Methods of data analysis

Analysis in action research is integral to reflection and future planning stages as it focuses more on identifying factors that can be used to facilitate change rather than solely interpreting findings (Hannan, 2007). Therefore, the methods of data analysis were used in accordance with this purpose by highlighting fundamental issues, expressed through the

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shared experiences of patients, that would be used later, in cycle two, as a platform for service development. The data formed the basis of a movement towards effecting change by exploring the realities of fallers. Only by providing a trustworthy and accurate account of their experiences could the data be effectively used to generate meaningful changes in cycle two.

The analysis of the data produced in this study focused on the qualitative responses given to the falls questions and the descriptive language used in the IR1 forms. The quantitative information, such as the recording of the day, time, location and degree of injury on the IR1 forms, was analysed using descriptive analysis.

Constant comparative analysis is a strategy commonly used in qualitative research as it involves comparing items of data with one another so as to develop conceptualisations of how data are related within the context in which they are experienced (Thorne, 2000). This is particularly congruent with the dialectical nature of this study in terms of exploring the sets of relationships that comprise the different realities of falls and falling. The analysis of the interviews also aimed to draw out themes shared between patients to strengthen the data to inform the basis of cycle two. However, there are other forms of data analysis used in qualitative research. A phenomenological approach seeks to discover underlying structures and the essence of experience through individual cases (Thorne, 2000). To achieve this, the analyst typically avoids cross comparisons and orientates analysis towards depth and detail. This was used when analysing the patient’s responses but not to the same degree as would be expected from a classic phenomenological study.

Ethnographic research focuses on aspects of human experience as beliefs, kinship patterns and ways of living (Thorne, 2000). Analysing data from an ethnographic tradition uses an iterative process in which the analyst typically experiences cultural behaviour with the participants themselves, detecting and interpreting thematic categories from data so as to discover inconsistencies, contradictions, and to generate conclusions regarding that experienced behaviour. This style of analysis was not appropriate for cycle one of this study as falling was a unique experience of the patients only. However, it was of more relevance for cycle two due to the collaborative nature of working with staff to facilitate changes.

One other method for analysing data that could have been used in this study, but alternative methods were chosen instead, is known as narrative analysis. This can be used to discover

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how human experience is influenced and understood through linguistic data. It attempts to analyse the meaning contained within the subjective representations of experiences as they are articulated in communication (Thorne, 2000). Rather than analysing the extent to which the patients’ stories provided insights into their experiences of falling, discourse analysis was a preferred method that is in contrast to narrative analysis by focusing more on the ways in which patients communicated their experiences so as to uncover societal influences underlying their beliefs, values and behaviours. This supported this study by examining the critical relationships between the internal, subjective realities of falling, and the external mechanisms that shaped and transformed experiences and outcomes.

The patient consultation, pilot phase and the IR1 forms all shared a common purpose - to enhance the authenticity, acceptance and trustworthiness of the main data collection phase of cycle one i.e. the development of the falls questionnaire (v.1) that evolved into the semi-structured interview questions (v.2. and v.3). The understanding of the phenomenon came from the analysis of the characteristics, regularities, meanings and reflections of the language used by the participants (Tesch, 1990). Their “voices” influenced the structure of the falls questions as well as the cyclical direction of the research (e.g. the need for a second cycle to involve members of staff to address the issues generated from cycle one).

Thematic analysis was the method used to identify, analyse and describe themes and patterns of living and/or behaviour from cycle one data (Aronson, 1994). This approach has a degree of theoretical flexibility that enables it to be a useful research tool, which can provide a detailed explanation of data (Braun and Clarke, 2006). Thematic analysis was used to group (“code”) patterns in the data relating to pre-determined themes - principally, the mechanisms, consequences and experiences of falls. Comments and reflections were added to these patterns so as to identify phrases, themes, similarities and differences, particularly between each participant. Throughout the evolving nature of the research, these consistencies in the data established a set of generalisations that were connected to the literature in the form of theories (Miles and Huberman, 1994). This was required to build a valid argument for their influence over other elements of the study (Aronson, 1994).

The second analytical approach used in this study was discourse analysis, also known as conversational analysis (Robson, 2011). It has been suggested that the study of language can lead to an understanding of social functioning (Robson, 2011); in this case, the

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phenomenon of in-patient falls. It is not only the content of the discourse, but also the intent (i.e. the styles and strategies of those creating the language) which is of significance.

The use of discourse analysis in this study was to “go beyond” the themes and opinions expressed in the semi-structured interviews and incident forms. By using both discourse and thematic analysis, the data was essentially analysed from its literal context, that is, measuring the genuine views of a participant, as well as the discursive meaning - understanding how each participant made sense of the phenomenon (Marshall, 1994). For example, the use of thematic analysis drew themes from the answers given by the patients in the interviews; discourse analysis placed these themes into a contextual understanding of the problem, so that insights could be ascertained regarding how these falls affected the patients in a deeper way than their words had initially suggested. Discourse analysis was particularly useful when the data from the IR1 forms were reviewed as staff tended not to make full use of the free-text space available on the forms. Therefore, it was initially difficult to identify themes from the IR1 data, although a more comprehensive evaluation of the language used by the staff generated a deeper understanding of the falls event.