What factors make qualitative research challenging and need consideration when undertaking it? The terms ‘analysis' and ‘interpretation' are often used interchangeably. What is the difference between them? Why do you think that ‘interpretive description' has become an increasingly popular approach to qualitative data analysis?

Question

What will be an ideal response?

Answer 1

ANSWERS Qualitative data analysis can provide challenges for the emerging researcher because: large volumes of unorganised data may be generated; analysis can be time-consuming; there may be no structured analytic processes; or there may be a number of suggestions within a particular research approach which can make it difficult to be certain about the best way to approach the analysis. The amount of data and how they are stored and managed can also provide obstacles to analysis. As well, qualitative data analysis will need to use cognitive processes such as intuition, sensory impressions and experiences (among others) to categorise the findings and discern patterns. Such skills may not be those with which the novice qualitative researcher is comfortable. While the terms ‘data analysis' and ‘data interpretation' are used interchangeably, they can be understood as two separate, although related, processes. Data analysis can be understood as the process of managing, or bringing order, to the data and reporting it in an understandable fashion. Interpretive description has become a popular approach because it provides a method for generating knowledge relevant to clinical contexts. Studies using this approach tend to be smaller in scale and focused on informing clinical understanding. They often involve relatively small samples, use a variety of data collection methods and do not require a particular methodological approach, but do draw upon aspects of many research approaches such as grounded theory and ethnography.