example of grounded theory research paper

10 Grounded Theory Examples (Qualitative Research Method)

Grounded theory is a qualitative research method that involves the construction of theory from data rather than testing theories through data (Birks & Mills, 2015).

In other words, a grounded theory analysis doesn’t start with a hypothesis or theoretical framework, but instead generates a theory during the data analysis process .

This method has garnered a notable amount of attention since its inception in the 1960s by Barney Glaser and Anselm Strauss (Corbin & Strauss, 2015). 

Grounded Theory Definition and Overview

A central feature of grounded theory is the continuous interplay between data collection and analysis (Bringer, Johnston, & Brackenridge, 2016).

Grounded theorists start with the data, coding and considering each piece of collected information (for instance, behaviors collected during a psychological study).

As more information is collected, the researcher can reflect upon the data in an ongoing cycle where data informs an ever-growing and evolving theory (Mills, Bonner & Francis, 2017).

As such, the researcher isn’t tied to testing a hypothesis, but instead, can allow surprising and intriguing insights to emerge from the data itself.

Applications of grounded theory are widespread within the field of social sciences . The method has been utilized to provide insight into complex social phenomena such as nursing, education, and business management (Atkinson, 2015).

Grounded theory offers a sound methodology to unearth the complexities of social phenomena that aren’t well-understood in existing theories (McGhee, Marland & Atkinson, 2017).

While the methods of grounded theory can be labor-intensive and time-consuming, the rich, robust theories this approach produces make it a valuable tool in many researchers’ repertoires.

Real-Life Grounded Theory Examples

Title: A grounded theory analysis of older adults and information technology

Citation: Weatherall, J. W. A. (2000). A grounded theory analysis of older adults and information technology. Educational Gerontology , 26 (4), 371-386.

Description: This study employed a grounded theory approach to investigate older adults’ use of information technology (IT). Six participants from a senior senior were interviewed about their experiences and opinions regarding computer technology. Consistent with a grounded theory angle, there was no hypothesis to be tested. Rather, themes emerged out of the analysis process. From this, the findings revealed that the participants recognized the importance of IT in modern life, which motivated them to explore its potential. Positive attitudes towards IT were developed and reinforced through direct experience and personal ownership of technology.

Title: A taxonomy of dignity: a grounded theory study

Citation: Jacobson, N. (2009). A taxonomy of dignity: a grounded theory study. BMC International health and human rights , 9 (1), 1-9.

Description: This study aims to develop a taxonomy of dignity by letting the data create the taxonomic categories, rather than imposing the categories upon the analysis. The theory emerged from the textual and thematic analysis of 64 interviews conducted with individuals marginalized by health or social status , as well as those providing services to such populations and professionals working in health and human rights. This approach identified two main forms of dignity that emerged out of the data: “ human dignity ” and “social dignity”.

Title: A grounded theory of the development of noble youth purpose

Citation: Bronk, K. C. (2012). A grounded theory of the development of noble youth purpose. Journal of Adolescent Research , 27 (1), 78-109.

Description: This study explores the development of noble youth purpose over time using a grounded theory approach. Something notable about this study was that it returned to collect additional data two additional times, demonstrating how grounded theory can be an interactive process. The researchers conducted three waves of interviews with nine adolescents who demonstrated strong commitments to various noble purposes. The findings revealed that commitments grew slowly but steadily in response to positive feedback, with mentors and like-minded peers playing a crucial role in supporting noble purposes.

Title: A grounded theory of the flow experiences of Web users

Citation: Pace, S. (2004). A grounded theory of the flow experiences of Web users. International journal of human-computer studies , 60 (3), 327-363.

Description: This study attempted to understand the flow experiences of web users engaged in information-seeking activities, systematically gathering and analyzing data from semi-structured in-depth interviews with web users. By avoiding preconceptions and reviewing the literature only after the theory had emerged, the study aimed to develop a theory based on the data rather than testing preconceived ideas. The study identified key elements of flow experiences, such as the balance between challenges and skills, clear goals and feedback, concentration, a sense of control, a distorted sense of time, and the autotelic experience.

Title: Victimising of school bullying: a grounded theory

Citation: Thornberg, R., Halldin, K., Bolmsjö, N., & Petersson, A. (2013). Victimising of school bullying: A grounded theory. Research Papers in Education , 28 (3), 309-329.

Description: This study aimed to investigate the experiences of individuals who had been victims of school bullying and understand the effects of these experiences, using a grounded theory approach. Through iterative coding of interviews, the researchers identify themes from the data without a pre-conceived idea or hypothesis that they aim to test. The open-minded coding of the data led to the identification of a four-phase process in victimizing: initial attacks, double victimizing, bullying exit, and after-effects of bullying. The study highlighted the social processes involved in victimizing, including external victimizing through stigmatization and social exclusion, as well as internal victimizing through self-isolation, self-doubt, and lingering psychosocial issues.

Hypothetical Grounded Theory Examples

Suggested Title: “Understanding Interprofessional Collaboration in Emergency Medical Services”

Suggested Data Analysis Method: Coding and constant comparative analysis

How to Do It: This hypothetical study might begin with conducting in-depth interviews and field observations within several emergency medical teams to collect detailed narratives and behaviors. Multiple rounds of coding and categorizing would be carried out on this raw data, consistently comparing new information with existing categories. As the categories saturate, relationships among them would be identified, with these relationships forming the basis of a new theory bettering our understanding of collaboration in emergency settings. This iterative process of data collection, analysis, and theory development, continually refined based on fresh insights, upholds the essence of a grounded theory approach.

Suggested Title: “The Role of Social Media in Political Engagement Among Young Adults”

Suggested Data Analysis Method: Open, axial, and selective coding

Explanation: The study would start by collecting interaction data on various social media platforms, focusing on political discussions engaged in by young adults. Through open, axial, and selective coding, the data would be broken down, compared, and conceptualized. New insights and patterns would gradually form the basis of a theory explaining the role of social media in shaping political engagement, with continuous refinement informed by the gathered data. This process embodies the recursive essence of the grounded theory approach.

Suggested Title: “Transforming Workplace Cultures: An Exploration of Remote Work Trends”

Suggested Data Analysis Method: Constant comparative analysis

Explanation: The theoretical study could leverage survey data and in-depth interviews of employees and bosses engaging in remote work to understand the shifts in workplace culture. Coding and constant comparative analysis would enable the identification of core categories and relationships among them. Sustainability and resilience through remote ways of working would be emergent themes. This constant back-and-forth interplay between data collection, analysis, and theory formation aligns strongly with a grounded theory approach.

Suggested Title: “Persistence Amidst Challenges: A Grounded Theory Approach to Understanding Resilience in Urban Educators”

Suggested Data Analysis Method: Iterative Coding

How to Do It: This study would involve collecting data via interviews from educators in urban school systems. Through iterative coding, data would be constantly analyzed, compared, and categorized to derive meaningful theories about resilience. The researcher would constantly return to the data, refining the developing theory with every successive interaction. This procedure organically incorporates the grounded theory approach’s characteristic iterative nature.

Suggested Title: “Coping Strategies of Patients with Chronic Pain: A Grounded Theory Study”

Suggested Data Analysis Method: Line-by-line inductive coding

How to Do It: The study might initiate with in-depth interviews of patients who’ve experienced chronic pain. Line-by-line coding, followed by memoing, helps to immerse oneself in the data, utilizing a grounded theory approach to map out the relationships between categories and their properties. New rounds of interviews would supplement and refine the emergent theory further. The subsequent theory would then be a detailed, data-grounded exploration of how patients cope with chronic pain.

Grounded theory is an innovative way to gather qualitative data that can help introduce new thoughts, theories, and ideas into academic literature. While it has its strength in allowing the “data to do the talking”, it also has some key limitations – namely, often, it leads to results that have already been found in the academic literature. Studies that try to build upon current knowledge by testing new hypotheses are, in general, more laser-focused on ensuring we push current knowledge forward. Nevertheless, a grounded theory approach is very useful in many circumstances, revealing important new information that may not be generated through other approaches. So, overall, this methodology has great value for qualitative researchers, and can be extremely useful, especially when exploring specific case study projects . I also find it to synthesize well with action research projects .

Atkinson, P. (2015). Grounded theory and the constant comparative method: Valid qualitative research strategies for educators. Journal of Emerging Trends in Educational Research and Policy Studies, 6 (1), 83-86.

Birks, M., & Mills, J. (2015). Grounded theory: A practical guide . London: Sage.

Bringer, J. D., Johnston, L. H., & Brackenridge, C. H. (2016). Using computer-assisted qualitative data analysis software to develop a grounded theory project. Field Methods, 18 (3), 245-266.

Corbin, J., & Strauss, A. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory . Sage publications.

McGhee, G., Marland, G. R., & Atkinson, J. (2017). Grounded theory research: Literature reviewing and reflexivity. Journal of Advanced Nursing, 29 (3), 654-663.

Mills, J., Bonner, A., & Francis, K. (2017). Adopting a Constructivist Approach to Grounded Theory: Implications for Research Design. International Journal of Nursing Practice, 13 (2), 81-89.

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• Correspondence
• Open access
• Published: 09 September 2011

How to do a grounded theory study: a worked example of a study of dental practices

• Alexandra Sbaraini 1 , 2 ,
• Stacy M Carter 1 ,
• R Wendell Evans 2 &
• Anthony Blinkhorn 1 , 2  

BMC Medical Research Methodology volume  11 , Article number:  128 ( 2011 ) Cite this article

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Qualitative methodologies are increasingly popular in medical research. Grounded theory is the methodology most-often cited by authors of qualitative studies in medicine, but it has been suggested that many 'grounded theory' studies are not concordant with the methodology. In this paper we provide a worked example of a grounded theory project. Our aim is to provide a model for practice, to connect medical researchers with a useful methodology, and to increase the quality of 'grounded theory' research published in the medical literature.

We documented a worked example of using grounded theory methodology in practice.

We describe our sampling, data collection, data analysis and interpretation. We explain how these steps were consistent with grounded theory methodology, and show how they related to one another. Grounded theory methodology assisted us to develop a detailed model of the process of adapting preventive protocols into dental practice, and to analyse variation in this process in different dental practices.

Conclusions

By employing grounded theory methodology rigorously, medical researchers can better design and justify their methods, and produce high-quality findings that will be more useful to patients, professionals and the research community.

Peer Review reports

Qualitative research is increasingly popular in health and medicine. In recent decades, qualitative researchers in health and medicine have founded specialist journals, such as Qualitative Health Research , established 1991, and specialist conferences such as the Qualitative Health Research conference of the International Institute for Qualitative Methodology, established 1994, and the Global Congress for Qualitative Health Research, established 2011 [ 1 – 3 ]. Journals such as the British Medical Journal have published series about qualitative methodology (1995 and 2008) [ 4 , 5 ]. Bodies overseeing human research ethics, such as the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans, and the Australian National Statement on Ethical Conduct in Human Research [ 6 , 7 ], have included chapters or sections on the ethics of qualitative research. The increasing popularity of qualitative methodologies for medical research has led to an increasing awareness of formal qualitative methodologies. This is particularly so for grounded theory, one of the most-cited qualitative methodologies in medical research [[ 8 ], p47].

Grounded theory has a chequered history [ 9 ]. Many authors label their work 'grounded theory' but do not follow the basics of the methodology [ 10 , 11 ]. This may be in part because there are few practical examples of grounded theory in use in the literature. To address this problem, we will provide a brief outline of the history and diversity of grounded theory methodology, and a worked example of the methodology in practice. Our aim is to provide a model for practice, to connect medical researchers with a useful methodology, and to increase the quality of 'grounded theory' research published in the medical literature.

The history, diversity and basic components of 'grounded theory' methodology and method

Founded on the seminal 1967 book 'The Discovery of Grounded Theory' [ 12 ], the grounded theory tradition is now diverse and somewhat fractured, existing in four main types, with a fifth emerging. Types one and two are the work of the original authors: Barney Glaser's 'Classic Grounded Theory' [ 13 ] and Anselm Strauss and Juliet Corbin's 'Basics of Qualitative Research' [ 14 ]. Types three and four are Kathy Charmaz's 'Constructivist Grounded Theory' [ 15 ] and Adele Clarke's postmodern Situational Analysis [ 16 ]: Charmaz and Clarke were both students of Anselm Strauss. The fifth, emerging variant is 'Dimensional Analysis' [ 17 ] which is being developed from the work of Leonard Schaztman, who was a colleague of Strauss and Glaser in the 1960s and 1970s.

There has been some discussion in the literature about what characteristics a grounded theory study must have to be legitimately referred to as 'grounded theory' [ 18 ]. The fundamental components of a grounded theory study are set out in Table 1 . These components may appear in different combinations in other qualitative studies; a grounded theory study should have all of these. As noted, there are few examples of 'how to do' grounded theory in the literature [ 18 , 19 ]. Those that do exist have focused on Strauss and Corbin's methods [ 20 – 25 ]. An exception is Charmaz's own description of her study of chronic illness [ 26 ]; we applied this same variant in our study. In the remainder of this paper, we will show how each of the characteristics of grounded theory methodology worked in our study of dental practices.

Study background

We used grounded theory methodology to investigate social processes in private dental practices in New South Wales (NSW), Australia. This grounded theory study builds on a previous Australian Randomized Controlled Trial (RCT) called the Monitor Dental Practice Program (MPP) [ 27 ]. We know that preventive techniques can arrest early tooth decay and thus reduce the need for fillings [ 28 – 32 ]. Unfortunately, most dentists worldwide who encounter early tooth decay continue to drill it out and fill the tooth [ 33 – 37 ]. The MPP tested whether dentists could increase their use of preventive techniques. In the intervention arm, dentists were provided with a set of evidence-based preventive protocols to apply [ 38 ]; control practices provided usual care. The MPP protocols used in the RCT guided dentists to systematically apply preventive techniques to prevent new tooth decay and to arrest early stages of tooth decay in their patients, therefore reducing the need for drilling and filling. The protocols focused on (1) primary prevention of new tooth decay (tooth brushing with high concentration fluoride toothpaste and dietary advice) and (2) intensive secondary prevention through professional treatment to arrest tooth decay progress (application of fluoride varnish, supervised monitoring of dental plaque control and clinical outcomes)[ 38 ].

As the RCT unfolded, it was discovered that practices in the intervention arm were not implementing the preventive protocols uniformly. Why had the outcomes of these systematically implemented protocols been so different? This question was the starting point for our grounded theory study. We aimed to understand how the protocols had been implemented, including the conditions and consequences of variation in the process. We hoped that such understanding would help us to see how the norms of Australian private dental practice as regards to tooth decay could be moved away from drilling and filling and towards evidence-based preventive care.

Designing this grounded theory study

Figure 1 illustrates the steps taken during the project that will be described below from points A to F.

Study design . file containing a figure illustrating the study design.

A. An open beginning and research questions

Grounded theory studies are generally focused on social processes or actions: they ask about what happens and how people interact . This shows the influence of symbolic interactionism, a social psychological approach focused on the meaning of human actions [ 39 ]. Grounded theory studies begin with open questions, and researchers presume that they may know little about the meanings that drive the actions of their participants. Accordingly, we sought to learn from participants how the MPP process worked and how they made sense of it. We wanted to answer a practical social problem: how do dentists persist in drilling and filling early stages of tooth decay, when they could be applying preventive care?

We asked research questions that were open, and focused on social processes. Our initial research questions were:

What was the process of implementing (or not-implementing) the protocols (from the perspective of dentists, practice staff, and patients)?

How did this process vary?

B. Ethics approval and ethical issues

In our experience, medical researchers are often concerned about the ethics oversight process for such a flexible, unpredictable study design. We managed this process as follows. Initial ethics approval was obtained from the Human Research Ethics Committee at the University of Sydney. In our application, we explained grounded theory procedures, in particular the fact that they evolve. In our initial application we provided a long list of possible recruitment strategies and interview questions, as suggested by Charmaz [ 15 ]. We indicated that we would make future applications to modify our protocols. We did this as the study progressed - detailed below. Each time we reminded the committee that our study design was intended to evolve with ongoing modifications. Each modification was approved without difficulty. As in any ethical study, we ensured that participation was voluntary, that participants could withdraw at any time, and that confidentiality was protected. All responses were anonymised before analysis, and we took particular care not to reveal potentially identifying details of places, practices or clinicians.

C. Initial, Purposive Sampling (before theoretical sampling was possible)

Grounded theory studies are characterised by theoretical sampling, but this requires some data to be collected and analysed. Sampling must thus begin purposively, as in any qualitative study. Participants in the previous MPP study provided our population [ 27 ]. The MPP included 22 private dental practices in NSW, randomly allocated to either the intervention or control group. With permission of the ethics committee; we sent letters to the participants in the MPP, inviting them to participate in a further qualitative study. From those who agreed, we used the quantitative data from the MPP to select an initial sample.

Then, we selected the practice in which the most dramatic results had been achieved in the MPP study (Dental Practice 1). This was a purposive sampling strategy, to give us the best possible access to the process of successfully implementing the protocols. We interviewed all consenting staff who had been involved in the MPP (one dentist, five dental assistants). We then recruited 12 patients who had been enrolled in the MPP, based on their clinically measured risk of developing tooth decay: we selected some patients whose risk status had gotten better, some whose risk had worsened and some whose risk had stayed the same. This purposive sample was designed to provide maximum variation in patients' adoption of preventive dental care.

Initial Interviews

One hour in-depth interviews were conducted. The researcher/interviewer (AS) travelled to a rural town in NSW where interviews took place. The initial 18 participants (one dentist, five dental assistants and 12 patients) from Dental Practice 1 were interviewed in places convenient to them such as the dental practice, community centres or the participant's home.

Two initial interview schedules were designed for each group of participants: 1) dentists and dental practice staff and 2) dental patients. Interviews were semi-structured and based loosely on the research questions. The initial questions for dentists and practice staff are in Additional file 1 . Interviews were digitally recorded and professionally transcribed. The research location was remote from the researcher's office, thus data collection was divided into two episodes to allow for intermittent data analysis. Dentist and practice staff interviews were done in one week. The researcher wrote memos throughout this week. The researcher then took a month for data analysis in which coding and memo-writing occurred. Then during a return visit, patient interviews were completed, again with memo-writing during the data-collection period.

D. Data Analysis

Coding and the constant comparative method.

Coding is essential to the development of a grounded theory [ 15 ]. According to Charmaz [[ 15 ], p46], 'coding is the pivotal link between collecting data and developing an emergent theory to explain these data. Through coding, you define what is happening in the data and begin to grapple with what it means'. Coding occurs in stages. In initial coding, the researcher generates as many ideas as possible inductively from early data. In focused coding, the researcher pursues a selected set of central codes throughout the entire dataset and the study. This requires decisions about which initial codes are most prevalent or important, and which contribute most to the analysis. In theoretical coding, the researcher refines the final categories in their theory and relates them to one another. Charmaz's method, like Glaser's method [ 13 ], captures actions or processes by using gerunds as codes (verbs ending in 'ing'); Charmaz also emphasises coding quickly, and keeping the codes as similar to the data as possible.

We developed our coding systems individually and through team meetings and discussions.

We have provided a worked example of coding in Table 2 . Gerunds emphasise actions and processes. Initial coding identifies many different processes. After the first few interviews, we had a large amount of data and many initial codes. This included a group of codes that captured how dentists sought out evidence when they were exposed to a complex clinical case, a new product or technique. Because this process seemed central to their practice, and because it was talked about often, we decided that seeking out evidence should become a focused code. By comparing codes against codes and data against data, we distinguished the category of "seeking out evidence" from other focused codes, such as "gathering and comparing peers' evidence to reach a conclusion", and we understood the relationships between them. Using this constant comparative method (see Table 1 ), we produced a theoretical code: "making sense of evidence and constructing knowledge". This code captured the social process that dentists went through when faced with new information or a practice challenge. This theoretical code will be the focus of a future paper.

Memo-writing

Throughout the study, we wrote extensive case-based memos and conceptual memos. After each interview, the interviewer/researcher (AS) wrote a case-based memo reflecting on what she learned from that interview. They contained the interviewer's impressions about the participants' experiences, and the interviewer's reactions; they were also used to systematically question some of our pre-existing ideas in relation to what had been said in the interview. Table 3 illustrates one of those memos. After a few interviews, the interviewer/researcher also began making and recording comparisons among these memos.

We also wrote conceptual memos about the initial codes and focused codes being developed, as described by Charmaz [ 15 ]. We used these memos to record our thinking about the meaning of codes and to record our thinking about how and when processes occurred, how they changed, and what their consequences were. In these memos, we made comparisons between data, cases and codes in order to find similarities and differences, and raised questions to be answered in continuing interviews. Table 4 illustrates a conceptual memo.

At the end of our data collection and analysis from Dental Practice 1, we had developed a tentative model of the process of implementing the protocols, from the perspective of dentists, dental practice staff and patients. This was expressed in both diagrams and memos, was built around a core set of focused codes, and illustrated relationships between them.

E. Theoretical sampling, ongoing data analysis and alteration of interview route

We have already described our initial purposive sampling. After our initial data collection and analysis, we used theoretical sampling (see Table 1 ) to determine who to sample next and what questions to ask during interviews. We submitted Ethics Modification applications for changes in our question routes, and had no difficulty with approval. We will describe how the interview questions for dentists and dental practice staff evolved, and how we selected new participants to allow development of our substantive theory. The patients' interview schedule and theoretical sampling followed similar procedures.

Evolution of theoretical sampling and interview questions

We now had a detailed provisional model of the successful process implemented in Dental Practice 1. Important core focused codes were identified, including practical/financial, historical and philosophical dimensions of the process. However, we did not yet understand how the process might vary or go wrong, as implementation in the first practice we studied had been described as seamless and beneficial for everyone. Because our aim was to understand the process of implementing the protocols, including the conditions and consequences of variation in the process, we needed to understand how implementation might fail. For this reason, we theoretically sampled participants from Dental Practice 2, where uptake of the MPP protocols had been very limited according to data from the RCT trial.

We also changed our interview questions based on the analysis we had already done (see Additional file 2 ). In our analysis of data from Dental Practice 1, we had learned that "effectiveness" of treatments and "evidence" both had a range of meanings. We also learned that new technologies - in particular digital x-rays and intra-oral cameras - had been unexpectedly important to the process of implementing the protocols. For this reason, we added new questions for the interviews in Dental Practice 2 to directly investigate "effectiveness", "evidence" and how dentists took up new technologies in their practice.

Then, in Dental Practice 2 we learned more about the barriers dentists and practice staff encountered during the process of implementing the MPP protocols. We confirmed and enriched our understanding of dentists' processes for adopting technology and producing knowledge, dealing with complex cases and we further clarified the concept of evidence. However there was a new, important, unexpected finding in Dental Practice 2. Dentists talked about "unreliable" patients - that is, patients who were too unreliable to have preventive dental care offered to them. This seemed to be a potentially important explanation for non-implementation of the protocols. We modified our interview schedule again to include questions about this concept (see Additional file 3 ) leading to another round of ethics approvals. We also returned to Practice 1 to ask participants about the idea of an "unreliable" patient.

Dentists' construction of the "unreliable" patient during interviews also prompted us to theoretically sample for "unreliable" and "reliable" patients in the following round of patients' interviews. The patient question route was also modified by the analysis of the dentists' and practice staff data. We wanted to compare dentists' perspectives with the perspectives of the patients themselves. Dentists were asked to select "reliable" and "unreliable" patients to be interviewed. Patients were asked questions about what kind of services dentists should provide and what patients valued when coming to the dentist. We found that these patients (10 reliable and 7 unreliable) talked in very similar ways about dental care. This finding suggested to us that some deeply-held assumptions within the dental profession may not be shared by dental patients.

At this point, we decided to theoretically sample dental practices from the non-intervention arm of the MPP study. This is an example of the 'openness' of a grounded theory study potentially subtly shifting the focus of the study. Our analysis had shifted our focus: rather than simply studying the process of implementing the evidence-based preventive protocols, we were studying the process of doing prevention in private dental practice. All participants seemed to be revealing deeply held perspectives shared in the dental profession, whether or not they were providing dental care as outlined in the MPP protocols. So, by sampling dentists from both intervention and control group from the previous MPP study, we aimed to confirm or disconfirm the broader reach of our emerging theory and to complete inductive development of key concepts. Theoretical sampling added 12 face to face interviews and 10 telephone interviews to the data. A total of 40 participants between the ages of 18 and 65 were recruited. Telephone interviews were of comparable length, content and quality to face to face interviews, as reported elsewhere in the literature [ 40 ].

F. Mapping concepts, theoretical memo writing and further refining of concepts

After theoretical sampling, we could begin coding theoretically. We fleshed out each major focused code, examining the situations in which they appeared, when they changed and the relationship among them. At time of writing, we have reached theoretical saturation (see Table 1 ). We have been able to determine this in several ways. As we have become increasingly certain about our central focused codes, we have re-examined the data to find all available insights regarding those codes. We have drawn diagrams and written memos. We have looked rigorously for events or accounts not explained by the emerging theory so as to develop it further to explain all of the data. Our theory, which is expressed as a set of concepts that are related to one another in a cohesive way, now accounts adequately for all the data we have collected. We have presented the developing theory to specialist dental audiences and to the participants, and have found that it was accepted by and resonated with these audiences.

We have used these procedures to construct a detailed, multi-faceted model of the process of incorporating prevention into private general dental practice. This model includes relationships among concepts, consequences of the process, and variations in the process. A concrete example of one of our final key concepts is the process of "adapting to" prevention. More commonly in the literature writers speak of adopting, implementing or translating evidence-based preventive protocols into practice. Through our analysis, we concluded that what was required was 'adapting to' those protocols in practice. Some dental practices underwent a slow process of adapting evidence-based guidance to their existing practice logistics. Successful adaptation was contingent upon whether (1) the dentist-in-charge brought the whole dental team together - including other dentists - and got everyone interested and actively participating during preventive activities; (2) whether the physical environment of the practice was re-organised around preventive activities, (3) whether the dental team was able to devise new and efficient routines to accommodate preventive activities, and (4) whether the fee schedule was amended to cover the delivery of preventive services, which hitherto was considered as "unproductive time".

Adaptation occurred over time and involved practical, historical and philosophical aspects of dental care. Participants transitioned from their initial state - selling restorative care - through an intermediary stage - learning by doing and educating patients about the importance of preventive care - and finally to a stage where they were offering patients more than just restorative care. These are examples of ways in which participants did not simply adopt protocols in a simple way, but needed to adapt the protocols and their own routines as they moved toward more preventive practice.

The quality of this grounded theory study

There are a number of important assurances of quality in keeping with grounded theory procedures and general principles of qualitative research. The following points describe what was crucial for this study to achieve quality.

During data collection

1. All interviews were digitally recorded, professionally transcribed in detail and the transcripts checked against the recordings.

2. We analysed the interview transcripts as soon as possible after each round of interviews in each dental practice sampled as shown on Figure 1 . This allowed the process of theoretical sampling to occur.

3. Writing case-based memos right after each interview while being in the field allowed the researcher/interviewer to capture initial ideas and make comparisons between participants' accounts. These memos assisted the researcher to make comparison among her reflections, which enriched data analysis and guided further data collection.

4. Having the opportunity to contact participants after interviews to clarify concepts and to interview some participants more than once contributed to the refinement of theoretical concepts, thus forming part of theoretical sampling.

5. The decision to include phone interviews due to participants' preference worked very well in this study. Phone interviews had similar length and depth compared to the face to face interviews, but allowed for a greater range of participation.

During data analysis

1. Detailed analysis records were kept; which made it possible to write this explanatory paper.

2. The use of the constant comparative method enabled the analysis to produce not just a description but a model, in which more abstract concepts were related and a social process was explained.

3. All researchers supported analysis activities; a regular meeting of the research team was convened to discuss and contextualize emerging interpretations, introducing a wide range of disciplinary perspectives.

Answering our research questions

We developed a detailed model of the process of adapting preventive protocols into dental practice, and analysed the variation in this process in different dental practices. Transferring evidence-based preventive protocols into these dental practices entailed a slow process of adapting the evidence to the existing practices logistics. Important practical, philosophical and historical elements as well as barriers and facilitators were present during a complex adaptation process. Time was needed to allow dentists and practice staff to go through this process of slowly adapting their practices to this new way of working. Patients also needed time to incorporate home care activities and more frequent visits to dentists into their daily routines. Despite being able to adapt or not, all dentists trusted the concrete clinical evidence that they have produced, that is, seeing results in their patients mouths made them believe in a specific treatment approach.

Concluding remarks

This paper provides a detailed explanation of how a study evolved using grounded theory methodology (GTM), one of the most commonly used methodologies in qualitative health and medical research [[ 8 ], p47]. In 2007, Bryant and Charmaz argued:

'Use of GTM, at least as much as any other research method, only develops with experience. Hence the failure of all those attempts to provide clear, mechanistic rules for GTM: there is no 'GTM for dummies'. GTM is based around heuristics and guidelines rather than rules and prescriptions. Moreover, researchers need to be familiar with GTM, in all its major forms, in order to be able to understand how they might adapt it in use or revise it into new forms and variations.' [[ 8 ], p17].

Our detailed explanation of our experience in this grounded theory study is intended to provide, vicariously, the kind of 'experience' that might help other qualitative researchers in medicine and health to apply and benefit from grounded theory methodology in their studies. We hope that our explanation will assist others to avoid using grounded theory as an 'approving bumper sticker' [ 10 ], and instead use it as a resource that can greatly improve the quality and outcome of a qualitative study.

Abbreviations

grounded theory methods

Monitor Dental Practice Program

New South Wales

Randomized Controlled Trial.

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Acknowledgements

We thank dentists, dental practice staff and patients for their invaluable contributions to the study. We thank Emeritus Professor Miles Little for his time and wise comments during the project.

The authors received financial support for the research from the following funding agencies: University of Sydney Postgraduate Award 2009; The Oral Health Foundation, University of Sydney; Dental Board New South Wales; Australian Dental Research Foundation; National Health and Medical Research Council Project Grant 632715.

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All authors have made substantial contributions to conception and design of this study. AS carried out data collection, analysis, and interpretation of data. SMC made substantial contribution during data collection, analysis and data interpretation. AS, SMC, RWE, and AB have been involved in drafting the manuscript and revising it critically for important intellectual content. All authors read and approved the final manuscript.

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Sbaraini, A., Carter, S.M., Evans, R.W. et al. How to do a grounded theory study: a worked example of a study of dental practices. BMC Med Res Methodol 11 , 128 (2011). https://doi.org/10.1186/1471-2288-11-128

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Home » Grounded Theory – Methods, Examples and Guide

Grounded Theory – Methods, Examples and Guide

Table of Contents

Grounded Theory

Definition:

Grounded Theory is a qualitative research methodology that aims to generate theories based on data that are grounded in the empirical reality of the research context. The method involves a systematic process of data collection, coding, categorization, and analysis to identify patterns and relationships in the data.

The ultimate goal is to develop a theory that explains the phenomenon being studied, which is based on the data collected and analyzed rather than on preconceived notions or hypotheses. The resulting theory should be able to explain the phenomenon in a way that is consistent with the data and also accounts for variations and discrepancies in the data. Grounded Theory is widely used in sociology, psychology, management, and other social sciences to study a wide range of phenomena, such as organizational behavior, social interaction, and health care.

History of Grounded Theory

Grounded Theory was first introduced by sociologists Barney Glaser and Anselm Strauss in the 1960s as a response to the limitations of traditional positivist approaches to social research. The approach was initially developed to study dying patients and their families in hospitals, but it was soon applied to other areas of sociology and beyond.

Glaser and Strauss published their seminal book “The Discovery of Grounded Theory” in 1967, in which they presented their approach to developing theory from empirical data. They argued that existing social theories often did not account for the complexity and diversity of social phenomena, and that the development of theory should be grounded in empirical data.

Since then, Grounded Theory has become a widely used methodology in the social sciences, and has been applied to a wide range of topics, including healthcare, education, business, and psychology. The approach has also evolved over time, with variations such as constructivist grounded theory and feminist grounded theory being developed to address specific criticisms and limitations of the original approach.

Types of Grounded Theory

There are two main types of Grounded Theory: Classic Grounded Theory and Constructivist Grounded Theory.

Classic Grounded Theory

This approach is based on the work of Glaser and Strauss, and emphasizes the discovery of a theory that is grounded in data. The focus is on generating a theory that explains the phenomenon being studied, without being influenced by preconceived notions or existing theories. The process involves a continuous cycle of data collection, coding, and analysis, with the aim of developing categories and subcategories that are grounded in the data. The categories and subcategories are then compared and synthesized to generate a theory that explains the phenomenon.

Constructivist Grounded Theory

This approach is based on the work of Charmaz, and emphasizes the role of the researcher in the process of theory development. The focus is on understanding how individuals construct meaning and interpret their experiences, rather than on discovering an objective truth. The process involves a reflexive and iterative approach to data collection, coding, and analysis, with the aim of developing categories that are grounded in the data and the researcher’s interpretations of the data. The categories are then compared and synthesized to generate a theory that accounts for the multiple perspectives and interpretations of the phenomenon being studied.

Grounded Theory Conducting Guide

Here are some general guidelines for conducting a Grounded Theory study:

• Choose a research question: Start by selecting a research question that is open-ended and focuses on a specific social phenomenon or problem.
• Select participants and collect data: Identify a diverse group of participants who have experienced the phenomenon being studied. Use a variety of data collection methods such as interviews, observations, and document analysis to collect rich and diverse data.
• Analyze the data: Begin the process of analyzing the data using constant comparison. This involves comparing the data to each other and to existing categories and codes, in order to identify patterns and relationships. Use open coding to identify concepts and categories, and then use axial coding to organize them into a theoretical framework.
• Generate categories and codes: Generate categories and codes that describe the phenomenon being studied. Make sure that they are grounded in the data and that they accurately reflect the experiences of the participants.
• Refine and develop the theory: Use theoretical sampling to identify new data sources that are relevant to the developing theory. Use memoing to reflect on insights and ideas that emerge during the analysis process. Continue to refine and develop the theory until it provides a comprehensive explanation of the phenomenon.
• Validate the theory: Finally, seek to validate the theory by testing it against new data and seeking feedback from peers and other researchers. This process helps to refine and improve the theory, and to ensure that it is grounded in the data.
• Write up and disseminate the findings: Once the theory is fully developed and validated, write up the findings and disseminate them through academic publications and presentations. Make sure to acknowledge the contributions of the participants and to provide a detailed account of the research methods used.

Data Collection Methods

Grounded Theory Data Collection Methods are as follows:

• Interviews : One of the most common data collection methods in Grounded Theory is the use of in-depth interviews. Interviews allow researchers to gather rich and detailed data about the experiences, perspectives, and attitudes of participants. Interviews can be conducted one-on-one or in a group setting.
• Observation : Observation is another data collection method used in Grounded Theory. Researchers may observe participants in their natural settings, such as in a workplace or community setting. This method can provide insights into the social interactions and behaviors of participants.
• Document analysis: Grounded Theory researchers also use document analysis as a data collection method. This involves analyzing existing documents such as reports, policies, or historical records that are relevant to the phenomenon being studied.
• Focus groups : Focus groups involve bringing together a group of participants to discuss a specific topic or issue. This method can provide insights into group dynamics and social interactions.
• Fieldwork : Fieldwork involves immersing oneself in the research setting and participating in the activities of the participants. This method can provide an in-depth understanding of the culture and social dynamics of the research setting.
• Multimedia data: Grounded Theory researchers may also use multimedia data such as photographs, videos, or audio recordings to capture the experiences and perspectives of participants.

Data Analysis Methods

Grounded Theory Data Analysis Methods are as follows:

• Open coding: Open coding is the process of identifying concepts and categories in the data. Researchers use open coding to assign codes to different pieces of data, and to identify similarities and differences between them.
• Axial coding: Axial coding is the process of organizing the codes into broader categories and subcategories. Researchers use axial coding to develop a theoretical framework that explains the phenomenon being studied.
• Constant comparison: Grounded Theory involves a process of constant comparison, in which data is compared to each other and to existing categories and codes in order to identify patterns and relationships.
• Theoretical sampling: Theoretical sampling involves selecting new data sources based on the emerging theory. Researchers use theoretical sampling to collect data that will help refine and validate the theory.
• Memoing : Memoing involves writing down reflections, insights, and ideas as the analysis progresses. This helps researchers to organize their thoughts and develop a deeper understanding of the data.
• Peer debriefing: Peer debriefing involves seeking feedback from peers and other researchers on the developing theory. This process helps to validate the theory and ensure that it is grounded in the data.
• Member checking: Member checking involves sharing the emerging theory with the participants in the study and seeking their feedback. This process helps to ensure that the theory accurately reflects the experiences and perspectives of the participants.
• Triangulation: Triangulation involves using multiple sources of data to validate the emerging theory. Researchers may use different data collection methods, different data sources, or different analysts to ensure that the theory is grounded in the data.

Applications of Grounded Theory

Here are some of the key applications of Grounded Theory:

• Social sciences : Grounded Theory is widely used in social science research, particularly in fields such as sociology, psychology, and anthropology. It can be used to explore a wide range of social phenomena, such as social interactions, power dynamics, and cultural practices.
• Healthcare : Grounded Theory can be used in healthcare research to explore patient experiences, healthcare practices, and healthcare systems. It can provide insights into the factors that influence healthcare outcomes, and can inform the development of interventions and policies.
• Education : Grounded Theory can be used in education research to explore teaching and learning processes, student experiences, and educational policies. It can provide insights into the factors that influence educational outcomes, and can inform the development of educational interventions and policies.
• Business : Grounded Theory can be used in business research to explore organizational processes, management practices, and consumer behavior. It can provide insights into the factors that influence business outcomes, and can inform the development of business strategies and policies.
• Technology : Grounded Theory can be used in technology research to explore user experiences, technology adoption, and technology design. It can provide insights into the factors that influence technology outcomes, and can inform the development of technology interventions and policies.

Examples of Grounded Theory

Examples of Grounded Theory in different case studies are as follows:

• Glaser and Strauss (1965): This study, which is considered one of the foundational works of Grounded Theory, explored the experiences of dying patients in a hospital. The researchers used Grounded Theory to develop a theoretical framework that explained the social processes of dying, and that was grounded in the data.
• Charmaz (1983): This study explored the experiences of chronic illness among young adults. The researcher used Grounded Theory to develop a theoretical framework that explained how individuals with chronic illness managed their illness, and how their illness impacted their sense of self.
• Strauss and Corbin (1990): This study explored the experiences of individuals with chronic pain. The researchers used Grounded Theory to develop a theoretical framework that explained the different strategies that individuals used to manage their pain, and that was grounded in the data.
• Glaser and Strauss (1967): This study explored the experiences of individuals who were undergoing a process of becoming disabled. The researchers used Grounded Theory to develop a theoretical framework that explained the social processes of becoming disabled, and that was grounded in the data.
• Clarke (2005): This study explored the experiences of patients with cancer who were receiving chemotherapy. The researcher used Grounded Theory to develop a theoretical framework that explained the factors that influenced patient adherence to chemotherapy, and that was grounded in the data.

Grounded Theory Research Example

A Grounded Theory Research Example Would be:

Research question : What is the experience of first-generation college students in navigating the college admission process?

Data collection : The researcher conducted interviews with first-generation college students who had recently gone through the college admission process. The interviews were audio-recorded and transcribed verbatim.

Data analysis: The researcher used a constant comparative method to analyze the data. This involved coding the data, comparing codes, and constantly revising the codes to identify common themes and patterns. The researcher also used memoing, which involved writing notes and reflections on the data and analysis.

Findings : Through the analysis of the data, the researcher identified several themes related to the experience of first-generation college students in navigating the college admission process, such as feeling overwhelmed by the complexity of the process, lacking knowledge about the process, and facing financial barriers.

Theory development: Based on the findings, the researcher developed a theory about the experience of first-generation college students in navigating the college admission process. The theory suggested that first-generation college students faced unique challenges in the college admission process due to their lack of knowledge and resources, and that these challenges could be addressed through targeted support programs and resources.

In summary, grounded theory research involves collecting data, analyzing it through constant comparison and memoing, and developing a theory grounded in the data. The resulting theory can help to explain the phenomenon being studied and guide future research and interventions.

Purpose of Grounded Theory

The purpose of Grounded Theory is to develop a theoretical framework that explains a social phenomenon, process, or interaction. This theoretical framework is developed through a rigorous process of data collection, coding, and analysis, and is grounded in the data.

Grounded Theory aims to uncover the social processes and patterns that underlie social phenomena, and to develop a theoretical framework that explains these processes and patterns. It is a flexible method that can be used to explore a wide range of research questions and settings, and is particularly well-suited to exploring complex social phenomena that have not been well-studied.

The ultimate goal of Grounded Theory is to generate a theoretical framework that is grounded in the data, and that can be used to explain and predict social phenomena. This theoretical framework can then be used to inform policy and practice, and to guide future research in the field.

When to use Grounded Theory

Following are some situations in which Grounded Theory may be particularly useful:

• Exploring new areas of research: Grounded Theory is particularly useful when exploring new areas of research that have not been well-studied. By collecting and analyzing data, researchers can develop a theoretical framework that explains the social processes and patterns underlying the phenomenon of interest.
• Studying complex social phenomena: Grounded Theory is well-suited to exploring complex social phenomena that involve multiple social processes and interactions. By using an iterative process of data collection and analysis, researchers can develop a theoretical framework that explains the complexity of the social phenomenon.
• Generating hypotheses: Grounded Theory can be used to generate hypotheses about social processes and interactions that can be tested in future research. By developing a theoretical framework that explains a social phenomenon, researchers can identify areas for further research and hypothesis testing.
• Informing policy and practice : Grounded Theory can provide insights into the factors that influence social phenomena, and can inform policy and practice in a variety of fields. By developing a theoretical framework that explains a social phenomenon, researchers can identify areas for intervention and policy development.

Characteristics of Grounded Theory

Grounded Theory is a qualitative research method that is characterized by several key features, including:

• Emergence : Grounded Theory emphasizes the emergence of theoretical categories and concepts from the data, rather than preconceived theoretical ideas. This means that the researcher does not start with a preconceived theory or hypothesis, but instead allows the theory to emerge from the data.
• Iteration : Grounded Theory is an iterative process that involves constant comparison of data and analysis, with each round of data collection and analysis refining the theoretical framework.
• Inductive : Grounded Theory is an inductive method of analysis, which means that it derives meaning from the data. The researcher starts with the raw data and systematically codes and categorizes it to identify patterns and themes, and to develop a theoretical framework that explains these patterns.
• Reflexive : Grounded Theory requires the researcher to be reflexive and self-aware throughout the research process. The researcher’s personal biases and assumptions must be acknowledged and addressed in the analysis process.
• Holistic : Grounded Theory takes a holistic approach to data analysis, looking at the entire data set rather than focusing on individual data points. This allows the researcher to identify patterns and themes that may not be apparent when looking at individual data points.
• Contextual : Grounded Theory emphasizes the importance of understanding the context in which social phenomena occur. This means that the researcher must consider the social, cultural, and historical factors that may influence the phenomenon of interest.

Advantages of Grounded Theory

Advantages of Grounded Theory are as follows:

• Flexibility : Grounded Theory is a flexible method that can be used to explore a wide range of research questions and settings. It is particularly well-suited to exploring complex social phenomena that have not been well-studied.
• Validity : Grounded Theory aims to develop a theoretical framework that is grounded in the data, which enhances the validity and reliability of the research findings. The iterative process of data collection and analysis also helps to ensure that the research findings are reliable and robust.
• Originality : Grounded Theory can generate new and original insights into social phenomena, as it is not constrained by preconceived theoretical ideas or hypotheses. This allows researchers to explore new areas of research and generate new theoretical frameworks.
• Real-world relevance: Grounded Theory can inform policy and practice, as it provides insights into the factors that influence social phenomena. The theoretical frameworks developed through Grounded Theory can be used to inform policy development and intervention strategies.
• Ethical : Grounded Theory is an ethical research method, as it allows participants to have a voice in the research process. Participants’ perspectives are central to the data collection and analysis process, which ensures that their views are taken into account.
• Replication : Grounded Theory is a replicable method of research, as the theoretical frameworks developed through Grounded Theory can be tested and validated in future research.

Limitations of Grounded Theory

Limitations of Grounded Theory are as follows:

• Time-consuming: Grounded Theory can be a time-consuming method, as the iterative process of data collection and analysis requires significant time and effort. This can make it difficult to conduct research in a timely and cost-effective manner.
• Subjectivity : Grounded Theory is a subjective method, as the researcher’s personal biases and assumptions can influence the data analysis process. This can lead to potential issues with reliability and validity of the research findings.
• Generalizability : Grounded Theory is a context-specific method, which means that the theoretical frameworks developed through Grounded Theory may not be generalizable to other contexts or populations. This can limit the applicability of the research findings.
• Lack of structure : Grounded Theory is an exploratory method, which means that it lacks the structure of other research methods, such as surveys or experiments. This can make it difficult to compare findings across different studies.
• Data overload: Grounded Theory can generate a large amount of data, which can be overwhelming for researchers. This can make it difficult to manage and analyze the data effectively.
• Difficulty in publication: Grounded Theory can be challenging to publish in some academic journals, as some reviewers and editors may view it as less rigorous than other research methods.

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Please note you do not have access to teaching notes, a practical example of using theoretical sampling throughout a grounded theory study: a methodological paper.

Qualitative Research Journal

ISSN : 1443-9883

Article publication date: 16 December 2019

Issue publication date: 20 January 2020

The purpose of this paper is to discuss the practical use of theoretical sampling as a method for selecting data that provide a richer and deeper understanding of the phenomenon being investigated.

Design/methodology/approach

Theoretical sampling is a well-known method in grounded theory studies to seek additional data based on concepts developed from initial data analysis. This method involves following where the data have led to expand and refine the evolving theory during the analytical process. However, there is a dearth of information detailing the practical steps needed to undertake theoretical sampling.

The authors used the theoretical sampling method in their study in four ways: asking additional interview questions and/or widening the scope of existing interview questions; recruiting participants with additional diversity of attributes within the same group; and adding a new group of participants and expanding research settings.

Originality/value

Theoretical sampling is a valuable and practical method for the purpose of addressing gaps in the data in qualitative research. When using theoretical sampling, it is essential to consider potential strategies for countering challenges that may arise. Practical recommendations are offered on the use of theoretical sampling during data analysis, for the purpose of achieving theoretical integration.

• Grounded theory
• Qualitative research methods
• Data selection
• Theoretical sampling

Acknowledgements

This paper is part of a doctoral degree programme. The authors acknowledge the Department of Foreign Affairs and Trade, Australian Government, for the funding provided for Titan Ligita’s Doctor of Philosophy study at James Cook University, Australia. The authors would also like to thank all participants who willingly shared their experiences and stories, without which this research would not have been possible.

Ligita, T. , Harvey, N. , Wicking, K. , Nurjannah, I. and Francis, K. (2020), "A practical example of using theoretical sampling throughout a grounded theory study: A methodological paper", Qualitative Research Journal , Vol. 20 No. 1, pp. 116-126. https://doi.org/10.1108/QRJ-07-2019-0059

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An Introduction to Grounded Theory with a Special Focus on Axial Coding and the Coding Paradigm

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In this chapter we introduce grounded theory methodology and methods. In particular we clarify which research questions are appropriate for a grounded theory study and give an overview of the main techniques and procedures, such as the coding procedures, theoretical sensitivity, theoretical sampling, and theoretical saturation. We further discuss the role of theory within grounded theory and provide examples of studies in which the coding paradigm of grounded theory has been altered in order to be better suitable for applications in mathematics education. In our exposition we mainly refer to grounded theory techniques and procedures according to Strauss and Corbin (Basics of qualitative research: Grounded theory procedures and techniques, Sage Publications, Thousand Oaks, 1990 ), but also include other approaches in the discussion in order to point out the particularities of the approach by Strauss and Corbin.

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Grounded Theory

Grounded Theory Methods

Grounded Theory Methodology: Principles and Practices

• Grounded theory
• Coding procedures
• Coding paradigm
• Coding families
• Theoretical sensitivity

1 Introduction

In 1967, sociologists Barney Glaser and Anselm Strauss published their seminal book “The discovery of grounded theory: Strategies for qualitative research” (Glaser and Strauss 1967 ), which lays the foundation for one of the most prominent and influential qualitative research methodologies in the social sciences and beyond. With their focus on theory development, they dissociate themselves from mere theory verification and the concomitant separation of the context of theory discovery and the context of theory justification, which was the prominent scientific method at that time. With their approach to qualitative research, they also go beyond the mere description of phenomena. Originally, the book was written as a book for young researchers. One of its main intentions was to legitimate qualitative research (Mey and Mruck 2011 ).

Quite soon after their joint publication in 1967, Glaser and Strauss developed grounded theory in different directions and started to argue their own understanding of grounded theory methodology and methods apart from each other in different ways, Glaser primarily on his own, Strauss also together with Juliet Corbin (Glaser 1978 ; Strauss 1987 ; Strauss and Corbin 1990 ). Later, students of Glaser and Strauss further developed the different interpretations of grounded theory methodology so that today there is a second generation of grounded theory researchers, namely Juliet Corbin, Adele E. Clarke, and Kathy Charmaz (Morse et al. 2009 ). As those further developments of grounded theory resulted in different research methodologies, it has been suggested to talk about grounded theory methodologies in plural or at least to acknowledge that there are numerous modi operandi involving grounded theory methods in different fields of research as well as different national traditions (Mey and Mruck 2011 ). In Germany, for instance, it is still most common to work with the grounded theory methodology version that was published by Strauss and Corbin in 1990 (German translation from 1996 ). The second generation’s developments are still hardly noticed.

As this chapter is an introduction to grounded theory methodology and methods, our aim is to outline the common core of the different approaches to grounded theory. Therefore, we give a short introduction to grounded theory as a methodology (Sect. 4.2 ) and its techniques and procedures (Sect. 4.3 ). We further discuss an issue that lies at the heart of grounded theory, namely the role of theory within the methodology (Sect.  4.4 ). There, we also describe some examples of studies that used grounded theory as the main methodology, but took a specific stance to theory development in using the methodology.

2 A Short Positioning of Grounded Theory

This section provides a short overview of grounded theory as a methodology. We aim to answer two questions: 1. What is a grounded theory? 2. What kind of research questions are appropriate for a grounded theory study?

2.1 What Is Grounded Theory?

There is no simple answer to this question as the term grounded theory adheres to different research elements. In the first place, grounded theory is a methodology, which is characterized by the iterative process and the interrelatedness of planning, data collection, data analysis, and theory development. Grounded theory further provides a particular set of systematic methods, which support abstraction from the data in order to develop a theory that is grounded in the empirical data. These methods include different coding procedures, which are based on the method of constant comparison. New data are gathered continuously and new cases are included in the analysis based on their potential contribution to the further development and refinement of the evolving theory. This sampling method is called theoretical sampling . The iterative process of data collection according to theoretical sampling, data analysis, and theory development is continued until new data do not contribute any longer to a substantial development of the theory, i.e. until theoretical saturation is achieved. The theory that is the product of this process is also referred to as grounded theory . The quality of a grounded theory is not evaluated according to the standard criteria of test theory, i.e. objectivity, reliability and validity, but according to criteria such as credibility, plausibility, and trustworthiness.

2.2 What Kind of Research Questions Are Appropriate for a Grounded Theory Study?

According to the usual scientific procedure, the research question is at the outset of any scientific endeavour. It is the essence of what the researcher wants to know. The overall purpose of the study is to find an answer to the research question. Methodology and related methods are but a vehicle to find the (possibly best) answer to the research question. Ideally, it should be the research question that determines the methodology and not vice versa. Thus, it is important to ask what kind of research questions are appropriate for a grounded theory study. The character of the research question will influence the methodology and the choice of methods. We will try to characterize the kind of questions to which grounded theory could probably provide a good answer.

The overarching goal of grounded theory is to develop theory. Therefore, grounded theory studies may be carried out related to research phenomena or objects, which lack a (sufficient) theoretical foundation. It may be, that no theory exists for the phenomena under study or that the existing theories are insufficient in that

they lack important concepts;

the relationships among the concepts are not elaborated enough;

the relevance of the concepts and their relationships has not been corroborated for the population or the context under study.

Due to the origins of grounded theory in the social sciences, the main epistemological interest lies in predicting and explaining behavior in social interaction. Thus, Strauss and Corbin ( 1990 ) stress the orientation towards action and processes of grounded theory research questions.

3 A Short Introduction to the Methods and Techniques of Grounded Theory

The methods and techniques of grounded theory make use of different elements: some relate to the collection, some to the evaluation of data, and some refer to the research process. The following section gives a short introduction to the most important methods and techniques to make the start of working with grounded theory easier for a newcomer to this vast field. A more detailed description of the procedures and techniques can be found in the original literature describing grounded theory (e.g., Glaser 1978 ; Strauss 1987 ; Strauss and Corbin 1990 ). Note that technical terms and procedures may differ (slightly) when adhering to literature from different traditions of grounded theory. Even within one tradition of grounded theory, the methodology may also change over time (see Sect.  4.3.3.2 for an example with relation to the coding paradigm proposed by Strauss and Corbin 1990 and Corbin and Strauss 2015 respectively). To gain a more practical idea about the application of grounded theory, we suggest looking at Vollstedt ( 2015 ) for an example of the application of grounded theory methods in an international comparative study in mathematics education carried out in Germany and Hong Kong.

3.1 Theoretical Sensitivity and Sensitizing Concepts

When starting to work with grounded theory, there is no fixed theory at hand with which to evaluate the data. On the contrary, the researcher moves into an open field of study with many unclear aspects. As described above, important concepts are missing, and/or their relationship is not elaborated enough. The longer the researcher will have worked in this field, the clearer those unclear aspects will (hopefully) become. In order to make sense of the data, an important ability of the researcher is theoretical sensitivity. The notion of theoretical sensitivity is closely linked to grounded theory and Glaser ( 1978 ) even devoted a whole book to this issue. Corbin and Strauss ( 2015 ) describe sensitivity as “having insights as well as being tuned into and being able to pick up on relevant issues, events, and happenings during collection and analysis of the data” (p. 78). According to Glaser with the assistance of Holton ( 2004 ) the essence of theoretical sensitivity is the “ability to generate concepts from data and to relate them according to normal models of theory in general” (para. 43). They further sum up a number of single abilities that characterize the theoretical sensitivity of a researcher. These are “the personal and temperamental bent to maintain analytic distance, tolerate confusion and regression while remaining open, trusting to preconscious processing and to conceptual emergence […] the ability to develop theoretical insight into the area of research combined with the ability to make something of these insights […] the ability to conceptualize and organize, make abstract connections, visualize and think multivariately” (para. 43).

The opinions about how a researcher might develop theoretical sensitivity differ between the two founders of grounded theory and are in fact one of the main differences between their approaches. While Glaser (with the assistance of Holton 2004 ) suggests that the “first step in gaining theoretical sensitivity is to enter the research setting with as few predetermined ideas as possible” (para. 43), Strauss and Corbin ( 1990 ) name different sources of theoretical sensitivity: these are respective literature, the professional and personal experience of the researcher as well as the analytical process itself. However, the researcher is not supposed to follow the beaten track of the literature or his/her personal experience, but to question these and go beyond in order to get novel theoretical insight. In “Basics of qualitative research” Strauss and Corbin ( 1990 ) describe techniques to foster theoretical sensitivity. These are questioning, analyzing single words, phrases or sentences, and comparing, thus techniques, which pervade grounded theory in general.

3.2 Interdependence of Data Collection, Analysis, and Development of Theory

One characteristic of grounded theory is that data collection, data analysis, and theory development are not successive steps in the research procedure but are intertwined and interdependent. Thus, action in terms of data collection and reflexion in terms of data analysis and theory development always alternate. Data collection and analysis initialize the process of theory development. Further cycles of data collection and analysis are guided by theoretical sampling and serve to specify the research focus on the one hand, and to develop hypotheses and theory on the other. Theoretical sampling denotes a cumulative sampling method, in which the selection of new cases that are to be included in the analysis is guided by the unfolding theory. In this context “cases” does not necessarily mean “people”. Corbin and Strauss ( 2015 ) point out that “it is concepts and not people, per se, that are sampled” (p. 135). The authors point out that the goal of theoretical sampling might vary throughout the process of theory development. In the beginning of the process, cases are selected, because they are likely to enable the discovery of new relevant concepts. Later on, cases are selected because they are likely to contribute to the differentiation, elaboration, consolidation, and validation of categories in terms of their properties, their dimensions, or their interrelations (see the next section for the development of concepts and categories).

Theoretical sampling and the development of theory are continued until theoretical saturation is achieved, i.e., new data do not seem to contribute any longer to the elaboration of categories. The relations between the categories are well developed and validated (Strauss and Corbin 1990 ).

3.3 Data Analysis

The overarching goal of data analysis in the grounded theory methodology is theory development. In order to achieve this goal, the collected data are evaluated by applying different ways of coding as the core process. Coding in grounded theory methodology is a process of conceptual abstraction by assigning general concepts (codes) to singular incidences in the data.

After having collected some (not necessarily all) data, the evaluation process may begin. Depending on which line of grounded theory methodology one follows, the different kinds of coding that are applied may vary in nomenclature as well as procedures (Glaser 1978 ; Mey and Mruck 2011 ; Strauss and Corbin 1990 ; Teppo 2015 ). Glaser ( 1978 ) discriminates between substantive coding, which consists of open and selective coding, and theoretical coding. In contrast, Strauss and Corbin ( 1990 ) differentiate between three kinds of coding procedures that are needed to develop a grounded theory from the data: open, axial, and selective coding. These procedures are not to be misunderstood as being precise procedures that are easily distinguishable. On the contrary, the procedures are neither clear-cut, nor do they easily define phases that chronologically come one after the other. They embody rather different ways of working with the data that can be combined with each other and between which the researcher can move back and forth if needed (Mey and Mruck 2011 ).

The following sections give a brief overview of open, axial, and selective coding following Strauss and Corbin ( 1990 ). Section  4.4 then focusses on the role of theory in grounded theory with a special focus on axial coding and the coding paradigm.

3.3.1 Open Coding

Although the different procedures of coding do not occur in a strict sequence, open coding is usually the first approach to the data. Core elements of open coding are posing sensitizing questions and constantly comparing data and codes.

Open coding is the part of data analysis that focuses on the conceptualisation and categorisation of phenomena through an intensive analysis of the data. In this first step of open coding, the data are broken up into smaller parts that are deeply analysed. The aim of this analysis is to grasp the core idea of each part and to develop a code to describe it. Open codes can be either developed in vivo, i.e. directly from the data using descriptions that also are derived from or close to the data, or with reference to technical literature referring, e.g., to theories from mathematics education, educational psychology, or other relevant areas of study.

In a second step then, these smaller analytical parts are compared with respect to similarities and differences. Similar parts can be labelled with the same code. Strauss and Corbin ( 1990 ) use the terms concept and category to denote a phenomenon that is categorized and conceptualized by assigning it to one code ( concept ) or concepts of higher order ( category ). This means that the concepts developed are then related to other concepts so that categories of a higher order emerge so that different dimensions of the category can be described. During the process of developing the dimensions of categories, theoretically relevant characteristics of every category are determined and explicated in the code descriptions (Mey and Mruck 2011 ).

The overall goal of open coding is to develop a wealth of codes with which to describe the data. To reach this goal, sensitizing questions are posed regarding the data when they are being analysed. This finally leads to new discoveries (Strauss and Corbin 1990 ). The following list shows some of the questions that offer rich answers for the interpretation of the data (Böhm 2004 ; Mey and Mruck 2011 ; Strauss and Corbin 1990 ):

What?—Which phenomenon is described?

Who?—Which people are involved? Which roles do they embody, or which ones are assigned to them?

How?—Which aspects of the phenomenon are dealt with? Which are left out?

When? How long? Where?—In what way is the spaciotemporal dimension biographically relevant or important for single actions?

Why?—Which justifications are given or deducible?

Whereby?—Which strategies are used?

What for?—Which consequences are anticipated?

To pose those sensitizing questions, the researcher uses his/her personal and professional experience as well as knowledge that was gained from the relevant literature. All those resources are used in a creative manner of free association (Strauss and Corbin 1990 ) to interpret the data and to develop codes to describe the interpretation found. Thus, the researcher’s own and other people’s presuppositions in relation to the phenomenon are questioned and investigated.

3.3.2 Axial Coding

To develop a grounded theory, the emerging relationships between the elaborated concepts need to be integrated into an overarching framework with one core category. Glaser ( 1978 ) calls this process theoretical coding ; Strauss and Corbin ( 1990 ) differentiate between axial coding and selective coding , but themselves emphasize that there is not much of a difference, except at the level of abstraction.

According to Strauss and Corbin ( 1990 ), axial coding is needed to investigate the relationships between concepts and categories that have been developed in the open coding process. As people act and interact with other people, they possess different strategies to handle their interpretations of the situations in which they are involved. Their acting as well as the pursuit of their strategies have consequences. Explanations contain conditions that have an impact on one’s actions and interaction as well as the consequences that result from these (Strauss and Corbin 1990 ). To work out the relations between the categories, Strauss and Corbin ( 1990 ) suggest examining the data and the codes based on a coding paradigm that focuses on and relates causal conditions, context, intervening conditions, action/interaction strategies, and consequences. These perspectives on the data help to detect relations between concepts and categories in order to relate them on a meta level. Strauss and Corbin ( 1990 ) perceive the coding paradigm as an obligatory element of a grounded theory: if the coding paradigm was not used in theory development, the theory would miss density and precision.

One of the most difficult questions for a researcher new to the field of grounded theory is as follows: How does the coding paradigm work? After having broken up the data in the process of open coding, they are joined together in a new way in the process of axial coding as links are worked out between a category and its subcategories. The focus of axial coding is on a category (the phenomenon) in relation to the following aspects. First, causal conditions specify the phenomenon with respect to incidents or occurrences that result in appearance or development of a phenomenon. Second, the context is the specific set of characteristics in which the phenomenon is embedded. Simultaneously, the context also characterizes the special set of conditions in which action/interaction strategies take place to overcome, handle or react to a certain phenomenon. Third, intervening strategies are the broad and general conditions that influence action/interaction strategies. These comprise, for instance, time, space, culture, socioeconomic status, technological status, career, history, and individual biography. Fourth, action or interaction strategies are directed towards the phenomenon. No matter whether the research is about individuals, groups or collectives, there is always action or interaction that is directed towards the phenomenon, to handle or to overcome it, to perform it, or to react to it. The phenomenon always appears in a certain context or under specific circumstances. The interactional component is related to the self of the acting person as well as to other interactions. And finally, action and interaction that are performed or—on the contrary—are not performed as an answer to or to overcome a phenomenon, lead to results and consequences. These are neither always predictable nor intended, and also the default of an action/interaction leads to results and consequences. Consequences can be real or hypothetical in the present or in the future. In addition, consequences can change their frame of reference as in one point of time they can be consequences of an action/interaction, whereas at a later point of time, they can be part of causal conditions for another phenomenon. Note that in the fourth edition of the “Basics of qualitative research”, Corbin and Strauss ( 2015 ) reduced the coding paradigm to the three main features “conditions”, “actions-interactions”, and “consequences or outcomes”.

As Glaser, Strauss, and his colleagues were social scientists, the aspects chosen for their coding paradigm do not necessarily meet the necessities for educational research. Thus, there have been researchers who have changed the procedure of axial coding such that they in general followed the idea to look for relations between the phenomena described in the categories that were developed in the process of open coding but changed the aspects in the coding paradigm to look for those relations. We take a deeper look at the coding paradigm and its possibilities of amendment in Sect.  4.4 .

3.3.3 Selective Coding

The goal of selective coding is to integrate the different categories that have been developed, elaborated, and mutually related during axial coding into one cohesive theory. To reach this goal, the results from axial coding are further elaborated, integrated, and validated. Thus, selective coding is quite similar to axial coding, but it is carried out on a more abstract level. The categories are theoretically integrated into a consistent overarching theory as they are subsumed under a core category that is linked to all other categories that were established in axial coding. As Teppo ( 2015 , with reference to Corbin and Strauss 2008 , p. 14) points out, the questions that have to be answered are “what is the research all about?” and “what seems to be going on here?”. Thus, selective coding is the process of choosing the core category and relating it with the other categories from axial coding. In addition, these relations need to be validated and some categories might need to be refined and further elaborated. The core category described “the central phenomenon around which all the other categories are integrated” (Strauss and Corbin 1990 , p. 116). If the core category is found, the story line of the research is set or, as Vollstedt ( 2015 ) writes, the path is detected that leads the way through all the trees so that the wood can finally be seen. Having detected the core category, the researcher knows the central phenomenon of his/her research and can finally answer the research question. The product of this research process finally appears: the grounded theory that arose from the data.

3.3.4 Memos and Diagrams

A further central rule of grounded theory methodology is to interrupt the coding process again and again to write down memos: “Stop coding and record a memo on your ideas”, as Glaser and Strauss ( 1967 , p. 113) put it. In general, memos are very special types of written notes as they keep track of the analytical process and the directions for the analyst. Thus, they not only describe the phenomena they are about, but move on a meta level by being analytical and conceptual and help the researcher to step back from the material to see it from an analytical distance (Strauss and Corbin 1990 ). Glaser (with the assistance of Holton 2004 , para. 61) writes: “Memos are theoretical notes about the data and the conceptual connections between categories. The writing of theoretical memos is the core stage in the process of generating theory. If the analyst skips this stage by going directly to sorting or writing up, after coding, he/she is not doing GT” [i.e., grounded theory].

There are different kinds of memos like memos on methodical decisions, planning steps, case selection, or interpretative team sessions. The most important variant for the development of a grounded theory is writing memos that contain code notes and theoretical notes. In the process of data analysis, codes can be elaborated so that code notes can be further developed into theoretical notes (see Strauss and Corbin 1990 for a detailed description). Although it is tempting not to write memos in the analytical process, “writing memos and doing diagrams are important elements of analysis and never should be considered superfluous, regardless of how pressed for time the analyst might be” (Strauss and Corbin 1998 , p. 218). Thus, writing memos should accompany the whole analytical process from the development of the first code to the final grounded theory. Memos are written only for the analyst in order to keep track of the analytical “process, thoughts, feelings, and directions of the research and researcher—in fact, the entire gestalt of the research process” (Strauss and Corbin 1998 , p. 218). Hence, they are hardly seen by people other than the researchers involved, but are nevertheless of high importance, also from the perspective of quality criteria. As mentioned above, the quality of a grounded theory can be judged—among other criteria—with reference to credibility, plausibility, and trustworthiness. Memos are needed to argue and prove the development of the grounded theory from the data and are thus a crucial aspect to draw back to when writing down the theory. In addition, Strauss and Corbin also warn “if memos and diagrams are sparsely done, then the final product theory might lack conceptual density and integration. At the end, it is impossible for the analyst to reconstruct the details of the research without memos” (Strauss and Corbin 1998 , p. 218).

Supplementary to written memos, diagrams also help the researcher to find relations between concepts and develop the grounded theory from the data. Strauss and Corbin ( 1998 ) define diagrams as “visual devices that depict the relationships among concepts” (p. 217). Thus, diagrams are needed to link concepts graphically, which is especially helpful for instance to illustrate the relations between the different elements of the coding paradigm (cf. Vollstedt 2015 for a concrete example).

4 The Role of Theory Within Grounded Theory and the Coding Paradigm

From its origins, there has been a conflict inherent in the grounded theory methodology, which relates to the role of theory. The main idea of grounded theory and one of its hallmarks is that categories, concepts, and finally theory ‘emerge’ from the data. In “The discovery of grounded theory” the researcher is therefore advised to “ignore the literature of theory and fact on the area under study, in order to assure that the emergence of categories will not be contaminated” (Glaser and Strauss 1967 , p. 37). However, Glaser and Strauss also admit that “of course, the researcher does not approach reality as a tabula rasa . He must have a perspective that will help him see relevant data and abstract significant categories from his scrutiny of the data” (Glaser and Strauss 1967 , p. 3). Thus, they acknowledge that in modern epistemology it is taken for granted that the world is always perceived through theoretical lenses and related conceptual networks, and empirical observation therefore is always influenced by the theoretical and conceptual knowledge of the observer. Thus, the inherent conflict in terms of the role of theory in grounded theory is, if it is possible that theory only “emerges” from the data or if theory is actually “forced” on the data. This has in fact been a major issue of debate between the two founders of grounded theory—Glaser and Strauss—which finally led to their separation and constitutes the fundamental difference between the two approaches to grounded theory today (Kelle 2005 ).

In order to resolve this conflict between an unbiased emerging of theory and the inevitably theory-laden perspective of the researcher, Glaser and Strauss introduce the notion of theoretical sensitivity . In later works, the coding families (Glaser 1978 ) and the coding paradigm (Strauss and Corbin 1990 ) can also be seen as answers to the same problem.

The coding families (Glaser 1978 ) are sets of general sociological concepts organized into loosely connected frameworks, which are supposed to foster the theoretical sensitivity of the researcher in order to support the development of theory from the data. Some illustrative examples of coding families are provided in Table  4.1 . Glaser’s ( 1978 ) original list is much more detailed and extensive.

Strauss and Corbin ( 1990 ) offer a general model, which they denote as “coding paradigm”, and which is supposed to provide a general frame for analyzing relationships between the categories and concepts. The coding paradigm has already been described in more detail in Sect.  4.3.3.2 .

Although the coding families and the coding paradigm are only very general and widely accepted perspectives on social reality, it is important to be aware that the coding families and the coding paradigm are themselves theoretical framings or orientations, which are utilized within grounded theory in order to develop theory. Thus, the development of theory is not independent, but is structured by the theoretical assumptions and relations provided by the coding families and the coding paradigm. Both encompass a particular perspective on social reality.

Due to the sociological background of Glaser and Strauss, the epistemological interest of grounded theory lies in predicting and explaining behavior and social processes. Accordingly, the coding paradigm focuses on action and interaction in social contexts and related strategies (Tiefel 2005 ). The causal assumptions that are inherent in the coding paradigm structure the development of theory as a whole. Accordingly, Kelle ( 2005 ) advises researchers, which “may feel that this approach goes contrary to their requirements and would be well advised to construct an own coding paradigm rooted in their own theoretical tradition” (para. 21). Tiefel ( 2005 ) also argues that especially in educational research, the coding paradigm of grounded theory is not universally applicable. She even goes one step further and suggests an alternated coding paradigm, which captures dimensions of individual construction of meaning in the dialectic between the individual and the social context (see Sect.  4.4.1.1 ). In mathematics education research, there are also studies that are based on a grounded theory methodology, but which altered the coding paradigm according to their needs. Two examples are presented in Sects.  4.4.1.2 and 4.4.1.3 .

4.1 Examples from Studies in Which the Coding Paradigm Was Changed

The following section provides a little insight into three studies in which the coding paradigm was altered. Tiefel ( 2005 , cf. Sect.  4.4.1.1 ) offers an amendment for learning and educational science; Vollstedt ( 2011 , cf. Sect.  4.4.1.2 ) and Rezat ( 2009 , cf. Sect.  4.4.1.3 ) are studies from mathematics education.

4.1.1 A Modification of the Coding Paradigm from the Perspective of Learning and Educational Theory

As Tiefel ( 2005 ) explicates, Strauss and Corbin offer with their coding procedures a technique that relates structures, actions, and subjectivity with each other. A special focus is put on the processes involved. Being sociologists, their spotlight is primarily on the prediction and explanation of (social) action and (societal) processes. The phenomena that they are especially interested in are, thus, closely linked to a pragmatistic understanding of an activistic significance of objects, which is raised by people’s action or work and which can be changed by interaction and over time. Thus, in this disciplinary context, theories that are grounded in data aim at the explanation of conditions, meanings and significances, as well as procedures that influence people in different situations and areas of their active construction of the world.

Tiefel ( 2005 ) continues that educational science also defines the analysis of interdependencies between biographic and structural processes by means of selected contexts and situations. Nevertheless, its cognitive interest focuses rather on the desire to understand individual decisions and actions. Thus, research in educational science also concentrates rather on the reconstruction of biographical processes in their interdependence with social relativities. Thus, in her research on processes of learning and education as well as the professional biography of an educational consultant, Tiefel ( 2005 ) developed a coding paradigm for processes of learning and education with a special focus on questions of understanding. She proposes the following three perspectives:

Perspective of meaning (especially referring to the reconstruction of the self-perception): How does the informant present him-/herself? What does the person say about him-/herself? What is not mentioned? Which orientations (norms, values, sciences, commonplaces etc.) are relevant for the informant?

Perspective of structure (especially referring to the reconstruction of the world view): Which conditions are shown as important or relevant for the possibilities and the spheres of action of the self? Which ideas, positions, and assumptions give orientation? Which social relations, institutional or social/historical connections are marked as being important for the self?

Courses of action: Which activities/interactions does the informant describe? Which options are noticed and how are they dealt with? Are the strategies rather active or passive, target-oriented or tentative seeking?

Tiefel’s ( 2005 ) suggestion for the modification of the coding paradigm with respect to learning and educational sciences is probably closer to the needs of many researchers in mathematics education than Strauss and Corbin’s ( 1990 ) coding paradigm. However, there are still areas where it does not provide the structure needed to grasp the relevant information to answer the research questions. Therefore, the following two sections provide insight into two studies that further adapted the coding paradigms to their needs to be able to develop a dense grounded theory.

4.1.2 Personal Meaning When Dealing with Mathematics in a School Context

The claim for meaning in education has been raised for many years and meaningful learning is assumed to be a central impetus (Biller 1991 ) as well as one of the major goals (Vinner 2007 ) of education. Hence, one of the challenges of education in general as well as of mathematics education in particular is to find convincing answers to the quest for meaning. Subsequently, to make learning meaningful for the students, we need to ask the students what is meaningful to them rather than imposing some kind of meaning that might be meaningful from a normative perspective, but can hardly be related to the students’ biography (Meyer 2008 ). Howson ( 2005 ) therefore distinguishes between two different aspects of meaning, “namely, those relating to relevance and personal significance (e.g., ‘What is the point of this for me?’) and those referring to the objective sense intended (i.e., signification and referents)” (p. 18). Hence, “even if students have constructed a certain meaning of a concept, that concept may still not yet be ‘meaningful’ for him or her in the sense of relevance to his/her life in general” (Kilpatrick et al. 2005 , p. 14). In her research, Vollstedt ( 2011 ) therefore took the students’ perspective when she was interested in the aspects of the learning process that make learning mathematics meaningful for them. To emphasize the focus on the learner’s perspective, the term personal meaning was coined to designate those aspects that are personally relevant for the students, i.e., the first aspect of meaning that was described by Howson above (cf. also Vollstedt and Duchhardt, in press).

One aim of the study was to develop a grounded theory about what personal meanings students construct when they are involved with mathematical contents in a school context. A second aim was to put a special focus on the role of the cultural background of the classroom situation. Therefore, the interview study was conducted in Germany and in Hong Kong. The two places were chosen as examples of a Western and a Confucian Heritage Culture (CHC, cf. Leung et al. 2006 ) to make sure to have quite distinct cultural backgrounds for teaching and learning mathematics.

Data gathered for the study comprised video recordings of three mathematics classrooms (9th and 10th grade) for one week in each place together with field notes taken by the researcher. The videos were used for a sequence of stimulated recall (Gass and Mackey 2000 ) at the beginning of each interview with volunteers from the classes (see Vollstedt 2011 or 2015 for further details).

In the process of axial coding it turned out that neither Strauss and Corbin’s ( 1990 ) nor Tiefel’s ( 2005 ) coding paradigm really fitted the data and the research questions. Therefore, the coding paradigm was also adapted to the individual needs of Vollstedt’s study in the following way: At first, there was a long and intense discussion with fellow researchers from the Graduate Research Group on Educational Experience and Learner Development at the University of Hamburg about how personal meaning might be constructed, and which aspects seemed to be relevant for its construction. In the final model it is assumed that there is an individual in a certain situation in which he/she is dealing with mathematics in a school context, e.g., the student Johanna is studying mathematics at home. The situational context, i.e., the context of the learning situation in terms of topic as well as classroom situation/home, is a crucial factor for the construction of personal meaning and of particular importance in this study as there was a special focus on cultural background of the teaching and learning situation. In this situation, there are certain preliminaries that are part of Johanna, such as her personal background, i.e., aspects that cannot be influenced by herself, including her socio-economic or migration background. In addition, personal traits, i.e., aspects that concern her self, are relevant. They comprise concepts that are discussed in various scientific fields such as educational psychology (self-concept, self-efficacy), mathematics education (beliefs), and educational science (developmental tasks). Based on these preliminaries, Johanna then constructs personal meaning with relation to the learning content and context. Depending on the result of this construction, different consequences can occur. Johanna might for instance appraise the situation with respect to her personal goals so that different actions might follow, e.g., she might not understand the contents she is dealing with and will therefore ask her neighbour for help. Or she might think that mathematics is not as important as spending time with her friends so that she will stop working on her tasks.

The relational framework given in Fig.  4.1 shows the diagram of how the aspects described above might be interrelated to describe the construction of personal meaning. It provided the basis for the coding paradigm used by Vollstedt ( 2011 ). For each category that was developed throughout the coding process, it was attempted to fit it in this model and relate it with other relevant concepts. Thus, finally, it was possible to describe preliminaries and consequences for each core category, i.e., personal meaning, that was developed in this study (see Vollstedt 2011 , 2015 ).

Relational framework of personal meaning (cf. Vollstedt 2011 )

Taking a closer look at this coding paradigm, reveals that there are relations to both versions of coding paradigms provided by either Strauss and Corbin ( 1990 ) or Tiefel ( 2005 ). Vollstedt’s ( 2011 ) situation embraces aspects from Strauss and Corbin’s ( 1990 ) context and intervening strategies , whereas some aspects of the latter are also part of Vollstedt’s preliminaries . Consequences are similar in both paradigms. Strauss and Corbin’s causal conditions and action/interaction strategies were not found to be relevant in Vollstedt’s study as they are directed towards the phenomenon, i.e., a kind of personal meaning. In Vollstedt’s theory, consequences occur after the individual has constructed a personal meaning, so that actions from her framework—being part of the consequences —are something different than action/interaction strategies from Strauss and Corbin. With respect to Tiefel’s ( 2005 ) aspects, on the one hand the perspective of meaning is similar to aspects that are described in the preliminaries like personal background and/or personal traits . The perspective of structure and the courses of action on the other hand relate to situation and preliminaries , and consequences respectively. Nevertheless, although nearly all aspects are somehow integrated in Vollstedt’s ( 2011 ) coding paradigm, neither Strauss and Corbin’s ( 1990 ) nor Tiefel’s ( 2005 ) coding paradigm would have grasped the particularities of the phenomenon under study. It is interesting to see, though, that Vollstedt’s approach is very close to the modifications made by Corbin and Strauss ( 2015 ) in the fourth edition of “Basics of qualitative research”. There, they reduced the aspects of the coding paradigm to conditions, actions - interactions , and consequences or outcomes . Still, having a sociological perspective, the focus is on actions and interactions whereas in Vollstedt’s research, educational processes are the focus. But nevertheless, as her coding paradigm also primarily looks at preliminaries and consequences from the context and individual’s perspective, the similarities of the two approaches cannot be overlooked.

4.1.3 Learning Mathematics with Textbooks

Rezat ( 2009 ) developed a grounded theory on how students learn mathematics autonomously with their mathematics textbooks. Theory development is grounded in data on the specific parts that students used on their own in their textbooks, and on students’ explanations of why they used these parts. He further conducted interviews with selected students in order to better understand how they proceeded when learning mathematics with their textbooks. Finally, he observed the mathematics lessons for the period of the study and took field notes (Rezat 2008 ).

The grounded theory comprises activities, in which students utilize their mathematics textbooks and students’ utilization schemes of the textbook within these activities. Rezat ( 2009 ) finds that students refer to their mathematics textbook related to four activities:

solving tasks and problems in order to get assistance from the textbook,

consolidation activities in order to use the contents of the book for practicing and consolidation,

acquiring mathematical knowledge that has not been a matter in class, and

activities associated with interest in mathematics.

These activities clarify the causal conditions under which textbook use occurs as well as attributes of the context of the investigated phenomenon, autonomous learning mathematics with the textbook . In terms of activity 1, this means that the causal condition for using the textbook is that students are working on a task or a problem (that might originate from the textbook or some other source) and they need assistance for solving it. The causal condition for textbook use related to activity 2 is students’ aspiration to practice and consolidate their mathematical knowledge/competencies. The inclination to acquire new mathematical knowledge or competencies is the causal condition for textbook use related to activity 3 and students’ interest in mathematics motivates textbook use related to activity 4.

Although the coding paradigm of grounded theory according to Strauss and Corbin ( 1990 ) allows for a general analysis of students’ actions and interactional strategies with their textbooks associated with the four activities, Rezat ( 2009 ) argues that the instrumental approach (Rabardel 2002 ) provides theoretical concepts and relations that grasp students’ interactions with their textbook better than the general focus on actions and interactional strategies of the coding paradigm in grounded theory. Therefore, he enhances the coding paradigm by including the instrumental approach (Rabardel 2002 ). Instead of analyzing actions and interactional strategies he analyses students’ “instrumentalization” und “instrumentation” (Rabardel 2002 ) of the mathematics textbook within the different learning activities. While the analysis of the instrumentalization of the mathematics textbook relates to functions that users attribute to the textbook within the activities, the analysis of instrumentation relates to the development of utilization schemes. The latter are characterized by “1. goals and anticipations; 2. rules of action, information seeking, and control; 3. operational invariants; 4. possibilities of inference” (Vergnaud 1998 , p. 173). Based on this conceptualization of schemes, Rezat reconstructs different utilization schemes of students using their textbook within the different activities. For example, he finds three different utilization schemes related to consolidation activities: (1) position-dependent practicing ; (2) block-dependent practicing ; and (3) salience depended practicing (Rezat 2013 ). The three schemes differ in particular in terms of their operational invariants. Position-dependent practicing is based on the operational invariant that contents of the textbook that is useful for practicing can be found at a certain relative position to other contents in the textbook, e.g. tasks that are appropriate for practicing are adjacent to tasks that the teacher explicitly asked the students to work on. On the contrary, block-dependent practicing is based on the selection of a specific structural element of the textbook such as tasks, rules (in a box) or worked examples for practicing. Finally, salience-dependent practicing is based on an operational invariant that takes salient visual features of the contents as the main criteria for selection of contents from the textbook.

On the one hand, the instrumental approach and the notion of utilization schemes is included in the study as a means to increase theoretical sensitivity and to describe the cognitive aspects of students’ actions and interactions with their textbooks. On the other hand, the concepts of the instrumental approach provide a language, which can be used to describe students’ actions and interactions with their textbooks from a cognitive perspective as exemplified in the three utilization schemes related to students’ consolidation activities with mathematics textbooks.

In the study by Rezat ( 2009 ), parts of the very general coding paradigm are substituted by a well elaborated theory. Consequently, the question has to be raised if this is actually still a grounded theory study or if a well-developed theory already existed before. However, a well-developed theory about the phenomenon under study, namely students’ autonomous learning of mathematics with their textbooks, had not existed before the study. Therefore, grounded theory appears to be an adequate overall methodology of the study. In order to grasp specific aspects of the phenomenon under study in more detail, Rezat ( 2009 ) refers to existing and more general theory, which is not solely linked to the phenomenon under study. While Rabardel’s ( 2002 ) theory conceptualizes human interactions with (technological) artefacts in general, Rezat ( 2009 ) develops a theory of students’ learning of mathematics with their textbooks. Therefore, his approach seems to reconcile theory development and building on existing theory. While the overall goal of the study is to develop a grounded theory related to a particular phenomenon, theory development builds on more general existing theories, which seems to be a helpful approach in order to focus and describe particular elements of the developing theory. Thus, existing theory seems to be included in the grounded theory wherever it appears to be useful in the developing theory.

5 Concluding Remarks

In this chapter, we gave a cursory introduction to grounded theory methodology and methods. We briefly described the coding procedures, the notions of theoretical sensitivity , theoretical sampling , and theoretical saturation and how these components serve the main aim of grounded theory, namely to develop a theory that is empirically grounded in the data. We recommend that the (early career) researcher, who has become curious and wants to start developing grounded theory, also refers to the original sources. These describe the techniques and procedures of grounded theory in much more detail. As already pointed out at the beginning of this chapter, some of them were even written for early career researchers.

Our chapter might support the early career researcher in becoming aware of differences between the two main schools of grounded theory—grounded theory in the tradition following the foundations of Glaser or of Strauss, respectively. These differences are mainly rooted in the role of theory within grounded theory. We pointed out that the role of theory is actually an inherent epistemological issue in grounded theory methodology. We further provided examples of studies that challenge this issue by adjusting the coding paradigm according to the needs of the phenomenon under study. However, in these cases, the researcher has to justify whether the study remains a grounded theory study. We see this as just another challenge to the theoretical sensitivity of the researcher. And theoretical sensitivity is the core ability a researcher has to bring to, cultivate within, and gain from the endeavor of developing a grounded theory.

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Vollstedt, M., Rezat, S. (2019). An Introduction to Grounded Theory with a Special Focus on Axial Coding and the Coding Paradigm. In: Kaiser, G., Presmeg, N. (eds) Compendium for Early Career Researchers in Mathematics Education . ICME-13 Monographs. Springer, Cham. https://doi.org/10.1007/978-3-030-15636-7_4

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Your complete guide to grounded theory research.

11 min read If you have an area of interest, but no hypothesis yet, try grounded theory research. You conduct data collection and analysis, forming a theory based on facts. Read our ultimate guide for everything you need to know.

What is grounded theory in research?

Grounded theory is a systematic qualitative research method that collects empirical data first, and then creates a theory ‘grounded’ in the results.

The constant comparative method was developed by Glaser and Strauss, described in their book, Awareness of Dying (1965). They are seen as the founders of classic grounded theory.

Research teams use grounded theory to analyze social processes and relationships.

Because of the important role of data, there are key stages like data collection and data analysis that need to happen in order for the resulting data to be useful.

The grounded research results are compared to strengthen the validity of the findings to arrive at stronger defined theories. Once the data analysis cannot continue to refine the new theories down, a final theory is confirmed.

Grounded research is different from experimental research or scientific inquiry as it does not need a hypothesis theory at the start to verify. Instead, the evolving theory is based on facts and evidence discovered during each stage.Also, grounded research also doesn’t have a preconceived understanding of events or happenings before the qualitative research commences.

Free eBook: Qualitative research design handbook

When should you use grounded theory research?

Grounded theory research is useful for businesses when a researcher wants to look into a topic that has existing theory or no current research available. This means that the qualitative research results will be unique and can open the doors to the social phenomena being investigated.

In addition, businesses can use this qualitative research as the primary evidence needed to understand whether it’s worth placing investment into a new line of product or services, if the research identifies key themes and concepts that point to a solvable commercial problem.

Grounded theory methodology

There are several stages in the grounded theory process:

1. Data planning

The researcher decides what area they’re interested in.

They may create a guide to what they will be collecting during the grounded theory methodology. They will refer to this guide when they want to check the suitability of the qualitative data, as they collect it, to avoid preconceived ideas of what they know impacting the research.

A researcher can set up a grounded theory coding framework to identify the correct data. Coding is associating words, or labels, that are useful to the social phenomena that is being investigated. So, when the researcher sees these words, they assign the data to that category or theme.

In this stage, you’ll also want to create your open-ended initial research questions. Here are the main differences between open and closed-ended questions:

These will need to be adapted as the research goes on and more tangents and areas to explore are discovered. To help you create your questions, ask yourself:

• What are you trying to explain?
• What experiences do you need to ask about?
• Who will you ask and why?

2. Data collection and analysis

Data analysis happens at the same time as data collection. In grounded theory analysis, this is also known as constant comparative analysis, or theoretical sampling.

The researcher collects qualitative data by asking open-ended questions in interviews and surveys, studying historical or archival data, or observing participants and interpreting what is seen. This collected data is transferred into transcripts.

The categories or themes are compared and further refined by data, until there are only a few strong categories or themes remaining. Here is where coding occurs, and there are different levels of coding as the categories or themes are refined down:

• Data collection (Initial coding stage): Read through the data line by line
• Open coding stage: Read through the transcript data several times, breaking down the qualitative research data into excerpts, and make summaries of the concept or theme.
• Axial coding stage: Read through and compare further data collection to summarize concepts or themes to look for similarities and differences. Make defined summaries that help shape an emerging theory.
• Selective coding stage: Use the defined summaries to identify a strong core concept or theme.

During analysis, the researcher will apply theoretical sensitivity to the collected data they uncover, so that the meaning of nuances in what they see can be fully understood.

This coding process repeats until the researcher has reached theoretical saturation. In grounded theory analysis, this is where all data has been researched and there are no more possible categories or themes to explore.

3. Data analysis is turned into a final theory

The researcher takes the core categories and themes that they have gathered and integrates them into one central idea (a new theory) using selective code. This final grounded theory concludes the research.

The new theory should be a few simple sentences that describe the research, indicating what was and was not covered in it.

An example of using grounded theory in business

One example of how grounded theory may be used in business is to support HR teams by analyzing data to explore reasons why people leave a company.

For example, a company with a high attrition rate that has not done any research on this area before may choose grounded theory to understand key reasons why people choose to leave.

Researchers may start looking at the quantitative data around departures over the year and look for patterns. Coupled with this, they may conduct qualitative data research through employee engagement surveys , interview panels for current employees, and exit interviews with leaving employees.

From this information, they may start coding transcripts to find similarities and differences (coding) picking up on general themes and concepts. For example, a group of excepts like:

• “The hours I worked were far too long and I hated traveling home in the dark”
• “My manager didn’t appreciate the work I was doing, especially when I worked late”
• There are no good night bus routes home that I could take safely”

Using open coding, a researcher could compare excerpts and suggest the themes of managerial issues, a culture of long hours and lack of traveling routes at night.

With more samples and information, through axial coding, stronger themes of lack of recognition and having too much work (which led people to working late), could be drawn out from the summaries of the concepts and themes.

This could lead to a selective coding conclusion that people left because they were ‘overworked and under-appreciated’.

With this information, a grounded theory can help HR teams look at what teams do day to day, exploring ways to spread workloads or reduce them. Also, there could be training supplied to management and employees to engage professional development conversations better.

 Advantages of grounded theory

• No need for hypothesis – Researchers don’t need to know the details about the topic they want to investigate in advance, as the grounded theory methodology will bring up the information.
• Lots of flexibility – Researchers can take the topic in whichever direction they think is best, based on what the data is telling them. This means that exploration avenues that may be off-limits in traditional experimental research can be included.
• Multiple stages improve conclusion – Having a series of coding stages that refine the data into clear and strong concepts or themes means that the grounded theory will be more useful, relevant and defined.
• Data-first – Grounded theory relies on data analysis in the first instance, so the conclusion is based on information that has strong data behind it. This could be seen as having more validity.

Disadvantages of grounded theory

• Theoretical sensitivity dulled – If a researcher does not know enough about the topic being investigated, then their theoretical sensitivity about what data means may be lower and information may be missed if it is not coded properly.
• Large topics take time – There is a significant time resource required by the researcher to properly conduct research, evaluate the results and compare and analyze each excerpt. If the research process finds more avenues for investigation, for example, when excerpts contradict each other, then the researcher is required to spend more time doing qualitative inquiry.
• Bias in interpreting qualitative data – As the researcher is responsible for interpreting the qualitative data results, and putting their own observations into text, there can be researcher bias that would skew the data and possibly impact the final grounded theory.
• Qualitative research is harder to analyze than quantitative data – unlike numerical factual data from quantitative sources, qualitative data is harder to analyze as researchers will need to look at the words used, the sentiment and what is being said.
• Not repeatable – while the grounded theory can present a fact-based hypothesis, the actual data analysis from the research process cannot be repeated easily as opinions, beliefs and people may change over time. This may impact the validity of the grounded theory result.

What tools will help with grounded theory?

Evaluating qualitative research can be tough when there are several analytics platforms to manage and lots of subjective data sources to compare. Some tools are already part of the office toolset, like video conferencing tools and excel spreadsheets.

However, most tools are not purpose-built for research, so researchers will be manually collecting and managing these files – in the worst case scenario, by pen and paper!

Use a best-in-breed management technology solution to collect all qualitative research and manage it in an organized way without large time resources or additional training required.

Qualtrics provides a number of qualitative research analysis tools, like Text iQ , powered by Qualtrics iQ, provides powerful machine learning and native language processing to help you discover patterns and trends in text.

This also provides you with research process tools:

• Sentiment analysis — a technique to help identify the underlying sentiment (say positive, neutral, and/or negative) in qualitative research text responses
• Topic detection/categorisation — The solution makes it easy to add new qualitative research codes and group by theme. Easily group or bucket of similar themes that can be relevant for the business and the industry (eg. ‘Food quality’, ‘Staff efficiency’ or ‘Product availability’)

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Article Contents

Introduction, distinguishing features of grounded theory, the role and timing of the literature review.

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Grounded theory: what makes a grounded theory study?

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Carley Turner, Felicity Astin, Grounded theory: what makes a grounded theory study?, European Journal of Cardiovascular Nursing , Volume 20, Issue 3, March 2021, Pages 285–289, https://doi.org/10.1093/eurjcn/zvaa034

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Grounded theory (GT) is both a research method and a research methodology. There are several different ways of doing GT which reflect the different viewpoints of the originators. For those who are new to this approach to conducting qualitative research, this can be confusing. In this article, we outline the key characteristics of GT and describe the role of the literature review in three common GT approaches, illustrated using exemplar studies.

Describing the key characteristics of a Grounded theory (GT) study.

Considering the role and timing of the literature review in different GT approaches.

Qualitative research is a cornerstone in cardiovascular research. It gives insights in why particular phenomena occur or what underlying mechanisms are. 1 Over the past 2 years, the European Journal of Cardiovascular Nursing published 20 qualitative studies. 2–21 These studies used methods such as content analysis, ethnography, or phenomenology. Grounded theory (GT) has been used to a lesser extent.

Grounded theory is both a methodology and a method used in qualitative research ( Table 1 ). It is a research approach used to gain an emic insight into a phenomenon. In simple terms, this means understanding the perspective, or point of view, of an ‘insider’, those who have experience of the phenomenon. 22 Grounded theory is a research approach that originated from the social sciences but has been used in education and health research. The focus of GT is to generate theory that is grounded in data and shaped by the views of participants, thereby moving beyond description and towards theoretical explanation of a process or phenomenon. 23

Grounded theory as a method and methodology

One of the key issues with using GT, particularly for novices, is understanding the different approaches that have evolved as each specific GT approach is slightly different.

The tradition of GT began with the seminal text about classic GT written by Glaser and Strauss, 24 but since then GT has evolved into several different types. The approach to GT chosen by the researcher depends upon an understanding of the epistemological underpinnings of the different approaches, the match with the topic under investigation and the researcher’s own stance. Whilst GT is frequently used in applied health research, very few studies detail which GT approach has been used, how and why. Sometimes published studies claim to use GT methodology but the approaches that form the foundation of GT are not reported. This may be due to the word limit in academic journals or because legitimate GT approaches have not been followed. Either way, there is a lack of clarity about the practical application of GT. The purpose of this article is to outline the distinguishing characteristics of GT and outline practical considerations for the novice researcher regarding the place of the literature review in GT.

There are several distinguishing features of GT, as outlined by Sbaraini et al. 25 The first is that GT research is conducted through an inductive process. This means that the researcher is developing theory rather than testing it and must therefore remain ‘open’ throughout the study. In essence, this means that the researcher has no preconceived ideas about the findings. Taking an inductive approach means that the focus of the research may evolve over time as the researchers understand what is important to their participants through the data collection and analysis process.

With regards to data analysis, the use of coding is initially used to break down data into smaller components and labelling them to capture the essence of the data. The codes are compared to one another to understand and explain any variation in the data before they are combined to form more abstract categories. Memos are used to record and develop the researcher’s analysis of the data, including the detail behind the comparisons made between categories. Memos can stimulate the researcher’s thinking, as well as capturing the researcher’s ideas during data collection and analysis.

A further feature for data analysis in a GT study is the simultaneous data analysis and sampling to facilitate theoretical sampling. This means that as data analysis progresses participants are purposefully selected who may have characteristics or experiences that have arisen as being of interest from data collection and analysis so far. Questions in the topic guide may also be modified to follow a specific line of inquiry, test ideas and interpretations, or fill gaps in the analysis to build an emerging substantive theory. This evolving and non-linear methodology is to allow the evolution of the study as indicated by data, rather than analysing at the end of data collection. This approach to data analysis supports the researcher to take an inductive approach as discussed above.

Theoretical sampling facilitates the construction of theory until theoretical saturation is reached. Theoretical saturation is when all the concepts that form the theory being developed are well understood and grounded in data. Finally, the results are expressed as a theory where a set of concepts are related to one another and provide a framework for making predictions. 26 These key features of GT are summarized in Table 2 .

Distinguishing features of a GT study (adapted from Sbaraini et al. 25 )

The identification of a gap in the published literature is typically a requirement of successful doctoral studies and grant applications. However, in GT research there are different views about the role and timing of the literature review.

For researchers using classic Glaserian GT, the recommended approach is that the published literature should not be reviewed until data collection, analysis and theory development has been completed. 24 The rationale for the delay of the literature review is to enable the researcher to remain ‘open’ to discover theory emerging from data and free from contamination by avoiding forcing data into pre-conceived concepts derived from other studies. Furthermore, because the researcher is ‘open’ to whichever direction the data takes they cannot know in advance which aspects of the literature will be relevant to their study. 27

In Glaserian GT, the emerging concepts and theory from data analysis inform the scope of the literature review which is conducted after theory development. 24 This approach to the literature review aligns with the rather positivist stance of Glaser in which the researcher aims to remain free of assumptions so that the theory that emerges from the data is not influenced by the researcher. Reviewing the literature prior to data analysis would risk theory being imposed on the data. Perhaps counterintuitively, Glaser does recommend reading literature in unrelated fields to understand as many theoretical codes as possible. 28 However, it is unclear how this is different to reading literature directly related to the topic and could potentially still lead to the contamination of the theory arising from data that delaying the literature review is intended to avoid. It is also problematic regarding the governance processes around research, whereby funders and ethics committees would expect at least an overview of the existing literature as part of the justification for the study.

A study by Bergman et al. 29 used a classic Glaserian GT approach to examine and identify the motive of power in myocardial infarction patients’ rehabilitation process. Whilst the key characteristics of GT were evident in the way the study was conducted, there was no discussion about how the literature review contributed to the final theory. This may have been due to the word limit but illustrates the challenges that novice researchers may have in understanding where the literature review fits in studies using GT approaches.

In Straussian GT, a more pragmatic approach to the literature view is adopted. Strauss and Corbin 30 recognized that the researcher has prior knowledge, including that of the literature, before starting their research. They did not recommend dissociation from the literature, but rather that the literature be used across the various stages of the research. Published literature could identify important areas that could contribute to theory development, support useful comparisons in the data and stimulate further questions during the analytical process. According to Strauss and Corbin, researchers should be mindful about how published work could influence theory development. Whilst visiting the literature prior to data collection was believed to enhance data analysis, it was not thought necessary to review all the literature beforehand, but rather revisit the literature at later stages in the research process. 30

A study published by Salminen-Tuomaala et al. 31 used a Straussian GT approach to explore factors that influenced the way patients coped with hospitalization for acute myocardial infarction. The authors described a reflexive process in which the researcher noted down their preconceived ideas about the topic as part of the data analysis process. The literature review was conducted after data analysis.

The most recent step in the evolution of GT is the move towards a constructivist epistemological stance advocated by Charmaz. 32 In simple terms, this means that the underlying approach reflects the belief that theories cannot be discovered but are instead constructed by the researcher and their interactions with the participants and data. As the researcher plays a central role in the construction of the GT, their background, personal views, and culture will influence this process and the way data are analysed. For this reason, it is important to be explicit about these preconceptions and aim to maintain an open mind through reflexivity. 32 Therefore, engaging in a preliminary literature review and using this information to compare and contrast with findings from the research undertaken is desirable, alongside completing a comprehensive literature review after data analysis with a specific aim to present the GT.

A study published by Odell et al. 33 used the modified GT approach recommended by Charmaz 32 to study patients’ experiences of restenosis after Percutaneous Coronary Intervention. The authors described the different GT approaches and key features of GT methodology which clearly informed the conduct of the study. However, there was no detail about how the literature review was used to shape the data analysis process and findings.

A solution: be clear on the approach taken to the literature review and why

Despite the clear differences in the approach to the literature review in GT, there appears to be a lack of precise guidance for novice researchers regarding how in depth or exhaustive a preliminary literature review should be. This lack of guidance can lead to a variety of different approaches as evidenced in the GT studies we have cited as examples, which is a challenge for the novice researcher. This uncertainty is further compounded by the concurrent approach to data collection and analysis which allows for the research focus to evolve as the study progresses. The complexity of the research process and the role and timing of the literature review is summarized in Figure 1 .

Literature review in Grounded Theory.

Taking a pragmatic approach, researchers will need to familiarize themselves with the literature to receive funding and approval for their study. This preliminary literature review can be followed up after data analysis by a more comprehensive review of the literature to help support the theory that was developed from the data. The key is to ensure transparency in reporting how the literature review has been used to develop the theory. The preliminary literature review can be used to set the scene for the research as part of the introduction, and the more extensive literature review can then be used during the discussion section to compare the theory developed from the data with existing literature, as per Probyn et al. 34

Whilst this pragmatic approach aligns with Straussian GT and Charmaz’s constructivist GT, it is at odds with Glaserian GT. Therefore, if Glaserian GT is chosen, the researcher should be explicit about deviation and provide a rationale.

Word count for journal articles is often a limiting factor in how much detail is included in why certain methodologies are used. Submitting detail about the methodology and rationale behind it can be presented as online supplementary material, thereby allowing interested readers to access further information about how and why the research was executed.

The use of GT as a methodology and method can shed light on areas where little knowledge is already known, generating theory directly from data. The traditional format of a published article does not always reflect the iterative approach to the literature review and data collection and analysis in GT. This can generate tension between how the research is presented in relation to how it was conducted. However, one simple way to ensure clarity in reporting is to be transparent in how the literature review is used.

The authors received no financial support for the research, authorship or publication of this article.

Conflict of interest : The authors declare that there are no conflicts of interest.

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ORIGINAL RESEARCH article

No change a grounded theory analysis of depressed patients' perspectives on non-improvement in psychotherapy.

• 1 Department of Psychoanalysis and Clinical Consulting, Ghent University, Ghent, Belgium
• 2 Fonds Wetenschappelijk Onderzoek, Brussels, Belgium

Aim: Understanding the effects of psychotherapy is a crucial concern for both research and clinical practice, especially when outcome tends to be negative. Yet, while outcome is predominantly evaluated by means of quantitative pre-post outcome questionnaires, it remains unclear what this actually means for patients in their daily lives. To explore this meaning, it is imperative to combine treatment evaluation with quantitative and qualitative outcome measures. This study investigates the phenomenon of non-improvement in psychotherapy, by complementing quantitative pre-post outcome scores that indicate no reliable change in depression symptoms with a qualitative inquiry of patients' perspectives.

Methods: The study took place in the context of a Randomised Controlled Trial evaluating time-limited psychodynamic and cognitive behavioral therapy for major depression. A mixed methods study was conducted including patients' pre-post outcome scores on the BDI-II-NL and post treatment Client Change Interviews. Nineteen patients whose data showed no reliable change in depression symptoms were selected. A grounded theory analysis was conducted on the transcripts of patients' interviews.

Findings: From the patients' perspective, non-improvement can be understood as being stuck between knowing versus doing, resulting in a stalemate. Positive changes (mental stability, personal strength, and insight) were stimulated by therapy offering moments of self-reflection and guidance, the benevolent therapist approach and the context as important motivations. Remaining issues (ambition to change but inability to do so) were attributed to the therapy hitting its limits, patients' resistance and impossibility and the context as a source of distress. “No change” in outcome scores therefore seems to involve a “partial change” when considering the patients' perspectives.

Conclusion: The study shows the value of integrating qualitative first-person analyses into standard quantitative outcome evaluation and particularly for understanding the phenomenon of non-improvement. It argues for more multi-method and multi-perspective research to gain a better understanding of (negative) outcome and treatment effects. Implications for both research and practice are discussed.

Negative outcome or nonresponse to treatment is undeniably part of clinical practice. It is estimated that 5 to 10% of patients deteriorates in therapy ( Cooper, 2008 ; Lambert, 2013 ), and a proportion of 35 to 40% of the participants in clinical trials do not improve ( Lambert, 2007 ). A better understanding of negative outcome and treatment effects is crucial for both research and clinical practice, yet outcome research has focused predominantly on capturing positive change and “what works,” while less is known about non-improvement or what it actually means when treatments fail ( Barlow, 2010 ).

There is no uniform understanding of negative outcome, nor is there agreement on the definition of treatment failure ( Lambert, 2011 ; Lampropoulos, 2011 ). “Negative outcome” and “negative therapeutic effects” are often used as synonyms, although they do not have a one-on-one relationship, as negative outcome is not necessarily caused by therapy ( Mays and Franks, 1985 ; Mohr, 1995 ). Depending on the perspective (e.g., patient, therapist, researcher), the type of outcome (e.g., symptoms, quality of life), measurement method (e.g., quantitative or qualitative) and time point (e.g., post treatment or follow-up) being used for treatment evaluation, the conception of outcome and treatment effects varies ( Lampropoulos, 2011 ).

In outcome research, outcome and treatment effects are typically evaluated using statistical tests of significance that provide an indication of the reliability of the measured change. Statistical significance shows that an outcome difference is larger than could have been expected by mere chance. Clinical significance shows whether such a statistical effect is also clinically meaningful (i.e., change toward a normal level of functioning) ( Jacobson et al., 1999 ; Ogles et al., 2001 ; Lambert et al., 2008 ; Lambert and Ogles, 2009 ). Based on the Jacobson and Truax widely used method for clinical significance, outcome can be classified into four categories: (1) recovery (i.e., clinically significant change), (2) improvement (i.e., reliable change), (3) no reliable change and (4) deterioration (i.e., reliable change in the negative direction). Generally, the first category “recovery” is taken as the gold standard outcome and treatment goal: a reliable decrease in symptoms 1 and return to a non-clinical level of functioning. When neither criterion is met, it is concluded that patients remained “unchanged” in comparison to their level of functioning prior to treatment ( Jacobson and Truax, 1991 ).

Despite the added value of clinical significance testing of measured changes, this type of statistical outcome classification cannot overcome the limitations that are voices for standard outcome research ( Hill et al., 2013 ). Quantitative pre-post outcome evaluation is criticised for relying predominantly on one-dimensional rating scales, most often symptom-based ( Braakmann, 2015 ), and consequently, for offering only an incomplete approximation of the multi-dimensional nature of human functioning ( Kazdin, 2001 ; Hill et al., 2013 ). The possible discrepancy between what is measured with outcome questionnaires and what is meaningful in patients' daily life has been problematised: a patient's outcome score might fall within the non-clinical range while it does not reflect the person's functioning ( Kazdin, 2011 ). Real-life contextualisation is necessary in order to make sense of what changes in scores (or the lack thereof) actually mean for an individual ( Blanton and Jaccard, 2006 ; Kazdin, 2006 ). The latter is typically missing in large sample standardised outcome studies, and consequently, the dissemination of research findings into clinical practice generally fails ( Kazdin, 2008 ).

The past decades have seen an accumulation of qualitative studies attempting to contribute to overcoming this research-practice barrier, gradually offering a more central role to the voice of patients ( Levitt et al., 2016 ). Qualitative research focusing on patients' experiences of outcome has provided a diverse picture of treatment-related changes ( McLeod, 2011 ). Apart from symptomatic changes, alterations on the level of patients' self, life, interpersonal relations, and self-understanding have been observed (e.g., Binder et al., 2009 ). The largest strand of qualitative psychotherapy research has focused on patients' experiences of therapy, aiming to identify helping and hindering aspects ( McLeod, 2013 ). Hindering elements in therapy that have been mentioned by patients are contra-productive therapist features (e.g., being unsure, absent or non-responsive, lack of direction and advise in therapy), patients' own difficulties to express or get in touch with their feelings and lack of commitment and motivation, and a lack of trust between patient and therapist ( Paulson et al., 2001 ; von Below and Werbart, 2012 ) and so forth. On the other hand, a joint exploration of difficulties and experiencing warmth, understanding and empathy in the relationship with the therapist were found to be helpful for patients ( Timulak and Lietaer, 2001 ; Lilliengren and Werbart, 2005 ; Bohart and Wade, 2013 ).

Interestingly, findings from qualitative outcome studies shine a somewhat more pessimistic light on psychotherapy outcome than is typically observed in quantitative studies. In general, patients tend to be more critical about therapy during interviews, for instance, expressing disappointment about unaltered core problems or ambivalence about the gains of therapy ( McLeod, 2013 ). Moreover, research findings suggest that, patients' treatment satisfaction does not correspond to changes in outcome scores. Werbart et al. (2015) , for instance, observed that only three out of twenty patients with a nonimproved or deteriorated outcome also clearly indicated to be dissatisfied about treatment.

Nonetheless, the association between quantitative and qualitative evaluations of therapy and outcome remains unclear ( Timulak and Creaner, 2010 ). Mixed-methods studies have amassed in the past couple of years, though whether and how patients' experiences correspond to quantitative outcome evaluation is underexplored ( McLeod, 2013 ). The few studies that have been executed differ in the extent to which qualitative and quantitative findings show an accord (see Svanborg et al., 2008 vs. Klein and Elliott, 2006 ). The study of McElvaney and Timulak (2013) found only little differences between patients classified as “recovered/ improved” and “unchanged/ deteriorated” regarding their experience of therapy. As the strict demarcation of “poor” and “good” outcome does not appear in qualitative inquiry, questions can be raised about how representative such a statistical distinction is for the clinical meaning of outcome for individual patients (see Lambert and Ogles, 2009 ).

So far, the meaning of negative or poor outcome—distinguished by means of standard outcome measures—in relation to patients' subjective experiences, remains underexplored. As non-improvement and worsening are likely distinct phenomena with potential different clinical implications ( Mohr, 1995 ; Lambert, 2011 ), more focused investigations are required in order to grasp the phenomenon of non-improvement (in contrast to the approach of McElvaney and Timulak, 2013 , who studied unchanged and deteriorated cases together). In past endeavours, most of the studies have focused on deterioration or other “extreme cases,” yet little attention has been allotted to understanding treatment nonresponse or patient non-improvement specifically ( Lambert, 2011 ). Given the observation that lack of improvement occurs in a significant number of cases, and considerably more frequently than deterioration, this lack of attention is striking ( Lambert, 2007 , 2013 ). Importantly, gaining a better understanding of cases who seemingly have not moved forward or backward, will contribute to a more thorough and nuanced understanding of treatment-response and outcome in general. More specifically, this nuanced understanding is pivotal to elaborate the clinical meaning of outcome for patients themselves.

The integration of multiple methods and specifically the comparison of quantitative and qualitative methods is an indispensable development for the field of psychotherapy research ( McLeod, 2013 ; Bowie et al., 2016 ). The current study therefore provides a mixed-method analysis of patients suffering from major depression. Major depression is one of the most prevalent mental disorders worldwide ( WHO, 2017 ), and previous research has shown symptomatic evaluation of change alone cannot live up to the task of representing depressed patients' experience of outcome ( Zimmerman et al., 2006 , 2012 ). Based on this representative case, the present study aims to complement quantitative pre-post outcome scores indicating no reliable change in depression symptoms with a qualitative inquiry of depressed patients' perspective. In doing so, we move beyond the level of description (i.e., a lack of change in symptom scores) and toward a level of in-depth understanding (i.e., patients' subjective experience). Finally, instead of adopting a single focus on experiences of outcome or experiences of therapy, the present study aims to understand their interrelation as well as the broader context of potential influences, as these are typically not limited to therapeutic features alone ( Drisko, 2004 ; De Smet and Meganck, 2018 ).

The current study investigates how non-improvement in pre-to-post symptom severity can be understood in relation the experience of depressed patients themselves. We examine: (1) which potential changes patients have experienced and which factors can help to explain these changes from their perspective; (2) which potential issues remained and which factors can help explain these remaining issues according to patients; (3) how patients' perspective on non-improvement relates to the quantitative outcome evaluation of non-improvement (or no reliable change) in symptom severity. For the purpose of the study, the term “non-improvement” is used to indicate a specific definition of negative or poor outcome in accordance to the widely used statistical concept of a lack of reliable change in outcome scores (cf. Jacobson and Truax, 1991 ). We use this categorisation as a starting point to be able to broaden this influential framework of understanding, by nuancing it based on patients' perspectives.

Methodology

An explanatory sequential mixed-methods study was conducted, comprising a quantitative pre-post outcome evaluation as well as a qualitative analysis of nonimproved patients' perspective. The study is “explanatory” as the focus is on understanding non-improvement in-depth, and “sequential” because, even though quantitative and qualitative data were gathered simultaneously, both strands were analysed independently and integrated at the phase of interpretation. The design can be summarised as “quan → QUAL”: The qualitative analyses build on the quantitative outcome evaluation yet becoming the most important focus of the explanatory study; “the quantitative study (quan) is in service of the more dominant qualitative (QUAL) one” ( Hesse-Biber, 2010 , p.71). In the current study, a first phase comprised a quantitative outcome evaluation, based on which the target sample was selected. In a second phase, the corresponding interviews were qualitatively analysed. Integration and comparison of the two strands allowed for a better understanding of both the quantitative and qualitative outcome findings. Given the aim for in-depth exploration of patients' experienced changes, as well as understanding of the processes and factors that may explain those experienced changes, a grounded theory approach was selected as method of choice for the qualitative analyses ( Strauss and Corbin, 1990 ). Grounded theory can be used to provide description and interpretation, with the aim to generate conceptual models that can consecutively be translated into further hypotheses ( Fassinger, 2005 ; Charmaz, 2014 ). For our purposes, thus, this method seemed well-suited to build a thorough understanding of negative outcome and non-improvement from patients' perspective.

This study is based on data from the Ghent Psychotherapy Study (GPS), an RCT on the treatment of major depression; the trial has been registered on Open Science Framework (ISRCTN 17130982). For a specific description of the GPS context and methodology, we refer to the pre-registered study protocol ( Meganck et al., 2017 ). Patients in this study were recruited via social media and general practitioners in the area of Ghent, Belgium. Patients included in the study qualified for a diagnosis of Major Depressive Disorder, measured by the Rating Scale for Depression ( Hamilton, 1967 ) and Structured Clinical Interview for DSM-IV-TR ( First et al., 2002 ), both well-established and frequently used interview-based instruments in depression studies ( Nezu et al., 2000 ). The assessment interviews were conducted by six postgraduate research assistants trained in the respective procedures. Further eligibility criteria were sufficient knowledge of the Dutch language and age between 18 and 65; patients with a primary diagnosis of substance abuse, acute psychosis and suicidal ideations were excluded. Patients were randomly assigned to time-limited Cognitive Behavioral Therapy (CBT) or Psychodynamic Therapy (PDT). Patients progress was evaluated using questionnaires accompanying every session, interviews were conducted prior to treatment, around the eighth session and after treatment termination. The follow-up period of the study spans 2 years (ongoing) and consists of 4 interviews and quantitative assessment. This study was approved by the Ethical Committee of the University Hospital of Ghent University (Belgium; EC/2015/0085). All participants gave written informed consent in accordance with the Declaration of Helsinki.

Treatment consisted of CBT and PDT for major depression, two types of therapy that can be distinguished based on their directive (i.e., CBT) and exploration (i.e., PDT) style of interventions. Therapy was provided by one of four therapists in each approach. Both treatments were manualised and time-limited, consisting of 16–20 sessions. Treatment was delivered with an average frequency of one session per week; sessions lasted approximately 45 min. The CBT manual was based on the Cognitive-Behavioral Protocol for Depression by Bockting and Huibers (2011) . The PDT manual was based on the Supportive-Expressive Time Limited manual for Major Depressive Disorder by Luborsky (1984) and Leichsenring and Schauenburg (2014) . Therapists had an average age of 33 ( SD = 9.6) and had 3 to 8 years of relevant clinical experience and training in CBT or PDT. In the study, all therapists received 2 days of training, one patient to practice the treatment manual and the research procedure under supervision, and bi-weekly supervision sessions throughout the study.

Instruments

Beck depression inventory.

The Beck Depression Inventory (BDI-II-NL; Beck et al., 1996 ; van der Does, 2002 ) 2 is a measure of self-reported depression severity. The questionnaire consists of 21 items that are scored on a scale of 0 to 3 and is divided into a cognitive, somatic and affective subscale. A total score between 0 and 13 indicates minimal depression, 14–19 mild depression, 20–28 moderate depression, 29–63 severe depression. The questionnaire shows good validity and reliability ( van der Does, 2002 ).

Semi-structured Interview

An adjusted version of the semi-structured Client Change Interview (CCI; Elliott et al., 2001 ) was administered. The interview guide was constructed to evoke participants' experiences of therapy, the changes they believe occurred during therapy, and what they believe influenced these changes, for instance, helping and hindering aspects of therapy. Every interview started with the open questions: “How are you doing in general?” and “How are you feeling compared to when you started therapy?” Subsequently, patients were asked more specifically about experienced changes: “Which changes have you noticed since the start of therapy (e.g., in relation to others, at school/work, in your emotional wellbeing)?” and the role of therapy or other factors: “How did therapy contribute to these changes?” and “What other factors (outside of therapy) do you think have contributed to these changes?” Patients were also explicitly asked about negative changes or lack of change: “Is there something that did not change or that you would like to change in the future?”; “Did something change in a negative sense during therapy?” All interviews were conducted at the psychology department (Ghent University, Belgium) in the week following therapy termination. Interviews lasted 60 min on average. Interviews were audiotaped, and transcripts were analysed using Nvivo 11 (QSR International).

Quantitative Outcome Classification on the BDI-II-NL

Participants were classified in terms of reliable change and clinically significant change based on the Jacobson and Truax (1991) method for outcome classification. Patients self-reported symptom severity was measured prior to therapy and 1 week after treatment ended. The outcome scores of the patient population were compared to Dutch norms ( van der Does, 2002 ). In order to reach reliable change for the BDI-II-NL total score, a person must show a decrease in scores equal to or larger than 9.6. The cut-off between the clinical and nonclinical population for the Dutch BDI is set at 11.3 (based on the internal consistency of 0.92; van der Does, 2002 ). This leads to four possible outcomes: Clinically significant change (CS; a decrease in scores equal to or larger than 9.6 and post-treatment score below 11.3), reliable change (RC; a decrease in scores equal to or larger than 9.6), no RC (a decrease or increase in scores <9.6) and deterioration (an increase in scores equal to or larger than 9.6). In the total sample of the RCT ( n = 94), 31.9% ( n = 30) of the patients changed clinically significant, 20.2% ( n = 19) changed reliably, 23.4% ( n = 22) remained unchanged and 3.2% ( n = 3) deteriorated in scores on the BDI-II-NL; 21.3% ( n = 20) had missing outcome data (see Figure 1 ).

Figure 1 . Flow chart of sample selection.

Participants

For the current study, patients showing no reliable change in pre-to-post outcome scores on the BDI-II-NL ( van der Does, 2002 ) were included. We did not incorporate deteriorated patients based on the assumption that non-improvement and worsening are distinct phenomena with potential different clinical implications (cf. supra; Mohr, 1995 ; Lambert, 2011 ). For the same reason, we excluded patients who ended treatment prematurely (i.e., drop-out from treatment), which was defined as the patient-initiated premature termination of therapy within four sessions of treatment (in line with other commonly used definitions of drop-out; Wierzbicki and Pekarik, 1993 ; cf. Barrett et al., 2008 ) This resulted in the selection of 19 participants. The flowchart in Figure 1 gives an overview of the selection process for this study. The sample consisted of 12 women and 7 men ranging in age from 21 to 59 ( M = 34; SD = 10.7). All patients were born in Belgium except for 1 patient who was born in the Netherlands; 1 patient had a parent of foreign origin. Table 1 gives an overview of the demographic information per patient. During the study, 8 patients received CBT; 11 patients received PDT. Patients' average treatment duration was 17 sessions (range 6–20 sessions). All patients were diagnosed with major depression prior to treatment (comorbid Axis I diagnoses as assessed using the SCID for DSM-IV-TR are presented in Table 1 ).

Table 1 . Demographical information of patients in the sample.

Grounded Theory Analysis

Grounded Theory ( Glaser and Strauss, 1967 ) can be described as an explorative and interpretative qualitative research method, aimed at the construction of new theories or rationales grounded in data (in our case patient interviews) ( Fassinger, 2005 ; Charmaz, 2014 ). Using this method, a tentative conceptual model of non-improvement that comprises patients' experienced changes and explanatory factors was created Characteristic of grounded theory, several stages of analysis were completed in a cyclic manner before arriving at the final conceptual model ( Mortelmans, 2013 ). This form of inquiry enabled the exploration of the phenomenon of non-improvement in the participants' terminology and to identify themes in the data in a bottom-up manner. As the interviews were conducted in the context of a larger study, the interview questions were not altered throughout the data gathering process as is often the case in grounded theory analysis.

Prior to the actual coding of the interview transcripts, the first author wrote a vignette about every participant that included demographic information, treatment duration, pre-post outcome scores and a summary of the most important themes addressed in the interview. The vignettes were used to get an initial idea of the individual cases in the sample prior to the analysis. During later stages, the first author repeatedly reread the vignettes to validate the constructed model and conclusions with the individual cases. The interview transcripts were subsequently analysed by the first author in dialogue with the third author; the second author functioned as an auditor throughout the process ( Hill et al., 1997 ).

Open Coding

Open coding is defined as “the analytic process through which concepts are identified and their properties and dimensions are discovered” ( Strauss and Corbin, 1990 , p. 101). In this phase, the interviews were first read and reread to identify relevant parts of the interviews relating to the research questions (cf. selecting meaning units; Giorgi and Giorgi, 2003 ). Labels were attached to certain parts of the text, differentiating experienced changes/remaining issues from therapy factors and other mentioned influences. Non-relevant parts, i.e., not dealing with the topic of well-being, experienced changes or therapy, for instance, were omitted. In order to prevent relevant information from being omitted during the coding process, this work was first conducted on printed versions of the interview transcripts and repeated in the Nvivo software package. This phase resulted in a first list of codes that were formulated with the intent to remain close to the narrative of patients. A first rough classification was made between the various codes (i.e., experienced changes, remaining issues, therapy effects, social context). They were discussed between the first and third author and altered until consensus was reached.

Axial Coding

Axial coding can be summarised as “the process of relating categories to their subcategories termed ‘axial' because coding occurs around the axis of a category, linking categories at the level of properties and dimensions” ( Strauss and Corbin, 1990 , p. 123). In this phase, the various codes were further divided into subcategories in order to refine the first initial classification of codes. In dialogue between the first and third author, the resulting codes were thematically connected and where needed rephrased. At the end of this phase, the first author looked for visual images and metaphors that could help to grasp the central categories and mechanisms emerging from the narratives of the patients (e.g., “stuck in a maze”; “impasse”). These were further developed and refined in the next phase.

Selective Coding

Selective coding comprises “the process of integration and refining the theory” ( Strauss and Corbin, 1990 , p. 143). In this phase the theory was cultivated by creating a core category and building other categories around it. In discussion with the third author, this theory was refined. The second author audited the selection of the core and subcategories by asking critical questions regarding the rationale behind the extracted central mechanism. At the end of this phase a set of subcategories was created based on the entire nonimproved sample. Subsequently, we looked into the frequencies of the different categories represented in the CBT and PDT group in order to unravel therapy-related differences. These were included in a detailed table. After finalising the theory, adequate and valuable phrases were chosen to describe the categories and informative quotes were selected to illustrate the various categories and their interrelations and influences. Patients were given a letter of the alphabet to anonymise text fragments (i.e., from A to S).

Credibility

Credibility checks were held at several stages of the analysis. At the end of every interview, patients were asked whether they wanted to add further information that had not been addressed in the interview. During the analysis, we tried to remain transparent about the entire process ( Stiles, 1993 ) and we acknowledge the influence of the perspective and background of the researchers. The researchers' personal interest in patients' idiosyncratic perspective for instance instructed the focus of the study and analysis. Potential consequences of implicit guiding assumptions were controlled as much as possible by making this idiosyncratic focus central to our study ( Creswell and Miller, 2000 ). We furthermore departed from the assumption that “non-improvement” can also include changes, therefore this was explicitly integrated in our research questions. We worked in a systematic manner to form conclusions and interpretations ( Stiles, 1993 ) and attempted to stay open for any information coming from the narratives throughout the entire process. The analysis aimed at outlining macro-processes in psychotherapy, i.e., examining a wide angle rather than micro-processes (e.g., specific therapeutic effects) and investigated the subjective experience of several different participants (i.e., between-case variation) ( Denzin and Lincoln, 2005 ). In line with our research aim to investigate therapy and outcome in a broader context, the analysis and interpretation of patients' narratives were conducted using a contextual perspective that departs from the assumption that the broader social context influences how patients give meaning to their experiences ( Boyatzis, 1998 ). Triangulation among researchers, several interviews, and quantitative and qualitative indications of outcome were applied to gain different perspectives on the issue. The ultimate themes were formed by asking critical questions regarding codes and categories ( Mortelmans, 2011 ).

In this section, we will present the quantitative pre-post outcome data and qualitative analysis of patients' experiences respectively. Interpretations of the quantitative and qualitative findings will be described separately; broader integrative conclusions and implications will be presented in the discussion.

Descriptive Pre-post Outcome Scores on the Beck Depression Inventory

Table 2 summarises the average score on the BDI-II-NL ( Beck et al., 1996 ; van der Does, 2002 ) before and after treatment, the standard deviations (SD) and range in scores (i.e., minimum and maximum score) for the entire nonimproved sample, the PDT and CBT group.

Table 2 . Pre-post outcome scores on the BDI-II-NL.

Both at the start and end of therapy, the non-improved patient group is characterised by a wide range in scores. At the start of treatment, patients scores varied between moderate depression ( n = 10) and severe depression ( n = 9) (cf. van der Does, 2002 ). At treatment termination, 1 patient scored mildly depressed, 9 scored moderately depressed and 9 others scored severely depressed. The average score both before (30) and after (30) therapy indicate severe depression for the total sample, although at the borderline of moderate depression. All patients remained in the clinical range and did not change reliably in scores compared to the start of treatment.

Conceptual Model of Non-improvement From Depressed Patients' Perspective

The grounded theory analysis of nonimproved depressed patients' narratives resulted in the core category Stuck between “knowing vs. doing .” Around this core category, a model was constructed consisting of 10 subcategories that help to explain this core concept. The subcategories are divided into the changes and remaining issues patients mentioned and the positive and negative influences patients ascribed these changes/remaining issues to. These influences are referred to as “explanatory factors” and specified as “facilitating factors” and “impeding factors.” Figure 2 depicts the conceptual model: The left part of the model comprises positive changes and facilitating factors, the right part of the model shows remaining issues and impeding factors. Table 3 summarises all core and subcategories in more detail for the entire nonimproved sample, the PDT, and CBT group. The frequencies of patients contributing to each category were added.

Figure 2 . Conceptual model of non-improvement from depressed patients' perspective.

Table 3 . Taxonomy of non-improvement based on depressed patients' perspective.

Core Category: Stuck Between “Knowing vs. Doing”

The central mechanism for understanding non-improvement from the patients' perspective is “knowing versus doing”: A feeling of having acquired certain changes yet being unable to go a step further, or to know what the problem is but feeling an incapacity to do deal with it. In general, patients wanted to move forward but felt unable to. Some patients stated this literally: “Rationally I know what my problems are or what I should do, but there is just nothing changing.” At the same time, the core category captures the effects of therapy that on the one hand facilitated patients' self-understanding and mental stability, but on the other have not been able to overcome certain barriers. A plus (for positive changes and positive influences) and minus (for remaining issues and negative influences) seem to cancel out each other, resulting in a stalemate.

“I have learned a lot, I have gained many insights. (…) I am not as despondent anymore, but if I say that ‘not that much has changed' I mean, I still have difficult periods and a few fundamental problems, which I do understand better now, are not really solved yet, or maybe they are not easy to solve. So, I know much more, I have improved on the level of knowing, but not so much on the more practical level.” (Patient C., CBT)

Positive Changes

The overarching experience of being stuck does not imply that patients have not experienced changes at all. Two themes resulted from the analysis showing that throughout the process of therapy, patients have grown mental stability and strength ( n = 14) and have gained more insight ( n = 15). Moreover, these changes seem interconnected, as increased understanding was said to have influenced patients' personal strength. In the model in Figure 2 , this is indicated by a dotted line (showing interconnection) and an arrow from “Insight” to “Mental stability and personal strength.”

“In general, I feel much stronger, mentally. I have gained many insights in therapy. (…) It gave me peace of mind and recognition that okay, my thoughts, experience and things I long for are not that strange.” (Patient J., PDT)

Mental stability and personal strength

Increased mental stability ( n = 11) consisted of two subthemes: A more positive state of mind ( n = 9) and the ability to accept and let things go (n = 6). Patients had learned to deal with certain situations, they felt less emotionally overwhelmed and believed they could handle challenges better. Patients' personal strength ( n = 11) consisted of an increased self-confidence ( n = 11) and being more vigorous ( n = 9). Patients felt more active, dared to socially interact and felt less anxious and insecure.

Interviewer: “So you say you are mentally not dispirited anymore. Can you explain the difference with before?”

Patient: “I think that before I was really struggling with myself, my self-image and now I feel more balanced. I can take a distance. The fights [with partner] are still intense, but I relate it to the relationship now, I've stopped blaming myself.” (Patient Q., CBT).

Increased insight was described on three levels. Patients were able to see things from a different perspective ( n = 9), understood themselves better ( n = 8) and had gained insight into the reasons why they experienced difficulties ( n = 8).

“Therapy made me reflect upon things and gave me some different ideas about situations that were clear to me but might not have been that clear after all or that needed to be looked at from a different perspective.” (Patient A., PDT).

“I have learned more about myself. I already knew I was stubborn, but we talked about it a lot [in therapy], about how I set my standards very high and I don't accept help from anyone and that, by this, I make life very difficult for myself.” (Patient H., PDT).

Facilitating Factors

The facilitating factors contributing to these positive changes according to patients include the role of therapy, the therapist and the patients' social and professional context. As indicated in Figure 2 by unidirectional arrows, these features were described as contributing to patients' mental stability and strength as well as insight.

Therapy offers self-reflection and guidance

Patients in CBT and PDT presented slightly different experiences of therapy. These differences seem in line with the specific nature of both types of therapy, given the explorative and expressive style of PDT and the directive approach in CBT. Especially in the PDT group, weekly therapy sessions were considered important for being able to talk, express feelings and thoughts ( n = 6) and therapy was seen a as a weekly moment of self-reflection ( n = 11). This seemed to have stimulated both patients' insight (cf. self-reflection) and mental stability and strength (e.g., letting things out; relief).

“By saying things out loud in therapy, you start reflecting on them and it becomes a reality that does not only exist in your head. We had one session where the therapist asked some questions about my relationship and because I really did not want to answer them, I started wondering, how I really feel in this relationship, I realised that wasn't very good.” (Patient B., PDT).

In the CBT group, similar aspects were mentioned ( n = 4), but therapy was also valued for actively providing patients with insight and practical help ( n = 5), making the facilitating role of therapy more guiding than reflective.

“She [the therapist] helped me to take certain steps. We tried to come up with means to…, like a priority list for my day, because it is difficult for me to…, although I know I have to do lots of things, I'm not organised.” (Patient R., CBT)

Benevolent therapist approach

Patients in both therapy groups ascribed important changes more to the therapist's way of being than to the therapy form as such. Therefore, we explicitly describe therapy and therapist separately, even though the factors are clearly intertwined. This reciprocity is indicated in the conceptual model ( Figure 2 ) by means of a bidirectional arrow. Firstly, a good therapeutic relationship was described by the majority of patients ( n = 16) as making it easier for them to talk and open up. More specifically, patients valued that the therapist did not judge but rather encouraged and acknowledged them ( n = 10). Secondly, the therapist had the skill to ask the right questions ( n = 15) that stimulated reflection and provided patients with a different perspective. The previously discussed themes “insight” and “mental stability” were described as influenced by this approach of the therapist. Although the therapist was mentioned as important in both CBT and PDT, the nature of the experienced role of the therapist's different: In PDT, the therapist was described as stimulating a mental process that was ongoing for the patient, while the CBT therapist was characterised as being an active participant or initiator in the therapy sessions.

“His questions, they often appeared so innocent, but when you think about it afterwards you see things from a different perspective. Very subtle because he does not tend to give his own opinion.” (Patient C., PDT).

“After a few sessions, my therapist came up with a scheme that summarised my life until now and where my anxiety comes from. I remember I had to cry for the first time. I noticed how good it felt to finally be understood. I still believe he can help me in the process of accepting it [certain life events].” (Patient S., CBT).

The context as an important impetus

Besides therapy and the therapist, patients mentioned the influence of their social context as a third facilitating factor. Significant others appeared as an important motivation to do something about problems, to find a job or to keep on going ( n = 11). For some patients, it had been important to be at home for a while (with sick leave) and to have the time for themselves in their own space ( n = 10). For others ( n = 5), work (i.e., the professional context) was an important support mechanism, as it gave them a reason to get up in the morning and structure to their day. The motivating context was therefore considered a facilitating factor for patients' mental stability and personal strength and seemingly a potential stimulus for engaging or continuing treatment.

“My son is one of the reasons for starting and continuing the course [i.e., education]. I want to be able to show him something, instead of being an unhappy person. I want to give him something, something positive. That's actually the only valuable thing in my life that's left. I used to be so materialistic, now the only thing that matters is him.” (Patient L., CBT).

Remaining Issues

Despite the positive changes in mental stability, personal strength and gained insight, certain issues remained. Feeling stuck was characterised by the wish or ambition to change yet feeling unable to do so. A reciprocal arrow between the categories “Ambition to change” and “Inability to change” represents this equilibrium.

Ambition to change

The majority of the patients experienced an ongoing struggle and carried hopes for further change ( n = 13). These aspects implied things they believed they still lacked or they should work on in the near future, such as tackling self-criticism and self-discipline.

“I wish I could have a more positive stance in life, to be able to counter my negative thoughts. I want to have the discipline to get things done, but the hours just slip away, I see the days pass by without getting anything done. That's wasted time to me. I want to get a grip of it.” (Patient I., PDT)

Inability to change

In spite of and seemingly in conflict with the ambition to change is an overall feeling of inability ( n = 13). Patients felt as if they were running behind on things, they lacked initiative and could not force themselves to move forward.

“I'm just not on top of things. I constantly feel rushed, but I lose so much time. Searching for things, not able to finish things because you are too distracted. I just can't seem to get out of it. Things pile up, it seems that for every problem I solve I get two in return” (Patient P., CBT)

Some patients described an inescapable cycle they seemed to repeat over and over again ( n = 3). This inability was also reflected in what seemed like an internal conflict ( n = 7), for instance, being stuck in the struggle between wanting to spend more time with the kids but at the same time aspiring for a professional career. One patient was highly preoccupied with a long-lost dream, which made it impossible to pursue a new goal in life.

Impeding Factors

Similar to the factors that help explain positive changes, patients brought up potential reasons for why certain issues remained unchanged. These factors include the limits of therapy, the role of the patient and a negative influence coming from patients' social context.

Therapy hits its limits

Notwithstanding its positive effects, therapy was described as hitting a limit by all patients. More specifically, advise or learned techniques were considered valuable, yet only up to a certain point. Patients stated that they were unable to use the techniques when feeling really bad, or they did not find the time to do so. For others, therapy had progressed too slowly, had not been valuable every session, or it had worked for some aspects but not for others. Therapy hit a limit in two ways: Something was missing in therapy ( n = 12) and/or the therapy mismatched the patient's needs or expectations at some point ( n = 17). Noteworthy is the observed difference between the PDT and CBT group. A few patients in PDT were displeased that they had not gained the right tools, were not given any directions ( n = 4) or stated therapy had a varying impact (sometimes it helped, sometimes it did not) ( n = 3).

“I expected her [the therapist] to give me good advice on how to deal with my problems. How I can worry less, how I can improve my breathing, just some tips. I must have imagined therapy the wrong way, she did not give me any tips. I'm kind of disappointed. (…) I still don't understand the purpose of talking about all these things, I often felt worse after the session.” (Patient G., PDT).

Some patients in the CBT group, on the other hand, stated therapy was too superficial and they needed a more intense form of treatment ( n = 5).

“The first three to four sessions, you tell your whole life story and all that is said about it is just okay, ‘you suffer most from the discussions [at home/with your partner] so let's see how we can handle them.' While I thought okay, I just told you my entire life story, about who I am and how I became who I am, that could have been included in therapy, but I actually felt that it wasn't at all, we just looked at one segment.” (Patient Q., CBT).

Moreover, therapy as hitting its limits seems to have contributed to a rather ambivalent attitude toward possible continuation of therapy ( n = 11). One third of the patients had no further need or motivation to continue psychotherapy ( n = 8). Some of them believed they had dealt with everything or had gotten everything out of therapy that they could, others had lost hope that therapy could help them or were disappointed about the results. Half of the patients indicated they would continue the same therapy, because they felt committed to the process ( n = 6) or because they had further specific issues they wished to address ( n = 4). Others, however, were interested in pursuing a different kind of therapy ( n = 7).

The patient's resistance and impossibility

Patients also reflected on their own role and position in therapy. Most patients described feeling a certain resistance toward therapy ( n = 16). For instance, they did not take therapy very seriously, had difficulties with opening up or were reluctant to do certain exercises. Several patients saw therapy as a task or an investment that asked too much from them (e.g., energy, time, money) ( n = 6). This rather ambivalent position in therapy was, for instance, described by patient R:

“I was afraid to fail in therapy. (…) I typically start things but can't manage to continue them. Maybe because (…) when it hasn't gone well one day, I can't let that go. It is all or nothing often, so I was afraid I would not do very well [in therapy] and also, sometimes I put effort into it, but often I was busy doing other things I thought I should be doing, like work.” (Patient R., CBT).

Secondly, many patients were convinced about the fundamental nature of their problems and the impossibility to change ( n = 15), sometimes referring to their own personality. Moreover, some patients indicated that therapy of 20 sessions is in general too little to solve more fundamental problems. The patient's resistance and idea of impossibility seem to correspond to the perspective on therapy as hitting a limit. In Figure 2 this was indicated by means of a reciprocal arrow, assuming a certain reciprocity between both explanatory factors.

“I think I'm quite a different case, I have quite a big tendency toward depression, if I compare myself to other people in my environment who have depression, they get over it after a year, but I think for me this is a bit more difficult, because of my childhood…I have been conditioned to think in a certain way, I think that matters a lot [for the duration and effect of therapy].” (Patient O., CBT).

Despite a mismatch, some patients described they were able to get passed initial resistance and adjusted to therapy, while for others, the limits of therapy, their own resistance or feelings of impossibility lasted throughout the therapy process.

“I might have expected therapy to be a bit more practical, but I noticed quite fast that this wasn't the goal of the sessions and I accepted that, I didn't see the talking as a waste of time” (Patient I., PDT).

“So, I think ‘okay, therapy has ended now and once again I'm nowhere, it did not help, and it only cost me money, a lot of time and energy, and why? For nothing.' (…) Of course, I know I did make progress, but I it's hard for me to see it that way. I just think, ‘it's the umpteenth thing I've tried and what is the use?”' (Patient P., CBT).

The context as a source of distress

Several contextual factors were mentioned as having a negative influence on patients' wellbeing during and after therapy. Firstly, patients' personal context was mentioned as being highly stressful ( n = 16). Several patients, for instance, encountered a conflict with family members ( n = 6). These difficulties in relationships were often considered to facilitate or perpetuate certain problems, and consequently they were believed to have influenced the therapy process and patients' progression. Patient F., for instance, described a critical moment in course of therapy:

“There was a crisis [during treatment]. It was when I just started working there [family business], it became too much with how my brother-in-law always got angry with me. I could not handle it. He yelled at me that I was making him bankrupted, I cost a fortune, I don't work well, I'm too slow. At a certain point I switched off my phone and just ran away, I wanted to disappear, commit suicide.” (Patient F., PDT).

Secondly, the professional context appeared as a source of stress or dissatisfaction ( n = 9). This subtheme contains patients who experienced high amounts of stress due to school-related deadlines, had difficulties adjusting to a corporate culture (e.g., not able to handle the given freedom) or did not experience any fulfillment at work. Finally, many patients mentioned external factors causing distress, like certain events or circumstances ( n = 12), for instance, dealing with unexplainable physical complaints and an ongoing lawsuit. The reciprocal arrow in the conceptual model between the patient's resistance and impossibility and stressful context indicates that both factors are understood as interacting and influencing the therapy and recovery process.

This study investigated the phenomenon of non-improvement in psychotherapy from the perspective of depressed patients in relation to their pre-post outcome scores showing no reliable change. By doing so, we answered the pressing need for further investigation of the phenomenon of negative outcome and the exploration of the relationship between quantitative and qualitative approaches to outcome and treatment evaluation in the field of psychotherapy ( McLeod, 2013 ).

First and foremost, the findings of this study showed that non-improvement as indicated by symptom-based outcome scores did not mean that patients did not experience any changes. Where a lack of change in outcome scores means a status quo on the level of symptom-severity, the interviews of the patients revealed a more nuanced and complex picture. Central to patients' experience of non-improvement is the mechanism of knowing vs. doing. While patients had the ambition to change, they felt unable to overcome certain problems, resulting in a stalemate of knowing what to change but not being able to. Positive changes were offset by substantial remaining issues: Increased mental stability, personal strength and insights were gained, yet these did not result in changes on other levels of patients' lives. From the patients' perspective, “no change” in symptom-based outcome scores seemed to be “not enough” change or a “partial change.” The therapy, the therapist, the patient and context facilitated positive changes but at the same time were unable to alter important issues or even impeded patients' progression (resulting in remaining issues). None of these factors can be considered the main or only explanatory reason but must be understood as interacting (cf. Mash and Hunsley, 1993 ; Werbart et al., 2015 ). In sum, an equilibrium between a positive and negative pole seems to characterise the depressed patients' experience of non-improvement.

A similar positive-negative balance has been observed by Werbart and colleagues in a study on non-improved patients' experience of psychotherapy (2015). Nonimproved patients perceived their therapy as “spinning one's wheels”: Therapy was valued for some aspects but disappointing on others and even though some changes occurred, core difficulties remained. The current study investigated nonimproved patients' experiences of outcome and therapy in a broader context of various potential explanatory factors (i.e., not limited to the effects of therapy). In that sense, the findings of this study and the study of Werbart et al. (2015) can be seen as complementing each other, also because different populations of patients were investigated (i.e., adults and young adults). Notably, the experience of both outcome and therapy are strongly congruent in reflecting a balance between a plus (i.e., positive changes and facilitating factors) and minus (i.e., negative changes/remaining issues and impeding factors).

The positive pole of the resulting conceptual model in this study, including increased mental stability, personal strength and insight, corresponds to findings of other qualitative outcome studies. Mental stability and personal strength relate to what has been described as feelings of empowerment and improved emotional functioning ( McElvaney and Timulak, 2013 ), and more generally, as changes on the level of the self ( Timulak and Creaner, 2010 ). Strikingly and in contrast to findings from studies on patients' experience of positive outcome, our nonimproved sample did not report changes on an interpersonal level ( Nilsson et al., 2007 ; Binder et al., 2009 ; Timulak and Creaner, 2010 ); reported positive changes were overall more self-focused. Indeed, we could wonder whether improvement on a symptomatic level enables or coincides with changes on a more interpersonal level. Regarding patients' gained insight, our findings seem partially in contrast to the commonly derived conclusion that insight is an important acquisition for obtaining positive outcome (see the recently published meta-analysis of Jennissen et al., 2018 ). In this study, increased insight facilitated patients' mental stability and personal strength, but it did not alleviate patients' self-reported symptoms or alter core difficulties. Similarly, Lilliengren and Werbart (2005) found that self-knowledge does not always coincide with changes in underlying problems. Qualitative studies suggest an important role for agency regarding this link between insight and outcome: Rather than gaining insight as such, it is important to gain the capacity to apply or act upon gained insight in daily life ( McLeod, 2013 ) 3 . Stage models of therapy (see for instance Hill, 2004 ), state that insight is only valuable to the extent that it leads to action. The absence of this active component could explain the lack of improvement on other levels in our research sample. As already stated by Freud, in order to gain substantial change, a step beyond intellectual insight toward experience might be required (see Bohart, 1993 ; Castonguay and Hill, 2007 ). More research on the mechanism of how insight promotes change is, however, warranted.

The helping role of treatment differed depending on the type of therapy. In accordance with the finding of Nilsson et al. (2007) , patients valued CBT and PDT for different reasons. In our study, therapy provided a moment of self-reflection for patients in the PDT group, while practical help and guidance was valued in the CBT group. Interestingly, while patients in both CBT and PDT mentioned the central role of the therapist, its specific effectuation differed seemingly. In line with the differentiation between the approach of the respective therapies, the PDT therapist was attributed a rather subtle though powerful technique stimulating reflection in patients. The CBT therapist, on the other hand, was considered an active participant in treatment who offered patients insight via tools such as schematic overviews. A good therapeutic relationship was one of the most important common factors in psychotherapy ( Lambert and Barley, 2001 ) mentioned by the majority of the patients in our study, similar to other qualitative findings ( Levitt et al., 2016 ).

Nonetheless, all patients stated therapy hit a certain limit. Again, in line with the observation of Nilsson et al. (2007) , both types of therapy were criticised on a different basis: In our sample, dissatisfied patients criticised CBT for being too superficial while PDT was criticised for not offering the right tools or direction. The latter corresponds to findings from the study of Lilliengren and Werbart (2005) , in which patients experienced similar disappointments in psychoanalytic therapy (e.g., wanting a more active therapist, guidance, feedback, and advice). A possible mismatch between certain patients' needs or expectations and the type of therapy supports the increasing emphasis in research to explore which type of therapy works best for whom and focus on the tailoring of treatment to patients' transdiagnostic characteristics ( Norcross and Wampold, 2011 ).

Beyond therapy hitting limits, patients in this study mentioned explicitly that they themselves encountered a certain resistance or hit their own limits and limitations. The patient's in-therapy behavior, such as client involvement and motivation, is the single most important predictor of outcome. Patient motivation has moreover been linked to expectations and hopefulness: Patients who do not believe they can change, and who feel hopeless, may have less motivation to participate in therapy ( Bohart and Wade, 2013 ). Accordingly, the participation in the therapy process seemed rather ambivalent in our sample. Notably, individual differences were observed: Some patients were able to get passed initial doubt about the therapy approach and their own ideas of impossibilities, while others did not. Although not mentioned by patients themselves, it is important to consider that many patients in the sample presented with one or more comorbid disorders, in most cases some kind of anxiety disorder at the start of therapy. Previous research has shown comorbidity in general predicts worse outcome (see Lambert, 2013 ).

Finally, our findings revealed the therapy process was intertwined with influences from outside the therapy room. Patients' personal context was both considered an important motivation as well as a large source of distress. Again, opposite effects facilitated and impeded changes. It has been outlined that the context plays a central role in sustaining involvement in psychotherapy or undermining this effort ( Lambert, 1992 ; Drisko, 2004 ). The impact of patients' professional context on their well-being mentioned in this study is in line with robust findings on the impact of job satisfaction on mental health ( Faragher et al., 2005 ). Whilst most qualitative studies tend to focus specifically on patients' experience of psychotherapy, our study provides a valuable additional element of contextualisation.

The resulting negative pole of the conceptual model of non-improvement, including the ambition yet inability to change, shows resemblance to what is considered a central characteristic of experiencing depression: Running behind on things, lacking initiative and motivation (DSM-5; APA, 2013 ). Feelings of hopelessness and helplessness were unresolved, in line with the remaining average score of severe depression in the sample. However, the question should be posed whether this feeling remained unaltered or rather emerged throughout the process of therapy, for instance, as a response to a lack of improvement. A pre-post research design, even when including retrospective inquiry of patients' experiences prior to treatment, falls short in answering this question. Longitudinal research that includes patients' experiences at the start of therapy as well as monitors changes throughout the process of therapy is needed (cf. De Smet and Meganck, 2018 ).

The contextual model of psychotherapy as described by Wampold and Imel (2015) , offers a valuable framework for interpreting our research findings. In this model, therapy is perceived as a “socially imbedded healing practice” (p. 258) in which the relationship between the therapist and patient is central. According to this model, three pathways lead to change in patients' wellbeing: The first pathway establishes the personal relationship (“real relationship”) between patient and therapist, characterised by genuine interest and empathy, the second pathways creates expectations in patients of being able to overcome their difficulties, and the final pathway includes therapy specific features or tasks. Although all three pathways lead to a certain degree of change, central for the therapy to work is that it can engage patients to follow the treatment rationale and overcome personal beliefs and explanations for distress.

Regarding the first pathway, the contextual model assumes that establishing a real relationship with the therapist leads to general well-being rather than symptom reduction ( Wampold and Imel, 2015 ). Correspondingly, we observed an increased mental stability and personal strength while patients remained unchanged on a symptomatic level. Patients' pessimistic expectations regarding improvement moreover remained unaltered and for many it was difficult to adapt to or engage in specific therapy features; the second and third pathway thus seem not (entirely) fulfilled. The dyadic concept of the patient-therapist working alliance ( Bordin, 1979 ) further demonstrates how “the collaborative purposive work” ( Hatcher and Barends, 2006 , p. 293) was obstructed by this discordance between patient and therapist or therapy; both by therapy not being able to meet patients' need, as well as by patients' resistance toward the requirements of therapy. This links up to the differentiation between two types of bonds: The work-supporting bond and personal relationship (cf. real relationship). The latter involves affective attachment, liking, trust and respect. The other type of bond is considered necessary for “the difficult work” in therapy, for instance dealing with affective or painful material or executing assignments like exposure and homework ( Bordin, 1979 ). This distinction helps to understand how, in our study, patients experienced a good therapeutic (or real) relationship but failed to engage in the work-supporting bond. Being at ease in therapy and feeling accepted and understood by the therapist thus seem important, for instance leading to increased well-being ( Wampold and Imel, 2015 ), mental stability and personal strength, though not enough to facilitate further life-changes. Correspondingly, gaining insight or self-understanding as such might not be enough when “the hard work” of dealing with affective material has not been worked through. While the contextual model ascribes most of the responsibility to the therapist, the current study and findings give more weight to the role of the patient and his personal context ( Wampold and Imel, 2015 ).

These findings yield a number of clinically relevant implications. Patients who find themselves stuck between knowing versus doing, may hit a certain limit due to a mismatch with the therapy offer, experiencing personal resistance or encountering difficulties outside of the therapy room. As these implications may be brought about by (idiosyncratic) underlying reasons, it may be worthwhile to take this as a particular clinical focus. In light of the increasing use of routine outcome measures in clinical care (see Boswell et al., 2015 ), a lack of changes in symptom severity could indicate any of these reasons and most likely a combination, yet monitoring instruments clearly require further exploration in dialogue with the patient. However, signs of non-improvement may not always be visible for the therapist. Studies have shown that therapists tend to underestimate negative outcome, as patients tend to keep dissatisfaction about therapy to themselves—possibly because they do not want to offend the therapist ( McLeod, 2013 ; Werbart et al., 2015 ). Therefore, it may be implicated to work on meta-communication in therapy, to avoid or restore possible ruptures in the therapeutic work and relationship ( von Below and Werbart, 2012 ). On the other hand, a well-established therapeutic relationship could change dissatisfaction about therapy into a negotiation, that is, an active focus point in therapy (cf. Wampold and Imel, 2015 ). In some cases, referring patients to a different approach that is more in line with patients' own rationale may be warranted ( Wampold, 2007 ), as what may work for 1 patient, might not work for the other ( Norcross and Wampold, 2011 ). Also, the optimal duration of treatment may differ among patients. In the current study, the number of sessions was fixed at twenty, which may have been too little to facilitate changes for some patients (e.g., the average “good enough level” has been estimated at 26 sessions; Barkham et al., 2006 ). Moreover, patients showing high levels of resistance in therapy may benefit from a less directive approach (see Beutler et al., 2002 , for an overview of the literature on resistance) in which therapy is adjusted to patients' own pace. This is supported by authors who warn that uniform time limits for treatment may not adequately serve individual patients' needs ( Baldwin et al., 2009 ).

This study addresses the critical concern about misrepresentation of patients' outcome by means of standard outcome evaluation and statistical classification ( Kazdin, 2008 ; Hill et al., 2013 ). First of all, no reliable change in outcome scores seemingly masked the significant changes experienced by patients and does not allow to represent the particular balance between remaining issues and positive changes. Furthermore, considering patients to be a uniform group based on a similar pattern of outcome scores might overlook important individual differences. None of the patients in our sample stated they were cured, although they did vary in the extent to which they experienced improvement and whether they wanted to continue treatment. In our study, the pre-post changes in outcome scores seem to give a rough preliminary indication of patients functioning, while the patients' narratives show non-improvement is more complex and diverse than can be grasped by a lack of symptom reduction (in line with Zimmerman et al., 2006 , 2012 ). This observation is not surprising in light of the complexity and heterogeneity of depression experiences ( Ratcliffe, 2014 ). It is plausible to assume that recovering from depression is at least equally diverse and layered (cf. von Below et al., 2010 ).

Consequently, the findings of this study shed light on the previously voiced question of how negative outcome and non-improvement should be conceptualised. In general, similar to previous research findings, patients' treatment satisfaction and negative outcome did not show a one-on-one correspondence ( Werbart et al., 2015 ); while all patients stated therapy hit a certain limit, a minority was also clearly dissatisfied. Mash and Hunsley (1993) have argued that “without a guiding theoretical framework for considering failing treatments, the assessment task is daunting, because almost any event in therapy might be construed as a possible indication that treatment is currently failing or is about to fail.” (p. 293). This study shows how this endeavour benefits from a mixed-methods research format that integrates a grounded theory approach. In line with the strengths of grounded theory ( Fassinger, 2005 ; Mortelmans, 2011 ; Charmaz, 2014 ), further theory-building research can mean an important contribution here (cf. Stiles, 2015 ).

Strengths, Limitations, and Future Directions

The implications of this study address the well-known gap between academic research and clinical practice ( Castonguay et al., 2013 ). RCTs as golden standard research format are limited in providing knowledge that can inform clinical practice ( Westen et al., 2004 ). The value of integrating qualitative research into this type of rigorous research has therefore been emphasised ( Midgley et al., 2014 ). The current study provides an actual example and informs both clinicians and research on the relationship between outcome scores and patients' experiences of non-improvement. It furthermore builds on the literature of helping and hindering therapy features ( Paulson et al., 2001 ; von Below and Werbart, 2012 ) by placing the experience of therapy in a broader context of potential explanatory factors as mentioned by patients.

The current study is one of few examining the relationship between quantitative and qualitative outcome evaluation of non-improvement ( McElvaney and Timulak, 2013 ; McLeod, 2013 ). Focusing on this particular subgroup rather than deteriorated or dissatisfied patients allows for the contribution to a lack of specificity in outcome research and the literature on negative outcome ( Lambert, 2011 ). Research suggests non-improvement, deterioration and patient satisfaction do not fully correspond, although they are often used interchangeably ( Lampropoulos, 2011 ). The current study gives an overall conceptual model of non-improvement and potential explanatory factors. Whether this is, however, representative for nonimproved depressed patients cannot be concluded. Further research should focus on investigating differences and similarities between various groups of outcomes (cf. recovery, improvement, no change, and deterioration; Jacobson and Truax, 1991 ) in order to get a better understanding of the clinical meaningfulness of change from the perspective of patients.

This study contributes to the understanding of non-improvement in psychotherapy and the relationship between quantitative and qualitative outcome evaluation. It cannot, however, answer the question whether outcome scores were representative for every individual patient. The focus of the present study was to provide an overall understanding, (i.e., a conceptual model) of non-improvement relying on a larger group of nonimproved patients. More idiosyncratic information still remains unaddressed and case-study research focusing on individual patients' narratives and outcome scores is warranted ( Kazdin, 2011 ). Similarly, the study cannot offer a fine-grained comparison of the specific effects of CBT and PDT, which could be further addressed in research on specific factors. The mixed methods research format in our study furthermore explicitly favoured the qualitative data over the quantitative outcome classification as focus of investigation, limiting the quantitative strand to a single, although psychometrically sound and often used, outcome measure. Our selection of patients based on self-reported symptoms nevertheless, had a considerable impact on our findings. With use of other means for categorisation, the sample likely would have turned out differently (e.g., using a different measure, multiple measures or relying on patients' satisfaction). Yet, as the use of statistical classification of clinically meaningful outcome (cf. Jacobson and Truax, 1991 ) is increasingly common in RCTs and standard outcome research at large ( De Los Reyes et al., 2011 ), this study explicitly aimed to relate the exploration of patients' experiences to the much-used classification tool. Therefore, the aim of the current study was not to address the issue of measurement as such, nor the validation of the specific questionnaire that was used, but to deepen the understanding of outcome that is gained by these much used categories. Our conclusions on the relation between quantitative and qualitative appraisals of outcome can however not be generalised to the entire field of quantitative outcome evaluation that undoubtedly has evolved in the past decades, for instance with an increasing focus on person-centered questionnaires ( Elliott et al., 2016 ). For the purpose of our study, an explanatory sequential design was most suited ( Hesse-Biber, 2010 ). Nevertheless, further research aiming at different approaches to mixing methods and including idiosyncratic quantitative outcome evaluation could contribute greatly to our knowledge on outcome and psychotherapy.

Given the controlled context of our study (as data was collected in the context of a broader RCT), it offers a strong level of control for confounds. For instance, the research sample was characterised by a primary disorder of major depression, outcome was systematically evaluated in all patients and treatments were manualised. A potential threat is therefore, however, the external validity of the findings ( Westen et al., 2004 ). Unlike in naturalistic studies, patients with more complex and acute psychopathologies were excluded. Nonetheless, all patients in our study showed comorbid disorders in line with clinical reality; for instance, the co-occurrence of major depression and anxiety disorders observed in this study is a robust finding throughout patient groups (cf. Hirschfeld, 2001 ). The participants in this study resembled a homogenous and local (predominately Caucasian, Flemish) group of patients, however. Specific (e.g., cultural, ethnic) or more diverse groups of patients could be the focus of complementing research. The research findings might also be biased by a selection of patients willing to participate in the study. Moreover, it is known that patients do not easily disclose negative experiences with therapy or with their therapist, and although interviews can enhance this openness ( McLeod, 2000 ), in general, socially desirable answers cannot be excluded ( Thurin and Thurin, 2007 ).

The model of nonimproved outcome must be considered tentatively, and we do not wish to make strong causal claims regarding the effectiveness of treatment or the causal influence of the therapist. In agreement with Strupp and Hadley (1977) , we emphasise that the patient perspective is only one perspective on outcome (e.g., in addition to therapist or societal perspectives), and therefore highlights certain elements while neglecting others. This limits the findings of this study, as previous research has shown patient, therapist, and observers' perspectives on outcome not always converge and all add valuable insights for clinical practice ( Altimir et al., 2010 ). Nevertheless, integrating in-depth inquiry of patients' narratives in the form of mixed methods research is of considerable value to outcome research and the study of non-improvement. In general, we argue that further research investigating the complex phenomena of outcome and therapy effects should aim at an integration of multiple methods as well as perspectives to grasp the wider picture ( McLeod, 2011 ).

Non-improvement in psychotherapy from the perspective of depressed patients can be understood as being stuck between knowing versus doing, resulting in a stalemate. Patients described both positive changes on the level of insight, mental stability and personal strength. The remaining issues were characterised by an ambition to change but feeling an inability to do so. No change in depression symptoms based on standard pre-post outcome evaluation thus becomes a partial change when considering patients' experience and shows a more complex picture in line with the complexity of experiencing depression. Investigating non-improvement by integrating in-depth analyses of patients' narratives in the form of mixed methods research proves to be of considerable value for understanding (negative) outcome and treatment effects more general.

Author Contributions

MDS: main author of the manuscript, contribution to data collection, main investigator responsible for data-analysis and interpretation; RM: conception and development of study design, coordinating contribution to data collection, contribution to data-analysis and interpretation, main reviewer of the manuscript; KV: contribution to data collection, contribution to data-analysis and -interpretation, reviewer of the manuscript; FT: contribution to data collection and reviewer of the manuscript revision; MD: conception and development of study design, coordinating contribution to data collection, reviewer of the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgements

We want to thank all patients and therapists for participating in the study. Acknowledgements to Ufuoma Norman for the careful reading of the final draft of this manuscript. Gratitude for contributing to the data collection for the Ghent Psychotherapy Study goes to Ruth Inslegers, Rosa De Geest, Goedele Hermans, Vicky Hennissen, and Ufuoma Norman. MDS is funded by the Flanders Research Foundation (FWO, Belgium).

1. ^ Note of nuance: as outcome is predominantly evaluated by means of symptom-based scales ( Braakmann, 2015 ), throughout this paper we will refer to a decrease in symptoms, even so we acknowledge outcome measurement is not limited to symptom-based scales but can also contain measures of general wellbeing, satisfaction and interpersonal functioning.

2. ^ Given the focus of the current study on patients being treated for major depression, the BDI-II-NL was selected as the outcome measure in this study. A complete overview of all measures used in the GSP can be found in the study protocol ( Meganck et al., 2017 ).

3. ^ See McLeod (2013) for a summary of qualitative studies on this topic, Bohart and Wade (2013) on the role of agency, Castonguay and Hill (2007) for an elaboration on the role of insight in psychotherapy.

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Keywords: non-improvement, psychotherapy, outcome research, grounded theory, depression-psychology, mixed-method analyses, qualitative and quantitative methods, patient perspective

Citation: De Smet MM, Meganck R, Van Nieuwenhove K, Truijens FL and Desmet M (2019) No Change? A Grounded Theory Analysis of Depressed Patients' Perspectives on Non-improvement in Psychotherapy. Front. Psychol . 10:588. doi: 10.3389/fpsyg.2019.00588

Received: 28 September 2018; Accepted: 01 March 2019; Published: 26 March 2019.

Reviewed by:

Copyright © 2019 De Smet, Meganck, Van Nieuwenhove, Truijens and Desmet. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Melissa Miléna De Smet, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Grounded Theory: Approach And Examples

Grounded theory is a qualitative research approach that attempts to uncover the meanings of people’s social actions, interactions and experiences….

Grounded theory is a qualitative research approach that attempts to uncover the meanings of people’s social actions, interactions and experiences. These explanations are called ‘grounded’ because they are grounded in the participants’ own explanations or interpretations.

Barney Glaser and Anselm Strauss originated this method in their 1967 book, The Discovery Of Grounded Theory . The grounded theory approach has been used by researchers in various disciplines, including sociology, anthropology, psychology, economics and public health.

Grounded theory qualitative research was considered path-breaking in many respects upon its arrival. The inductive method allowed the analysis of data during the collection process. It also shifted focus away from the existing practice of verification, which researchers felt didn’t always produce rigorous results.

  Let’s take a closer look at grounded theory research.

What Is Grounded Theory?

How to conduct grounded theory research, features of grounded theory, grounded theory example, advantages of grounded theory.

  Grounded theory is a qualitative method designed to help arrive at new theories and deductions. Researchers collect data through any means they prefer and then analyze the facts to arrive at concepts. Through a comparison of these concepts, they plan theories. They continue until they reach sample saturation, in which no new information upsets the theory they have formulated. Then they put forth their final theory.

  In grounded theory research, the framework description guides the researcher’s own interpretation of data. A data description is the researcher’s algorithm for collecting and organizing data while also constructing a conceptual model that can be tested against new observations.

  Grounded theory doesn’t assume that there’s a single meaning of an event, object or concept. In grounded theory, you interpret all data as information or materials that fit into categories your research team creates.

  Now that we’ve examined what is grounded theory, let’s inspect how it’s conducted. There are four steps involved in grounded theory research:

• STAGE 1: Concepts are derived from interviews, observation and reflection
• STAGE 2: The data is organized into categories that represent themes or subplots
• STAGE 3: As the categories develop, they are compared with one another and two or more competing theories are identified
• STAGE 4: The final step involves the construction of the research hypothesis statement or concept map

Grounded theory is a relatively recent addition to the tools at a researcher’s disposal. There are several methods of conducting grounded theory research. The following processes are common features:

  Theoretical Memoing

  compile findings.

Data collection in the grounded theory method can include both quantitative and qualitative methods.

By now, it’s clear that grounded theory is unlike other research techniques. Here are some of its salient features:

It Is Personal

It is flexible, it starts with data, data is continually assessed.

Grounded theory qualitative research is a dynamic and flexible approach to research that answers questions other formats can’t.

Grounded theory can be used in organizations to create a competitive advantage for a company. Here are some grounded theory examples:

• Grounded theory is used by marketing departments by letting marketing executives express their views on how to improve their product or service in a structured way
• Grounded theory is often used by the HR department. For instance, they might study why employees are frustrated by their work. Employees can explain what they feel is lacking. HR then gathers this data, examines the results to discover the root cause of their problems and presents solutions
• Grounded theory can help with design decisions, such as how to create a more appealing logo. To do this, the marketing department might interview consumers about their thoughts on their logo and what they like or dislike about it. They will then gather coded data that relates back to the interviews and use this for a second iteration

These are just some of the possible applications of grounded theory in a business setting.

Its flexibility allows its uses to be virtually endless. But there are still advantages and disadvantages that make the grounded theory more or less appropriate for a subject of study. Here are the advantages:

• Grounded theory isn’t concerned with whether or not something has been done before. Instead, grounded theory researchers are interested in what participants say about their experiences. These researchers are looking for meaning
• The grounded theory method allows researchers to use inductive reasoning, ensuring that the researcher views the participant’s perspectives rather than imposing their own ideas. This encourages objectivity and helps prevent preconceived notions from interfering with the process of data collection and analysis
• It allows for constant comparison of data to concepts, which refines the theory as the research proceeds. This is in contrast with methods that look to verify an existing hypothesis only
• Researchers may also choose to conduct experiments to provide support for their research hypotheses. Through an experiment, researchers can test ideas rigorously and provide evidence to support hypotheses and theory development
• It produces a clearer theoretical model that is not overly abstract. It also allows the researcher to see the connections between cases and have a better understanding of how each case fits in with others
• Researchers often produce more refined and detailed analyses of data than with other methods
• Because grounded theory emphasizes the interpretation of the data, it makes it easier for researchers to examine their own preconceived ideas about a topic and critically analyze them.

As with any method, there are some drawbacks too that researchers should consider. Here are a few:

• It doesn’t promote consensus because there are always competing views about the same phenomenon
• It may seem like an overly theoretical approach that produces results that are too open-ended. Grounded theory isn’t concerned with whether something is true/false or right/wrong
• Grounded theory requires a high level of skill and critical thinking from the researcher. They must have a level of objectivity in their approach, ask unbiased, open-minded questions and conduct interviews without being influenced by personal views or agenda.

While professionals may never have to conduct research like this themselves, an understanding of the kinds of analytical tools available can help when there are decisions to be made in the workplace. Harappa’s Thinking Critically course can help with just this. Analytical skills are some of the most sought-after soft skills in the professional world. The earlier managers can master these, the more value they’ll bring to the organization. With our transformative course and inspiring faculty, empower your teams with the ability to think through any problem, no matter how large.

Explore Harappa Diaries to learn more about topics such as Meaning Of Halo Effect , Different Brainstorming Methods , Operant Conditioning Theory of learning and How To Improve Analytical Skills to upgrade your knowledge and skills.

The Grounded Theory: Definition and Application Essay

Introduction, definition of the grounded theory, starting a research project.

Grounded theory is typically deployed to uncover social processes, including behaviors and relationships. The critical characteristics of the model involve the simultaneous occurrence of data gathering and analysis and the use of theoretical sampling to refine categories. Other notable features of the methodology are integrating classes into a theoretical framework and using analytical memos between writing and coding (Charmaz & Belgrave, 2019). The grounded approach offers new strategies for analysis and streamlines data collection. It is essential to define grounded theory and how one can start a project using the methodology.

Grounded theory is a qualitative approach that enables an investigator to study a specific process or phenomenon and discover new models grounded on the data collection and analysis. In contrast to the traditional presumption-deductive methodologies whereby a researcher creates a hypothesis and attempts to prove or disprove it, grounded theory is an inductive approach where modern theories are derived from the data (Strauss & Corbin, 1998). The data gathering, analysis, and model development are iterative until the researcher reaches theoretical saturation since the additional data offers no extra insight into the new theory. The grounded approach is typically utilized when no other methodology explains the studied phenomenon (Strauss & Corbin, 1998). The data collected to develop the new model is incomplete as it is not gathered from research respondents (Charmaz, 2014). The three phases of data analysis in grounded theory include axial, open, and selective coding.

Grounded theory gives the researcher focus and flexibility and offers instruments for conducting a successful study by providing the much-needed strategies to finish the project. There is a procedure that an investigator can deploy to start a research project by using grounded theory. Firstly, the researchers must determine the initial study queries, which assists in giving guidance for the early stages of recruiting and data analysis. Secondly, with the grounded model, recruiting respondents is iterative. One can use theoretical sampling to collect data, enabling enlisting small groups of participants based on the initial study queries (Charmaz, 2014). After the researcher has some database from the in-depth interviews, the data prepared for evaluation is transitioned into transcripts. Thirdly, the investigator commences open coding, which disintegrates transcripts into excerpts and starts contrasting them with one another (Strauss & Corbin, 1998). Therefore, grounded theory effectively utilizes the constant comparative method to determine the differences and similarities of particular behaviors and relationships among research variables.

Fourthly, the grounded theory enables the investigator to group excerpts having the same concept or the central idea by using open coding. The fifth phase of the grounded methodology is the axial coding that enables an investigator to compare the correlation between conducts and establish the reactions (Charmaz & Thornberg, 2021). The sixth step of the approach involves extensive analysis of more excerpts by deploying a constant comparative method, whereby the investigator analyzes extra interview transcripts and either contradiction, support, or expansion of the existing categories (Charmaz, 2014). The seventh stage involves collecting and analyzing data until theoretical saturation is attained. Lastly, the grounded theory helps the investigator to use selective coding to integrate the research findings, after which they start writing their project.

Grounded theory uncovers social processes, such as correlations and behaviors, and it is applied when no other approach explains the studied phenomenon. The grounded theory offers critical steps researchers use to start their research project. Such phases include determining the initial study queries, theoretical sampling, open coding, and axial coding. Other stages that assist the investigator are using the constant comparative method, attaining theoretical saturation, defining the central idea via selective coding, and writing the methodology to commence the research project.

Charmaz, K. (2014). Constructing grounded theory (2 nd ed.). Sage.

Charmaz, K., & Belgrave, L. L. (2019). Thinking about data with grounded theory . Qualitative Inquiry , 25 (8), 743-753. Web.

Charmaz, K., & Thornberg, R. (2021). The pursuit of quality in grounded theory . Qualitative Research in Psychology , 18 (3), 305-327. Web.

Strauss, A., & Corbin, J. (1998). Grounded theory methodology: An overview. In N.K. Denzin & Y.S. Lincoln (Eds.), Strategies of qualitative inquiry (pp. 156-183). Sage.

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