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Clinical Decision Making > Midterm Study Guide > Flashcards

Midterm Study Guide Flashcards

1
Q

what is evidence based dentistry?

A

3-part harmony, all optimize treatment outcomes

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2
Q

what are the three parts to evidence based dentistry?

A

best evidence
clinical judgement
patient values

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3
Q

best evidence

A

evaluation of the best available scientific evidence

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4
Q

clinical judgement

A

recognition of your own clinical expertise

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5
Q

patient values

A

understanding patients needs and preferences

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6
Q

why would you not use EBD?

A

Not simply just reporting the findings of the study or considering just one
study. It seeks to evaluate all scientific evidence on a specific topic. This allows us to broaden our treatment options by using more current evidence.

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7
Q

The steps in developing an evidence based approach to practice is:

A
  1. Determining your clinical question (What do you want to know?)
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8
Q

the hierarchy of evidence is based on the ability to

A

control for bias and demonstrate cause and effect in humans

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9
Q

hierarchy of evidence from top to bottom (7)

A 
meta analysis 
systematic review
randomized controlled trial
cohort studies 
case control studies 
case series/case report
animal studies
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10
Q

types of questions patients ask (6)

A 
prevalence
etiology/risk
diagnosis 
therapy 
prognosis 
phenomena
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11
Q

prevalence

A

what is the frequency?

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12
Q

etiology/risk

A

what causes the problem?

cohort study>case control>case series

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13
Q

diagnosis

A

does the person have it?

prospective, blind comparison to a gold standard (RCT) or cross-sectional

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14
Q

therapy

A

what is the best treatment?

randomized control study> cohort study

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15
Q

prognosis

A

who will get the problem? (group of linked individuals)

cohort study>case control>case series

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16
Q

phenomena

A

what are the concerns?

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17
Q

PICO

A

population/patient/problem
intervention
comparison (dont always have this)
outcome

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17
Q

PICO

A

population/patient/problem
intervention
comparison (dont always have this)
outcome

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18
Q

most common questions of PICO

A

diagnosis
treatment
etiology/harm
prognosis

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19
Q

doctor uses given info to search for best evidence to answer the question, critically appraising the evidence and applying results in

A

clinical practice

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20
Q

what key words do you use when searching in pubmed?

A

PICO keywords

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21
Q

what order do you write your questions?

A

PICO

in patients with…will…as compared to…result in…

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22
Q

when searching for evidence, what order do you use?

A

I, C, P, O

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23
Q

what are common barriers to rational decision making?

A

cognitive biases

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24
Q

research question

A

presents the idea that is to be examined in a study and is the foundation of the research study

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25
Q

hypothesis

A

testable prediction; attempts to answer the research question

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26
Q

PICO

A

clinical question that cannot be tested

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27
Q

searching pubmed

A

use PICO for ket words during search; indexed with MeSH terms and newer items not indexed for searching

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28
Q

clinical queries

A

filters out all research not related to clinically related questions

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29
Q

Cochrane library

A

systematic reviews and Cochrane reviews; they have their own libraries they review

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30
Q

ADA’s EBD site

A

keeps up with hot topics, great for once you are out of school

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31
Q

TRIP

A

pulls up reviews easily

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32
Q

CEBD

A

won’t need as much and is harder to use

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33
Q

limited of databases (5)

A 
language 
age 
time period/date
gender/sex
publication types
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34
Q

publication types (5)

A 
systematic reviews 
meta
RCT
practice guidelines 
reviews
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35
Q

MeSH terms

A

medical subject headings

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36
Q

puimde is indexed with MeSJ terms and newer items not

A

indexed for searching

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37
Q

midline is indexed with only

A

mesh terms for search

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38
Q

MeSH is a

A

national library of medicines controlled vocabulary thesaurus

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39
Q

terms naming descriptions in hierarchical structure that permits searching at various level

A

specificity

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40
Q

boolean operators

A

a connection word or symbol that allows a computer user to include or exclude items in a test search

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41
Q

OR

A

broadens search

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42
Q

AND

A

narrows search

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43
Q

NOT

A

excludes

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44
Q

boolean operators must be — in pubmed

A

capitalized

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45
Q

internal validity (3) questions

A

are the results valid for the patients in the study?
was the study performed correctly?
was any difference between groups seen?

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46
Q

threats to internal validity (3)

A

selection bias
maturation
instrumentation

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47
Q

— — to groups addresses many threats to internal validity, but not all

A

Random assignment

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48
Q

external validity (2) questions

A

are the results valid for patients not involved in the study?
does the study population represent the larger group?

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49
Q

external ability to generalize findings beyond (2)

A

beyond subjects in the study

beyond the environmental constrains of the current study and to other temporal periods

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50
Q

as controls — (increasing internal validity), the generalizability of finding may — (decreasing external validity)

A

increase

suffer

51
Q

threats to external valid (2)

A

publications

financial

52
Q

quantitative

A

inquiry rooted in empiricism

only those phenomena which can be measured are “real”
measures are often numeric scales

53
Q

qualitative

A

inquiry based in hermeneutics

the interpretation of contextual meaning
measures are subject and dependent upon perceptual bias (subjective data)

54
Q

meta analysis

A

subset of systematic reviews; method for combining
qualitative and quantitative data from several selected studies to develop
a single conclusion that has greater statistical power

55
Q

systematic reviews

A

provides a comprehensive review of all relevant

studies on a particular clinical topic

56
Q

randomized control trials

A

participants are randomly assigned to an
experimental group or a control group. The only expected difference between the control and the experimental group is the outcome variable being studiedexperimental

57
Q

cohort study

A

one or more samples (cohorts) are followed prospectively and subsequent status evaluations are conducted to determine which initial participants risk factors are associated with a disease or outcome. Outcome from participants in each cohort is measured and relationships with specific characteristics are determinedobservational

58
Q

case study

A

compares patients who have a disease or outcome of interest (cases) with patients who do not (controls), and look back retrospectively

to determine the relationship between risk factor and disease observational

59
Q

case study limits

A

RR calculation because cases are selected on basis of disease rather than exposure

60
Q

cross sectional study

A

analysis of data collected from a population or representative subset at one specific point in time. Used to describe some feature of a population (i.e., prevalence of an illness)descriptive

61
Q

case reports

A

an article that describes and interprets an individual case, often written in the form of a details story. Describes unique cases that cannot be explained, variations of a disease, unexpected events, etc. Considered the lowest level of evidencedescriptive

62
Q

which studies are observational studies (2)

A

cohort studies

case control studies

63
Q

observational studies

A

Researcher does not test an intervention such as a drug, but instead looks for relationships between exposure and outcomes (exposure = outcomes), such as the relationship between smoking and lung cancer.

64
Q

strongest evidence for demonstrating cause and effect

A

randomized control trial

65
Q

RCT reduces the effect of

A

bias due to intervening variables

assumes that confounding conditions will be equally distributed among groups

66
Q

RCT includes (4)

A

at least one “varied condition” (treatment vs no treatment)
concurrent enrollment
random assignment to groups
follow up

67
Q

RCT using blinding attempt to

A

reduce bias due to the expectations or preconceptions of patients or investigators (ex. double blind)

68
Q

experimental research (3)

A

Quantitative
Investigative cause
Researcher controls or manipulates variables under investigation

69
Q

observational research (4)

A
  • May be quantitative or qualitative
  • Without experimental controls (may include comparisons to natural
    groups)
  • Sometimes called “quasi” experiments
  • Designs provide for the investigation of relationships, but not cause
70
Q

examples of variable (4)

A

unknown or known factors relevant to a study

age
ethnicity
socioeconomic status
disease history

71
Q

independent factor, aka

A

causative factor

72
Q

independent variable

A

a factor or condition that changes naturally or is intentionally manipulated by the investigator to observe an effect

73
Q

independent variable is known and

A

controlled by the experimenter

74
Q

dependent variable aka

A

response or outcome

75
Q

dependent variable

A

observed variable in an experiment in which changes are determined by the presence or degree of one or more independent variables

76
Q

dependent variable is a factor directly

A

affected by another

77
Q

confounding variables aka

A

error or confounding influences

78
Q

confounding variables

A

An extraneous variable that correlates significantly with both the
independent and dependent variable

A factor not considered or recognized by the experimenter that has
significant impact on dependent variable or outcome of interest

79
Q

nominal/categorical data

A

Label or category without rank or order (mutually exclusive)

80
Q

examples of nominal data (2)

A

male/female, dead/alive, pass/fail

81
Q

ordinal data

A

Label or category with meaningful order or sequence

82
Q

how to measure ordinal data

A

Not measured - without definite boundaries/levels

83
Q

example of ordinal data

A

severity of disease

84
Q

likert scale

A

strongly agree, agree, disagree, strongly disagree

85
Q

ordinal data use

A

mann/whitney

86
Q

ordinal data tests differences in

A

rank order

87
Q

interval

A

continuous; scaled measure with arbitrary zero (temperature)

88
Q

interval difference between — is meaningful

A

levels

89
Q

tests for interval data

A

T-test or ANOVA

90
Q

interval tests differences in

A

means

91
Q

ratio

A

scaled measure with an absolute/true zero (test score)

92
Q

odds ratio (OR)

A

Comparing the odds of an event in one group to the odds of an event in a
comparison group

93
Q

what does odds ratio compare

A

subgroup and remained of population

94
Q

odds ratio is an estimate of

A

association

odds of female disease with exposure
offs of male disease with exposure

95
Q

relative risk/risk ration (RR)

A

Measure of risk based on a comparison of disease incidence in two
distinct groups

96
Q

relative risk/risk ratio (RR) compares subgroup to

A

entire population

97
Q

RR is the ratio of the

A

probability (percentage) of event occurring (or not occurring) in exposed vs non exposed group

98
Q

when exposure is negative

A

incidence rate of people exposed to risk factor

incidence rate of people not exposed to risk factor

99
Q

when exposure is positive

A

incidence rate of person not exposed to risk factor

incidence rate of people exposed to risk factor

100
Q

Both odds ratio and relative risk compare the

A

likelihood of an event occurring between 2 distinct groups. RR is easier to interpret and consistent with the general intuition (comparison between subgroup and entire population rather than subgroup and remainder of population)

101
Q

Experimental event rate (EER)

A

event rate in the treated/affected group

102
Q

Control event rate (CER)

A

event rate in the control/unaffected group

103
Q

Absolute Risk Reduction (ARR)

A

compares treatment effectiveness (CER-EER)

- How much does the treatment reduce the risk

104
Q

Attributable Risk

A

opposite of ARR (EER-CER)

105
Q

Relative Risk Reduction (RRR)

A

percentage of original risk removed (ARR/CER)

  • How much is risk reduced in comparison to the baseline
  • Not a good number/test (can inflate numbers or findings)
  • “more or less likely to happen”
106
Q

Number Needed to Treat (NNT)

A

number of patients needed to prevent one additional bad outcome
- 1/ARR – inverse of absolute risk reduction

107
Q

Sensitivity

A 
# of people who have the disease and test positive /# of
people who have the disease (SNOUT)

o Highly sensitive tests catch the disease every time

  • Sometimes they are wrong (false +)
  • Good at detecting/screening
108
Q

Specificity

A

of people who do NOT have the disease and test negative / # of people who do NOT have the disease (SPIN)

o Highly specific tests are rarely wrong

  • Sometimes they miss the diagnosis (false – )
  • Good at being right/confirming the diagnosis
109
Q

Positive Predictive Value

A

chance that when the test is positive you actually have the disease

110
Q

Negative Predictive Value

A

chance that when the test is negative you actually do NOT have the disease

111
Q

Hypothesis

A

assumed proposition

112
Q

Null Hypothesis

A

prediction that the observed difference is due to chance alone and not due to a systematic cause (“no difference”)

  • Statistics provide the evidence to reject or fail to reject the Null
113
Q

Type I error

A

false positive (alpha)

o No difference between groups when the study shows a difference

114
Q

Type II error

A

false negative (beta)

o Difference between groups when the study shows no difference

115
Q

confidence intervals

A

Most likely range within which the true size of effect lies

  • Confidence that if anyone reproduced this study they would have the
    same results due to independent variable(s)
  • Three things impact the width of a confidence interval
116
Q

Confidence level

A

typically 95%

117
Q

Variability

A

standard deviation

118
Q

Sample size

A

smaller sample sizes generate wider intervals

119
Q

P-value (“alpha level”)

A
  • Tests the likelihood of differences occurring by chance alone
  • Predetermined probability that the researcher is willing to make a type I
    error
120
Q

p < 0.05 =

A

5% probability that observed difference was due to chance

121
Q

Chi Square

A

Nominal data

122
Q

Mann-Whitney

A

Ordinal data

123
Q

T-test

A

Interval/ratio with 2 independent groups

124
Q

ANOVA

A

Interval/ratio with 3+ independent groups

125
Q

Statistical

A

used in hypothesis testing

126
Q

Clinical

A

practical importance of a treatment effect – whether it has a real,
palpable, noticeable effect on daily life

Clinical Decision Making (5 decks)

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