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Qualitative Content Analysis: Defined

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 231-232).

The qualitative approach to content analysis traces its roots to the mid-20th Qualitative content analysis: Definedcentury when qualitative researchers began to modify the approaches that had been used by quantitative content analysis researchers. The purpose was to enrich what qualitative researchers believed was an overly sterile approach that focused preponderantly on manifest (surface) content and largely missed the richer latent content, consequently missing much of the meaning underlying the text or other form of content being studied. The “content” in qualitative content analysis often originates from other qualitative methods (e.g., transcripts from in-depth interviews, group discussions, and ethnographic field notes). With this point in mind, qualitative content analysis researchers devised and advocated for a methodical process similar to quantitative content analysis but with a greater emphasis on subjective interpretations of the meaning in qualitative content so as to identify relevant themes and patterns (Zhang & Wildemuth, 2009; Hsieh & Shannon, 2005).

There is no shortage of definitions associated with the content analysis method. In fact, there appear to be no two definitions that are identical. Two researchers, Berg and Lune (2017), draw on several sources to define content analysis as “a careful, detailed, systematic examination and interpretation of a particular body of material in an effort to identify patterns, themes, biases, and meanings” (p. 182). Similarly, Krippendorff (2019) states that “content analysis is a research technique for making replicable and valid inferences from text (or other meaningful matter) to the contexts of their use” (p. 24). Information researchers Zhang and Wildemuth (2009) take the latent aspect one step further in their discussion of qualitative content analysis with the assertion that the aim is “to understand social reality in a subjective but scientific manner” (p. 308).

Regardless of the definition, there are six essential components to the content analysis method in qualitative research. Qualitative content analysis:

  1. Encompasses all relevant qualitative data sources, including text, images, video, audio, graphics, and symbols.
  2. Is systematic, process-driven method.
  3. Draws meaningful interpretations or inferences from the data based on both manifest and latent content.
  4. Is contextual, that is, relies on the context within which the information is extracted to give meaning to the data.
  5. Reduces a unit of qualitative data to a manageable level while maintaining the critical content.
  6. Identifies patterns and themes in the data that support or refute existing hypotheses or reveal new hypotheses.

Looking at these elements of the content analysis method, Roller and Lavrakas (2015) derive the definition of qualitative content analysis as, the systematic reduction or “condensation” (Graneheim & Lundman, 2004) of content, analyzed with special attention to the context in which it was created, to identify themes and extract meaningful interpretations of the data. Qualitative content analysis can be used as a secondary or primary method.

Graneheim, U. H., & Lundman, B. (2004). Qualitative Content Analysis in Nursing Research: Concepts, Procedures and Measures to Achieve Trustworthiness. Nurse Education Today, 24(2), 105–112. https://doi.org/10.1016/j.nedt.2003.10.001

Hsieh, H.-F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687

Krippendorff, K. (2019). Content Analysis: An Introduction to Its Methodology (4th ed.). Thousand Oaks, CA: Sage Publications.

Lune, H., & Berg, B. L. (2017). Qualitative Research Methods for the Social Sciences. Pearson.

Roller, M. R., & Lavrakas, P. J. (2015). Applied Qualitative Research Design: A Total Quality Framework Approach. New York: Guilford Press.

Zhang, Y., & Wildemuth, B. M. (2009). Qualitative Analysis of Content. In B. M. Wildemuth (Ed.), Applications of Social Research Methods to Questions in Information and Library Science (pp. 308-319). Westport, CT: Libraries Unlimited.

Ethnography: Number of Observations

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 199-201), a qualitative methods text covering in-depth interviews, focus group discussions, ethnography, qualitative content analysis, case study, and narrative research.

An important decision that ethnographic researchers need to make is the ethnographynumber of observations to conduct, or, more accurately, the number of:

  • Sites to observe.
  • People within sites to observe.
  • Observational events (e.g., how often to revisit a particular site).

Addressing this question can be complex—a process of both art and science—or fairly straightforward. In the simplest case, the number of sites to observe and observation events will be dictated by the (1) breadth and depth of the research objectives, (2) breadth and depth of the target population, and/or (3) practical realities of the research (e.g., the accessibility of the target participants, financial resources, and time available to complete the study). If, for example, the research objective is to examine the implementation of new procedures at a county free clinic, the number of sites to observe is just one (the clinic) and the frequency of observations will be determined by such factors as the fluctuation in the patient load (i.e., the slow- and high-volume hours in the clinic) and level of procedural details the observer wants to capture.

A more complex situation arises when the focus of the research is on a broad target population such as consumers. For instance, ethnographic research to study how consumers shop for vitamins would most likely require many observations of the same or different individuals within a variety of retail environments (e.g., supermarkets, drug stores, and superstores such as Read Full Text

Focus Groups: Heterogeneity vs. Homogeneity

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 107-109).

Heterogeneity

homogeneity

Fundamental to the design of a focus group study is group composition. Specifically, the researcher must determine the degree of homogeneity or heterogeneity that should be represented by the group participants. As shown below, there are many questions the researcher needs to contemplate, such as the extent of similarity or dissimilarity in participants’ demographic characteristics, as well as in their experiences and involvement with the subject matter.

Questions When Considering Heterogeneity vs. Homogeneity
A few of the questions the focus group researcher might consider when determining the desired heterogeneity or homogeneity among group participants include:

  • Should participants be in the same age range and/or stage of life?
  • Should participants be the same gender, race, and/or ethnicity?
  • Should participants be at a similar income, socio-economic, or educational level?
  • Should participants reside in the same community, be members of the same organization(s)?
  • Should participants have similar professions or jobs (including, job titles)?
  • Should participants have a similar involvement, experience, or knowledge with the research topic, e.g., the same types of problems with their 13 year old boys? the same healthcare service provider? the same purchase behavior? the same level of expertise with a new technology?

Whether or not—or the degree to which—group participants should be homogeneous in some or all characteristics has been at the center of debate for some years. On the one hand, Grønkjær, Curtis, Crespigny, and Delmar (2011) claim that at least some “homogeneity in focus group construction is considered essential for group interaction and dynamics” (p. 23)—for example, participants belonging to the same age group may have similar frames of reference and feel comfortable sharing their thoughts with people who have lived through the same experience. In the same vein, Read Full Text