Research Flashcards

(48 cards)

1
Q

Clinical Trial

A
  • Tests how well methods of screening, prevention, dx or tx of a disease work in people
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Completely Randomized Design

A
  • Subjects are randomly assigned to different groups and each group receives a unique intervention
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Crossover Design

A
  • Subjects receive BOTH treatments in random ordered separated by period of NO TREATMENT
  • Subjects serve as their OWN CONTROL
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Factorial Design

A
  • 2 or more independent variables are investigated with different subjects assigned to the various combinations of levels of the independent variables
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Pretest-posttest Control Group Design

A
  • Compares outcomes of 2+ groups formed by random assignment by testing all groups BEFORE and AFTER treatment
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Posttest Only Control Group Design

A
  • Compares outcomes of 2+ groups formed by random assignment by testing all groups ONLY AFTER treatment
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

RCT

A
  • Clinical trial where individual is randomly assigned to an experimental group or control group
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Repeated Measure Design

A
  • Subjects are tested under ALL CONDITIONS

- Act as their OWN CONTROL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Sequential Clinical Trial

A
  • Data is analyzed as it becomes available so the trial can be stopped as soon as evidence is sufficient
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Single-subject Design

A
  • Drawing conclusions about the effects of treatment based on the responses of a single patient
  • Repeated measurements of a response over time
  • At least 2 test period phases: (1) baseline before treatment + (2) after treatment
  • Can be replicated
  • —– Ex: A-B, A-B-A, A-B-A-B, etc
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Quasi Experimental Design: One-group Pretest-posttest Design

A
  • Measurements are made on ONE group of subjects BEFORE and AFTER treatment
  • TIME is INDEPENDENT VARIABLE
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Quasi Experimental Design: One-way Repeated Measures Design Over Time

A
  • Extension of One-group Pretest-posttest design

- Measurements are made on one group of subjects at MULTIPLE, PRESCRIBED TIME INTERVALS

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Quasi Experimental Design: Time Series Design

A

Multiple Measurements are made BEFORE and AFTER treatment to observe patterns or trends during the pretreatment and posttreatment periods

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Nominal

A
  • Aka classification scale
  • Values of the variable are mutually exclusive and exhaustive categories
  • Can only be in ONE category
  • Qualitative
  • Ex: blood type, type of breath sound, type of arthritis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Ordinal

A
  • AKA Ranking scale
  • Data ranked on basis of a property of a variable, intervals between may not be equal or known
  • Ex: MMT, levels of assistance, pain, joint laxity grades
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Interval

A
  • Intervals between adjacent values are EQUAL, but NO TRUE ZERO
  • Ex: temperature
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Ratio

A
  • Intervals between adjacent values are EQUAL, AND there IS A TRUE ZERO
  • Ex: ROM, distance walked, time to complete an activity, nerve conduction velocity
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Reliability

A
  • Reproducibility or repeatability of measurements
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Reliability: Alternate Forms Reliability

A
  • AKA Parallel Form Reliability
  • Assesses the consistency or agreement of measurements obtained with different forms of a test
  • NECESSARY if different forms of test are to be used INTERCHANGEABLY
  • ——Ex: NPTE
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Reliability: Internal Consistency

A
  • Extent to which items or elements that contribute to a measure reflect one basic phenomenon or dimension
21
Q

Reliability: InTRArater Reliability

A
  • Same person over time
22
Q

Reliability: InTERrater Reliability

A
  • Different people
23
Q

Reliability: Test-retest Reliability

A
  • Same individual on separate occasions
24
Q

Validity

A
  • Degree to which a useful of meaningful interpretation can be inferred from a measurement
25
Validity: Face Validity
- Degree to which a measurement appears to test what it is supposed to
26
Validity: Content Validity
- Degree to which a measurement reflects the meaningful elements of a construct and the items in a test adequately reflect the content domain of interest and not extraneous elements - Whoever wrote this should burn in hell
27
Validity: Construct Validity
- Degree to which a theoretical construct is measured by a test or measurement
28
Validity: Criterion-related Validity
- Validity of the measurement is established by comparing it to either a different measurement (gold standard) or data obtained by different forms of testing
29
Validity: Criterion-related Validity: Concurrent Validity
- Comparing a measurement to a "gold standard" at APPROXIMATELY THE SAME TIME
30
Validity: Criterion-related Validity: Predictive Validity
- Measurement is considered to be valid because it is predictive of a future behavior or event - Ex: High school GPA to predict performance in college
31
Validity: Criterion-related Validity: Prescriptive Validity
- Measurement suggests the form of treatment a person should receive
32
External Validity
- Degree to which results of the research study are generalizable to populations or circumstances beyond those included in the study - Threats: interaction of tx with specific type of subjects tested, setting/place and time/history in which the experiment is performed
33
Internal Validity
- Degree to which an intervention being evaluated is the cause of the outcome measured in the study - Threats: history, maturation, attrition, testing, instrumentation, regression toward the mean
34
Type I Error (Alpha Error)
- Aka false positive - Concluding there is a relationship when there is NOT - Wrongly rejecting the null hypothesis
35
Type II Error (Beta Error)
- Aka false negative - Concluding there is NOT a relationship when there is one - Wrongly deciding not to reject the null hypothesis
36
Effect Size
- Measure of the magnitude of the difference between 2 treatments or the magnitude of the relationship between 2 variables - LARGER ES = more likely it is statistically significant
37
Effect Size Index
- Represents effect size using a standardized value - Calculation: Mean control group - (subtract) mean experimental group / (divided by) std deviation of one of the groups - ------ < 0.1 = trivial effect - ------ 0.1 - 0.3 = small effect - ------ 0.3 - 0.5 = mod effect - ------ > 0.5 = large effect
38
Minimal Clinically Important Difference (MCID)
- Smallest difference in condition that the patient or PT consider WORTHWHILE
39
Minimal Detectable Change (MDC)
- Smallest difference that is NOT DUE TO CHANCE = that it is statistically significant
40
Standard Deviations
- 1 std deviation (above + below) = 68% - 2 std deviations (above + below) = 95% - 3 std deviations (above + below) = 99%
41
Coefficient of Variation (CV)
- Ratio of the std deviation of a distribution to the mean - Expressed as a % - Equation: CV = (s / mean) x 100
42
Parametric Stats
- Assume samples come from NORMAL DISTRIBUTION
43
Parametric Stats: ONE-Way Analysis of Variance (ANOVA)
- Tests the equality of means between 2 or more populations by analyzing sample variances - Similar to t-test but accommodates 2+ population means - Separated into different groups on the basis of ONE characteristic/factor/independent variable
44
Parametric Stats: TWO-Way Analysis of Variance (ANOVA)
- Tests the equality of means between 2 or more populations by analyzing sample variances - Compare 2+ population means with 2 independent variables
45
Parametric Stats: Repeated Measure ANOVA
- All individuals are measured under a number of different experimental conditions - Used ONLY if there is limited learning/carryover
46
Pearson Product Moment Correlation
- Measures the magnitude + direction of a linear relationship between 2 variables - Range -1.0 to +1.0 - ---- -1.0 = inverse relationship in a straight line - ---- +1.0 = both increase/decrease at the same time - ---- 0 = no relationship
47
Sensitivity
- The % of people who test positive for a specific disease who actually have the disease (i.e. testing positive when the person ACTUALLY has it) - SNOUT - used to rule out a dx because if the test is NEGATIVE the person does NOT have it (because if it were positive the test would be positive)
48
Specificity
- The % of people who test negative for a specific disease who do NOT have the disease (i.e. testing negative when you do NOT actually have it) - SPIN - used to rule IN a dx because if it is POSITIVE the person HAS it (because if it was negative the test would be negative)