research Flashcards

1
Q

PICO

A
  • patient/problem - target of interest
  • intervention
  • comparison
  • outcome
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2
Q

levels of evidence

A
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3
Q

systematic review

A
  • comprehensive review of med lit that uses explicit methods to systematically search, ID, appraise, and summarize all literature about a specific issue
  • Cochrane
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4
Q

meta-analysis

A
  • systematic review that uses a statistical technique to derive an estimate of effect size by combining results of several randomized control trials to determine overall effectiveness of a treatment
  • minimze problem of small sample size from individual studies - pooling of trials increases overall sample size
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5
Q

randomized control trials (RCT)

A
  • experimental research to assess relative effect of a specific intervention compared to a control condition
  • pts randomized into control group and at least 1 experimental group
  • control goup - no treatment or standard default treatment
  • random assignment reduces bias and increases probability that differences btw groups are d/t intervention
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6
Q

cohort study

A
  • longitudinal, observational study
  • individuals w/ a risk factor or exposure are followed over time to compare disease occurrence in the exposed group to that in a group not exposed
  • measure of association is relative risk - ratio of incidence rate of exposed to that of controls
  • prospectively and retrospectively
  • limitations: excessive length of time, other variables can impact
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7
Q

case control study

A
  • retrospective, observational study
  • individuals w/ a disease are matched with a comparison group of individuals without disease
  • history of exposure and characteristics recorded through interview
  • control group provides estimate of frequency and amount of exposure in subjects in population without disease
  • measure of association btw exposure and occurrence of disease is odds ratio - ratio of oddds of exposure in diseased subjects to odds of exposure in non-diseased
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8
Q

cross-sectional study

A
  • observational study of data or observations made at only one point in time and all subjects tested at same time
  • aims to describe relationship btw disease and factors of interest in a specified population at a given time
  • describe prevalence of disease and demonstrate association
  • cannot distinguish between newly occurring and long-established conditions
  • cannot ID causal relationships
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9
Q

case report or case series

A
  • in-depth description of a condition or response to a treatment
  • can be used to generate theories and hypotheses for future research
  • cannot test hypotheses or establish cause-effect relationships
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10
Q

institutional review board (IRB)

A
  • scientists and non-scientists charged with protecting rights and welfare of participants in research
  • review and approve research invoving human subjects
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11
Q

informed consent for research

A
  1. statement that study involves research
  2. explanation of purpose of research
  3. description of procedures
  4. description of foreseeable risks
  5. description of benefits to subject
  6. disclosure of alternative procedures or treatments that might be advantageous
  7. description of who will have access to records that ID subjects
  8. explanation of compoensation if involves > minimal risk
  9. who to contact for answers about rights ro issues d/t study
  10. participation is voluntary
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12
Q

types of data

A
  • continuous: height, weight, distance, ROM; covers range with no gaps
  • discrete: measured in whole units; HR, pts diagnosed w/ cancer, number of visits to PT
  • dichotomous: yes or no, pass or fail, smoking or nonsmoking
  • qualitative: categorical, non-numeric; eye color, blood type, hand dominance
  • quantitative: numbers that represent counts of measurements
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13
Q

scales of measurement

A
  • nominal: qualitative, you can only be in one category; blood type, type of breath sounds, type of arthritis
  • ordinal: ranking; MMT grades, level of assist, pain
  • interval: temeprature, functional status tests
  • ratio: distance walked, time to complete an activity
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14
Q

internal consistency

A
  • extent to which items or elements that contribute to measurement reflext one phenomenon or dimension
  • ex: a functional assessment scale should only include items that relate to patients’ physical function
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15
Q

intrarater reliability

A
  • consistency of repeated measurements by one person over time
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16
Q

interrater reliability

A
  • consistency of measurements made by more than 1 person
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17
Q

test-retest reliability

A
  • consistency of repeated measurements of same person on different occasions
  • can be affected by interval between tests, fatigue, learning
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18
Q

face validity

A
  • degree to which a measurement tests what it is supposed to
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19
Q

content validity

A
  • degree a measurement reflects meaningful elements of a construct and items in a test reflect domain of interest and not other extra things
  • ex: McGill pain questionnaire is good bc it addresses analogue pain scale and ALSO intensity, location, quality, duration
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20
Q

construct validity

A
  • degree to which a theoretical construct is measured by a test
  • ex: MMT scores would have construct validity as indicators of innervation status of muscle if there was a relationship between MMT scores and results of EMG testing
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21
Q

criterion-related validity

A
  • validity of measurement estabilished by comparing it to either different measurement often considered “gold standard”
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22
Q

concurent validity

criterion related

A
  • interpretation is justified by comparing to a gold standard at the same time
  • ex: HR by palpation and ECG
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23
Q

predictive validity

criterion related

A
  • measurement is valid because it is predictive of a future event
  • ex: use of GPA or GRE as admission criteria for grad school based on presumptive ability to predict future academic success
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24
Q

prescriptive validity

criterion related

A
  • measurement suggests form of treatment person should receive - based on successful outcome of treatment
  • ex: asystole on ECG has prescriptive validity if patients with this arrhythmia are successfully revived by CPR
25
Q

probability sampling

A
  • method of sampling that uses some form of random selection
  • every member of population must have same probability of being selected for sample
  • sample should be free of bias and representative of the population
26
Q

simple random sampling

probability sampling

A
  • subjects have an equal chance of being selected for sample
  • relies on table of random numbers or random number generator
  • not most statistically efficient
  • might not be most representative sample
27
Q

systematic sampling

probability sampling

A
  • subjects are selected by taking every nth subject from population
  • size of interval based on size of populatin and desired sample size
  • simple
28
Q

stratified random sampling

probability sampling

A
  • proportional or quota random sampling
  • population divided into homogenous subgroups (strata) and then simple random sample drawn from each
  • assures sample will be representative of key subgroups of population in addition to overall population
29
Q

cluster sampling

probability sampling

A
  • population divided into clusters or areas and a random sample of clusters is selected
  • less costly, more efficient than simple random sampling
30
Q

non-probability sampling

A
  • any method of sampling that does not involve random selection of subjects
31
Q

convenience sampling

non-probability sampling

A
  • selected from subjects who are convenient or readily available to researcher
32
Q

purposive sampling

non-probability sampling

A
  • subjects deliberately selected based on predefined criteria chosen by investigators
33
Q

quota sampling

non-probability sampling

A
  • subjects not selected randomly
  • after ID subgroups of interest, researcher uses convenience sampling to select required number of subjects
34
Q

snowball sampling

non-probability sampling

A
  • subjects IDed by asking existing subjects to ID names of other potential participants
  • when characteristic to be studied is rare and would be difficult and costly to ID individuals with this characteristic
35
Q

external validity

A
  • degree to which results of research are generalizable to populations or circumstances beyond those included in study
  • threats to EV: interaction of treatment with specific types of subjects tested and place (setting) and time (history) of the experiment
36
Q

internal validity

A
  • degree to which an intervention being evaluated (independent variable) is the cause of the outcome measured in the study (dependent variable) and not the result of extraneous factors
  • threats to IV: hisotry, maturation, attrition, testing, instrumentation, regression toward mean
37
Q

hawthorne effect

A
  • an untreated subject experiences change simply from participating in the research study
  • tendency for people to change behaviors just because they know they are being watched
38
Q

independent variable

A
  • variable that is presumed to have caused or influenced dependent variable
  • what is controlled or manipulated by researcher
39
Q

dependent variable

A
  • response or outcome assumed to be caused by effect of independent variable
  • what the researchers are looking for change in
40
Q
A
41
Q

p-value

A
  • probability that a particular statistical result could have happened by change
  • when smaller than alpha, null hypothesis is rejected
  • when larger than alpha, null hypothesis is not rejected
  • alpha: significance level, probability of rejecting null hypothesis when it is true, usually 0.05 or 0.01
42
Q

steps in testing a statistical hypothesis

A
  1. state null hypothesis and alternate hypothesis
  2. select appropriate test statistic
  3. select level of significance for statistical test (0.05)
  4. calculate test statistic from sample data
  5. interpret result
43
Q

types of errors

A
  • type I error (alpha error): wrongly deciding to reject null hypothesis, concluding that there is significant different when there is not; false positive; if signif is 0.01, 1% chance of Type I error
  • type II error (beta error): error the researcher makes when wrongly deciding not to reject null hypothesis, concluding there is no relationship when there is; false negative
44
Q

statistical power

A
  • chance that statistical test will lead to rejection of false hypothesis
45
Q

MCID vs MDD

A
  • minimal clinically important difference (MCID): smallest difference in patient’s condition that pt or clinician considers worthwhile for the costs and side effects
  • minimal detectable difference (MDD): smallest difference or change that would be statistically significant, standard error of measurement
46
Q

what each graph is best for

A
  • bar graph: magnitude or frequency of categories
  • box and whisker plot: distribution of values within a group with minimum, lower quartile, median, upper quartile, max
  • forest plot: in meta-analysis, results of individual studies and cumulative summary of all studies
  • histogram: display of frequency distribution
  • line graphs: demonstrate relationship between two or more quantitative variables
  • scatter plot: graphical display that illustrates relationship between two quantitative variables
  • stem and leaf plots: graphical display which enables reader to observe entire distribution of data without losing info
47
Q

bell curve

A
  • kurtosis: peakedness of a distribution
  • in a normal distribution, majority of data are clustered around mean - mean, median, and mode are all the same
  • skewness: asymmetry of a distribution for (+) or (-) skey; whatever the skew is has the longer tail and the mean, then the median, then the mode
48
Q

standard deviation

A
  • descriptive measure of the spread or dispersion of data
  • positive square root the variance
49
Q

variance

A
  • sum of squared deviations of each data point from the mean
50
Q

inferential statistics

A
  • branch of statistics that use sample data to make inferences about a population
  • parametric and nonparametric
51
Q

parametric statistics

A
  • assume that samples come from populations that are normally distributed and there is homogeneity of variance
52
Q

analysis of variance

A
  • ANOVA
  • inferential statistic procedure used to test the equality of means between two or more populations
53
Q

confidence interval

A
  • range of values used to estimate a population parameter
54
Q

intraclass correlation (ICC)

A
  • form of correlation coefficient that assesses both degree of correspondence and agreement among scores
  • ranges from 0.0 to 1.0 and is calculated from variance estimates derived from an analysis of variance
55
Q

nonparametric statistics

A
  • do not assume that samples come from populations that are normally distributed and do not assume homogenity of variance
  • uses chi-square test: for nominal data, evaluates difference between observed and expected frequencies to examine association or independence between categorical variables
56
Q

sensitivity

A
  • percentage of people who test positive for a disease among a group of people who had the disease
  • SnNout: with high sensitivity, a negative rules out the diagnosis
57
Q

specificity

A
  • percentage of people who test negative for a specific disease among a group of people who do not have the disease
  • SpPin: with high specificity, a positive diagnostic test rules in diagnosis
58
Q

incidence vs prevalence

A
  • I: number of new cases of a disease during a time, new cases per 100,000 people at risk
  • P: number of existing cases, including new and pre-existing, number of existing cases per 100,000 at risk