Lauren Summer 2025 > Research Basics > Flashcards

Research Basics Flashcards

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1
Q

Independent Variable

A

-manipulated
-intervention

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2
Q

Dependent Variable

A

-measured
-change in strength

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3
Q

Confounding Variable

A

-variable that could influence outcome of the study

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4
Q

Quantitative Research

A

-uses numbers
-IV manipulated
-reduce confounding variable
-t-test, ANOVA, mean med mode
-control is important

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5
Q

Qualitative Research

A

-understand a problem from the perfpective of the affected population
-interviews
-no control or manipulation of IV

Strengths:
-descriptions
-human side of issues

Limitations:
-time and cost
-cannot measure validity and reliability
-cannot be generalized

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6
Q

Single-Subject

A

-one or few participants measured several times
-usually unique pop or intervention

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7
Q

Nominal Scale

A

-qualitative
-identified only by name
-show differences in individuals

ex: gender, disease, zip code

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8
Q

Ordinal Scale

A

-qualitative
-ordered categories
-direction of differences between individuals
-no true number value (“subjective” numbers)

ex: no help, some help, independent, MMT

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9
Q

Interval/Ratio Scale

A

-quantitative
-ordered series of equal size
-direction and magnitude

Interval: zero is arbitrary
Ratio: real zero

ex: feet, temp, ROM, speed

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10
Q

Descriptive Studies

A

-Retrospective
-Normative
-qualitative

-describes data

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11
Q

Exploratory Studies

A

-correlational: relationships
-predictive: reliability and validity
-case control (quasi experimental)

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12
Q

Experimental Studies

A

-RCT only true
-cause and effect

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13
Q

Quasi-Experimental

A

-no manipulated IV
-pre exisiting variable
-cohort studies

You’re comparing two groups to see if something makes a difference.
But, you didn’t randomly choose who eats carrots and who doesn’t. You just used two classes that already existed.

ex: pre/post, dx A vs dx B

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14
Q

Alpha Level

A

-predetermed before study
-pre set significance level
-0.05 usually, 5% chance data relationships are not significant

Smaller: high risk - consequences of Type I error are high (false positive)
Larger: important even if theres a chance at not being effective

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15
Q

P-Value

A

-determined by outcome of study
-actualy probability that results occured by chance
- <0.05 to be significant (reject null hypothesis)

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16
Q

Validity

A
  • accuracy
    -info is believable and useful
    -does it measure what it says it measures
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17
Q

Internal Validity of Study

A

-did the IV cause the change in DV
-RCT is the best design to maximize

“where my methods sound?”

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18
Q

Internal Validity: History

A

-something happend between pre and post to change result

You are interested in studying the effects of an aquatic exercise program at varying intensities in
those individuals that are s/p CVA. All of the participants are at least 1 year post-stroke. You
randomly select 60 individuals for placement into three groups. One group will receive aquatic
therapy 3 x per week (180 minutes). One group will receive aquatic therapy 1 x per week (60
minutes) and one group will not receive any aquatic therapy. All individuals must provide their
own transportation. All groups will be asked to exercise at least 180 minutes per
week….therefore, if not in the pool, they will be performing a home exercise program. As part of
the pre-intervention testing, all participants completed a battery of physical performance tests
including the 6 minute walk. You recruit all of your participants from a local stroke survivor
support group by sharing a flyer with the group leader. It is October in Houston and the weather
has just cooled off so the support group will start their outdoor walking program for interested
individuals

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19
Q

Internal Validity: Maturation

A

-did participants change over time

ex: children aging, disease progression

During a class early in PT school, the students were given an exam on the best ways to approach the care of an individual with RA. Then the students were given 5 modules on the care of patients with RA during the first semester. Due to midterms and other classwork, the follow-up exam (determining if the educational intervention made a difference in the students’ learning) was given at the end of the 2nd semester.

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20
Q

Internal Validity: Attrition/Mortality

A

-who dropped out and why

Dr. Mitchell is conducting a study at the Star of Hope Homeless shelter in Houston. She has
trained 6 shelter volunteers to provide fun active games (as well as education on wellness) for the
children and their mothers on a daily basis to determine if there is an impact on their quality of
life both in the short and long-term while homeless. The volunteers start the program with 75
mother/child pairs. Over the course of the first week, 4 pairings are placed in temporary housing.
And over the next 6 weeks, all find temporary or permanent housing. 82% of the pairings return
for the follow-up testing

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21
Q

Internal Validity: Repeated Testing

A

-did the repetiitons change the outcome

ex: doing the same thing for weeks will ensure better performance

A PhD student was interested in the ability of individuals post-stroke to learn a new motor task with their lower extremity in a seated position. The participants were given a home program and
tested every week for six weeks to determine if the home program was improving their ability to perform the task.

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22
Q

Internal Validity: Instrumentation

A

-was the instrument changed
-calibrated

A PhD student was interested on whether or not an in-school exercise intervention could impact children with high BMIs in inner-city Houston. The outcome measure was weight, BMI and
percentage body fat and was tested at the beginning of the school year and again at the end of the school year. The intervention was to provide short duration, high intensity exercise bouts in
their school classroom by their teacher. The children were tested at seven different HISD
elementary schools using the PE teachers’ scales and the measurements were all done by the same researcher

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23
Q

Internal Validity: Regression to the Mean

A

-groups with extreme scores tend to regress towards mean

ex: really bad pt will get better and really good might stay or get worse closer to the mean

You are a researcher at TIRR and are conducting a study in collaboration with TWU professor. You
are interested in the impact of whole-body vibration on bone density in those individuals with post-polio syndrome. You recruit 30 participants with post-polio and randomly divide them into two groups. One group will receive the whole body vibration and the other will receive a sham treatment. The participants bone density was measured prior to the 4 week intervention and immediately following the intervention. The treatment group had a mean bone density pre- intervention of **T=-2.8 **and the sham group had a mean bone density pre-intervention of T=-1.8.
Following the intervention, the treatment group had a mean of T=-2.0 and the sham group had a mean of T=1.8. There was no difference between the groups after the intervention

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24
Q

Internal Validity: Experiementer Bias

A

-biased

Dr. Gleeson is the former head of the APTA education section and one of the main individuals responsible for CI training in the state of Texas. Dr. Gleeson is interested in studying the professional behaviors of CIs as viewed by the CIs themselves as well as by their students. All of the selected CIs have participated in Dr. Gleeson’s CI training courses. The students consent to participate at the start of the rotation and their views regarding their CIs are assessed half-way
through the rotation. The CIs are asked to consent half-way through the rotation and are assessed via a qualitative semi-structured interview at the end of the rotation. Dr. Gleeson will be conducting all of the interviews

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25
Internal Validity: Selection
-did the groups differ -sample not representative of population You are interested in the health habits of graduate students at TWU – all campuses. You randomly select **100 students from Houston as your sample**. You ask the participants to complete an extensive survey on diet, exercise, study schedules, health priorities, family health patterns, relaxation, etc. You plan on sharing your results with the new Chancellor of the University so that she can implement programs that would best serve the **graduate school student body as a whole**
26
Contruct Validity
-are we measuing what we think we are | ex: BMI as a measure of fitness
27
External Validity for Study
-can the results be generalized by the population -is it specific enough to have a difference but not too specific that you cant generalize it
28
Statistical Conclusion Validity
"Did I use the right stats?" Low Power: small sample size, too much variability -sample size too small to be representative -used the wrong test -error rate (Type 1: reject null when shouldnt or Type 2: fail to reject when should have
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Simple Random Sample
-everyone has the same chance
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Systematic Sampling
-select in a certain order ex: In a clinic, you could survey every 5th person who checks in on a given day. That’s systematic sampling: a fixed, regular pattern, starting from a random point.
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Stratified Sampling
-select sample then divide into parts -divide a population into individuals ex: 10 students from **every** age group
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Cluster Sampling
-double random -random population and randomly divide into groups ex: 5 random schools and select 10 random people from each of those schools
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Convenience Sampling
-members volunteer or self select -usual
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Sampling Error
the discrepency between a sample statistic and its population parameter -sample doesn't match population
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Cohen's D
-measure of effect size: meaningful amount of change -generally larger with bigger differences less variability = larger ES d= change in means/mean of SD's Small= 0.2 Medium= 0.5 Large= 0.8
36
Power
probability that a test will correctly reject a false null hypothesis (chance of finding a significant diff) -Increase effect size → increase power -increase number of participants → increase power | want a high power to reduce false negatives
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Validity
-how correct it is -measures what it should -cannot exit without reliability
38
Reliabiliy
-how consistent it is -degree of association -can exist without validity
39
Contingency Table
True Positive: a; tested positive with test; have the condition False Positive: b; tested positive; don't have the condition False Negative: c; tested negative; have the condition True Negative: d; tested negative; don't have condition
40
Sensitivity
-snout: rule out -true positive test -loves to give positive tests so if you test negative you CAN rules it out -true positive/(true positive + false negative)
41
Specificity
The proportion of people without the condition who are correctly identified as negative. -spin: rule in -true negative -shows all the negative so it rules in the positives -true negatives/(true negatives+ false positives)
42
predictive values
If the test result is positive, how likely is it that the person actually has the disease? "how much can i trust a positive test?" "Do they really have it?" Dependent on disease prevalence
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Predictive Value (+)
-If the test result is positive, how likely is it that the person actually has the disease? -true positive/(true positive + false positive) "There is a 25% chance that the disease is present when the test is positive" | What is the probability that a person with a + test has the condition?
44
a positive predictive value increases as the prevalence of a disease in a population ________.
increases
45
Predictive Value (-)
If the test is negative, how likely is it they don’t have the condition? -true negative/(true negative +false negative) "there is a ____% chance that the disease is NOT present when the test is negative"
46
negative predictive value increases as the prevalence of a disease in a population _____________.
decreases
47
likelihood ratios
How much a test result changes the odds of disease + rules in - rules out
48
Positive Likelihood Ratio
A high LR+ (e.g., >10) greatly increases the likelihood someone has the disease if the test is positive. -ratio of true to false -Sensitivity/ (1- Specificity) -higher= more likely
49
Negative Likelihood Ratio
-A low LR− (e.g., <0.1) greatly decreases the likelihood if the test is negative. -decreased odds of having condition if testing negative -ratio of false to true -(1- Sensitivity)/ Specificity -lower= less likely
50
Guide to Interpreting LR
-most powerful tool for quantifying importance of a particular test 10+, Best, inc by 45% 5+: OK, inc by 30% 2+: Poor, inc by 15% 1.0-: Useless, 0% 0.5-: Poor, dec by 15% 0.2-: Ok, dec by 30% 0.1-: Best, Dec by 45%
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Minimal Detectable Change
-MDC -amount of change needed to overcome measurement error -increase reliability of test decreases MDC
52
Minimal Clinical Important Difference
-MCID -amount of important change from the perspective of individual -should be bigger than MDC
53
One-Way Repeated Research Design
-one group doing the same thing over titme Your doctoral student would like to measure dynamic balance (limits of stability) on the Balance Master both before and after a balance training program that is pre-programmed in the Balance Master for individuals with PSP. She plans on **testing the participants before the training, immediately after the training, 6 weeks after the training and 6 months after** the training
54
Posttest-Only Randomized Group
-randomized -2+ groups that are only measured after the intervention 500 participants with LBP are randomized into 2 groups. One group receives manual therapy only and the other group receives the standard of care. Both groups have pain **assessed at discharge only**
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Posttest-Only Non-Randomized Research Design
-non randomized -2+ groups that are only measured after the intervention You are interested in comparing the length of stay (number of days) from your rehabilitation facility. **You decide to compare 3 groups of discharged clients**: individuals following a traumatic brain injury, a CVA, or a degenerative condition such as ALS or Parkinson’s disease
56
Factorial-Fully Independent Research Design
-2+ interventions at the same time -each person stays in the same group the whole time Is there is a difference among 4 groups of students that take kinesiology with a lab and those that take kinesiology without a lab with one of two different instructors? The outcome will be measured by the students’ performance on a comprehensive kinesiology final exam (I/R). **Students are randomly assigned to both an instructor and type of course structure.**
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Factorial-Fully Repeated Research Design
-2+ interventions at the same time -all participants switch groups throughout the study Is there a difference in athletes that train on various surfaces at various times of the day? **All athletes train on all surfaces and all of the available times of day.**
58
Factorial Mixed/Split Plot Research Design
-with or without randomization -Participants in designated groups move through repeated conditions (pre, post 1, post 2) -most common in PT 100 participants with vertigo treated at Richmond PT are randomized into three groups. All participants are measured before and after the intervention. **Two groups receive the intervention and one group receives a placebo**
59
Crossover Research Design
-with or without randomization -groups switch interventions after 1st is done Twenty participants with OA are to receive a new drug. They are randomized into 2 groups (one group receives a placebo). The participants are assessed before and after the drug is administered. **After 6 months with no treatment, the drug is given to the other group **and both groups are re-assessed both before and after the second drug administration.
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Measurement Theory
-psychometrics -foundation for evaluating tests and their uses -reliability and validity are most fuindamental measurment theory
61
Measurement Study
-any study that investigates the reliability or validity of a research measure
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Operational Definition
-objective variables must be defined in study
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Inter-Tester Reliability
-different raters get the same score -tester reliability
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Intra-Tester Reliability
-same rater coninuously gets the same score
65
Test-Retest reliability
-is the instrument consistent enough to get the same score -is the patient consistent enough to get the same score -instrument reliability
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Agreement
-if 2 ratings are similar or match exactly
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Parallel Reliability
-aka equivalent forms reliability -2 of the same tests are given to 2 groups -do the groups meausre similarly | 2 versions of same test
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Split-Half Reliability
-questions from the same sources are both giiven to one group -does the group measure the same on each | Test A split in half
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Face Validity
-does it measure what it's supposed to
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Content Validity
-dooes it measure the entirety of what it is suposed to according to experts
71
Criterion-Based Validity
-degree to whih the outcomes correlate with the gold standard
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Concurrent Validity
-degree to which the outcomes correlate with another test (gold standard or not) -given at the same time
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Predictive Validity
-can it be used to predict some outcome -Berg balance
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Construct Validity
-degree to which a theorhetical construct is measured by an instrument
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Responsiveness to Change
-extent to which significant changes in the participants are reflected -ceiling/floor effects alter this -more items: more responsiveness
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ROC (Receiver Operating) Curves
- a means to help establish cut off scores for a specific measure -Sensitivity vs False positives -Increased area under the line= high sensitivity and specificity -want greater than 1/2 under the line
Lauren Summer 2025
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