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Nursing Knowledge and Research > Definitions > Flashcards

Definitions Flashcards

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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
Q

Type 2 error

A

False negative error

26
Q

Baseline data

A

Data that is collected before the intervention but after the recruitment

27
Q

P value equal or less that 0.001

A

Most statistically significant

28
Q

Inferential statistics

A

Statistics that produce P value

29
Q

Confidence interval

A

Measure of the precision with which the quantity of interest is estimated

30
Q

Qualitative methods

A

Useful when you know little about a subject or problem

Studies are small scale and provide rich insight into lives of people

31
Q

Ethnography

A

Study of culture

32
Q

Phenomology

A

The study of phenomena - study of the lived experiences of individuals

33
Q

Grounded theory

A

Developed by Laser and Strauss

  • idea is to generate a theory
  • hypothesis generated
34
Q

Data collection in qualitative research - observation

A

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
Q

Data collection in qualitative research - individual interviews

A

Useful in exploring individual perceptions of a culture/phenomenon

  • unstructured but interview guide (questions evolve)
  • audio-recorded
36
Q

Data collection in qualitative research - focus group interviews

A

Useful when a topic is slightly sensitive/confrontational

- generates ideas, group dynamics

37
Q

Qualitative data analysis

A

Produces vast amounts of rich data, needs to be reduced

38
Q

Purpose of qualitative data analysis

A

Description, develop theory, develop hypothesis for research (constant comparative analysis)

39
Q

Quantitative data analysis

A

Quantifies - decision about how to quantify made before data collection

40
Q

Thematic content analysis

A

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
Q

Framework analysis

A

Take a framework to the data and put the data into the categories

42
Q

Member checking

A

If more than one researcher working on project, all analyse and compare analyses to validate
Difficulties:
- analysis is interpretive

43
Q

presentation of data

A

In a journal

Lengthy quotes followed by clear analysis and interpretation is a good way

44
Q

Qualitative research less scientific?

A

Lack scientific rigour due to small sample sizes

45
Q

Rigour

A

Trustworthiness - methodological soundness and adequacy, member checking

46
Q

Generalisability

A

Transferability - findings can be transferred to a similar context

47
Q

Objectivity

A

Confirmability - important that findings are not the result of the researcher’s preconceptions

48
Q

Negative cases

A

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
Q

Peer review

A 
Triangulation: examine topic from different perspectives:
Data triangulation (common) i.e. different groups, settings, times
Methodological triangulation i.e. two or more methods
50
Q

Audit trial

A

Making all the decisions made throughout the research explicit

51
Q

Reflexivity

A

Reflect on pre-conceptions: own actions, conflicts and feelings

52
Q

CASP qualitative tool

A

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
Q

Dependability

A

Findings are consistent and accurate

54
Q

Credibility

A

Participants recognise researchers interpretations

55
Q

Transferability

A

Findings can be generalised to other contexts

56
Q

Confirmability

A

Important findings are not the result of the researchers preconceptions

Nursing Knowledge and Research (2 decks)

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