As I have previously articulated, the aim of this study is to explore the experiential nature of serious illness from the perspective of young adults. In order to do so, I analysed transcripts of the accounts of illness that participants provided during the in-depth interviews. In accordance with phenomenological approaches to social research, the central focus of analysis is on the embodied experience of illness and, specifically, what it is like to be ill as a young adult and the issues that illness introduces. I also examined the photographs generated by participants
according to the meanings that they assigned to them in interviews, as well as what the
By analysing participants’ accounts of illness and their photographs, I seek to connect their individual experiences to broader social structures (Richardson 1997) and socio-cultural ideals regarding the life course. I now outline the specifics of my approach to data analysis.
The analysis of interviews began after the initial meeting or interview took place. This preliminary analysis involved a review of the information provided by participants by listening to the recording of the interview and reading notes made post-interview in order to identify areas in which elaboration or clarification was needed. This review helped to guide the second
interview after participants had discussed their photographs. Thus, the second interview, with those participants who took part in more than one interview (n=8), involved questions that were specific to the participant. Additionally, the second interviews allowed me to introduce topics broached by other participants in order to determine if similarities in experience existed among participants. Thus, these interviews provided important directions for my analysis of the data, as they allowed participants to draw attention to relevant aspects of their experiences via their photographs, and for myself to obtain a clearer understanding of the significance of certain issues.
Drawing upon Mason’s (2002) guidelines for qualitative data analysis, I identified themes emerging from the data both holistically and cross-sectionally. Holistic data analysis involves looking at individual cases within the data set in order to understand the “particular in context” (Ibid, p.165). Cross-sectional analysis refers to the application of a consistent set of categories to the entire set of data which allows for the identification of similarities and differences (Ibid). By drawing upon both holistic and cross-sectional approaches to data analysis, I sought to generate a comprehensive understanding of each participant’s experiences of serious illness, and also common experiences and issues that arose for participants due to illness. The photographs were
also analysed both holistically and cross-sectionally, using both their content and the meanings attributed to them by participants to determine how they were categorized thematically. Such a combination of holistic and cross-sectional analyses was successfully used by Thompson et al. (2008) in their photovoice study that explored experiences of chronic mental illness.
The majority of data analysis occurred once verbatim transcription of the interviews had been completed. Transcription was performed by me and two experienced transcriptionists, following which I compared each transcript against the interview audio-file for accuracy. Then, an initial reading of each transcript was done to generate a preliminary sense of the interview and to identify broad thematic categories. Further readings of the transcripts were then performed to refine the main themes. Once broad themes and sub-themes had been identified, the transcripts were coded using the qualitative software program, Atlas.ti. This software aided in coding and organizing the data and allowed for themes to be further refined. As stated above, a holistic analysis of each participant’s illness experience yielded themes that are reflective of their subjective experience and its context, which are presented in the participant profiles in Chapter Four. The cross-sectional analysis of the data, which forms the basis of Chapters Five, Six and the first part of Seven, highlights themes that were identified as relevant to the experiences of some or all of the participants.
The analysis process involved reading the data in three different ways: literally,
interpretively, and reflexively (Mason 2002). A literal reading of the data involves focusing on the language used by participants to discuss their illness, as well as the content of the interviews and photographs. Such a reading focuses on “what is there” (Ibid, p. 149) and provides an initial understanding of participants’ experiences. This type of reading corresponds to
knowledge and preconceptions about a social phenomenon. According to Creswell (1998), phenomenological approaches to data analysis aim to uncover the “essence” or “the central underlying meaning of the experience” by setting aside all prejudgements and instead “relying on intuition, imagination, and universal structures to obtain a picture of the experience” (Ibid, p.52). Through “bracketing”, I situated my analysis in the words and experiences of participants, rather than in pre-existing beliefs about what it would be like to be affected by a serious illness during young adulthood. While literal readings of qualitative interview data encourage
researchers to consider what exactly it is that participants are conveying about their experiences, I believe interpretive readings of such data are also useful and necessary in order to illuminate how subjective experiences are situated in broader socio-cultural contexts.
Further readings of the data allowed for interpretations to be made regarding participants’ experiences, as well as for the recognition of the role that I played in data generation. According to Mason (2002), interpretive readings provide a version of what the researcher thinks the data mean or the insights that have been gained through analysis. Interpretivist approaches contend that making interpretations about other people’s experiences is legitimate because interpretation is a fundamental aspect of social life (see for example, Schwandt 1998). However, I attempt to distinguish, where possible, between my own and participants’ interpretations in order to avoid misrepresenting participants’ understandings of their experiences as conveyed during the interviews. Next, a reflexive reading of the data seeks to reveal the role that I played in and possible influences on data generation and analysis. This type of reading involves a critical analysis of the questions that were asked, my reaction to participants, and my personal biography. For example, a gendered analysis of participants’ experiences emerges from my incorporation of a feminist perspective into my research approach, which in turn may result in
my viewing a certain situation differently from a participant who does not apply feminist thought to their everyday life.
In addition to the interview transcripts and photographs, I referred to documents and other sources of information that participants indicated they had used to learn more about their illness. The information gathered from these additional sources often provided clarification, especially of medical terminology and procedure, as well an insight into what information is available to young adults who are diagnosed with a serious illness. For example, Aurelie gave me a handbook full of invaluable information that is available through the brain tumour support group that she belongs to. Attention was also paid to participants’ signs of emotion in the data analysis, which was done by observing emotional states during interviews (e.g., laughter, sniffles, tears), and by noting variations in the dialogue (e.g., pauses, emphasis on certain words or phrases, repetition). These indicators, which were recorded either during or following the interview and in the transcription process, provided supplemental evidence of participants’ feelings regarding their experiences. By being attentive to these additional details, as well as employing Mason’s three ways of reading qualitative data, I arrived at a more comprehensive understanding and credible analysis of the data than if I had only focused on the text and its literal meaning.