RESEARCH IN SOCIAL CARE: GUIDELINES FOR RESEARCHERS
There are many different ways of analysing the data coming
from social care research, but a distinction is often made between qualitative
and quantitative data.
The analysis of qualitative data
- Qualitative
data analysis collates and summarises the mass of information generated by
interviews or observation
- It
involves researchers seeking relationships between different themes that
have been identified for the research and creating patterns out of the
data
- The
behaviour, experiences and attitudes of respondents may be related to
their biographical characteristics, such as age, sex, income level and so
on
- Implications
for policy or practice may be derived from the data
- Theory
may be tested or developed
- Although
methods of analysis vary greatly, the following steps are typical:
- Tape
recorded interview material is transcribed
- Anonymising of data
- Familiarisation
with the data through repeated reading
- Organising
of the data for easy examination, for example, by setting key facts or
comments out on a spread sheet or framework
- Use
of a specialist computer programme such as NVivo or NUD*IST
- Identification
of themes related to the original research question
- Development
of provisional categories
- Exploration
of relationships between categories
- Refinement
of themes and categories
- Choice
of examples to illustrate themes and categories
- Comparison
of new data with original research questions
The analysis of quantitative data
- Quantitative
data analysis collates and summarises the mass of information generated by
interviews and other forms of data collection
- In
the initial analysis the characteristics of the data may be described and
explored by using cross tabulations, creating graphs and charts, and
calculating means and standard deviations
- Further
analyses will build on these initial findings, seeking patterns and
relationships in the data by comparing means, exploring correlations, and
performing multiple regressions or analyses of variance
- Advanced
modelling techniques may be used to build sophisticated explanations of
how the data addresses the original questions
- Although
methods may vary greatly, the following steps are typical:
- Identifying
a data entry and analysis programme eg SPSS
- Coding
the data and reviewing it for completeness
- Entering
the data and checking
- Carrying
out simple exploratory analyses
- Reviewing
the results
- Performing
more sophisticated analyses as appropriate
- Development
of theory
- Comparison
of new data with original research questions
There are many sources of data already in existence which could be used to explore social and health care issues. Many of these data sets contain information from thousands of people, are based on nation-wide random samples and are processed in an extremely professional way. They thus offer data in quality and quantity which far surpasses anything which can be obtained in the average project. The two points to consider are whether a particular data set contains the information that is required and whether the researcher has the skills to manage the analysis.
Existing data sets can be obtained from the ESRC Data Archive at the University of Essex. For example:
- The English Longitudinal Survey of Ageing (ELSA) collects data about 12,000 people over 50 and about how their health, social and economic circumstances change over time
- The General Household Survey contains data from nearly 13,000 households about their use of social and health services and quality of life
- The Millennium Cohort Study collects longitudinal evidence about 19,000 children born in 2000 and about their birth and early years, their family circumstances and their physical, emotional and social development
- The National Child Development Study follows the lives of 17,000 people who were born in 1958; it contains information about health and social care, family relationships, and other topics
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