Final thoughts. For example, when using a descriptive question such as “Could you please tell me, how do you take care of yourself?” the researcher has to consider the aim of data collection and try to extract data for that purpose. From the perspective of trustworthiness, a key question is, “What is the relationship between prefiguration and the data collection method, that is, should the researcher use descriptive or semi-structured questions?” Nowadays, qualitative content analysis is most often applied to verbal data such as interview transcripts (Schreier, 2012). The trustworthiness of data collection can be verified by providing precise details of the sampling method and participants’ descriptions. al., 2011). Our suggestion is that one researcher is responsible for the analysis and others carefully follow-up on the whole analysis process and categorization. In this column, I will discuss the components of According to Hsieh and Shannon (2005), an important problem is failure to develop a complete understanding of the context, resulting in failure to identify the key categories. The e-mail addresses that you supply to use this service will not be used for any other purpose without your consent. For example, the aim of the study may be merely to identify concepts. utility of qualitative research. Here researchers seek to satisfy four criteria. Prior to using the method, the researcher should ask the question, “Is this method the best available to answer the target research question?” No analysis method is without drawbacks, but each may be good for a certain purpose. Holloway and Wheeler (2010) have stated that researchers often have difficulty in agreeing on how to judge the trustworthiness of their qualitative study. Content analysis per se does not include a technique to connect concepts (Elo & Kyngäs, 2008; Harwood & Garry, 2003). If you have access to a journal via a society or association membership, please browse to your society journal, select an article to view, and follow the instructions in this box. This video describes Lincoln and Guba's trustworthiness framework related to qualitative research. Information on the sample size is essential when evaluating whether the sample is appropriate. The research question specifies what to analyze and what to create (Elo & Kyngäs, 2008; Schreier, 2012). Although qualitative content analysis is commonly used in nursing science research, the trustworthiness of its use has not yet been systematically evaluated. In this phase, it is essential to consider whether the categories are well created, what the level of interpretation is, and how to check the trustworthiness of the analysis. Princeton, NJ 08543, Citation: Cohen D, Crabtree B. When using a deductive content analysis approach, the categorization matrix also needs to be pretested in a pilot phase (Schreier, 2012). Very often, these aspects can be shown in the same figure, for example, a diagram that illustrates the hierarchy of concepts or categories may also give an insight into the analysis process (see, for example, Timlin, Riala, & Kyngäs, 2013). A combined search of Medline (Ovid) and CINAHL (EBSCO) was conducted, using the following key words: trustworthiness, rigor OR validity, AND qualitative content analysis. This means that any report of research is a representation by the author. Guba and Lincoln ask the central question about the aims of any social research: “How do we know when we have specific social inquiries that are faithful enough to some human construction that we may feel safe in acting on them, or, more important, that July 2006. 24, No. She is in charge of the Teacher Education Program in Health Sciences. addressing the issue. Satu Elo, PhD, is a Senior university lecturer in University of Oulu, Institute of Health Sciences. The trustworthiness of qualitative research is frequently interrogated by positivists, perhaps because their concepts of validity and reliability cannot be addressed in the same way in naturalistic study. Outi Kanste (PhD) is a senior researcher at the National Institute for Health and Welfare in Finland. For example, the language restrictions may have influenced the findings; research studies in other languages might have added new information to our description. In qualitative content analysis, the homogeneity of the study participants or differences expected between groups are evaluated (Burmeister, 2012; Sandelowski, 1995a). The preparation phase consists of collecting suitable data for content analysis, making sense of the data, and selecting the unit of analysis. Content analysis has also been commonly used in quantitative studies to analyze answers to open-ended questions. Thus, the researcher should put a lot of thought into how to collect the most suitable data for content analysis. The authors asserted that using the same criteria for judging quantitative in addition to manifest content (Catanzaro, 1988; Robson, 1993) as it may result in over interpretation (Elo & Kyngäs, 2008). To manage the data, pre-testing of the analysis method is as important in qualitative as in quantitative research. Too narrow a meaning unit may result in fragmentation. It is recommended that the analysis be performed by more than one person to increase the comprehensivity and provide sound interpretation of the data (Burla et al., 2008; Schreier, 2012). The findings must reflect the participants’ voice and conditions of the inquiry, and not the researcher’s biases, motivations, or perspectives (Lincoln & Guba, 1985; Polit & Beck, 2012) This is one reason why authors often present representative quotations from transcribed text (Graneheim & Lundman, 2004), particularly to show a connection between the data and results. (2018). (, Emden, C., Hancock, H., Schubert, S., Darbyshire, P. (, Guthrie, J., Yongvanich, K., Ricceri, F. (, Kyngäs, H., Elo, S., Pölkki, T., Kääriäinen, M., Kanste, O. 105-117). Together, these phases should give a reader a clear indication of the overall trustworthiness of the study. According to Pyett (2003), a good qualitative researcher cannot avoid the time-consuming work of returning again and again to the data, to check whether the interpretation is true to the data and the features identified are corroborated by other interviews. The main consideration is to ensure that the structure of results is equivalent and answers the aim and research questions. Types of qualitative sampling include convenience, purposive, theoretical, selective, within-case and snowball sampling (Creswell, 2013; Higginbottom, 2004; Polit & Beck, 2012). This is useful when using deductive content analysis, which is based on a categorization matrix or coding scheme. Pre-interviews may help to determine whether the interview questions are suitable for obtaining rich data that answer the proposed research questions. For example, in one of our studies, two research team members checked the adequacy of the analysis and asked for possible complements (Kyngäs et al., 2011). In the inductive approach, the organization phase includes open coding, creating categories, and abstraction (Elo & Kyngäs, 2008). Contact us if you experience any difficulty logging in. In addition, failure to complete the analysis abstraction process may mean that concepts are presented as results that are not mutually exclusive, leading to oversimplistic conclusions (Harwood & Garry, 2003; Weber, 1990). Guba’s constructs, in particular, have won considerable favour and form the focus of this paper. A key question is, “In what detail should trustworthiness be presented in scientific articles?”—particularly as word limits often apply. Rigor of qualitative research continues to be challenged even now in the 21st century—from the very idea that qualitative research alone is open to questions, so with the terms rigor and trustworthiness. Members of _ can log in with their society credentials below, Satu Elo, Maria Kääriäinen, Outi Kanste, Tarja Pölkki, Kati Utriainen, and Helvi Kyngäs, This article is distributed under the terms of the Creative Commons Attribution 3.0 License (. Ideally, quotations should be selected that are at least connected to all main concepts and widely representative of the sample. We fully agree with van Manen (2006) that qualitative methods require sensitive interpretive skills and creative talents from the researcher. Table 1. However, high intercoder reliability (ICR) is required when more than one coder is involved in deductive data analysis (Vaismoradi et al., 2013). In many studies, content analysis has been used to analyze answers to open-ended questions in questionnaires (Kyngäs et al., 2011). Naturalistic research is concerned with phenomena as they exist in their natural settings, and qualitative research methods are perfectly suited for exploring such phenomena. This video describes Lincoln and Guba's trustworthiness framework related to qualitative research. Start studying Ch 17 Trustworthiness & Integrity in Qualitative Research. Qualitative researchers are advised to be systematic and well organized to enhance the trustworthiness of their study (Saldaña, 2011). In qualitative research, rigour is synonymous with quality and is demonstrated by evidencing the trustworthiness of the research findings to others (LINCOLN & GUBA, 1985). PhD Background: Mixed methods, two phased doctoral research study. Trustworthiness in Qualitative Research Criteria for trustworthiness in qualitative research are closely tied to the paradigmatic underpinnings of the particular discipline in which a particular investigation is conducted. (Lincoln’s name may be familiar to you from the Sage Handbook of Qualitative Research which she co-edited with Norman Denzin.) When using purposeful sampling, decisions need to be made about who or what is sampled, what form the sampling should take, and how many people or sites need to be sampled (Creswell, 2013). However, depending on the aim of the study, the collected data may be open and semi-structured. When saturation is not achieved, it is often difficult to group the data and create concepts (Elo & Kyngäs, 2008; Guthrie et al., 2004; Harwood & Garry, 2003), preventing a complete analysis and generating simplified results (Harwood & Garry, 2003; Weber, 1990). Lincoln and Guba (1985) suggest qualitative research produces 'thick description' which provides a strong foundation to make a judgement about transferability of the findings. From the perspective of establishing credibility, researchers must ensure that those participating in research are identified and described accurately. Researchers have continued to adapt and refine the criteria to ensure the quality of the data and findings. The content and structure of concepts created by content analysis should be presented in a clear and understandable way. The most commonly used method in content analysis studies is purposive sampling (Kyngäs, Elo, Pölkki, Kääriäinen, & Kanste, 2011): purposive sampling is suitable for qualitative studies where the researcher is interested in informants who have the best knowledge concerning the research topic. In trial coding, researchers independently try out the coding of the newly developed matrix (Schreier, 2012) and then discuss any apparent difficulties in using the matrix (Kyngäs et. As a research method, it represents a systematic and objective means of describing and quantifying phenomena (Downe-Wamboldt, 1992; Schreier, 2012). Maria Kääriäinen is Professor in University of Oulu, Institute of Health Sciences. Thus, scientific writing is a skill that needs to be enhanced by writing and comparing others’ analysis results. The discussion in this article helps to clarify how content analysis should be reported in a valid and understandable manner, which would be of particular benefit to reviewers of scientific articles. The purpose of trustworthiness in qualitative research is to support the argument that the inquiry’s results are “worth paying attention to”. How rigour is achieved, however, remains an elusive concept for many qualitative researchers. This may have led to improvements in the quality of reports on the process of content analysis. Criteria: Truth Value Credibility is one method… ity?” [6] Lincoln and Guba argue that ensuring credibility is one of most important factors in establishing trustworthiness [7]. . However, the reporting of results systematically can often be challenging (Kyngäs et al., 2011). Introduction Qualitative content analysis is used mostly when the researcher wants to analyze qualitative data.