The initial sweep of the data from the women and EHPs was through coding the data in NVivo into categories known as ‘nodes’. Larger themes were made into ‘parent nodes’ and contained within them several ‘child nodes’. Each parent node was descriptive of a significant broader category (e.g. menstrual hygiene management), whilst each child node denoted a specific topic within that theme (e.g. techniques, access to toilets, changing frequency). The node labels were determined by the topics being discussed according to the interview topic guides (e.g. drinking), and emergent issues which were identified in the data but were not anticipated prior to the data collection (e.g. accessibility and attendant issues of ageing). The labels for the nodes reflected the general topic emerging from the data (e.g. using a towel), or where data that were particularly unexpected, but of interest, were labelled with a direct phrase used by a participant in the transcripts (e.g. ‘bad spirits at night’) The first sweep of data produced 421 nodes overall (323 for women, 98 for EHPs) (see Appendix 13). The data from each node were then manually processed, to determine the number of times a particular node was referred to across the data set. For example, menstruation was coded 53 times from the interview transcripts and 8 times in the participatory maps. This figure reflects that the data were coded under the node ‘menstruation’ 53 times collectively from the 14 interview transcripts from the women, and 8 times across the 4 participatory maps. The detailed data for these nodes are presented in tables in Appendix 14.
After the coding process, attempts were made to model and visualise the findings through a cluster analysis. From the dendrograms, cluster maps, tree maps and charts produced by the cluster analysis, no obvious patterns of analysis were ascertained. It was not possible to neatly group together the data via visual representation through NVivo, because the experiences of the women and the solutions from the EHPs was too diverse. The outcomes of the analysis process for the data from the women is discussed in Chapter 5, and for the EHPs in Chapter 6.
156 3.10.2 Theoretical models
Existing theoretical models were trialled for the analysis to provide structure to the process.
Models were identified to trial for data analysis using the nodes from NVivo, through informal discussions with supervisors, with the intention to short-cut the analysis process. The models were examined, adapted and critiqued for their applicability to the study. Table 3.9 summarises the models trialled, and evaluates them:
157
Model Applicability Evaluation
DPSIR • The DPSIR is a comprised of a chain of causal links:
driving force, pressure, state, impact and response.
Perimenopause in this context is interpreted as a
“natural event” – rather than environmental impact which DPSIR conventionally assesses (Kristensen, 2004).
• Driving force: the driving force of the WASH needs of perimenopausal women is the biological changes in hormones. The perimenopause is caused by a decline in oestrogen and an increase in follicle stimulating hormone
• Pressure: Changing hormones cause pressure in the body. Pressure manifests through a range of symptoms which are typical of the perimenopause
• State: effects of the symptoms which arise as a result of particular symptoms
• Impact: Experiencing different perimenopausal symptoms leads to various different hygiene practices
• Response: Appropriate WASH service provision is needed to meet the needs of perimenopausal women, by helping women to better deal with their symptoms
• Shows how everything is linked together broadly – general overview of the research
• Provides analogy to perimenopause as a natural process – links the nature of perimenopause to the WASH response from the sector, but this is an obscure comparison
• Does not allow for consideration of wider factors which affect the WASH needs of PM women
• Need other constructs to examine women’s experiences of PM and direct uses and interactions with seek to meet their individual, personal needs, feminist concerns intersect with ecological concerns, and is based on social ecology (Nichols, 2014)
• Intersections occur across three levels:
• Facilitates exploration of subtle elements of WASH needs for PM women
• Difficult to link diverse experiences to wider context, cannot pluralise findings because it works on individual people only and not the bigger picture. Would need to
158 Micro-system level – knowledge, choices, values and
beliefs of PM women
Meso-system level – relationships of PM women with the community or at particular stages in their lives e.g.
education
Macro-system level – structures at a wider level e.g. laws or cultural beliefs
model every single individual and this would be practically challenging
• PM WASH needs are individual and private and difficult to easily map onto wider picture e.g. linking bathing to laws about water provision is obscure
PESTLE model • Looks at political, economic, social, technical, legal and environmental factors affecting the WASH needs of PM women
• More relevant to EHP perspective
• Difficult to apply to the WASH needs of PM women retrospectively, because these elements are not vivid in the narratives of women. Ideally needed to be incorporated into the theoretical framework of the research to influence the research design
SWOT model • Method to analyse strengths, weaknesses, opportunities and threats
• Better for methodological data collection evaluation, because it analyses the effectiveness of the strategy, not really for ‘evaluating’ the WASH needs of perimenopausal women
• Difficult to strengthen argument if focus is on weaknesses of data
Table 3.9: Evaluation of models trialled for analysis
159 Ultimately, models did not allow for a greater focus upon the narratives of the women in detail. The most suitable approach, which was a thematic approach, was adopted.