Secondary & Primary Qualitative Content Analysis: Distinguishing Between the Two Methods

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 secondary vs. primary content analysisdepending 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QCA method is used when the source of content is an existing, naturally occurring repository of information (such as historical documents, media content, and diaries), i.e., when content analysis is being used as a primary method.

Secondary 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 categories for these adolescents, i.e., parents, peers, health care providers, school, technology, and pets.

Primary Method

The primary QCA method – which focuses on naturally occurring data – has also been used across a number of disciplines. These data sources are often textual in nature (i.e., written accounts of some kind, see below); however, this is not always the case. For instance, television content has been the focal point for public health researchers examining direct-to-consumer prescription drug commercials (Kaphingst, DeJong, Rudd, & Daltroy, 2004) as well as sociologists such as David Altheide (1987) who utilized content analysis to study television news coverage of the Iranian hostage crisis.  The analysis of patients’ “scribbles” from art psychotherapy sessions (Egberg-Thyme, Wiberg, Lundman, & Graneheim, 2013) as well as racism and the depiction of interracial relationships in U.S.-made films (Beeman, 2007) are other examples of using QCA as a primary method where the focus is on non-textual content.

Content analysis as a primary method to explore textual data has been used in: (a) sociological research to look at gender biases reflected in the Boy Scouts’ and Girl Scouts’ handbooks (Denny, 2011); (b) mass communication to study the portrayal of female immigrants in the Israeli media (Lemish, 2000); (c) sports marketing to investigate the social outreach programs among the four major professional leagues via a content analysis of their respective community website pages (Pharr & Lough, 2012); and (d) corporate management, including studies that analyze the content of corporate mission statements to understand “the messages communicated to organizational stakeholders” (Morris, 1994, p. 908).

Primary QCA is also used to study online content, including the examination of websites (such as Pharr & Lough, 2012, mentioned above) and the numerous ways people interact on social media. Once again, researchers in the health care industry have been particularly active using QCA to study social and other web-based phenomena.  As an example, Nordfeldt, Ängarne-Lindberg, and Berterö (2012) used the content analysis method to examine essays written by 18 diabetes health-care professionals concerning their experiences using a web portal designed for young diabetes type 1 patients and their significant others. The capabilities and use of social media, however, present qualitative researchers with new challenges.  Comments – made on blogs, networking sites, user groups, and content-sharing sites – and the use of hyperlinks are just two examples of how social media content is rarely isolated and, to the contrary, represent a highly integrated form of communication where finding themes or patterns from the multiplicity of interactions may present an extremely daunting task for the researcher. For this reason, information systems researchers such as Herring (2010) and Parker, Saundage, and Lee (2011) advocate a different, non-traditional way of thinking about the content analysis method in terms of developing units of analyses, categories, and patterns based on the realities of the interactive, linked world of online social media.

* Not unlike the steps discussed in this 2015 Research Design Review article.

Beeman, A. K. (2007). Emotional segregation: A content analysis of institutional racism in US films, 1980–2001. Ethnic and Racial Studies, 30(5), 687–712.

Berg, A., & Hansson, U. W. (2000). Dementia care nurses’ experiences of systematic clinical group supervision and supervised planned nursing care. Journal of Nursing Management, 8(6), 357–368.

Denny, K. E. (2011). Gender in context, content, and approach: Comparing gender messages in Girl Scout and Boy Scout handbooks. Gender & Society, 25(1), 27–47.

Egberg-Thyme, K., Wiberg, B., Lundman, B., & Graneheim, U. H. (2013). Qualitative content analysis in art psychotherapy research: Concepts, procedures, and measures to reveal the latent meaning in pictures and the words attached to the pictures. The Arts in Psychotherapy, 40(1), 101–107.

Herring, S. C. (2010). Web content analysis: Expanding the paradigm. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International handbook of Internet research (pp. 233–249). Dordrecht, Netherlands: Springer.

Kaphingst, K. A., DeJong, W., Rudd, R. E., & Daltroy, L. H. (2004). A content analysis of direct-to-consumer television prescription drug advertisements. Journal of Health Communication, 9(6), 515–528.

Kyngäs, H. (2004). Support network of adolescents with chronic disease: Adolescents’ perspective. Nursing and Health Sciences, 6(4), 287–293.

Lemish, D. (2000). The whore and the other: Israeli images of female immigrants from the former USSR. Gender & Society, 14(2), 333–349.

Morris, R. (1994). Computerized content analysis in management research: A demonstration of advantages & limitations. Journal of Management, 20(4), 903–931.

Nordfeldt, S., Ängarne-Lindberg, T., & Berterö, C. (2012). To use or not to use: Practitioners’ perceptions of an open web portal for young patients with diabetes. Journal of Medical Internet Research, 14(6), e154.

Parker, C., Saundage, D., & Lee, C. Y. (2011). Can qualitative content analysis be adapted for use by social informaticians to study social media discourse? A position paper. In ACIS 2011: Proceedings of the 22nd Australasian Conference on Information Systems (pp. 1–7). Sydney, Australia.

Pharr, J. R., & Lough, N. L. (2012). Differentiation of social marketing and cause-related marketing in US professional sport. Sport Marketing Quarterly, 21(2), 91–103.

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach. New York: Guilford Press.

Söderberg, S., & Lundman, B. (2001). Transitions experienced by women with fibromyalgia. Health Care for Women International, 22(7), 617–631.


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