The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 241-244).
The definition and use of the content analysis method in qualitative research varies depending on the particular type of qualitative content analysis (QCA) being conducted. The most common QCA method is utilized when it plays a supportive analytical role in combination with other qualitative methods, such as in-depth interviews (IDIs) and focus group discussions, i.e., when content analysis is being used as a secondary method. The other less common QCA method is used when the source of content is an existing, naturally occurring repository of information (such as historical documents, media content, and diaries), i.e., when content analysis is being used as a primary method.
A systematic application of QCA* as a secondary method has been conducted across a variety of disciplines. Health care researchers in particular have used content analysis in conjunction with other qualitative methods to investigate a broad range of topics. For example, Söderberg and Lundman (2001) applied the content analysis method to analyze the results from 25 unstructured IDIs conducted with women inflicted with fibromyalgia, from which they isolated five areas in these women’s lives impacted by the onset of this condition. In a similar approach, Berg and Hansson (2000) examined the lived experiences of 13 nurses working in dementia care at a psychogeriatric clinic who received clinical group supervision and individually planned nursing care. Berg and Hansson conducted unstructured, open-ended IDIs with each nurse and executed a content analysis that revealed two principal and five subordinate themes indicating supportive needs at the personal and professional level. Kyngäs (2004) studied the support network among 40 teenagers suffering from a chronic disease, such as asthma or epilepsy, by way of semi-structured IDIs. Content analysis in this instance showed six distinct social network Read Full Text
There is an article that ran in Research Design Review back in 2013 having to do with the interactions that ensue in focus group discussions. Specifically, this article addresses the idea that participants’ interactions have a significant impact on the outcomes of focus group discussions and yet this “facet of the focus group method…is largely ignored in the analysis and reporting of group research.” This article goes on to give an example of a way to think about the interaction effect in the focus group method.
Missing from this article is the question of whether – or the extent to which – interactions even exist in the discussions being analyzed. It seems self-evident that a “discussion” would involve two or more people exchanging ideas and thoughts – that is, an interaction. And yet, one of the most difficult skills to teach in focus group training is how to ignite an interactive environment where participants engage with the moderator as well as with each other. Moderators-in-training are coached on various skills and techniques to spur thoughtful discourse in face-to-face* focus groups and how to create an “engaged discussion environment,” but Read Full Text
The funnel approach to in-depth interview (IDI) and focus group guide development is an effective and efficient method for gaining key insights among qualitative research participants within an allotted time frame. A 2015 article in Research Design Review offers a schematic of this approach and outlines the intended purpose associated with each of the four basic stages (see “Interview Guide Development: A 4-Stage ‘Funnel’ Approach”).
But what exactly does “effective and efficient” mean as it relates to guide development, and why should we care? The answers lie in the fact that a thoughtful funnel approach to guide development enables the researcher to derive quality data from their qualitative research while achieving research objectives and maximizing the ultimate usefulness of the outcomes. By having a clear understanding of what it means to develop an interview or discussion guide that is both effective and efficient, the researcher has added greatly to the integrity of the qualitative research data and design.
There are at least six ways that the funnel approach to guide development is important to the effectiveness and efficiency of IDI and focus group research. The funnel approach:
- Mitigates bias. Progressively moving to the primary topic of interest allows the interviewer/moderator to gather an understanding of perceptions and behavior unblemished by the researcher’s own agenda.
- Helps identify variations. The general-to-narrow approach inherently provides the researcher with the necessary fundamental information that is needed to compare and contrast earlier comments with participants’ later remarks. In this way, the interviewer/moderator is able to identify variations in what is being said and conduct the necessary follow-up.
- Fosters rapport through a friendly flow of conversation. By beginning the interview or discussion with questions that are general in nature, the interviewer/moderator is facilitating the researcher-participant relationship in a conversational and non-threatening way.
- Reduces repetition. The flow of conversation that is grounded in a general-to-narrow method logically circumvents the potential problem of inappropriately repeating the same or similar topic areas or asking redundant questions.
- Encourages engagement and cooperation. Just as the funnel approach facilitates rapport building through conversation, it also creates an atmosphere in which participants feel emboldened to engage with the researcher and, in focus groups, with the other participants. This heightened level of cooperation fuels otherwise hidden insights which in turn help to mitigate bias and bolster data quality.
- Aids in analysis. By mitigating bias, helping to identify variations in the data, fostering rapport, reducing repetition, and encouraging engagement and cooperation, the funnel approach to guide development ultimately advances data analysis. The analyst is able to discern categories and themes, as well as outliers, in the data in a straightforward way based on well-thought-out transitions in the conversations.
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