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Evidence Based Practice > Fall 2023 > Flashcards

Fall 2023 Flashcards

1
Q

What is a natural disease?

A

The usual course of disease over time

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2
Q

Prognostic Factor

A

Something (environmental factor, personal characteristic, behavior) that can be used to estimate the chance of recovery or recurrence

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3
Q

Risk Factor

A

Something (environmental factor, personal characteristic, behavior) that increases the chance of developing a disease

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4
Q

Prospective Cohort Study

A

1- Identify Sample at Risk
2- Asses Risk Factors @ Interest
3- Measure who develops outcome/not

Incidence (rate of developing)
Risk Ratio

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5
Q

Retrospective Case-Control Study

A

1- Collect data/review chart or records to determine who had exposure/risk factor or not
2- Identify “Cases” and “Controls”

Prevalence
Odds Ratio

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6
Q

Prevalence

A

Number of people who have the outcome at a given point in time / # of people at risk at that point in time

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7
Q

Incidence

A

Number of new people who develop the outcome over a period of time / # at risk during that period

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8
Q

Risk Ratios // Relative Risk

A

Likelihood with which those that have the risk factor will develop the outcome compared to those that don’t have the risk factor (prospective)

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9
Q

Odds Ratios

A

Likelihood with which those who have a condition (or outcome) have been exposed to a risk factor compared to those who don’t have the condition (retrospective)

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10
Q

Relative Risk - Cross Tabulation

A

a/(a+b)
_______
d/(c+d)

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11
Q

Odds Ratio - Cross Tabulation

A

ad
___
bc

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12
Q

RR/OR > 1

A

RR/OR - 1 = __ * 100% =
___% increase in Risk/Odds

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13
Q

RR/OR < 1

A

1 - RR/OR = __ * 100% =
___% reduction in Risk/Odds

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14
Q

Rule with RR/OR Confidence Interval

A

If it includes 1, there is no significance

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15
Q

Unadjusted or Crude Odds Ratio

A
  • 2x2 Table or Logistic Regression
  • Accounts for One Relationship
  • One Independent, One Dependent
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16
Q

Adjusted Odds Ratio

A
  • Calculations using Logistic Regression
  • Accounts for Multiple Variables that Might Affect Relationship
  • Multiple Independent Variables
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17
Q

Internal Validity

A

Relationship between independent (intervention) and dependent (outcome) variable

Tight control of experiment leads to higher internal validity

Efficacy of Treatment

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18
Q

External Validity

A

Extent to which the independent (intervention) and dependent (outcome) can be generalized outside of the experiment

Tight control of experiment can decrease external validity

Effectiveness of Treatment

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19
Q

Efficacy

A

Benefit of an intervention in an experimental setting
-Control of many variables

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20
Q

Effectiveness

A

Benefit of an intervention in a real-world setting
-Less control of variables, bias

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21
Q

Threats to External Validity

A

Selection
Setting
History
Intervention/Protocol
Construct Validity

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22
Q

Statistical Inference

A

Estimating characteristics of a population (parameter) from sample data (statistics)
-Population aggregate of persons/objects/events that meet a specific criteria

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23
Q

Probability Sampling

A

Simple Random
Systemic
Cluster
Stratified Random (Proportional / Disproportional)

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24
Q

Non-Probability Sampling

A

Convenience (Consecutive / Volunteer)
Quota
Purposive

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25
Q

Inclusion Criteria

A

Primary traits of the target and accessible population that qualifies them as a subject

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26
Q

Exclusion Criteria

A

Factors that would preclude someone from being a subject

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27
Q

WEIRD Bias

A

Western (White)
Educated
Industrialized
Rich
Democratic

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28
Q

Construct Validity

A

Abstract behavior or event that cannot be directly observed, but is inferred from other relevant observable variables

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29
Q

Operational Definition

A

The measure(s) used by a particular study to quantify the construct

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30
Q

Parametric Tests

A

-Estimation of Population
-Assume Normal Distribution
-Often continuous/discrete variable

Ex: T-test, ANOVA

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31
Q

Non-Parametric Tests

A

-Not based on population parameters
-Assuming Non-Normal Distribution
-Nominal or Ordinal Variables

Ex: Mann-Whitney U Test, Wilcoxon Signed Rank Test, Friedman/Kruskal-Wallis ANOVA, Chi-Square or Fisher Exact Test

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32
Q

ANOVA

A

More than 2 groups (independent or dependent/repeated measures)

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33
Q

T-Test

A

Between two groups (independent or unpaired)

Within one group (before & after intervention) (dependent or paired)

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34
Q

alpha

A

% chance that we found a difference but there wasn’t one (chance of type 1 error)

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35
Q

p

A

How rarely we would expect a difference this large (found in the study) by chance

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36
Q

Effect Size - Index/Ratio

A

Difference between groups (treatment + error) / variability within groups (error) = Cohen’s d

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37
Q

Cohen’s d

A

Index/Ratio

0.2 - 0.5 = small
0.5 - 0.8 = medium
> 0.8 = large **lower variability/rule of thumb too large

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38
Q

Type I Error (alpha)

A

Conclude an effect is real when it is actually due to chance // found a difference when there really isn’t

-extremely large samples make it easier to find significant effect

1 - .95 = .05(alpha) —> 5% risk of Type 1 Error

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39
Q

Type II Error (beta)

A

Conclude an effect is due to chance when it is actually real // found no difference when there really is

-not enough subjects per group to detect difference

.8 power = 1 - beta(.20) —> 20% risk of Type 2 Error

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40
Q

a priori

A

planned comparisons prior to data collection

can correct for Type 1 Error with alternate t-test (Bonferroni)

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41
Q

Post-hoc

A

unplanned comparisons made after data is analyzed (ANOVA)

can correct for Type I error with alternate t-tests (Tukey’s)

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42
Q

Confounding Variable

A

Anything other than the independent variable that could potentially affect the dependent variable

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43
Q

Stratification

A

Equal recruitment in each group to decrease confounding variable (known prior to recruitment)

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44
Q

Blocking

A

Randomized sequence in pre-determined blocked groups to ensure equal distribution between groups

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45
Q

Bias

A

Any tendency which prevents unprejudiced consideration of a question

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46
Q

Selection Bias

A

Selecting non-equivalent groups

RCT

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47
Q

Maturation Bias

A

Time on the health condition recovery (natural history)

RCT

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48
Q

Concealment

A

When the person who is screening the participants for eligibility does not know the randomization sequence

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49
Q

Performance Bias

A

When participants or personnel perform differently based on knowing what group they are in

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50
Q

Detection Bias

A

When the personnel assessing the outcomes perform differently based on knowing what group participants are in

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51
Q

Blinding

A

Reduces bias by keeping researchers and/or participants ignorant of group assignments and/or research hypotheses (single/double/assessor)

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52
Q

Attrition Bias

A

Effects of loss of participants during the trial (drop outs)

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53
Q

Standardized Reporting

A

Reporting number loss to follow-up at each time point (intention to treat analysis performed)

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54
Q

Intention to Treat

A

Data analyzed according to group assignment, regardless if subject completes study or “switches” group

Attrition > 20% then question results

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55
Q

Testing Bias

A

Confounding effects of repeated testing or use of an outcome

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56
Q

Instrumentation Bias

A

Poor reliability of tests/outcomes can influence outcomes

57
Q

Standardization

A

Standardize # of Tests/Order or Valid Outcomes/Standardize Procedures

58
Q

PICO

A

Population
Intervention
Comparison
Outcome

59
Q

Health Condition

A

Medical Disease, Disorder, Syndrome, or Injury

60
Q

Participation Restriction

A

Difficulty with Involvement in life situation or social role

61
Q

Activity Limitation

A

Difficulty with Execution of a task or action by an individual

62
Q

Impairments

A

Problems in body structure(s) and/or function(s)

63
Q

Personal Factors

A

Any identifiable element intrinsic to a person (including physical and psychological co-morbidities) that influences the way that person conducts his or her life

64
Q

Environmental Factors

A

Any identifiable element extrinsic to a person (including physical and psychological co-morbidities) that influences the way that person conducts his or her life

65
Q

Background Searching

A

-General Information
-Novice on Topic
-General Question

66
Q

Foreground Searching

A

-Specific Clinical Question
-Comparison of Intervention
-Properties of Test and Measures
-Prognostic Factors
-Answers clinical question applied to patient

67
Q

Where to do Background Searches

A

APTA
Physio-pedia
RehabMeasures
UptoDate
Clinical Key

68
Q

Where to do Foreground Searches

A

PubMed

69
Q

PACO

A

Person
Assessment (Test/Measure)
Comparison Assessment
Outcome

70
Q

PECO

A

Person
Exposure (Risk/Prognostic Factor)
Comparison Exposure
Outcome

71
Q

What sections of a research paper are most objective?

A

Methods & Results

72
Q

What sections of a research paper are most subjective?

A

Abstract
Intro
Discussion
Conclusion

73
Q

Cross Sectional Design

A

-Observations/Surveys/Measurements made at one time point (or multiple, but no intervention)
-Correlation/Association of 2 Variables

74
Q

Advantages/Limitations of Cross Sectional Design

A

Advantages:
-Efficient
-Inexpensive
-Minimal Loss to Follow Up

Limitation:
-No Time Component
-Correlation/Association Only (No Causation)

75
Q

Prospective Cohort Design

A

-Identify sample, “Follow” over time
-Common design for prognosis
-Emphasis on “Risk of Developing”

76
Q

Advantages/Limitations of Prospective Cohort Design

A

Advantages:
-Establish Temporal Association
-Short Intervals of Exposure to Outcome & Common Conditions
-Multiple Exposures

Limitations:
-Expensive
-Long Follow Up (Attrition)
-Not Ideal for Rare Outcomes

77
Q

Retrospective Design

A

-Identify Outcomes and “Go Back” to Determine Exposures
-Emphasis on odds of having a past exposure given already having the condition

78
Q

Advantages/Limitations of Retrospective Design

A

Advantages:
-Less Expensive
-Little/No Attrition
-Better for Rare Outcomes
-Relatively Easy to Collect Data

Limitations:
-Dependence on Medical Records/Patient Reporting
-Recall Bias
-Less Certain for Temporal Relationship
-Prevalence not Incidence

79
Q

Randomized Control Trial Design

A

-Studying Intervention Efficacy
-Compares at least 2 groups
-Randomly assigned groups
-Intervention Implemented, while controlling other variables

80
Q

Advantages/Limitations of RCT

A

Advantages:
-Controls/Reduces Bias
-Creates Similar Groups at Baseline
-Conclusions to Infer Cause/Effect

Limitations:
-Costly & Time Intensive
-May not be Generalizable
-Attrition Risk is High

81
Q

Quasi-Experimental Design

A

-Lack Random Assignment/Comparison Group
-Or only one group gets intervention (pre/post)
-Increased Bias to RCT

82
Q

Case Report or Case Series Design

A

-In-depth study/description of a patient
-Rare condition, Combination of Conditions, Novel Treatment
-Insight into Clinical Decision Making

83
Q

Parameters

A

Measured Characteristic of a Population

84
Q

Statistics

A

Measured Characteristic of a Sample

85
Q

Continuous

A

-Data that takes on any value along a continuum
-Infinite Number of Fractional Values

Ex: Strength, Distance, Weight

86
Q

Discrete

A

-Can only be described in whole units
-Cannot be divided further

Ex: People, Number of Groceries you buy

87
Q

Dichotomous

A

Can only have two values

Ex: Heads/Tail, Yes/No

88
Q

Ratio

A

Numbers represent units with equal intervals (related to zero)

Ex: distance, age, time, weight, strength, ROM

89
Q

Interval

A

Equal intervals between numbers (not related to zero)

Ex: Calendar Years, IQ, Degrees

90
Q

Ordinal

A

Numbers indicate rank order of observations (unequal intervals)

Ex: MMT, Pain Scale

91
Q

Nominal

A

Numerals represent category labels only

Ex: Sex, Nationality, Blood Type, Clinical Diagnosis

92
Q

Independent Variable

A

-Can predict or cause a given outcome
-What is being controlled/manipulated

93
Q

Dependent Variable

A

-Response that varies with changes in the independent variable
-The Measured Outcome

94
Q

Mean

A

Sum of Scores / # of Scores (Average)

Parametric Analysis
-Continuous Variables
-Non-Continuous but Normal Distribution

95
Q

Median

A

Divides a rank-order distribution into equal parts

Non-Parametric Analysis

96
Q

Point Estimate

A

A single statistic that estimates population parameter

97
Q

Variability for Mean

A

Standard Deviation

98
Q

Variability for Median

A

Range (difference between lowest and highest values)

Interquartile Range (divides into four equal quartiles)

99
Q

Confidence Interval

A

-A measure of variability of the mean
-Estimates a range of scores that can contain the “true” population mean
-Specified Certainty (typically 95%)

100
Q

Type I Error

A

Acceptable Risk of Falsely Concluding that an effect is real

Alpha ~ 0.05 … 5% chance a difference was found, when there really wasn’t

101
Q

Probability / P-Value

A

Probability of finding an effect as big as the one observed in the study BY CHANCE

102
Q

P < Alpha

A

Significant Effect

103
Q

P > Alpha

A

No Significant Effect

104
Q

Correlation + 2 statistics used

A

A measure of the relationship between two variables

Pearson product moment correlation (r) = normally distributed

Spearman’s rho (p) = not normally distributed

105
Q

Positive and Negative values for Correlation

A

+ = Directly or Positively related
- = Inversely or Negatively related

106
Q

Simple Linear Regression

A

Establishes relationship between two variables as a basis for prediction
(scatter plot, regression equation, evaluate)

107
Q

R^2 (Coefficient of Determination)

A

Accuracy of prediction of linear regression equation

0 = no accuracy
1.0 = full accuracy

108
Q

Multiple Linear Regression

A

Established the predictive relationship between a set of independent variables and one dependent variable

109
Q

Outcome Measure vs. Diagnostic Test

A

Measure & Track Changes

Identify, Diagnose or Discriminate

110
Q

Validity

A

The extent to which a test is measuring what it is intended to measure

111
Q

Convergent

A

Two measures reflecting the same construct will have similar results in the same group

or

The ability of a test to measure same construct in different groups

112
Q

Discriminant

A

Two measures reflecting different constructs will have different results when measured in same group

or

One measure having different results in different groups

113
Q

Concurrent

A

Measures compared with each other at the same time

Often to establish properties of newer, more feasible measure

114
Q

Reliability

A

The extent to which a measure is consistent and free from error

115
Q

Test-Retest Reliability

A

measures the stability of an instrument or test (consistency)

EX: identical test performed on two different occasions

116
Q

Rater Reliability:
Intra vs. Inter

A

Intra - stability of data recorded by a single rater across multiple trials

Inter - stability of data recorded by multiple raters when measuring the same variable

117
Q

Intraclass Correlation Coefficient (ICC)

A

A single index that reflects both correlation and agreement among ratings

0 - not reliable
1- perfectly reliable

118
Q

Reference Standard

A

The “Gold Standard” of an existing diagnostic tool

119
Q

Validity is to Reliability
as
Diagnostic is to ______

A

Outcome Measure

120
Q

Sensitivity

A

-The probability that someone with the condition will test positive
-The ability of the test to be positive when the condition is present

121
Q

Specificity

A

-The probability that someone without the condition will test negative
-The ability of a test to be negative when the condition is absent

122
Q

What type of error is correlated to sensitivity?

A

Type I Error
False Positives

123
Q

What type of error is correlated to specificity?

A

Type II Error
False Negatives

124
Q

Utilizing the Receiver Operating Characteristic (ROC) Curve with sensitivity and specificity, what constitutes excellent vs useless?

A

Area under the curve

.9-1.0 = excellent
<.6 = useless

125
Q

Positive Predictive Value

A

Probability of a. person testing positive and having the condition

(true positive / (true + false positive))

126
Q

Negative Predictive Value

A

Probability of a person testing negative and not having the condition

(true negative / (true + false negative))

127
Q

SPin

A

With high specificity, a positive test rules IN the diagnosis

128
Q

SNout

A

With high sensitivity, a negative test rules OUT the diagnosis

129
Q

Positive Likelihood Ratio

A

How many times more likely a positive test will be seen in those with the disorder than in those without the disorder

(Sensitivity/1-Specificity)
(True Positives / False Positives)

130
Q

Negative Likelihood Ratio

A

How many times more likely a negative test will be seen in those without the disorder than in those with the disorder

(1-Sensitivity/Specificity)
(False Negatives/True Negatives)

131
Q

Closer or Further from 1.0 indicates more important results for Likelihood Ratios?

A

Further

132
Q

Narrative Review

A

Summary of literature, often single author, does not address question rather it is a background on a topic, potentially biased

133
Q

Systematic Review

A

Usually PICO formatted question, systematic search, structured appraisal, critical assessment and evaluation of research

134
Q

Meta-Analysis

A

Systematic review using quantitative methods to combine results (pooling)

135
Q

Publication Bias

A

The publication or non-publication of research findings, depending on the nature and direction of the results

(not publishing because the outcome was not interesting or in the direction desired)

136
Q

Two tools for assessing risk of bias

A

PEDro Scale (Physiotherapy Evidence Database)
Cochrane Risk of Bias Tool

137
Q

Heterogeneity

A

The scale of differences between study’s ….. populations, treatment groups, design of study, attrition, length of follow up, treatment, outcomes, interventions

138
Q

Homogeneity and chart used

A

When studies have common ______.

Forest Plot used to compare different values amongst the individual studies.

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