The possibilities of computer programs in supporting those qualitative steps of analysis are shown and the possibilities and limits of the approach are discussed. The qualitative content analysis MAYRING ; 7th edition , as it is presented here, consists in a bundle of techniques for systematic text analysis which we developed ca. Conducting about open-ended interviews we received more than The main idea of the procedure of analysis is thereby, to preserve the advantages of quantitative content analysis as developed within communication science and to transfer and further develop them to qualitative-interpretative steps of analysis.
Further information to quantitative content analysis are available via the Internet at http: The object of qualitative content analysis can be all sort of recorded communication transcripts of interviews, discourses, protocols of observations, video tapes, documents Content analysis analyzes not only the manifest content of the material—as its name may suggest.
The analysis of formal aspects of the material belongs to its aims as well. As outlined below content analysis embeds the text into a model of communication within which it defines the aims of analysis. Qualitative content analysis defines itself within this framework as an approach of empirical, methodological controlled analysis of texts within their context of communication, following content analytical rules and step by step models, without rash quantification.
We can distinguish different phases in the historical background of content analysis cf. We find different approaches to analysis and comparison of texts in hermeneutic contexts e. The basis of quantitative content analysis had been laid by Paul F. Interdisciplinary broadening and differentiation: In the sixties of 20th century the methodological approach found its way into linguistics, psychology cf.
RUST , sociology, history, arts etc. The procedures had been refined fitting into different models of communication; analysis of non-verbal aspects, contingency analysis, computer applications cf. Phase of qualitative critics: Since the middle of 20th century objections were raised against a superficial analysis without respecting latent contents and contexts, working with simplifying and distorting quantification KRACAUER If we say, qualitative content analysis wants to preserve the advantages of quantitative content analysis for a more qualitative text interpretation, so what are those advantages?
I want to emphasize four points:. Fitting the material into a model of communication: It should be determined on what part of the communication inferences shall be made, to aspects of the communicator his experiences, opinions feelings , to the situation of text production, to the socio-cultural background, to the text itself or to the effect of the message.
The material is to be analyzed step by step, following rules of procedure, devising the material into content analytical units. Categories in the center of analysis: The aspects of text interpretation, following the research questions, are putted into categories, which were carefully founded and revised within the process of analysis feedback loops. Criteria of reliability and validity: The procedure has the pretension to be inter-subjectively comprehensible, to compare he results with other studies in the sense of triangulation and to carry out checks for reliability.
For estimating the inter-coder reliability we use in qualitative content analysis in contrary to quantitative content analysis only trained members of the project team and we reduce the standard of coder agreement COHENS Kappa over. The above listed components of quantitative content analysis will be preserved to be the fundament for a qualitative oriented procedure of text interpretation. We developed a number of procedures of qualitative content analysis cf.
Classical quantitative content analysis has few answers to the question from where the categories come, how the system of categories is developed: But within the framework of qualitative approaches it would be of central interest, to develop the aspects of interpretation, the categories, as near as possible to the material, to formulate them in terms of the material. For that scope qualitative content analysis has developed procedures of inductive category development, which are oriented to the reductive processes formulated within the psychology of text processing cf.
The specific steps cannot be explained largely within this short overview. The main idea of the procedure is, to formulate a criterion of definition, derived from theoretical background and research question, which determines the aspects of the textual material taken into account. Following this criterion the material is worked through and categories are tentative and step by step deduced. Within a feedback loop those categories are revised, eventually reduced to main categories and checked in respect to their reliability.
If the research question suggests quantitative aspects e. Deductive category application works with prior formulated, theoretical derived aspects of analysis, bringing them in connection with the text. The qualitative step of analysis consists in a methodological controlled assignment of the category to a passage of text. Even if several procedures of text analysis are processing that step, it is poorly described.
Here the step model within qualitative content analysis: Then main idea here is to give explicit definitions, examples and coding rules for each deductive category, determining exactly under what circumstances a text passage can be coded with a category. Those category definitions are putted together within a coding agenda.
High subjective conviction to have successfully coped with the situational demands, which means. Everyone can make mistakes. We got it all together. All three aspects of thew definition have to point to "high" self confidence no aspect only "middle". Only partly or fluctuating conviction to have successfully coped with the situational demands. All three aspects of definition point to low self confidence, no fluctuations recognizable.
Example for a coding agenda [ 16 ]. Category definitions, prototypical text passages, and rules for distinguishing different categories were formulated in respect to theory and material, are completed step by step, and are revised with the process of analysis.
Especially within the last years several computer programs had been developed within the framework of qualitative analysis to support not to replace steps of text interpretation cf. The computer plays here a triple role:. He works as assistant, supporting and making easier the steps of text analysis on screen working through the material, underlining, writing marginal notes, defining category definitions and coding rules, recording comments on the material He offers helpful tools handling the text searching, jumping to different passages, collecting and editing passages Teddlie and Tashakkori distinguish four different stages of an investigation: According to these authors, in all four stages, mixing is possible, and thus all four stages are potential points or integration.
However, the four possible points of integration used by Teddlie and Tashakkori are still too coarse to distinguish some types of mixing. It is at the point of integration that qualitative and quantitative components are integrated. Some primary ways that the components can be connected to each other are as follows:. More generally, one can consider mixing at any or all of the following research components: One can also include mixing views of different researchers, participants, or stakeholders.
Topic: Data from Qualitative Social Research | RatSWD ‒ Rat für Sozial- und Wirtschaftsdaten
Substantively, it can be useful to think of integration or mixing as comparing and bringing together two or more components on the basis of one or more of the purposes set out in the first section of this article. In the case of development, integration consists of an adjustment of an, often quantitative, for example, instrument or model or interpretation, based on qualitative assessments by members of the target group. The power of mixed methods research is its ability to deal with diversity and divergence.
In the literature, we find two kinds of strategies for dealing with divergent results. One possibility is to carry out further research Cook ; Greene and Hall Further research is not always necessary. The aim is to develop an overall explanation that fits both the sense and the anti-sense Bazeley and Kemp ; Mendlinger and Cwikel Alternatively, one can question the existence of the encountered divergence.
Differences between results from different data sources could also be the result of properties of the methods involved, rather than reflect differences in reality Yanchar and Williams In general, the conclusions of the individual components can be subjected to an inference quality audit Teddlie and Tashakkori , in which the researcher investigates the strength of each of the divergent conclusions. As already mentioned in Sect. Note, however, that not all types of typologies are equally suitable for all purposes.
Although some of the current MM design typologies include more designs than others, none of the current typologies is fully exhaustive.
How to Construct a Mixed Methods Research Design
Various typologies of mixed methods designs have been proposed. Our summary of these designs runs as follows:. We expect that many published MM designs will fall into the hybrid design type. Morse and Niehaus listed eight mixed methods designs in their book and suggested that authors create more complex combinations when needed. Our shorthand labels and descriptions adapted from Morse and Niehaus , p. Notice that Morse and Niehaus included four mixed methods designs the first four designs shown above and four multimethod designs the second set of four designs shown above in their typology.
The reader can, therefore, see that the design notation also works quite well for multimethod research designs. In addition, they assume that the core component should always be performed either concurrent with or before the supplemental component. The resulting mixed methods design matrix see Johnson and Christensen , p. The above set of nine designs assumed only one qualitative and one quantitative component.
However, this simplistic assumption can be relaxed in practice, allowing the reader to construct more complex designs. The Morse notation system is very powerful. Something similar applies to the classification of the purposes of mixed methods research.
Of all purposes involved, then, which one should be the primary basis for the design? Or should the design be based upon all purposes included? And if so, how? Related to this, two different approaches to design can be distinguished: The most frequently mentioned interactive approach to mixed methods research is the approach by Maxwell and Loomis The researcher should therefore regularly check during the research and continuing design process whether the components still fit together, and, if not, should adapt one or the other component to restore the fit between them.
In an interactive approach, unlike the typological approach, design is viewed as an interactive process in which the components are continually compared during the research study to each other and adapted to each other. Typological and interactive approaches to mixed methods research have been presented as mutually exclusive alternatives. In our view, however, they are not mutually exclusive.
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Some authors state that design typologies are particularly useful for beginning researchers and interactive approaches are suited for experienced researchers Creswell and Plano Clark This makes an interactive approach desirable, also for beginning researchers. We agree with Greene , who states that the value of the typological approach mainly lies in the different dimensions of mixed methods that result from its classifications. In this article, the primary dimensions include purpose, theoretical drive, timing, point of integration, typological vs.
Unfortunately, all of these dimensions are not reflected in any single design typology reviewed here. Emergent designs arise, for example, when the researcher discovers during the study that one of the components is inadequate Morse and Niehaus Some designs contain an emergent component by their nature. Initiation, for example, is the further exploration of unexpected outcomes.
Unexpected outcomes are by definition not foreseen, and therefore cannot be included in the design in advance. The question arises whether researchers should plan all these decisions beforehand, or whether they can make them during, and depending on the course of, the research process. The answer to this question is twofold. On the other hand, developments during research execution will sometimes prompt the researcher to decide to add additional components.
In general, the advice is to be prepared for the unexpected. When one is able to plan for emergence, one should not refrain from doing so. Next, mixed methods designs are characterized by their complexity. In the literature, simple and complex designs are distinguished in various ways. The primary message of this section is as follows: It is the responsibility of the researcher to create more complex designs when needed to answer his or her research question s.
For example, data might be collected both at the levels of schools and students, neighborhood and households, companies and employees, communities and inhabitants, or medical practices and patients Yin Integration of these data does not only involve the integration of qualitative and quantitative data, but also the integration of data originating from different sources and existing at different levels.
This is an area in need of additional research. The fully-integrated mixed design is more complex because it contains multiple points of integration. As formulated by Teddlie and Tashakkori , p. In these designs, mixing occurs in an interactive manner at all stages of the study. At each stage, one approach affects the formulation of the other, and multiple types of implementation processes can occur.
Complexity, then, not only depends on the number of components, but also on the extent to which they depend on each other e. Many of our design dimensions ultimately refer to different ways in which the qualitative and quantitative research components are interdependent. Different purposes of mixing ultimately differ in the way one component relates to, and depends upon, the other component. The dependence among components, which may or may not be present, has been summarized by Greene Of these two design categories, integrated designs are the more complex designs.
The primary design dimensions explained above have been the focus of this article. The above design dimensions are now illustrated by examples. Summary of Roth , research regarding the gender-wage gap within Wall Street securities firms. Adapted from Hesse-Biber , pp. Gender and Money on Wall Street , tackles gender inequality in the workplace.
This example nicely illustrates the distinction we made between simultaneity and dependency. The data collection in this example was conducted simultaneously, and was thus concurrent — the quantitative closed-ended questions were embedded into the qualitative in-depth interviews. In contrast, the analysis was dependent, as explained in the next paragraph. One of the purposes of this study was explanation: The qualitative data were used to understand the processes underlying the quantitative outcomes. Conceptually, explanatory designs are often dependent: The qualitative component is used to explain and clarify the outcomes of the quantitative component.
Yet, it was complex in the sense of involving multiple levels; both the level of the individual and the organization were included. Sarah McMahon wanted to explore the subculture of college student athletes and specifically the meaning, role, and salience of rape myths within that culture.
It is sequential, because the qualitative focus groups were conducted after the survey was administered. The analysis of the quantitative and qualitative data was independent: Both were analyzed independently, to see whether they yielded the same results which they did not. This purpose, therefore, was triangulation. We doubt, however, whether this is the most appropriate label, because the qualitative component did not provide an explanation for quantitative results that were taken as given.
On the contrary, the qualitative results contradicted the quantitative results. Notice further that the second case study had the same point of integration as the first case study. The two components were brought together in the results. Thus, although the case studies are very dissimilar in many respects, this does not become visible in their point of integration.
It can therefore be helpful to determine whether their point of extension is different. Therefore, the point of extension is the research question. In the second case study, both components answered the same research question. They differed in their data collection and subsequently in their data analysis: In this case study, the point of extension was data collection.
Thus, the point of extension can be used to distinguish between the two case studies. First, we showed that there are there are many purposes for which qualitative and quantitative methods, methodologies, and paradigms can be mixed. This must be determined in interaction with the research questions. The second dimension is theoretical drive in the sense that Morse and Niehaus use this term.
This language is sometimes included in the design name to communicate this characteristic of the study design e. The third dimension is timing , which has two aspects: The fourth design dimension is the point of integration, which is where the qualitative and quantitative components are brought together and integrated. This is an essential dimension, but it usually does not need to be incorporated into the design name. The fifth design dimension is that of typological vs.
There are many typologies of designs currently in the literature. Our recommendation is that readers examine multiple design typologies to better understand the design process in mixed methods research and to understand what designs have been identified as popular in the field. The seventh design dimension is called complexity. One sort of complexity mentioned was multilevel designs, but there are many complexities that can enter designs. This is not something to avoid. It is the responsibility of the researcher to learn how to construct and describe and name mixed methods research designs.
The more one knows and thinks about the primary and secondary dimensions of mixed methods design the better equipped one will be to pursue mixed methods research. Mixed methods in early childhood education. Springer ; The multilevel mixed intact group analysis: Journal of Mixed Methods Research Research methods, design and analysis. Boston, MA with L. Turner ; Educational research: Quantitative, qualitative and mixed approaches.
Los Angeles, CA with L. Christensen ; The Oxford handbook of multimethod and mixed methods research inquiry. New York, NY with S. How is it done? National Center for Biotechnology Information , U. Kolner Z Soz Sozpsychol. Published online Jul 5. Judith Schoonenboom 1 and R.
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