Week 7: Diagnostic Studies, Clinical Prediction, Qualitative Research, Synthesis Research Flashcards
What type of research is Diagnostic Studies?
Exploratory and Descriptive
Diagnostic studies test a “special test” against a…
gold standard to assess its validity
Diagnostic tests have three potential purposes:
- focuses the examination
- identify problems that require physician referral
- assist in classification
Index test =
diagnostic test being studied
Gold standard =
an accurate indication of the patient’s true status
EBP Perspective
- all about probabilities and limiting uncertainty
- Pretest probability –> test –> posttest probability
pretest probability =
baseline probability of a certain condition before any testing takes place
posttest probability =
the revised likelihood of the diagnosis based on the outcome of the test
test threshold
“The probability below which a diagnostic test will not be ordered or performed because the possibility of the diagnosis is so remote”
yellow section
treatment threshold
“the probability above which a diagnostic test will not be ordered or performed because the possibility of the diagnosis is so great that immediate treatment is indicated.”
green section
Sensitivity
proportion of people WITH the disease who have a positive test result
True Positive
Specificity
Proportion of people WITHOUT the disease who have a negative test result
True Negatives
True positive is
positive clinical test, condition present
False negative is
negative clinical test, condition present
False positive is
positive clinical test, condition absent
True negative is
negative clinical test, condition absent
100% sensitivity
- detects all the TRUE POSITIVES
- helpful for “ruling out” the condition (when negative test)
- good screening tests are highly sensitive
100% specificity
- detects all of the TRUE NEGATIVES
- helpful for “ruling in” the condition (when positive test)
- more important for diagnostic special tests
SpPin
- a test with HIGH specificity
- that is positive
- helps rule a condition IN
SnNout
- a test with HIGH sensitivity
- that is negative
- helps rule a condition OUT
Likelihood Ratios (LRs)
sensitivity information combined with specificity information
if diagnostic test is positive:
use +LR
if diagnostic test is negative:
use -LR
with +LR, you want probability of false positives to be
to be LOW
with -LR, you want probability of true negatives to be
to be HIGH
Clinical Prediction Rules can be for
diagnosis, screening, factors that predict response to treatment
Diagnosis is for
rule in, specificity, +LR
Screening is for
rule out, sensitivity, -LR
Validating CPRs Steps
deriving the model, validation of the rule, impact analysis
deriving the model
- look for factors that contribute to diagnosis
- Sn and Sp: good for ruling dx in or out?
- OARs: Sn = 95%; Sp = 50% (better for ruling out)
validation of the rule
- confirm accuracy on different samples
- narrow vs broad
impact analysis
- has a CPR been adopted, and has it improved diagnosis?
- OARs have significantly reduced number of X-rays
Issues with CPRs
greater sample size, the more power there is in the study
CPRs can help predict…
the presence of a diagnosis, a patient’s prognosis, and/or treatment response
Most CPRs have NOT held up to
validation
What type of research is Qualitative Research?
Descriptive and exploratory
Qualitative Research qualities
- understanding
- discovering frameworks
- interview/observation
- textual (words)
- theory generating
- quality of informant > sample size
- subjective
- model of analysis: fidelity to text or words of interviewees
Quantitative Research qualities
- prediction
- existing frameworks
- survey/questionnaires
- numerical
- theory testing
- sample size corer issue in reliability of data
- objective
- model of analysis: parametric, non-parametric
example of qualitative
“it’s really hard for me to explain how I am feeling…”
example of quantitative
“How difficult would you say that is, on a scale from 1-10?”
Qualitative Research
- based on the belief that all interactions are inherently social phenomena
- considered an inductive process
- in natural setting
purposes and uses of qualitative research
- generating theories that can be tested by further research
- developing theory to explain observed phenomena
- investigating complex phenomena
Qualitative Research question
- PICO questions do not apply
- no specific hypothesis based on the research question
3 main types of Qualitative Research
- ethnography
- grounded theroy
- phenomenology
Ethnography
“who lives it”
describes cultural characteristics and behaviors in a specific group
-investigators immerse themselves in the settings and activities
Grounded theory
- individual responses contribute to understanding theoretical relationships that can explain behavior
- “constant comparison”
Phenomenology
seeks to explain how events and circumstances influences perspectives and behaviors
Methods of Qualitative Data Collection: Qualitative only
- observation
- interviews
- written documents
Methods of Qualitative Data Collection: mixed methods
- convergent
- sequential
- embedded
- multiphase
Sampling in Qualitative Research
non-probability sampling
sample size: may be large or small
- till saturation
**no set # of people
non-probability sampling types
convenience, purposive, snowball
sample size in qualitative research may be
larger or small
- till saturation so there is no set # of people required for a study
Credibility of Qualitative Studies
- are the results believable? can we have confidence in the results?
- like “validity” in quantitative research
Transferability of qualitative studies
- can the results be applied to people in similar circumstances?
- like “generalizability” in quantitative research
Dependability of qualitative studies
- how stable are the data over time?
- like “reliability” in quantitative research
Confirmability of qualitative studies
- are the findings due to the beliefs and experiences of the participants or is it bias?
Triangulation
more than one source
member checking
confirm interpretation with others, including participants and colleagues
negative case analysis
explain conflicts that emerge from preliminary data
thick description
of narrative data; improves ability to make comparisons (voices, feelings, actions…adds context)
purposive sampling
choosing participants who can be good informants
audit trail
documenting decisions so another researcher can confirm findings
reflexivity
examining how the researcher’s beliefs may influence interpretation of data; mitigated by including multiple researchers
qualitative methods + quantitative methods =
“mixed methods”
Three types of literature reviews
scoping review, systematic review, meta-analysis
scoping review
- selective review of the literature that is less systematic.
- exploratory assessments of available literature on a broad topic
systematic review
- utilizes exacting search strategies to make certain that the maximum extent of relevant research has been considered
- original articles are methodologically appraised and synthesized
meta-analysis
- quantitatively combines the results of studies that are the result of a systematic literature review
- capable of performing a statistical analysis of the pooled results of relevant studies
scoping reviews can answer…
background questions
- do not critically appraise articles for methodological quality
- PICO questions are too specific
What are systematic reviews?
they search, appraise, and summarize the existing info on a topic
Sources of bias in selection in Systematic Review
- publication bias
- access clinical trials registries
- access the “grey literature”
- conferences, abstracts, websites, dissertations
selection bias
- random assignment
- allocation concealment
performance bias
blinding of patients and investigators
detection bias
blinding of assessors
attrition bias
incomplete outcome data
reporting bias
selective reporting
PRISMA
preferred reporting items for systtematic reviews and meta analyses
Meta-analysis does what
uses math and numbers to extract and combine data to produce a summary result
Point estimate
a single value that represents the best estimate of the population value
confidence interval
a range of values that we are confident contains the population value
if the confidence interval includes 0 it means it is NOT
statistically significant