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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
Single Subject (ABAB Design)
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).
25
Ethnography
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)
26
Phenomenology
A way of doing research (method) and a way of conceptualizing thought How the ordinary/ everyday experience is perceived and expressed by the individual
27
Grounded theory
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
28
Skewness
a measure of symmetry or more precisely the lack of symmetry, a NORMAL distribution or data set is symmetric (skewness = 0)
29
Kurtosis
a measure of whether the data are peaked or flat relative to a normal distribution
30
Variance
compare how much one group will vary from another
31
Standard deviation
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
32
z-score
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.
33
Prospective Non-Experimental Analysis of Differences: Cohort Studies
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
34
Retrospective, non-experimental, analysis of differences
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
35
Simple random sampling
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)
36
Systematic Random
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
Convenience sampling
Find people that are easy to find: whoever walks in first
38
Snowball
Find a few people that are relevant to your topic and ask them to refer you to more people
39
Quota sampling
Determine what the population looks like in terms of specific qualities, create “quotas” based on those qualities, select people for each quota
40
Inter-rater reliability
Variance among multiple testers on same subjects
41
Intra-rater / test-retest reliability
1 tester repeated on same subjects
42
Total Variance:
Total variance= TV (true variance) + EV (error variance)
43
Measurement reliability: statistical meaning
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
Validity: 3 ways to test
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
Point Estimate
a single sample statistic that serves as an estimate of a population parameter (EX: sample mean X)
46
Interval Estimate
an interval within the value of a parameter of a population that has a stated probability of occurring (EX: confidence interval)
47
Confidence interval (CI):
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
Top Down Coding
start with a set of predetermined codes then find excerpts that fit those codes
49
Bottom Up Coding
start with no codes and develop codes as you analyze the dataset
50
In Vivo Coding
based on the actual language of participants, ex: “I hope”
51
Analytic Memos
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
Three basic classifications of validity:
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
threats to internal validity
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
Levels of Blinding:
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
p value
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
parametric test
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
Non-parametric
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
Level 1 evidence
experimental study, randomized controlled trial (RCT), systematic review of RCTs, with or without meta-analysis
59
Level 2 evidence
Quasi-experiemntal study , systematic review of a combination of RCTs & quasi-experiemntal, or quasi-experimental studies only, with or w/o meta-analysis
60
Level 3 evidence
Non-experiemntal study, qualitative study or meta-synthesis
61
Level 4 evidence
Opinion of respected authorities and/or nationally recognized expert committee/ consensus panels based on scientific evidence includes: clinical practice guidelines & consensus panels
62
Level 5 evidence
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
Assumptions for the Mann Whitney U Test:
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
ANOVA
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
Within group variance
refers to how spread out the data points are in a single group. The more widespread the data points, the bigger the variance
66
Between group variance
looks at how different the different groups are from each other at the same
67
The H statistic
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
The Bonferroni adjustment
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
Friedman Test
Nonparametric version of comparing 3 or more groups
70
What is the number “p” needs to be in order to be significant?
less than .05
71
What is the only statistic that looks at both between and within group variances at the same time?
ANOVA
72
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?
ABA Withdrawal Design
73
The range of scores within specific boundaries that should contain the population means is the?
confidence interval
74
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
snowball technique
75
If researchers and participants do not know the assignment of participants into groups this is considered?
double blinding
76
Ethnography, ground theory, phenomenology, and case studies are all examples of?
Qualitative Research
77
Pearson and Spearman are used as what type of test?
Correlation tests
78
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 ?
Translational research
79
Why is clinical research important to the field of OT?
Do no harm principle, expanding OT treatment and credibility of OT with evidence based practice
80
Which research design allows for manipulation of the independent variable?
experimental design
81
T/F: Inferential statistics involves a decision making process that allows us to estimate population characteristics from sample data
true
82
TRUE OR FALSE: A discrete variable can ONLY be described in whole units.
true
83
A declarative statement that predicts the relationship between the independent and dependent variables, specifying the population that will be studied is also known as?
research hypothesis
84
A statistical hypothesis which states that the group means are not different is?
a null hypothesis
85
TRUE OR FALSE: A repeated measures research design falls under a a non-experimental research design.
false
86
TRUE OR FALSE: A prospective study is occurring in real time while a retrospective study is looking over past study.
true
87
What is a number that can take on any value along a continuum within a defined range?
Continuous Variable
88
What is a study in which patients who presently have a certain condition are followed over time?
cohort study
89
When a subset of the population is selected randomly, what kind of sampling is this?
probability sample

OT 520 Research (1 decks)

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