CASP Keywords Flashcards
Abstract Summary
make summary of the larger paper
- report aim and outcomes
Acceptability - to accept something
how much the people delivering consider it appropriate
Aim
the purpose of the study - what it is and what it’s trying to achieve
Assumption of Normality
how does it appear on a graph?
assuming that the sample destruction is normal
- bell curve
- most score close to the mean
Blinding.
participants don’t know
Double Blinding.
the participants and researchers don’t known
Calibrate
making sure measurements are at consistent quality
case report.
to describe and interpret an individual case
case-control study, what’s the purpose?
patient who have disease vs patients who don’t
- to compare risk factors and disease with exposures to risk factors
clinical trial
testing new drugs or approaches to surgery to improve disease diagnosis and quality of life
cohort study
1+ samples are followed to determine the link of risk factors to a disease
conclusion
sum up key points and provide statement of opinion/decision reaches
confidence interval
the probability that a population parameter will fall between 2 set values
- help to measure the degree of uncertainty
conflict of interest
individual becomes unreliable because of clash of self interest and professionalism
confounding variable.
a third variable influencing the independent and dependent, if you don’t account the links are invalid
critical appraisal
evaluate, judge a papers validity and relevance
cross-sectional study
a one-off
- exposure and outcome is measured at the same time
data analysis
data - inspect, model
discover useful information, good conlusion
dependent variable
what can be measured and changed
drop-out
participants leave a study
- differences between those who continue create bias = attrition bias
discussion
explore relevance, significance and meaning
exclusion criteria
factors that make a person ineligible to participate or make a study ineligible
experimental group
group who receive the experimental treatment
external reliability
the extent to which a measure is consistent when assessed over time
external validity
how much the study can be generalised to other measures
fidelity
how much the delivery of intervention adheres to the original protocol
aka the degree exactness to how it was meant to be done
what is feasibility used for?
to estimate the important parameter that make the study possible
hypothesis
precise prediction
inclusion criteria
factors what the participants must meet to take part
independent variable
what I, the researcher can change/control
internal reliability
how much a measure is consistent within itself
aka if ur measuring me and I have bi-polar, I don’t have internal reliability
internal validity
the degree of confidence that the established link is trustworthy and not influenced by other factors
inter-rater reliability
how much different raters have the same level of agreement
interventional studies
study to evaluate direct impact of exposure on outcome
- then to determine the effectiveness of intervention
introduction
establish context
background information
state purpose of the study
explain method
highlight potential outcome
longitudinal study
repeated observation of the same variable over a period of time
meta-analysis
combining study date from several studies to develop single conclusion with large statistical power
non-parametric
statistical data that doesn’t meet the assumption of normality
objective measure
consistent measure independent of researcher
- time, criteria
objective
statment to define how the outcome comes about
parametric test
statistical data that meets the assumption of normality
PPI
patient and public involvement
research carried out ‘with’ or ‘by’ patients and those who have experience of a condition
pilot-study
studies which aim to investigate whether crucial
components of a main study will be feasible
power calculation
allows you to calculate how many participants are
needed in a study to get an effect of a certain size and avoid statistical errors (i.e
process evaluation
aim to explain how an intervention works or does not work by looking at:
- how it is implemented
- the theories behind
- reasons for participation
qualitative, what is the aim?
non-numerical data
- produce detailed description of the study
quantitative, what is the aim?
numerical data
- produce objective, empirical data
- test hypothesis, identify pattern and make predictions
recruitment
identify eligible participants, get valid consent, maintain ethical until study is complete
reliability
the consistency of the results, should be able to be repeated with the same result
results
state finding, without bias or interpretation
retention
keeping participants for the duration of the study
saturation
no new data is discovered
sample
group of representative people taken from a larger population so we can generalise for the whole population
self-report/subjective
participants respond to the researcher’s questions without interference
significance
measure of the probability of the null hypothesis being true
results are significant if p value <0.05, can reject the null hypothesis
split-half reliability
measures how much all parts of the test contribute to what’s being measured
- compare results of one half of the test with the other
- similar results = internal reliability
standardisation
procedures are kept the same
stratification
partitioning the participants by a factor other then exposure/treatment
- gender, age
subjective measure
self-report measures
what the participants say they experience
systematic review
comprehensive review of all the studies on a topic
test-re-test reliability method
measures stability of a test over time
give the same participants, the same test on 2 separate occasions
- if similar results = external reliability
user involvement
involving the users of research
validity
how much your findings truly represent what you’re claiming to measure
