

A

observational research designs that compare individuals with a specific outcome or condition (cases) to those without it (controls) in order to identify factors associated with the development of that outcome or condition

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26
Q

Steps in Practicing EBM

A
  1. identify a good question
  2. find relevant literature
  3. critically evaluate data
  4. synthesize and apply to patients
  5. recognize gaps and design solutions
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27
Q

Two types of study designs

A
  1. experimental
  2. observational
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28
Q

Experimental study can be categorized as

two

A
  1. randomized control trial (RCT)
  2. non-randomized control trial
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29
Q

observational studies can be grouped as

two

A
  1. analytical
  2. descriptive
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30
Q

analytical studies can be

two

A
  • case-control
  • cohort
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31
Q

descriptive studies can be

A

cross-sectional

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32
Q

internal validity

A

How well do the study estimates represent what was intended in the study plan?

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33
Q

external validity

A
  • How relevant are the study estimates to the research question?
  • AKA: Generalizability
  • Are study results applicable to the patient/population/problem in front of me?
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34
Q

three threats to validity

A
  1. chance (random error)
  2. bias (systematic error)
  3. confouding
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35
Q

chance (random error)

A
  • errors that occur by chance
  • improved by increasing sample size
  • measured by CI
  • can affect precision
  • Lots of random error/chance = poor precision
  • There can be random error in both sampling and measurement
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36
Q

bias (systematic error)

A
  • can include selection bias, volunteer bias, measurement bias
  • can affect accuracy
  • errors caused by choices, compromises and mistakes we make in how we conduct our study and not by random processes
  • Lots of systematic error/bias = poor accuracy
  • There can be systematic error in both sampling and measurement
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37
Q

confounding

A

third variable associated with both exposure and outcome

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38
Q

prevalence

A

currently have a disease

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39
Q

incidence rate

definition

A

new cases per unit person-time

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40
Q

point prevalence

A

proportion with disease at a particular point in time

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41
Q

period prevalence

A

proportion with disease at any point in time during the period (short lived ex: COVID-19, migraine)

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42
Q

point prevalence formula

A

number of people with a disease or trait / total # of people in a study population

43
Q

period prevalence formula

A

number of people with a disease or trait in specific time period / total # of people in study population

44
Q

cumulative incidence formula

A

number of new cases of the disease during a specific time period / number of people in study population

45
Q

incidence rate formula

A

number of new cases of a disease / number people in population * time period

46
Q

RCT scheme

A

Participants are randomly assigned to different groups: one group receives the intervention being tested (the treatment group), and another group (the control group) receives either a placebo or a standard treatment, depending on
the study design.

47
Q

RCT strengths

A
  • Provides strongest causal evidence
  • Randomization minimizes confounding and blinding minimizes measurement bias
48
Q

RCT weaknesses

A
  • $$$ and time-consuming
  • Low external validity
  • Ethics: some exposures impossible to study
49
Q

RCT association measures

A

relative risk

50
Q

cohort scheme

A
  • Follow 2+ groups with different exposures over an extended period of time and compare outcomes
  • Ideal for common diseases and rare exposures
51
Q

cohort strengths

A
  • Can measure incidence of multiple outcomes
  • Can study effects of multiple risk factors
  • Provides strong causal evidence due to time sequence
52
Q

cohort weaknesses

A
  • $$$ and time-consuming
  • Vulnerable to confounding because we know the exposure beforehand
  • Difficult to assess rare outcomes
  • Loss to follow up
53
Q

association measures

A

relative risk

54
Q

case-control scheme

A
  • Identify 2 groups with and w/o an outcome interest, collect data and compare odds of exposure
  • Ideal for rare outcomes and outcomes with a long latency
55
Q

case-control strengths

A
  • $ and not time-consuming, quick
  • Can assess multiple outcomes and study rare outcome
56
Q

case-control weaknesses

A
  • Recall and selection biases → low internal validity
  • Vulnerable to confounding - Can only study one outcome
57
Q

association measures

A

odds ratio

58
Q

cross-sectional scheme

A
  • Sample at one point in time to describe the distribution of exposures and outcomes
  • Ideal for hypothesis generation
59
Q

cross-sectional strengths

A
  • $ and not time-consuming, quick
  • Can measure prevalence
  • Can assess several exposures & outcomes
60
Q

cross-sectional weaknesses

A
  • No temporal ordering → weak causal evidence
  • Vulnerable to confounding
  • Cannot measure incidence
61
Q

association measures

A

odds ratio

62
Q

PICO

A

Population
Intervention
Comparison
Outcome

63
Q

Relative-risk (RR)

A
64
Q

Odd ratio (OR)

A
65
Q

RR >1

A

exposed are X times more likely to have a disease compared to unexposed

66
Q

OR > 1

A

cases have X times higher odds of exposure compared to controls

67
Q

RR = 1

A

exposed and the unexposed are equally likely to have a disease

68
Q

OR = 1

A

odds of exposure in cases and controls are the same

69
Q

RR < 1

A

exposed are (1-X)% less likely to have a disease compared to unexposed

70
Q

OR < 1

A

odds of exposure in cases is (1-X)% lower than in controls

71
Q

cumulative incidence

definition

A

new cases during time period

72
Q

The frequency of of new COPD diagnosis in smokers is 33 per 1,000 person-years

incidence or prevalence

A

Incidence rate

73
Q

In the same study, 5 had active wheezing at baseline exam

incidence or prevalence

A

Period prevalence

74
Q

In the same study, 11 reported at baseline that they had taken opioid medications for pain at some point in the last year

prevalence or incidence

A

Point prevalence

75
Q

In a study of 1,000 young adults, 24 developed diabetes over 10 years

prevalence or incidence

A

Cumulative incidence

76
Q

measurement

A

making observations about the individuals who are sampled for the study

77
Q

measurement can be

A

numeric (quantitative)
thematic (qualitative)

78
Q

intervention

A

intentionally expose people to something

79
Q

stages of conducting a research study

A

1) Specifying a research question
2) Making a study plan
3) Implementing that plan

80
Q

point estimate

A

best guess about what the truth is

81
Q

95% confidence interval

A

The interval within which the TRUE parameter will be found 95% of the time (this helps us understand the precision of an estimate)

82
Q

bias is a problem with

A

accuracy

83
Q

Lots of random error =

A

chance is playing a large role = poor precision

84
Q

Lots of systematic error =

A

bias is playing a large role = poor accuracy

85
Q

Sampling

A

Choosing particular individuals from a population

86
Q

Census

A

we study every individual in a population

87
Q

Experimental study

A

You manipulate an exposure by doing an
“intervention” (usually with one or more control groups), and then see what happens

88
Q

Observational study

A

You just observe without any intervention

89
Q

Three types of Observational study

A

Cross-sectional
Cohort
Case-control

90
Q

Target population

A

The population for whom the research question is relevant

91
Q

Accessible population

A

The population the researchers have access to and plan to
study

92
Q

Study sample

A

the actual study subjects who were included in the study and whose data were analyzed and included in the study estimates

93
Q

Target phenomenon

A

The thing you want to learn about

94
Q

Intended variables

A

The things you think you can realistically measure in a research study

95
Q

Actual measurements

A

The measurements that are actually made (with error) for a study

96
Q

Inference

A

A conclusion reached on the basis of evidence and reasoning

97
Q

Estimate

A

Numerical best guess informed by data

98
Q

prevalence

A

current disease

99
Q

incidence

A

new disease

100
Q

average incidence rate

A

number of events / person-time

101
Q

Kaplan-meier

A
  • the graph can be for the rate of mortality or rate of survival
102
Q

time-to-event analysis

A

cumulative incidence over time

103
Q

rate

A
  • must have time in denominator
  • ex: incidence rate = events/person-year
104
Q

proportion

A
  • numerator is subset of denominator (between 0-1)
  • ex: cumulative incidence = # developing disease / # total

FND I - Summative III (5 decks)

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