Midterm Flashcards
Levels of Evidence (best–>worst)
meta-analyses, randomized controlled trials, cohort studies, case-control studies, case series/case reports, editorials/expert opinion
Criteria for making clinical decisions
patient’s circumstances, patient’s wishes, evidence
PICOT Question
P- patient, population, or disease
I- intervention or issue of interest
C- comparison
O- outcome
T- time frame
Prospective study
examine current conditions and follow individuals over a designated period of time
Retrospective Study
studies that examine data that have already been collected
Descriptive study
Case study, Case series, time series, surveys and questionnaires, cross sectional studies
Case Study
In-depth examination of a specific patient
Case series
follows a group of patients with a similar diagnosis or procedure over time
Time series
observation of a participant or group over multiple time instances
NHANES
National health and nutrition examination survey
Cross-sectional designs
examination of a specific point in time
Cohort studies
group of individuals with similar characteristics (diseases)
Case-Control Studies
individuals chosen for a study based on if they have a condition of interest (retrospective)
Qualitative Studies
used to understand social phenomena in natural settings.
Nominal Scale
Measures the presence or absence of something
Not Measured
Not Ordered
Not Equidistant
No Meaningful 0
Ordinal Scale
Order to data, hierarchy of meaning, sequence (ex- 1st, 2nd, 3rd place)
Not Measured
Ordered
Not Equidistant
No Meaningful 0
Interval Scale
ordinal characteristic and equal distance between data points (ex- temp)
Measured
Ordered
Equidistant
No Meaningful 0
Ratio Scale
most sensitive, interval but has a true zero (ex- height, distance, time, speed)
Measured
Ordered
Equidistant
Has Meaningful 0
Nonparametric and Parametric data scale
Nonparametric (qualitative)-
Nominal, Ordinal (discrete)
Parametric(quantitative)-
Interval, Ration (continuous)
Independent variable
variable that is influenced by the researcher and contains various levels
Dependent Variable
The outcome variable that is measured by the researcher
Descriptive Statistics
summary statistics about the main characteristics of the data collected within the study (age, mass, sex, division)
Inferential Statistics
statistics used to draw conclusions about the hypothesis
Effect size
magnitude of difference or relationship between 2 variables in a standardized way so that results can be compared (0.00-3.00)
Type 1 Error
researcher rejects a null hypothesis that is actually true
Type 2 error
researcher fails to reject a null hypothesis that is actually false
Statistical Power
the probability that a test will reject a false null hypothesis
Validity
do the findings produce answers to what was being examined?
are results applicable to population?
the applicability of a conclusion drawn in the context of a scientific experiment to the world at large (can it be applied effectively)
Reliability
Can the findings of the study be reproduced?
Were the measurements accurate and consistent?
Internal validity threats
include treatments, procedures, or experiences of the participants that threaten the researcher’s ability to draw conclusions (ex- ulterior motive)
Maturation
changes that occur naturally to a participant over time that are independent of external events
External validity threats
occur when researchers draw incorrect conclusions or inferences to populations or settings other than what was originally studied
Face Validity*
determined by expert opinion or subjective assessment of a few individuals (weak measure)
Content / Construct Validity
ability of an instrument or assessment to measure a more abstract concept (ex- pain, confidence)
Error Rate
as the number of repeated statistical tests goes up the potential for incorrect findings/conclusions goes up
Intrarater reliability
consistency of one rater across multiple trials
interrater reliability
consistency of data recorded by multiple raters who measure the same group of subjects
Intraclass Correlation Coefficient (ICC)
the measure of the reliability of measurements or ratings
Test-Retest reliability
assesses the stability of an instrument (used for surveys)
Internal consistency
used to assess the characteristics of a group of items.
Percent Agreement
determined by taking the sum of observed agreements divided by the number of paired scores obtained (simplest form of reliability assessment)
Kappa Statistic
for categorical data to assess the proportion of observed agreements expected by chance
