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Nursing Knowledge and Research > Definitions > Flashcards

Definitions Flashcards

1
Q

Null Hypotheses

A

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.

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2
Q

Dependant variable

A

The outcome of interest (for example healing time of a wound)

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3
Q

Independent variable

A

The intervention factor (for example the dressing being used in the intervention)

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4
Q

PROBABILITY sampling

A

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

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5
Q

NON-PROBABILITY sampling

A

Non-random and the chance of being selected cannot be estimated

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6
Q

Falsification

A

Hypothesis testing

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7
Q

Hypothesis

A

Statement of the relationship between 2 variables

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8
Q

Standardised

A

Can be repeated and verified

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9
Q

Reliability

A

Must be repeatable with consistent results, dependability

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10
Q

Validity

A

Must measure what it intended to measure, credibility

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11
Q

Stratified random sampling

A

Put in groups according to characteristics (like gender) and then randomly selected

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12
Q

Cluster sampling

A

Random selection of larger units (like hospitals) which participants are then randomly selected from

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13
Q

Systematic sampling

A

Random selection of predetermined intervals

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14
Q

Factors affecting sample size

A

Population, Design, measurement, practical factors

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15
Q

Single blind trial

A

One person knows which aim of the trial they are in, person assessing the outcome does not know

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16
Q

Double blind trial

A

Neither participant nor person assessing outcomes knows the aim

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17
Q

Internal validity

A

Study results legitimate because of the way the study was conducted

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18
Q

External validity/generalisability

A

Concerns whether results are transferable to other groups

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19
Q

Threats to internal validity

A

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

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20
Q

Threats to external validity

A

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

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21
Q

Descriptive statistics

A

A way of displaying and summarising quantitative (numerical) data in ways that are easily understood

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22
Q

Levels of measurement

A

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)

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23
Q

Hypothesis testing

A

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
24
Q

Type 1 error

A

False positive error

25
Type 2 error
False negative error
26
Baseline data
Data that is collected before the intervention but after the recruitment
27
P value equal or less that 0.001
Most statistically significant
28
Inferential statistics
Statistics that produce P value
29
Confidence interval
Measure of the precision with which the quantity of interest is estimated
30
Qualitative methods
Useful when you know little about a subject or problem | Studies are small scale and provide rich insight into lives of people
31
Ethnography
Study of culture
32
Phenomology
The study of phenomena - study of the lived experiences of individuals
33
Grounded theory
Developed by Laser and Strauss - idea is to generate a theory - hypothesis generated
34
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
35
Data collection in qualitative research - individual interviews
Useful in exploring individual perceptions of a culture/phenomenon - unstructured but interview guide (questions evolve) - audio-recorded
36
Data collection in qualitative research - focus group interviews
Useful when a topic is slightly sensitive/confrontational | - generates ideas, group dynamics
37
Qualitative data analysis
Produces vast amounts of rich data, needs to be reduced
38
Purpose of qualitative data analysis
Description, develop theory, develop hypothesis for research (constant comparative analysis)
39
Quantitative data analysis
Quantifies - decision about how to quantify made before data collection
40
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
41
Framework analysis
Take a framework to the data and put the data into the categories
42
Member checking
If more than one researcher working on project, all analyse and compare analyses to validate Difficulties: - analysis is interpretive
43
presentation of data
In a journal | Lengthy quotes followed by clear analysis and interpretation is a good way
44
Qualitative research less scientific?
Lack scientific rigour due to small sample sizes
45
Rigour
Trustworthiness - methodological soundness and adequacy, member checking
46
Generalisability
Transferability - findings can be transferred to a similar context
47
Objectivity
Confirmability - important that findings are not the result of the researcher’s preconceptions
48
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
49
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 ```
50
Audit trial
Making all the decisions made throughout the research explicit
51
Reflexivity
Reflect on pre-conceptions: own actions, conflicts and feelings
52
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?
53
Dependability
Findings are consistent and accurate
54
Credibility
Participants recognise researchers interpretations
55
Transferability
Findings can be generalised to other contexts
56
Confirmability
Important findings are not the result of the researchers preconceptions

Nursing Knowledge and Research (2 decks)

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