The optional reading this week addressed two different approaches to narrative research. The process of ‘restorying’ data compiled from participants is performed by breaking down definable aspects of a narrative into themes or designated content (such as characters, plot, etc.) and then reforming the story and presenting it in text. The process sounds simple enough in theory. I believe that every one of us participates in this process every time we pass along a story heard from a friend. In these casual circumstances, we subconsciously extrapolate the components of the narrative that we find of particular interest, and then reform the “same” story by highlighting these aspects and ultimately downplaying others. Essentially, through the process of dissecting a narrative and retelling it, we have altered the composition to such an extent that it is no longer the same story we were told. The content is forever altered.
Although I believe that the same is true of formalized ‘restorying’ in the sense that the narratives are forever changed; a formalized procedure and guideline for this restructuring is of even greater significance because of the nature of the activity itself. A framework for recording, reading, analyzing, grouping and then retelling the data must be applied if there is to be any validity in this practice. Not applying a formalized technique, or choosing an incorrect approach to this form of narrative research is tantamount to verbally retelling the story of a friend days later through the filter of your subconscious selection and weakened memory.
The two processes outlined in the article present very distinct approaches to analysis. The problem-solution approach defines key elements such as setting, characters, actions, resolution, etc. As a result, this approach produces what could be considered a more traditionally structured narrative story. The three-dimensional space approach defines elements temporary by examining the past, present and future themes in the data as well as other less concrete aspects such as social elements. Obviously, such an approach will produce a substantially distinct version of the same story than the traditional version noted above.
It would have been helpful for the article to outline the types of studies that would benefits from the differing approaches. My initial feeling is that the three-dimensional approach has more to offer in terms of interpretative analysis and therefore value in producing the narrative of the content. Alternatively, the problem-solution technique involves less independent evaluation and therefore has the potential to present the data in a clearer and less-diluted form... Thoughts?
3 comments:
I'm a little uneasy about the concept of ‘restorying’ data analyses, having just read Ollerenshaw and Creswell’s article. Perhaps it's the process, or the interpretation aspect of the research itself, but I feel that restorying presents far too great a risk of skewing data for the analysis to present truly reliable results. As mentioned, this is very similar to the everyday situation in which a person hears a story from a friend and retells it in his or her own way, stressing certain aspects over others – like a game of telephone. The only problem when playing telephone (and in my opinion this applies to restorying, too) is that certain aspects are indeed stressed more than others – which results in an entertaining story, but not much substance to base an academic study on.
To respond to your questions – I too agree that the three-dimensional model to restorying has far more to offer for an interpretive analysis. I feel that overall, the three-dimensional method analysis produces a rewritten story (and subsequently an analysis) that is far less ‘inflated’ and idealistic compared to the problem-solution technique. The authors note in their concluding discussion that “unquestionably… more methodological and method discussions about narrative research need to occur” – a statement I can agree with (Ollerenshaw & Creswell, 2002, p. 345) . While I personally am not completely disinterested in narrative research, I feel that there are many contentious aspects of said practice that I (and other researchers) would undoubtedly have to hash out before jumping into any research studies. Considering that task, part of me feels that defending restorying as a solid research method that produces reliable data would be a futile effort.
After reading this article, I also had a few reservations about Ollerenshaw and Creswell’s description of the restorying process. Ollerenshaw and Creswell define restorying as “gathering stories, analyzing them for key elements of the story, and then rewriting the story to place it within a chronological sequence” (2002, pg. 332). Personally, I think “rewriting” is a poor word choice because of its negative connotations in academic research. As the original blogger mentioned, it makes it sound like the restorying process is akin to altering a story until it is unrecognizable and, as Amy noted, it brings to mind the risk of skewed data results. The restorying process’s association with “rewriting” also undermines its credibility because it invites one to draw a parallel with the everyday experiences of miscommunication (i.e. “broken telephone”).
However, when I think about the raw qualitative data set of unstructured interviews and informal conversations, narrative data analysis seems like an appropriate fit because rich data requires interpretive techniques that have a fair balance of flexibility and structure. The two interpretive analysis options of narrative research, problem solution approach and three dimensional space approach, allow the researcher to find the significant elements and patterns that are buried in the holistic-content of casual interviews and conversations through the process of restructuring the chronology and identifying the themes embedded in the data set. The formal categorization of the problem solution approach and the focus on narrative continuity in the three dimensional approach help make the implications of the research findings easier to comprehend. Being able to explain and support the “so what?” question, gives credibility to a research design. In this way, the use of people’s life experiences as a research data set gains legitimacy through the proper execution of narrative analysis approaches.
Hi there, I would like to read this article.
Could you provide the name of it? thanks a lot
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