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EBP :/ > Module 6-Slides > Flashcards

Module 6-Slides Flashcards

1
Q

Measurement

A

Process of assigning NUMERALS to variables to represent QUANITITIES of characteristics according to certain rules

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2
Q

Construct

A

An ABSTRACT variable that is not observable and is defined by the measurement used to assess it
Considered a latent trait because it reflects a property within a person and is not externally observable
~intelligence, health, pain, mobility, and depression

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3
Q

Purpose of Measurement

A

Way of understanding, EVALUTING, and differentiating characteristics of people, objects, and systems by scientists and clinicians
Allows to communicate in ONJECTIVE TERMS, giving a common sense of “how much” or “how little” w/out ambiguous interpretation

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4
Q

Levels of Measurement

A

Nominal
Ordinal
Interval
Ratio

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5
Q

Ratio

A

Distance, age, time, decibels, weight / Numbers represent units with equal intervals, measured from true zero
*The highest level of measurement with an absolute zero point

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6
Q

Interval

A

Calendar years, Celsius, Fahrenheit / Numbers have equal intervals, but no true zero
*Possesses rank order but also has known and equal intervals between consecutive values but no true zero

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7
Q

Ordinal

A

Manual muscle test, function, pain assessment scale / Numbers indicate rank order
*A rank-ordered measure where intervals between values are unknown and likely unequal

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8
Q

Nominal

A

Gender, blood type, diagnosis, ethnicity / Numerals are category labels
*Classifies objects or people into categories with no quantitative order

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9
Q

T/F Measurements cannot be taken at different LEVELS or rated using various SCALES.

A

False; Measurements CAN be taken at different LEVELS or rated using various SCALES

Example: pain measurement
yes or no: nominal scale
from 0-10: ordinal scale

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10
Q

Why is it important to accurately identify the “level” of measurement?

A

Because Selection of Statistical tests is based on certain assumptions about data including but not limited to the level of measurement

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11
Q

Parametric tests

A

Arithmetic manipulations requiring Interval or Ratio level of data

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12
Q

Nonparametric tests

A

Do not make the same assumptions; are used with Ordinal or Nominal data

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13
Q

Reliability

A

The extent to which “a measured value can be obtained CONSISTENTLY during REPEATED assessment of unchanging behavior”

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14
Q

What are the 2 basic types of measurement error?

A

Systematic error
Random error

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15
Q

Systematic error

A

Predictable, occurring in a consistent overestimate or underestimate of a measure

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16
Q

Random error

A

Have no systematic bias and can occur in any direction or amount

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17
Q

Sources of measurement error

A
  1. Measuring INSTRUMENT itself: does not perform in the same way each time
  2. The person/individual taking the measurements (the rater): does not perform the test properly
  3. VARIABILITY of the characteristic being measured: the variable being measured is not consistent over time (ex: BP)
18
Q

Reliability coefficient

A

Provide values that help estimate the degree of reliability (a range from 0.0 to 1.0)

19
Q

4 general approaches to reliability testing

A
  1. Test-retest reliability
  2. Rater reliability
  3. Alternate forms
  4. Internal consistency
20
Q

Test-Retest Reliability

A

An assessment of how well an instrument will perform from one trial to another assuming that no real change in performance has occurred

Coefficient:
-ICC (Intraclass correlation coefficients) for quantitative
-Kappa coefficient for categorial

21
Q

Inter-Rater (two or more raters) Reliability

A

Concerns variation between two or more raters who are measuring the same property

Coefficient: ICC or Kappa

22
Q

Intra-Rater (one rater) Reliability

A

A measure of the stability of data recorded by one tester across two or more trials

Coefficient: ICC or Kappa

23
Q

Change Scores

A

Reflect difference in performance from one session to another, often a PRETEST AND POSTEST. If measures don’t have strong reliability, change scores may primarily be a reflection of error

24
Q

Reliability of measurement

A

A prerequisite for being able to interpret change scores

25
Q

Minimal detectable change (MDC)

A

Amount of change in a variable that must be achieved beyond the minimal error in a measurement, a threshold above which can be confident that a change reflects true change and not just error

26
Q

Minimal detectable difference (MDD)

A

Amount of change that goes beyond error; smallest real difference, smallest detectable change, or the reliability change index

27
Q

Measurement validity

A

Concerning the meaning or interpretation that we give to a measurement
Characterized as the extent to which a test measures what itis intended to measure

28
Q

Distinctions
Between
Reliability and Validity

A

Reliability relates to consistency of a measurement
Validity relates to alignment of the measurement with a targeted construct
Measuring validity is NOT as straightforward as reliability

29
Q

Similarities
Between
Reliability and Validity

A

Do not consider it as all-or-none (1 or 0)

30
Q

How can validity be fairly evaluated?

A

Only within the context of an instrument’s intended use

31
Q

Reliability and Validity scores

A

A. Scores are reliable, not valid (missing the center)
B. Scores show random error, average validity (near the center)
C. Scores are not reliable, not valid (off the center)
D. Scores are both reliable and valid (center)

32
Q

T/F A reliable measure guarantees that the measure is valid

A

False; it does NOT guarantee it

33
Q

Types of Evidence for Validity

A

Depending on specific conditions, several types of evidence can be used to support a tool’s use, often the 3 Cs

34
Q

The 3 Cs

A
  1. Content validity
  2. Criterion-related validity
  3. Construct validity
35
Q

Content validity

A

Establishes that the multiple items that make up a questionnaire, inventory, or scale adequately sample a wide domain or (the UNIVERSE of content) that defines the variable or construct being measured

36
Q

Criterion-related validity

A

Establishes the correspondence between a Target test (to be validated) and a REFERENCE OR “GOLD” STANDARD (as the criterion) to determine that the Target test is measuring the variable of interest

37
Q

Construct validity

A

Establishes the ability of an instrument to measure the dimensions and theoretical foundation of an abstract construct
~Abstract constructs do not directly manifest as physical events; thus, making inferences through observable behaviors, measurable performance, or patient self-report

38
Q

Minimal clinically important difference (MCID)

A

Smallest difference that signifies an important difference in a patient’s condition

39
Q

Methodological Research

A

Involves the development and testing of both reliability and validity of measuring instruments to determine their application and interpretation in a variety of clinical situations

40
Q

Ways to maximize Reliability

A

Standardize measurement protocols
Train raters
Calibrate and improve the instrument
Take multiple measurements
Choose a sample with a range of scores
Pilot testing

41
Q

Ways to maximize Validity

A

Fully understand the construct
Consider the clinical context
Consider several approaches to validation
Consider validity issues if adapting existing tools
Cross-validate outcomes

EBP :/ (11 decks)

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