PC: Evidence Based Practice

Question 1

validity

Answer 1

the extent to which a test or measurement actually measures what it is intended to measure

*validity trumps reliability

Question 2

reliability

Answer 2

the extent to which a test or measurement produces consistent and stable results over time

Question 3

responsiveness

Answer 3

ability to detect change over time in the measured construct

Question 4

PT examples of responsiveness

Answer 4

ROM/flexibility
muscle strength
Pain
outcome measures

Question 5

true positive

Answer 5

a test that correctly identifies the presence of a condition

condition present

Question 6

false positive

Answer 6

the test that incorrectly identifies the presence of a condition

condition absent

Question 7

false negative

Answer 7

the test that misses the condition - it is present, but the test fails to detect it

condition present

Question 8

true negative

Answer 8

test that correctly identifies the absence of a condition

condition absent

Question 9

sensitivity

Answer 9

SnOUT: good for ruling out
“correctly identifies _ % of individuals with condition”

given that the individual has the condition, probability that test will be positive

true positive / (true positive + false negative)

Question 10

specificity

Answer 10

SpIN: rule in
“correctly identifies _ % of individuals who do NOT have the condition”, positive test → RULE IN

given that the individual does NOT have the condition, probability that the test will be negative

true negative / (true negative + false positive)

Question 11

100% sensitivity

Answer 11

the test detects ALL true cases of the condition, but may same some healthy people have the condition (false positives)

Question 12

100% specificity

Answer 12

if you test positive, you definitely have the condition, but it might miss some people who actually have the condition (false negatives)

Question 13

what is the difference between a good diagnostic test and a good screening test?

Answer 13

high sensitivity: diagnostic

high specificity: screening

Question 14

positive predictive value

Answer 14

given a positive test result, the probability that the individual has the condition

true positive/(true positive + false positive)

Question 15

negative predictive value

Answer 15

given a negative test result, the probability that the individual DOES NOT have the condition

true negative/ (true negative + false negative)

Question 16

limitations using predictive values

Answer 16

sample specific

depends highly on prevalence of condition in study population

Question 17

why will the predictive values look like in a condition with low prevalence?

Answer 17

lower positive predictive values → many false positives

higher negative predictive values → few false negatives

Question 18

likelihood ratios

Answer 18

combine sensitivity and specificity values to tell you how much a test result changes the probability of the disease

Question 19

positive likelihood ratio

Answer 19

given a positive test result → increase in odds favoring the condition

the increased LR+ → the more certain the individual has the condition (rule in)

sensitivity/(1- specificity)

Question 20

negative likelihood ratio

Answer 20

given a negative test result → decrease in odds favoring the condition

the decreased LR - (close to 0) → the odds that the individual has the condition is LESS (rule out)

(1-sensitivity)/specificity

Question 21

interpreting likelihood ratios: Positive LR

Answer 21

LR+ > 10 Large evidence to rule in disease
LR+ 5–10 Moderate evidence to rule in disease
LR+ 2–5 Small but sometimes meaningful increase
LR+ 1-2 No diagnostic value

Question 22

interpreting likelihood ratios: negative LR

Answer 22

LR- < 0.1 Large evidence to rule out disease
LR- < 0.1-0.2 Moderate evidence to rule in disease
LR- < 0.2-0.5 Small but sometimes meaningful increase
LR- < 0.5-1 No diagnostic value

Question 23

minimal detectable change

Answer 23

“are you better than the error”

statistic used to represent amount of change needed to exceed measurement error of the test
- reliability measure of change

Question 24

increase the reliability of the test → _____ MDC value in that population

Answer 24

decrease

*MDC values differ between different populations

Question 25

Minimal clinical important difference

Answer 25

"does it clinically matter (function)" smallest difference detected that represents an important improvement from the perspective of individuals with the condition MCID should exceed MDC