Final Flashcards
measurement
process of assigning numbers to objects, events or situations representing the amount of an attribute using a specified set of rules
nominal measurement
classify or categorize data
labels
lowest of 4 levels
ordinal measurement
order/rank values w/out equal intervals
continuum of numeric values w/ small numbers representing lower levels and large number higher lvls but adding them has no meaning
3rd lowest
ex: ordering
interval measurement
give values meaning w/ equal intervals may or may not contain a sero manmade scales of measurements 2nd highest level of evidence ex. scored response survey
ratio measurement
give values meaning with equal intervals w/ absolute zero point
highest form of measurment
numbers in order
ex: weight or height
measurement error
difference between the true measure and what is actually measured
systematic error
error that occurs in the same way with each measurement
random error
errors that occur by chance w/out pattern during measurement
correlation coefficient
measures reliability (consistency)
1.00 is perfect reliability wheras 0.00 is none
needs to be at least .7
test for 3 attributes
stability, equivalence, internal consistency
methods to test for reliablity
test-retest reliability
parallel or alternate form
validity of an instrument
the extent that an instrument measures a concept accurately
types of validity
content validity (face validity/content validity index) criterion-related validity (concurrent - degree of correlation btwn two variables or predictive - measure btwn a measure and a future measure) construct validity (how much an instrument actually measures the theoretical concept)
qualitative data methods
questionnaires interviews focus groups case studies observations
appraising qualitative data collection
assess sample/setting
data collection and report
report of biases
phenomenology
indepth interviews/diaries/artwork
track an experience/phenomenon
grounded theory
observations/open-ended questions w/ individuals or small groups
develops a theory
ethnography
participant/direct observations/interviews/diagrams/documents/photographs
historical
open-ended interviews/documents/photographs/artifacts
sampling error
difference btween a sample statistic and a population parameter
sampling bias
occurs when the sample is not representative of whole pop
4 steps to ensure representative sample
define the target population and their essential characteristics
ID a pop the researcher has access to for the study and see if it resembles the target pop
develop a method to approach them (sampling frame)
select subjects from the accessible population to include in sample
simple random sampling
probability sampling
each subject has the same chance to be selected
randomized
stratified random sampling
probability sampling
strata must be mutually exclusive so a subject can be assigned to only one stratum
random sampling to select subject from each stratum
cluster sampling
probability sampling
simple random sampling selects groups/cluster then select subjects w/in each cluster
systematic sampling
probability sampling
count each kth subject by first IDing the start location
convenience sampling
nonprobability
inclusion criteria ID then subjects invited to participate
quota sampling
nonprobability
strata mutually exclusive then convience sampling used to select subject from each stratum
purposive sampling
nonprobability
research selects sample of experts
commonly used in qualitative research
research chooses based on defined criteria
theoretical sampling
nonprobability
data collection and analysis occurs simultaneously
usually for grounded theory research
power analysis
statistical analysis to determine acceptable sample size (standard power of .8)
effect size
estimate of how large a difference will be observed between gorups
alpha level
level of significance
0.05 0.01 or 0.001
nursing as a sceince
propositional knowledge (knowledge that is formal, explicit and derived from research/scholarship) generalizable
case study
“real life” context
used to report the story of one patient in a clinical scenario
methodologies for qualitative research studies
concept analysis
provide for the exploration of the attributes and characteristics of a concept
Walker & AVant
process of concept analysis
select concept, determine purpose of analysis, ID use of concept, determine attributes, …define empirical referents
systematic review
rigorous synthesis of research findings about a clinical problem
literature/narrative reviews
article based on common/uncommon elements
little concern fr research methods/design/reporting
integrative reveiws
scholarly paper synthesizing published studies
meta-analysis
scholarly paper that combines results of studies published and unpublished into a statistical predictor
meta-synthesis
study that combines results of many qualitative studies
“S”tatistics
branch of mathematics that collects, analyzes, interprets and presents data related to samples and populations
statistics
numerical outcomes and probability from accumulations on raw data
descriptive statistics
collection and presentation of data to explain characteristics about the variable
inferential statistics
analysis of data to base your predictions related to what you’re studying/phenomenon of interest
strongly related to your hypothesis
univariate analysis
presents information on only one variable at a time
frequency distribution, central tendency, shape of distribution, variability
bivariate analysis
describes relationship btwen 2 variables
correlations, direction, magnitude
multivariate analysis
relationship btween 3+ variables
regressions, clustering, concept mapping
grouped frequencies
interval and ratio raw data collapsed into classification to ease interpretations
group size should be consistent
easier to interpret but may lose some information
ungrouped frequencies
presenting nominal an ordinal data where the raw data represents a characteristic of data
central tendency
most frequently occuring value in the dataset
mode
median
exact point where 1/2 of the data is above and 1/2 below
average but not very affected by any outliers
mean
mathematical average of the data
most commonly used
distribution
visual representation of the central tendencies (normal = symmetrical, same value for mean/median/mode)
skewed (negatively asymptomatic or positively)
kurtosis
how peaked or flat the dataset appears in a distribution
homogenous
little variability, lost of similarity
heterogenous
lost of variability
little similarity
confidence intervals
ranges taht estimate the probability of being correct
commonly 95 or 99%
type I error
researcher rejects the null hypothesis when it should have been accepted
thought something happened but nothing actually does
type II error
researcher accepts null hypothesis but it should have been rejected
an intervention was successful but not seen as so due to error or chance
alpha level .05
likely to make a type I error
usually used in nursing research
alpha .01
likely making a type II
between group statistical test
chi square t statistic (determine if there's difference between interval and ratio data) analysis of variance
relationships among variables
pearson’s r (correlation coefficient)
multiple regressions (describes rlt of 3+ variables interval or ratio)
nominal data(phi, point biserial, contingency coefficients)
ordinal data
outcomes
consequences or visible results
who, types, time, nursing care effectiveness
choosing outcomes
need indicator (specific quantitative data) consider other factors
3 Ps of dissemination
poster
presentation
paper
oral presentations best suited for
philosophical work
theoretical work
completed work
content in EBP posters
clinical question review of literature methods title/authors/affiliations synthesis of findings decision about practice implementation evaluation discussion acknowledgements/references
5 step approach for EBP from straus
ask acquire appraise apply assess
active rejection
pilot was tried or innovation adopted but no further implementation of innovation
passive rejection
reviewing info/evidence then decide not to make any changes
stetler EBP
focus on how individuals adopt research findings at the bedside
de-emphasizes ritual/isolated unsystematic clinical experience ungrounded
John Hopkins Nursing EBP PET process
practice question
evidence
translation
strats to promote adoption of EBP
put in writing the evidence
use quick reference guides/decision aids
clinical reminders
