Studied by 16 people
Lecture 1: #1-8, Lecture 2: #9-26, Lecture 3: #27-36, Lecture 4: #37-41, Lecture 5: #42-56
Theory
a set of concepts and relationships among those concepts that helps us understand or explain some phenomenon
Evidence
a set of observations in the real world
develops methods observed to work in a sample
Practice
used when an intervention works for a client
Evidence Based Practice
the process of applying a scientifically sound intervention technique to a particular client
Three components:
External scientific evidence
Clinical expertise/expert opinion
is this appropriate for this client?
Client/caregiver perspectives
client/caregiver should be given options if possible, but have overall autonomy over decision
Induction
type of reasoning that makes broad generalizations from specific observations
there is data, then conclusions are drawn from the data
from observations, clinicians/scientists discern a pattern, make a generalization, and infer an explanation or a theory
Deduction
type of reasoning that starts out with a general statement and examines the possibilities to reach a specific, logical conclusion
the scientific method uses this to test a theory, idea, or relationship, form a hypothesis, and test the hypothesis in a set of observations
Inferencing
“carry forward” from data to theory
PICOT Questions
used to help find the evidence
__P__opulation: who is the intervention effective for?
__I__ntervention: what is the intervention?
__C__omparison: what is being compared?
__O__utcome: what do we want to change?
__T__ime: how long does it take?
The Scientific Method
a search for knowledge concerning general truths
a process of objectively studying a problem via collection of data
a process of constant questioning
a self-correction mechanism for knowledge acquisition
a highly controlled version of clinical decision-making
Process:
write a research question with measurable independent and dependent variables
test your hypothesis (plan and gather data)
identify potential problems in your study
write a new research question…
Database
organized portal which you can search multiple journals at the same time
ex: Google Scholar, PsychInfo, EBSCO
Journal
a magazine-like publication of a scientific society
ex: ASHA’s four journals; Journal of Speech, Language, and Hearing Research, American Journal of Speech Language Pathology, American Journal of Audiology, and Language, Speech, and Hearing in the Schools
Peer Reviewed Journal
a journal where the articles are only published after they have been reviewed by other researchers with content expertise
often authors are required to revise and resubmit their articles
only articles with strong research designs should be published in a peer reviewed journal
Peer Review Process
when authors submit to a journal, the editor determines if the article might be a good fit
if so, article is sent out to volunteer reviewers who write up a review of the article
they can do the following; accept, accept with minor revisions, revise and resubmit, or reject
Double-Blind Peer Review
when neither the authors know the reviewer nor to the reviewers know the author
this is the best quality, but can be meaner
Primary Study
studies that collect their own data
Secondary Studies
studies that review other people’s data
Systematic Review
Plan for review is determined in advance
Includes ALL studies about a given topic that you can find by searching multiple databases
Includes a search strategy
Narrows down to a smaller number of articles based on inclusionary and exclusionary criteria
Reviews all the identified articles - no picking/choosing ones that match hypothesis
Determines the level of evidence (quality of evidence) for each article
Formulates an opinion based on ALL the evidence, focused on highest levels of evidence
Meta-Analysis
does everything a systematic review does, plus re-analyzes the data from all participants in the previous studies using effect sizes
Randomized Controlled Trials
an experimental design in which the researcher adds or removes a variable to look at the impact of that variable of interest
participants are randomly assigned to groups
measured across groups
measured across time
gold standard of research
also:
between subjects (treatment vs. control, or treatment A vs. treatment B)
within subjects (DV is measured both before and after we manipulate the IV; pre vs. post)
also has random assignment: participants are randomly assigned to treatment or control
this attempts to eliminate the chance of group A looking different from group B before the treatment begins
Skeptical
open to new information, maintaining an attitude of constant questioning
Experimental Studies
implement a treatment to determine if the treatment was effective (like RCTs)
without randomization, these studies are biased by subject selection
Include an IV and DV
Observational Studies
simply watch (and compare or correlate) what is happening out on the world, do not implement treatment so you cannot say whether or not a treatment was effective
lack control
Narrative Reviews
NOT systematic
includes expert opinion including textbooks
very bottom of study pyramid
Independent Variable
presumed cause
the variable we manipulate
determines if the question is comparative or correlational
Dependent Variable
presumed effect
variable we measure the change of
has to be the same or higher level of measurement as the independent variable
Causation
to have this, we must have
relationship between IV and DV (correlation)
temporal precedence (IV before DV)
NOTHING ELSE CAN BE THE CAUSE
Variable
anything that can change or be changed
any factor that can be manipulated, controlled for, or measured in an experiment
Value
measurement of the variable
metric of measurement
Nominal Values
aka name values, may be sets of 2 or 3
yes/no
yes/no/maybe
rural/suburban/urban
we code these with numbers, but they are not technically numeric
Ordinal Values
values that have a greater than/lesser than scale
strongly agree/agree/neutral/disagree/strongly disagree
less than high school/high school education/some college/college degree/advanced degree
we will also code these as numbers, typically in order
Interval Values
go in order like ordinal values but with equal spacing
proportional values
these values are typically already in numbers
temperature (fahrenheit or celsius), time (in minutes, hours)
Ratio Values
values that go in order (like ordinal) and with equal spacing (like interval) but also have a true zero and cannot be negative
age (in years, months)
height (meters, feet) or weight (lbs, kg)
Descriptive Questions
what is? (one variable)
how many students in this class are first generation college students (percentage)
what is the average age of students in this major (mean)
Inferential Questions
how are two (or more) variables connected?
Do first generation college students take longer to graduate than students who have family members who have previously graduated college?
Are students in CSAD, on average, younger than students in construction management?
Null Hypothesis
no difference/no correlation
the treatment groups does not differ from the control group
Directional Hypothesis
specifies a value difference
the treatment group differs from the control group (non-directional)
the treatment group was more successful than the control group (directional; comparison)
the number of hours of therapy was positively associated with outcome (directional; correlation)
Quantitative Research
research involving numbers
Qualitative Research
research involving categorizations that we can code into numbers
Confounding Variable
other variables that may change the DV but we are not manipulating
managed by having a control
Control
done via inclusionary and exclusionary criteria
also done mathematically (“after controlling for age, we found that X was associated with Y)
Double-Blind Study
one group of patients may be given a placebo, while another is given the actual medication that’s being tested
neither patients nor the researchers know which group is taking the placebo
the effects of the medication and placebos are then studied and compared with one another to determine the effectiveness of the medication itself
Observational Measurement
researchers observe the potential effect of a risk factor (eg. demographic variable), diagnostic test, or treatment strategy without trying to manipulate
still have an IV (we just aren’t manipulating it) and a DV (outcome measure) and DV (outcome measure) and still use inferential statistics
this type of research is important because we cannot randomly assign things like smoking, which why we cannot prove the impact of smoking
Comparative Studies
studies that examine the difference in the DV between two or more different groups (IV)
different from experimental studies because you cannot manipulate the IV
use inclusionary and exclusionary criteria
Case-Control Study
researchers identify people with an existing health problem (cases) and a similar group without the problem (controls) and then compare them on a task
type of comparative study
Retrospective Study
looking back, they already have the problem/concern/diagnosis when you begin the study
type of comparative study
Cohort Study
researchers follow a cohort and track exposures to a variable of interest
compare the outcomes of the cohort on the basis of events/exposures
prospective looking forward
type of comparative study
Cross-Sectional Studies
compare across groups
cheaper
faster
more room for outside factors to have an influence (time)
type of comparative study
Longitudinal Studies
compare across time
within a group
can also compare between groups at multiple time points
we do not manipulate the IV
type of comparative study
Correlation
a relationship or association between two variables (IV and DV)
Correlational Studies
studies that identify relationships between variables of interest
also may see the word “predict” to mean correlation
they all run between -1 and 1
Bimodal Distribution
distribution with two modes
if your correlation looks like a v-shape, you cannot use correlational statistics
Participant Randomization
reduces bias between groups
no “opt-in” bias like in cohort designs
but may not be ethical
Subject Matching
e.g.- age-matched, language-matched
control the participants by inclusionary and exclusionary criteria
who is allowed to participate?
Counterbalancing Measurements
control the measurement order
which test do you do better on, first exam or last?
Statistical Control
if you know you have a confounding variable, you can remove the correlation between CV and DV before examining the relationship between the IV and DV
Replication
repeating a study to see if you get the same results in a different sample (same population) at a different time
have someone else do the study over
exact/direct replication
conceptual replication
Note 
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