Definitions Flashcards
Null Hypotheses
There will be no difference between the control and intervention arms
This is assumed to be true at the start of the study and has to be DISPROVED.
Dependant variable
The outcome of interest (for example healing time of a wound)
Independent variable
The intervention factor (for example the dressing being used in the intervention)
PROBABILITY sampling
Designed to give an UNBIASED sample where everyone (who meets the criteria) has a chance of selection
This is to choose the SAMPLE of those entering the trial Four types: Simple random, stratified random, cluster and systematic random
NON-PROBABILITY sampling
Non-random and the chance of being selected cannot be estimated
Falsification
Hypothesis testing
Hypothesis
Statement of the relationship between 2 variables
Standardised
Can be repeated and verified
Reliability
Must be repeatable with consistent results, dependability
Validity
Must measure what it intended to measure, credibility
Stratified random sampling
Put in groups according to characteristics (like gender) and then randomly selected
Cluster sampling
Random selection of larger units (like hospitals) which participants are then randomly selected from
Systematic sampling
Random selection of predetermined intervals
Factors affecting sample size
Population, Design, measurement, practical factors
Single blind trial
One person knows which aim of the trial they are in, person assessing the outcome does not know
Double blind trial
Neither participant nor person assessing outcomes knows the aim
Internal validity
Study results legitimate because of the way the study was conducted
External validity/generalisability
Concerns whether results are transferable to other groups
Threats to internal validity
History: Events happening outside the study
Maturation: Changes that happen over time
Testing: Change due to experience of the test
Instrumentation: Changes in measurement rather than change in status
Mortality: Differences in study drop out
Selection bias: Participants different to non-participants
Threats to external validity
Selection effects: generalisability to other populations, when ideal sample population cannot be obtained.
Reactive effects: Response to just being in a study (HAWTHORNE EFFECT).
Measurement effects: Measurement and testing affects the generalisability
Descriptive statistics
A way of displaying and summarising quantitative (numerical) data in ways that are easily understood
Levels of measurement
Nominal (categories)
Ordinal (different categories that can be ranked)
Interval (different categories that are ranked with equal spaces in-between)
Ratio (different categories that can be ranked, with equal spaces in-between and a fixed zero)
Hypothesis testing
P VALUE
- probability of obtaining results if the null hypothesis is true
- closer P value is to 0 the more likely that the null hypothesis will be rejected
- if P is smaller or eqial to 0.05 = reject null hypothesis
- if P is bigger or equal to 0.05 then we accept the null hypothesis
Type 1 error
False positive error
Type 2 error
False negative error
Baseline data
Data that is collected before the intervention but after the recruitment
P value equal or less that 0.001
Most statistically significant
Inferential statistics
Statistics that produce P value
Confidence interval
Measure of the precision with which the quantity of interest is estimated
Qualitative methods
Useful when you know little about a subject or problem
Studies are small scale and provide rich insight into lives of people
Ethnography
Study of culture
Phenomology
The study of phenomena - study of the lived experiences of individuals
Grounded theory
Developed by Laser and Strauss
- idea is to generate a theory
- hypothesis generated
Data collection in qualitative research - observation
Observer will inevitably participate to some extent
Observing and recording what is seen
Unstructured and sometimes spontaneous
- useful in exploring something that cannot be easily articulated
- field notes taken/audio record
Data collection in qualitative research - individual interviews
Useful in exploring individual perceptions of a culture/phenomenon
- unstructured but interview guide (questions evolve)
- audio-recorded
Data collection in qualitative research - focus group interviews
Useful when a topic is slightly sensitive/confrontational
- generates ideas, group dynamics
Qualitative data analysis
Produces vast amounts of rich data, needs to be reduced
Purpose of qualitative data analysis
Description, develop theory, develop hypothesis for research (constant comparative analysis)
Quantitative data analysis
Quantifies - decision about how to quantify made before data collection
Thematic content analysis
Common way is to go through the transcript line by line and look for common themes - things that crop up over and again, ‘commonalities’
‘Emerge from the data’
Themes are given a code - codes collapsed to categories = reducing data into something more manageable and meaningful
Interrogate data
Framework analysis
Take a framework to the data and put the data into the categories
Member checking
If more than one researcher working on project, all analyse and compare analyses to validate
Difficulties:
- analysis is interpretive
presentation of data
In a journal
Lengthy quotes followed by clear analysis and interpretation is a good way
Qualitative research less scientific?
Lack scientific rigour due to small sample sizes
Rigour
Trustworthiness - methodological soundness and adequacy, member checking
Generalisability
Transferability - findings can be transferred to a similar context
Objectivity
Confirmability - important that findings are not the result of the researcher’s preconceptions
Negative cases
Identification of data that buck the trend
Don’t fit with explanations, challenge the themes
Researchers need to ask why and consider revising interpretation
Peer review
Triangulation: examine topic from different perspectives: Data triangulation (common) i.e. different groups, settings, times Methodological triangulation i.e. two or more methods
Audit trial
Making all the decisions made throughout the research explicit
Reflexivity
Reflect on pre-conceptions: own actions, conflicts and feelings
CASP qualitative tool
Critically appraising qualitative research studies is useful
1. Clear statement of aims of research?
2. Qualitative methodology appropriate?
3. Research design appropriate to address aims?
4. Recruitment strategy appropriate to aims?
5. Data collected in way that addressed issue?
Clear statement of aims of research?
6. Relationship between researcher and participants adequately considered?
7. Ethical issues taken into consideration?
8. Data analysis sufficiently rigorous?
9. Clear statement of findings?
10. How valuable is the research? Transferable?Practice? Policy? Further research?
Dependability
Findings are consistent and accurate
Credibility
Participants recognise researchers interpretations
Transferability
Findings can be generalised to other contexts
Confirmability
Important findings are not the result of the researchers preconceptions
