empirical research narrative

• Open access
• Published: 16 September 2021

Developing new ways to listen: the value of narrative approaches in empirical (bio)ethics

• Bernadette Roest   ORCID: orcid.org/0000-0002-1178-8150 1 ,
• Megan Milota 2 &
• Carlo Leget 1  

BMC Medical Ethics volume  22 , Article number:  124 ( 2021 ) Cite this article

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The use of qualitative research in empirical bioethics is becoming increasingly popular, but its implementation comes with several challenges, such as difficulties in aligning moral epistemology and methods. In this paper, we describe some problems that empirical bioethics researchers may face; these problems are related to a tension between the different poles on the spectrum of scientific paradigms, namely a positivist and interpretive stance. We explore the ideas of narrative construction, ‘genres’ in medicine and dominant discourses in relation to empirical research. We also reflect on the loss of depth and context that may occur with thematic or content analyses of interviews, and discuss the need for transparency about methodologies in empirical bioethics. Drawing on insights from narrative approaches in the social sciences and the clinical-educational discipline of Narrative Medicine, we further clarify these problems and suggest a narrative approach to qualitative interviewing in empirical bioethics that enables researchers to ‘listen (and read) in new ways’. We then show how this approach was applied in the first author’s research project about euthanasia decision-making. In addition, we stress the important ethical task of scrutinizing methodologies and meta-ethical standpoints, as they inevitably impact empirical outcomes and corresponding ethical judgments. Finally, we raise the question whether a ‘diagnostic’, rather than a ‘problem-solving’, mindset could and should be foregrounded in empirical ethics, albeit without losing a commitment to ethics’ normative task, and suggest further avenues for theorizing about listening and epistemic (in)justice in relation to empirical (bio)ethics.

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How are qualitative interviews typically conducted in bioethics research? And how might narrative approaches Footnote 1 in the social sciences, humanities and clinical education enrich this research practice? These questions constitute the foundation and impetus of this article. We pose these questions because qualitative methods—in particular, face-to-face interviews and focus-groups—have become increasingly popular amongst bioethics-scholars in the last decades [ 5 , 6 ]. That being said, the implementation of these methods in empirical bioethics Footnote 2 can be challenging. This is due, in part, to difficulties aligning (moral) epistemologies and methods. Problems can also arise when determining if and how to distinguish facts and values. In addition, researchers must choose from a concordant multitude of methodologies and may be insufficiently trained in empirical methods traditionally used in the social sciences [ 5 , 6 , 7 , 8 , 9 , 10 ].

As academics working at the intersection of clinical practice, education and research in bioethics, we have personal experience with many of these challenges. We have found that qualitative methods for gathering and analyzing data in one field aren’t always accepted in another. Standards for assessing quality, evaluating research ethical-issues and reporting on findings can also be vastly disparate [ 11 , 12 ]. A qualitative study of focus groups published in a linguistically-oriented journal looks very different from a focus group study in a biomedical journal, for instance. Even the ways in which qualitative methods are taught to students and researchers varies between faculties and fields. Meanwhile, we also observed a need to broaden our toolkit of qualitative methods in empirical bioethics, to obtain more detailed and contextualized accounts of illness and caring experiences that seem vital to understand and ethically assess complex healthcare practices.

While searching for robust and transparent methodologies that could address the above mentioned challenges, we actively deepened our affiliations with narrative approaches and Narrative Medicine. Footnote 3 These engagements gradually taught us to ‘listen (and read) in new ways’. They enriched our understanding of qualitative research practices and simultaneously changed our teaching and clinical practice. Meeting regularly from 2018 till date to discuss theoretical backgrounds and possible applications, we attempted to ‘translate’ valuable skills and insights from these disciplines to empirical bioethics.

In this article, we will share some of our insights into our version of ‘narrative thinking’. In particular, we describe a narrative approach to qualitative interviewing with illustrative examples from the first author’s research project on euthanasia decision-making in Dutch general practice. We hope this detailed exposition will prove helpful for fellow-researchers in bioethics searching for methodological guidance.

Furthermore, the considerations and approaches discussed in this paper are intended to draw attention to a ‘diagnostic’ attitude in empirical bioethics, an attitude marked by a continuous re-examination of the questions we ask our research participants, the stories they tell us, and the frames we use in our inquiries. We contend that this diagnostic attitude, in contrast to a more problem-solving one, seems most appropriate should we as empirical bioethicists want to formulate ethical guidance that is more attuned to the ambiguous and nuanced lives and concrete care-practices of patients, relatives and healthcare professionals.

A spectrum of scientific paradigms and the implications for qualitative research in bioethics

As a result of our immersion in narrative approaches and Narrative Medicine, we came to understand that conducting qualitative research in bioethics not only entails working at the intersection of different disciplinary fields (ethics/philosophy, social science, medicine) but also between different poles of a spectrum of scientific paradigms, namely positivist versus interpretivist traditions [ 1 , 12 , 17 ]. Contemporary medicine, the discipline most frequently collaborated with in empirical bioethics [ 5 ], mainly operates from the positivist pole of this spectrum. In contrast, most approaches in qualitative research can be found at the interpretivist pole. Footnote 4 For empirical bioethicists conducting qualitative research, it seems necessary to recognize this spectrum of scientific paradigms in order to avoid certain pitfalls and to become aware of (and balance between) the different standards of good research that come with the different positions on the spectrum.

Narrative construction, genres and dominant cultural narratives

When one approaches interviews from a positivist stance, the clinician or researcher may take the interview content at face value, as objective answers to objective questions posed by an interlocutor operating from a neutral position. Footnote 5 However, scholars in narrative research operating from an interpretivist paradigm take a different perspective Footnote 6 ; every qualitative interview is an encounter in which narrative construction takes place on multiple levels simultaneously. This construction is influenced by both the interviewer and participant, each with their own specific backgrounds and positions, and is always tied to a specific historical and cultural context [ 18 , 19 , 20 , 21 , 22 ].

Chambers points at something similar when he argues that “as narrative theorists know well (and most philosophers when pressed) there are no objective stories; all tales are told by some teller in a way that simultaneously reveals and conceals events” [ 23 , p. 40]. He describes how medical-ethical cases—bioethicists’ objects of analysis—seem to follow a ‘genre’ with specific narrative features: action-oriented, characters lacking psychological depth and with sparse attention for historical time and life-worlds outside the clinic.

In a similar way, patients’ stories seem to take a specific shape in their encounters with clinicians; they can be disjointed, focusing on medical-technical aspects, and leaving out clues to social and cultural contexts [ 18 , 20 , 24 ]. Furthermore, factors such as age, gender, cultural and mental health background, expectations and power-imbalances in the doctor–patient relationship, and organizational factors have shown to profoundly influence what is being told by patients and how clinicians respond to it [ 25 , 26 , 27 , 28 ]. And even when a person-centered care approach is deliberately applied, some patients’ stories are taken more seriously than others [ 29 ]. On a level transcending medicine and bioethics, both social scientists and philosophers have described (and criticized) dominant cultural narratives in Western countries that focus on the autonomous self, coherence, control and continuity [ 30 , 31 , 32 , 33 ].

An awareness of a narrative’s form, structure and underlying ‘genre’ combined with an attention to dominant cultural discourses present in the narrative may enable an empirical bioethicist to look more critically at the process of qualitative interviewing and the results it may yield. The researcher can furthermore reflect on his or her own contribution to the construction of the interview-data and to what extent the interview questions and subsequent analysis of the data may reproduce existing ‘genres’ in medicine and bioethics. A final question worth asking is whether or not fragmented, contradictory or non-coherent stories receive sufficient attention and representation in research design, data analysis and valorization compared to more coherent stories [ 25 ].

Breadth versus depth in the analysis of qualitative interview-data

Another point worth considering for qualitative researchers in empirical bioethics, is how a positivist or interpretive outlook influences the analysis of interview data. Content analysis and thematic analysis—admittedly valuable and widely applicable approaches—are the most popular techniques for analyzing qualitative interviews among empirical bioethicists [ 5 ]. However, these approaches aim at generating overarching themes across multiple interviews and therefore run the risk of diverging into a positivist approach marked by generalization and quantification. Footnote 7 Some scholars have criticized this approach, voicing a concern that “analyst were ignoring the meaning-making person through decomposing interview transcripts into a series of themes or discourses” [ 36 paraphrasing 19 ].

In contrast, narrative researchers often focus in their analysis on “ how and why a particular event is storied” [ 21 , p. 12], emphasis added. In other words, they explore who is able to speak about certain themes and under what conditions; they also focus on the particularities and context of the stories told. If thematic analysis is subsequently applied in narrative research, it focuses on the emergence and sequencing of themes inside a specific interview instead of across interviews [ 21 ]. This “case-centered commitment” constitutes the most significant difference between narrative methods and other “category-centered models” of qualitative research [ 21 , p. 12, 74 ] .

The analytical arsenal for narrative researchers extends far beyond the aforementioned ‘thematic narrative analysis’. In health psychology, medicine and ethics, scholars have studied ‘storyline elements’ or ‘narrative features’. Examples include voice, teller, characters, place, time, acts or events, breaches, ‘peripeteia’ (i.e. sudden changes), mood, metaphor, purpose and plot [ 14 , 21 , 23 , 36 , 37 , 38 ]. Another point of focus for narrative researchers are the different levels of narrative construction, namely the personal-autobiographical, the dialogical-interpersonal and societal-cultural level [ 20 , 39 ]. Other scholars have also applied structural analysis [ 21 , 40 ] or have drawn inspiration from socio-linguistics and ethnomethodological approaches like conversation analysis and discourse analysis in their analyses of narrative interviews [ 40 , 41 ]. Footnote 8

The choice in analytic approach always depends on the research aim and question. However, a specific challenge seems to be finding analytical approaches that foster an in-depth inquiry of interview data while simultaneously yielding results that are deemed relevant to the ethical issues and clinical practices being scrutinized. An analysis of interview data focusing on the particularities of language and organization of stories may at first cause medical practitioners and clinical bioethicist to exclaim ‘So what?’. However, we contend that certain research aims and questions require a more thorough and in-depth analysis and that approaches from the field of narrative research provide the much needed additions to the current toolbox of analytical approaches that bioethicists commonly employ.

Stringent methodological guidelines and ‘interpretive magic’

The tension between the positivist and interpretivist traditions can be found in discussions about the need for stringent methodological frameworks in qualitative research in empirical bioethics. Some scholars have warned against too much standardization of qualitative research as it could undermine approaches that rely heavily on researchers’ involvement in the data collection process. Standardization could also diminish or prohibit one of the fundamental aspects of qualitative research: the variation in interpretations [ 42 , 43 ].

Researchers working in an environment dominated by positivist traditions or world views run the risk of having their findings dismissed as subjective and non-generalizable. In the worst case, results may be derided as a form of ‘interpretive magic’, even when the research project in question has followed the quality-criteria connected to that specific research practice and the related scientific paradigm. As scholars who have studied and worked in both medical and humanities faculties, we understand both sides of this debate. A strategy that has worked for us is to become acquitted with and refer to existing guidelines for conducting and reporting qualitative research in order to facilitate transparency and study replicability [ 7 , 10 , 44 , 45 ].

A narrative approach to qualitative interviewing and analysis in empirical bioethics: fostering close-listening and close-reading

As a result of our conversations with each other, our own experiences as researchers and educators, and our Narrative Medicine training, we have attempted to develop an approach for conducting qualitative interview studies in empirical bioethics that is informed by the insights of narrative research and narrative medicine. The approach is aimed at 1) fostering a more in-depth understanding of the persons and practices being studied and 2) helping researchers trained in medicine and bioethics access valuable insights and techniques from interpretivist traditions. In the following section, we will first describe the approach as it was used by the first author (BR) in her research project on euthanasia decision-making in Dutch general practice. This description can serve as a guide for other researchers as well. Afterwards, we discuss some critical insights that emerged from working with this approach. These insights are meant to illustrate how ‘narrative thinking’ can further enrich our understanding of qualitative research projects in bioethics.

A narrative approach to qualitative interviewing and analysis

BR’s research project on euthanasia decision-making in Dutch general practice was inspired by a discrepancy she observed as a GP between the close involvement of family members in euthanasia decision-making in practice, versus the silence about their position in legislation and guidelines [ 46 ]. In addition, she noticed that it seemed difficult to capture the messiness and complexity of everyday euthanasia-practices, as well as their social-political context, in empirical research and normative reflection [ 47 , 48 ]. Therefore, she searched new ways to explore the Dutch practice of euthanasia and found directions in the moral epistemology of Margaret Urban Walker [ 33 , 49 ]. BR has described this moral epistemological stance and the connection with narrative approaches to qualitative research in detail in an earlier publication [ 47 ].

BR formulated a twofold research-question to address both the descriptive and normative dimension of the research-project, which we consider to be deeply interrelated: (1) What can we learn from both content and form of co-constructed interview-narratives about the needs and felt responsibilities of patients suffering from cancer, their relatives and healthcare professionals during euthanasia decision-making; and (2) what impact may this knowledge have on our ethical evaluation of euthanasia decision-making in Dutch general practice?

As one can see, the research questions reflect the previously discussed ideas about narrative construction in qualitative interviews. Furthermore, in this research project a broad conception of ‘narrative’ was adopted. Following Riessman and Squire, interviews were seen as “narrative occasions” [ 21 , p. 23]; in other words, both verbatim transcribed interviews (including non-verbal utterances) Footnote 9 and field notes of pre- and post-interview conversations and -impressions were considered part of these narrative occasions to be analyzed [ 2 , 21 , 51 ]. In addition, the narratives were considered a means of representing, reconstituting and expressing experience [ 52 ], rather than unmediated, direct expressions of experience.

BR recruited patients, relatives, GPs and other healthcare professionals (minimal 10 participants per group) via purposive and snowball-sampling. For the interviews, BR employed informal, open-ended interviewing techniques rather than more rigidly organized semi-structured interviews [ 21 , 40 , 53 ] . The aim was to elicit detailed narratives of experiences and practices in the interviews by using short, open prompts and questions, and by following the thread of the interview-participant with explorative, probing questions and a minimum of interruptions. BR also tried consciously to practice active listening skills during the interviews by staying engaged and attentive throughout the whole interview [ 21 , 40 ].

In the analysis of the interview data, BR aimed to integrate a thematic lens while paying attention to narrative features and contextual levels. The goal was to enrich the understanding of what is said in qualitative interviews, how , and in what context . For these reasons, BR developed a narrative approach to analyze the interview-data in different cycles and through multiple lenses as a means of avoiding some of the aforementioned pitfalls of qualitative analysis [ 1 , 54 , 55 ]. This approach was partly inspired by the work of Murray and Sools on narrative research [ 36 ] and of Charon et al. [ 14 , 38 ] on close-reading of texts, but was adjusted to the specific research aim and setting. A grid was developed that summarizes the different cycles/lenses and that could be used as a supportive tool during analysis. See Fig.  1 for this analysis-grid.

Analysis-grid

Prior to the in-depth analysis of the interviews, all transcripts were read and re-read several times by BR and the other members of the interdisciplinary research team in order to get acquainted with the data. Preliminary thoughts, impressions and questions were jotted down. Following that, an in-depth analysis of the interviews was carried out following the different cycles presented in the grid, whereby all interviews we analyzed by BR and a subset by MM and CL.

In this stage of the research process, only one interview-encounter (including both the verbatim transcript and corresponding fieldnotes) was taken as the unit of analysis at a time. A comparative analysis of similarities and differences between the interviews was carried out at a later phase, a point we will address later. The first cycle of analysis consisted of an inductive process of in vivo coding of sentences and paragraphs that were seen as “summative, salient, essence-capturing, and/or evocative” in light of the research questions [ 55 , p. 3]. If patterns of codes seem to emerge, they were organized into themes, thus resembling thematic narrative analysis [ 21 ].

The second cycle of analysis consisted of identifying and coding narrative features as described in the previous section of this article. While a multitude of narrative features could be discerned and analyzed in a text, for the sake of feasibility BR reduced her scope to the questions of ‘who, where, when, what, what for, how is it described (including metaphor), how does it feel?’ Building on insights gained from the methods of close-reading and -listening as taught in Narrative Medicine, BR also recorded unexpected twists and layered/nested stories.

The third cycle of analysis consisted of identifying and coding words and passages that referred to different levels of narrative construction as described by Murray and Riessman: autobiographical/personal, dialogical/interpersonal, positional and socio-political/cultural context [ 20 , 21 ]. In this stage of analysis, attention was also paid to co-creative moments in the interviews, evidence of differences in social position between the researcher and interviewee, and possible meta-narratives or culturally shared stories present in the content (transcript) or the performance of the interview (fieldnotes).

The fourth cycle of analysis consisted of synthesizing the results of the previous steps of analysis in light of the research questions. In addition, one or two quotes per interview were recorded that seemed to summarize the core points of that specific interview. Interestingly, two different types of quotations were often sufficient to summarize the interview: one reflecting the interviewee’s ideas with regard to the research question, and one reflecting what seemed to be off-topic with regard to the research question but nevertheless was considered very important for the interviewee. See Fig.  2 for an illustration of these four cycles of analysis and the use of the analysis-grid in this process.

Illustration of the four cycles of analysis and the use of the analysis-grid

After completing these four cycles of analysis for each of the interviews, the next step was a comparison and discussion of differences and similarities in the analyses of individual interviews between BR and the other researchers. Once this step was completed, BR performed a comparative analysis, first among groups of participants (i.e. the interviews of patients) and then across all the participants. This was done in order to determine whether specific themes, narrative features (such as metaphors) or contextual elements emerged among groups of participants that could shed new light on the research question. See Table 1 for an illustration of this process.

The results of this comparative analysis were again discussed in the research team (and involved posing the question: could it have been otherwise?) and different cycles of member checks were performed (see section below). In addition, specific insights from Narrative Medicine guided the analysis and interpretation, namely (1) tolerating uncertainty and ambiguity, (2) narrative and cultural humility, and (3) focusing not only on problematic elements but also on possible strengths and sources of resilience in the stories of participants and practices being studied [ 13 , 57 , 58 ].

Emerging critical insights emerging from a narrative approach

While conducting the project as described above, additional insights emerged about the possibilities and challenges of using narrative approaches in qualitative research in bioethics. In this last part of the paper, we list these insights and illustrate them with concrete examples.

The added value of training researchers through Narrative Medicine: experiencing (inter)subjectivity and practicing close-listening, close-reading and reflexivity.

While courses on social science methodology can help those without a social science background get acquainted with the application of methods in qualitative research, we discovered that training in Narrative Medicine (NM) teaches qualitative researchers skills and attitudes that are better aligned with an interpretive stance. In NM training, participants practice close-reading literature and artworks as well as close-listening to others’ accounts of their lived experiences [ 13 , 14 ]. As BR experienced while taking NM classes, and MM observed while teaching them, immersion in Narrative Medicine activities provide opportunities to reflect on the ways in which one’s own dynamic and evolving values and personality impact all interpersonal encounters. In addition, NM activities help participants attune to details in in a patient’s story and encourage participants to practice ‘listening for the sake of listening’ rather than listening with a problem-solving or therapeutic mindset.

While the (inter)subjectivity of reading, listening and interpreting—a core tenet of the interpretive paradigm and of qualitative research—is often explained as a concept in methodology courses, we noticed that NM help participants e xperience it as a practice . For empirical bioethics researchers immersed in positivist traditions, this training can be a means of becoming sensitized to what the interpretivist traditions entail. Footnote 10 In addition, the repeated close-reading of literature and patients’ stories in NM activities, including an analysis of storyline elements (such as voice, place, time, mood and metaphor), also constitute valuable practice for researchers interested in exploring these elements in interview data.

This awareness of (inter)subjectivity helped BR better integrate concrete reflexive elements into her project [ 59 , 60 ]. For example, she discussed preliminary judgements and starting positions with the research team at the start of the research, kept a field journal throughout the whole research process (with both methodological and personal-reflective notes) and frequently debriefed with team-members and with an independent consultant (in this case, a humanistic pastoral counsellor) as a form of “third party” debriefing [ 43 ].

Sampling and conducting interviews: everyone speaks (and listens) from somewhere.

Ideas about narrative construction and the interactional context of storytelling influenced reflections in the research project about sampling and interviewing strategies. BR aimed for a heterogeneous sample of patients, relatives, GPs and other primary care professionals and chose purposive and snowball sampling techniques to recruit participants via a variety of networks (patients and relatives via both GPs and patients’ organizations, GPs and other care-professionals via both academic and professional networks), which are common practices in qualitative research.

One cannot prevent some degree of selection bias towards participants who have a special interest in the topic; this is especially true in regards to a contentious issue like euthanasia. However, the narrative approach made BR aware that more subtle forms of selection bias may be present as well; an interview in itself presupposes a certain degree of cognitive and verbal capacities on the part of the interviewee. This method of data collection can thus exclude those who are less capable of speaking in coherent stories or who may not be able or willing to read a study’s often lengthy information letter. See Table 2 for a further illustration.

In addition, the narrative approach sensitized us to the role the researcher’s personality and positionality played in the interview process. While actively avoiding medical language and utterances during the interviews, BR nevertheless noticed that some interviewees frequently utilized ‘medical language’. This could have been partially due their awareness of BR’s position as both a researcher and MD. With other interviewees, BR noticed another effect of her dual role as researcher and medical professional. Because of her background as a MD, some participants—especially other GPs—seemed to be more willing to share personal details, which could be interpreted as a form of ‘confidence bonus’ [ 10 ]. Seen from an interpretivist paradigm, these issues are not problems that could or should be avoided. Rather, they constitute important methodological and analytical facets of the study that should be explicitly considered when interpreting the data.

Validity and research-ethics: navigating amongst interpretivist traditions.

Assessing the validity of a qualitative research project is again an undertaking that highly depends on one’s epistemological stance. While generalizabilityand internal and external validation are criteria corresponding to a positivist paradigm, narrative researchers use norms such as trustworthiness, relevance, pragmatic use and reflexivity when assessing a study [ 21 , 40 , 62 , 63 , 64 ]. Loh [ 62 ] offers a list of techniques for establishing trustworthiness; these include member checks, prolonged engagement, triangulation (of methods, sources and investigators), searching for contrasting cases, peer debriefing and thick description of research-results.

These strategies and techniques may be relatively straightforward in theory, but we want to highlight the fact that they can be difficult to apply in practice. Such techniques require a delicate dance back and forth between the interpretive and positivist paradigms, and often result in compromises when addressing methodological, research-ethical and practical issues. We encountered this tension when trying to address the ‘validation’ of our analysis grid and when we tried to conduct member-checks. Footnote 11

We tested the grid as a tool in our narrative approach for qualitative interviewing by using it with different researchers. During this process we wondered whether it could be considered a ‘good’ tool and if it would ‘produce’ similar interpretations (cf. a positivist stance) or richer and deeper understanding (cf. an interpretive stance) amongst the various researchers. During this process, we discovered the interpretive value of both intercoder-agreement and -disagreement. We also found that discussing the tone or mood of an interview with other researchers enriched the process of analysis. See Table 3 for an illustration of this point.

Member-check was another point of complexity. As described above, it could be seen as a methodological requirement given the co-constructed nature of interview-narratives. It could also be seen as an research-ethical requirement following the idea of the ethics of interpretation and representation—research-ethical requirements specific to narrative research apart from informed consent and confidentiality [ 52 , 65 ]. That being said, details about how exactly to perform member checks—when, what and with whom—are matters of dispute, with opinions varying from merely returning the interview-transcript to participants to research-participants becoming co-analysists or co-interpretivists in the project [ 52 , 66 ]

BR encountered various problems related to the process of member-checks; research-participants were not always willing or able (due to cognitive- or emotional reasons) to engage with returned research-results. Some were in a different phase of life (or even deceased) at the moment narrative summaries of the interviews were shared. Other scholars have experienced similar problems with member-checks and some have also noticed how participants may be agreeing with their own interview-narrative, but not with the interpretations stemming from a cross-case analysis [ 21 , pp. 196–199, 67 ].

In her research-project, BR tried to balance the ethical requirements of careful representation and not harming participants with the methodological requirement of conducting member checks, while committing to the idea that co-construction also means that the researcher may see things that participants haven’t seen themselves or may not agree with. For example, participating patients and relatives were asked if they wanted to receive and comment on a narrative summary of their interview, but not all participants were interested in this offer. In order to ensure that patients’ and relatives’ perspectives were still being accurately represented in the data, BR also asked representatives of patient-federations to provide feedback on the interview-data as summarized in draft articles.

On a final note, the trustworthiness and relevance of this project will ultimately be determined by the broader professional and scholarly community as “validity rests on a consensus within a community of speakers” [ 63 , p. 474]. This implies that a researcher be able to address and ‘speak the language’ of these various communities.

From the empirical to the normative: the moral work of choosing methodologies

The final step in an empirical bioethics project typically entails linking the empirical results to normative conclusions. In the case of BRs research project, the goal was to critically explore and ultimately inform the ethical evaluation of euthanasia decision-making in general practice. Following Walker and other ethics scholars who have written on narrative approaches, we take the stance that narratives—or any empirical data—cannot ‘speak for themselves’ as leading to normative conclusions. In other words, coherent and authentic narratives cannot serve as a substitute for moral justification [ 33 , 47 , 68 ]. Walker [ 33 , p.13] argues for a “fully normative reflection” which could be assessed with criteria of good philosophical argumentation [ 10 , 69 ].

While BR is still in the process of evaluating the empirical results at the time of writing this article, one issue that comes to the fore is the need to rethink the question of ‘plot’: what is the underlying purpose or goal of euthanasia, and according to whom? While GPs may frame it as a last resort in case of untreatable symptoms when death is imminent, patients and relatives may speak of it as a possibility to avoid the dying process and accompanying physical deterioration and dependency, or merely as ‘one more way of dying’. In addition, a detailed look at the who, where and when in the stories about both euthanasia and palliative care in the home-care setting raises questions about access to and availability of professional care in theory versus practice. Furthermore, a close-reading of metaphors helps one reflect upon different perceptions of care-receivers versus -providers in regards to equality, dependency and the role of emotions in end-of-life decision-making. These issues will be discussed in an upcoming publication.

In this article, our main goal was to draw attention to the ‘normative work of choosing methodologies’. Like Mertz et al., we contend that it is an important ethical task to scrutinize the methodologies we use, because “poor methodology in EE may give rise to misleading ethical analyses, evaluations or recommendations, not only depriving the study of scientific and social value, but also risking ethical misjudgment” [ 10 ]. Or to use a medical analogy: if one only uses an ophthalmoscope (i.e. an instrument to look into the eyes), one will never hear the heartbeat.

Finally, our thorough consideration of methodology has also lead us to reflect critically about the purported aims and ambitions of empirical bioethics. With this article and corresponding methodological approach, we want to stress the importance of what we call the ‘diagnostic task’ of empirical bioethics. In other words, we actively tried to conduct an open-ended examination of moral dimensions that were previously not in the scope of ethicist or that may be framed or perceived differently in practice [ 70 ]. In our view, this also includes considering issues such as epistemic (in)justice in medicine and biomedical or bioethical research [ 25 , 71 , 72 ] and further theorizing about the subject of listening and how that relates to bioethics and broader, to democratic practices [ 73 ]. We intend to explore these issues in future publications as well.

Conclusions

In this article, we have discussed the challenges one may face when conducting qualitative interviews for bioethics research as well as the tensions related to positivist and interpretivist traditions in science. We have shown how insights from narrative research and Narrative Medicine could enrich qualitative interviewing in medicine and bioethics by deepening our understanding of the co-construction and situatedness of stories (whether in the clinic or in research-encounters) and the importance of (inter)subjectivity and positionality.

We do not consider these insights and corresponding approach to be a substitute for positivist approaches in bioethics and medicine, rather as a necessary complement. We also realize that “fancy epistemological footwork” may be required when one tries to combine different traditions and corresponding methods in one’s research project or department [ 51 , p. 706]. In addition, narrative approaches to conducting and analyzing qualitative interviews may be time-consuming and labor-intensive. However, we think that some topics in bioethics require ‘slow-reading’ and profound reflection in order to grasp the nuances and particularities of the topic, and to formulate ethical guidance that is in-tune with the utterances of those who will effected by such guidance.

Furthermore, we realize that, “any methodological standpoint is, by definition, partial, incomplete and historically contingent” [ 51 , p. 706], and therefore hope to engage in further conversations on the issues foregrounded in this article. We are currently trying to further develop narrative approaches in the field of empirical bioethics, and are exploring the possibility of integrating ethnographic approaches Footnote 12 with insights from cultural/socio-narratology and narrative ethics. [ 76 , 77 , 78 , 79 , 80 ]

Last, we shared some of our ongoing process of considering and scrutinizing meta-ethical and methodological positions, which we see not just as a practical but as an ethical task that influences the course and outcome of one’s empirical bioethics project. We think that bioethics could benefit more from approaches that foster close-listening and close-reading of people and practices in healthcare, thereby enabling more ‘diagnostic thinking’, an attitude we consider to be a prerequisite for formulating ethical guidance. Whether our narrative approach will be useful to others in the field, is a question that will have to be answered in the future. In the meantime, our work can already serve as a valuable contribution to ongoing discussions about the place of interpretivist traditions in empirical bioethics that entail a different view on knowledge-generation and subsequently on quality criteria for validation, reporting, research-ethical evaluation and training for researchers.

Availability of data and materials

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We use ‘narrative approaches’ as an umbrella term for the work done by a broad group of scholars in diverse academic disciplines and professions (sociology, anthropology, literature studies, ethics, healthcare, social work, psychotherapy and more) who all focus on storied forms of knowledge marked by (inter)subjectivity, contingency and temporality. Nevertheless, a myriad of research methods and theoretical assumptions can be found among these different scholars. See Spector–Mersel [ 1 ] for an interesting discussion of this diversity and commonalities among narrative researchers and the historical background of the ‘narrative turn’. See Squire [ 2 ], Greenhalgh [ 3 ] and Nelson [ 4 ] as well for background information about narrative approaches in the social sciences, healthcare and bioethics respectively.

We define ‘empirical bioethics’ as the broad interdisciplinary academic field (involving health professionals, ethicists, social scientists and scholars with other backgrounds) dedicated to addressing normative questions related to healthcare practices through empirical inquiry and theoretical reflection.

Narrative Medicine is the phrase used by Charon and colleagues for their clinical-educational literature and medicine program that has taken shape at Columbia University NYC since the start of this millennium [ 13 , 14 ]. See the article of Charon et al. [ 14 ] for a summary of their pedagogy of “teaching attention, representation and affiliation” through the study of literature and artworks (close-reading) and creative writing, and its theoretical underpinnings. This article also includes a “Reading guide for reflective practice” that illustrates how one could examine a text following concepts such as ‘form’, ‘voice’ and ‘mood’. See Jones [ 15 ] and Crawford et al. [ 16 ] for comprehensive background information about the role of narrative and literature in the medical humanities in the past three decades.

Interpretivism is used as an umbrella term for epistemologies marked by a view on reality as “multifaceted (..), exchanging the positivist desire to create a ‘true’, neutral and unbiased picture of the ‘actual’ reality for an emphasis on the subjective component inherent in the study of social reality” [ 1 , p. 209]. For the sake of clarity, we have somewhat simplified the question of epistemology by using two poles of positivism and interpretivism. However, different types of interpretivist traditions can be discerned (see Spector–Mersel, 2010 [ 1 ]) and other epistemologies such as critical theory or pragmatism could also inform qualitative and narrative research.

Experienced bioethics researchers may easily move along the spectrum of paradigms and concordantly different views on what kind of results qualitative research may engender. However, we have noticed that this is less easy for (young) healthcare professionals who have just started immersing themselves in bioethics and/or qualitative research. To provide one example, in a third-year required course on Medical Humanities at the UMC Utrecht, one of the goals is to help students become more aware of their norms and values, and to situate utterances like these in broader philosophical, social and cultural contexts. At the onset of the course, students must write a short essay answering the question “what is science” and describing what they consider the definition and purpose of scientific research to be. The overwhelming majority of essays in MM’s groups are positivistic in stance and content, for example defining science as “reliable and not subjective”.

Again, this is a simplification of theoretical standpoints for the sake of clarity in this article. See Squire et al. [ 2 ] for a nuanced discussion of “theoretical divisions in narrative research”, as well as Spector-Mersel [ 1 ] for a discussion about “factist” versus “discursive, constructivist or postmodern” views on narratives.

See Vaismoradi et al.[ 34 ] for an in-depth discussion of thematic and content analysis and Hardy et al. [ 35 ] for a comparison of content analysis and discourse analysis.

This article confines itself to a discussion of narrative approaches that are common in biomedical fields (including the related disciplines of health psychology and social work). We are well aware that insights from the field of narratology could further enrich our thinking about narrative approaches, see our comments in the conclusion.

According to many narrative scholars including Riessman, the mode of transcription is already an important part of analysis and interpretation. See McLellan et al. [ 50 ] for useful background information about and guidelines for transcription.

In conversations about this topic, BR and MM spoke about the ways in which NM activities helped ‘expand the frame of scientific thinking’ that BR as a positivist-minded physician/researcher initially operated from. We don’t want to imply that this effect cannot be reached by taking methodology courses or being mentored by experienced qualitative researchers. However, BR was surprised by how NM activities fostered a deeper understanding of (inter)subjectivity than the various methodology courses she had previously followed.

Other emerging research-ethical issues will be discussed in a separate publication.

A narrative approach to qualitative interviews proved to be most suited to BR’s research project, but we certainly think that the study of ‘enacted stories’ [ 3 ] could further enrich our understanding of (moral) life in healthcare. MM is currently conducting empirical research on the digital transition in pathology and radiology for the RAIDIO study (Responsible Artificial Intelligence in clinical DecisIOn-making). As part of the project, interviews and field observations will be used to develop and publically screen an ethnographic film about the use of AI in image-based medicine as a means of generating public debate and reflection on the digitalization of image-based health care [ 74 , 75 ].

Abbreviations

General practitioner

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Acknowledgements

We would like to thank Ghislaine van Thiel, Margo Trappenburg, staff and fellow-students of Columbia Universities Narrative Medicine CPA-program and fellow-participants of the empirical ethics working group at the UvH for the many constructive conversations about methodology, empirical ethics and narrative approaches that led up to the writing of this article.

In 2018 Megan Milota and Ghislaine van Thiel received a one-year Dutch Comenius Teaching Fellows grant (file nr. 405.18865.277) to develop narrative medicine courses and workshops at the UMC Utrecht. The funding body had no role in the design of the study described in this article, the collection, analysis and interpretation of data, and the writing of the manuscript.

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All authors were involved in conversations about the background theories and concepts as explored in this article and in the data-analysis of a subset of interviews from BR’s research-project using the grid. BR wrote the first draft of the article, MM and CL made substantial changes and contributions. All authors approved the final manuscript.

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The research project of BR as described in this article was evaluated by the Medical Ethical Review Committee of the University Medical Center Utrecht (protocol 19-303/C). The project did not fall within the scope of the Dutch Medical Research Involving Human Subject Act (WMO) and the need for further ethics approval was waived. The Dutch Code of Ethics for research in the social and behavioral sciences involving human participants (2018) was followed . Written informed consent or a recorded verbal consent (in case of interviewing via video-call due to the covid19-pandemic) was obtained from all study participants.

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Not applicable. The examples from the first author’s research project used in this manuscript have been altered to protect the privacy of interviewees. The example provided in Fig.  2 is a fictional example, based on several different interviews.

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Roest, B., Milota, M. & Leget, C. Developing new ways to listen: the value of narrative approaches in empirical (bio)ethics. BMC Med Ethics 22 , 124 (2021). https://doi.org/10.1186/s12910-021-00691-7

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The scope of empirical narratology

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A Review of Empirical Studies Investigating Narrative, Emotion and Meaning-Making Modes and Client Process Markers in Psychotherapy

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• Volume 51 , pages 31–40, ( 2021 )

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• Ana Aleixo   ORCID: orcid.org/0000-0002-6620-9937 1 , 3 ,
• António Pazo Pires 1 ,
• Lynne Angus 2 ,
• David Neto 1 &
• Alexandre Vaz 1  

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Despite the importance of narrative, emotional and meaning-making processes in psychotherapy, there has been no review of studies using the main instruments developed to address these processes. The objective is to review the studies about client narrative and narrative-emotional processes in psychotherapy that used the Narrative Process Coding System or the Narrative-Emotion Process Coding System (1.0 and 2.0). To identify the studies, we searched The Book Collection, PsycINFO, PsycARTICLES, PsycBOOKS, PEP Archive, Psychology and Behavioral Sciences Collection, Academic Search Complete and the Web of Knowledge databases. We found 27 empirical studies using one of the three coding systems. The studies applied the Narrative Process Coding System and the Narrative-Emotion Process Coding System to different therapeutic modalities and patients with various clinical disorders. In some studies, early, middle and late phases of therapy were compared, while other studies conducted intensive case analyses of Narrative Process Coding System and Narrative-Emotion Process Coding System patterns comparing recovered vs unchanged clients. The review supports the importance to look for the contribution of narrative, emotion, meaning-making patterns or narrative-emotion markers, to treatment outcomes and encourages the application of these instruments in process-outcome research in psychotherapy.

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Introduction

The narrative of lived stories has been intrinsic to human beings and their relationships (Angus 2012 ; Gonçalves and Gonçalves 2007 ). The importance of personal narratives to our existence is consensual among diverse authors from philosophy, social sciences and psychology (McAdams 2008 ). Given its importance to human interaction, some authors were interested in narrative expression on therapist-client discourse (Gonçalves 1995 ; Neimeyer and Levitt 2000 ).

The critical assumption of the Narrative Process theory of therapy is that therapists and clients work together to form a coherent self and a meaningful client macronarrative (Angus et al. 1999 ). According to this theory, all forms of psychotherapy with good therapeutic results involve the articulation, elaboration and transformation of clients’ macronarratives. In the 90s, researchers published the first studies on narrative processes in psychotherapy with the development of the Narrative Process Coding System, intentionally designed to identify extended sequences of therapist-client dialogue (Angus 2012 ; Angus and Hardtke 1994 ; Angus et al. 1999 ). These studies already focused on the interconnection of narrative storytelling, emotional expression and meaning-making processes. Since 2014, with the development of the Narrative-Emotion Process Coding System, other articles appeared that focused on increasing levels of narrative-emotion integration in psychotherapy (Angus et al. 2017 ). This integration of narrative and emotion is mainly due to the relevance of scientific evidence that shows that emotional expression and narrative expression, acting alone, are not enough for good therapeutic outcomes (Boritz et al. 2011 ). However, despite the importance of narrative and emotional processes in psychotherapy, a review of the Narrative Process Coding System (Angus et al. 1992 , 1996 ) and the Narrative-Emotion Process Coding System (Angus Narrative-Emotion Process Lab 2015; Angus et al. 2017 ) has not been published yet. Two previous publications (Angus 2012 ; Angus et al. 2017 ) focus on the multi-methodological steps to the creation of Narrative-Emotion Process Coding System (Versions 1.0 and 2.0). In this study, we will briefly describe the development of Narrative Process Coding System and Narrative-Emotion Process Coding System and then focus on their empirical research findings. To our knowledge, there is no other coding system that explicitly addresses the essential interrelationship of narratives (autobiographical memory descriptions) and emotional/experiential processes in therapy session dialogues. It is also the only coding system that explains how narrative and emotion processes are the basis for enhanced self-reflectivity, new meaning-making and self-narrative change.

The Development of Coding Systems

The Narrative Process Coding System is an observer-based empirical measure used by independent raters that enables researchers to identify narrative process modes occurring in therapy session transcripts throughout therapist-client’ dialogue, regardless of therapeutic modality (Angus et al. 1999 ). It was drawn from a dialectical constructivist view of therapeutic change and psychotherapeutic discourse. It enables researchers to capture the micronarrative and macronarrative change processes in psychotherapy in terms of one of three process modes which lead to self-change in psychotherapy. These three narrative processes emerged from the recognition of similarities in the discourse used in the coconstruction of the clients’ macronarratives within the therapy hour, in different modalities.

Both clients and therapists engage in these three different narrative modes: (1) E xternal Narrative mode includes the disclosure of personal stories/autobiographical memories (micronarrative). (2) Internal Narrative mode includes descriptions of bodily felt feelings and emotions, the expression and articulation of affections. (3) Reflexive Narrative mode or meaning-making processes draws into the coupling of both storytelling and emotion processes, and it results in new life themes and self-understandings. These three categories made the Narrative Process Coding System a comprehensive category method of therapeutic interaction, allows the researchers to identify interactional units that contain the verbal interchanges between therapists and clients and understand what happened (External Narrative mode), how it feels (Internal Narrative mode) and what it means (Reflexive Narrative mode). All three narrative types had a critical function to fulfil in the coconstruction of the clients’ self-narrative change (Angus et al. 1999 ).

Over the years, the researchers have established good levels of interrater agreement for the measure’ application (Cohen’s Kappa 0.75), as reported in a series of studies (Angus et al. 1999 , 2004 ). The Narrative Process Coding System was applied with different therapeutic modalities. However, years later, Angus and Greenberg ( 2011 ) realized that in good Emotion-Focused Therapy sessions, narrative processes and emotional processes do not act in isolation but co-occur in the context of enriched storytelling and emotional meaning-making sequences.

To enhance narrative-emotion integration in Emotion-Focused Therapy sessions, Angus and Greenberg ( 2011 ) created eight clinically derived narrative-emotion integration markers. These markers were initially identified for the implementation of process-guiding therapeutic responses. The authors subdivide these Narrative-Emotion Process markers into two categories, to discern the client’s problematic vs productive narrative indicators. The Problem Markers include: Same Old Storytelling, Empty Storytelling, Unstoried Emotion, Superficial Storytelling. The Change Markers include: Competing Plotlines Storytelling, Inchoate Storytelling, Unexpected Outcome Storytelling, Discovery Storytelling. The identification of these critical Narrative-Emotion Process markers makes it possible to improve clinical practice, adjust therapist interventions and support future studies.

Boritz and collaborators developed a first version of Narrative-Emotion Process Coding System (version 1.0) (Boritz et al. 2012 ) to include these Narrative-Emotion Process markers. The Narrative-Emotion Process Coding System 1.0 enables the identification of verbal and non-verbal indicators of narrative and emotion integration by researchers in video-based therapy sessions. This video-based coding system allows access to paralinguistic and non-verbal indicators of narrative-emotion processes, not presented in therapy transcriptions. Several process-outcome studies applied the Narrative-Emotion Process Coding System 1.0.

Three years later, Angus Narrative-Emotion Marker Lab (2015) refined the coding system and standardized a video-based manual to bring different levels of client reflection and meaning-making processes in videotaped therapy sessions. These second version (2.0) includes one new marker subgroup—Transition Markers, with three individual markers. The Narrative-Emotion Process Coding System 2.0 (Angus Narrative-Emotion Marker Lab. 2015 ; Angus et al. 2017 ) identifies 10 individual Narrative-Emotion Process markers, separated by three categories: Problem Markers (Same Old Storytelling, Empty Storytelling, Unstoried Emotion, Superficial Storytelling), Transition Markers (Competing Plotlines Storytelling, Inchoate Storytelling, Experiential Storytelling, and Reflective Storytelling) and Change Markers (Unexpected Outcome Storytelling, Discovery Storytelling). Numerous studies applied the Narrative-Emotion Process Coding System 2.0 to a diverse range of therapeutic modalities and clinical disorders. Previous studies have established excellent levels of interrater agreement (Cohen’s kappa of \(0.80^{ + }\) ) for the application of the Narrative-Emotion Process Coding System 2.0 to a range of therapy approaches and clinical samples.

The present article is the first review of all empirical studies that used one of the three coding systems: either the Narrative Process Coding System (Angus et al. 1992 , 1996 ), or the Narrative-Emotion Process Coding System 1.0 (Boritz et al. 2012 ) or Narrative-Emotion Process Coding System 2.0 (Angus Narrative-Emotion Marker Lab. 2015 , Angus et al. 2017 ). The review will address the research findings emerging from the application of these two measures to a range of clinical disorders and theoretical orientations, followed by a critical discussion of future research directions and implications for practice.

Systematic electronic searches were independently performed by two researchers without a time limit, for the following formula: narrative-emotion processes or NEPCS or Narrative-Emotion Process Coding System or narrative-emotion markers or narrative processes or NPCS or Narrative Process Coding System (full text) and Angus, Lynne (author) in the electronic databases Book Collection, PsycINFO, PsycARTICLES, PsycBOOKS, PEP Archive, Psychology and Behavioral Sciences Collection, Academic Search Complete and Web of Knowledge. We examined the list of references from the review articles, original articles and book chapters to find any more potential study. As inclusion criteria, studies had to apply either the Narrative Process Coding System (Angus et al. 1992 , 1996 ), or Narrative-Emotion Process Coding System 1.0 (Boritz et al. 2012 ) or Narrative-Emotion Process Coding System 2.0 (Angus Narrative-Emotion Marker Lab. 2015 , Angus et al. 2017 ). After careful screening of the records, 27 articles were eligible for inclusion. Footnote 1 We integrated the findings into a narrative review, which involved describing critically, appraising, and comparing the studies into a coherent theoretical framework.

We identified 27 empirical studies, 14 applying the Narrative Process Coding System (Angus et al. 1992 , 1996 ), 3 using the Narrative-Emotion Process Coding System 1.0 (Boritz et al. 2012 ) and 10 the Narrative-Emotion Process Coding System 2.0 (Angus Narrative-Emotion Marker Lab. 2015 ; Angus et al. 2017 ). The empirical findings from the 27 studies are thematically clustered and reviewed in the context of three major subsections: (a) Studies with the Narrative Process Coding System; (b) Studies with the Narrative-Emotion Process Coding System and (c) New Directions in Narrative Process Coding System and Narrative-Emotion Process Coding System Research Studies. The Narrative Process Coding System focuses on narrative modes and the Narrative-Emotion Process Coding System on Narrative-Emotion Process markers. For this reason, we chose to analyze separately the studies carried out with both instruments. In each section we decided to group the studies according the following classification: process-outcome studies, studies using client, therapist, or treatment variables.

Studies with Narrative-Process Coding System

Process-outcome studies.

Most of the studies in this section looked for the relationship between the proportion of narrative modes at different stages of therapy and outcomes. Angus and Hardtke ( 1994 ) illustrate a pioneer study exploring the relationship between narrative process modes and therapeutic outcomes in Brief Dynamic Therapy. The authors applied the Narrative Process Coding System (Angus et al. 1992 ) to the three best and the three worst therapeutic outcomes in different phases of therapy. The results show that successful clients had a higher frequency of Reflexive Narrative modes than unsuccessful clients (42% vs 28%) and a lower frequency of External Narrative modes (47% vs 57%) and Internal Narrative modes (11% vs 15%). Also, the researchers noted that the percentage of Internal and External Narrative modes increased over time in the group with the worst results, compared to the group with the best results, while the frequency of Reflexive Narrative modes increased throughout the therapy sessions (33%, 45%, 48%).

Clients often express themselves with metaphors, but there is a lack of studies focusing on metaphoric expression in psychotherapy. To bridge this gap, Levitt et al. ( 2000 ) sought to understand the relationship between ‘burden’ metaphors and different therapeutic outcomes comparing one recovered vs one unrecovered client in process-experiential therapy. The results demonstrate a significant statistical difference between the two outcomes [ \(X^{2}\) = 13; df = 2; p < 0.001]. While in the best outcome, as the therapy progresses, the burden metaphors are transformed into metaphors “in which the burden is unloaded”, there is no evident transformation in poor therapeutic outcome. Besides, the percentage of metaphors in Reflexive Narrative modes is higher in the case with a good outcome, than in the case with a poor therapeutic outcome (67% vs 65%). The relationship is similar concerning Internal Narrative modes (32% vs 15%). The main conclusion of this study is that successful clients express metaphors to represent personal and internal experiences during the established therapeutic relationship through the expression of internal narratives.

Banham and Schweitzer ( 2015 ) examined the relationship between the results of therapist-client dyads and the narrative processes that occurred in session in initial, mid- and late phases of therapy. They compared the six best therapeutic results with the six worst therapeutic results of a sample of patients diagnosed with depression, followed up in three different therapeutic modalities. The researchers concluded that dyads with better therapeutic outcomes show significant statistical increases [F(2,15) = 19.09; p < 0.001] in the total number of Reflexive Narrative modes throughout the therapy and a higher percentage of Internal Narrative modes in the middle phase [F(1,10) = 14.76; p < 0.01], compared with the group with the worst outcomes. The results also highlight that while at the beginning of therapy, both groups tend to express External Narrative modes, clients with the best results evidenced more Reflexive Narrative modes at the end of the treatment. In contrast, the clients with the worst results continue to engage External Narrative modes, regardless of the stage of therapy.

Lewin’s study corresponds to a methodological progress because it addressed narrative mode shifts instead of the proportion of different narratives. Lewin ( 2010 ) sought to understand the prediction effect of Internal—Reflexive Narrative mode shifts to therapeutic outcome. So, she compared early, middle and late phases of Emotion-Focused Therapy and Client-centered Therapy of recovered vs unrecovered depressed clients. The results revealed no significant statistical association between narrative mode shifts and treatment outcome in Emotion-Focused Therapy sample, using Beck Depression Inventory (p = 0.80) and Global Symptom Index as outcomes (p = 0.76). Client-centered Therapy sample revealed similar results (p = 0.89).

Most of the External Narrative modes identified in psychotherapeutic sessions are reports of autobiographic memories. Some studies have used the Narrative Process Coding System to identify autobiographic memories in External narrative modes and investigate the relationship with treatment outcomes for clinical depression (Boritz et al. 2008 , 2011 ). Boritz et al. ( 2008 ) focused the relationship between autobiographic memories’ specificity and depression. They conducted a study to investigate the relationship between the change in the level of client’s depression and autobiographic memories’ specificity, comparing initial, middle and final phases of Client-centered Therapy and Emotion-Focused Therapy. The authors report the existence of a pattern, regardless of the treatment type and level of clients’ symptomatology at the end of therapy: autobiographic memories’ specificity increases significantly throughout therapy [early to late: t(147) = 2.002; p = 0.047 and middle to late: t(147) = 2.373; p = 0.019]. Boritz et al. ( 2011 ) carried out a similar study to investigate the role of emotional intensity in session. Results suggested a significant statistically positive relationship between autobiographic memories’ specificity and emotional intensity peaks [t(744) = 2.396; p = 0.016] for recovered clients. Thus, the specificity of autobiographic memories if accompanied by high levels of emotional expression seems to be related to better therapeutic outcomes. Literature support this relationship. Researchers highlight that autobiographic memories’ narration, the symbolization of emotions in narrative form, the reflection that takes place in session and the creation of new meanings, allows clients to identify, differentiate and organize their subjective internal experiences (Angus 2012 ; Angus et al. 2004 ).

Treatment and Client Variables

Shortly after being created, Narrative Process Coding System started to be used for comparing narrative modes in different treatment models. Levitt and Angus ( 1999 ) compared Process-Perceptual Therapy, Process-Experiential Therapy and Client-Centered Psychodynamic Therapy. The therapists selected three clients with good therapeutic outcomes for the study. The results demonstrated significant differences in terms of the number of narrative sequences [ \(X^{2}\) (2) = 11.61; p = 0.003] and the type of narrative modes [ \(X^{2}\) (4) = 25.40; p = 0.0001]. There was a higher frequency of Internal Narrative mode in Emotion-Focused Therapy (29%), in comparison to the other two therapies. The therapy with most Reflexive Narrative mode was Process-Perceptual Therapy (54%); with the same frequency of External Narrative mode in Client-Centered Psychodynamic Therapy. Emotion-Focused Therapy demonstrated more narrative mode sequences, emphasizing more narrative mode shifting in therapy. This study stresses the importance of the focus on the internal experiences and self-questioning for good results in therapy and the importance of experiential and information processing as promoters and facilitators of narratives that contribute to good therapeutic outcomes.

Lewin ( 2010 ) pursued a second objective: understand the relationship between narrative process mode shifts of recovered clients and their Experiencing levels (using the Experience Scale, Klein et al. 1970 ). So, regarding recovered Emotion-Focused Therapy and Client-centered Therapy clients, she found a significant statistically relationship (p = 0.00001; p = 0.004), respectively, between Internal – Reflexive Narrative mode shifts and higher levels of clients’ Experiencing, from early stages to late sessions of therapy.

Daniel ( 2011 ) looked for differences in narrative processes in patients with different attachment types. She used the Adult Attachment Interview (AAI) to classify different kinds of attachment. Four dismissing clients and four preoccupied clients, with a diagnosis of bulimia nervosa (DSM-IV-TR), were randomly selected for Cognitive-Behavioral Therapy (CBT) or Psychoanalytic Therapy. The author used six of the first 20 sessions from each of the eight therapy dyads (the most difficult experienced three sessions vs the least difficult experienced three sessions). The authors rated only External modes and Reflexive modes. The results show that the preoccupied clients initiate more narrative mode shifts. However, the study was inconclusive as to the differences between the predominance of External mode and Reflexive mode shifts, for dismissing and preoccupied clients.

In 2013, Armstrong conducted two studies with novice trainee therapists. In the first study, he explored the relationship between narrative process modes, the therapeutic alliance and the evaluation of the session by the client (depth, smoothness, positivity and intensity). The results indicated that Internal to External Narrative process mode shifts and External to Reflexive Narrative process mode shifts predicted client-rated smoothness [(β = − 2.41; p = 0.044); (β = 0.30; p = 0.01)] and client positivity [(β = 0.23; p = 0.030); (β = − 2.82; p = 0.021)], respectively. The narrative process shifts not predicted the client-rated alliance. This study emphasizes the importance of emotion-reflective shifts to a therapy session. As Internal to External mode shifts increased in frequency, client-rated smoothness and positivity decreased. In contrast, as the shifts between External Narrative modes and Reflexive Narrative modes increased, client smoothness and client positivity increased.

Therapist Variables

Armstrong’ ( 2013 ) second study explored the relationship between narrative mode shifts and therapists’ facilitative interpersonal skills measured by Facilitative Interpersonal Skills-In Session (Uhlin et al. 2010 ). Researchers applied this measure to the middle-session or working-phase of each dyad, to explore the influence of other in-session interaction variables and compare the facilitative interpersonal skills’ ratings with client-rated measures linked to outcome. The results point out that shifts between External and Reflexive Narrative mode and between External and Internal narrative mode predicted therapist’ persuasiveness [(β = − 0.03; p = 0.04); (β = 0.33; p = 0.04)] and empathy [(β = − 0.03; p = 0.03) (β = 0.35; p = 0.01)], respectively. Besides, External to Reflexive Narrative mode shifts predicted alliance bond capacity (β = − 0.03; p = 0.05). This study highlights the importance of the therapists’ contribution to Internal – Reflexive mode shifts for facilitating the movement between emotion and meaning-making processes in the session.

The Narrative Process Coding System can also be used to analyze the therapists’ narrative mode. Goates-Jones et al. ( 2009 ) examined the relationship between the timing and the effectiveness of the therapist response modes (using the Helping Skills System, Hill 2004 ) and client narrative modes in the exploration stage of Hill’s helping skills model. The results demonstrated a significant association between therapist response modes and client narrative modes in at least one dyad [ \(X^{2}\) (8) = 93.46; p < 0.001]. Besides, 31% of the cases used more Internal Narrative modes than External or Reflexive Narrative modes when therapists used open questions about feelings and reflections of feelings. Therefore, the authors suggest that, perhaps, some clients are more receptive than others, to respond with feelings or need to highlight their emotional arousal to focus their attention on emotions.

Studies with Narrative-Emotion Process Coding System

Most of studies used Narrative-Emotion Process Coding System to look for the relationship between the proportion of narrative markers in different phases of therapy and outcomes. Boritz et al. ( 2014 ) were the first to apply Narrative-Emotion Process Coding System 1.0 at three phases of the therapeutic process in Client-Centered Therapy, Emotion-Focused Therapy and Cognitive Therapy. Comparing two recovered patients with two patients not recovered from depression, the researchers explored the role of Narrative-Emotion Process markers in psychotherapeutic change. The results emphasize significant higher proportions of Problem Markers in the unrecovered group, namely Abstract Story, in contrast to the recovered clients, in the middle phase of the therapy [t(28) = 2.02; p = 0.05]. Besides, results show significantly higher proportions of Change Markers in the recovered group [F(2,12) = 4.79; p = 0.03], compared to the unrecovered group, independently of the therapy and in all its phases. Among Transition Markers, Inchoate Storytelling [F(1,6) = 7.041; p = 0.037] and Discovery Story [F(1,6) = 25.113; p = 0.002] are significantly associated with client recovery. Besides, the group recovered in Emotion-Focused Therapy demonstrated a significantly higher proportion of Competing Plotlines [F(1,12) = 5.97; p = 0.031] in the middle phase of therapy than the unrecovered group. In turn, the group recovered in Client-centered Therapy showed a significantly higher proportion of this marker, in the initial [F(1,12) = 26.88; p = 0.0002] and middle phases of therapy [F(1,12) = 10.67; p = 0.0067], compared to the non-recovered group. Researchers suggests that Inchoate Storytelling can pave the way to clients’ symbolization and elaboration of their inner experiences and turn Same Old Stories into new views of the self. Thus, an Inchoate Storytelling can be considered a promoter of a Discovery Story, an indicator of the clients’ agency capacity to reflect on new emotional experiences and visions of self.

A new research area is addressing the role of narrative and emotion integration when treating clients for Complex Trauma. Initially, Carpenter et al. ( 2016 ) applied Narrative-Emotion Process Coding System 1.0 to two initial, middle, and final sessions of Emotion-Focused Therapy for Trauma for two recovered clients vs two unrecovered clients. Researchers randomly selected their sample for Imaging Confrontation and Empathic Exploration. The researchers found higher proportions of Transition Markers, namely, Competing Plotlines in the initial (M = 0.08) and mid (M = 0.11) Emotion-Focused Therapy for Trauma phases, in the recovered group, compared to the unrecovered group (initial: M = 0.05; mid: M = 0.03). In turn, the proportion of Competing Plotlines in the last phase of therapy was higher (M = 0.11) in the unrecovered group, compared to the group that recovered (M = 0.00) from the trauma. Regarding Change Markers, Unexpected Outcome Story and Discovery Story, results show a significant stage by outcome interaction [ \(X^{2}\) (2) = 7.74; p = 0.021; \(X^{2}\) (2) = 6.31; p = 0.04], respectively. Thus, in the last phase of therapy, the proportion of Unexpected Outcome Story (M = 0.15) and Discovery Story (M = 0.07) were higher in recovered clients compared to unrecovered clients (M = 0.01, in both markers). Regarding Problem Markers, the unrecovered group showed higher proportions (M = 0.10) than the recovered group (M = 0.02) of Unstoried Emotion. The main conclusion of Carpenter et al. ( 2016 ) is that while unchanged trauma clients have difficulty in elaborating their emotional experiences and solving their problems, the changed clients show greater ease in constructing more positive and cohesive narratives, with new associated meanings.

To expand the research of narrative processes to another diagnosis, implementing the Narrative-Emotion Process Coding System 2.0, Macaulay et al. (under review) carried out a study to identify which Narrative-Emotion Process markers occurred in the sessions associated with good vs poor therapeutic outcomes. Their sample suffered from Generalized Anxiety Disorder (GAD) and went through a Motivational Interviewing integrated with CBT. The results show that unchanged clients have higher proportions of Problem Markers, compared to recovered clients [β = 19.74; t(32) = 2.73; p = 0.01]. In contrast, recovered clients present higher proportions of Change Markers [β = 25.89, t(32) = 4.42, p < 0.001] and Transition Markers, Competing Plotlines [β = 6.06; t(32) = 2.05, p = 0.049] and Reflective Storytelling [β = 8.06; t(32) = 3.82; p < 0.001], when compared to unchanged clients. The main conclusion of this study is that Competing Plotlines and Inchoate Storytelling seem to be processes of potential change when combined with Reflective Storytelling markers. In this sense, it seems essential for some clients, the access to conflicts and the expression of contrary emotions, as indicated by Angus et al. ( 2017 ). Competing Plotlines seems functioning as a sort of catalyst that unlocks the Same Old Storytelling and provides new opportunities for the emergence of more adaptive self, other visions of their emotions and different visions of others.

Khattra et al. ( 2018 ), using a similar methodology to Macaulay et al. (under review), extended the application of Narrative-Emotion Process Coding System 2.0 to CBT for GAD. The results indicate that, throughout therapy, there were no significant differences in the proportions of Problem Markers between recovered vs unrecovered clients. In turn, Transition Markers [t(32) = − 0.09; p = 0.0028] are more frequent in recovered CBT clients compared to unchanged clients, namely Reflective Storytelling [t(32) = − 5.91; p < 0.001]. Researchers also recorded a double proportion of Change Markers in recovered clients [t(32) = − 0.04; p = 0.0206], compared to unrecovered clients, specifically, Unexpected Outcome Storytelling [t(32) = − 0.03; p = 0.0232]. These results agree with Macaulay et al. (under review), supporting the evidence that successful CBT informed therapies for GAD allow the client to reflect on the events that are highlighting a joint experiential work between therapist and client to counter the ambivalence and typical concern of patients with GAD. On the other hand, less successful therapies do not allow the elaboration of new meanings and the adoption of more adaptive actions and emotions.

Using a similar methodology, Bryntwick ( 2016 ) extended her research to a more significant number of participants. The author applied the Narrative-Emotion Process Coding System 2.0 to two early, two middle and two late Emotion-Focused Therapy for Trauma sessions selected from 12 clients (six recovered from the trauma vs six unchanged). The results are consistent with Carpenter et al. ( 2016 ) and Boritz et al. ( 2014 ). Recovered clients have significant statistically higher proportions of Transition Marker (Inchoate Storytelling) in early and mid-therapy phase [Wald \(X^{2}\) (1) = 13.05; p = 0.003; Wald \(X^{2}\) (1) = 12.87; p = 0.003, respectively] and Change Marker (Discovery Storytelling) in mid and late-therapy phases [Wald \(X^{2}\) (1) = 6.67; p = 0.049; Wald \(X^{2}\) (1) = 8.84; p = 0.021, respectively]. In contrast, clients who remained unchanged by treatment termination evidenced significantly more Problem Marker at all stages of therapy [early: Wald \(X^{2}\) (1) = 9.96; p = 0.013; mid: Wald X 2 (1) = 16.02; p = 0.0008; late: Wald X 2 (1) = 13.66; p = 0.002]. The author suggests that the study findings indicate that unchanged clients evidence heightened emotional avoidance throughout treatment phases, while clients who can access, symbolize, and story their inner experiences are more likely to recover (Bryntwick 2016 ).

Recently, some authors tried to understand how narrative flexibility (shifting between the three categories of Narrative-Emotion process markers or movement between individual Narrative-Emotion Process markers) contributes to therapeutic outcome. Boritz et al. ( 2016 ) used the same methodology of the previous study with depressed clients. The results indicate that recovered clients (50.6%) are more likely to have narrative changes than clients who remain depressed (37%) at the end of therapy regardless of the therapeutic modality. Also, the study points out that this probability of change remains constant throughout therapy in recovered clients (β = − 0.0002; t = − 0.53; p = 0.59) and decreases in unrecovered clients (β = − 0.002; t = − 6.63; p < 0.001). On the other hand, unrecovered clients have more difficulty switching from Problem Markers to Change Markers (18.8%) than clients recovered at the end of therapy (33.4%) Wald X 2 = 57.77; p ≤ 0.0001). Results provided preliminary support for the contribution of narrative flexibility to treatment outcome.

The main conclusion to be drawn from the first studies described is that, on the one hand, there appear to be unique patterns of Transition and Change markers that facilitate client change processes in different therapy approaches (Angus et al. 2017 ). Lastly, Boritz et al. ( 2016 ) also highlight that greater narrative flexibility between Narrative-Emotion Process markers and individual markers is associated with recovery. Furthermore, recovered clients have a higher likelihood of productive narrative shifting. Examples of productive shifting are: from a Problem marker to either a Transition or Change marker, from Transition marker to another Transition marker, a Transition marker to a Change marker, Change marker to another Change marker, or from No Client Marker to a Transition marker or a Change marker (Angus et al. 2017 ). On the other hand, unrecovered clients appear to tend to unproductive narrative changes (Bryntwick 2016 ). There is a significant duration of time in any Narrative-Emotion Process Coding System marker and Narrative-Emotion Process Coding System shifting through session (Wald X 2 = 4.01; p = 0.045) (Boritz et al. 2016 ). Narrative shifting appears to be particularly tricky in clients who remain unchanged throughout therapy (Angus et al. 2017 ).

Recently, Duarte ( 2019 ) sought to identify specific interventions used by therapists that promote productive narrative shifting. She used 20 video recorded sessions of the American Psychological Association (APA) from 12 different therapeutic approaches. All videos were rated with the Narrative Emotion Process Coding System 2.0, in minute units, by two trained raters and productive narrative shifting were identified. Two other trained raters rated the therapist’s interventions that preceded each productive shift using the items of the Multitheoretical List of Therapeutic Interventions items (MULTI-60, McCarthy and Barber 2009 ). The results demonstrated that a wide range of interventions facilitated productive narrative shifts. The most frequently used interventions were: (1) focusing on the here-and-now and emotions, exploring the patient’s present feelings and encouraging the patient to talk about avoided emotions; (2) focusing on interpersonal functioning, specifically, identifying the patient’s problematic relational patterns; (3) supporting the patient to examine their interpersonal relationships. These results confirm and expand the results of Friendlander et al. ( 2019 ) looking for a better understanding of what a therapist can do to promote clients’ productive shifting.

New Directions in Narrative Process Coding System and Narrative-Emotion Process Coding System Research Studies

Several authors used Narrative Process Coding System or Narrative-Emotion Process Coding System in intensive case-studies with an exploratory purpose: to explore and analyze narrative processes in different therapeutic modalities (Angus and Bouffard-Bowes 2003 ; Angus and Hardtke 2006 ; Laitila et al. 2001 ; Macaulay and Angus 2019 ; Paivio and Angus 2017 ); to understand the change’ mechanisms or the narrative sequences of change (Angus et al. 2018 ; Friendlander et al. 2018 ; Levenson et al. 2020 ), or identifying specific interventions used by therapists that promote productive narrative shifting (Friendlander et al. 2019 ).

Conclusions and Future Directions

Compared to previous studies, the present empirical review has the benefit of being the first to date that brings together the results of studies applying the Narrative Process Coding System and Narrative-Emotion Process Coding System (1.0 and 2.0). Most studies have been process-outcome studies that looked for the contribution of narrative, emotion, meaning-making patterns, or narrative-emotion markers, to treatment outcomes. In some studies, early, middle, and late phases of therapy were compared, while other studies conducted intensive analyses of Narrative Process Coding System and Narrative-Emotion Process Coding System patterns comparing recovered vs unchanged clients. The research of change patterns in narrative modes and Narrative-Emotion Process markers, using Narrative Process Coding System and Narrative-Emotion Process Coding System, have shown remarkable results, irrespective of therapeutic approaches. Unchanged clients show a significantly higher proportion of External Narrative modes (Narrative Process Coding System) or Problem Markers (Narrative-Emotion Process markers) than successful clients. Results also reveal that recovered clients evidence a significantly higher proportion of Transition Markers (Narrative-Emotion Process markers) earlier in treatment than unchanged clients, that expresses Transition Markers in late-stage sessions, or not at all. These findings have been cross validated in a range of studies and therapy approaches, addressing hundreds of hours of videotaped sessions. Generalization of these findings remains limited by the relatively small number of participants.

Unchanged clients also evidence significantly less narrative flexibility when compared to recovered clients. The literature emphasizes that although a high proportion of Reflexive Narrative modes and Internal Narrative modes is associated with good therapeutic outcomes, the narrative flexibility between different narrative processes modes contributes uniquely, promoting the therapeutic success. While successful clients are more likely to engage in productive narrative shifts, less successful therapy clients have greater difficulty in doing so.

These results allow concluding that recovered clients begin to engage in productive narrative-emotion processing soon after the initiation of treatment. We may think that brief therapies are specifically short for unchanged patients who need more time to elaborate on their emotional experiences and solve their problems. These clients perhaps need more time to adopt more adaptive emotions and actions, as well as creating more coherent narratives of their history. We may also hypothesize that therapeutic interventions for these patients must be specially carved.

Some studies highlight the importance of Transition Markers as susceptible to promote therapeutic change, namely Competing Plotlines and Inchoate Storytelling. In Competing Plotlines, different views connote incoherence and create tension that leads clients to question. In Inchoate Story, the client focuses inward, contacting emergent experience, searching for new meaning. Inchoate Storytelling can pave the way for the symbolization and elaboration of inner experiences and promote the transformation of the Same Old Stories into new views of the self.

The study of autobiographic memories helped to realize the role of specific memories, their reconsolidation and the linking of these memories and emotion in clients’ change. Recently, researchers conclude that the emotions’ exploration and differentiation throughout specific autobiographic memories supports adaptive memories reconsolidation and self-narrative change (Angus et al. 2017 ). Narrative-Emotion Process Coding System 2.0 is an instrument that describes these change processes in session. It identifies storytelling marks that show the degree that client discloses specific autobiographic memories, express, explore, symbolize emotions and bodily felt experiences, reflect on their own or others’ minds, actions and stories and coherently integrate change in a meaning personal story (Angus et al. 2017 ).

Since there is substantial evidence that Transition Markers and narrative flexibility are related to good outcome, and can increase through therapy, clinical implications should be drawn helping therapists to enhance their clinical practice. At the end of a session, therapists can usually tell whether or not it was productive. But they have a harder time saying why, and specially knowing what to do to promote productive sessions. Knowledge of the Narrative-Emotion Process Coding System can help therapists to identify, during the session, if the client is in a non-productive process, repeating his problems, making impersonal, and superficial narratives (Problem Markers), or if he is in a process of change (Transition Markers). Knowledge of the various forms of change that should be happening during the session, such as having conflicting views, believes or action (Competing Plotlines), noticing, exploring and symbolizing bodily felt experiences (Inchoate Storytelling), re-experiencing some events (Experiential Story), or exploring general patterns (Reflective Story) can, in turn, guide the therapist to find interventions to bring about that processes.

Regarding future research, we must emphasize the need to repeat the studies but performed with larger samples because most of the samples studied are small. Several studies do not have more than six clients. On the other hand, the researchers applied Narrative Process Coding System or Narrative-Emotion Process Coding System to short-term therapies. Future research needs to replicate the findings in long-term therapies and consider the severity of symptoms to understand how and when the more difficult patients change. Future studies should also focus on the characteristics and interventions of the therapist for client change in Narrative-Emotion Process markers, namely, what specific interventions and features of the therapist promote productive transitions. Only a few studies addressed these topics. Within the same therapeutic approach there is such a wide variety of ways of intervening therapeutically and a wide range of efficacy among therapists that exploring the variety of ways to bring about productive change, and especially with the most challenging cases, should be explored. We need further studies to amplify the promising results of the narrative change in Emotion-Focuded Therapy for Trauma.

You can request the table of included studies by contacting the first author.

The studies included in this review are marked with *

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Ana Aleixo, António Pazo Pires, David Neto & Alexandre Vaz

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Aleixo, A., Pires, A.P., Angus, L. et al. A Review of Empirical Studies Investigating Narrative, Emotion and Meaning-Making Modes and Client Process Markers in Psychotherapy. J Contemp Psychother 51 , 31–40 (2021). https://doi.org/10.1007/s10879-020-09472-6

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What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 36min read

Ever wondered how we gather the facts, unveil hidden truths, and make informed decisions in a world filled with questions? Empirical research holds the key.

In this guide, we'll delve deep into the art and science of empirical research, unraveling its methods, mysteries, and manifold applications. From defining the core principles to mastering data analysis and reporting findings, we're here to equip you with the knowledge and tools to navigate the empirical landscape.

What is Empirical Research?

Empirical research is the cornerstone of scientific inquiry, providing a systematic and structured approach to investigating the world around us. It is the process of gathering and analyzing empirical or observable data to test hypotheses, answer research questions, or gain insights into various phenomena. This form of research relies on evidence derived from direct observation or experimentation, allowing researchers to draw conclusions based on real-world data rather than purely theoretical or speculative reasoning.

Characteristics of Empirical Research

Empirical research is characterized by several key features:

• Observation and Measurement : It involves the systematic observation or measurement of variables, events, or behaviors.
• Data Collection : Researchers collect data through various methods, such as surveys, experiments, observations, or interviews.
• Testable Hypotheses : Empirical research often starts with testable hypotheses that are evaluated using collected data.
• Quantitative or Qualitative Data : Data can be quantitative (numerical) or qualitative (non-numerical), depending on the research design.
• Statistical Analysis : Quantitative data often undergo statistical analysis to determine patterns , relationships, or significance.
• Objectivity and Replicability : Empirical research strives for objectivity, minimizing researcher bias . It should be replicable, allowing other researchers to conduct the same study to verify results.
• Conclusions and Generalizations : Empirical research generates findings based on data and aims to make generalizations about larger populations or phenomena.

Importance of Empirical Research

Empirical research plays a pivotal role in advancing knowledge across various disciplines. Its importance extends to academia, industry, and society as a whole. Here are several reasons why empirical research is essential:

• Evidence-Based Knowledge : Empirical research provides a solid foundation of evidence-based knowledge. It enables us to test hypotheses, confirm or refute theories, and build a robust understanding of the world.
• Scientific Progress : In the scientific community, empirical research fuels progress by expanding the boundaries of existing knowledge. It contributes to the development of theories and the formulation of new research questions.
• Problem Solving : Empirical research is instrumental in addressing real-world problems and challenges. It offers insights and data-driven solutions to complex issues in fields like healthcare, economics, and environmental science.
• Informed Decision-Making : In policymaking, business, and healthcare, empirical research informs decision-makers by providing data-driven insights. It guides strategies, investments, and policies for optimal outcomes.
• Quality Assurance : Empirical research is essential for quality assurance and validation in various industries, including pharmaceuticals, manufacturing, and technology. It ensures that products and processes meet established standards.
• Continuous Improvement : Businesses and organizations use empirical research to evaluate performance, customer satisfaction, and product effectiveness. This data-driven approach fosters continuous improvement and innovation.
• Human Advancement : Empirical research in fields like medicine and psychology contributes to the betterment of human health and well-being. It leads to medical breakthroughs, improved therapies, and enhanced psychological interventions.
• Critical Thinking and Problem Solving : Engaging in empirical research fosters critical thinking skills, problem-solving abilities, and a deep appreciation for evidence-based decision-making.

Empirical research empowers us to explore, understand, and improve the world around us. It forms the bedrock of scientific inquiry and drives progress in countless domains, shaping our understanding of both the natural and social sciences.

How to Conduct Empirical Research?

So, you've decided to dive into the world of empirical research. Let's begin by exploring the crucial steps involved in getting started with your research project.

1. Select a Research Topic

Selecting the right research topic is the cornerstone of a successful empirical study. It's essential to choose a topic that not only piques your interest but also aligns with your research goals and objectives. Here's how to go about it:

• Identify Your Interests : Start by reflecting on your passions and interests. What topics fascinate you the most? Your enthusiasm will be your driving force throughout the research process.
• Brainstorm Ideas : Engage in brainstorming sessions to generate potential research topics. Consider the questions you've always wanted to answer or the issues that intrigue you.
• Relevance and Significance : Assess the relevance and significance of your chosen topic. Does it contribute to existing knowledge? Is it a pressing issue in your field of study or the broader community?
• Feasibility : Evaluate the feasibility of your research topic. Do you have access to the necessary resources, data, and participants (if applicable)?

2. Formulate Research Questions

Once you've narrowed down your research topic, the next step is to formulate clear and precise research questions . These questions will guide your entire research process and shape your study's direction. To create effective research questions:

• Specificity : Ensure that your research questions are specific and focused. Vague or overly broad questions can lead to inconclusive results.
• Relevance : Your research questions should directly relate to your chosen topic. They should address gaps in knowledge or contribute to solving a particular problem.
• Testability : Ensure that your questions are testable through empirical methods. You should be able to gather data and analyze it to answer these questions.
• Avoid Bias : Craft your questions in a way that avoids leading or biased language. Maintain neutrality to uphold the integrity of your research.

3. Review Existing Literature

Before you embark on your empirical research journey, it's essential to immerse yourself in the existing body of literature related to your chosen topic. This step, often referred to as a literature review, serves several purposes:

• Contextualization : Understand the historical context and current state of research in your field. What have previous studies found, and what questions remain unanswered?
• Identifying Gaps : Identify gaps or areas where existing research falls short. These gaps will help you formulate meaningful research questions and hypotheses.
• Theory Development : If your study is theoretical, consider how existing theories apply to your topic. If it's empirical, understand how previous studies have approached data collection and analysis.
• Methodological Insights : Learn from the methodologies employed in previous research. What methods were successful, and what challenges did researchers face?

4. Define Variables

Variables are fundamental components of empirical research. They are the factors or characteristics that can change or be manipulated during your study. Properly defining and categorizing variables is crucial for the clarity and validity of your research. Here's what you need to know:

• Independent Variables : These are the variables that you, as the researcher, manipulate or control. They are the "cause" in cause-and-effect relationships.
• Dependent Variables : Dependent variables are the outcomes or responses that you measure or observe. They are the "effect" influenced by changes in independent variables.
• Operational Definitions : To ensure consistency and clarity, provide operational definitions for your variables. Specify how you will measure or manipulate each variable.
• Control Variables : In some studies, controlling for other variables that may influence your dependent variable is essential. These are known as control variables.

Understanding these foundational aspects of empirical research will set a solid foundation for the rest of your journey. Now that you've grasped the essentials of getting started, let's delve deeper into the intricacies of research design.

Empirical Research Design

Now that you've selected your research topic, formulated research questions, and defined your variables, it's time to delve into the heart of your empirical research journey – research design . This pivotal step determines how you will collect data and what methods you'll employ to answer your research questions. Let's explore the various facets of research design in detail.

Types of Empirical Research

Empirical research can take on several forms, each with its own unique approach and methodologies. Understanding the different types of empirical research will help you choose the most suitable design for your study. Here are some common types:

• Experimental Research : In this type, researchers manipulate one or more independent variables to observe their impact on dependent variables. It's highly controlled and often conducted in a laboratory setting.
• Observational Research : Observational research involves the systematic observation of subjects or phenomena without intervention. Researchers are passive observers, documenting behaviors, events, or patterns.
• Survey Research : Surveys are used to collect data through structured questionnaires or interviews. This method is efficient for gathering information from a large number of participants.
• Case Study Research : Case studies focus on in-depth exploration of one or a few cases. Researchers gather detailed information through various sources such as interviews, documents, and observations.
• Qualitative Research : Qualitative research aims to understand behaviors, experiences, and opinions in depth. It often involves open-ended questions, interviews, and thematic analysis.
• Quantitative Research : Quantitative research collects numerical data and relies on statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys.

Your choice of research type should align with your research questions and objectives. Experimental research, for example, is ideal for testing cause-and-effect relationships, while qualitative research is more suitable for exploring complex phenomena.

Experimental Design

Experimental research is a systematic approach to studying causal relationships. It's characterized by the manipulation of one or more independent variables while controlling for other factors. Here are some key aspects of experimental design:

• Control and Experimental Groups : Participants are randomly assigned to either a control group or an experimental group. The independent variable is manipulated for the experimental group but not for the control group.
• Randomization : Randomization is crucial to eliminate bias in group assignment. It ensures that each participant has an equal chance of being in either group.
• Hypothesis Testing : Experimental research often involves hypothesis testing. Researchers formulate hypotheses about the expected effects of the independent variable and use statistical analysis to test these hypotheses.

Observational Design

Observational research entails careful and systematic observation of subjects or phenomena. It's advantageous when you want to understand natural behaviors or events. Key aspects of observational design include:

• Participant Observation : Researchers immerse themselves in the environment they are studying. They become part of the group being observed, allowing for a deep understanding of behaviors.
• Non-Participant Observation : In non-participant observation, researchers remain separate from the subjects. They observe and document behaviors without direct involvement.
• Data Collection Methods : Observational research can involve various data collection methods, such as field notes, video recordings, photographs, or coding of observed behaviors.

Survey Design

Surveys are a popular choice for collecting data from a large number of participants. Effective survey design is essential to ensure the validity and reliability of your data. Consider the following:

• Questionnaire Design : Create clear and concise questions that are easy for participants to understand. Avoid leading or biased questions.
• Sampling Methods : Decide on the appropriate sampling method for your study, whether it's random, stratified, or convenience sampling.
• Data Collection Tools : Choose the right tools for data collection, whether it's paper surveys, online questionnaires, or face-to-face interviews.

Case Study Design

Case studies are an in-depth exploration of one or a few cases to gain a deep understanding of a particular phenomenon. Key aspects of case study design include:

• Single Case vs. Multiple Case Studies : Decide whether you'll focus on a single case or multiple cases. Single case studies are intensive and allow for detailed examination, while multiple case studies provide comparative insights.
• Data Collection Methods : Gather data through interviews, observations, document analysis, or a combination of these methods.

Qualitative vs. Quantitative Research

In empirical research, you'll often encounter the distinction between qualitative and quantitative research . Here's a closer look at these two approaches:

• Qualitative Research : Qualitative research seeks an in-depth understanding of human behavior, experiences, and perspectives. It involves open-ended questions, interviews, and the analysis of textual or narrative data. Qualitative research is exploratory and often used when the research question is complex and requires a nuanced understanding.
• Quantitative Research : Quantitative research collects numerical data and employs statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys. Quantitative research is ideal for testing hypotheses and establishing cause-and-effect relationships.

Understanding the various research design options is crucial in determining the most appropriate approach for your study. Your choice should align with your research questions, objectives, and the nature of the phenomenon you're investigating.

Data Collection for Empirical Research

Now that you've established your research design, it's time to roll up your sleeves and collect the data that will fuel your empirical research. Effective data collection is essential for obtaining accurate and reliable results.

Sampling Methods

Sampling methods are critical in empirical research, as they determine the subset of individuals or elements from your target population that you will study. Here are some standard sampling methods:

• Random Sampling : Random sampling ensures that every member of the population has an equal chance of being selected. It minimizes bias and is often used in quantitative research.
• Stratified Sampling : Stratified sampling involves dividing the population into subgroups or strata based on specific characteristics (e.g., age, gender, location). Samples are then randomly selected from each stratum, ensuring representation of all subgroups.
• Convenience Sampling : Convenience sampling involves selecting participants who are readily available or easily accessible. While it's convenient, it may introduce bias and limit the generalizability of results.
• Snowball Sampling : Snowball sampling is instrumental when studying hard-to-reach or hidden populations. One participant leads you to another, creating a "snowball" effect. This method is common in qualitative research.
• Purposive Sampling : In purposive sampling, researchers deliberately select participants who meet specific criteria relevant to their research questions. It's often used in qualitative studies to gather in-depth information.

The choice of sampling method depends on the nature of your research, available resources, and the degree of precision required. It's crucial to carefully consider your sampling strategy to ensure that your sample accurately represents your target population.

Data Collection Instruments

Data collection instruments are the tools you use to gather information from your participants or sources. These instruments should be designed to capture the data you need accurately. Here are some popular data collection instruments:

• Questionnaires : Questionnaires consist of structured questions with predefined response options. When designing questionnaires, consider the clarity of questions, the order of questions, and the response format (e.g., Likert scale , multiple-choice).
• Interviews : Interviews involve direct communication between the researcher and participants. They can be structured (with predetermined questions) or unstructured (open-ended). Effective interviews require active listening and probing for deeper insights.
• Observations : Observations entail systematically and objectively recording behaviors, events, or phenomena. Researchers must establish clear criteria for what to observe, how to record observations, and when to observe.
• Surveys : Surveys are a common data collection instrument for quantitative research. They can be administered through various means, including online surveys, paper surveys, and telephone surveys.
• Documents and Archives : In some cases, data may be collected from existing documents, records, or archives. Ensure that the sources are reliable, relevant, and properly documented.

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Data Collection Procedures

Data collection procedures outline the step-by-step process for gathering data. These procedures should be meticulously planned and executed to maintain the integrity of your research.

• Training : If you have a research team, ensure that they are trained in data collection methods and protocols. Consistency in data collection is crucial.
• Pilot Testing : Before launching your data collection, conduct a pilot test with a small group to identify any potential problems with your instruments or procedures. Make necessary adjustments based on feedback.
• Data Recording : Establish a systematic method for recording data. This may include timestamps, codes, or identifiers for each data point.
• Data Security : Safeguard the confidentiality and security of collected data. Ensure that only authorized individuals have access to the data.
• Data Storage : Properly organize and store your data in a secure location, whether in physical or digital form. Back up data to prevent loss.

Ethical Considerations

Ethical considerations are paramount in empirical research, as they ensure the well-being and rights of participants are protected.

• Informed Consent : Obtain informed consent from participants, providing clear information about the research purpose, procedures, risks, and their right to withdraw at any time.
• Privacy and Confidentiality : Protect the privacy and confidentiality of participants. Ensure that data is anonymized and sensitive information is kept confidential.
• Beneficence : Ensure that your research benefits participants and society while minimizing harm. Consider the potential risks and benefits of your study.
• Honesty and Integrity : Conduct research with honesty and integrity. Report findings accurately and transparently, even if they are not what you expected.
• Respect for Participants : Treat participants with respect, dignity, and sensitivity to cultural differences. Avoid any form of coercion or manipulation.
• Institutional Review Board (IRB) : If required, seek approval from an IRB or ethics committee before conducting your research, particularly when working with human participants.

Adhering to ethical guidelines is not only essential for the ethical conduct of research but also crucial for the credibility and validity of your study. Ethical research practices build trust between researchers and participants and contribute to the advancement of knowledge with integrity.

With a solid understanding of data collection, including sampling methods, instruments, procedures, and ethical considerations, you are now well-equipped to gather the data needed to answer your research questions.

Empirical Research Data Analysis

Now comes the exciting phase of data analysis, where the raw data you've diligently collected starts to yield insights and answers to your research questions. We will explore the various aspects of data analysis, from preparing your data to drawing meaningful conclusions through statistics and visualization.

Data Preparation

Data preparation is the crucial first step in data analysis. It involves cleaning, organizing, and transforming your raw data into a format that is ready for analysis. Effective data preparation ensures the accuracy and reliability of your results.

• Data Cleaning : Identify and rectify errors, missing values, and inconsistencies in your dataset. This may involve correcting typos, removing outliers, and imputing missing data.
• Data Coding : Assign numerical values or codes to categorical variables to make them suitable for statistical analysis. For example, converting "Yes" and "No" to 1 and 0.
• Data Transformation : Transform variables as needed to meet the assumptions of the statistical tests you plan to use. Common transformations include logarithmic or square root transformations.
• Data Integration : If your data comes from multiple sources, integrate it into a unified dataset, ensuring that variables match and align.
• Data Documentation : Maintain clear documentation of all data preparation steps, as well as the rationale behind each decision. This transparency is essential for replicability.

Effective data preparation lays the foundation for accurate and meaningful analysis. It allows you to trust the results that will follow in the subsequent stages.

Descriptive Statistics

Descriptive statistics help you summarize and make sense of your data by providing a clear overview of its key characteristics. These statistics are essential for understanding the central tendencies, variability, and distribution of your variables. Descriptive statistics include:

• Measures of Central Tendency : These include the mean (average), median (middle value), and mode (most frequent value). They help you understand the typical or central value of your data.
• Measures of Dispersion : Measures like the range, variance, and standard deviation provide insights into the spread or variability of your data points.
• Frequency Distributions : Creating frequency distributions or histograms allows you to visualize the distribution of your data across different values or categories.

Descriptive statistics provide the initial insights needed to understand your data's basic characteristics, which can inform further analysis.

Inferential Statistics

Inferential statistics take your analysis to the next level by allowing you to make inferences or predictions about a larger population based on your sample data. These methods help you test hypotheses and draw meaningful conclusions. Key concepts in inferential statistics include:

• Hypothesis Testing : Hypothesis tests (e.g., t-tests, chi-squared tests) help you determine whether observed differences or associations in your data are statistically significant or occurred by chance.
• Confidence Intervals : Confidence intervals provide a range within which population parameters (e.g., population mean) are likely to fall based on your sample data.
• Regression Analysis : Regression models (linear, logistic, etc.) help you explore relationships between variables and make predictions.
• Analysis of Variance (ANOVA) : ANOVA tests are used to compare means between multiple groups, allowing you to assess whether differences are statistically significant.

Inferential statistics are powerful tools for drawing conclusions from your data and assessing the generalizability of your findings to the broader population.

Qualitative Data Analysis

Qualitative data analysis is employed when working with non-numerical data, such as text, interviews, or open-ended survey responses. It focuses on understanding the underlying themes, patterns, and meanings within qualitative data. Qualitative analysis techniques include:

• Thematic Analysis : Identifying and analyzing recurring themes or patterns within textual data.
• Content Analysis : Categorizing and coding qualitative data to extract meaningful insights.
• Grounded Theory : Developing theories or frameworks based on emergent themes from the data.
• Narrative Analysis : Examining the structure and content of narratives to uncover meaning.

Qualitative data analysis provides a rich and nuanced understanding of complex phenomena and human experiences.

Data Visualization

Data visualization is the art of representing data graphically to make complex information more understandable and accessible. Effective data visualization can reveal patterns, trends, and outliers in your data. Common types of data visualization include:

• Bar Charts and Histograms : Used to display the distribution of categorical data or discrete data .
• Line Charts : Ideal for showing trends and changes in data over time.
• Scatter Plots : Visualize relationships and correlations between two variables.
• Pie Charts : Display the composition of a whole in terms of its parts.
• Heatmaps : Depict patterns and relationships in multidimensional data through color-coding.
• Box Plots : Provide a summary of the data distribution, including outliers.
• Interactive Dashboards : Create dynamic visualizations that allow users to explore data interactively.

Data visualization not only enhances your understanding of the data but also serves as a powerful communication tool to convey your findings to others.

As you embark on the data analysis phase of your empirical research, remember that the specific methods and techniques you choose will depend on your research questions, data type, and objectives. Effective data analysis transforms raw data into valuable insights, bringing you closer to the answers you seek.

How to Report Empirical Research Results?

At this stage, you get to share your empirical research findings with the world. Effective reporting and presentation of your results are crucial for communicating your research's impact and insights.

1. Write the Research Paper

Writing a research paper is the culmination of your empirical research journey. It's where you synthesize your findings, provide context, and contribute to the body of knowledge in your field.

• Title and Abstract : Craft a clear and concise title that reflects your research's essence. The abstract should provide a brief summary of your research objectives, methods, findings, and implications.
• Introduction : In the introduction, introduce your research topic, state your research questions or hypotheses, and explain the significance of your study. Provide context by discussing relevant literature.
• Methods : Describe your research design, data collection methods, and sampling procedures. Be precise and transparent, allowing readers to understand how you conducted your study.
• Results : Present your findings in a clear and organized manner. Use tables, graphs, and statistical analyses to support your results. Avoid interpreting your findings in this section; focus on the presentation of raw data.
• Discussion : Interpret your findings and discuss their implications. Relate your results to your research questions and the existing literature. Address any limitations of your study and suggest avenues for future research.
• Conclusion : Summarize the key points of your research and its significance. Restate your main findings and their implications.
• References : Cite all sources used in your research following a specific citation style (e.g., APA, MLA, Chicago). Ensure accuracy and consistency in your citations.
• Appendices : Include any supplementary material, such as questionnaires, data coding sheets, or additional analyses, in the appendices.

Writing a research paper is a skill that improves with practice. Ensure clarity, coherence, and conciseness in your writing to make your research accessible to a broader audience.

2. Create Visuals and Tables

Visuals and tables are powerful tools for presenting complex data in an accessible and understandable manner.

• Clarity : Ensure that your visuals and tables are clear and easy to interpret. Use descriptive titles and labels.
• Consistency : Maintain consistency in formatting, such as font size and style, across all visuals and tables.
• Appropriateness : Choose the most suitable visual representation for your data. Bar charts, line graphs, and scatter plots work well for different types of data.
• Simplicity : Avoid clutter and unnecessary details. Focus on conveying the main points.
• Accessibility : Make sure your visuals and tables are accessible to a broad audience, including those with visual impairments.
• Captions : Include informative captions that explain the significance of each visual or table.

Compelling visuals and tables enhance the reader's understanding of your research and can be the key to conveying complex information efficiently.

3. Interpret Findings

Interpreting your findings is where you bridge the gap between data and meaning. It's your opportunity to provide context, discuss implications, and offer insights. When interpreting your findings:

• Relate to Research Questions : Discuss how your findings directly address your research questions or hypotheses.
• Compare with Literature : Analyze how your results align with or deviate from previous research in your field. What insights can you draw from these comparisons?
• Discuss Limitations : Be transparent about the limitations of your study. Address any constraints, biases, or potential sources of error.
• Practical Implications : Explore the real-world implications of your findings. How can they be applied or inform decision-making?
• Future Research Directions : Suggest areas for future research based on the gaps or unanswered questions that emerged from your study.

Interpreting findings goes beyond simply presenting data; it's about weaving a narrative that helps readers grasp the significance of your research in the broader context.

With your research paper written, structured, and enriched with visuals, and your findings expertly interpreted, you are now prepared to communicate your research effectively. Sharing your insights and contributing to the body of knowledge in your field is a significant accomplishment in empirical research.

Examples of Empirical Research

To solidify your understanding of empirical research, let's delve into some real-world examples across different fields. These examples will illustrate how empirical research is applied to gather data, analyze findings, and draw conclusions.

Social Sciences

In the realm of social sciences, consider a sociological study exploring the impact of socioeconomic status on educational attainment. Researchers gather data from a diverse group of individuals, including their family backgrounds, income levels, and academic achievements.

Through statistical analysis, they can identify correlations and trends, revealing whether individuals from lower socioeconomic backgrounds are less likely to attain higher levels of education. This empirical research helps shed light on societal inequalities and informs policymakers on potential interventions to address disparities in educational access.

Environmental Science

Environmental scientists often employ empirical research to assess the effects of environmental changes. For instance, researchers studying the impact of climate change on wildlife might collect data on animal populations, weather patterns, and habitat conditions over an extended period.

By analyzing this empirical data, they can identify correlations between climate fluctuations and changes in wildlife behavior, migration patterns, or population sizes. This empirical research is crucial for understanding the ecological consequences of climate change and informing conservation efforts.

Business and Economics

In the business world, empirical research is essential for making data-driven decisions. Consider a market research study conducted by a business seeking to launch a new product. They collect data through surveys , focus groups , and consumer behavior analysis.

By examining this empirical data, the company can gauge consumer preferences, demand, and potential market size. Empirical research in business helps guide product development, pricing strategies, and marketing campaigns, increasing the likelihood of a successful product launch.

Psychological studies frequently rely on empirical research to understand human behavior and cognition. For instance, a psychologist interested in examining the impact of stress on memory might design an experiment. Participants are exposed to stress-inducing situations, and their memory performance is assessed through various tasks.

By analyzing the data collected, the psychologist can determine whether stress has a significant effect on memory recall. This empirical research contributes to our understanding of the complex interplay between psychological factors and cognitive processes.

These examples highlight the versatility and applicability of empirical research across diverse fields. Whether in medicine, social sciences, environmental science, business, or psychology, empirical research serves as a fundamental tool for gaining insights, testing hypotheses, and driving advancements in knowledge and practice.

Conclusion for Empirical Research

Empirical research is a powerful tool for gaining insights, testing hypotheses, and making informed decisions. By following the steps outlined in this guide, you've learned how to select research topics, collect data, analyze findings, and effectively communicate your research to the world. Remember, empirical research is a journey of discovery, and each step you take brings you closer to a deeper understanding of the world around you. Whether you're a scientist, a student, or someone curious about the process, the principles of empirical research empower you to explore, learn, and contribute to the ever-expanding realm of knowledge.

How to Collect Data for Empirical Research?

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Empirical Research: Defining, Identifying, & Finding

Defining empirical research, what is empirical research, quantitative or qualitative.

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Calfee & Chambliss (2005)  (UofM login required) describe empirical research as a "systematic approach for answering certain types of questions."  Those questions are answered "[t]hrough the collection of evidence under carefully defined and replicable conditions" (p. 43). 

The evidence collected during empirical research is often referred to as "data." 

Characteristics of Empirical Research

Emerald Publishing's guide to conducting empirical research identifies a number of common elements to empirical research: 

• A  research question , which will determine research objectives.
• A particular and planned  design  for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
• The gathering of  primary data , which is then analysed.
• A particular  methodology  for collecting and analysing the data, such as an experiment or survey.
• The limitation of the data to a particular group, area or time scale, known as a sample [emphasis added]: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
• The ability to  recreate  the study and test the results. This is known as  reliability .
• The ability to  generalize  from the findings to a larger sample and to other situations.

If you see these elements in a research article, you can feel confident that you have found empirical research. Emerald's guide goes into more detail on each element. 

Empirical research methodologies can be described as quantitative, qualitative, or a mix of both (usually called mixed-methods).

Ruane (2016)  (UofM login required) gets at the basic differences in approach between quantitative and qualitative research:

• Quantitative research  -- an approach to documenting reality that relies heavily on numbers both for the measurement of variables and for data analysis (p. 33).
• Qualitative research  -- an approach to documenting reality that relies on words and images as the primary data source (p. 33).

Both quantitative and qualitative methods are empirical . If you can recognize that a research study is quantitative or qualitative study, then you have also recognized that it is empirical study. 

Below are information on the characteristics of quantitative and qualitative research. This video from Scribbr also offers a good overall introduction to the two approaches to research methodology: 

Characteristics of Quantitative Research 

Researchers test hypotheses, or theories, based in assumptions about causality, i.e. we expect variable X to cause variable Y. Variables have to be controlled as much as possible to ensure validity. The results explain the relationship between the variables. Measures are based in pre-defined instruments.

Examples: experimental or quasi-experimental design, pretest & post-test, survey or questionnaire with closed-ended questions. Studies that identify factors that influence an outcomes, the utility of an intervention, or understanding predictors of outcomes. 

Characteristics of Qualitative Research

Researchers explore “meaning individuals or groups ascribe to social or human problems (Creswell & Creswell, 2018, p3).” Questions and procedures emerge rather than being prescribed. Complexity, nuance, and individual meaning are valued. Research is both inductive and deductive. Data sources are multiple and varied, i.e. interviews, observations, documents, photographs, etc. The researcher is a key instrument and must be reflective of their background, culture, and experiences as influential of the research.

Examples: open question interviews and surveys, focus groups, case studies, grounded theory, ethnography, discourse analysis, narrative, phenomenology, participatory action research.

Calfee, R. C. & Chambliss, M. (2005). The design of empirical research. In J. Flood, D. Lapp, J. R. Squire, & J. Jensen (Eds.),  Methods of research on teaching the English language arts: The methodology chapters from the handbook of research on teaching the English language arts (pp. 43-78). Routledge.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=125955&site=eds-live&scope=site .

Creswell, J. W., & Creswell, J. D. (2018).  Research design: Qualitative, quantitative, and mixed methods approaches  (5th ed.). Thousand Oaks: Sage.

How to... conduct empirical research . (n.d.). Emerald Publishing.  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research .

Scribbr. (2019). Quantitative vs. qualitative: The differences explained  [video]. YouTube.  https://www.youtube.com/watch?v=a-XtVF7Bofg .

Ruane, J. M. (2016).  Introducing social research methods : Essentials for getting the edge . Wiley-Blackwell.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1107215&site=eds-live&scope=site .  

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Andrew Piper , Richard Jean So , David Bamman

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[Narrative Theory for Computational Narrative Understanding](https://aclanthology.org/2021.emnlp-main.26) (Piper et al., EMNLP 2021)

• Narrative Theory for Computational Narrative Understanding (Piper et al., EMNLP 2021)
• Andrew Piper, Richard Jean So, and David Bamman. 2021. Narrative Theory for Computational Narrative Understanding . In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , pages 298–311, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.

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Causal Inference About the Effects of Interventions From Observational Studies in Medical Journals

• 1 CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
• 2 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
• 3 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
• 4 Smith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
• 5 Statistical Editor, JAMA
• 6 Department of Medicine, University of California, San Francisco
• 7 Department of Epidemiology and Biostatistics, University of California, San Francisco
• 8 Editor in Chief, JAMA and JAMA Network
• Editor's Note Meaning of Proposed Causal Inference Framework for the JAMA Network Annette Flanagin, RN, MA; Roger J. Lewis, MD, PhD; Christopher C. Muth, MD; Gregory Curfman, MD JAMA

Importance   Many medical journals, including JAMA, restrict the use of causal language to the reporting of randomized clinical trials. Although well-conducted randomized clinical trials remain the preferred approach for answering causal questions, methods for observational studies have advanced such that causal interpretations of the results of well-conducted observational studies may be possible when strong assumptions hold. Furthermore, observational studies may be the only practical source of information for answering some questions about the causal effects of medical or policy interventions, can support the study of interventions in populations and settings that reflect practice, and can help identify interventions for further experimental investigation. Identifying opportunities for the appropriate use of causal language when describing observational studies is important for communication in medical journals.

Observations   A structured approach to whether and how causal language may be used when describing observational studies would enhance the communication of research goals, support the assessment of assumptions and design and analytic choices, and allow for more clear and accurate interpretation of results. Building on the extensive literature on causal inference across diverse disciplines, we suggest a framework for observational studies that aim to provide evidence about the causal effects of interventions based on 6 core questions: what is the causal question; what quantity would, if known, answer the causal question; what is the study design; what causal assumptions are being made; how can the observed data be used to answer the causal question in principle and in practice; and is a causal interpretation of the analyses tenable?

Conclusions and Relevance   Adoption of the proposed framework to identify when causal interpretation is appropriate in observational studies promises to facilitate better communication between authors, reviewers, editors, and readers. Practical implementation will require cooperation between editors, authors, and reviewers to operationalize the framework and evaluate its effect on the reporting of empirical research.

• Editor's Note Meaning of Proposed Causal Inference Framework for the JAMA Network JAMA

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Dahabreh IJ , Bibbins-Domingo K. Causal Inference About the Effects of Interventions From Observational Studies in Medical Journals. JAMA. Published online May 09, 2024. doi:10.1001/jama.2024.7741

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Empirical Tests of the Green Paradox for Climate Legislation

The Green Paradox posits that fossil fuel markets respond to changing expectations about climate legislation, which limits future consumption, by shifting consumption to the present through lower present-day prices. We demonstrate that oil futures responded negatively to daily changes in the prediction market's expectations that the Waxman-Markey bill — the US climate bill discussed in 2009-2010 — would pass. This effect is consistent across various maturities as the proposed legislation would reset the entire price and consumption path, unlike temporary supply or demand shocks that phase out over time. The bill’s passage would have increased current global oil consumption by 2-4%. Furthermore, a strengthening of climate policy, as measured by monthly variations in media salience regarding climate policy over the last four decades, and two court rulings signaling limited future fossil fuel use, were associated with negative abnormal oil future returns. Taken together, our findings confirm that restricting future fossil fuel use will accelerate current-day consumption.

We would like to thank Kyle Meng and Derek Lemoine for sharing the prediction market data and for helpful feedback, as well as participants of the Virtual Seminar on Climate Economics by the Federal Reserve Bank of San Francisco and the Harvard Seminar in Environmental Economics and Policy. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

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Title: pangea: procedural artificial narrative using generative ai for turn-based video games.

Abstract: This research introduces Procedural Artificial Narrative using Generative AI (PANGeA), a structured approach for leveraging large language models (LLMs), guided by a game designer's high-level criteria, to generate narrative content for turn-based role-playing video games (RPGs). Distinct from prior applications of LLMs used for video game design, PANGeA innovates by not only generating game level data (which includes, but is not limited to, setting, key items, and non-playable characters (NPCs)), but by also fostering dynamic, free-form interactions between the player and the environment that align with the procedural game narrative. The NPCs generated by PANGeA are personality-biased and express traits from the Big 5 Personality Model in their generated responses. PANGeA addresses challenges behind ingesting free-form text input, which can prompt LLM responses beyond the scope of the game narrative. A novel validation system that uses the LLM's intelligence evaluates text input and aligns generated responses with the unfolding narrative. Making these interactions possible, PANGeA is supported by a server that hosts a custom memory system that supplies context for augmenting generated responses thus aligning them with the procedural narrative. For its broad application, the server has a REST interface enabling any game engine to integrate directly with PANGeA, as well as an LLM interface adaptable with local or private LLMs. PANGeA's ability to foster dynamic narrative generation by aligning responses with the procedural narrative is demonstrated through an empirical study and ablation test of two versions of a demo game. These are, a custom, browser-based GPT and a Unity demo. As the results show, PANGeA holds potential to assist game designers in using LLMs to generate narrative-consistent content even when provided varied and unpredictable, free-form text input.

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Build an aquarium? What Halifax people say might bring them downtown more

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New findings from a market research company suggest that parking, safety, and lack of public transit options are causing some Halifax residents to limit time spent in the city’s downtown area. But some interesting incentives, such as building the city’s first aquarium, might see more people make the trip.

In a report titled “Why residents visit Downtown Halifax” published by Narrative Research on May 9 — which received input from 507 Halifax locals, aged 18 years or older, in January — results indicated that half of those living in the municipality visit the downtown area only once or twice a month.

“Most downtown experiences are described as positive, and restaurants, the picturesque waterfront, and cultural events are the biggest draws,” the study revealed.

“When asked what could get them to visit downtown more often, responses focus on increasing parking, having a wider array of cultural events, improving safety, and offering better public transportation to downtown from off the peninsula.”

Some attractions that residents said would inspire them to commute downtown more frequently included the construction of an aquarium, a new performing arts centre, and other “more family-friendly attractions.”

The aquarium proved to be the most popular suggestion. Forty-nine per cent of people said an aquarium would encourage them to visit the city’s downtown more often, which was the highest out of the five options provided by the researchers.

Ideas that generated less interest — but still received a positive response from about one in five participants — involved a new art gallery and soccer stadium.

In addition, 37 per cent of the survey’s participants said they only visit the downtown core “a few times a year” while about one in 10 said they rarely find themselves downtown.

One in three people said that Halifax has become more vibrant since the pandemic.

Regarding security, six in 10 residents said they feel safe when visiting the city’s downtown while 18 per cent do not.

“Slightly fewer (47 per cent) say they feel at home when they visit compared to 29 per cent who do not feel at home in Downtown Halifax,” the report said.

The survey concluded by noting that people living with disabilities are “significantly” less likely to say that downtown Halifax is a safe place to visit.

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