3.3.2.5 Principles of research design Participatory Action Research
The methodologies employed fall under Participatory Action Research or participative methods. Fine (2008:215) states that PAR seeks to ensure ‘a democratic commitment to break the monopoly on who holds knowledge and for whom social research should be undertaken’.
88 PAR therefore has an explicit focus on collaborating with marginalised individuals who may be classed as ‘vulnerable’ (Kindon et al, 2007). Considering the lack of knowledge on the WASH needs of perimenopausal women, PAR is suited to this study because it is an approach which encourages methodologies to be adapted according to contexts, relations between researcher and participants and problems faced, thereby enabling creativity and innovation in the techniques used. Moreover, PAR provides the space to use various methodologies to generate different forms of knowledge (Kindon et al, 2007). This is done through: aiming to change social structures, social media and practices that maintain unjust, irrational and dissatisfying existence (McTaggart, 1997); addressing real life problems according to context; viewing participants as reflexive and competent in all parts of the process; creating interventions and outcomes which incorporate local values and beliefs; enriching the research process through diverse community experiences; reflect on action to create new meaning; and finally, use the extent to which the research enables community self-determination and solves problems as a measure of validity and credibility (Kindon et al, 2007). In the context of researching with perimenopausal women whose WASH needs and realities are obscured, participatory research is appropriate in enabling capacity, knowledge and skills development during the process (Kesby et al, 2005), in order to identify solutions to meet PM women’s needs.
Interdisciplinary approaches
Interdisciplinary approaches involve the ability to produce knowledge by bringing together researchers with different viewpoints and different backgrounds into a project, who can engage in all aspects of the research and share their interpretation of the findings (O’Cathain et al, 2008). This research has drawn on perspectives from feminist research, civil engineering and geography. These approaches have shaped the design of the research.
Qualitative and quantitative research
Research has traditionally been characterised by qualitative approaches and quantitative approaches. For Creswell (2014:3), ‘research approaches are plans and the procedures for research that span the steps from broad assumptions to detailed methods of data collection, analysis and interpretation’. Research approaches necessarily dictate research design.
Qualitative methods explore meanings given to human problems by particular people through data collection in participants’ settings (Creswell, 2014). An inductive approach, qualitative research principles argue that interactions between people construct social ideas, and is
89 therefore also constructivist (Robson and McCartan, 2016). Qualitative research methods are best suited to the feminist stance taken in this research. Feminist oral history interviews are characterised as a two-way non-hierarchal conversation with reciprocity and rapport building (Oakley, 1981). Women are placed at the centre of the research in consideration of the fact that their reality counts. Yet, the research explores the WASH needs of PM women which women do not discuss with others, particularly men. Qualitative approaches through interviewing for example are necessary because the topic is feminist by definition, and gender helps to build rapport into the conversation. Whilst PM women are being listened to and placed at the centre, the only way to access knowledge of their WASH needs is to have a less formal non-hierarchical conversation which eases the participant but maintains the focus on the women and not the researcher.
Quantitative approaches examine the relationship between variables, to test objective theories, by producing numerical data which can be statistically analysed (Cresswell, 2014).
An emphasis is on quantifying the data collection and analysis processes. For quantitative researchers, reality is deductive and objective (Bryman, 2016). Quantitative research design is either experimental or non-experimental, involving the use of tools such as surveys (Cresswell, 2014). Quantitative data is typically presented in number format (Denscombe, 2003). The quantitative approach has been rejected for this study due to its analytical weaknesses:
hypothesis testing means that phenomena may be missed, theories may not reflect participants’ understanding and knowledge may be too generalised (Johnson and Onwuegbuzie, 2004).
From validity and error to trustworthiness and robustness: principles of valid research design
This research is designed according to principles of social research, in that it is inspired by developments and changes in society (Bryman, 2016). In this thesis, this is an increasing population of PM women (WHO, 1996). Social research then explores these issues using ideas from the social sciences (Bryman, 2016).
This research uses a combination of traditional measures of ensuring good research design from a quantitative perspective as well as a qualitative perspective. Whilst exploring the WASH needs of PM women lends itself to a qualitative approach, the results need to be valid across all disciplines, because it is interdisciplinary; the results need to be communicated to
90 engineers who traditionally use a quantitative approach. This effective communication is key to ensuring that the WASH needs of PM women can be met, because it is engineers who will implement the practical measures required at a community level. Environmental health professionals need to know that this research is valid and robust, across all disciplines from engineers to health workers. Research is robust if it considers validity and accuracy, bias and error, rigour, credibility and trustworthiness among other elements.
Validity and accuracy
Validity and accuracy concern the reasons why people believe claims to truth. Validity is about justifying the reasons to believe claims such as descriptions, accounts, statements of fact, propositions, generalisations, interpretations, arguments, judgements or influences (Norris, 1997). Whilst threats to validity in quantitative research can be generically eliminated by including randomisation and controls, this is more challenging for qualitative research (Maxwell, 1992). Qualitative research should be scrutinised for validity because researchers are fallible, they can make mistakes and therefore the research is prone to error, no matter what the paradigm is (Norris, 1997).
Reliability and consistency
Research needs to be reliable and consistent, and the two are linked to each other. Reliability is the consistency of analytical procedures and biases which may influence the data.
Consistency is reflected when the researcher’s decisions through the process are clear and transparent through a ‘decision trail’, with clear decision points. The methodology for this study should ensure consistency and enable similar or comparable findings to be reached if the study is conducted by an independent researcher, the decision trail for which is reflected in the outcomes of the research methods (Lincoln and Guba, 1985).
Rigour
The research must be richly rigorous and robust (Tracy, 2013). This research has multiple participatory methods applied in different contexts with purposefully selected samples.
Rigour is also ensured by being able to design the research methods appropriately, triangulate the results produced from the method, ensuring transparency in the process, and having a sufficient sample to demonstrate that the findings show the wider picture. This chapter seeks to demonstrate the rigour of this research by outlining the process from beginning to the end.
91 Bias and error
This research needed to account for bias, to eliminate the risk of error in the data. Chambers (2006a) outlines six types of bias which need to be considered in this research:
• Spatial and project bias: where is the researcher visiting and not visiting? What is being seen and not seen?
• Person bias: who is being met and seen and heard?
• Seasonal bias: what are things like during other times of the year?
• Diplomatic bias: what questions are not being asked?
• Professional bias: what does the researcher notice or ask about?
• Security bias: are insecure areas being excluded?
Chambers (2017) notes that there are different sources from which error is generated, including:
• Power: to recognise and reward or to penalise and dismiss
• Interests and motivations: of individuals and institutions, benefits and disbenefits, such as through funding
• Mindsets: of personal and professional ideologies, predispositions and orientations, and how things are seen and interpreted
• Ego: esteem in which a researcher is held as a determinant of behaviour
• Misleading data: presenting misleading data without testing assumptions, including cumulative errors, propagating ‘results’ to conveniently confirm beliefs
• Extrapolating out of context: deriving simple narratives through scaling up local research
• Behaviours and experiences: embedded narratives and beliefs, selective experiences through visits, repeating narratives, stories and statistics
• Repetitive confirmation bias: searching for, favouring, recalling and repeating information to confirm researcher beliefs
92 Trustworthiness: credibility, transferability, dependability, and confirmability
This study has predominantly used a qualitative approach, which is designed under the principle of trustworthiness as a means of assessing ‘how good’ a study which uses qualitative approaches is (Lincoln and Guba, 1985). There are four criteria against which the trustworthiness of the research can be measured (Bryman, 2016):
• Credibility: how believable are the findings from the method (internal validity)? Can what is being shared be trusted as the truth?
• Transferability: can the findings be applied to other contexts (external validity)?
• Dependability: how likely are the findings to apply at other times(reliability)?
• Confirmability: to what extent have the researcher’s values intruded upon the research (objectivity)?
Triangulation
Triangulation is intended to counter all threats to validity. Threats to validity in qualitative approaches can include: inaccurate or incomplete data, imposing a framework on the data instead of deriving meaning from emerging themes or events, bias and lack of rigour, and failing to account for alternative explanations to the data found. Triangulation enhances the rigour of research (Robson and McCartan, 2016). Table 3.3 summarises different forms of triangulation:
Data triangulation The use of multiple methods to collect data Methodological triangulation Using both quantitative and qualitative data
with multiple methods
Theory triangulation Using more than one theory or perspective Observer triangulation Using multiple insider and outsider
observers
Table 3.3: Triangulation types (Denzin, 1988)
93 Sampling
Sampling is ‘an act, process or technique of selecting an appropriate sample’ (American Heritage College Dictionary, 1993: 1206). Sampling in the context of qualitative research can comprise various different factors. According to Robinson (2014: 26), a four-point approach can be taken to conduct qualitative sampling. Table 3.4 summarises the four-point approach:
Name Definition Key decisional issues
Point 1 Define a sample
Point 4 Source the sample Recruit participants from the target
Table 3.4: The four-point approach to qualitative sampling (Robinson 2014: 26)