Research Exam 1: Set 6

Front 1

validity

Back 1

extent to which an instrument measures what it is intended to measure

(validity is continuum - no perfect research construct in all validity domains)

Front 2

internal validity

Back 2

integrity of the experimental design - effects are true for study participants

(given IV and DV, is there evidence that one causes the other)

Front 3

external validity

Back 3

appropriateness and extent by which results can be applied to non-study patients or populations

(can results be generalized outside of experiment)

Front 4

maturation
(definition and how to control)

Back 4

subjects may chance in the course of the experiment or between repeated measurements of the DV due to passage of time

multiple baseline measures

Front 5

repeated testing
(definition and how to control)

Back 5

prior measurement of the dependent variable may affect the results obtained from subsequent measurements

practice first, don't reveal results, randomize order

Front 6

instrumentation error
(definition and how to control)

Back 6

reliability of the instrument used to measure the DV variable or manipulate IV may change in the course of an experiment

calibration, multiple baseline measures

Front 7

selection bias

Back 7

subjects can have unique characteristics which can affect testing and measurement, some learned and some inherent

random selection

Front 8

mortality/attrition

Back 8

some subjects may drop out before completed

large sample size, intention to treat analysis for EBM

Front 9

content validity

Back 9

items that make up instrument adequately sample the universe of content that defines the variable being measured

Front 10

construct validity

Back 10

ability of an instrument to actually measure an abstract concept or construct

Front 11

inadequate definition of constructs
(definition and example)

Back 11

"inadequate preoperations explication of constructs" ($10 word for a $1 idea)

what is patient satisfaction?

Front 12

experimenter expectancies
(definition and example)

Back 12

can bias results of a study in countless ways, both consciously or unconsciously

communicate a desired study outcome, encourage a participant in one trial

Front 13

interaction of different treatments
(definition and example)

Back 13

that are not part of research design

drug-treatment interactions

Front 14

interaction of testing and treatment
(definition and example)

Back 14

measurement itself makes groups more sensitive or receptive to the treatment

gait assessment over a force plate may change gait

Front 15

restricted generalizability
(definition and example)

Back 15

"unintended consequences" or negative consequences of the side effects of a treatment

a drug reduces pain but promotes growth of facial hair (ok for men, not women)

Front 16

criterion validity

Back 16

ability of a test/instrument/measure to predict results obtained using a gold standard or criterion measure already known to be valid