Early%20Adopters%20of%20NVivo7

1
Early Adopters of NVivo7
TAGG ORAM PARTNERSHIP

• Sarah Edwards, Karen Miller, Sharon Millar - The
  Health Foundation (www.health.org.uk)
• Dr Clare Tagg - Tagg Oram Partnership(clare_at_taggo
  ram.co.uk)

2
The Problem

• Complex evaluation
• Multi-level scheme, cohort, individual
• Longitudinal
• Existing quantitative database (GIFTS)
• Team project
• 3 researchers with different approaches
• Variable experience and commitment to N6/NVivo2
  software
• Organisational pressures
• Sound analytical background
• Decision to go for NVivo7
• Size of project (ie not suitable for NVivo2)
• Complexity of documents not suitable for N6

3
Setting up the project

• Use of training/consultancy
• Software proved easy intuitive to learn
• Used 3 sessions for structuring the project - an
  outsiders view
• Project structure merging
• Each person has their own documents - based on
  tracking individuals to provide continuity
• Shared folder, node attribute structure
• Project merged to give overall picture of cohorts
  schemes
• Merge also used for importing new decisions about
  node trees etc

4
Documents

• Documents structure
• stored in folders for each scheme/cohort
• names chosen to order documents by scheme,
  cohort, individual
• Case node structure reflects cohort/scheme/individ
  ual
• Complex structure but easy to rectify mistakes
• Attributes
• Attributes applied on document import using case
  inheritance
• Difficult to apply using casebook
• Memos annotations
• Memos based on individuals
• Annotations added as researcher thoughts
• See also found to be too complex

5
Conceptual coding

• Stage 1 - autocoding based on document structure
• Structured interviews documents indicated
  auto-coding for speed
• Stage 2 - tree based on model
• Conceptual tree structure grew out of model
• Overlaps between conceptual coding auto-coding
• Stage 3 - tree and attributes based on sticky
  analysis
• Used a brainstorm to develop new conceptual tree
  value-laden attributes
• Auto-coding abandoned
• Analytic coding easy because of researcher
  experience but some software issues

6
Future

• Individual case studies
• Increased use of memoing to support individual
  case study approach
• Theory building
• Modelling
• Searching
• Relationships
• Realistic
• Time - limited time, not an academc environment
• Personal approach - can stifle creativity
• Avoid software leading to a process oriented
  approach

7
A good decision?

• Yes
• Project structure merge
• Document structure
• Niggles
• Financial cost hardware, time
• Coding needs a mouse, not straightforward
• Case nodes add complexity