Worksheets416 Exam 2 pt. 1
Total questions: 251
Worksheet time: 2hrs 7mins
NO intervention
nonexperimental design
experimental design
inclusion criteria
subject must speak and read English
subject must be 18 years or older
subject must not have a terminal illness
exclusion criteria
subject is unable to speak and read english
subject is under 18 years of age
subject has a terminal illness
process of selecting a part of the population to represent the entire population for a particular study
sampling
sample
narrow the population to a researchable size and characteristics that define the population
eligibility criteria
ineligibility criteria
the subset of the population that is chosen to represent the population for a given study
sampling
sample
involves random selection of elements: each element has an equal, independent chance of being selected
nonprobability sampling
probability sampling
elements chosen in nonrandom way; means not every element of population has opportunity to be chosen for the sample
nonprobability samples
probability samples
accidental/incidental; subjects for study are chosen as they become available
convenience sampling
quota sampling
consecutive sampling
weakest form of sampling
convenience sampling
quota sampling
consecutive sampling
a sample whose key characteristics closely approximate those of the population
representative sample
sampling bias
non-probability sample
researcher takes into account some knowledge of population to build in representativeness to the sampling plan
consecutive sampling
quota sampling
purposive sampling
researcher wants to study patient satisfaction with emergency department nursing care
quota sampling
purposive sampling
snowball sampling
the systematic overrepresentation or underrepresentation of some segment of the population in terms of key characteristics
sampling bias
representative sample
nonprobability sampling
recruit all of the people from those that are accessible who meet the eligibility criteria, (1) until the specified sample is obtained or (2) the specific time interval is completed
consecutive sampling
purposive sampling
snowball sampling
researcher "hand picks" the subjects for the study; most often used in qualitative research
purposive sampling
snowball sampling
quota sampling
researcher only selects persons who have experienced loss due to a Hurricane
purposive sampling
snowball sampling
quota sampling
researcher uses subjects to access other potential subjects; used to identify people with distinctive characteristics
purposive sampling
snowball sampling
consecutive sampling
a researcher wishes to study health habits of elderly people living in a retirement community. the researcher has one subject and then asks that subject to refer other people in the building to the study
snowball sampling
purposive sampling
consecutive sampling
which type of sampling is most vulnerable to bias
convenience sampling
snowball sampling
quota sampling
purposive sampling
does not involve selection of elements at random
nonprobability sampling
probability sampling
subjects selected in random fashion; each element of the population has an equal independent chance of being chosen for the study
probability sampling
simple random
stratified random
researcher obtains list of all elements in the population (sampling frame); assigns a number to each element
simple random
stratified random
cluster sampling
size is in proportion to their representation in the population
proportionate sample
disproportionate sample
same as non-probability quota sampling except after homogeneous subsets or strata are established, elements for each stratum are chosen by simple random sampling
stratified random
simple random
systematic sampling
different proportions of study participants sampled when comparing strata; helps make sure smaller strata are adequately represented
proportionate sample
disproportionate sample
involves successive random sampling of units that progresses from large groups or clusters to smaller groups or clusters
cluster sampling
random sampling
stratified sampling
researcher wants to generalize to all Baccalaureate nursing student in US
cluster sampling
stratified sampling
random sampling
the researcher chooses each element of the population from a list or group
systematic sampling
cluster sampling
stratified sampling
researcher wants to sample all emergency department patients seen in last year
systematic sampling
cluster sampling
stratified sampling
all insulin dependent diabetics in Cabell County
target population
accessible population
strata
stratified random sampling enhances representativeness
true
false
as sample size increases, sampling error
increases
decreases
determines how large the sample size must be to detect a difference
power analysis by cohen
statistical conclusion validity
male/female, chronically ill/acutely ill
target populations
accessible populations
strata
risk of getting it wrong increases if sample is too small
power analysis by cohen
statistical conclusion validity
method of processing and analyzing numbers in systematic manner
statistics
methods
probabilities
subpopulations of a population
target population
accessible population
strata
used when research problem does not lend itself to an experimental design
nonexperimental design
experimental design
those within the subjects; characteristics of the study participants
external factors (confounding variables)
internal factors (confounding variables)
age, gender, underlying medical illness, personality traits, emotions, perceptions of an event, etc
external factors (confounding variables)
internal factors (confounding variables)
those within the subjects; characteristics of the study participants
external factors (confounding variables)
internal factors (confounding variables)
sex, blood type, age, etc
independent variable inherently unable to manipulate
independent variable ethically unable to manipulate
randomly selecting subjects for each group; each member has an equal chance of being selected
random sampling
random assignment
homogeneity
smoking
independent variable inherently unable to manipulate
independent variable ethically unable to manipulate
sample too small
low statistical power
weakly defined "cause"
low intervention fidelity
independent variable not powerful
low statistical power
weakly defined "cause"
low intervention fidelity
most effective means of controlling internal confounding variables; confounding variables will be distributed over both groups evenly
random sampling
random assignment
homogeneity
unreliable implementation of a treatment
low statistical power
weakly defined "cause"
low intervention fidelity
examine internal and external validity to evaluate the adequacy of the research design
true
false
when effects detected in a study are a true reflection of reality and not the result of the effects of extraneous variables
internal validity
external validity
when some event other than the experimental intervention which might influence the dependent variable; ex. news program on breast self-examination
threat of history
selection threat bias
threat of maturation
occurs when groups differ before intervention in characteristics; ex. smoking
threat of history
selection threat bias
threat of maturation
if it is impractical to manipulate independent variables such as lack of time or lack of funds
nonexperimental designs
experimental designs
occurs when natural changes occur within subjects during a study which might affect results; ex. school nurse study of nutritional status of children
threat of maturation
threat of mortality
threat of testing
the function of random assignment is to choose a comparison group that is as much like the intervention group as possible
true
false
controlled by use of comparison group and random assignment
threat of maturation
threat of mortality
threat of instrument change
occurs when pretest is given and the subjects may remember the answers
threat of testing
threat of instrument change
threat of mortality
occurs when different pretest and posttest instruments are used; best if the instruments have similar quality assessment values
threats of mortality
threat of instrument change
threat of testing
occurs when subject dropout rate is different between intervention and comparison groups; difficult to control
threat of mortality
threat of testing
threat of instrument change
concerns to what extent to which the findings of a study can be generalized (applied to other people or settings)
external validity
internal validity
concerns whether the sample is representative of population is an inadequacy of sampling design threat
true
false
ascertaining the prevalence of a health problem or trait
descriptive
descriptive correlational
occurs when subjects in a study change behavior simply because they know they are in a study
hawthorne effect threat
experimenter effect threat
pretest effect threat
used when random assignment not feasible; researcher chooses for the study only those subjects who are alike with respect to the extraneous variables
random sampling
random assignment
homogeneity
occurs when characteristics or behavior of the researcher affect behavior or responses of subjects
experimenter effect threat
hawthorne effect threat
pretest effect threat
use subject characteristics to match subjects on one-on-one basis to make groups comparable on extraneous variables such as age, gender, and race
matching
homogeneity
statistical control
clothes, facial expressions, gender, and body build
experimenter effect threat examples
hawthorne effect threat examples
pretest effect threat examples
occurs when subjects are pre-tested; researchers cannot generalize people who were not pre-tested
experimenter effect threat
hawthorne effect threat
pretest effect threat
data must not be influenced by data collection
objective data collection
systematic data collection
the purpose is to describe whether variables are related, without ascribing a cause-and-effect connection
descriptive
descriptive correlational
everyone must collect data in the same way
objective data collection
systematic data collection
existing data
historical (letters, diaries, minutes of meetings, etc)
records (hospital, school, and corporate)
data which the researcher prospectively collects
new data
existing data
randomly select subject in the experimental and then a subject that is similar to that subject is randomly selected for the control group
matching
random assignment
homogeneity
historical data that is convenient and economical; secondary or meta-analysis
new data
existing data
assessment of clinical measures (e.g. blood pressure, O2 saturation, potassium level)
biophysiological measures
self-reports
patient-reported outcome
observations
purpose is to observe, describe, and explain aspects of situation
descriptive designs
nonexperimental designs
experimental designs
descriptive correlational
subject's perceptions (e.g. interview)
biophysiological measures
self reports
patient-reported outcome
observations
what size pool of subjects do you need for matching
large
small
medium
direct questioning of study subjects
biophysiological measures
self-reports
patient-reported outcome (self report)
observations
can control for confounding variables using various statistical methods
statistical control
threat bias
homogeneity
researcher's perceptions (e.g. direct observation of behavior)
biophysiological measures
self-reports
patient-reported outcome (self report)
observations
the ability to detect true relationships statistically
statistical conclusion valididty
internal validity
external validity
construct validity
use of special equipment to make measurements; complex or simple equipment
physiological or biological measurements
quantitative self-report
data collection measures
may compare two or more groups on an attribute but no intervention
descriptive designs
nonexperimental designs
retrospective designs
performed directly within or on living organisms (e.g. BP)
in vivo measures
in vitro measures
the extent to which it can be inferred that the independent variable caused or influenced the deoendent variable
statistical conclusion validity
internal validity
external validity
construct validiity
biophysiologic material is taken and analyzed outside the body (e.g. blood chemistry levels, cytology, etc)
in vivo measures
in vitro measures
cause-probing questions for which manipulation is not possible are typically addressed with
correlational design
retrospective design
prospective design
data are collected with a formal instrument
quantitative structured self-reports
qualitative structured self-reports
the generalizability of the observed relationships across samples, settings, or time
statistical conclusion valididty
internal validity
external validity
construct validity
quantitative structured self-reports
interview schedule (face-to-face or telephone)
questionnaire (written form)
allows persons to respond in their own words in a narrative fashion
open-ended questions
closed-ended questions
an association between variables and can be detected through statistical analysis
correlation
coefficient
convolution
provide answers to choose from
open-ended questions
closed-ended questions
when items are combined to obtain an overall score
scale
comparison
total
used to make fine quantitative discriminations among people with different attitudes, perceptions, and traits
scales
likert scales
semantic differntial scales
cause-probing questions (e.g. prognosis or harm/etiology questions) for which manipulation is not possible are typically addressed with a correlational design
descriptive correlational design
retrospective design
prospective design
summated rating scales; respondents indicate their view on a topic
scales
likert scales
semantic differential scales
consists of several declarative statements; responses are on an agree/disagree continuum
likert scales
semantic differential scales
assign numbers to represent the amount of an attribute of characteristic present in a person or object
measurement
observation
obtained if no error in measurement; never known
true score
observed score
error score
measure obtained
true score
observed score
error score
amount of random error in the measurement process
true score
observed score
error score
causes a person's observed score to vary in no particular manner around their true score
random error
systematic error
rate concepts using bipolar adjectives
scales
likert scales
semantic differential scales
random error does not influence direction of the mean but increased the amount of unexplained variance
true
false
not random in nature and occurs due to measurement of something else in addition to concept
random error
systematic error
uses a continuum of bipolar adjectives (good/bad, strong/weak), and respondents are asked to rate a given concept, situation, or experience on a scale between each set of adjectives
likert scales
semantic differential scales
scale not properly calibrated therefore subject's weights were lower or higher than true weight
systematic error
random error
systematic error can affect the mean score
true
false
on a descriptive continuum, typically bipolar
rating scales
visual analogue scale
semantic differential scales
effects of the environmental factors on scores; temperature, lighting, time of day
situational contaminants
response-set biases
transitory personal factors
includes characteristics of the subjects that interfere with accurate measurement; socially desirable responses, extreme responses, education
situational contaminants
response-set biases
transitory personal factors
give answers consistent with prevailing views in society
social desirability response set bias
extreme response set bias
acquiescence response set bias
factors with the subjects which can affect measurement; fatigue, hunger, anxiety, mood
transitory personal factors
administration variations
response-set biases
refers to whether the instrument looks as though it is an appropriate measure of the construct; based on judgement
face validity
content validity
construct validity
criterion-related validity
determines that the scale adequately examines the domain of the concept, all items are relevant, and all aspects are included
face validity
content validity
construct validity
criterion-related validity
indicator of the degree of instrument's validity based upon the average of ratings by the expert panel
content validity index
construct validity
coefficient alpha
consistent expression using extreme responses (e.g. strongly agree)
social desirability response set bias
extreme response set bias
acquiescence response set bias
broad term which encompasses other types of validity and determines if the instrument measures the construct it says it measures
construct validity
face validity
content validity
criterion-related validity
statistical method for testing construct validity; closely related items cluster together into factors
factor analysis
content validity index
calculated by analyzing the relationship between scores on the instrument and the criterion; desirable is 0.70 or higher
validity coefficient
predictive validity
concurrent validity
occur when variations in intervention administration or procedure for collecting data from one subject to another affect measurement; arm not in same position for BP, change in test questions by interviewer
administration variations
transitory personal factors
instrument clarity
the instrument's ability to distinguish people whose performance differs on a future criterion
validity coefficient
predictive validity
concurrent validity
the instrument's ability to distinguish individuals who differ on a present criterion
validity coefficient
predictive validity
concurrent validity
the difference between predictive validity and concurrent validity is
timing of the measurement
number of the measurement
date of the measurement
measure subjective experiences such as pain, nausea, vomiting, grief, and anxiety
likert scales
semantic differential scales
visual analogue scales
differentiate between score on GRE and grades in graduate school
example of predictive validity
example of concurrent validity
score on the Beck Depression Inventory and nurses ratings of severity of the patients symptoms of depression
example of predictive validity
example of concurrent validity
occurs if instruments used for measuring are vague or poorly understood; different interpretations by various respondents due to questions not being clear
transitory personal factors
instrument clarity
item sampling
the instrument's ability to correctly identify a "case" - i.e. to diagnose a condition
sensitivity
specificity
result of poor sampling of items that are used to measure an attribute in instrument; score may vary as to what items are included on the test
instrument clarity
item sampling
administration variations
involves a plan for choosing a group of people, events, behaviors or other elements for conducting a study
sampling designs
method designs
nonexperimental designs
the instrument's ability to correctly identify noncases, that is, to screen out those without the condition
sensitivity
specificity
the process of making the selection
sampling
the sample
the true score is the score that would be obtained with an infallible measure
true
false
the selected group or elements chosen to represent to the entire population
sampling
the sample
complete set of persons, events, objects, that possess the characteristics the researcher is interested in studying
population
sample
all insulin dependent diabetics
target population
accessible population
strata
the portion of the target population that is accessible to the researcher, from which a sample is drawn
target population
accessible population
strata
composed of entire group of people or objects in which researcher is interested
target population
accessible population
strata
indicates how consistently and accurately the research instrument (such as scale) measures the variable of interest over time; ex. thermometer
reliability
validity
exists in degrees and is expressed in the form of a coefficient ranging from 1.00 to 0.00
reliability
validity
always in agreement with the statement regardless of content; nay-sayers always disagreement
social desirability response set bias
extreme response set bias
acquiescence response set bias
1.00
perfect reliability
no reliability
refers to the consistency of a tool over time; similar scores each time it is used
reliability
validity
0.00
perfect reliability
no reliability
a reliability coefficient less than 0.80 for a well developed instrument is
good
concerning
a reliability coefficient of 0.80 - 0.95 is preferred
true
false
evaluates stability over time; the same instrument is given to the same subjects at two points in time
stability
internal consistency
equivalence
stability reliability is not recommended for testing attributes that might
stay the same
change over time
an outcome in the present (e.g. depression) is linked to a hypothesized cause occurring in the past (e.g. having had a miscarriage)
retrospective design
prospective design
nonexperimental design
as one variable increases, the other variable increases (ex. increase in salt, increase in BP)
positive relationship
negative (inverse) relationship
refers to whether the questionnaire is measuring what it says it is measuring
reliability
validity
increase in one variable and decrease in other (ex. increase in height, decrease in BMI)
positive relationship
negative (inverse) relationship
tests whether the instrument items measure the same attribute; requires only one test administration
internal consistency
equivalence
stability
all behaviors of a specific type recorded, and each behavior is assigned to one mutually exclusive category
exhaustive system
nonexhaustive system
requires only one test administration
internal consistency
stability
equivalency
assessed by coefficient alpha (Cronbach's alpha)
internal consistency
stability
equivalency
specific behaviors, but not all behaviors, recorded
exhaustive system
nonexhaustive system
0.00 to +1.00
coefficient alpha values
reliability coefficient
"cases" (e.g. those with lung cancer) are compared to "controls" (e.g. those without lung cancer) on prior potential causes (e.g. smoking habits)
case-control design (retrospective)
case-control design (prospective)
used to test agreement between/among different observers or interviewers
internal consistency
equivalence
stability
when determining the reliability of a measurement tool, which value would indicate that the tool is most reliable
0.50
0.70
0.90
1.10
reliability is lower in _____ than in _____ samples
homogeneous than in heterogenous
heterogeneous than in homogeneous
formal systems for systematically recording the incidence or frequency of prespecified behaviors or events
category systems
idk what to put
reliability is lower in ____ than in ____ multi-item scales
shorter than in longer
longer than in shorter
the determination of the extent to which an instrument measures what it says it measures
reliability
validity
a potential cause in the present (e.g. experiencing vs. not experiencing a miscarriage) is linked to a hypothesized later outcome (e.g. depression 6 months later)
prospective correlational design
retrospective correlational design
experimental design
validity is never proven, only supported
true
false
determine subjects behavior under different circumstances
quantitative observational methods
qualitative observational methods
stronger than retrospective in supporting causal inferences
prospective designs
nonexperimental designs
retrospective designs
sampling of time intervals for observation
time sampling
event sampling
neither prospective or retrospective designs are stronger than experimental designs
true
false
observation of integral events
time sampling
event sampling
observational methods for capturing many clinical phenomena and behaviors
true
false
factors that can interfere with objective observation; emotions, anticipation, personal views
reactivity
observational biases
looks to the past
retrospective
prospective
potential problem of this when people are aware that they are being observed
reactivity
observational biases
looks to the future
retrospective
prospective
same information in the same manner from all subjects
structure
quantifiable
objectivity
does not yield persuasive evidence for casual inferences
disadvantage of nonexperimental research
advantage of nonexperimental research
disadvantage of experimental research
can be collected in a way to allow statistical analysis
structure
quantifiable
objectivity
strive to be objective not subjective
structure
quantifiable
objectivity
efficient way to collect large amounts of data when intervention and/or randomization is not possible
disadvantage of nonexperimental research
advantage of experimental research
advantage of nonexperimental research
groups are formed through self selection therefore cannot assume the groups are equal or similar prior to the occurrence of the independent variable
selection bias (nonexperimental designs)
selection bias (experimental designs)
data are collected at a single point in time
cross-sectional desing
longitudinal design
attrition
data are collected two or more times over an extended period
cross-sectional design
longitudinal design
attrition
better at showing patterns of change and at clarifying whether a cause occurred before an effect (outcome)
longitudinal designs
latitudinal designs
challenge in longitudinal studies is _____ or the loss of participants over time
attrition
longitudinal design
cross-sectional design
better at showing patterns of change and at clarifying whether a cause occurred before an effect (outcome) but are expensive, time-consuming, and have risk of attrition
longitudinal designs
prospective designs
retrospective designs
plan for obtaining answers to research questions and/or for testing hypotheses
research design
hypothesis design
research design determines the amount of control the researcher exerts on the research situation
true
false
same people compared at different times or under different conditions
within-subjects design
between-subjects design
different people are compared (e.g. men and women)
within-subjects design
between-subjects design
when will information on independent and dependent variables be collected
relative timing
location timing
multiple studies
retrospective
case-control
cohort
prospective
case-control
cohort
one way to control over confounding variables is to randomly assign subjects to either experimental or control group
true
false
most _____ research questions are about causes and effects
quantitative
qualitative
research questions that seek to illuminate causal relationships need to be addressed with appropriate designs
causality
probability
what would have happened to the same people exposed to a "cause" if they simultaneously were not exposed to the cause
counterfactual
effect
represents the difference between what actually did happen when exposed to the cause and what would happen with the counterfactual condition
counterfactual
effect
the cause must precede the effect in time
temporal
relationship
confounder
there must be a demonstrated association between the cause and the effect
temporal
relationship
confounder
the relationship between the presumed cause and effect cannot be explained by a third variable or confounder; another factor related to both the presumed cause and effect cannot be the "real" cause
temporal
relationship
confounder
the causal relationship should be consistent with evidence from basic physiologic studies
biologic plausibility
intervention
offer the strongest evidence of whether a cause (an intervention) results in an effect (a desired outcome)
experimental designs
nonexperimental designs
true and quasi
experimental
non-experimental
descriptive and correlational
experimental
non-experimental
the researcher does something to some subjects - introduces an intervention (or treatment)
intervention
control
the researcher introduces controls, including the use of a control group counterfactual
intervention
control
the experimenter assigns participants to a control or experimental condition on a random basis
randomization
intervention
control
a true experimental design must have
manipulation of a treatment/intervention
control
random assignment (randomization)
which of the following would be a key criterion for causality
cause occurring before the effect
third variable involved with cause and effect
no empirical relationship between cause and effect
single-source evidence about the relationship
true experimental designs
pretest-posttest
posttest
factorial designs
crossover designs
allow for simultaneous manipulation of 2 or more variables at one time
factorial designs
retrospective designs
prospective designs
researchers can examine the effect of combining the interventions with factorial designs
true
false
subjects are given more than one treatment sequentially rather than concurrently
factorial design
crossover design
prospective design
subjects are exposed to 2+ conditions in random order
crossover design
factorial design
prospective design
the effects of the treatment on the same subject are compared in crossover
true
false
whether the treatment as planned was actually delivered and received
intervention fidelity
placebo
control group gets no treatment at all
no intervention is used
usual care
placebo
standard or normal procedures used to treat patients
no intervention is used
usual care
placebo
alternative intervention
example - auditory vs. visual stimulation
no intervention is used
usual care
alternative intervention
placebo
presumed to have no therapeutic value, but is used
no intervention is used
usual care
alternative intervention
placebo
extra attention, but not the active ingredient of the intervention
attention control
delayed treatment ("wait-listed controls")
alternative intervention
the intervention is given at a later date
attention control
delayed treatment ("wait-listed controls")
no intervention is used
most powerful method for testing cause and effect because researcher controls research situation
true experimental designs
quasi experimental designs
there is a high confidence in effectiveness of intervention with ____ experimental
true
quasi
the knowledge if being in a study may cause people to change their behavior
hawthorne effect of true experimental
hawthorne effect of quasi experimental
a true experiment requires that the researcher manipulate the independent variable by administering an experimental treatment (or intervention) to some subjects while withholding it from others
true
false
those getting the intervention are compared with a nonrandomized comparison group
nonequivalent control group designs (quasi)
within-subjects designs = one group design (quasi)
involve an intervention but lack either random assignment or control group
quasi experimental design
true experimental design
one group is studied before and after the intervention and one group is studied after the intervention
nonequivalent control group designs (quasi)
within-subjects designs = one group design (quasi)
time series (quasi)
one group studied over a period of time
nonequivalent control group designs (quasi)
within-subjects designs = one group design (quasi)
time series (quasi)
involves 2 or more groups of subjects observed before and after the intervention
nonequivalent control group pretest-posttest
within subject designs
nonequivalent control group posttest only design is much weaker
true
false
two or more groups of subjects observed after the intervention
nonequivalent control group posttest only
nonequivalent control group pretest-posttest
collect data over a period of time and introduce the IV or treatment during the data collection
one group pretest-posttest design (within subject design)
nonequivalent control group posttest only design
one group of subjects observed before and after the intervention
one group pretest-posttest design
nonequivalent control group pretest-posttest
typically yield extremely weak evidence of a causal relationship; lacks ways to control external factors that may result in differences
one-group pretest-posttest design
true experimental
factorial design
one-group posttest only design
introduce the IV or treatment, then collect the data; one group of subjects observed after the intervention
one group posttest-only design
one group pretest-posttest design
involves one group of subjects observed over multiple times both before and after the intervention
time series (within subjects)
one group pretest-posttest
one group posttest only
do time series have a comparison group
no
yes
to be classified as an experimental design (true or quasi) there MUST be
an intervention
no intervention
the design is automatically nonexperimental if there is
no intervention
an intervention
those that are a result of research situation
external factors (confounding variables)
internal factors (confounding variables)
type of setting, time of day the data was collected, how the data is collected, etc
external factors (confounding variables)
internal factors (confounding variables)
