This document outlines a research study exploring the lived experiences of male health visitors. It discusses the rationale for the study, which is that previous research identified a shortage of male professionals in child and family health services. The study aims to understand what it is like for men working as health visitors. It will use interpretative phenomenological analysis to interview male health visitors and analyze the themes from their perspectives. The methodology is described as is the multi-step data analysis process following an interpretative phenomenological approach. Issues of bias, rigor, and trustworthiness in the research are also addressed.

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Considerations in
Data Analysis

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Considerations in Data
Analysis
Navjot Kaur Virk
Suzanne Le Blond

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Outline of the Session
Discuss data analysis, importance, types and process briefly.
Discuss common pitfalls to avoid in data analysis
Discuss data analysis consideration with an example of current
research

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Data Analysis
Data analysis is defined as a process of cleaning, transforming
and modelling data to discover useful information for decision
making .
There are various data analysis tools which can be used to
process and manipulate data, analyse the relationship and
correlations between data sets which helps to identify patterns
and trends for interpretation.

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Importance of Analysing data
 Describe and summarise the data
 Identify relationships between
variables
 Compare and differentiate between
variables
 Forecast Outcomes

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Types of Data Analysis
Text Analysis
Statistical Analysis
Diagnostic Analysis
Predictive Analysis
Prescriptive Analysis

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Data Analysis Process
Data
Collection
Data
Cleaning
Data Analysis
Data
Interpretation
Data
Visualisation

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Books

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Data Analysis Activity (True or Myth )
Question True (T)/
Myth (M)
1. Common analysis and big words impress people
2. Analysis comes at the end after all the data is collected and collated .
3. Quantitative analysis is the most accurate type of data analysis.
4. Data have their own meaning
5. Stating limitations to the analysis weakens the evaluation.
6. Computer analysis is always easier and better .
Please select most relevant answer:

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Top Tips to avoid Data Pitfalls

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Data Analysis Process
Define your question
Set Clear
Measurement priorities
Collect Data
Analyse Data
Data Interpretation

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Common Pitfalls in Data Analysis
Sources of Bias
Errors in Methodology
Problems with Interpretation

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Sources of Bias

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Sources of Bias

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Errors in Methodology

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Errors in Methodology
• Designing Experiments with
Insufficient Statistical power
• Ignoring Measurement Error
• Performing Multiple
Comparisons

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Problems with Interpretation
• Determining the Significance of
Certain Findings
• Avoiding Confusion between
precision and accuracy .
• Unravelling the causal
relationship among variables

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Blind Men and the Elephant

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Doctor of Health and Social Care Practice (Nursing)
Suzanne Le Blond. Year 7

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The Research Study
Title of investigation:
An exploration of the lived experience of male Health Visitors: An Interpretive
phenomenological analysis.
Aim of the investigation:
The aim of the study is to explore the lived experience of being a registered
male Health Visitor.
Objectives of the investigation:
1. To explore the lived experience of the male Health Visitor.
2. To investigate why these men chose Health Visiting as a profession.
3. To consider the impact on service delivery from a male Health Visitor
perspective.

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Rationale
Previous study 2010
revealed a shortage of men
working in Child and Family
Health Care Services who
fathers could relate to.
As a Health Visitor myself I
looked at this field of
practice.
A gap in literature on men
working as Health Visitors
was noted.

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Why this methodology?
• Exploration was needed to discover what it must be like for
men working in the field of Health Visiting-inductive
• I wanted to know how it feels for them-relativist
• To gather their perspective and the meanings they give to
their experience-subjectivist + constructivist through an insider
lens
• Utilise double hermeneutics to interpret the interpretations of
the participant of the phenomenon
• Finally, to use a robust method of data analyse- Interpretative
phenomenological analysis (IPA).

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Ref: NHS Institute for innovation and improvement. Available at
http://www.institute.nhs.uk/quality_and_service_improvement_tools/quality_and_service_improvement_tools/plan_do_study_act.html
accessed Sept 29th 2015.
Act
Evaluate process & outcome
Submit paper for publication
Make recommendations
Disseminate Findings
Study
Read & reread
Analyse Data
Analyse Data
Write up
Plan
Thematic analysis of lit search to
formulate Q’s
Decide Research approach
Time scales for ethics committee
Do/Implement
Apply for ethics approval
Formulate Q’s
Invite participants
Complete semi structured
interviews (n=6)
Tape and transcribe verbatim
Pilot Study
Mirrors
the
research
process

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Main Study
Study inclusion criteria
 Be a Nursing and Midwifery
Council (NMC) Registered
Health Visitor.
 Be male
Securing the right sample
• Initial difficulties
Sample Size
• r=11 from across England
(seen here in green)

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Data analysis
Smith, Flowers and Larkin, (2009 p82-107) present a clear six stage
methodical approach to data analysis in their text allowing the
researcher to follow the Interpretative Phenomenological Analysis (IPA)
process from a step by step perspective.
• Step 1. ‘Thorough reading’ of the transcripts, over and over, to submerse oneself
in the data.
• Step 2. The ‘Initial Noting’, considering concepts, description and linguistics,
while noting in the left and right margins comments and themes respectively.
• Step 3. ‘Developing emergent themes’, by adding the transcripts and notes to
create a substantive set of data then moving toward data reduction by merging,
mapping and linking patterns through a synergistic process to create a new
totality.
• Step 4. ‘Searching for connections across emergent themes’ both similarities
and diversities, significant events, frequently used references and purposes.
• Step 5. ‘Moving to the next case’ and repeating the process to create individual
themes and new themes.
• Step 6. ‘Look for patterns across the cases’ potentially charting or mapping
graphically.

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Bias ! where is it?
• My gender bias?
• My cultural bias?
• The distribution of the participants?
• Personal contact-personality?
• Their gender bias?
• Their cultural bias?
• The themes I choose to draw out?
• The conclusions I decide to make?
• Where I choose to publish?

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Rigour, Trustworthiness and Authenticity
• Rigour is related to the quality of research -
thoroughness/accuracy
• Keeping a detailed research diary (Evolving info
technology e.g emails, folders etc)
• Sticking to the ethical parameters agreed.
• Following structured analysis
• Triangulation with insider knowledge, the pilot study
and academic theories.

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Any Questions