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This chapter explains how to perform inductive content analysis, a method that is commonly used in qualitative studies to analyse data. This method can be applied to open or half-structured data. Inductive content analysis utilises the process of abstraction to reduce and group data so that researchers can answer the study questions using concepts, categories or themes. After a unit of analysis has been chosen, the researcher goes through the data to identify open codes, which are then combined with other open codes that include similar content to form sub-concepts, -categories and -themes. As in the previous step, these sub-concepts, -categories and -themes are combined into concepts, categories and themes, which can still further be organised into main concepts, categories and themes. The identified concepts, categories and themes (or main concepts, categories and themes) will serve as the basis for reporting content analysis results. This type of analysis is data-sensitive; hence, the researcher should return to the original data several times during the analytical process to ensure that the results show a strong connection to the analysed data.

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Correspondence to Helvi Kyngäs .

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Kyngäs, H. (2020). Inductive Content Analysis. In: Kyngäs, H., Mikkonen, K., Kääriäinen, M. (eds) The Application of Content Analysis in Nursing Science Research. Springer, Cham.

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