Exam prep week 11 (Mixed methods research clinical governance) - wk 12 (Descriptive data analysis and findings) Flashcards

(37 cards)

1
Q

What is mixed methods research?

A

“Research in which the investigator collects and analyses data, integrates the findings and draws inferences using both qualitative and quantitative approaches or methods in a single study”
(Tashakkori & Creswell 2007:265)

Studies that have used two designs, qualitative and quantitative

Offers a different approach

Not limited to constraints of one or the other

Journal Of Mixed Methods Research

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Methodological Triangulation (Pluralism)

A

Triangulation : usually applied to qualitative research

Reduces error/increases rigor

Different methods of data collection used in same study

For example: interviews + participant observation + documentation + focus groups etc

Now used to denote single study using combination of research designs/paradigms

Triangulation (more commonly used term)= pluralism = Mixed Methods

Becoming much more common/popular especially in nursing research

Not always labelled as such

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Terminology/Rationales Associated with Mixed Methods

A
Triangulation
Completeness
Off-setting weakness & providing stronger inferences
Answering different research questions
Wider explanation of findings
Broader illustration of data
Hypothesis development & testing
Instrument development & testing
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

REMEMBER!!

A

The appropriate research design is the one that will best answer the research question

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Value of Mixed Methods

A

Potential for more complete & comprehensive research opportunity

Can give additional perspectives & insights beyond scope of single design

Weaknesses of one method may be counter-balanced by strengths of another

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Limitations of Mixed Methods

A

Complex
Time consuming
Involved
Resource-intensive
Knowledge required of researchers- both qualitative & quantitative knowledge
Understanding & acceptance by research community needed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Action Research

A

Narrows gap between research and implementation of results

Research in the real world situation

Occurs in a spiral/cycle design

May use any type of research methodology

Emphasis on continual improvement

Limitation: may be weak experimental design

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Delphi Technique

A

Uses expert opinion on a clinical practice problem

Non-empirical approach (ie no data collection)

Useful when experimental approach not feasible

Limitation: only represents opinion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Clinical Guidelines

A

Provide recommendations on clinical management

Generate national/international consensus on management principles

Allow for application of Research and EBP relating to a specific area of clinical practice

Are not mandatory

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Tools to guide clinical decision making

A

Tools to guide clinical decision making eg standards, policies, & procedures, algorithms, clinical pathways, clinical guidelines

Assist to make appropriate decisions about patient care to result in best patient outcomes
Historically developed by individual/groups of experts

No process to determine validity/reliability

Evidence based practice has led to clinical guidelines being systematically developed

Based on best available research evidence

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Definitions

A

Algorithms: clinical guidelines on flowchart

Clinical pathways: document essential steps in a clinical process eg COPD pathway

Clinical guidelines: systematically developed statements to assist clinical and patient decisions

Policies: written plans of an organisation’s official position eg Medication Administration Policy

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Definitions (cont.)

A

Procedures: series of formal steps for performing specific tasks

Protocols: rigid, prescribed statements

Standards: accepted discipline-based principles for patient care processes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Policy

A

“A document that describes the organisation’s purpose or standard for a given customer process or issue, the expected outcome, guiding principles, roles and responsibilities, definition of terms within the document and references. Compliance with policies is mandatory”

(“Definitions of policy related documents within WA Health,” n.d.)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Procedure

A

A document that generally supports a policy by describing an instruction that clearly prescribes the actions of each step of a process to be taken and by whom.

(“Definitions of policy related documents within WA Health,” n.d.)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Characteristics of Effective Clinical Guidelines

A

No internationally recognised framework but general world-wide agreement

Key qualities for guidelines to be effective

Should be considered when appraising existing national guidelines before adapting to local situation and when developing new guidelines

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

NH&MRC Nine Guiding Principles for Effective Guideline Development

A
Validity
Reproducibility
Representativeness
Flexibility
Adaptability
Cost-effectiveness
Applicability
Reliability
Usefulness
17
Q

Clinical Governance

A

“A system through which organisations are accountable for continuously improving the quality of their services and safeguarding high standards of care by creating an environment in which excellence in clinical care will flourish”

(Scally & Donaldson 1998:61 in Courtney & McCutcheon 2010:116)

18
Q

What Do Clinical Audits Measure?

A

Monitor use of interventions/care received by patients against agreed standards

Assess effectiveness: does an intervention do what it is intended to do?

Need evidence to determine if intended outcomes were achieved

Audits show success/failure of intended outcomes

Identify departure from “best practice”

19
Q

Descriptive vs Inferential Statistics

A

Descriptive statistics:
Allow researchers to describe, organise and summarise raw data

Inferential statistics:
Allow researchers to estimate how reliably they can make predictions and generalise their findings based on the data

20
Q

Results Section of Research Papers

A

Summarise findings with two major goals:

  • To describe/explain phenomenon of interest
  • To predict aspects related to that phenomenon
21
Q

Data Analysis in Qualitative Research

A

Research question always kept in mind

Data collected are formally interpreted

Data analysis is:
deliberate
considered
systematic

22
Q

Qualitative Data Analysis

A

When is it performed?

After data collection complete
Simultaneously with data collection
(Constant comparative data analysis)
Data collection & analysis “staged

Two major styles:

Fracturing, grouping, gluing (bits)

Circling and parking (whole)

23
Q

Fracturing, Grouping, Gluing

A

Most common style of qualitative analysis

Major analysis strategy is that of coding:
ie data are:

  • fractured (divided into labelled bits=codes)
  • categorised (codes are grouped into tentative categories & labelled)
  • integrated (linked/glued together)
24
Q

Circling & Parking

A

Data set treated as mass of information

Not fractured into small bits/sections

Aim: understanding overall themes

‘Circle’ data set

‘Park’ for closer scrutiny

‘Circle’, ‘Park’, ‘Circle’ etc until understanding complete

25
Other Styles of Analysing Qualitative Data
“Magnifying glass” style: data that are focus of study subjected to minute scrutiny Layering & Comparing: eg in Ethnography; data analysed in layers
26
Quantitative Descriptive Statistics
Statistical procedures: give organisation & meaning to numerical data Descriptive statistics: describe, organise, summarise raw data of Inferential Statistics: make predictions & generalise findings
27
Two important functions of descriptive statistics
Organisation of data into figures eg piecharts, histograms, scatter plots, tables, line graphs -Graphical & numerical techniques for organising & interpreting data So enable trends & differences to be noted & calculation of simple statistics Condense/reduce large quantities of numerical information into meaningful units -Can be condensed & summarised using statistics eg measures of central tendency & measures of variability
28
Statistics: | Levels of Measurement
Nominal Ordinal Interval Ratio
29
Statistics: | Ordinal Measures
Used to show relative ranking of events/objects Conveys more information than nominal data eg “Please rate the quality of nursing care received in this hospital” Very poor, poor, average, good, very good, excellent
30
Statistics: | Frequency Distribution
The most basic way of organising data ``` The number of times each event occurs is counted Often expressed as percentages (%) May be numbers of cases (N or n) N=number in the whole sample n=number in subgroup of the sample ```
31
``` Statistics: Interval Measures (Continuous) ```
Differences between scores/measures can be treated as equal There is a specific numerical distance between each of the levels No absolute zero ``` eg Temperature (°C); blood pressure (mmHg) ```
32
Statistics: | Ratio Measures
Also continuous Show ranking of events/objects with equal intervals Do have absolute zero: makes the ratio of scale values meaningful Highest level of measurement eg height, weight, distance, pulse, blood pressure
33
Statistics: | Measures of Central Tendency
Single central score- enables summarising distribution of data set Describe the centre of a distribution of scores Three measures most common: Mode Median Mean
34
Statistics: | Normal Distribution
Symmetrical & bell-shaped Mean is at the centre Most common score (mode) at the centre Middle score (median) at the centre Shows normal distribution- few values low or high- most in middle.
35
Statistics: | Skewness, Symmetry and Kurtosis
Skewness: measure of the asymmetry of the distribution of scores Can have =ve/-ve skew Symmetry: 2 halves of a distribution are mirror image of each other Kurtosis: Related to the ‘peakness’ or flatness of a distribution
36
Statistics: | Measures of Variability/Dispersion
Concerned with the spread of data Variability answers: - Is the sample homogeneous or heterogeneous? - Are the samples similar or different? Measures of variation describe extent to which individuals/scores in sample vary Most common measures are: - range - variance - standard deviation
37
Statistics: | Range
Simplest & most unstable measure of variability The difference between the highest & lowest scores Disadvantage: depends on the 2 extreme scores only (outliers) Can use difference between other scores e.g. semi-quartile range