Midterm Flashcards
Qualitative Designs
using words to provide evidence
Benefits to qualitative research
systemic, subjective approach to describe life experiences/give them meaning focuses on understanding flexible does not test hypothesis not true causality
Four major types of Qualitative Research
phenomenology
ethnography
grounded theory
historical
Phenomenology
describes teh meaning of human experience
Bracketing
process of identifying and holding abay preconceived beliefs and opinions about phenomenon that is being studied
Reflective Journal
clarify persona vlaues/areas of bias
Main data source for phenomenology
in-depth conversations with participants
Grounded Theory
aims to discover theoretical precepts about social psychological processes and social structures (grounded in data)
Grounded Theory has
number of theoretical roots (symbolic interaction)
focuses on social psychological processes and social structures
Ethnography
focuses on the culture of a group of people
seeks to understand an emic perspective (insiders’ view)
Etic perspective
researcher’s perspectives/interpretation
Ethnography relies on
fieldwork and participant observation
Historical Research
establishes facts about/relationships among past events
Historical research sources
written records
photographs
interviews
pictures
historical research
external criticism (authenticity of the source) internal criticism (worth of the evidence)
Other types of qualitative research
case studies narrative analysis (focus on studies and individuals) feminist research participatory action research descriptive qualitative
Qualitative Sampling
not representative
not random selection
stop sampling when data saturation is met
Convenience sampling
volunteer (not preferred but economical)
snowball sampling
network sampling
purposive sampling
researchers choose cases that will contribute to the study the most
theoretical sampling
involves decisions about where to find data to develop an emerging theory optimally
maximum variation sampling
cases with wide variation on phenomenon of interest
extreme case sampling
most unusual/extreme cases
typical case sampling
cases that illustrate what is typical
homogenous sampling
reducing variation
Focus group discussion pros
cost effective
tend to be enjoyable
interactions enhance data
focus group cons
number of questions available response time skill of interviewer minority perspective confidentiality
artifacts
diaries
photos
letter
books
qualitative data
texts transcripts field notes memos books pictures maps memoirs videos audio tapes newspapers
qualitative data analysis occurs
concurrently with data collection
ways to analyze qualitative data
transcribing and checking reading the whole and between the line coding identify themes validate themes/patterns
Coding data:
inductive analysis
open coding/codes
primary coding
first level
axial coding
naming categories
second level of coding
sorting/grouping
selective coding
naming theme
higher level of coding
qualitative data interpretation
verifying the analysis (representativeness/replication)
researcher offers their own interpretation
can focus on usefulness of findings for practice
trustworthiness
the “truth value” of qualitative data and analysis
four criteria of trustworthiness
credibility (confidence of truth in data)
dependability (stability over time and conditions)
confirmability (objectivity of data)
transferability (extent that findings can be transferred to other settings/groups)
strategies enhancing trustworthiness
prolonged engagement persistent observation comprehensive/vivid recording of info audit trail/decision trail member checking (provide feedback to participants and obtain reactions--controversial)
strategies enhancing trustworthiness II
data triangulation (use of multiple data sources, time/space/person)
negative case analysis (specific search for invalidating cases)
peer review/debriefing
inquiry audit (formal scrutiny of data/supporting documents by external reviewer)
thick/contextualized description
researcher credibility
Epidemiology
study of distribution and determinants of disease in human population
distribution
frequency/pattern
determinants
causes/risk factors
disease
health conditions/events
epidemiologic triangle
host
agent
environment
count data
ratio
proportion
rate
raw number
a/b
a/a +b multiplied by 1000
number of cases divided by the size of population per unit of time
Prevalence
number of existing cases of a disease in a population regardless of when acquired
incidence
number of new cases of a disease during a specific period
analytic epidemiology
use of a comparison group
descriptive epidemiology
use to generate hypotheses 5W's who (person) where (place) when (time) why/how (causes/risk factors/modes of transmission) what (health issue) examples: case report/series ecologic studies cross-sectional studies
case report/case series
1 patient or over one patient
describes new disease
used to explain changes in disease patterns/alert healthcare community to unusual signs/symptoms
lacks a comparison group = no hypothesis
ecologic studies
compare summary measure disease frequency
uses aggregate data
uses a population as unit of analysis
expedient
lacks link of exposure to disease to specific individuals
cross-sectional studies
measures exposure/disease as each exists in one defined population at one specific point in time
snapshot of population characteristic
calculates prevalence ratio
difficult to distinguish determinants of cause of disease from determinants of survival
analytic epidemiology
used to test hypotheses
test association between exposure/disease
case-control studies/cohort studies (observational)
intervention/experimental studies
case-control studies
sample group WITH and group WITHOUT disease or outcome measure under study
ask individual to recall past exposures to risk factors
determine cases(individuals with disease of interest) and controls (without disease but at risk to develop disease)
calculate odds ratio
Odds Ratio
A(# RFw/Disease) x D (#noRFw/oDisease) / B(#RFw/odisease) x C(noRFw/Disease)
=1 exposure does not affect odds
>1 exposure positively associated
<1 exposure negatively associated
cohort study
researcher records whether each study participant is expose or not and tracks participant to see if they develop disease of interest
representative group of target population
compare probability of disease in exposed individuals to unexposed individuals
calculate relative risk
relative risk
incidence in exposed group / incidence in unexposed group
=1 no association
>1 positive association
<1 negative association
intervention studies
manipulates exposure of interest
assigns subjects to one or more exposure groups (placebo/standard of care and intervention)
uses random assignment
uses risk ratio
evidence hierarchy
- systematic reviews/ meta analysis/ EBP guidelines
- randomized controlled trials
- controlled trials w/out randomization
- cohort studies/case control studies
- evidence from systematic reviews of descriptive and qualitative studies
- evidence from single descriptive/qualitative study
- evidence from opinion of authorities/reports of expert committees
screening
tests people w/out known disease to determine if they have a disease
offers early detection
aims to reduce morbidity/mortality
screening validity measures
sensitivity
specificity
positive predictive value
sensitivity
ability of test to correctly id people w/ disease w/ positive test result (%true positive)
true positive + false-negative
specificity
ability of test to id people w/out disease by negative test result (%true negative)
true negative + false positive
positive predictive value
probability that person screening positive actually has the disease
(true positive / (true positive + false positive)
Experimental Designs
must have
cause-and-effect strong causality 1. manipulation of independent variable 2. randomization of subjects 3. control
Quasi-Experiment
must have
but can lack
can test cause and effect
weaker causality
manipulation
randomization or control/comparison group
six types of true experimental designs
two group, pretest-posttest (classic) two group, posttest only solomon four-group multiple experimental groups (but one control group)crossover designs factorial design
Factorial design
researches add at least one additional intervention
tests for multiple causality
three common quasi-experimental designs
nonequivalent control group pretest-posttest
time series design
pre-experimental designs
nonequivalent control group pretest-posttest
two groups measured before and after an intervention
experimental/comparison groups but no randomization
threats to internal validity (selection, maturation, testing, mortality)
time series design
one group is measured prior to an intervention then measured multiple times over a prolonged period
useful for determining trends over time
data collected multiple times to determine change from baseline
pre-experimental designs
posttest only design
experimental and/or comparison groups neither is pretested nor measured
no randomization used
useful when testing effects are suspected to be a threat to internal validity
non-experimental designs used for
describing a phenomenon in detail
explaining/predicting relationships among variables
non-experimental research designs
no manipulation
no randomization
no control group
Types of non experimental design
descriptive
correlational
exploratory descriptive research
conduced in natural setting to answer a research question r/t incidence/prevalence/frequency of a phenomenon
comparative descriptive resaesrch
two distinct groups are described and compared in terms of their variables
survey research
collects detailed descriptions of existing variables
uses self-report questionnaire
correlational research design
qualifying strength/direction (+/-) of relationship
flexible and efficient
Descriptive (simple) correlational design
uses statistics
model-testing designs
tests proposed relationship w/in a theoretical model
uses statistical tests
usually path analyses and structural equation modeling
quantitative design
examines cause and effect
experimental and quasi-experimental
potential sources of bias
operational definitions measurement methods sample researches or research assistants individual subjects data
between groups designs
compare different groups of subjects
within-groups designs
compare same group but at different point in time
panel designs
same subjects provide data at multiple points in time
trend studies
non experimental
gather data in target pop across time
crossover design
subjects receive more than one experimental tx and then followed over time
study validity
internal validity
statistical conclusion validity
external validity
construct validity
internal validity threats
intrusion of extraneous variables
established by ruling out threats
selection bias
history (past event that effects DV)
maturation (developmental processes that operation w/in a person over time)
testing
instrumentation (changes in equipment used)
mortality (or attrition)
statistical conclusion validity (no type II error)
external validity
degree to which the results of the study can be generalized to other subjects/setting/times
threats to external validity
construct validity (instruments are actually measuring theoretical concepts) effects of selection interx of tx and selection of subjects interx of tx and setting/history
metaparadigm of nursing
global perspective of a discipline
person - environment - health - nursing
deductive approach
use to test a theory
involve quantitative approach
start with a research question/testable idea
inductive approach
use to develop a theory
involve qualitative approach
start with data
introduction section
problem statement
literature review
guidelines for conducting ethical research
nuremberg code declaration of helsinki informed consent the ana voluntary consent rights of subjects to withdraw protection of subjects from physical and mental harm/suffering/death balance of benefits and risks
vulnerable populations
children pregnant women unborn fetuses frail elderly prisoners mentally handicapped
minimal risk =
expedited review
ex noninvasive monitoring, research on benign drugs
no apparent risk =
exempt from review
most educational research
associative hypothesis
relationship between variables
causal hypothesis
causal relationship between variables
non directional hypothesis
an association between variables
directional hypothesis
positive or negative relationship
null hypothesis
no relationship between variables
Evidence-based practice
integration of best research evidence, clinical expertise and patient values
nursing research
planned/systematic activity that leads to new knowledge and/or discover of solutions r/t nursing
steps of ebp
ask clinical question search literature critically appraise evidence implement practice change evaluate outcomes
