Data analysis

The proposed procedures for data analysis pertained to both the quantitative and the qualitative data to be collected.

5.5.1 Quantitative data description

Data from the MBSRQ would be analyzed using SPSS and it would be entered manually by the researcher. The correct process for the analysis of the MBSRQ is outlined in the User’s Manual (Cash, 1994a). This manual provides details for the scoring of each of the subscales and the computing of values on each of the subscales when using SPSS.

5.5.2 Qualitative analysis

According to Patton (2002b), qualitative data analysis transforms data into findings. Choosing an appropriate method in qualitative research, he suggested, should not be driven by laws about the significance of procedures, but should be well matched to the purpose of the research. The techniques that gave shape to findings in the present study were chosen from practices Patton associated with pattern or thematic content analysis. They included inductive practices such as (a) coding, (b) memoing and (c) data displays. These inductive practices are appropriate in identifying what Patton (p. 453) referred to as “core consistencies” in the data. He also suggested that those consistencies can be identified via a process of (d) “analytic induction” (p. 454), which can be undertaken alongside inductive practices, but brings to the data predetermined “sensitizing concepts” (p. 456).

5.5.2.1 Inductive coding

Coding and memoing are essential to the process of induction used in qualitative analyses. Punch (1998) noted that there are two main types of codes, (a) descriptive codes and (b) inferential codes. Descriptive codes have a denotative quality. They were used in the present study when seeking to become familiar with the data in the early stages of analysis. Inferential codes on the other hand, have a more interpretive quality. They would be used in summarizing the descriptive codes, and would serve to reduce large portions of the data into smaller, manageable and more abstract units of meaning.

It was anticipated that the technique of inductive coding would serve to summarize the interview data into units of meaning most efficiently. Patton (2002b) suggested that inductive coding identifies core consistencies within the data from an emic perspective. This suggests that the units of meaning that emerge have the stamp of the research participants’ expressive resources upon them. In other words, they are what he referred to as “indigenous concepts” (p. 454).

5.5.2.2 Analytic induction and the use of sensitizing concepts

According to Patton (2002b), analytic induction is a technique suitable for qualitative analysis that begins with the researcher examining the data from the point of view of theoretical propositions. He suggested also that analytic induction might take place alongside the more emergent inductive analyses generally associated with the identification of patterns or themes in qualitative data. In the present study, in accordance with the first aim and first research question, analytic induction would serve to establish a priori themes, or what Patton (2002, p. 454) referred to as “theory-derived sensitizing concepts”. Sensitizing concepts provide an external reference point in the analysis of qualitative data by providing “directions along which to look” (Patton, p. 456, citing Blumer, 1969) and provide a very immediate and salient device for the coding of data when it is important to establish the pervasiveness of a priori concepts within a particular group. The sensitizing concepts would be constructed from Schilder’s (1935/1978) core propositions concerning movement presented in Section 3.4.2 in Chapter three. They included (a) The unconscious, (b) The active process, (c) Finding the body, (d) Anticipatory plans, (e) Plasticity

and (f) Reflective emotion. These sensitizing concepts were pertinent to the understanding of the data from the point of view of Schilder’s (1935/1978) dynamic theory.

5.5.2.3 Memoing

Memoing is yet another procedure associated with the analysis of qualitative data. According to Punch (1998, p. 207), memoing takes the task of analysis “from the empirical to the conceptual”. It is identified as the note taking done by the data analyst that accompanies the coding process. In the present study, memoing would be invaluable as a means to explore substantive, metaphorical or theoretical ideas as they emerged. The advantage of memos, according to Punch, is that they have a speculative quality and thereby can highlight patterns and themes in the data during the early stages of analysis.

5.5.2.4 Data displays

Punch (1998) noted that data displays “organize, compress and assemble information” (p. 203). They are used to transform the bulky and sequential arrangement of qualitative data into a simultaneously organized, visual format. In the present study the data display will take the form of a matrix, with rows assigned to themes and columns assigned to participants’ research names. Miles and Huberman (1994) described the procedures for building data displays. It was anticipated that this technique would provide the opportunity to reduce the extensiveness of the textual data, so that the examination of convergence and divergence between participants’ contributions could be established quickly and easily.

5.5.2.5 Identifying patterns in the data

According to Patton (2002b), the identification of patterns or units of meaning in qualitative data, is organized primarily by one’s research questions. He suggested that research questions guide the analyses in such a way so as to prevent qualitative findings from becoming too abstract or

removed from the aim of the research. Miles and Huberman (1994) described practical considerations when identifying patterns in qualitative data. Their model presented the individual tasks such as inductive coding, analytic induction and memoing as part of the process of data reduction. Further, they characterized the application of these tasks as an iterative process, referred to as the interactive model. Figure 4 reproduces Miles and Huberman’s interactive model.

Figure 4. Components of data analysis: Interactive model (Miles & Huberman, p. 12).

The combination of the separate tasks applied in qualitative analysis take on an iterative character since they are applied in a concurrent, yet interwoven manner. Each stage of reduction can generate the necessity for further iterations and refinement of the patterns emerging in the data. Analysis is evaluated as being completed when the level of abstraction attained by the analysis can be formalized for discussion. In other words, when the patterns have become conspicuous. Data collection Data display Conclusions: drawing/verifying Data reduction

CHAPTER SIX