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OT 520 Research > Final > Flashcards

Final Flashcards

1
Q

Basic science research (benchtop)

A

acquisition of new knowledge for its own sake, motivated by intellectual curiosity, without reference the potential practical use of results

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2
Q

Translational research

A

the application of basic scientific findings to clinically relevant issues and simultaneously, the generation of scientific questions based on clinical dilemmas

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3
Q

Applied Research

A

is directed toward solving immediate practical problems with functional applications and testing the theories that direct practical

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4
Q

Hierarchy of Evidence

A

prioritizing sources of knowledge based upon their scientific rigior (and how relevant it is to your clinical question)

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5
Q

Experimental Design

A

Allows for manipulation of independent variables
Longitudinal or cross sectional study
Prospective study (occuring in “real time”)

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6
Q

Non-experimental design

A

CAN NOT manipulate independent variable (ex: case study, case control, thematic analysis)
Correlational study
Retrospective study (looking over past studies)

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7
Q

Descriptive Statistic

A

characterizes shape, central tendency, and variability within a set of data, often with the intent to describe a population

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8
Q

Inferential Statistics

A

To derive a conclusion from facts or premises

involves a decision making process that allows us to estimate population characteristics from sample data

analysis of data is based on testing a statistical hypothesis, which differs from the research hypothesis in that it will always express no difference or relationship between the independent and dependent variables.

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9
Q

Variable

A

a property that can differentiate individuals or objects. It can be a number or characteristic that is coded in numerical form

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10
Q

Independent variable

A

presumed to cause, explain or influence a dependent variable, a variable that is manipulated or controlled by the researcher, who sets its values or levels

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11
Q

Dependent variable

A

a response variable that is assumed to depend on or be caused by another (independent variable)

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12
Q

Continuous variable

A

a # that can take on any value along a continuum within a defined range (like a number line). Between any 2 points, there exists an infinite number of fractional values -> THINK QUANTITATIVE DATA

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13
Q

Discrete Variable

A

can ONLY be described in whole units. If the choices are only 2, you can call them dichotomous variables -> THINK QUALITATIVE DATA

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14
Q

Ratio

A

scale data, measurements along a continuous scale whole scale begsins at 0 (length or width), distance, age, time

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15
Q

Interval

A

scale data, same as ratio, but data do not have 0 as low end of scale years, degrees (C, F)

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16
Q

Ordinal

A

scale data, generally used for irregular scaled data converted to ranks or relative position manual muscle test, function, pain

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17
Q

Nominal or categorical data (ex: binary data)

A

gender, blood type, dx

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18
Q

Single Factor Experimental

A

manipulates 1 independent variable but the independent variable may have diff levels if the variable is exercise, levels may be no exercise, aerobic exercise or weight training.

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18
Q

Alternative hypothesis

A

true difference between the groups and the treatment was effective

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19
Q

null hypothesis

A

statistical hypothesis which states that the group means are not different

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20
Q

Repeated measures design

A

WITHIN subjects design, results of one intervention compared to results of another intervention in the same subjects
Same subjects are measured under ALL levels of the independent variable.
VERY powerful design, as using same subjects as their own controls eliminates threats to internal validity

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21
Q

Single subject design (n of one)

A

results of one intervention compared to results of another intervention in the same subject

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22
Q

Single-case experimental design (SCED)

A

researcher controlling for variables

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23
Q

Single Subject (ABA or Withdrawl Design)

A

A: the number of observarions with no treatments
B: number of observations with treatments
If the treatment is successful there should be improvement on the dependent varaible in the B sessions. To show the improvement is the effect of the IV, A session is given. If improvement reverse, the hypothesis is supported.

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24
Q

Single Subject (ABAB Design)

A

Represents an attempt to measure a baseline (the first A), a treatment measurement (the first B), the withdrawl of treatment (second A), and the re-intro of treatment (the second B).

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25
Q

Ethnography

A

Discover and describe the perspective of people or social scene/cultural group, a systematic investivagtion of language, activities, routines, structures of social life, relationsips, and cultural beliefs (habits)

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26
Q

Phenomenology

A

A way of doing research (method) and a way of conceptualizing thought
How the ordinary/ everyday experience is perceived and expressed by the individual

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27
Q

Grounded theory

A

Inductive reasoning designed to construct a theory
Theory emerges from already collected data
The theory is a generalization of the empirical data collected by the investigator
Existed theory doesn’t direct the investigation

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28
Q

Skewness

A

a measure of symmetry or more precisely the lack of symmetry, a NORMAL distribution or data set is symmetric (skewness = 0)

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29
Q

Kurtosis

A

a measure of whether the data are peaked or flat relative to a normal distribution

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30
Q

Variance

A

compare how much one group will vary from another

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31
Q

Standard deviation

A

how much variability there is within a dataset that is expressed in terms of the same units as the dataset in question
SD reported with the average mean as a way to express something about how variable the sample datasets are

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32
Q

z-score

A

a statistical measurement that describes a value’s relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean.

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33
Q

Prospective Non-Experimental Analysis of Differences: Cohort Studies

A

Involves identification of 2 groups (cohorts) one that received the treatment (exposure) of interest and one that did not
Not randomized or blinded
Ex: smoking (follow over time, compare)
A study in which patients who presently have a certain condition and/or receive a particular treatment are followed over time and compared with another group who are not affected by the condition under investigation
PROBLEM is they can end up taking a very long time since researchers have to wait for the conditions of interest to develop

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34
Q

Retrospective, non-experimental, analysis of differences

A

a study involving the identification of patients who have the outcome of interest (cases) and control patients without the same outcome, and looking back to see if they have exposure of interest
Case Control Studies: patients who already have a condition compared to people who don’t. Ex: lung cancer pt asked how much they smoked in the past compared to general

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35
Q

Simple random sampling

A

Get a list or sampling frame (hard part bc it must not systemically exclude anyone)
Generate random numbers
Select one person per random number (equal opportunity)

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36
Q

Systematic Random

A

Select a random #, which will be known as K
Get a list of ppl, or observe flow of ppl
Select every Kth person
Make sure there is no systematic rhythm
If every 4th person is rich for ex, void this method

37
Q

Convenience sampling

A

Find people that are easy to find: whoever walks in first

38
Q

Snowball

A

Find a few people that are relevant to your topic and ask them to refer you to more people

39
Q

Quota sampling

A

Determine what the population looks like in terms of specific qualities, create “quotas” based on those qualities, select people for each quota

40
Q

Inter-rater reliability

A

Variance among multiple testers on same subjects

41
Q

Intra-rater / test-retest reliability

A

1 tester repeated on same subjects

42
Q

Total Variance:

A

Total variance= TV (true variance) + EV (error variance)

43
Q

Measurement reliability: statistical meaning

A

Reliability coefficients often based on measure of correlation.
Correlation refers to the degree of association between 2 sets of data
Below 0.50 represent poor reliability
0.5 to 0.75 represent moderate reliability
ABOVE 0.75 represent good reliability

44
Q

Validity: 3 ways to test

A

Content: assume the test matches instructional objectives

Criterion: test scores agree with concurrent validity or predict external criterion
Do the results accurately measure the concrete outcome they are designed to measure?

Construct: assessment corresponds to other variables as predicted by some rationale or theory
Does the test measure the concept that it’s intended to measure?

45
Q

Point Estimate

A

a single sample statistic that serves as an estimate of a population parameter (EX: sample mean X)

46
Q

Interval Estimate

A

an interval within the value of a parameter of a population that has a stated probability of occurring (EX: confidence interval)

47
Q

Confidence interval (CI):

A

range of scores w boundaries or confidence limits that should contain the population mean. The boundaries are based on the sample mean and its standard error
The bigger the confidence level, the bigger the boundaries will be*
Confidence intervals gives us the boundaries that the population mean should fall within using single sample data

48
Q

Top Down Coding

A

start with a set of predetermined codes then find excerpts that fit those codes

49
Q

Bottom Up Coding

A

start with no codes and develop codes as you analyze the dataset

50
Q

In Vivo Coding

A

based on the actual language of participants, ex: “I hope”

51
Q

Analytic Memos

A

How you personally relate to participants or phenomenon
Your research questions, your code choices
Emerging patterns, categories, themes and concepts
Any problems with the study, personal or ethical dilemmas
Future directions for the study

52
Q

Three basic classifications of validity:

A
  1. Internal
    Applied only to experimental strategy
    Basic strategy to increase internal validity is maximize control over experimental settings
  2. Measurement
    Is the measurement measuring what its supposed to measure?
  3. External
    Are the results generalizable?
53
Q

threats to internal validity

A
  1. History: external events that intervene between pre/post testing (not client hx, pt hx is part of inclusion/exclusion)
  2. Maturation: changes within a subject between pre and post testing
  3. Testing: familiarity and practice
  4. Instrumentation: tools may change, env may change
  5. Regression to mean: occurs when subjects selected on the basis of a single high/low score, retests show a spontaneous regression to mean, outliers have greater variability
  6. Assignment errors: groups different at start of study
  7. Mortality: death or withdrawal at diff rates between groups
  8. Diffusion or imitation of treatments: subjects share information about treatments
  9. Compensatory equalization of treatments: researcher shows unequal attention to one group
  10. Compensatory rivalry or demoralization: subjects guess study objectives, develop “we’ll show them or why bother attitude”
54
Q

Levels of Blinding:

A

Double Blind -> researcher and subject don’t know assignment
Single Blind -> either the researcher or the subject is blind (one not both)
Non Blinded -> both researcher and subject know the assignment

55
Q

p value

A

level of significance or alpha
The p value indicates the probability that findings reflect a real difference or change. Reject the null hypothesis if the p value is less than 5% (less than 5% probability that the difference or change is a chance occurrence).
If p > alpha (0.05) accept Ho
If p < alpha (0.05) reject Ho, accept Ha

56
Q

parametric test

A

Samples are randomly drawn from populations with normal distributions
Samples from each group have comparable variances (homogeneity of variances)
Data is on ratio/interval scale

57
Q

Non-parametric

A

tests make fewer assumptions about population data and can be used when parametric criteria are not met (or you’re just not sure)
Assumed distribution: ANY non-parametric
Assumed variance: ANY non-parametric
Typical data: Ordinal or Nominal non-parametric
Usual central measure: median non-parametric

58
Q

Level 1 evidence

A

experimental study, randomized controlled trial (RCT), systematic review of RCTs, with or without meta-analysis

59
Q

Level 2 evidence

A

Quasi-experiemntal study , systematic review of a combination of RCTs & quasi-experiemntal, or quasi-experimental studies only, with or w/o meta-analysis

60
Q

Level 3 evidence

A

Non-experiemntal study, qualitative study or meta-synthesis

61
Q

Level 4 evidence

A

Opinion of respected authorities and/or nationally recognized expert committee/ consensus panels based on scientific evidence includes: clinical practice guidelines & consensus panels

62
Q

Level 5 evidence

A

Based on experiential and non-research evidence. Includes: literature review, quality improvement, program or financial evaluation, case reports, opinion of nationally reocgnized experts based on experiential evidence

63
Q

Assumptions for the Mann Whitney U Test:

A

Your dependent variable should be measured at the ordinal or continuous level
Your independent variable should consist of 2 categorical independent groups
You should have independent of observations, which means there is no relationship between the observations in each group or between the groups themselves
A Mann-Whitney U test can be used when your 2 variables are NOT normally distributed
Using SPSS to do a Mann Whitney U test is EASY

64
Q

ANOVA

A

If there are 3 or more groups: use ANOVA
the only statistic that can look at within and between group variances at the same time (Very versatile statistic)

65
Q

Within group variance

A

refers to how spread out the data points are in a single group. The more widespread the data points, the bigger the variance

66
Q

Between group variance

A

looks at how different the different groups are from each other at the same

67
Q

The H statistic

A

measures whether one of the independent variables has a different effect on the response variable, depending on the value of the other independent variable

68
Q

The Bonferroni adjustment

A

The Bonferroni adjustment is simply to divide 0.05 by the # of possible pair-wise comparisons that could be made from the data set

69
Q

Friedman Test

A

Nonparametric version of comparing 3 or more groups

70
Q

What is the number “p” needs to be in order to be significant?

A

less than .05

71
Q

What is the only statistic that looks at both between and within group variances at the same time?

A

ANOVA

72
Q

Debbie, a participant in your study, was observed as having 9/10 pain due to arthritis in her hand. Debbie was then given a new OT intervention for decreasing pain in arthritis and researchers observed outcomes related to pain. Researchers found decreased pain during intervention observations. Researchers later observed Debbie again after intervention had stopped and saw an increase in her pain. What type of study design is this?

A

ABA Withdrawal Design

73
Q

The range of scores within specific boundaries that should contain the population means is the?

A

confidence interval

74
Q

You are conducting a study with a few people relevant to your topic. After meeting with your participants you ask them to refer more people to you from their community. This is type of sampling an example of

A

snowball technique

75
Q

If researchers and participants do not know the assignment of participants into groups this is considered?

A

double blinding

76
Q

Ethnography, ground theory, phenomenology, and case studies are all examples of?

A

Qualitative Research

77
Q

Pearson and Spearman are used as what type of test?

A

Correlation tests

78
Q

The application of basic scientific findings to clinically relevant issues and simultaneously, the generation of scientific questions based on clinical dilemmas is also know as ?

A

Translational research

79
Q

Why is clinical research important to the field of OT?

A

Do no harm principle, expanding OT treatment and credibility of OT with evidence based practice

80
Q

Which research design allows for manipulation of the independent variable?

A

experimental design

81
Q

T/F: Inferential statistics involves a decision making process that allows us to estimate population characteristics from sample data

A

true

82
Q

TRUE OR FALSE: A discrete variable can ONLY be described in whole units.

A

true

83
Q

A declarative statement that predicts the relationship between the independent and dependent variables, specifying the population that will be studied is also known as?

A

research hypothesis

84
Q

A statistical hypothesis which states that the group means are not different is?

A

a null hypothesis

85
Q

TRUE OR FALSE: A repeated measures research design falls under a a non-experimental research design.

A

false

86
Q

TRUE OR FALSE: A prospective study is occurring in real time while a retrospective study is looking over past study.

A

true

87
Q

What is a number that can take on any value along a continuum within a defined range?

A

Continuous Variable

88
Q

What is a study in which patients who presently have a certain condition are followed over time?

A

cohort study

89
Q

When a subset of the population is selected randomly, what kind of sampling is this?

A

probability sample

OT 520 Research (1 decks)

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