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Research Guides

Ethnographic Case Studies

Jeannette Armstrong; Laura Boyle; Lindsay Herron; Brandon Locke; and Leslie Smith

Description

This research guide discusses ethnographic case study. While there is much debate over what, precisely, delimits a case study , the general consensus seems to be that ethnographic case studies differ from other types of case studies primarily in their focus, methodology, and duration. In essence, ethnographic case studies are case studies “employing ethnographic methods and focused on building arguments about cultural, group, or community formation or examining other sociocultural phenomena” (Schwandt & Gates, 2018, p. 344), typically with a long duration, per the demands of ethnographic work. In essence, ethnographic case studies are case studies “employing ethnographic methods and focused on building arguments about cultural, group, or community formation or examining other sociocultural phenomena” (Schwandt & Gates, 2018, p. 344), typically with a long duration, per the demands of ethnographic work. Indeed, in its very situatedness, ethnography has a “case study character” and is “intimately related” to case studies (Ó Rian, 2009, p. 291); though there is currently a move to extract ethnographic work from overly situated contexts and use extended case methods, “[e]thnographic research has long been synonymous with case studies, typically conceived of as grounded in the local and situated in specific, well-defined and self-contained social contexts” (Ó Rian, 2009, p. 290). Because ethnography, in practice, is often a kind of case study, it’s useful to consider ethnography and case studies each in their own right for a fuller picture of what ethnographic case study entails.

Ethnographic research is one approach under the larger umbrella of qualitative research. Methodologically, it is, “a theoretical, ethical, political, and at times moral orientation to research, which guides the decisions one makes, including choices about research methods” (Harrison, 2014, p. 225), that is at its crux “based upon sharing the time and space of those who one is studying” (Ó Rian, 2009, p. 291)–a situated, nuanced exploration seeking a thick description and drawing on methods such as observation and field notes. According to …an ethnography focuses on an entire culture-sharing group and attempts to develop a complex, complete description of the culture of the group. Creswell and Poth (2018), an ethnography focuses on an entire culture-sharing group and attempts to develop a complex, complete description of the culture of the group. In doing so, ethnographers look for patterns of behavior such as rituals or social behaviors, as well as how their ideas and beliefs are expressed through language, material activities, and actions (Creswell & Poth, 2018). Yin (2016)  suggests that ethnographies seek “to promote embedded research that fuses close-up observation, rigorous theory, and social critique. [Ethnographies foster] work that pays equal attention to the minutiae of experience, the cultural texture of social relations, and to the remote structural forces and power vectors that bear on them” (p. 69).

Case study research, meanwhile, is characterized as an approach “that facilitates exploration of a phenomenon within its context using a variety of data sources” (Baxter & Jack, 2008, p. 544). The aim of case studies is precise description of reconstruction of cases (Flick, 2015). The philosophical background is a qualitative, constructivist paradigm based on the claim that reality is socially constructed and can best be understood by exploring the tacit, i.e., experience-based, knowledge of individuals. There is some debate about how to define a The philosophical background is a qualitative, constructivist paradigm based on the claim that reality is socially constructed and can best be understood by exploring the tacit, i.e., experience-based, knowledge of individuals. “case” (e.g., Ó Rian, 2009), however. As Schwandt and Gates (2018) write, “[A] case is an instance, incident, or unit of something and can be anything–a person, an organization, an event, a decision, an action, a location”; it can be at the micro, meso, or macro level; it can be an empirical unit or a theoretical construct, specific or general; and in fact, “what the research or case object is a case of may not be known until most of the empirical research is completed” (p. 341). The two authors conclude that given the multifarious interpretations of what case study is, “[b]eyond positing that case study methodology has something to do with ‘in-depth’ investigation of a phenomenon . . . , it is a fool’s errand to pursue what is (or should be) truly called ‘case study’” (p. 343, 344).

Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13 (4), 544-559.

Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry & research design: Choosing among five approaches (4th ed.). Los Angeles, CA: SAGE.

Flick, U. (2015). Introducing research methodology . Los Angeles, CA: SAGE.

Rian, S. (2009). Extending the ethnographic case study. In D. Byrne & C. C. Ragin (Eds.), The SAGE handbook of case-based methods (pp. 289–306). Thousand Oaks, CA: SAGE.

Schwandt, T. A., & Gates, E. F. (2018). Case study methodology. In N. K. Dezin & Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (5th ed.; pp. 341-358). Thousand Oaks, CA: SAGE.

Yin, R. K. (2016). Qualitative research from start to finish (2nd ed.). New York, NY: The Guilford Press.

Key Research Books and Articles on Ethnographic Case Study Methodology

Fusch, G. E., & Ness, L. R. (2017). How to conduct a mini-ethnographic case study: A guide for novice researchers. The Qualitative Report , 22 (3), 923-941.  Retrieved from https://nsuworks.nova.edu/tqr/vol22/iss3/16

In this how-to article, the authors present an argument for the use of a blended research design, namely the Ethnographic Case Study, for student researchers. To establish their point of view, the authors reiterate recognized research protocols, such as choosing a design that suits the research question to ensure data saturation. Additionally, they remind their reader that one must also consider the feasibility of the project in terms of time, energy, and financial constraints.

Before outlining the benefits and components of the Ethnographic Case Study approach, the authors provide detailed narratives of ethnographic, mini-ethnographic (sometimes referred to as a focused ethnography ), and case study research designs to orient the reader. Next, we are introduced to the term mini-ethnographic case-study design, which is defined as a blended design that is bound in time and space and uses qualitative ethnographic and case study collection methods. The benefits of such an approach permit simultaneous generation of theory and the study of that theory in practice, as it allows for the exploration of causality.

Ethnographic Case Study research shares many characteristics with its parent approaches.  For example, subjectivity and bias are present and must be addressed. Next, data triangulation is necessary to ensure the collected qualitative data and subsequent findings are valid and reliable. Data collection methods include direct observation, fieldwork, reflective journaling, informal or unstructured interviews, and focus groups. Finally, the authors discuss three limitations to the ethnographic case study. First, this design requires the researcher to be embedded, yet the duration of time may not be for as long when compared to full-scale ethnographic studies.  Second, since there are fewer participants, there should be a larger focus on rich data as opposed to thick data, or said differently, quality is valued over quantity. Third, the researcher must be aware that the end-goal is not transferability, but rather the objective is to gain a greater understanding of the culture of a particular group that is bound by space and time.

Gregory, E. & Ruby, M. (2010) The ‘insider/outsider’ dilemma of ethnography: Working with young children and their families in cross-cultural contexts. Journal of Early Childhood Research, 9 (2), 1-13. https://doi.org/10.1177/1476718X10387899

This article focuses on the dilemma of insider and outsider roles in ethnographic work. It challenges the notion that a researcher can be both an insider and an outsider at the same time. There is no insider/outsider status; it is one or the other–not both.

It is easy to make assumptions about one’s status as an insider. It is not uncommon for a researcher to assume that because one is working amongst his/her “own” people sharing a similar background, culture, or faith that she/he is an insider. Likewise, a researcher may assume that it will be easy to build rapport with a community with which he/she has commonalities; however, it is important to keep in mind that the person may be an insider but the researcher may not have this same status. When the person enters into the protective space of family or community as a researcher, it is similar to being an outsider. Being a researcher makes one different, regardless of the commonalities that are shared. It is not the researcher’s presumed status of “insider” or “outsider” that makes the difference; rather, researcher status is determined by the participants or community that is being studied. It is wise for researchers to understand that they are distinctively one of “them” as opposed to one of “us”. This is not to say that researchers cannot become an “insider” to some degree. But to assume insider status, regardless of the rationale, is wrong. Assuming common beliefs across cultures or insider status can lead to difficulties that could impact the scope or nature of the study.

In conclusion, regardless of the ethnographic design (e.g., realist ethnography, ethnographic case study, critical ethnography), it is important for the researcher to approach the study as an “outsider”. Although the outsider status may change over time, it essential to understand that when one enters a community as a researcher or becomes a researcher within a community, insider status must be earned and awarded according to the participants in the community.

Ó Rian, S. (2009). Extending the ethnographic case study. In D. Byrne & C. C. Ragin (Eds.), The SAGE handbook of case-based methods (pp. 289–306). Thousand Oaks, CA: SAGE.

In this chapter, Ó Rian valorizes the problems and potential hiding within the vagaries of ethnographic “case” boundaries, arguing that “whereas the fluid and multi-faceted aspects of the ethnographic case pose dilemmas for ethnographers, they can also become resources for ethnographers in exploring theoretical and empirical questions” (p. 292). Indeed, he views the idea of firm case boundaries as a weakness, as “definitions of the case will rule in and out certain social processes,” and suggests ethnography’s flexibility can deal with this problem well because it permits researchers to “question the boundaries of the case as the study proceeds,” leading to a “de- and re-construction of the case that . . . places ethnography at the centre of a resurgent contextualist paradigm of social inquiry . . . that is increasingly self-consciously exploring its own theoretical and methodological foundations” (p. 304). Most of the chapter delves into these possibilities for exploration, offering an insightful (if occasionally difficult to follow) perspective on how they have been proceeding.

The chapter offers considerations that might be particularly helpful to researchers undertaking ethnographic case studies who are struggling to connect their cases, so firmly rooted in a particular context and their own personal experiences and observations, to a bigger picture. Ó Rian elucidates the reflexive strategies various ethnographers have adopted as they’ve sought “[t]o achieve a link between context-specific data and meso- or macro-level generalizations,” categorizing these strategies into three “interlocking extensions of case study research” (p. 292): personal extensions (related to “the shaping of the boundaries of the case by the ethnographer’s location within the field and . . . how ethnographers can convey their personalized experiences and tacit learning to readers” [p. 292]), theoretical extensions (which bridge the gap between the situated worlds being explored and “the larger structures and processes that produced and shaped them” [p. 292]), and empirical extensions (“creative efforts to experiment with the empirical boundaries of the ethnographic case” [p. 292] by bringing in, for example, historical context, social networks, etc.). The crux of his argument is that ethnographic researchers have a prime opportunity to push against the boundaries of their context and “extend their cases across space, time and institutional structures and practices” so that the ethnographer is “multiply, if perhaps a bit uncomfortably, situated” (p. 304), and also to include an “emphasis on the ongoing process of theoretical sampling within the process of the ethnographic study, with close attention to be paid to the paths chosen and rejected, and the reasons for these decisions” (p. 304). These kinds of extensions offer an opportunity for theories to “be refined or reconstructed” as the researcher attempts to locate their personal experience within a broader framework, allowing “[t]he case study . . . to challenge and reconstruct the preferred theory” while also connecting the case to a larger body of work, particularly because theory “carries the accumulated knowledge of previous studies” (p. 296).

Ó Rian’s in-depth descriptions of how other researchers have varyingly handled these personal, theoretical, and empirical extensions might be a bit overwhelming to novice researchers but overall can offer a way to “locate their cases within broader social processes and not solely within their own personal trajectories” (p. 294)–while also helping to situate their reflections and extensions within a larger body of literature replete with researchers struggling with similar questions and concerns.

This chapter offers an  in-depth, generally accessible (but occasionally overwhelming) overview of case studies of all sorts and integrates an extensive review of relevant literature. The authors provide an informed perspective on various considerations and debates in the case study field (e.g., varying definitions of what a “case” is construed to be; interpretive vs. critical realist orientations; the relative benefits of and techniques involved in different types of approaches), helping novice researchers locate and better describe their own approach within the context of the field. The information is quite detailed and delves into a wide variety of case study types, suggesting this chapter might best be first skimmed as an initial introduction, followed by more careful readings of relevant sections and perusal of the key texts cited in the chapter. The breadth of this chapter makes it a helpful resource for anyone interested in case-study methodology.

The authors do not specifically explore ethnographic case studies as a separate type of case study. They do, however, briefly touch on this idea, locating ethnography within the interpretive orientation (comprising constructivist approaches offering “phenomenological attention to lived experience” [p. 344]). The authors also cite researchers who distinguish it due to its “[employing] ethnographic methods and focus on building arguments about cultural, group, or community formation or examining other sociocultural phenomena” (p. 344). Ethnographic case study is placed in contrast to case studies that use non-ethnographic methods (e.g., studies “relying perhaps on survey data and document analysis”) or that “are focused on ‘writing culture’” (p. 344).

Two aspects of this chapter are particularly useful for novice researchers. First, it is worth highlighting the authors’ discussion of varying definitions of what a “case” is, as it can provide an interesting reconceptualization of the purpose of the research and the reason for conducting it. The second noteworthy aspect is the authors’ detailed descriptions of the four main case study uses/designs ( descriptive, hypothesis generation or theory development, hypothesis and theory testing , and contributing to normative theory ), which the authors beautifully align with the respective purposes and methods of each type while also offering insight into relevant conversations in the field.

Further Readings

Moss, P. A., & Haertel, E. H. (2016). Engaging methodological pluralism. In D. H. Gitomer & C. A. Bell (Eds.), Handbook of Research on Teaching (pp. 127–247). Washington, DC: American Educational Research Association.

Simons, H. (2014). Case study research: In-depth understanding in context. In P. Leavy (Ed.), The Oxford handbook of qualitative research (pp. 455–470). Oxford, UK: Oxford University Press.

Recent Dissertations Using Ethnographic Case Study Methodology

Cozzolino, M. (2014). Global education, accountability, and 21st century skills: A case of curriculum innovation . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3648007)

This dissertation is self-described as an ethnographic case study of a small, public, suburban high school in Pennsylvania. In this study, the researcher investigates the school’s process of integrating global education into its curriculum by implementing a school-wide initiative (Global Studies Initiative or GSI) as well as a program of study (Global Studies Credential or GSC). Cozzolino asserts that her framework has been shaped by both social constructivism and critical/Freirean pedagogy. From the constructivist view, she views knowledge as constructed through social interaction, and thus she sought to understand the world in which the research participants work, learn, and experience large parts of their lives. It is here that she situates the first three research questions that entail looking at the the GSI and the GSC in terms of their features, rationales, and implementations. The fourth question involves understanding the students’ views and perceptions of the GSC and here the author takes up a critical and Freirean pedagogy to honor and hear the voices of the students themselves.

The study design is therefore an embedded single-case study in that it is bound by the place (Olympus High School) and by its population. Furthermore, it is also a case within a case, as it seeks to understand the students’ perspectives of the global programming. The case study is ethnographically rooted through the multiple ethnographic data sources such as participant-observations and a prolonged engagement at the research site. Cozzolino embedded herself in the research site over a five-year period and became an active and invested member of the school community, thereby establishing a sound rationale for an ethnographic case-study approach.

The author concludes that there were some competing priorities about the overall initiative from stakeholders inside and outside the school district. This resulted in a less than ideal implementation of the program of study across the curriculum. Nonetheless, the students who were enrolled in these courses reported it to be a worthwhile experience. While Cozzolino presents specific recommendations for the improvements at Olympus High, she also offers implications for several other groups. First, she provides advice for implementation to other educational institutions that aim to integrate a global focus into their curriculum. Next, she gives recommendations for local, state, and national policy changes. Finally, she gives suggestions for engaging all parties in fruitful discourse to achieve their ultimate goal of implementing a meaningful and valuable global education curriculum.

Hamman, L. (2018). Reframing the language separation debate: Language, identity, and  ideology in two-way immersion . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 2089463322)

This study explored the issues of surrounding language separation in two-way immersion (TWI) classrooms. The author looked at how classroom language practices and teacher ideologies influenced the student experience and how the students’ understanding of what it means to be bilingual is influenced in a classroom that purports to be equitable in terms of language use.

The study is theoretically grounded in sociocultural, critical, and postcultural theories and adapted Lemke’s ecosocial system to conceptualize TWI classroom. Hamman also drew upon translanguaging theory and dynamic bilingualism to provide a framework for a more modern and nuanced perspective of bilingualism, bilingual learning, and bilingual students.

The author combined a single-case study approach with ethnographic methods to “engage in close analysis of classroom language use and the discursive negotiation of identities and ideologies, while situating these analyses within a rich understanding of the sociolinguistic context of this TWI classroom” (p. 78-79). She employed various ethnographic methods such as taking fieldnotes, conducting participant observations, interviewing, and memoing. The study is “bound” in that it takes place in one 2nd-grade classroom with one teacher and 18 students over the course of one year.

Hamman concludes that student perspectives on language separation should be considered, since this forced separation of language influenced how they thought of their developing bilingualism and identity as bilinguals. Furthermore, the study envisages a linguistic “middle ground” to strict separation that allows for appropriate and meaningful spaces for linguistic negotiation. Finally, this dissertation asserts that the strict separation of languages codifies a monoglossic ideology mindset and limits learners’ possibilities for learning and making connections across languages.

Kim, S. (2015). Korean migrant youth identity work in the transnational social field: A link between identity, transnationalism, and new media literacy . Retrieved from University of Missouri-St. Louis Institutional Repository Library. https://irl.umsl.edu/dissertation/158/

This doctoral dissertation takes an ethnographic case study approach to explore the identity formation of transnational Korean youth. The researcher, herself a Korean immigrant to the U.S. navigating complex identity processes, focuses on these research questions: “1) what are the contexts in which migrant youth negotiate their identities? 2) how do youth understand and negotiate their sense of belonging? 3) how do youth’s [sic] cultural and literacy practices inform and shape their identities? 3i) how do youth make use of transnational new media for their identity work? 3ii) how do literacy practices potentially shape their identities?” (p. 7).

Drawing on Leander and McKim (2013), the author conceptualizes her study as a “connective ethnography” (p. 36) encompassing multiple spaces, both digital and physical, in which “space” comprises a variety of relationships, instead of a more traditional ethnography bounded by physical space. The “case study” aspect, meanwhile, refers to the four specific participants in which she chose to focus. She chose Korean immigrants in St. Louis, in general, due to their mobility between the U.S. and Korea, their high use of digital communication and information technology, and their limited access to the cultural resources of Korea in a Midwestern city. From an initial 32 possible participants purposively selected, the researcher chose four focal participants based on their Korean ethnicity, biliteracy in Korean and English, age (between 11 and 19 years old), residence in the U.S. (for at least 2 years), and their use of digital communication technologies. Data sources included an initial screening survey, an identity map each participant created, informal recorded conversations, recorded interviews in either English or Korean, field notes from the researcher’s interactions with the youth in various settings (home, school, community centers), and “literacy documents” (evidence of literacy practices from participants’ school and home, emails to the researcher, or activities in digital spaces). She used social semiotic multimodal discourse analysis and what she describes as “grounded theory thematic analysis” to analyze the data.

This is a reflective, thoughtful, and interesting dissertation. The author carefully notes the relationship between the data sources and her research questions, specifically addresses steps she took to ensure the validity of the data (e.g., triangulation via multiple data sources and theoretical frameworks, member checks, and feedback from her professors and other researchers), and discloses her own positionalities and biases. Her discussion includes not only a clear thematic exploration of her findings but also offers specific practical suggestions for how her findings can be applied and extended in the classroom.

Internet Resources

Abalos-Gerard Gonzalez , L. (2011). Ethnographic research . Retrieved from https://www.slideshare.net/lanceabalos/ethnographic-research-2?from_action=save

Created by Lance Gerard G. Abalos, teacher at the Department of Education-Philippines, this SlideShare, Ethnographic Research , explains that, regardless of specific design, ethnographic research should be undertaken “without any priori hypothesis to avoid predetermining what is observed or that information is elicited from informants . . .hypotheses evolve out of the fieldwork itself” (slide 4). It is also suggested that researchers refer to individuals from whom information is gathered as ‘informants’ is preferred over the term ‘participants’ (slide 4).

According to Abalos, “It is not the data collection techniques that determine whether the study is ethnographic, but rather the ‘socio-cultural interpretation’ that sets it apart from other forms of qualitative inquiry” (slide 6). A social situation always has three components: a place, actors, and activities (slide 8) and it is the socio-cultural interpretation of the interactions of these three that is the focus of the ethnographic research.

Ethnographic questions should guide what the researcher sees, hears, and collects as data (slide 9). When writing the ethnography, it is essential to ‘bring the culture or group to life’ through the words and descriptions used to describe the place, actors, and activities.

Abalos describes three types of ethnographic designs:

• Realist Ethnographies : an objective account of the situation, written dispassionately from third-person point of view, reporting objectively on information learned from informants, containing closely edited quotations (slide 11-12).
• Ethnographic Case Studies : researchers focus on a program, event, or activity involving individuals rather than a group, looking for shared patterns that develop as a group as a result of the program, event, or activity (slide 13).
• Critical Ethnographies: incorporating a ‘critical’ approach that includes an advocacy perspective, researchers are interested in advocating against inequality and domination (slide 14).

As ethnographic data is analyzed, in any design (e.g., realist, case study, critical), there is a shift away from reporting the facts to making an interpretation of people and activities, determining how things work, and identifying the essential features in themes of the cultural setting (slide 22). “The ethnographer must present the description, themes, and interpretation within the context or setting of the culture-sharing group (slide 23).

Brehm, W. (2016, July 21). FreshEd #13 – Jane Kenway . Retrieved from http://www.freshedpodcast.com/tag/ethnography/ (EDXSymposium: New Frontiers in Comparative Education).

Jane Kenway is with the Australian Research Council and is an emeritus professor at Monash University in Melbourne, Australia. In this podcast, she explains “traditional’ forms of ethnography and multi-sited global ethnography, which are her area of specialization. She considers “traditional” ethnography to have three components: space, time, and mobility.

Insider/outsider stance is explained within the context of spatiality, community, and culture of space specific to ‘traditional” ethnography. Researchers are outsiders who are attempting to enter a space and become insiders, then leave the space once the research is completed. Research is conducted over an extended period of time in one place/space. As a result, researchers will get to know in an extremely intimate manner the ways of life of the community or group. “Work is supposed to be a temporality of slowness. In other words, you don’t rush around like a mad thing in a field, you just quietly and slowly immerse yourself in the field over this extended period of time and get to understand it, get to appreciate it bit by bit.” (minute 7:56).

“Traditional” ethnographers are not necessarily interested in mobility over time or exploring who enters and exits the site. Most ethnographers are only interested in the movement that occurs in the space that is being studied during the time that they are in the field. It is about looking at the roots of the space, not necessarily about looking at the movements into and out of the space.

Multi-sited global ethnography tries to look at the way bounded sites can be studied as unbounded and on the move, as opposed to staying still. It considers how certain things (e.g., things, ideas, people) are  followed as they move. The researcher moves between sites, studying change that is encountered in different sites. From this perspective, the interested lies in the connections between sites. Multiple sites with commonalities can also be studied at the onset, without the need to physically follow.

Paulus, T. M., Lester, J. N., & Dempster, P. G. (2014). Digital Tools for Qualitative Research. Los Angeles, CA: SAGE.

While this text is not solely about ethnographic case studies, it is rich with countless ideas for utilizing digital tools to aid in the multiple facets of qualitative research. In Chapter 5 of their text, entitled Generating Data, the authors dedicate a section to exploring Internet archives and multimedia data. They state that, “in addition to online communities, the Internet is rich with multimedia data such as professionally curated archives, ameteur-created YouTube and Vimeo videos and photo-sharing sites” (p. 81). They provide three specific examples, each explained below: The Internet Archive, CADENSA, and Britain’s BBC Archives.

The Internet Archive ( https://archive.org ) is a non-profit library of millions of free books, movies, software, music, websites, and more. The site also contains a variety of cultural artifacts that are easily available and downloadable. CADENSA ( http://cadensa.bl.uk ) is an online archive of the British Library Sound and Moving Image Catalogue. And finally, the BBC Archives ( http://www.bbc.co.uk/archive/ ) is a particularly useful site for researchers interested in reviewing documentary film and political speeches.

Wang, T. (2016, September). Tricia Wang: The human insights missing from big data. [Video file]. Retrieved from  https://www.ted.com/talks/tricia_wang_the_human_insights_missing_from_big_data

In this TED Talk, Tricia Wang discusses her ethnographic work with technology and advocates for the need to save a place for thick data as opposed to relying only on big data. She argues that while companies invest millions of dollars in generating big data because they assume it will efficiently provide all the answers, it routinely does not provide a good return on investment. Instead, companies are left without answers to the questions about consumer preferences and behaviors, which leaves them unprepared for market changes.

In turn, Wang coins the term thick data, which is described as “precious data from humans, like stories, emotions, and interactions that cannot be quantified” (Minute 11:50). Wang suggests that this thick data may only come from a small group of individuals, but it is an essential component that can provide insights that are different and valuable. As an example, while working for Nokia, her ethnographic experiences in China provided her with new understandings on the future demand for smartphones. However, her employer did not take her findings seriously, and as a result, they lost their foothold in the technology market. She posits that a blended approach to collecting and analyzing data (i.e. combining or integrating thick data analysis with big data analysis) allows for a better grasp on the whole picture and making informed decisions.

Her conclusions for a blended approach to data collection also have implications for blending ethnographic and case-study approaches. While Wang took more of an ethnographic approach to her research, one could envision what her work might have looked like if she had used an Ethnographic Case Study approach. Wang could have clearly defined the time and space boundaries of her various ethnographic experiences (e.g. as a street vendor, living in the slums, hanging out in internet cafés). This would have allowed her to infer causality through the generation of thick data with a small sample size for each location and bound by each group.

Ethnographic Case Studies Copyright © 2019 by Jeannette Armstrong; Laura Boyle; Lindsay Herron; Brandon Locke; and Leslie Smith is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Methodology

• What Is Ethnography? | Definition, Guide & Examples

What Is Ethnography? | Definition, Guide & Examples

Published on March 13, 2020 by Jack Caulfield . Revised on June 22, 2023.

Ethnography is a type of qualitative research that involves immersing yourself in a particular community or organization to observe their behavior and interactions up close. The word “ethnography” also refers to the written report of the research that the ethnographer produces afterwards.

Ethnography is a flexible research method that allows you to gain a deep understanding of a group’s shared culture, conventions, and social dynamics. However, it also involves some practical and ethical challenges.

Table of contents

What is ethnography used for, different approaches to ethnographic research, gaining access to a community, working with informants, observing the group and taking field notes, writing up an ethnography, other interesting articles.

Ethnographic research originated in the field of anthropology, and it often involved an anthropologist living with an isolated tribal community for an extended period of time in order to understand their culture.

This type of research could sometimes last for years. For example, Colin M. Turnbull lived with the Mbuti people for three years in order to write the classic ethnography The Forest People .

Today, ethnography is a common approach in various social science fields, not just anthropology. It is used not only to study distant or unfamiliar cultures, but also to study specific communities within the researcher’s own society.

For example, ethnographic research (sometimes called participant observation ) has been used to investigate  football fans , call center workers , and police officers .

Advantages of ethnography

The main advantage of ethnography is that it gives the researcher direct access to the culture and practices of a group. It is a useful approach for learning first-hand about the behavior and interactions of people within a particular context.

By becoming immersed in a social environment, you may have access to more authentic information and spontaneously observe dynamics that you could not have found out about simply by asking.

Ethnography is also an open and flexible method. Rather than aiming to verify a general theory or test a hypothesis , it aims to offer a rich narrative account of a specific culture, allowing you to explore many different aspects of the group and setting.

Disadvantages of ethnography

Ethnography is a time-consuming method. In order to embed yourself in the setting and gather enough observations to build up a representative picture, you can expect to spend at least a few weeks, but more likely several months. This long-term immersion can be challenging, and requires careful planning.

Ethnographic research can run the risk of observer bias . Writing an ethnography involves subjective interpretation, and it can be difficult to maintain the necessary distance to analyze a group that you are embedded in.

There are often also ethical considerations to take into account: for example, about how your role is disclosed to members of the group, or about observing and reporting sensitive information.

Should you use ethnography in your research?

If you’re a student who wants to use ethnographic research in your thesis or dissertation , it’s worth asking yourself whether it’s the right approach:

• Could the information you need be collected in another way (e.g. a survey , interviews)?
• How difficult will it be to gain access to the community you want to study?
• How exactly will you conduct your research, and over what timespan?
• What ethical issues might arise?

If you do decide to do ethnography, it’s generally best to choose a relatively small and easily accessible group, to ensure that the research is feasible within a limited timeframe.

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There are a few key distinctions in ethnography which help to inform the researcher’s approach: open vs. closed settings, overt vs. covert ethnography, and active vs. passive observation. Each approach has its own advantages and disadvantages.

Open vs. closed settings

The setting of your ethnography—the environment in which you will observe your chosen community in action—may be open or closed.

An open or public setting is one with no formal barriers to entry. For example, you might consider a community of people living in a certain neighborhood, or the fans of a particular baseball team.

• Gaining initial access to open groups is not too difficult…
• …but it may be harder to become immersed in a less clearly defined group.

A closed or private setting is harder to access. This may be for example a business, a school, or a cult.

• A closed group’s boundaries are clearly defined and the ethnographer can become fully immersed in the setting…
• …but gaining access is tougher; the ethnographer may have to negotiate their way in or acquire some role in the organization.

Overt vs. covert ethnography

Most ethnography is overt . In an overt approach, the ethnographer openly states their intentions and acknowledges their role as a researcher to the members of the group being studied.

• Overt ethnography is typically preferred for ethical reasons, as participants can provide informed consent…
• …but people may behave differently with the awareness that they are being studied.

Sometimes ethnography can be covert . This means that the researcher does not tell participants about their research, and comes up with some other pretense for being there.

• Covert ethnography allows access to environments where the group would not welcome a researcher…
• …but hiding the researcher’s role can be considered deceptive and thus unethical.

Active vs. passive observation

Different levels of immersion in the community may be appropriate in different contexts. The ethnographer may be a more active or passive participant depending on the demands of their research and the nature of the setting.

An active role involves trying to fully integrate, carrying out tasks and participating in activities like any other member of the community.

• Active participation may encourage the group to feel more comfortable with the ethnographer’s presence…
• …but runs the risk of disrupting the regular functioning of the community.

A passive role is one in which the ethnographer stands back from the activities of others, behaving as a more distant observer and not involving themselves in the community’s activities.

• Passive observation allows more space for careful observation and note-taking…
• …but group members may behave unnaturally due to feeling they are being observed by an outsider.

While ethnographers usually have a preference, they also have to be flexible about their level of participation. For example, access to the community might depend upon engaging in certain activities, or there might be certain practices in which outsiders cannot participate.

An important consideration for ethnographers is the question of access. The difficulty of gaining access to the setting of a particular ethnography varies greatly:

• To gain access to the fans of a particular sports team, you might start by simply attending the team’s games and speaking with the fans.
• To access the employees of a particular business, you might contact the management and ask for permission to perform a study there.
• Alternatively, you might perform a covert ethnography of a community or organization you are already personally involved in or employed by.

Flexibility is important here too: where it’s impossible to access the desired setting, the ethnographer must consider alternatives that could provide comparable information.

For example, if you had the idea of observing the staff within a particular finance company but could not get permission, you might look into other companies of the same kind as alternatives. Ethnography is a sensitive research method, and it may take multiple attempts to find a feasible approach.

All ethnographies involve the use of informants . These are people involved in the group in question who function as the researcher’s primary points of contact, facilitating access and assisting their understanding of the group.

This might be someone in a high position at an organization allowing you access to their employees, or a member of a community sponsoring your entry into that community and giving advice on how to fit in.

However,  i f you come to rely too much on a single informant, you may be influenced by their perspective on the community, which might be unrepresentative of the group as a whole.

In addition, an informant may not provide the kind of spontaneous information which is most useful to ethnographers, instead trying to show what they believe you want to see. For this reason, it’s good to have a variety of contacts within the group.

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The core of ethnography is observation of the group from the inside. Field notes are taken to record these observations while immersed in the setting; they form the basis of the final written ethnography. They are usually written by hand, but other solutions such as voice recordings can be useful alternatives.

Field notes record any and all important data: phenomena observed, conversations had, preliminary analysis. For example, if you’re researching how service staff interact with customers, you should write down anything you notice about these interactions—body language, phrases used repeatedly, differences and similarities between staff, customer reactions.

Don’t be afraid to also note down things you notice that fall outside the pre-formulated scope of your research; anything may prove relevant, and it’s better to have extra notes you might discard later than to end up with missing data.

Field notes should be as detailed and clear as possible. It’s important to take time to go over your notes, expand on them with further detail, and keep them organized (including information such as dates and locations).

After observations are concluded, there’s still the task of writing them up into an ethnography. This entails going through the field notes and formulating a convincing account of the behaviors and dynamics observed.

The structure of an ethnography

An ethnography can take many different forms: It may be an article, a thesis, or an entire book, for example.

Ethnographies often do not follow the standard structure of a scientific paper, though like most academic texts, they should have an introduction and conclusion. For example, this paper begins by describing the historical background of the research, then focuses on various themes in turn before concluding.

An ethnography may still use a more traditional structure, however, especially when used in combination with other research methods. For example, this paper follows the standard structure for empirical research: introduction, methods, results, discussion, and conclusion.

The content of an ethnography

The goal of a written ethnography is to provide a rich, authoritative account of the social setting in which you were embedded—to convince the reader that your observations and interpretations are representative of reality.

Ethnography tends to take a less impersonal approach than other research methods. Due to the embedded nature of the work, an ethnography often necessarily involves discussion of your personal experiences and feelings during the research.

Ethnography is not limited to making observations; it also attempts to explain the phenomena observed in a structured, narrative way. For this, you may draw on theory, but also on your direct experience and intuitions, which may well contradict the assumptions that you brought into the research.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Atherton H, Brant H, Ziebland S, et al. The potential of alternatives to face-to-face consultation in general practice, and the impact on different patient groups: a mixed-methods case study. Southampton (UK): NIHR Journals Library; 2018 Jun. (Health Services and Delivery Research, No. 6.20.)

The potential of alternatives to face-to-face consultation in general practice, and the impact on different patient groups: a mixed-methods case study.

Chapter 4 focused ethnographic case studies, methodology and description of sites.

• Rationale for the methodological approach

Focused ethnography approach

This study used team-focused ethnographic methods. In a focused ethnography, rather than embedding a single researcher in a social setting for a lengthy period, more targeted data collection is used to explore the study topics. Using existing information from the literature and from what is known in clinical practice helps to determine the research question and, subsequently, to generate findings that are relevant and useful. 139

This project is a team-based ethnography as it involved three ethnographers working across a total of eight general practice sites in three regions (Scotland, Oxford and Bristol). Team-based ethnographies have become increasingly popular across disciplines. 140 – 142 This trend has been linked to funding bodies that encourage multidisciplinary team-based research, because of the wider range of expertise that will be brought to a project. 140 , 142 The use of a team-focused ethnography for this study has been explored further by Bikker et al. 143

Although ethnographic methods have been used in primary care for several notable studies, 144 – 146 they have usually required an intensive period of immersion (often by a sole researcher) in the study setting. The focused ethnographic approach lends itself well to health services research, because it is an efficient way to obtain an insightful understanding of concepts and processes within the fast-moving context of health-care policy development. This method was particularly suited to this study’s research questions as it allowed data to be collected on a predefined topic guided by the conceptual review work, while emphasising the importance of the context and the cultural landscape of the practices within a limited time frame.

• Focused ethnographic team

Composition

The case study team consisted of three researchers with experience of ethnographic research who were employed to conduct the focused ethnographic fieldwork. Although having three researchers collecting data was time efficient, to minimise the costs, two of the researchers were employed solely for the duration of the data collection (12 months). The third researcher was employed for the duration of the project (27 months) and also took on the role of project manager. The ethnographic researchers were based in two universities in England and one in Scotland. They had different backgrounds, which included medical and social anthropology, nursing and mixed-methods research methodologies. The three ethnographers were managed by two co-applicants: Helen Atherton on a day-to-day basis with input from Sue Ziebland (see Table 1 , Chapter 1 ). This subteam of five researchers made up the ‘focused ethnographic team’. The wider study team was also involved in providing a ‘check’ on the data the ethnographic team were collecting.

Communication

Steps were taken to ensure that the focused ethnographic team worked cohesively on the data collection and analysis. Over the period of the fieldwork and analysis, this involved:

• the focused ethnographic team setting out a strategy for teamworking during their initial meeting
• the three ethnographers having a weekly telephone meeting
• the three ethnographers and the day-to-day focused ethnographic team lead (HA) having a fortnightly telephone meeting
• the three ethnographers contacting the day-to-day lead (HA) via e-mail or telephone, when necessary
• the day-to-day lead meeting regularly with the senior focused ethnographic team lead (SZ)
• the entire focused ethnographic team attending three data collection and analysis workshops over the course of the project: two in Oxford and one in Edinburgh
• the ethnographers attending the project meetings (both face-to-face and telephone meetings) during the 12 months of fieldwork, allowing for updates to be made to the wider study team, and for the ethnographers to hear about the progress of all elements of the project.
• Patient and public involvement

We recruited three PPI representatives who reviewed the information sheet and consent forms, leading us to make to a number of improvements. These included:

• rewording the titles
• removing all abbreviations
• an expansion of the information provided about observing consultations between the doctor and the patient/carer
• simplification of the information provided to patients and carers invited to participate in an interview.

The three PPI representatives were recruited through a request for involvement circulated via the newsletter of ‘People in Health West of England’. Support was provided by the PPI lead, Andy Gibson. Andy Gibson explained the aims of the project and the purpose of involvement activities to potential participants. Feedback was given to participants on the amendments made to the ethics application as a result of their contribution.

• Case study recruitment

Selection of sites

We recruited eight practices as planned. Two were in Scotland, three were in Oxfordshire and three were in Bristol. The scoping survey (see Chapter 3 ) was used to identify potential practices. Based on our survey data, we constructed a matrix of practices detailing various practice characteristics. Characteristics included experience of implementing different types of alternatives to face-to-face consultations; the size of population the practices serve; and location, in terms of whether it is urban or rural and deprived or affluent (based on deprivation scores). We then selected practices to approach, ensuring that we covered a range of demographic characteristics and applications of alternatives to the face-to-face consultation, for example ‘currently using’, ‘tried and rejected’ or ‘substantially modified their plans to use’ alternatives.

We sent invitation letters to practices, followed by telephone calls to the practice manager and/or GP to ensure that the invitation had been received. When practices were interested, a researcher visited to provide more information and discuss the implications of participation. Practices that declined to participate stated excessive workload and/or staff shortages as the reason.

• Data collection and management

The remit of the focused ethnography was guided by the findings from the conceptual review, which helped to shape the case study guide and the staff and patient topic guides (see Chapter 2 for a fuller explanation and see Appendix 4 for the case study guide).

One ethnographer was based at each practice. Data were gathered through non-participant observation, informal conversations and semistructured interviews with practice administration staff, GPs and patients. Practice documents and protocols on alternatives to the face-to-face consultations were reviewed. Anonymised data about consultations were collected and these contributed to a quantitative analysis (see Chapter 6 ).

Consent and observational work

The ethnographers observed practice staff in all areas of the practice, such as clinical areas, reception desks and administrative offices. Observations included consultations, both face to face and alternatives to face-to-face consultations.

In the first instance, the practice manager agreed to the practice participating in the research and informed all staff that the ethnographers would be situated in the practice for a number of weeks.

On commencing the research within the practice, informed consent for observation was sought by the ethnographer from all members of the practice. This involved providing all staff members with an information sheet about the study and providing a consent form. The information sheet outlined that the ethnographers may observe them at work, engage in informal conversation and take notes. They were given up to 1 week to read the sheet and complete the consent form before a further enquiry was made. Some staff members were not based in the practice and declined to consent, on the basis that we would not be observing them. A small number of staff members declined to consent. We ensured not to engage them in informal conversation or directly observe their work. We did not take notes on any work they were engaged in. In addition, those consenting were informed that, at any point during the research period, they could decline observation or conversation. Staff members engaging in interviews were given an additional information sheet and completed an additional consent form for participation in the interview.

Observations of consultations were at the discretion of the GP. Patients were invited to consent to their face-to-face consultation being observed, given an information sheet and asked to consent to the observation. For observation of telephone and e-mail consultations, the ethnographers were not party to patient-identifiable data and so consent was not required; however, the clinician was able to decline the observation if they felt that it was not appropriate. If the ethnographer observed the GP within their consulting room but outside a consultation, they took notes but did not make notes relating to a patient or their condition, being focused only on how the GP worked (e.g. when they responded to e-mail consultations or when they scheduled their telephone consultations). Data were collected using field notes in all cases, and these did not include patient-identifiable data.

Summary profile

In each practice, the ethnographers completed a summary profile for that practice. This was designed to capture the detail obtained by the ethnographers in the field in their own words. It included, among other details, the types of alternative consultations that are (or were) provided, how these are/were provided (e.g. timing, volume, staffing) and any parameters for the types of patients who are/were allowed or encouraged to use alternatives to face-to-face consultations, including variations between practitioners. Over the course of the data collection, the ethnographers added any new observations about the practice to the summary profile template for each of the eight sites. This allowed individual field notes to be transformed into a common format. As a result, comparing the observations between practices became more straightforward, even though the personal styles of completing field notes differed between the ethnographers. At the start of the data collection, the discussion about the research topics among the focused ethnographic team was more general, reflecting the exploratory nature of the study and the process of familiarisation with the field. However, as the data collection progressed, the format of the summary profile template evolved and became more focused on alternatives to the face-to-face consultation.

The ethnographers recorded their own field notes during observations. In more formal settings, such as practice meetings, minimal notes were made by ethnographers in real time, followed by more detailed field notes retrospectively.

Document collection

In each of the case study practices, we sought to review notes and minutes from practice meetings over the preceding 6-month period. Some practices were reluctant to give our researchers full access to these notes and minutes, and so the practice managers in each practice reviewed the minutes, identifying and extracting any relevant information.

In each practice, researchers requested that they be invited to observe practice meetings during which alternatives to the face-to-face consultation would be discussed. In the end, this was the case for only one meeting in one practice, where the researcher attended the meeting and kept notes.

Semistructured interviews

Each interview participant provided informed consent. Interviews were digitally recorded, using an encrypted recorder. The files were transcribed verbatim by a professional transcription service.

Staff interviews were usually conducted in the general practice (one GP was interviewed at home). Additional interviews relating to video consultation at non-case study sites were conducted over the telephone. Information was collected on sex, age, ethnicity, role in the practice, length of time in the role, length of time since qualifying and the type of alternative to the face-to-face consultation used.

Patient and carer interviews were conducted at a location of their choosing, usually their home (or the general practice). Information was collected on sex, age, ethnicity, whether or not they were a carer, whether or not they had a long-term condition or disability, level of education and occupation.

The initial design of the topic guides was based on the findings of the conceptual review and templates used by focused ethnographic team members in previous studies. The topic guides were then revised iteratively among the ethnographic team once the ethnographers were working in the field, and a final topic guide was agreed on for both staff and patient interviews. The staff topic guide differed slightly according to the staff member being interviewed; for example, GPs were asked specifically about how the alternative to the face-to-face consultation affected their relationship with patients (see Appendix 5 for the topic guide).

• Interview participant recruitment

Case study site staff

Once they had been conducting observations in the practice for a few weeks, the ethnographers identified relevant staff members to participate in the interviews. The ethnographers had made contact with potential interviewees during non-participant observation, and provided them with the information sheet relating to the interview. If they were willing to participate, an interview was arranged at a time that was convenient for the staff member.

In each practice, administrative staff (including receptionists), GPs and nurses were recruited to be interviewed. When relevant, other members of the practice team were also interviewed, for example, a rural health worker in one practice, a patient manager and an IT manager in another. The team of ethnographers remained in close contact throughout the process, to ensure that the range of staff members being interviewed was suitably varied in regard to factors such as role in the practice, knowledge or involvement in alternatives to the face-to-face consultation.

At the protocol stage, we intended to interview allied health professionals working in general practice, such as phlebotomists and community-based pharmacists. However, it became apparent during observations that, where allied health professionals were working in the practices, they had little to no involvement in the introduction or use of alternatives to face-to-face consultations. Recognising the importance of the wider study team members within general practice, each ethnographer engaged in informal conversations with these staff members to ensure that their perspectives were covered. These conversations were recorded in the researcher’s field notes and subsequently referred to in the structured summary profile.

Users of video consultation

As described in Chapter 3 , we recruited an additional four participants from outside the case study sites. These were general practice staff members who were using, were about to use or employed a system that used video consultations.

• We approached practices that had been funded by the GP Access Fund 14 to employ video consultations.
• We approached practices that had publicised their use of video consultation in news articles or reports.

Has your practice offered patients video/skype consults? We are looking for GPs to do a 30m phone interview for AltCon study.

• We used personal contacts (HA and CS) obtained via related research studies.

Two participants were recruited via Twitter, and a further two were recruited via personal contacts (HA). We were unable to contact all of the GP Access Fund 14 practices and, in the case of those we did contact, we could not identify individuals who were using video consultation. We received no reply from the practices that had publicised their use of video consultation via news articles or reports.

Patients/carers

The aim was to interview patients with different characteristics in relation to age, sex, ethnicity, disability, frequency of attendance and whether or not they had long-term health conditions. All patients invited to participate in interviews had experience of using an alternative to the face-to-face consultation within the practice.

Initially, patients were identified opportunistically, based on those who had engaged in contact with the practice via an alternative to the face-to-face consultation. In subsequent interviews, patients were purposively sampled to ensure that participants with the range of characteristics listed above were included. Practice staff and GPs helped to identify patients and carers and provided potential participants with a study information pack, either via post or in person when attending the practice. This pack included information about the study, an invitation to take part and a reply slip, which they could return via prepaid post. The researcher then called to arrange a convenient time for the interview.

Hard-to-reach and disadvantaged groups

In using a purposive sampling technique, we specifically included people who were identified in the protocol as being in hard-to-reach groups with regard to accessing general practice. Examples included parents/carers of people with complex needs, young men, the vulnerably housed and minority ethnic groups.

The other groups of interest were those that might be disadvantaged by limited provision of alternatives to the face-to-face consultation. These groups were described in the protocol, and further relevant groups were identified in the conceptual review (see Chapter 2 ). These included patients with mental health conditions, patients living in rural areas, patients with restricted mobility, patients with hearing loss, patients at a great distance from the practice (e.g. working away) and patients with low health literacy and/or low computer literacy.

The aim was to look at the range of problems and issues for these groups, rather than making statements about specific population subgroups. To make it easier for people in these groups to participate, there was flexibility about timings and locations for interviews, with telephone interviews offered when appropriate. Participants in hard-to-reach and disadvantaged groups were identified by the practices so that they could be invited to interview.

• Quantitative data

Quantitative data on the numbers and types of consultations recorded were collected from the six English practices, as they all used the same electronic medical record system (the Scottish practices used another system). The ethnographer in each of the practices enquired as to how consultation types were recorded and then conducted an audit of the reliability of this record-keeping by observing practitioners at work and asking a GP to review the last 20 consultations in which each of the alternatives to face-to-face consultations was used in the practice and note whether or not the type had been accurately recorded. Any use of protocols was also noted. Further details of the method and analysis of the quantitative data can be found in Chapter 6 .

• Data analysis

The coding frame for analysis of the ethnographic data was devised by the focused ethnographic team at a face-to-face meeting early in the data collection period. Each ethnographic team member had read a series of field notes and transcripts, and contributed to devising a coding structure for the staff data and another different coding structure for the patient data, which comprised interview data only. The three ethnographers read and coded interview transcripts and field notes [using the comment facility in Microsoft Word 2013 (Microsoft Corporation, Redmond, WA, USA)]. Once the coding frame was in place, the field notes were coded and each ethnographer condensed their findings into a summary profile. The day-to-day lead (HA) read the coding of the field notes into the summary profile and read every transcript, checking the coding to ensure reliability and comparability, and adding or making adjustments where relevant. The transcripts and summary profiles were then entered into NVivo software, which allowed thematic reports to be generated.

A series of NVivo reports were generated to gather related sections of the data together. At this point, two of the ethnographers had completed their contracts. The day-to-day lead of the focused ethnographic team (HA), senior team lead (SZ) and remaining ethnographer (HB) read all of the reports. They applied the OSOP method 90 to identify the line of argument in each thematic report and identify outliers or negative cases. The data from the staff and patient interviews and the field notes were integrated, and a condensed summary was produced for each thematic code.

At this point, the wider study team became involved and were paired with the remaining members of the ethnographic team to discuss the interpretation of the data (HA and BM, HB and CS, SZ and JC). The core messages were presented at a wider team meeting and the analysis refined through discussion among all the team members.

In addition, we held a stakeholder workshop to present and discuss the initial findings and their application. Attendees included academics, policy-makers and health-care professionals. The responses from the workshop delegates were considered during the final stages of the data synthesis. See Chapter 7 for further information on the stakeholder workshop.

• Ethics and research governance permissions

Ethics approval was obtained from NHS Yorkshire and the Humber-South Yorkshire Research and Ethics Committee on 23 March 2015 (15/YH/0135). NHS research and development approvals were obtained for the health boards (Scotland) and the CCGs (England) for the participating practices. Approval, via a substantial amendment, was obtained to recruit and interview four general practice staff from practices outside the case study sites. Consent was obtained from primary care staff and patients participating in the focused ethnography. Participation was voluntary and the optional nature of the study was explained in the information sheet.

• Description of the case study sites

We approached 20 practices and invited them to participate. Of these, one practice had closed and we received no response from two others. Nine practices declined to participate, stating excessive workload and/or staff shortages as the reason. Eight case study sites were recruited in total, and details of these practices and the period of time spent in each practice can be seen in Table 5 . A more detailed summary of each practice can be found in Appendix 6 , which includes contextual information about the practices collected by the ethnographers during the course of their observations.

Description of case study sites

• Description of interview participants

Staff interview participants

We interviewed 45 members of staff from the case study sites, and a further four from other practices. In the case study sites, we interviewed 19 GPs, eight practice managers, two deputy practice managers, one practice co-ordinator, two senior practice nurses, three practice nurses and one nurse practitioner, one rural health worker, four senior receptionists, one receptionist, one patient service manager, one practice administrator and an IT manager. The four participants from practices outside the case study sites were three GPs and one practice manager. Various different types of alternatives to the face-to-face consultation were used by staff in the case study sites. All GPs and nurses were using telephone consultations.

The participants from outside the case study sites were interviewed about video consultation; one had used video consultation with patients, two had limited experience of using video consultation with patients and one practice manager was in the process of setting up a video-consultation service.

Of the 48 staff interviewed, 33 were female. The age of participants ranged from 31 to 68 years. The majority of participants were white British. For clinical staff, the length of time since qualifying varied from 7 years to 40 years. Staff had been in their current role for varying amounts of time, from 10 months to 31 years. Of the GPs, 16 were partners and six were salaried.

Full details about staff interview participant characteristics can be found in Appendix 7 .

Patient and carer interview participants

We interviewed 39 patient and carer participants. All participants were using or had used an alternative to the face-to-face consultation with a health-care professional at their practice. We collected information on their ethnicity, age, sex, current health conditions and whether or not they were carers, alongside information about their level of education and current employment status. Full details about patient interview participant characteristics can be found in Appendix 8 .

The sample included a wide range of participants who may find it difficult to engage with general practice settings for varying reasons. These included a parent looking after a disabled child, an asylum seeker who was vulnerably housed, two men aged < 30 years (who typically do not engage in health care) and three participants in minority ethnic groups with English as a second language.

The sample also included patients who may find themselves disadvantaged by the current limited provision of alternatives to the face-to-face consultation, namely six patients with mental health conditions, four patients living in a very rural area, nine patients with restricted mobility and two patients with hearing loss.

Patient and public involvement and young people

The age range of our patient/carer participant sample was wide, but it did not include any participants younger than 24 years (range 24–91 years). Young persons below the age of 18 years were not eligible for inclusion in the study. Being mindful of the potential importance of alternatives to the face-to-face consultation in young people, we sought to obtain the views of young adults to supplement the study. We did this by organising a PPI event for young people. We were able to do this via ‘Bristol Young Health Watch’, a group of young people aged between 16 and 19 years who work alongside the Bristol CCG. The study PPI lead (AG) met with the group during one of their regular existing meetings. Group members were asked to comment on a number of issues related to alternatives to face-to-face consultations in primary care. These comments were recorded on flip charts during the meeting.

Although the people attending the workshop felt comfortable with potentially using new technology to access GP services, they reported similar concerns to other patient groups about issues of confidentiality, being able to exert choice over when to use alternatives and seeing these as a supplement rather than an alternative to face-to-face consultations. The content of the discussion was used to provide context for the findings obtained via interviews and observation.

• Cite this Page Atherton H, Brant H, Ziebland S, et al. The potential of alternatives to face-to-face consultation in general practice, and the impact on different patient groups: a mixed-methods case study. Southampton (UK): NIHR Journals Library; 2018 Jun. (Health Services and Delivery Research, No. 6.20.) Chapter 4, Focused ethnographic case studies, methodology and description of sites.
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Qualitative research methodologies: ethnography

• Related content
• Peer review
• Scott Reeves , associate professor 1 ,
• Ayelet Kuper , assistant professor 2 ,
• Brian David Hodges , associate professor and vice chair (education) 3
• 1 Department of Psychiatry, Li Ka Shing Knowledge Institute, Centre for Faculty Development, and Wilson Centre for Research in Education, University of Toronto, 200 Elizabeth Street, Eaton South 1-565, Toronto, ON, Canada M5G 2C4
• 2 Department of Medicine, Sunnybrook Health Sciences Centre, and Wilson Centre for Research in Education, University of Toronto, Toronto, ON, Canada M4N 3M5
• 3 Department of Psychiatry, Wilson Centre for Research in Education, University of Toronto, Toronto, ON, Canada M5G 2C4
• Correspondence to: S Reeves scott.reeves{at}utoronto.ca

The previous articles (there were 2 before this 1) in this series discussed several methodological approaches commonly used by qualitative researchers in the health professions. This article focuses on another important qualitative methodology: ethnography. It provides background for those who will encounter this methodology in their reading rather than instructions for carrying out such research.

What is ethnography?

Ethnography is the study of social interactions, behaviours, and perceptions that occur within groups, teams, organisations, and communities. Its roots can be traced back to anthropological studies of small, rural (and often remote) societies that were undertaken in the early 1900s, when researchers such as Bronislaw Malinowski and Alfred Radcliffe-Brown participated in these societies over long periods and documented their social arrangements and belief systems. This approach was later adopted by members of the Chicago School of Sociology (for example, Everett Hughes, Robert Park, Louis Wirth) and applied to a variety of urban settings in their studies of social life.

The central aim of ethnography is to provide rich, holistic insights into people’s views and actions, as well as the nature (that is, sights, sounds) of the location they inhabit, through the collection of detailed observations and interviews. As Hammersley states, “The task [of ethnographers] is to document the culture, the perspectives and practices, of the people in these settings. The aim is to ‘get inside’ the way each group of people sees the world.” 1 Box 1 outlines the key features of ethnographic research.

Box 1 Key features of ethnographic research 2

A strong emphasis on exploring the nature of a particular social phenomenon, rather than setting out to test hypotheses about it

A tendency to work primarily with “unstructured data” —that is, data that have not been coded at the point of data collection as a closed set of analytical categories

Investigation of a small number of cases (perhaps even just …

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Case Study vs. Ethnography

What's the difference.

Case study and ethnography are both research methods used in social sciences to gain a deeper understanding of a particular phenomenon or group of people. However, they differ in their approach and focus. A case study typically involves an in-depth examination of a single individual, group, or event, aiming to provide a detailed analysis of a specific situation. On the other hand, ethnography involves immersing oneself in a particular culture or community over an extended period, observing and interacting with its members to understand their beliefs, behaviors, and social dynamics. While case studies provide detailed insights into specific cases, ethnography offers a broader understanding of the cultural context and social interactions within a community.

Further Detail

Introduction.

Case study and ethnography are two research methods commonly used in social sciences and other fields to gain a deeper understanding of a particular phenomenon or group of people. While both methods aim to provide rich and detailed insights, they differ in their approach, scope, and data collection techniques. In this article, we will explore the attributes of case study and ethnography, highlighting their similarities and differences.

Definition and Purpose

Case study is a research method that involves an in-depth examination of a specific individual, group, or event. It aims to provide a comprehensive analysis of a particular case, often focusing on a unique or rare occurrence. On the other hand, ethnography is a qualitative research method that involves immersing the researcher in the natural environment of a group or community to observe and understand their culture, behaviors, and social interactions.

Scope and Generalizability

One key difference between case study and ethnography lies in their scope and generalizability. Case studies are typically more focused and specific, aiming to provide detailed insights into a particular case or situation. The findings of a case study may not be easily generalized to a larger population due to the uniqueness of the case being studied.

On the other hand, ethnography aims to capture the broader cultural and social dynamics of a group or community. By immersing themselves in the natural setting, ethnographers can observe and document the behaviors, beliefs, and practices of the group. Ethnographic research often seeks to uncover patterns and themes that may be applicable to similar groups or communities, allowing for a higher level of generalizability.

Data Collection

Another important aspect to consider when comparing case study and ethnography is their data collection techniques. In case studies, researchers often rely on multiple sources of data, including interviews, surveys, observations, and document analysis. These various data sources help provide a comprehensive understanding of the case being studied.

On the other hand, ethnography primarily relies on participant observation, where the researcher actively engages with the group being studied, often for an extended period. This immersive approach allows the researcher to gain firsthand experience and insights into the culture, norms, and practices of the group. Ethnographers may also conduct interviews and collect artifacts or documents to supplement their observations.

Time and Resources

Case studies and ethnography also differ in terms of the time and resources required to conduct the research. Case studies are often more time-efficient, as they focus on a specific case or event. Researchers can collect data relatively quickly and analyze it in a shorter timeframe. However, the depth of analysis and the level of detail may vary depending on the complexity of the case.

On the other hand, ethnography is a time-consuming process that requires a significant investment of time and resources. Researchers need to spend an extended period in the field, building rapport with the community, and gaining their trust. The immersive nature of ethnography allows for a more comprehensive understanding of the group, but it also demands a longer-term commitment from the researcher.

Analysis and Interpretation

Both case study and ethnography involve a detailed analysis and interpretation of the collected data. In case studies, researchers often employ various analytical frameworks or theories to make sense of the data and draw conclusions. The analysis may involve identifying patterns, themes, or causal relationships within the case being studied.

Similarly, ethnographic research involves a rigorous analysis of the collected data. Ethnographers often engage in a process called coding, where they categorize and organize the observations, interviews, and other data sources. This coding process helps identify recurring themes, cultural practices, and social dynamics within the group. Ethnographers may also use theoretical frameworks to interpret their findings and provide a deeper understanding of the observed phenomena.

Applications

Both case study and ethnography have diverse applications across various disciplines. Case studies are commonly used in psychology, business, medicine, and law to examine individual cases, diagnose specific conditions, or understand unique situations. They provide valuable insights into complex phenomena that cannot be easily replicated or studied through other research methods.

On the other hand, ethnography finds its applications in anthropology, sociology, cultural studies, and other social sciences. Ethnographic research allows for a holistic understanding of different cultures, communities, and social groups. It helps uncover the underlying meanings, values, and practices that shape the lives of individuals within a specific cultural context.

In conclusion, case study and ethnography are two distinct research methods that offer valuable insights into specific cases or cultural contexts. While case studies provide a detailed analysis of a particular case, ethnography allows for a broader understanding of social and cultural dynamics. Both methods have their strengths and limitations, and the choice between them depends on the research objectives, scope, and available resources. By employing these research methods appropriately, researchers can gain a deeper understanding of the complexities of human behavior, culture, and society.

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Case study and ethnography: understanding the differences.

Home » Case Study and Ethnography: Understanding the Differences

Methodological distinctions exist between case studies and ethnography, which are essential for researchers to understand. Case studies focus on a specific instance, providing in-depth insights into a particular phenomenon or situation. In contrast, ethnography immerses researchers in a cultural context, offering a broader perspective on social practices and behaviors.

Understanding these distinctions allows researchers to choose the appropriate method for their objectives, ultimately shaping the findings and implications of their work. While both approaches aim to enrich knowledge, their methodologies serve different purposes—case studies for focused analysis and ethnography for cultural understanding. Identifying these differences enhances the research process and contributes to more accurate interpretations.

Defining Case Study and Ethnography

Case studies involve an in-depth exploration of a specific instance, event, or phenomenon. They often focus on real-life scenarios, providing valuable insights into complex issues. This approach enables researchers to draw conclusions and identify patterns that may not be evident with broader quantitative methods. A case study’s emphasis on context and detail allows for a comprehensive understanding of the subject matter, guiding practical applications in various fields.

In contrast, ethnography is centered on immersing oneself in a particular culture or community to gather qualitative data. This method emphasizes understanding the social dynamics, rituals, and interactions of the subjects over time. Ethnographers prioritize firsthand experiences to interpret behaviors and meanings in a contextualized manner. While both methodologies offer unique insights, they differ significantly in purpose and execution. Understanding these methodological distinctions aids researchers and practitioners in choosing the right approach for their specific objectives.

What is a Case Study?

A case study serves as a detailed examination of a particular instance, event, or phenomenon. It provides an in-depth analysis that facilitates understanding of complex issues within real-life contexts. By focusing on a specific subject, researchers can uncover patterns, influences, and outcomes that may not be apparent in broader studies. This targeted approach allows the investigation of a unique case, generating insights that can have wider implications.

In the realm of research, methodical distinctions arise when comparing case studies to other qualitative approaches. For example, case studies typically concentrate on the particular, while ethnographies emphasize cultural contexts and social relationships over time. Both methods yield valuable findings, but understanding their differences is essential for selecting the appropriate approach for a given research goal. Ultimately, case studies illuminate intricate realities, providing meaningful insights that guide future decisions and strategies.

What is Ethnography?

Ethnography is a qualitative research method focused on understanding the lived experiences of people within their cultural contexts. It involves immersive observation and participation, allowing researchers to collect in-depth insights about social practices and beliefs. This method differs from traditional research techniques in that it prioritizes the everyday attitudes and behaviors of participants instead of merely collecting data.

Key elements of ethnography include participant observation, interviews, and field notes. Participant observation requires the researcher to engage directly with the community, providing a nuanced view of their interactions. Interviews allow for deeper exploration of individual perspectives, while field notes capture contextual details that enhance understanding. Collectively, these methods provide a rich tapestry of human behavior and culture, highlighting methodological distinctions from other research approaches, like case studies, which may rely more heavily on structured data analysis.

Methodological Distinctions: Data Collection Techniques

Understanding the methodological distinctions between data collection techniques is crucial in both case studies and ethnography. Each approach employs different methods to capture data, reflecting their unique research objectives. Case studies often rely on structured interviews, surveys, and document analysis, focusing on specific instances or cases to derive insights. In contrast, ethnography emphasizes immersive observation and participation, collecting qualitative data through direct interaction in the field.

The choice of data collection techniques significantly influences the research outcomes. In case studies, data is often gathered from various sources, providing a comprehensive view of the subject. Ethnography, however, prioritizes in-depth engagement with participants, allowing researchers to obtain richer, contextual insights. By employing either method, researchers must remain aware of their specific goals and the intricacies involved in data collection, ensuring their techniques align with the intended outcomes of the study.

Case Study Data Collection Methods

In case study research, data collection methods play a crucial role in gathering pertinent information. Various techniques are employed to ensure a comprehensive understanding of the subject, leading to meaningful insights. Interviews are a primary method, allowing for in-depth engagement with participants. This technique facilitates the exploration of personal experiences and perspectives, making data collection rich and nuanced.

Observations can also be a powerful method in case studies. Researchers can gain first-hand insights by observing behaviors and contexts in real-time. Surveys may be utilized to collect data from a wider audience, enabling researchers to gather quantifiable data. Additionally, document analysis can provide historical or contextual insights, enriching the overall understanding. Methodological distinctions between these various techniques are essential to accommodate different research objectives and participant needs. Each approach contributes uniquely, reinforcing the need for a blend of methods to capture the complexity of the studied phenomenon.

Ethnographic Data Collection Methods

Ethnographic data collection methods play a vital role in understanding cultural and social dynamics within specific communities. Researchers use a variety of techniques to gather rich, contextual insights that often differ from traditional case study methods. Key methods include participant observation, in-depth interviews, and ethnographic field notes. Participant observation involves immersing oneself in the daily lives of subjects, fostering a deeper understanding of their experiences.

In-depth interviews enable researchers to explore individual perspectives, revealing nuanced attitudes and beliefs. Employing ethnographic field notes is essential for capturing real-time observations and reflections throughout the research process. These methodological distinctions set ethnography apart from case studies, which may rely more on secondary data or structured interviews. The combination of these techniques ensures a comprehensive and holistic view of the studied phenomenon, leading to more robust insights. Ethnographic methods, therefore, are indispensable for grasping the complexities of human behavior and culture.

Case Study Versus Ethnography: Analytical Methods and Applications

When comparing case studies and ethnography, it is essential to consider their methodological distinctions. Case studies focus on an in-depth examination of a specific instance or group within its real-life context. They aim to gain insights into complex phenomena by analyzing factors such as decisions, actions, and outcomes. On the other hand, ethnography emphasizes the cultural and social dynamics of a group over an extended period. Researchers immerse themselves in the environment to document experiencing life from the participants' perspectives.

The applications of these methods differ greatly. Case studies are often utilized in clinical, business, or educational settings, driving decisions based on specific instances. Conversely, ethnography finds common usage in anthropology and sociology, where understanding cultural nuances is vital. By choosing the appropriate method based on research objectives, scholars and practitioners can effectively draw meaningful conclusions from their work. Understanding these distinctions ensures researchers select the most suitable approach for their inquiries.

Methodological Distinctions: Analytical Approaches

Methodological distinctions in research hinge on differentiating analytical approaches, particularly in case studies and ethnography. While both methods seek to understand human behavior and experiences, their strategies are distinct. Case studies typically involve an in-depth examination of a specific instance or phenomenon. Researchers gather quantitative and qualitative data, focusing on broader implications or patterns that can be generalized across multiple contexts. This structured analysis facilitates a clear differentiation between data sources and findings.

Conversely, ethnography emphasizes immersive observation and participant engagement. Researchers adopt a more flexible approach, often spending extended time within communities to collect rich, descriptive data. This method values the intricacies of participant perspectives and cultural nuances, allowing for a deeper understanding of social dynamics. Recognizing these methodological distinctions helps scholars select the most appropriate approach for their research objectives, thereby enhancing the validity and effectiveness of their findings.

Analysis in Case Studies

Analyzing case studies provides unique insights that help differentiate findings from various research methodologies. Methodological distinctions play a critical role in how researchers approach the analysis, allowing them to focus on different aspects of data interpretation. In a case study, the analysis often revolves around specific situations or phenomena, extracting contextual information and driving practical insights. The emphasis is placed on understanding the narratives shaped by individual experiences.

The process typically involves gathering qualitative data and identifying key themes. By dissecting various components, such as challenges and opportunities within the situation, researchers can present a clear picture of the underlying issues. Combining these elements with direct evidence enhances credibility and comprehensiveness. More importantly, the analysis ensures that insights derived are not just surface-level observations, but rather deep explorations that inform future strategies and recommendations. This thoughtful analysis ultimately contributes to richer knowledge in the respective field, bridging gaps and enhancing understanding.

Analysis in Ethnography

Analysis in ethnography involves a deep understanding of cultural contexts and social interactions. This methodology focuses on observing and interpreting societal behaviors. Through direct immersion in the community studied, researchers can glean insights that quantitative methods might overlook. Methodological distinctions between ethnography and case studies emphasize the qualitative richness of ethnographic analysis.

In ethnography, data collection is often unstructured, permitting researchers to follow leads as they emerge. This allows the researcher to adapt their focus based on what is observed in real-time. Furthermore, analysis is interpretive, relying on the researcher's ability to engage with the community's meanings and narratives. The aim is not merely to describe behaviors but to understand the underlying cultural dynamics guiding those behaviors. Thus, ethnography offers a holistic view that can reveal the complexities of human interaction.

Real-World Applications

Understanding the real-world applications of case studies and ethnography reveals important methodological distinctions. Case studies often focus on a specific instance or scenario, providing in-depth insights into a subject. Ethnography, on the other hand, immerses researchers in communities or environments to understand broader cultural contexts. Recognizing these differences allows professionals to choose the most appropriate method for their research objectives.

In practice, these methodologies serve diverse fields such as education, healthcare, and market research. For instance, a case study may examine a successful education program's implementation within a particular school, providing useful lessons for others. Conversely, ethnographic research in healthcare could uncover deep-rooted beliefs affecting patient behaviors. By understanding the unique strengths of each approach, stakeholders can effectively apply their insights to enhance decision-making and foster actionable changes.

When to Use a Case Study

Case studies are particularly beneficial when deep insights into specific instances or phenomena are required. They are an excellent method for exploring complex issues within real-life contexts, making them ideal for research questions that necessitate in-depth analysis. By focusing on a single case or a small number of cases, researchers can gather comprehensive data that quantitative methods may overlook.

You should consider using a case study when your research objectives include understanding intricate dynamics, revealing unique patterns, or capturing subjective experiences. Additionally, case studies are useful in situations where existing theories are challenged or require refinement. Unlike ethnography, which immerses researchers in broader cultural contexts, case studies offer a more focused lens on particular cases. This methodological distinction helps clarify the most appropriate approach for your research needs, ensuring that you choose the method that best aligns with your inquiry objectives.

When to Use Ethnography

Ethnography shines in contexts requiring deep cultural insights and rich narrative detail. Employ this methodology when the goal is to understand behaviors, social interactions, and meanings attributed to specific groups or environments. Particularly advantageous is ethnography’s ability to provide nuanced perspectives that quantitative methods might overlook.

Consider focusing ethnography on complex social settings such as workplaces, schools, or communities. When the research question revolves around lived experiences and cultural practices, ethnography offers unparalleled depth. This approach is ideal for exploring how context shapes individual behavior and group dynamics, allowing for a more comprehensive understanding of the research subject. Moreover, if the research demands a long-term observation to capture evolving behaviors or interactions, ethnography stands out as the method of choice. Understanding these methodological distinctions can ultimately enhance the effectiveness of the research process.

Conclusion: Methodological Distinctions and Practical Implications

In exploring the methodological distinctions between case study and ethnography, we recognize their unique approaches to research. Case studies offer an in-depth exploration of specific instances or entities, focusing on observed outcomes and fostering learning. Ethnography, on the other hand, immerses researchers into cultural contexts, allowing them to comprehend social dynamics from within and yielding rich, qualitative insights.

Understanding these distinctions is paramount for practical applications. Researchers can select methodologies that align with their specific research questions and contexts. By carefully choosing the appropriate approach, scholars can ensure deeper insights and more actionable findings, advancing both academic understanding and practical implications in real-world scenarios. Each methodology offers distinctive perspectives that enrich our grasp of human behavior and social phenomena.

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Between Ideals and Realities: Investigating Perspectives of Chinese Postgraduate Researchers with Experience and Expertise in Higher Education Internationalization

• Original Article
• Published: 24 August 2024

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• Hantian Wu   ORCID: orcid.org/0000-0003-0904-8281 1 &
• Jie Zheng   ORCID: orcid.org/0000-0002-4155-2309 2  

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This study examines the perspectives and experiences of mainland Chinese postgraduate researchers regarding the internationalization of higher education in China. Using a partial ethnographic case study methodology, the research explores the situation at two case universities in China through interviews and observations. The findings highlight a macro-level shift from a neoliberal approach to an arrangement dominated by nationalist narratives and grand strategies, reflecting the complex interplay of domestic politics and geopolitical dynamics. This transformation raises concerns about the authenticity of internationalization efforts, described by participants as ‘fake internationalization’, due to a perceived lack of real global integration and reciprocal international interactions. Despite these challenges, the study reveals a cautious optimism among participants, who suggest that future internationalization could be sustained through regional collaborations and a reinvigorated focus on meaningful academic exchange and knowledge production.

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This study was supported by the National Social Science Fund of China (Education) [grant number CIA210277].

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Wu, H., Zheng, J. Between Ideals and Realities: Investigating Perspectives of Chinese Postgraduate Researchers with Experience and Expertise in Higher Education Internationalization. High Educ Policy (2024). https://doi.org/10.1057/s41307-024-00375-y

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Research Article

A local community on a global collective intelligence platform: A case study of individual preferences and collective bias in ecological citizen science

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Information Systems, The University of Haifa, Haifa, Israel

Roles Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing

Affiliation Department of Learning and Instructional Sciences, The University of Haifa, Haifa, Israel

Roles Conceptualization, Funding acquisition, Writing – review & editing

Affiliation School of Environmental Sciences, The University of Haifa, Haifa, Israel

Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

Affiliations Department of Information Systems, The University of Haifa, Haifa, Israel, School of Information Systems, Academic College of Tel Aviv-Jaffa, Tel Aviv-Yafo, Israel

• Ofer Arazy, 
• Keren Kaplan-Mintz, 
• Dan Malkinson, 
• Yiftach Nagar

• Published: August 26, 2024
• https://doi.org/10.1371/journal.pone.0308552
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The collective intelligence of crowds could potentially be harnessed to address global challenges, such as biodiversity loss and species’ extinction. For wisdom to emerge from the crowd, certain conditions are required. Importantly, the crowd should be diverse and people’s contributions should be independent of one another. Here we investigate a global citizen-science platform—iNaturalist—on which citizens report on wildlife observations, collectively producing maps of species’ spatiotemporal distribution. The organization of global platforms such as iNaturalist around local projects compromises the assumption of diversity and independence, and thus raises concerns regarding the quality of such collectively-generated data. We spent four years closely immersing ourselves in a local community of citizen scientists who reported their wildlife sightings on iNaturalist. Our ethnographic study involved the use of questionnaires, interviews, and analysis of archival materials. Our analysis revealed observers’ nuanced considerations as they chose where, when, and what type of species to monitor, and which observations to report. Following a thematic analysis of the data, we organized observers’ preferences and constraints into four main categories: recordability, community value, personal preferences, and convenience. We show that while some individual partialities can “cancel each other out”, others are commonly shared among members of the community, potentially biasing the aggregate database of observations. Our discussion draws attention to the way in which widely-shared individual preferences might manifest as spatial, temporal, and crucially, taxonomic biases in the collectively-created database. We offer avenues for continued research that will help better understand—and tackle—individual preferences, with the goal of attenuating collective bias in data, and facilitating the generation of reliable state-of-nature reports. Finally, we offer insights into the broader literature on biases in collective intelligence systems.

Citation: Arazy O, Kaplan-Mintz K, Malkinson D, Nagar Y (2024) A local community on a global collective intelligence platform: A case study of individual preferences and collective bias in ecological citizen science. PLoS ONE 19(8): e0308552. https://doi.org/10.1371/journal.pone.0308552

Editor: Hong Qin, Old Dominion University, UNITED STATES OF AMERICA

Received: November 16, 2023; Accepted: July 26, 2024; Published: August 26, 2024

Copyright: © 2024 Arazy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: This research was supported in part by the Data Science Research Center (DSRC), University of Haifa, Grant #100009444. Co-authors DM and OA are the recipients of this funding award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Crowds and groups of individuals working in coordinated manners, can exhibit collective intelligence—an emergent capacity to collectively learn, generate knowledge and insights, solve problems, make predictions, and produce artifacts [ 1 , 2 ]. This collective intelligence is often harnessed through various digital platforms and technologies, such as Wikipedia or iNaturalist (with over 150 million observations as of August 2023), where users contribute, rate, and curate content [ 3 , 4 ]. In Wikipedia, for example, diverse groups of people collaboratively produce high-quality articles, accurately and comprehensively representing a wide variety of topics [ 5 ]. On iNaturalist, communities of nature lovers report on plant and animal observations, collectively generating maps of species’ tempo-spatial distribution [ 6 ].

Global collective intelligence platforms often organize people through networks of local or national groups. For example, at a global level, Wikipedia is organized around languages, operating over 300 language-specific communities, where a language is often associated with specific geographical regions (or nations) and cultures; and within each such community, work is sometimes organized around topic-specific projects (i.e. WikiProjects; [ 7 ]). Similarly, iNaturalist is organized as a network of national “nodes” (over 20 national representatives) and projects (each focusing on a particular species or region) [ 8 ].

Individuals in these communities have preferences and dispositions that, when aggregated, could potentially yield biases in the collectively-generated artifact (note: to maintain clarity, in this paper we tried to reserve the use of the term "bias" to denote an uneven or disproportionate representation of a particular subject or variable within the collectively-generated artifact, whereas when to individual people, we use “preferences” or “dispositions” etc.). For instance, when like-minded people come together to create a Wiki article, the article may not provide a balanced representation of the topic at hand [ 9 ]. Likewise, if nature observers on iNaturalist have a preference for a particular species, (e.g., a rare species, or a “charismatic” species, such as large mammals or colorful insects [ 10 ]) they are likely to over-report observations of that species, and similarly under-report other species’ observations (e.g., species that are very common, or considered “uninteresting,” such as flies), yielding a bias in the aggregate map of species distribution [ 11 , 12 ].

Theories of Collective Action and Collective Intelligence suggest that under certain conditions, namely when the group is diverse in terms of members’ knowledge, experiences, and perspectives, and when individuals’ inputs are largely independent of one another, concerns for participation bias [ 13 ] and social influence [ 14 , 15 ] are largely alleviated, and group members’ biases could offset and collectively cancel one another out, yielding an unbiased outcome [ 16 – 19 ]. Nevertheless, eliminating bias and achieving unbiased outcomes in collective intelligence systems is difficult [ 20 , 21 ]. Notably, the literature on Wikipedia discusses racial, cultural, gender, and other biases [ 22 – 25 ]; researchers have shown, for example, that Wikipedia’s coverage of Western culture, geography, and history is much more comprehensive than its coverage of other cultures [ 20 , 26 – 28 ]. Likewise, bias exists in other collective intelligence systems.

We investigated one form of such collective intelligence: contributory science [ 12 , 29 ], or more specifically citizen science (CS), which allows scientists to leverage participant-generated data while providing an opportunity for engaging with local community members [ 30 , 31 ]. CS is becoming a powerful means for addressing complex scientific challenges [ 32 – 34 ] and scientific breakthroughs, such as the achievements made by contributors to Foldit , an online game in which the crowd predicts chemically-stable foldings of proteins [ 35 ]. Our focus here is on CS projects for ecological monitoring, where CS presents an alternative to traditional professional protocols [ 31 , 34 , 36 – 42 ]. As smartphones became a ubiquitous commodity, their widespread availability and adoption equipped many citizens with high-resolution cameras and GPS capabilities, which enable them to record geolocated images and videos. The data they record are collected on digital citizen-science platforms (notable examples include eBird and iNaturalist), which have become the largest source of biodiversity data [ 43 ]. These data allow professional scientists to address ecological and evolutionary questions regarding both geographic and temporal patterns [ 12 ]. In summary, the increased scope of CS projects for ecological monitoring in recent years has provided a new and important means for large-scale data collection [ 34 , 41 ], which in turn plays a pivotal role in the efforts to conserve, manage, and restore natural environments [ 44 – 46 ].

The ability to use citizen-generated data (in particular, from unstructured monitoring) hinges on the quality of these data. Data quality is often defined in terms of its “fitness for use” [ 47 , 48 ], a definition that is commonly applied to geographic information [ 49 , 50 ]. In order to assess the “fitness for use” of citizen-generated biodiversity data, we need to consider the possible uses of these data. Recent research has demonstrated that CS data (including data from sporadic monitoring) can be valuable for addressing a variety of research questions, related to issues such as species’ behaviors and traits, a species’ spatial distribution, and species’ richness (a count of distinct species) in a particular region: For example, CS data have been used to document the presence and range of rare species and morphs [ 51 , 52 ] and to examine organismal responses to climate change and human activity [ 53 – 55 ]; digital applications such as eBird and iNaturalist are used to understand species demographics and range expansion [ 56 , 57 ]; and finally, the availability of this plethora of biodiversity data has facilitated the development of a cost-effective framework for managing wildlife habitats and populations [ 58 – 61 ]. Although the possible uses of data determine its “fitness” and quality, often not all uses are known at the time of data collection [ 62 ]. We, thus, adopt a “use-agnostic” perspective [ 63 , 64 ] and our analysis attempts to provide a broad assessment of observer-based biases that transcends any particular ecological research question.

Challenges associated with CS data

Despite the potential benefits introduced by CS data, recurrent spatial and temporal biases can sabotage or dilute their applicability [ 12 ]. Especially with unstructured CS data, sampling locations and objectives are generally not predefined, and participants autonomously choose to collect data on certain organisms in certain areas and times. Would-be participants consequently select areas and environments they perceive as safe or have access to [ 65 ]. Also, areas of environmental justice concern (e.g., poor air and water quality, and high toxicant levels) are frequently underrepresented [ 66 ]. In particular, thus far, the biases inherent to CS data have prevented scientists from using unstructured CS data for estimating species abundance, which is particularly relevant for conservation aims [ 11 ]. The risks to data quality, and specifically the concerns regarding potential biases in CS data, have called into question the ability to use such data for research and practical purposes (e.g., developing conservation policies and intervention programs). Whereas CS has recently been employed for addressing some of these purposes, to date, other uses (specifically, estimating species’ abundance) still rely almost entirely on traditional systematic monitoring protocols, as scientists are cautious of the potential data-quality risks in CS data [ 11 , 12 ]. In sum, notwithstanding the potential benefits of CS, ensuring that CS-collected data are fit for scientific use poses a key challenge. Hence, a potential solution for environmental scientists and for collective intelligence systems in general is to eliminate biases and thus ensure the quality of the collectively-produced artifact [ 5 , 34 , 41 , 67 – 70 ]. The need to understand the quality of CS data, and specifically the potential biases in these data, served as the impetus for this research.

In the context of CS for ecological monitoring, prior research has attempted to deduce the community’s overall bias towards a species, time, or location of observations from the community’s aggregate pattern of reported observations [ 11 , 34 , 41 ]; however, such attempts are inherently limited, given that often there is no other existing measure representing the species’ true tempo-spatial behavior at a given moment (i.e., ground truth). Consequently, without having any objectively obtained measure for comparison, relying on the aggregate pattern of community-members’ reports in effect risks mixing the notion of nature’s true state with the preferences and choices of the people involved in the CS project [ 12 ]. Consider, for instance, the case where the aggregate pattern of reported observations shows a yearly increase in the count of a particular species, say wolves. This trend in the reported data may reflect an actual increase in the wolf population, or alternatively, it may reflect the community’s growing interest in wolves (e.g., due to recent attacks on livestock). Likewise, a decrease in the number of yearly reports on a species may reflect either an actual drop in that species’ numbers or, alternatively, the community’s reduced interest in that species (e.g., because the species is considered extremely common). Deducing peoples’ biases from reported observations is nearly impossible, suggesting that alternative methods should be employed for studying community-members’ biases.

In this study, our aim was to pursue such an alternative, by providing a rich contextual description of peoples’ preferences and biases, revealing the nuances of their considerations regarding the content they choose to record and share with the collective intelligence system. First, we need to examine what is known to date regarding how CS has been used and how the issue of bias has been addressed.

Related work

In this section we review prior studies on biases in CS. Whereas at the individual level, we focus on personal preferences or constraints that affect community-members’ contribution-related decisions, at the aggregate level, we are interested in the way in which these choices translate into biases in the collectively-produced artifact.

Citizen science for ecological monitoring.

Citizen science has been applied to ecological purposes such as estimating species dynamics, mapping species distributions, and studying climate change ecology [ 44 , 71 , 72 ]. The majority of CS projects for ecological monitoring are nonsystematic and unstructured, i.e., some guidelines are provided but not imposed, such that participants are free to report on any specimen from any species they observe without any spatiotemporal restrictions (i.e., monitoring is opportunistic) [ 73 ]. That is also the case with many of the projects on the iNaturalist platform. Such an opportunistic monitoring approach stands in stark contrast to traditional structured monitoring, where observers are required to adhere to formal sampling protocols, which define all aspects of sampling events, including location, duration, timing, target species, etc. [ 74 , 75 ]. Although unstructured projects usually benefit from wide participation due to their data collection flexibility, they are more susceptible to observer-based biases [ 34 , 41 , 42 , 70 , 76 – 78 ]. As a result, to date, scientists have been wary of using unstructured CS data, despite the potential benefit of wide participation [ 11 , 12 ].

In an effort to address this situation, researchers have started to pay greater attention to observer-based biases in CS ecological monitoring projects [ 11 , 12 , 34 , 41 , 79 – 81 ]. More broadly, this body of research is related to the study of biases in collective intelligence systems [ 24 , 82 , 83 ]. Recent studies have attempted to account for these biases using various statistical approaches [ 12 , 84 – 87 ], but these models do not consider the complexity of human social variables that create biases in these datasets [ 12 ]. We maintain that a key impediment to the development of robust bias-correction methods is an insufficient understanding of observers’ attitudes, preferences, and decision considerations. Understanding observers’ monitoring and reporting behaviors can shed light on observers’ decision-making process, as well as on the manners in which, collectively, individuals’ choices may amplify or attenuate biases, and hence is essential for developing statistical bias-correction methods.

Observer-based biases in ecological monitoring, CS projects.

The data reported to CS biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological factors, leading to biased data. Though empirical work has highlighted the biases in CS data, little work has articulated how biases arise in CS data. The literature on CS ecological monitoring distinguished between biases that are associated with species-inherent properties (e.g. size and pattern of species, which influences their detectability), and observer-based biases such as those linked to observers’ expertise, preferences, and monitoring equipment [ 12 ]. Our focus here is on the latter: observer-based biases. Observers’ considerations could be broadly classified into three categories: temporal, spatial, and species-related (or taxonomic) biases [ 76 ]. Thus, observers’ reports may be spatially clustered due to ease of access to some areas, such as proximity to the observer’s residence or commuter route [ 88 – 90 ], or difficulty accessing other areas [ 77 , 91 ]. Such reporting patterns yield spatial redundancies or gaps in the collected data [ 79 ]. Similarly, observers’ temporal activity patterns and their preference for certain species may introduce additional biases [ 34 , 77 , 78 ]: the fact that more people are active during the day can lead to gaps in reporting of nocturnal species. To date, the discussion of biases in the literature has been primarily conceptual, lacking an empirical investigation of observers’ attitudes, preferences, and choices. An exception is Bowler et al. [ 92 ], who used a questionnaire to study citizen scientists’ decision-making processes when recording species observations. They focused on factors related to observers’ motivations, experience, and knowledge; however, they did not directly investigate preferences and biases.

In sum, although previous relevant research has acknowledged the importance of observer-based biases in CS ecological monitoring projects, there is a paucity of human-centered studies that investigate observers’ specific considerations. In an attempt to address this gap in the literature, our study posed two primary research questions: RQ1–what are observers’ considerations when deciding where, when, and what to observe, as well as which observations to report? And RQ2 –to what extent are there commonalities in observers’ considerations? We recall that the aggregate pattern of community-members’ preferences and/or constraints has immediate implications for the consequential reliability of the database of reported observations, and—as a result—to scientists’ ability to gain reliable, actionable insights from the data.

Materials and methods

In order to address these research questions, we wanted to closely study the mindset of citizen scientists of a local community. We chose a particular citizen-science community, that allows its members extraordinary levels of autonomy, i.e., affording them to report on any species they choose, at any place or time, and only providing limited guidance and direction (corresponding to the project’s goal of representing species’ spatiotemporal distribution). We assumed that such a setting would likely expose a broad range of observer motivations, attitudes and preferences, and allow us also to reveal commonalities that could turn into collective biases in the data they report.

We conducted a multimethod case-study [ 93 , 94 ], over the course of four years, collecting data from observations, questionnaires, interviews, and archival textual material. This prolonged, in-depth investigation of the project enabled us to provide a streamlined and comprehensive view of the community members’ citizen-science practices, capturing observers’ perceptions and attitudes [ 94 – 96 ]. The data collected for this study was qualitative, and was analyzed using thematic analysis methods [ 97 ].

Research setting

The setting for this study is “Tatzpiteva” (in Hebrew, a compound of “nature” and “observation”), a CS project that is unrestricted in its biological scope, allowing observer-based preferences to manifest. That is, the observation protocol is unsystematic and opportunistic, as opposed to systematic monitoring that is commonly used in scientific research, whereby observers are free to choose the species, time, and location of observation. Tatzpiteva, launched in January 2016, is a local citizen-science initiative which focuses on a rural area the size of 1,200 square km in Israel’s northern region, where residents live in small communities (the only town in the area has a population of 7,000) and the dominant land use is open rangelands. The project is operated by the regional council together with the University of Haifa. Observations are reported by a local community of volunteers. A part-time employee of the regional council who is an expert naturalist, works as the community manager, encouraging participation, curating the volunteered observations, and educating observers on nature-monitoring procedures. In particular, the community manager encourages the reporting of all species, so as to provide a representation of the region’s biodiversity.

Tatzpiteva employs the iNaturalist online CS platform ( https://www.inaturalist.org/ ) [ 98 ], whereby observers use a mobile phone (both Android and iPhone applications) and a website. In addition, Tatzpiteva ( https://www.inaturalist.org/projects/tatzpiteva ) has developed its own localized mobile application and web site, and data is transmitted to the iNaturalist platform via an API. Observations are recorded using a camera and then reported (or uploaded) to the online database; when using a smartphone app, recording and reporting are performed at once (unless limited internet connection delays upload); and when using a standalone camera to record observations, reporting is performed at a later stage via the website. During the time of our study, roughly 40,000 observations were reported on Tatzpiteva by 400 observers, making up roughly half of all the iNaturalist observations in Israel. Most of Tatzpiteva’s observations were contributed by the community’s core members, whereas the majority of members are peripheral and contribute only occasionally. The Tatzpiteva community of citizen scientists is also very active in the physical sphere, with face-to-face gatherings (e.g., biannual community meetings, exhibitions of observers’ photos) and nature-observation field trips (e.g., on topics such as mushrooms or animals’ tracks), which are organized by the project’s staff, as well as by volunteers.

Participants

The composition of online communities is often described in terms of core and peripheral members. While there is no single accepted definition of a community’s core, the literature discusses core members in terms of their activity pattern (commonly, a small group of core members is responsible for the majority of the work), their tenure within the community, and by the roles and responsibilities they take [ 99 ] (for example, becoming a “curator” on iNaturalist).

During our study, we studied the community-at-large by participatory observations in many meetings over the course of four years, as well as by analyzing archival materials. But the bulk of this research was focused on the community’s core members. We noted that there were 38 members who constituted the core of the community: these were highly-active observers (with a minimum of twenty-five observations reported), held special responsibilities and, at the time of our study, had been active for at least six months. These members were all sent a questionnaire (described hereafter), and 27 of them signed an informed consent to participate in the study, and answered the questionnaire.

Tracking the online profile of those 27 participants on the iNaturalist platform revealed that they were responsible for 82% of the recorded observations in the entire Tatzpiteva project. Eight of them had been formally assigned “curator privileges” in the Tatzpiteva project, a position that corresponds to an administrator status in other online communities.

In the next stage, 15 of the questionnaire responders were interviewed, six of whom held curator responsibilities.

Data sources

Our acquaintance with the Tatzpiteva project began at its inception in 2016. Over the course of four years, we spent an average of two weekly hours informally both viewing co-located activities (meetings with the project administrators and community meetings) and reviewing online activities (reports on the Tatzpiteva website). We thus accumulated about 400 hours of informal observations. These immersive experiences allowed us to gain a deep and intimate familiarity with the Tatzpiteva project and community, and to accumulate substantial formal and tacit knowledge regarding its procedures, governance, and community aspects. The rich knowledge gained from these sessions provided the context for understanding and interpreting the qualitative data that we later collected in more formal, systematic manners.

In general, we used archival textual materials as a source for background information about the community and how it works and functions, and both the questionnaires and the interviews provided the data pertaining directly to the research questions posed.

Archival materials.

Archival textual materials were used as a source for obtaining information about the community and its workings, and specifically about the process by which the project leaders planned and guided the community’s activity. These materials included the original funding proposal (November 2014), three yearly reports by the project’s ecologist, and periodic newsletters issued by the community manager.

Questionnaires.

Data for addressing our research questions, in particular, data regarding observers’ considerations as to where, when, and what to observe, as well as which observations to report, were based on questionnaires and on follow-up interviews with focal community members. The questionnaire focused primarily on observers’ species-related dispositions. It included closed questions regarding observers’ demographics, activity frequency, and preferences, as well as three open-ended questions regarding participants’ criteria for selecting what species to record. In particular, two of the questionnaire’s open-ended questions asked participants: (Q3) How do you decide which observations to report and which to omit? What are the criteria you consider? (Q4) Are your observations oriented towards a particular species? If yes, which one? Do you actively go out into nature in an attempt to detect and record these species?

In addition, we introduced several questions regarding observers’ reporting behavior. In order to ground these questions, we asked participants to focus on a limited number of species that are common in the region and thus participants had likely encountered them. To sample a broad range of preferences, constraints, and behavior, we selected species that vary in terms of their detectability (the observer’s ability to notice the animal when it is nearby; determined by such factors as animal size, skin pattern and camouflage, as well as its general vigilance and its fear of humans or lack thereof), recordability (observers’ ability to record an animal once detected; this is affected by a number of factors, including the animal’s speed, as well as photography equipment), and rarity . Thus we opted to anchor the questionnaire, by focusing on four species—tortoise ( Testudo graeca ), wild boar ( Sus scrofa ), mountain gazelle ( Gazella gazelle ), and golden jackal ( Canis aureus ), which vary along the aforementioned dimensions of detectability, recordability, and rarity. For each of these four species, the third open-ended question asked: (Q5): During your monitoring activities, how likely were you to have observed [this species] yet refrained from reporting this observation? What was the reason for not reporting this observation? This was preceded by a close-ended question, (Q2): Please rank the animals observed by Tatzpiteva participants to reflect your preferences or the strength of your or emotional connection to each (1 = most preferred; 9 = least preferred, regarding nine species that are common in the region: jackal , wild boar , tortoise , porcupine , mole rat , hedgehog , fox , gazelle , and mongoose ). The list of questionnaire questions is included in S1 Appendix .

Interviews.

The questionnaire was followed-up with interviews. A member of the research team conducted and recorded the semistructured telephone interviews that were held with 15 highly involved community members (six of the interviewees had curator privileges). Interviewees (all of whom had completed the abovementioned questionnaire) were selected based on the community leader’s referral. The interview lasted approximately 15–20 minutes. The goal of the interviews was to shed light on the broader context of participation, and expose preferences that are related to the locations and times of observations. The interviews also probed participants on their patterns of activity and views regarding Tatzpiteva’s unstructured monitoring protocol. The guideline for semistructured interviews is included in S2 Appendix .

To summarize our investigation, after embedding ourselves in the Tatzpiteva community, we proceeded to collect data from the questionnaires and interviews. The relevant data set included all the data from the questionnaires and from the sections of the interviews pertaining to the constraints and preferences that shaped the participants’ decisions regarding when, where, and what to observe and how they decided what they included in their reports. As all of the collected data were in Hebrew, a translation into English was provided by two members of the research team, both bilingual native-level speakers of English and Hebrew).

Data analysis

In analyzing the questionnaire data, we followed the thematic analysis method [ 97 , 100 – 102 ]. In accordance with the goals of our study, we focused on a detailed description of the particular qualitative themes that reflect the participants’ thoughts regarding their criteria for choosing where, when, and what to observe, as well as which observations to document and report.

We performed the thematic analysis in two steps, beginning with the questionnaires, and then continuing to interviews. In the absence of a solid theoretical framework regarding the factors that influence observers’ reporting decisions, which could have guided a theory-driven investigation, we performed an inductive, bottom-up thematic analysis, such that themes were directly derived from the data. Given the inductive nature of our thematic analysis, we were careful not to delve deep into the literature at this stage, so as not to approach the data analysis with preconceptions. The thematic analysis was performed independently by two members of the research team. Upon completion of their analysis, their resulting thematic maps were compared and discussed. We found the independent analyses to be highly consistent, wherein the key difference—beyond the wording of codes—centered on whether to consolidate two closely-related codes into a single composite code. In addition, there were four cases in which the meaning of the text was not entirely clear, which led to disagreements regarding the code that best corresponded to each of these text segments. The researchers discussed these inconsistencies until a consensus was reached. The result of this process was a set of agreed-upon codes and their definitions, the association of text segments to codes, and a grouping of codes to higher-order themes.

Next, we transcribed the interviews and applied the themes that had emerged earlier to our analysis of interview contents. The analysis of interviews, too, was initially performed independently by two members of the research team, and then consolidated through discussions between the researchers. The codebook is included in S3 Appendix .

Finally, through discussions, and relying on our intimate, unmediated acquaintance with the community, we synthesized findings and insights from all sources (questionnaires, interviews, and archival data) into emerging themes which we present next.

The presentation of results in this chapter is organized according to the emerging themes we identified through the process described above. As common and recommended in qualitative research, and specifically in ethnographic studies, we illustrated our findings with archetypal quotes that serve to highlight common attitudes and behaviors of the community members [ 103 – 106 ]. Quoted members are designated with brackets (e.g. [pr5] indicates participant #5).

Background and descriptive statistics

Analysis of archival data, as well as interviews with the community members and administrators, shed light on the ways in which the project administration sought to shepherd the activity of the local community of observers. Whereas the nature-monitoring protocol that was used was entirely opportunistic, the project’s administrators attempted to channel observers’ participation by encouraging them to record all species, everywhere, at any time. Observers were encouraged to put aside personal preferences or any assumptions as to what is important (e.g., rare species) and try to record any species, across the entire area during all seasons and times. To wit, the community manager is quoted in the regional newspaper saying:

At the highest level, the public decides what to monitor, performs monitoring, and takes part in drawing conclusions. There is no requirement to photograph only rare species, but [rather] also what seems trivial: crows and sparrows, wild boar and porcupines, wolves and chrysanths, oak and pine trees. This way, we will learn to know the entire [ecological] system …. [May 2016 , the regional council’ newspaper] .

A year later, the community manager was interviewed for the same newspaper and added:

Observers ask me: what should I record? and I respond: in order to deeply study the region’s nature, we should record everything!—From ants to vultures, flowers, and every species in nature—they are all part of the ecological system … Furthermore, when we are taking a walk in nature, we see a plant and a few strides later we see the same plant again—should one upload another observation? The answer is Yes. Beyond species richness, we are also studying species abundance… . [July 2017 , the regional council’ newspaper] .

The results regarding observers’ considerations are based on the responses of the 27 participants who returned the questionnaires; a statistical summary of their characteristics is shown in Table 1 .

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https://doi.org/10.1371/journal.pone.0308552.t001

The primary factors underlying participants’ reports

Altogether, we thematically analyzed 211 utterances that were extracted from questionnaires, and grouped them initially into 20 subcategories and then later into four themes, namely, the primary factors underlying participants’ decisions of where, when, and what to observe, as well as which observations to report: (a) recordability , i.e. the ability to record the species once observed; (b) community value ; (c) personal preferences ; and (d) convenience .

Recordability.

Many of the questionnaire participants pointed to constraints in their ability to record species that have been detected—i.e., recordability —as a key factor. Constraints were linked to two primary factors: First, certain species are easier to record than others, namely species that move slower and are less sensitive to the presence of humans, such as plants or slow-moving animals, e.g., tortoise (in contrast to shy and fast-moving animals, such as gazelles or jackals ). A typical statement made by observers when describing the factors influencing their reporting process is: “The ability to take a picture” [pr3]. An example of a response explaining why a participant did not report on a particular species: “Animals that run away faster than it is possible to photograph [are] not reportable …” [pr4]. Second, recordability was heavily influenced by the observers’ photography equipment and its ability to capture the distinctive features that facilitate accurate identification of the species, i.e., those using professional cameras were able to photograph at a distance. Typical statements describing observers’ reasons for not reporting a detected species include: “Difficult to photograph using a smartphone” [pr7] and “inappropriate [camera] lens” [pr8]. Overall, in the context of our questionnaire, recordability emerged as the primary factor affecting an observer’s recording behavior, with 76 utterances (36% of 211 utterances).

Value to the community.

Community value , that is, the extent to which reporting the species is considered valuable for other members of the community or to the project’s goal of creating an archive of the region’s biodiversity, emerged as a key factor that influenced the decision of where, when, and what to observe, as well as which observations to report. Community value was associated with either the ability to accurately identify the species in photos; species’ rarity or abundance in the region; the importance the observer ascribed to the archive of observations, or other assorted importance-related considerations. First, we found that the ability to identify the species was a key consideration in deciding what to report. Some participants mentioned their own ability to identify (or name) the species, whereas others indicated that they take into account the community’s ability to identify the species. For example, [pr10] wrote: “I report everything that I see and I know it would be possible to identify. If the photo was of low quality or it was not possible to identify the observation (for example, a plant with no flower or fruit) I gave up. I have learned to differentiate between the identifiable features and those that are not identifiable” [pr10].

Second, we found that the extent to which observations are rare was a primary reason for reporting on a detected species, and conversely species’ abundance was a key reason for opting not to record or report an observation. Survey participants frequently mentioned “rare” or “rarity” explicitly in their considerations for recording observations. Along the same lines, participants indicated that they were less likely to record “Species that are highly abundant—a crested lark is an abundant species and nobody reports it. Same as sparrows. The same goes for wild boars and gazelles” [pr1].

Third, a few participants mentioned that they chose to record an observation when it was important for other members of the local community or to other viewers of the data. Typical justifications for recording an observation included “An observation that I think may interest others …” [pr3] and “[the] importance of the information to the general knowledge base” [pr16]. In the interviews, three participants pointed to specific collective concerns related to the future development and the potential danger to nature, specifically the deployment of wind turbines in the region, as a reason for monitoring that particular area. For example, [pr10] stated the following:

It may be possible to link [Tatzpiteva monitoring] to an environmental and social issue. For instance, now there is this issue of wind turbines in the region, we could conduct a [monitoring] project focusing on this issue, monitoring biodiversity in the area, which could serve as the basis for discussion and decision-making. That would be valuable from both the environmental and the communal perspectives. [pr10]

Lastly, questionnaire participants brought up additional importance -related considerations. Notably, several highly-active observers exhibited an understanding of systematic monitoring protocols (although not formally required in projects such as Tatzpiteva) and mentioned that their reporting decisions did not privilege any specific species, such that they recorded everything they encountered, for example, “I report everything, but mostly mammals and birds” [pr17]. Overall, in the context of our questionnaire, community value was found to be a key factor affecting observers’ recording decisions, with 45 utterances (22% of 211 utterances). Rarity was the primary factor in this category, providing roughly half of all utterances associated with community value .

Personal preferences.

Observers’ personal preferences also had a substantial effect on participants’ reporting decisions. We identified several categories for these preferences: personal preference for a particular species, region, or time; attraction to a species’ specific features (e.g., the smell of a particular flower); the desire to learn more through others’ feedback; limiting one’s recurrent reporting of a particular species; and other personal preferences. First, many observers simply indicated that they chose to report what they personally found interesting and they avoided reporting what they found to be uninteresting. Related to this, a few participants mentioned emotional attachment or a personal previous experience (e.g., “… mostly, personal experience …” [pr8]) had influenced their reporting decisions.

Second, several participants mentioned that they chose to report species that they found attractive and beautiful (e.g., have a preference for what is “beautiful… awesome …” [pr3]) or have special features (e.g. “plants—color, size … will cause me to take more photos” [pr17]).

A third type of a personal preferences was the desire to learn, and a few questionnaire participants mentioned that they chose to record “…Things that I do not know and want to know …” and “I upload [images of] plants that I’m interested in knowing their name …” [pr14].

A fourth personal preference was the desire to avoid reporting the same species multiple times (e.g., [a consideration is] “The number of times that I reported the species in the past” [pr16]; [reason for not reporting] “tortoise—too trivial” [pr9]) Finally, some participants indicated their preference to report certain species or places, without providing an explanation. Overall, in the context of our questionnaire, 62 utterances (29% of 211 utterances) indicated personal preferences as influencing observers’ decisions regarding what to record.

Convenience.

Another important factor influencing observers’ reporting decisions was the extent to which they found it convenient, in terms of the time and effort required to report an observation. For example, participants indicated that “I don’t have time to engage with this” [pr2] and “[I don’t have] spare time” [pr13]. Convenience is linked to several circumstances. First, some observers only make sporadic reports, such that observations are made when the person is engaged in a different activity—leisurely outdoor activity, professional work (e.g., a tour guide) or when driving—and is less attentive to reporting observations. For example, when describing her considerations regarding what to report, one participant mentioned “I report on observations while driving as part of my work … sometimes when I had some spare time on my way to work, I stopped to take a picture. I don’t take a drive especially to make observations” [pr19]. Others mentioned that they do not carry a camera when in nature.

A second convenience -related consideration pertains to the equipment used, especially for observers who use professional cameras, and need to later upload those to the Tatzpiteva website, sometimes requiring them to edit and resize images, as evident in the following quote from an observer who uses a professional camera: “Lots of images taken, but only few are reported, for many reasons: lack of time to resize, sort, and uploading images [to the website]” [pr8].

Finally, convenience was also associated with location-based and temporal preferences, for example, observers indicated that they preferred to be active in certain places (e.g., not far from home; places that are easily accessible, in proximity to roads) and times (i.e., certain times of the day or week). For example, some indicated that they chose to monitor places with easy access or in a location with an abundance of species, “When I’m at a point with rich fauna, I’ll document a large part of that fauna” [pr17]. Overall, in the context of our questionnaire, convenience was found to be an important factor affecting (28 of 211 utterances, constituting 13%) of observers’ recording decisions.

Summary of findings regarding observers’ considerations

In sum, findings from our study provided in-depth insights regarding observer’s considerations when deciding where, when, and what to report. Fig 1 below provides a summary of the count of utterances per each of the four primary factors discussed above. Recordability and personal considerations each made up roughly a third of the utterances regarding observers’ decision of what to report (36% and 29% of the total 211 utterances, respectively), community value accounted for 22% of the utterances, and convenience had a lesser impact (13%) on observers’ decision whether to report a species that had been detected. We note that participants often pointed to several factors that influence their decisions, and the average participant provided quotes that were linked to 2.5 of the four themes. The interviews provided a similar picture, with 14, 10, 12, and 7 interviewees addressing the themes of recordability , community value , personal preferences , and convenience (respectively).

https://doi.org/10.1371/journal.pone.0308552.g001

Overall, we conclude that observers’ decisions are affected by multiple factors, rather than by a single consideration. An illustrative quote from the questionnaire’s response regarding one responder’s considerations: “Free time, rarity, the ability to take a high-quality photo” [pr13].

Amassing individuals’ preferences—Biases in the aggregate database

To understand the extent to which individuals’ preferences and constraints amass to biases in the aggregate database of observation, we performed a secondary analysis on the labelled data. Going back to our original organization of utterances into subcategories and primary themes, we analyzed each subcategory and considered: (a) the extent to which each factor that influenced the decision whether to record or report an observation was common among the participants; and (b) whether such a shared preference/constraint could skew the aggregate database spatially, temporally, or taxonomically. Whereas answering the former was based directly on the labelled questionnaire data, determining the latter—i.e., the potential for aggregate biases—was also guided by the literature, the participants’ behavior, and by the subject-matter expert (ecologist) in our research team. For example, when analyzing the subcategory labelled as “Photographing equipment enabling or inhibiting the ability to record” (under the theme of recordability ), we found (a) that about two-thirds of the study’s participants used a similar recording device, a smartphone; and (b) we determined that such a common pattern was likely to cause a taxonomic bias in the aggregate database (e.g., fewer photos of a species that can be seen only from afar), but unlikely to yield spatial and temporal biases.

Next, we summarized the data and identified the key risks to taxonomic, spatial, and temporal biases. In addition, we analyzed participants’ ranking of their affinity to nine species (see Question 2 of the Questionnaire, in S1 Appendix ), looking for common patterns. We present our findings below. As the next section demonstrates, in all three dimensions—spatial, temporal, and species-related (i.e., taxonomic), preferences and constraints were common—at least to some extent—among many of the participants, suggesting that the aggregate database of observations in the collective intelligence system is likely to be biased in particular directions.

Temporal patterns.

Our analysis reveals several preferences/constraints that are commonly shared between community members, which may result in temporal biases in the aggregate database. Specifically, almost all observations are reported during hours in the day where it is convenient for people to be out in nature: during daytime, especially in hours when the weather permits (not too cold; not too hot) and during weekends and holidays, where people have more time of leisure. This effect may interact with other factors, for instance, recording observations at specific times may require special photography equipment, hence the (lack of) availability of such special equipment may affect temporal activity patterns. For example, addressing the reasons for not reporting an observation, one member explained that "Encounters [with wild boar] are often in the dark or by surprise, and by the time the camera gets into action it’s too late" [pr9].

Such a consideration is applicable to the majority of community members, who rely on smartphones for taking pictures. Additionally, our data indicate that participants often reported on observations only when they were able to identify the species with confidence. Here, again, there is an imbalance, with more reported data collected during the daytime, given that it may be more difficult to identify species in a picture that was taken during nighttime.

Spatial patterns.

Our analysis identified a few preferences/constraints that were commonly shared among community members, which may result in spatial biases in the aggregate database.

First, Accessibility is a major issue. In the region that is at the focus of this study, accessibility is primarily affected by the following three factors:

• Place of residence . People tend to report close to home, and more broadly—in more accessible places [ 107 ]. Hence, the uptake of contributory science platforms by observers is uneven across space and demography [ 12 ]. That is, when a significant portion of the community is concentrated in a particular city or village, we can expect a high volume of reports from that area.
• Terrain . Some areas are hard to access on foot—these could be steep slopes, canyons, areas of dense thorny bush, etc. While these terrains are also less accessible to some animal species, there are plants, as well as some animal species, e.g., the Rock Hyrax (Procavia capensis) , which do inhabit such areas.
• Enclosed areas . Some areas are enclosed by government or by private landowners, limiting all observers’ access and thus their ability to report observations (we note that beyond the effect on observers’ patterns of reporting, enclosure can also affect animals’ spatial behavior patterns).

While accessibility was not often explicitly mentioned in response to the questionnaire, it was mentioned in some of the interviews. We suspect this may be because members did not think it was worth mentioning in writing, it did not occur to them, or it may have seemed obvious to them. However, the effect of accessibility on the breadth of the data is clearly evident in the participants’ reports (please refer to [ 11 ] for a discussion on this matter). Second, when people share a concern regarding an ecologically harmful activity that takes place in a particular location (e.g., industrial development), they are more likely to monitor that area.

Lastly, tree and plant coverage may affect community-members’ ability to identify the species in the image and, consequently, it might also reduce their tendency to report from these regions, where the vegetation allows animals to camouflage.

Species-related patterns.

Individuals’ preference towards particular species is a factor that greatly affects their reporting patterns. To the extent that community members share such preferences, the aggregate database may be crucially biased in terms of over- and under-representation of certain species. Some factors that are shared among community members exert a particularly strong influence on observers’ choices regarding what to monitor, posing a serious threat to the database’s reliability.

Affinity . We first notice that people tend to feel some affinity towards certain species. As part of our questionnaire, we asked people to rank their personal affinity towards nine species. The results reveal common attitudes among community members, indicating a communal preference. Particularly, Gazelles , which were first on the list for nearly half of the participants, ranked first overall. In contrast, jackals were ranked last, with half of the participants ranking them in the last two spots. Table 2 below presents the order of participants’ affinity for the various species, based on the average rankings.

https://doi.org/10.1371/journal.pone.0308552.t002

Attractiveness . We noted a bias towards species that have a unique or attractive appearance, e.g., some butterflies, birds, and colorful plants. The large portion of observers that reported on these attractive species resulted in over-representation of these species in the aggregate database (and an under-representation of species with a more casual appearance). A common answer to the question regarding reporting criteria was: “Usually I report something that is unique” [pr6]. (Similar responses were provided by [pr1, pr2, pr4, pr11]). We suspect Attractiveness is one (probably a major) driver of affinity towards certain species.

Rarity . Our data show that preference for monitoring (looking for, and reporting) rare species was common among many members of the community. Species’ abundance in the area is perhaps the most salient factor influencing observers’ choices of what species to report: people are much less likely to report on common species. For instance, when answering “How do you choose what to report?” and “What factors are considered?” (Q1), [pr7] echoed the responses of many participants and answered: “ I choose to report rare species. ”

Rarity is a species-related feature, so it is likely to affect all observers in a similar manner, and thus yield a major bias in the aggregate database, with an over-representation of the rare species. For example, the Tatzpiteva database includes more reports of porcupines than of ants (which are more abundant by several orders of magnitude [ 108 ]).

Ascribed-importance . Another related factor is the importance that the community assigns to specific species (e.g., gazelle is a national emblem; in northern Israel, wolves present a danger to livestock): the more community members share the beliefs regarding what is “important,” the more skewed the aggregate database will be. For example, reflecting the attitudes of several community members, [pr9] stated: “[I report on] plants that people would encounter and would want to know their names.”

Species identification . Participants noted that they often report on observations only when they are able to identify the species with confidence. A repeated theme was: “[I don’t report observations that] are very difficult to identify” [pr14]. On aggregate, this may lead to an over-representation of easily-identifiable species (e.g., mammals) and an under-representation of species that are more difficult to identify (e.g., mushrooms).

Finally, it is worthwhile pointing out another factor that might contribute to cumulative biases in the database, even though it is not directly related to people’s affinities or attitudes towards wildlife, and that is the equipment they use.

Equipment-effect . Observers’ photography equipment greatly influences the species that they choose to monitor and report. Professional equipment allows taking photos from afar, which is particularly important for recording observations of animals that shy from humans, as well as for small-size animals (e.g., insects). On the other hand, in some cases, smartphone cameras could be operated more quickly, allowing observers to capture images of animals that they come upon unexpectedly. To the extent that the majority of the community uses a single type of equipment (e.g., in our case, over two thirds of the participants used smartphone cameras), the aggregate database may be skewed, by including mostly animals that lend themselves to be recorded using that type of equipment.

It is worth noting that some of the factors discussed here are not constant, but rather may change over time. For example, as an observer amasses more observations of a particular species, he or she is less likely to report on this type of observation over time. Along the same lines, the importance that is assigned to species may shift over time, which suggests an interaction between species-related and temporal biases.

The underlying rationale for this study was the recognition that while unstructured CS projects better succeed in engaging the public and thus have the advantage of potentially producing large amounts of biodiversity data, they are also more likely to be vulnerable to bias. When each observer decides when, where, and what to monitor, as well as which observations to report, then to the extent that observers share preferences, views, values, etc.—which is especially likely in smaller, local communities—these individual considerations might accumulate to create collective biases, yielding archives of citizens’ reports which do not reflect the actual spatiotemporal distributions of species in the environment [ 11 , 12 , 41 , 42 , 76 – 78 , 89 , 90 , 109 , 110 ].

Prior studies have raised concerns regarding the existence of such bias, and a few have even provided empirical evidence demonstrating that the data in the co-produced archives of observations were skewed [ 89 , 90 , 109 , 110 ]. Yet, until recently, there has been a lacuna in academic literature on citizen science regarding the specific considerations and/or constraints that underlie observers’ reporting decisions. A primary contribution of this paper is in bringing observers’ authentic voices regarding their consideration as to where, when, and what to observe, as well as which observations to report. The findings from our case study surface the intricacies and nuances in observers’ decision-making process.

In recent years, studies have introduced conceptual frameworks that describe citizens’ monitoring process [ 11 , 12 ], greatly contributing to our understanding of observer-based biases. These frameworks describe the monitoring and reporting process as a series of stages. Notably, Arazy and Malkinson [ 11 ] describe observers’ decision-making process as: monitoring, identifying, recording, and reporting observations; and Carlen et al. [ 12 ] depict the process as a series of “filters”, where each filter places a restriction on the possibility of reporting observed species, gradually moving away from the true state of nature (i.e. ground truth). The classification of biases that emerged from our empirical analysis largely corresponds to the stages in these conceptual frameworks. Specifically, our Recordability and Convenience categories correspond to a large extent to Carlen et al.’s [ 12 ] Detectability and Sampling filters, respectively. Nonetheless, our findings challenge other aspects of these conceptualizations. One noticeable divergence is that the observer’s decision-making process that emerged from our analysis is not a linear one; rather, observers’ decisions intricately combine multiple factors and considerations, as illustrated by the following quote from an interview: “I report on an interesting observation. If there is an observation that seems to me as valuable. If there is something that I don’t recognize, usually I report it. If these are things that are abundant, then it depends whether I feel like reporting it or not” [pr10].

Crucially, to the best of our knowledge, no prior study has linked individual observer considerations to biases in the aggregate database, or studied the conditions under which individual observer preferences cancel-out one another, which could provide a way to keep the aggregate database unbiased, or at least, less biased.

Our multimethod case study of a local community of nature observers—Tatzpiteva—on the iNaturalist platform sought to address this gap. The results pertaining to RQ 1 revealed the main factors that shape observers’ reporting decisions, namely, recordability , community value , personal preferences , and convenience; identifying these categories enabled us to highlight commonalities in observers’ considerations. The results of our analysis pertaining to RQ2 indicated that there is a real risk that some considerations are widely shared, yielding biases in the aggregate database of observations.

These findings not only inform and enrich the existing knowledge in the fields of CS and collective intelligence; importantly, they also suggest practical implications for both CS community custodians and for scientists that need citizen-produced reports to be reliable and “fit” for addressing scientific objectives. We detail some recommendations subsequently in the Practical implications section.

Contribution to the literature on biases in ecological citizen science

An important contribution of this study is in exposing the categories of factors that shape observers’ decisions on where, when, and what to observe, as well as which observations to report, namely, recordability , community value , personal preferences and convenience . Few prior studies have alluded to these factors [ 12 , 76 – 78 , 81 , 90 ]. In particular, our findings suggest that—at least in the context of CS projects that require a species’ photograph to be recorded and shared using smartphone or web upload– recordability is the most salient factor that influences observers’ choices (in our study, 36% of utterances). The literature makes a distinction between expertise-based CS projects (where trained and certified volunteers monitor a species within a region employing professional monitoring protocols and equipment) and evidence-based projects (such as iNaturalist) [ 11 ]. The quality assurance processes in expertise-based projects rely primarily on the expert’s (or trained volunteer’s) ability to identify focal species and follow monitoring protocols), such that there is no requirement for providing evidence in the form of time-stamped geo-tagged photo. Without the requirement for a photo, recordability is not an issue, the hence prior studies of observer behavior in expertise-based CS were concerned with detectability (aka “observability”) [ 12 , 45 , 111 – 113 ]. We note that only few prior works explicitly discussed the notion of recordability [ 11 , 76 , 78 ].

Our findings also highlight the importance of community value (e.g., contributing to the project’s goals, species’ rarity; 29% of utterances in our study) and personal preferences (e.g. favoring particular species, learning; 22% of utterances in our study) in shaping observers’ reporting decisions. Finally, our results show that convenience -related considerations also affect observers’ reports (in our study, 13% of utterances).

We noted substantial differences in observers’ decision whether to record an observation (i.e., recordability ), in the extent to which species rarity influenced their observation patterns (i.e., community value ), in their affinity for certain species (i.e., personal preferences ), and in the way various constraints influenced their decisions on where, when, and what to observe, as well as which observations they reported (i.e., convenience ).

In addition to the four categories identified, our study of observers’ decision-making process revealed that their views regarding the monitoring protocol were varied. Some observers reported on a narrow list of species, primarily based on attachment to the species; others were primarily interested in a broad category of species, for instance insects or plants, and within that category attempted to record a large variety of subspecies, and a smaller group of particularly active observers attempted to record every species. Recognizing the risk of bias and the benefits of a more structured monitoring protocol, this small group opted to monitor in a semisystematic manner. This indicates that the majority of participants preferred the flexibility and autonomy enabled by the unsystematic protocol.

In this context, it is worth noting that some shared attitudes and preferences, such as the value that observers place on the communal goal of producing a valuable, high-quality archive of observations, are apt to reduce , rather than heighten, temporal, spatial, and taxonomic biases. For example, community-members’ awareness of the importance of recording both diurnal and nocturnal animals may lead them to conduct more nighttime observations. Similarly, understanding the importance of collectively developing an accurate “map” of nature may encourage observers to report also on common species. Interestingly, without being asked about bias directly, participants addressed this issue as one aspect of community value , reflected specifically in their desire to learn, and to produce a reliable archive of observations.

Our findings further suggest that the effects that participant preferences and communalities have on temporal, spatial, and taxonomic bias differ: First, observers’ biases are not likely to pose a serious threat to ecologists’ ability to identify temporal trends in the data (e.g., changes of population sizes over time). Given that ecologists often focus on a particular species and study seasonal or yearly trends, communalities of a more granular character (e.g., a preference for weekend vs. weekday observations) are not likely to affect the conclusions about seasonal/yearly trends. Second, when considering the effect of participant trends and commonalities on spatial bias in CS data, the issue of a localized group of observers, their access to certain terrains or enclosed areas, and their shared ecological concerns regarding a specific ecological threat, are all factors that are likely to result in spatial bias . However, in this regard we wish to point out that the systematic monitoring protocols employed by scientists and nature conservation agencies are also affected by—and subject to—accessibility constraints. Their solution is to collect data from a few selected locations (e.g., a transect survey), the trends of which are then extrapolated to surrounding areas. We note here that similar extrapolation methods could be applied when working with CS data. Hence, it may be surmised that the risk of spatial biases in unstructured CS data is not particularly high, as compared to the similar risks involved when using systematic monitoring protocols. Finally, on the question of CS-collected data leading to taxonomic or species-related bias, our results demonstrated numerous trends that affect participants’ behaviors, which together increase the likelihood of taxonomic bias in the accumulated database. Here we mention yet another behavioral trend that is likely to increase taxonomic bias (but was not presented in the results section because it was expressed by only one participant), namely, perceived danger . Animals perceived as posing a potential danger to humans are difficult to record. Assuming that people share these fears, the aggregate database of reports is likely to under-represent dangerous animals. Although in the particular context of our study, the animals observed only rarely pose a threat to humans, the fact that perceived danger may be a salient factor in other CS projects further increases the likelihood that CS-collected data will contain taxonomic bias.

Another novel insight and a contribution of our study is in revealing the instability in observers’ attitudes and preferences. Our questionnaire and interviews revealed that temporal shifts in observers’ choices are common. Such shifts may be associated with a key event (e.g., moving one’s residence or purchasing new photography equipment), learning and developing new interests (an expert in reptiles gradually takes interest in insects), or may reflect change in habit (e.g., change in one’s availability during the week, ceasing to monitor regions that are open to the public only during weekends). Such shifts may have key implications for our understanding of observer-based biases and for the distortion they create in the community-generated database of observations.

Together, our findings inform the literature on citizen scientists’ perceptions, attitudes, and behavior [ 11 , 12 , 67 , 114 – 133 ]. Knowing what the biases are and understanding their salience is important for the design of interventions [ 79 ] and statistical methods [ 84 – 86 , 134 ] that attempt to alleviate observer-based biases in CS ecological monitoring projects.

Contribution to the literature on biases in collective intelligence systems

For the most part, prior works on biases in ecological CS have been restricted to that particular context, thus missing an opportunity to inform, as well as to be informed by, relevant literature in the related field of collective intelligence. A contribution of this study is in placing the discussion of biases in ecological CS within the broader discourse on biases in collective intelligence systems. When considering the reliability of data collected by citizens on a CS platform, and especially a project that does not enforce a strict protocol, we note that such concerns are not limited to CS ecological monitoring, but rather are relevant to other collective intelligence systems.

The literature on biases in user-generated content and social networks has been mostly concerned with large-scale collective intelligence platforms, such as Wikipedia [ 20 , 26 – 28 , 135 – 141 ]. In those settings, people’s preferences, attitudes, worldview, and expertise determine what content they choose to contribute [ 23 , 137 ] (referred to as ‘motivational biases’ [ 138 , 139 ]). However, because of the group’s size, diversity, and the range of members’ independent opinions [ 142 , 143 ], their preferences cancel each other out and thus, bias in the aggregate outcome is attenuated [ 17 – 19 ].

By contrast, the global/local (or glocal ; [ 144 ]) organization of collective intelligence, such as the nodes on the iNaturalist platform, challenges the assumptions of group diversity and independence, and calls into question the platform’s ability to successfully distill “wisdom from the crowd”, or in other words, valuable, truthful insight from the information that is gathered from local monitoring projects. Clearly, local configurations are important for encouraging members’ contribution and engagement, as well as for organizing and coordinating activity [ 145 , 146 ]. Nonetheless, as our findings indicate, the content generated by such local communities is particularly prone to biases [ 147 ], because social networks and geographical collocation help foster common values, beliefs, and concerns, which spread and take hold in groups and organizations [ 9 , 148 – 150 ]. For example, the identification of the subcategories of importance to the community and importance to the archive of observations under the category of community value suggest that members of a rural community may ascribe particular importance to the observation of a species that preys on their livestock or harms their crops, resulting in over-representation of that predator in the collective database. In another example, our participants ascribed importance to the deployment of wind turbines, which was endangering the birds in the area. In a similar manner, particular area threatened by future industrial development may organize to track and record wildlife in that particular location (e.g., bio-blitz), resulting in over-representation of the region and its wildlife.

Furthermore, norms and social pressures may be heightened for people who live in the same small local community, causing people to behave in a similar manner. This is especially relevant to the subcategories of personal preferences (i.e., for a particular species, region, or time), as neighbors may organize joint observations at a particular time and/or area, or share their affiliation for a particular species, thus yielding an over-representation of these species in the archive. Hence, despite some diversity in members’ preferences and constraints (as discussed above), in the context of a local community, members are likely to share common preferences and constraints, which—when aggregated—yield biases, especially taxonomic biases, in the database of observation.

Another concern that is pertinent when considering biases in both CS and collective intelligence projects is participants’ uneven activity patterns. Prior studies have demonstrated that activity distributions within cyber CS projects—and more broadly, in online communities (e.g., open-source software development, Wikipedia)—approximate a power law distribution, whereby the vast majority of peripheral participants contribute only few observations and few highly-active core community members are responsible for a large portion of observations [ 99 , 151 – 153 ]. Presumably, this may further increase the likelihood of bias. When the few highly-active participants, especially in a local CS project, share the same preferences, the aggregate database may suffer from biases, despite diversity in the attitudes and preferences of other, less active community members. To sum, we make a fundamental distinction between local CS communities and global environmental monitoring platforms, arguing that aggregate database of observations that are generated by local communities of observers are more likely to be biased.

Practical implications

Findings from our study have important implications for the practice of CS, beyond the contributions to the scholarly literature that were discussed above. We offer some directions for enhancing the quality of CS data, to be used as a standalone source of biodiversity data, or alternatively as a data source that complements data generated through the use of systematic monitoring protocols [ 154 ].

In particular, we point to two key practical implications: the first pertains to the governance of the project and to procedures intended to reduce biases, whereas the second concerns the possibility of statistically adjusting for biases in the citizen-reported data. Is there a way for project leaders and custodians to guide the monitoring process, such that the aggregated data is less biased? Possibly, volunteers could be instructed to follow systematic monitoring protocols, but this would require special training, may have detrimental effects on volunteers’ motivation and commitment, and essentially go against the fundamental tenets of opportunistic CS projects such as iNaturalist. Nonetheless, they may be some ways to softly “nudge” volunteer observers, in an attempt to influence their reporting decisions and reduce biases [ 79 ], for example, by recommending that they monitor less visited areas. Biases could possibly be moderated by explicitly asking observers to vary their observations in terms of location, time, and species, recommending that observations be performed across the entire region, across seasons, and times of day, and for all species. In addition, project leaders could organize observation events (e.g. bio-blitzes) to target less recorded species, regions, and times (e.g., nighty events).

An alternative strategy to manipulating the community as a whole, which leverages the personal differences that were identified in this study, is to try and control for the composition of the observer community, for example, by intentionally inviting volunteers that specialize in various species (e.g., some with a special interest in birds, others with an interest in reptiles, etc.), such that in aggregate, all species are covered. Another way of reducing biases is curbing constraints that are associated with the reporting tools, e.g., solving technical problems with the mobile app or encouraging volunteers to use professional photography equipment. We recommend that providing such directions to volunteer observers should be practiced with extra caution, as posing restrictions on the monitoring process could have detrimental effects on their motivation and engagement [ 31 , 67 , 129 ]. Hence, in light of the personal differences in observers’ motivation, preferences, and behaviors, it may be most useful to allow for multiple forms of engagement [ 145 ]. In other words, it may be useful for the level of guidance to be personalized (e.g., some may prefer more guidance and structure regarding what to record, whereas others may prefer the autonomy to follow their interests).

A second implication involves the attempts to develop statistical methods that would (partially) correct for biases in biodiversity databases produced using opportunistic monitoring procedures. Researchers in the field are concerned that datasets gathered through citizen-science methods often do not accurately represent species’ distribution over space and time, and thus may induce errors in models attempting to predict species distribution or abundance patterns [ 11 , 12 , 74 , 90 ]. In particular, the likelihood of recording a species within a region is a function of sampling bias, imperfect detection [ 85 ], and observers’ decisions regarding what to report [ 12 ]. For example, Bird et al. [ 155 ] demonstrated that not accounting for detection probability resulted in a dramatic underestimate of species abundance and occurrence. In recognition of these issues, scholars have called for statistically controlling for observer-based biases [ 76 , 155 – 157 ]. Developing validated methods for correcting sampling bias for citizen-generated data is an active area of research in the species distribution modeling field (e.g. [ 158 ]).

In light of our findings regarding the variance in observers’ preferences the development of bias-correction methods which account for individual-level biases could be beneficial. However, simple approaches, e.g., controlling for the effects associated with observers’ skills and location/time preferences through standardization, may not suffice to eliminate the heterogeneity, as there are other variables that influence species detectability and recordability , for example, the effort (or time) spent in each monitoring excursion [ 159 ]. Another useful approach may be to cluster observers based on their prototypical psychological and behavioral patterns, along the lines of the approach suggested in other studies [ 78 , 109 ], and to adjust the bias-correction method per clusters of observers. Over the past decade, there have been preliminary attempts to develop statistical methods for correcting biases in data gathered through opportunistic monitoring [ 84 , 85 , 160 ]. Although these approaches provide a sound starting point to tackle observer-based biases, none of these methods has considered the factors that affect the likelihood of reporting an observation once it has been detected. We propose that complementing these types of statistical methods with data collected regarding volunteers’ preferences and attitudes (e.g., using a questionnaire or advanced empirical methods, such as virtual reality simulations) could provide a potential remedy. Just as semistructured monitoring projects, such as eBird, gather metadata about the observation process (e.g., start and end times), collecting information about preferences and attitudes can be utilized to generate a biodiversity archive that serves scientific purposes [ 81 , 161 ]. Although this would entail extra effort and would require engaging with the community of volunteer observers, we believe that the potential value of such a hybrid approach—i.e., making the vast amounts of citizen-science biodiversity data suitable for scientific research and policy making—outweighs the disadvantages.

Limitations and suggestions for future research directions

Conclusions drawn from this study should be considered in light of several limitations. First, we investigated one particular case of a nature-monitoring project (Tatzpiteva) on a specific CS platform (iNaturalist). Granted, iNaturalist is probably the largest platform of its kind and Tatzpiteva is a very large project on that platform (the largest in Israel, representing roughly 50% of the national records on the iNaturalist platform); nevertheless, some of the distinct features of our setting may have influenced our findings. For instance, design choices of the iNaturalist platform (specifically: the requirement to upload photos, which constrains observer behavior, as discussed above), as well properties of the project and of the community: Tatzpiteva is general in its purpose, recording all species within a region, and the observers form a tightly-knit local community, rooted within the geographical, societal, cultural context of Israel with its own unique characteristics. When attempting to generalize findings to different citizen science platform, one should consider the project’s socio-technical setting, including platform design and the character of the community. Although the factors underlying observers’ reporting decisions that were identified in this study are likely to be found in other settings, the relative salience of these factors may differ between CS platforms, projects, and cultural settings. For example, observers’ tendency to record observations close to their home is particularly prominent for citizen scientists that reside in rural areas where nature is just outside the door, but is likely to be less salient in urban projects. Hence, we call for future research to investigate observer-based biases in alternative settings.

Second, although the multimethod case-study approach that we employed provided a rounded and comprehensive view of CS practices, the number of participants was not large; it may possible to expand the scope and dive somewhat deeper using a particular method (e.g., including more interviews). Furthermore, although we triangulated our data collection using more than a single method, much of our findings are based on observers’ self-reports, and these may not fully reflect observers’ actual decision-making processes [ 162 ]. Indeed, we found that participants were not entirely consistent in their responses to the various questions. For instance, some participants stated that they report everything that they detect, yet also indicated that a consideration for recording their observations is a personal interest in the species (e.g., [pr4]). There is a need for future research that would explore the linkage between observers’ decision-making processes, their actual reporting behavior, and the consequential biases in the aggregate data. For example, future research could conduct a large-scale empirical study to statistically analyze the extent to which various observer considerations predict their reporting patterns, attempting to assign weights to these various biasing factors [ 110 ]. An additional interesting avenue for future research is to investigate the motivational processes underlying observers’ considerations. Prior research on the motivation for participation in CS projects [ 67 , 163 ] has employed generic frameworks such as Self Determination Theory [ 164 ] or the model for collective action [ 165 ]. We suggest that future research move beyond these generic conceptualizations to study the specific motivational factors that are directly linked to observer-based biases. A deeper understanding of the motivational dynamics underlying observers’ behavior could yield insights that may be relevant for mitigating the biases.

Additionally, our study investigated observer-based biases within a local community of nature observers, studying the biases of those who have selected to participate . Additional biases may stem from the socioeconomic factors that shape the demographics of citizen scientists, i.e., participation bias [ 12 ]. For example, people’s demographic background greatly influences the way in which they navigate space [ 166 , 167 ]. To empirically study participation bias, future research is encouraged to expand the analysis of observers’ preferences and constraints to other cultures and geographies. Finally, notwithstanding the value of the “use-agnostic” approach [ 63 , 168 ] that we have adopted in the current study, we encourage future research to dig deeper into the possible uses of citizen science data and consider the extent to which observer-based biases impact specific ecological research questions, such as species’ richness, temporal distribution and population sizes.

We also call for future research that would delve deeper into biases that stem from the project’s design. Namely, data quality in CS projects is influenced not only by observer-based biases; importantly, project sponsors goals and design choices can also have significant effects on data collection, and eventually, on the quality of the data. Specifically, a “fitness for use” approach, which is often adopted means that project sponsors might design protocols to meet specific research goals, potentially neglecting broader biodiversity aspects. For example, a project focused on bird species may not gather adequate data on insects or plants [ 169 ], whether because of focus of guidance and instructions, or due to prioritizing resource allocation towards certain goals. This may seem like a non-issue at first glance. After all, project is designed to achieve certain goals, it seems only natural that it will be designed accordingly. However, as Follett and Strezov [ 170 ] have pointed out, there is a growing number of studies which rely on the re-use of collected datasets from past citizen science research projects. Uses might not necessarily be fully known at the time a project is designed and launched, and may change over time (consider, e.g., Pharr, Cooper [ 62 ], where data from a CS project is combined with US government light and noise data to answer questions not considered when the original CS project was designed). In that context, a “use agnostic” perspective [ 63 , 64 ] can be useful for considering issues of data quality.

Similarly, another source of potential bias is bias induced by the platform design. In particular, iNaturalist employs specific work processes that stem from its evidence-based opportunistic monitoring approach. One of the key factors that emerged in our data as affecting observers’ monitoring decisions is recordability –the ability to take a picture or record a video. While photographic evidence is useful for enabling verification, and is obviously helpful in species identification, mandating photographic evidence also introduces systemic bias, driven by platform design rather than by observers’ preferences. In this case, a bias against species that are smaller, nocturnal, and/or more agile and difficult to capture in a photo. Hence, we encourage future research to investigate the way in which project and platform design choices shape observers’ decisions, and consequently biases in the co-created archive of reported observations.

As the world’s ecosystems are undergoing rapid and significant changes, characterized by a continuous decline in biodiversity and in the abundance of insects, birds, and mammals [ 171 , 172 ], scientists must be able to detect changes and identify warning signs much quicker, in order to develop and aim productive timely conservation activities. However, several factors limit the ability of traditional scientific monitoring methods to detect ecological changes, as they rely on systematic protocols and professionally trained observers, and are costly and difficult to scale [ 11 , 12 , 110 ]. As a consequence, long-term and wide-scale monitoring initiatives are often limited to very few sampling sites within limited regions and to particular times; however, the attempt to generalize from these limited findings to different places and times is problematic. Furthermore, given the budget constraints and scientists’ focus on particular species, most of a region’s species are not monitored systematically, limiting ecologists’ ability to consider interspecies interactions and thus making it difficult to assess long-term trends in the ecological system.

Citizen science, and specifically unstructured CS, has the potential to become an important approach for biodiversity monitoring, which will overcome the limitations of traditional monitoring methods. Prior research has described observer-based biases in CS data [ 11 , 12 , 173 – 175 ], but less attention has been given to how these biases arise as a result of both social and ecological variables. A major impediment for employing unstructured CS data is that it reflects both the ecological reality at a given time and place and observers’ preferences and choices [ 12 ]. Without decoupling the two, it would be impossible to determine the state of nature [ 11 ].

We studied a local community of nature observers, which operates a project ( Tatzpiteva , in Israel) using a global collective intelligence platform, iNaturalist. Community members monitor, record, and share geo-and time-tagged images of plants and animals. This project affords observers very high levels of autonomy, allowing them to report on any species they choose, at any place or time, providing limited guidance and direction. Hence, such a setting was likely to reveal a broad range of biases. We collected data through observations, questionnaires, interviews, and archival textual material. Our findings identified four key factors that influence an observer’s decisions about what, when, and where to observe, as well as which specimens to report once detected: recordability , community value , personal preferences , and convenience . Examining these factors, we demonstrated that local nature observers within a community share common considerations when determining their observations and reporting choices. Thus, we add to the literature on CS, and specifically to our understanding of data-quality issues in ecological monitoring by citizen scientists [ 11 , 12 , 34 , 36 , 40 , 41 , 68 – 70 ]. We make a broader contribution to the scholarly discourse on biases in collective intelligence systems [ 17 , 18 , 176 – 180 ] by showing that, at least in the context of our study, individuals’ reports tend to demonstrate a trend in a particular direction, such that some biases are not cancelled out but rather are amplified, naturally leading to inaccuracies in the collective intelligence system.

Our findings regarding the potential for taxonomic biases in the aggregate database of observations call into question the use of unstructured CS data for determining species’ spatiotemporal distribution (e.g., estimating populations sizes). According to Arazy and Malkinson [ 11 ], the key for decoupling the ecological process from observers’ decision-making process is to elucidate the probability for a specific observer to report on a particular species once encountered. Hence, such a framework is both person- and species-specific. Findings from our study lend support to this approach, as they highlight the intricate array of personal considerations underlying an observer’s decision to report a particular species. For such an approach to become practical, future research in two primary directions is warranted. First, it is necessary to develop methods for estimating the probability of an observer-species reporting preference. This may be possible using traditional behavioral research approaches, e.g., a questionnaire [ 11 ], or by employing more advanced methods, such as nature immersed Virtual Reality simulations [ 181 , 182 ]. Either newly developed statistical measures (or proxies) or existing comparative statistical analysis could be used to determine the likelihood of reporting once a species is observed. Another potential avenue for future research is to develop novel statistical methods that would take the abovementioned probability as an input and produce estimates for the state of nature, specifically regarding species’ spatiotemporal distribution.

To conclude, CS has great societal benefits in linking people to nature, resulting in a strengthened sense of community, belonging, and caring for the local environment [ 183 – 185 ], as well as greater personal agency [ 186 ], environmental advocacy, and activism [ 187 – 189 ]. Beyond the societal benefits, we believe that it is possible to utilize the vast amounts of biodiversity data gathered using online platforms such as iNaturalist for assessing the state of nature. We hope that this study will encourage future research on observers’ psychology and behavior, facilitating the development of statistical methods that correct for observer-based biases in unstructured CS data, so as to facilitate scientists’ efforts to track trends in the world’s biodiversity. Enhancing our ability to detect trends in species populations can help us to promptly design, tailor, and execute informed interventions that are much needed to protect and sustain the environment.

Supporting information

S1 appendix. questionnaire..

https://doi.org/10.1371/journal.pone.0308552.s001

S2 Appendix. Interview protocol.

https://doi.org/10.1371/journal.pone.0308552.s002

S3 Appendix. Code book.

https://doi.org/10.1371/journal.pone.0308552.s003

https://doi.org/10.1371/journal.pone.0308552.s004

Acknowledgments

We thank the anonymous reviewers for insightful comments that helped us improve this paper. We thank members of the Tatzpiteva community, and in particular the community leader, Ariel Shamir, for their efforts in recording biodiversity and working to conserve nature, as well as for their contribution to this study. We commemorate Arie Ohad, one of the founders of the community and an active member, who has passed away recently.

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Ethnography | A Deep Dive into Media Audiences & Consumption

• May 31, 2024 August 25, 2024

Ethnography is a qualitative research method rooted in anthropology. Researchers immerse themselves in the daily lives of the subjects they study. This method is crucial in Media and Communications because it allows researchers to understand how people interact with media in their everyday contexts. Ethnography provides deep insights into the cultural, social, and individual dimensions of media use. These are often overlooked by quantitative research methods.

Historical Background of Ethnography

Ethnography has its origins in anthropology, particularly in the works of early anthropologists like Bronisław Malinowski and Margaret Mead. Malinowski’s study of the Trobriand Islanders and Mead’s work in Samoa are classic examples of ethnographic research. These researchers spent extended periods living with the communities they studied, learning their languages, and participating in their daily routines. This immersive approach allowed them to understand the cultures they studied from an insider’s perspective; a concept known as “emic” understanding.

In Media and Communications, Ethnography began to gain prominence in the 1970s and 1980s. Researchers realised that to truly understand how people use and interpret media, it was essential to observe them in their natural settings. This shift marked the beginning of “Audience Ethnography”. Scholars focused on how audiences engage with media in their everyday lives (Hammersley & Atkinson, 2019).

The Ethnographic Method

Ethnography is a flexible and adaptive research method. The process usually begins with the researcher selecting a specific group or community to study. This could be anything from a small village to an online community. The researcher then spends a significant amount of time observing and participating in the daily activities of this group. This participation is key; the researcher must become a part of the community to gain a true understanding of it.

Participant Observation

Participant observation is the core of ethnographic research. It involves the researcher taking part in the daily activities of the group they are studying while also observing and recording these activities. The dual role of participant and observer can be challenging. The researcher must balance involvement with the community and the objective observation needed to analyse their behaviours critically.

For example, a media ethnographer might spend time with a family in their home to understand how they consume television. The researcher would not only observe which programmes the family watches but also participate in discussions about the shows. Therefore, observe how family members interact during viewing, and note how television fits into their broader daily routines (Morley, 1986).

Field Notes & Reflexivity

Field notes are the primary data collection tool in Ethnography. These notes are detailed descriptions of observations, interactions, and thoughts that the researcher records during and after their time in the field. It is essential to write these notes as soon as possible to capture the details while they are still fresh in the researcher’s mind.

Reflexivity is also a critical component of Ethnography. Reflexivity means that the researcher must constantly reflect on their role in the research process and how their presence might influence the group they are studying. For instance, a researcher might notice that people behave differently when they know they are being observed. Acknowledging and accounting for these changes is part of the ethnographic process (Hammersley & Atkinson, 2019).

In-Depth Interviews

In-depth interviews complement participant observation. These interviews allow the researcher to explore specific topics in more detail. Thus, gaining insights into the participants’ perspectives, feelings, and interpretations. The interviews are typically semi-structured, with the researcher preparing a list of topics or questions to cover but allowing the conversation to flow naturally.

For example, in an ethnographic study of social media use, the researcher might interview participants about their motivations for using specific platforms, their experiences of online interactions, and how these activities impact their offline lives. These interviews can reveal deeper layers of meaning that are not always visible through observation alone.

Applications of Ethnography in Media & Communications

Researchers have applied Ethnography in various ways in Media and Communications research. This method offers a unique lens for exploring how media integrates into people’s lives, shapes identities, and influences social relations.

Audience Studies

One of the primary areas where Ethnography has been applied is in audience studies. Traditional media research often relied on surveys and ratings to understand audiences. However, these methods could not capture the complex ways in which people engage with media. Ethnography filled this gap by providing a more nuanced understanding of audience behaviour.

For instance, David Morley’s study “The Nationwide Audience” (1980) is a seminal work in this field. Morley conducted ethnographic research on how different social groups interpreted the same television programme. His findings revealed that people from different social backgrounds interpreted media content in varied ways, shaped by their cultural and social contexts. This study highlighted the importance of considering the audience’s socio-cultural background in media analysis.

Media Production

Ethnography is also valuable in studying media production. By observing and participating in the processes of media creation, researchers can gain insights into the decision-making processes, power dynamics, and cultural influences that shape media content.

For example, an ethnographer might study a newsroom to understand how journalists select and frame news stories. By attending editorial meetings and accompanying journalists in the field, the researcher can observe how they negotiate news values and how external pressures, such as political or commercial interests, influence the final product. This approach reveals the complexities and challenges of producing media in a real-world context.

Digital Ethnography

With the rise of digital media, Ethnography has adapted to study online communities and digital interactions. Digital Ethnography, also known as Netnography, involves studying communities that exist in online spaces, such as social media platforms, forums, or virtual worlds.

For instance, researchers might study how fan communities organise online, create and share content, and develop their cultural norms and practices. By immersing themselves in these online environments, ethnographers can understand how digital media facilitates new forms of social interaction and identity construction.

A notable example is the work of Christine Hine. She conducted ethnographic research on the use of the internet in everyday life. Hine’s work highlighted how the internet is not just a tool for communication but a cultural space where people live out significant parts of their lives (Hine, 2000).

Challenges of Ethnographic Research

While Ethnography offers many benefits, it also presents several challenges that researchers must navigate. These challenges include ethical considerations, time commitment, and the subjective nature of the research.

Ethical Considerations

Ethnographic research often involves close interaction with participants, which raises several ethical issues. Researchers must obtain informed consent from their participants. This approach ensures that participants understand the nature of the research and how researchers will use their data. In some cases, obtaining consent can become complicated, especially in contexts where people might not fully grasp the implications of the research.

Moreover, ethnographers must be mindful of privacy and confidentiality. Since ethnographic research often involves detailed observations of people’s lives, there is a risk of exposing sensitive information. Researchers must take care to anonymise their data and consider how their findings might impact the communities they study.

Time Commitment

Ethnography is a time-intensive research method. It requires researchers to spend extended periods in the field, often months or even years. This time commitment can be challenging, especially for researchers working under time constraints or with limited resources.

The long duration of ethnographic research also means that it is often difficult to cover large populations. Instead, Ethnography typically focuses on small, specific groups, which can limit the generalisability of the findings. However, the depth of understanding gained from Ethnography often outweighs this limitation.

Subjectivity & Reflexivity

Ethnography is inherently subjective. The researcher’s background, beliefs, and experiences can influence their observations and interpretations. This subjectivity is not necessarily a weakness, but it does require the researcher to be constantly reflexive. Reflexivity involves critically examining one’s role in the research process and acknowledging how personal biases might affect the findings.

For example, a researcher studying a community with very different cultural norms from their own might unintentionally interpret behaviours through the lens of their cultural background. Being reflexive means recognising these biases and striving to understand the community’s practices from their perspective.

The Value of Ethnography in Media & Communications

Despite its challenges, Ethnography remains a valuable method in Media and Communications research. It offers unique insights that are difficult to obtain through other research methods. By immersing themselves in the contexts they study, ethnographers can uncover the rich, complex ways in which media influences people’s lives.

Richness of Data

One of the main strengths of Ethnography is the richness of the data it produces. Unlike surveys or experiments, which often reduce social phenomena to numbers and variables, Ethnography captures the complexities and nuances of human behaviour. This richness allows researchers to develop a deep understanding of their subjects. Thus, providing insights that can lead to more effective and culturally sensitive media practices.

Grounded Theory Development

Ethnography often leads to the development of grounded theory. Grounded theory is an inductive approach where theories emerge from the data rather than being imposed from the outset. This approach is particularly useful in Media and Communications, where rapidly changing technologies and cultural practices often outpace existing theories.

For example, an ethnographic study of how people use mobile phones in a particular community might reveal new patterns of behaviour that challenge existing theories of media consumption. By allowing theories to emerge from the data, Ethnography can contribute to the development of more accurate and relevant models of media use.

Influence on Policy & Practice

Ethnographic research can also have a significant impact on policy and practice. By providing a detailed understanding of how people engage with media, Ethnography can inform the design of media content, platforms, and policies that are more aligned with users’ needs and cultural contexts.

For instance, an ethnographic study of children’s television viewing habits might reveal that certain programmes reinforce gender stereotypes. These findings could then be used to advocate for more inclusive and diverse content that better reflects the realities of children’s lives.

Ethnography is a powerful tool in Media and Communications research. It allows researchers to gain a deep, nuanced understanding of how media is embedded in the social and cultural contexts of people’s lives. While it presents challenges, such as ethical considerations and the time-intensive nature of the research, the insights gained through ethnography are invaluable. By immersing themselves in the worlds they study, ethnographers can uncover the rich, complex ways in which media shapes and is shaped by human behaviour.

In a rapidly changing media landscape, where new technologies and platforms are constantly emerging, Ethnography remains a vital method for exploring the cultural and social dimensions of media use. As Media and Communications continue to evolve, ethnographic research will undoubtedly play a crucial role in helping us understand the intricate relationships between media, culture, and society.

Hammersley, M. and Atkinson, P. (2019) Ethnography: Principles in Practice . 4th edn. London: Routledge.

Hine, C. (2000) Virtual Ethnography . London: SAGE Publications.

Morley, D. (1980) The Nationwide Audience: Structure and Decoding . London: BFI.

Morley, D. (1986) Family Television: Cultural Power and Domestic Leisure . London: Routledge.

Home » Education » Difference Between Case Study and Ethnography

Difference Between Case Study and Ethnography

Main difference – case study vs ethnography.

Case studies and ethnographies are two popular detailed, qualitative studies used in the field of social science . Although there are certain similarities between these two methods such as their holistic nature, and the extended time period, there are also some differences between the two. The main difference between case study and ethnography is their focus; ethnography aims to explore cultural phenomenon whereas case studies aim to describe the nature of phenomena through a detailed investigation of individual cases.

What is a Case Study

A case study is a detailed investigation of a single event, situation or an individual in order to explore and unearth complex issues. Yin (1984) defines case study as “an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used.” Although case studies are always associated with qualitative research, they can also be quantitative in nature. They are often used to explore community-based issued such as poverty, illiteracy, unemployment, prostitution, and drug addiction.

A successful case study is context-sensitive, holistic, systematic, layered and comprehensive. The process of a case study involves,

• Identifying and defining the research questions
• Selecting the cases and deciding techniques for data collection and analysis
• Collecting data in the field
• Evaluating and analysing the data
• Preparing the report

Data collection methods in a case study may involve interviews, observations, questionnaires, checklists, analysis of recorded data and opinionnaires. Case studies can also be divided into different categories. Exploratory, descriptive and explanatory case studies are three such categories.

Case studies are preferred by many researchers in the field of social sciences since they offer detailed and in-depth information about a particular phenomenon. However, it is difficult to use the data obtained from a case study to form generalisation since it only focuses on a single event or phenomenon.

Figure 1: Questionnaires are one method of data collection in a case study.

What is an Ethnography

Ethnography is a detailed and in-depth study of everyday life and practice. In other words, it is the systematic study of people and cultures. A researcher who is engaged in ethnography is known as an ethnographer . Ethnographers explore and study culture from an insider’s point of view (emic perspective).

Ethnography traditionally involved focusing on a bounded and a definable race, ethnicity or group of people; for example, study of a particular African tribe. However, modern ethnography also focus on different aspects of the contemporary social life.

Ethnographic research mainly involves field observations, i.e., observations of behaviour in a natural setting. The researchers have to spend a considerable amount of time inside a community in order to make such observations. Information about particular socio-cultural phenomena in a community is typically obtained from the members of that particular community. Participant observation and interviews are two of the main data collection methods in this type of studies. Ethnographic studies take a longer period of time than other types of research since it takes long-term involvement and observation to understand the attitudes, beliefs, and behaviours of a community.

Figure 2: Observation and participant interviews are main data collection methods in ethnography.

Definition 

Case Study: A case study is a detailed investigation of a single event, situation or an individual in order to explore and unearth complex issues.

Ethnography: An ethnography is the detailed and systematic study of people and cultures.

Case Study: Case studies focus on a single event, incident or individual.

Ethnography: Ethnography observes cultural phenomenon.

Case study: Case study intends to uncover the tacit knowledge of culture participants.

Ethnography: Ethnography aims to describe the nature of phenomena through detailed investigations of individual cases.

Data Collection Methods

Case Study: Case studies may use interviews, observations, questionnaires, checklists, analysis of recorded data and opinionnaires.

Ethnography: Ethnographic studies use participant observations and interviews.

Special Requirements

Case Study: The researcher does not have to live in a particular community.

Ethnography: The researcher has to spend a considerable amount time inside that particular community.

Conclusion 

Case study and ethnography may have some similarities; however, there is a considerable difference between case study and ethnography as explained above. The main difference between case study and ethnography lies in their intent and focus; case studies intend to uncover the tacit knowledge of culture participants whereas ethnographic studies intend to describe the nature of phenomena through detailed investigations of individual cases. There are also differences between them in terms of data collection and analyis. 

• Cohen, Arie. “Ethnography and case study: a comparative analysis.”  Academic Exchange Quarterly  7.3 (2003): 283-288.
• Yin, Robert. “Case study research. Beverly Hills.” (1984).

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• Volume 8, Issue 1
• Children’s cognition and attitudes during long-term cancer treatment: an ethnographic study
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• http://orcid.org/0000-0003-1512-5829 Ryoko Michinobu 1 , 2 ,
• http://orcid.org/0000-0002-0288-7990 Masaki Yamamoto 2 ,
• Keita Igarashi 2 , 3 ,
• Yoshiyuki Sakai 4 ,
• http://orcid.org/0000-0001-8090-8235 Yusuke Akane 2 ,
• Dai Yamamoto 5 ,
• http://orcid.org/0000-0002-9660-1833 Akira Takebayashi 2 ,
• Takahiro Mikami 6 ,
• Hiroyuki Tsutsumi 2 , 7 ,
• http://orcid.org/0000-0001-7226-3000 Takeshi Tsugawa 2
• 1 School of Nursing and Social Welfare Sciences , Fukui Prefectural University , Fukui , Japan
• 2 Department of Pediatrics , Sapporo Medical University School of Medicine , Sapporo , Japan
• 3 Department of Pediatric Hematology/Oncology , Hokkaido Medical Center for Child Health and Rehabilitation , Sapporo , Japan
• 4 Department of Pediatrics , Hakodate Municipal Hospital , Hakodate , Japan
• 5 Department of Pediatrics , Kushiro City General Hospital , Kushiro , Japan
• 6 Division of Pediatrics , Sapporo Medical University Hospital , Sapporo , Japan
• 7 Midorinosato , Saiseikai Otaru Hospital , Otaru , Japan
• Correspondence to Professor Ryoko Michinobu; michinor{at}fpu.ac.jp

Background Cancer treatment for children is typically long-term and difficult, and the experience is unique for each child. When designing child-centred care, individuals’ values and preferences are considered equally important as the clinical evidence; therefore, understanding children’s thoughts and attitudes while they receive long-term treatment could offer valuable insights for better clinical practice.

Methods We conducted long-term consecutive participatory observations and interviews with seven children, who were hospitalised and receiving cancer treatment for the first time. The daily observational data on those children’s discourses, behaviours and interactions with health professionals were systematically collected and thematically examined. The analysis was expanded to explore significant narratives for each child to capture their narrative sequence over time.

Results The initial analysis identified 685 narrative indexes for all observation data, which were categorised into 21 sub-codes. Those sub-codes were assembled into five main themes by thematic analysis: making promises with health professionals, learning about the treatment procedures through participation, taking care of oneself, increasing the range of activities one can perform and living an ordinary life.

Conclusion We observed a forward-looking attitude toward understanding cancer, accepting treatment and looking forward to the future among children undergoing in-hospital cancer treatment. In addition, the children developed cognitively, affectively and relationally throughout cancer treatment processes. These findings have implications for better clinical practice in child-centred care, including children’s participation in shared decision-making in paediatric oncology.

• Qualitative research
• Anthropology

Data availability statement

Data are available upon reasonable request. The data supporting this study’s findings that do not compromise the participants’ privacy are available upon reasonable request from the corresponding author, RM ([email protected]). All such data are in Japanese. Because the study investigated a small number of patients over a long period at one medical institution, some of the supporting data are not available in a public repository owing to ethical reasons, the legal protection of participants’ personal information, and the need to ensure participants’ privacy. These data include details of physical conditions, medical records and observational records that contain information about the patients’ personal circumstances.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjpo-2023-002405

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Consideration of children’s values and preferences is an important factor in decision-making in paediatric oncology, however, its inclusion remains insufficient. This may partly reflect a lack of understanding of children’s thoughts and attitudes in the ward.

WHAT THIS STUDY ADDS

This longitudinal observational study in a paediatric cancer ward clarified that children developed forward-looking thoughts and attitudes through supportive interactions with health professionals and others in the ward.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The development of strong relationships between children and individuals who support their emotional and social development would improve the clinical practice of child-centred care, including the addition of children’s participation in shared decision-making in paediatric oncology.

Introduction

In paediatric oncology, paediatricians have recently emphasised the need to consider the values and preferences of children and their families in selecting treatment options. 1–3 Social norms are changing to include the perspectives of children in all aspects of life, a change reflected in clinical policies and practices, which are now beginning to proactively include child patients. 4 Paediatricians must openly share information about cancer diagnoses with children and their families in consultation, although this may be challenging in various cultural and social contexts. Despite these cultural constraints, children can better participate in decision-making and collaborate with paediatricians about their own care, which is the most important aspect of child-centred care. 3 5 6

Currently, more research is needed on patient participation to identify optimal procedures and the effects of collaboration. 7–9 Theoretically, child-centred care is developed specifically for paediatric patients, facilitating tailored care and support to fulfil the child’s best interests. 5 However, the research-based evidence for children’s participation is sparse. 10 Most of the literature on children’s experiences is based on reports by caregivers, healthcare professionals, and adolescent patients or survivors, not on reports by the children themselves. 6 11–18 Most relevant research comprises cross-sectional studies using one-time interviews or surveys, and therefore fails to capture the children’s history. 10

Therefore, we designed this long-term participatory observational study to examine children’s emotions, thoughts and actions—and changes in them over time—during hospitalisation for cancer treatment. The longitudinal design allowed us to consider how, in each child’s case, particular values and preferences emerged and developed during an extended hospitalisation. The findings could have valuable implications for better informed clinical practice in paediatric oncology.

Principal investigator

The principal investigator (PI) is a trained specialist in medical anthropology and public health. The PI has over 20 years of research experience in social science and medicine, including 9 years in paediatric oncology.

Research design and data collection

We designed a long-term, participatory observational study to examine children’s perceptions and actions toward cancer treatment over time. This study occurred in the context of long-term hospitalised treatment in a paediatric ward at Sapporo Medical University Hospital, Sapporo, Japan. The university hospital paediatric ward provides medical care for children with various health problems. The data were collected over 141 days between January 2016 and March 2018.

Patient and public involvement

Before starting the research, we conducted a month-long pilot study and established relationships with potential participants. We carefully developed the research question and protocol to include the insights of children undergoing cancer therapy and their parents. The coinvestigators were the children’s primary physicians (MY, KI, YS, YA, DY, AT) and chief nurse (TM), and so were familiar to the children. The children first became acquainted with the PI during the pilot phase. The PI was a hospital volunteer to the children and informed them that she wished to talk and play with them.

In the full study, the PI observed the children four to five times monthly, from morning until evening. The PI also carefully observed how, during morning and evening examinations and treatments, health professionals tell children about treatment procedures and encourage them to participate or show their willingness to participate. The PI frequently conversed with children and their caregivers, following an interactional guideline developed in the research protocol and tested in the pilot study. The PI observed children in a natural setting in the absence of children not involved in this study.

The participating children comprised five boys and two girls hospitalised for haematological cancer treatment at the first onset of the disease. Their ages ranged from 5 years and 2 months to 10 years and 2 months (median: 8 years and 8 months). The study period for each child lasted from 111 to 230 days, and their total participation ranged from 20 to 28 days.

One of the primary physicians (MY) selected potential participants following the criteria in the research protocol. MY explained the study aims and goals to the children and parents, who provided informed assent and consent, respectively. No one declined to participate or withdrew from the study.

The PI took a field note for each observation and later wrote a clean copy to be sent to the coinvestigators. The primary physicians ensured the physical state of the participating children on the day of the observation and permitted the PI to conduct observations each time.

Narrative analysis

We analysed a large amount of data on observed narratives and children’s discourse, using a qualitative analysis that combined classic thematic narrative analysis, 19 which is widely used in clinical and healthcare research, 19 20 and longitudinal narrative analysis. 21 The PI read and re-read the observational records during the initial analysis process, identified meaningful narratives that revealed recurrent patterns of children’s actions and discourse, and extracted the narrative segments by indexing. The narrative segments conveying the emotions and viewpoints of the children were also indexed.

Collecting data through extensive engagement with the children, the PI memoed, indexed and coded all the text from the observations and informal dialogues. The coinvestigators read the text and coded results using a reflexive approach, questioning each finding and considering alternative interpretations. Instead of a formal member check, direct responses from the participating children and their caregivers were obtained promptly in situ.

The analysis proceeded by obtaining an overall sense of the meaning of each day’s record and comparing and contrasting the parts of each account in relation to the whole set of records. 20 We continued this process until we arrived at holistic understandings or identified overarching themes encompassing the meanings of the parts. The analysis required close scrutiny of the social context of daily actions and discourses and a deep focus on each account individually and in relation to other accounts, rather than simply indexing and counting the narrative codes. 20

The PI then carefully examined the meanings of the indexed narratives, sorted related ones into a sub-code, and finally assembled related sub-codes into a larger inclusive theme. Next, the PI arranged the indexed narratives chronologically for each individual to comprehend the entire history of the children’s treatment experiences and examine their longitudinal development. This secondary analysis was based on a theoretical assumption that narratives have reasons for how and when they emerge. 21 This approach thus captured the unique history of each patient thematically.

This longitudinal narrative analysis gave investigators valuable insight into theoretically comprehending and arranging the sequence of sub-codes and inclusive themes. Accordingly, the observations and informal dialogues were carried out until the patients were discharged from the hospital, and new patients were added until theoretical data saturation. The prolonged engagement and dialogue with participating children throughout the study enabled researchers to clarify the meanings of children’s attitudes and actions from the children’s perspectives, a primary method of validating interpretation in an observational narrative study. 22 The final results emerged through extensive analytical discussions between the principal supervising coauthor (HT) and the PI, and were reviewed by all coinvestigators.

The observations in the ward from 2016 to 2018 yielded approximately 577 000 characters of data in Japanese. The initial analysis identified 685 narrative indexes for all observation data and categorised them into 21 sub-codes. The subsequent thematic analysis assembled the 21 sub-codes into five main themes. Longitudinal analysis of the appearance of corresponding narratives determined the order of these five main themes to approximate the following: making promises with health professionals, learning about the treatment procedures through participation, taking care of oneself, increasing the range of activities one can perform and living an ordinary life. Table 1 presents short narratives of individual children to illustrate the themes.

• View inline

Inclusive themes and illustrative narratives: children’s perspectives

Making promises with health professionals

The first theme comprised five sub-codes, which were represented in 98 indexed narratives: receive treatment while facing challenges, N=38; rely on physicians and parents, N=19; make promises and take responsible actions, N=17; share one’s mind by listening, speaking and getting an answer, N=14; develop one’s will for treatment through long-term relationships with health professionals, N=10.

During the first period of treatment, children listened to the procedures and made promises with health professionals rather passively, facing challenges and difficulties they had never faced. Through everyday promises and interactions in the ward, they gradually overcome the challenges and came to behave responsibly, and their cognitions and attitudes toward cancer care were transformed positively.

Learning about the treatment procedures through participation

The second theme comprised three sub-codes, represented in 80 indexed narratives: learn by oneself through repeating, reflecting and remembering, N=30; learn by hearing from physicians and asking questions, N=28; learn by participating and taking an active role in the treatment, N=22.

It is essential for children to be able to learn many things in the context of everyday relations, and to make promises with healthcare professionals. The children cultivated a positive attitude, learnt about treatment while becoming familiar with the hospital environment and demonstrated their growth over time.

Taking care of oneself

The third theme comprised four sub-codes, which were represented in 91 indexed narratives: take care of one’s body in awareness of one’s therapy and bodily conditions, N=33; take care of each other with one’s friends on the ward, N=27; take care of one’s body by notifying caregivers of one’s body status and changes, N=19; and relax to make oneself better, N=12.

Children in the ward had many bitter experiences during their long hospitalisation, particularly resulting from their cancer treatment. Such experiences enhanced their alertness to their body conditions. To receive care as necessary, they must be able to consciously relax without being overactive and inform their caregivers of any changes. The presence of their friends could help alleviate their suffering.

Increasing the range of activities one can perform

For this fourth theme, 115 indexed narratives were classified into five sub-codes: be able to receive treatment confidently, N=43; be able to carry out various activities on one’s own, N=24; be able to see goals and plan ahead, N=22; be able to live an ordinary life, N=16; and be able to do activities in supportive relationships, N=10.

When their health improved, the patients could think about and engage in what they could do in the ward. Their cancer treatment was not endured alone but was supported by many people, particularly during complex and challenging times. By improving their performance, they gained confidence and enjoyed their everyday life.

Living an ordinary life

Indexed narratives for the fifth and last theme were the most numerous at 301, and were categorised into four sub-codes: have a pleasant time with one’s friends, N=139; live naturally as one ordinarily does, N=75; see and live the treatment days as usual, N=58; and live an ordinary life with the support of surrounding people in the ward, N=29.

Children were nurtured by their parents, families and others, even in a hospital environment. These people helped to create a caring atmosphere similar to children’s home lives so that their time in the ward was as pleasant as possible. Their genuine desire for ordinary life could also be fulfilled through friendships and interactions with other children in the ward.

Longitudinal and thematic narrative analysis of ethnographic observational data on children undergoing inpatient cancer treatment revealed children’s emotions, thoughts and actions during their long-term hospitalisation. Through daily clinical encounters, the children trusted health professionals, made promises with them and accepted medical procedures. This development accompanied situational learning and taking responsibility for their body and health. Through receiving valid information and making promises with health professionals, children were able to face their treatment positively and with the hope of eventually leading a normal life again. As they gradually recovered their health and increased their range of activities, they partly regained their usual life, or foresaw the possibility of such a life. Our most significant finding was that daily interactions in the ward can generate cognitive, emotional and learning development in individual children.

A narrative review of the illness identity among children and youth with cancer revealed that their experience profoundly affected their identity formation both positively and negatively. 23 The reliable relationships with health professionals observed repeatedly in our study could be a positive influence on children’s identity formation. Similarly, a qualitative study on adolescents and young adults with cancer found that self-care or self-advocacy is essential for facing long-term illnesses. 17 Furthermore, self-management has emerged as an important theme among young childhood cancer survivors. 24 Our study also identified self-care actions among younger children after hospitalisation, indicating that such self-care begins at much younger ages and earlier in the treatment process than expected.

The present study illuminates the longitudinal processes of childhood cancer patients engaging in various activities and living their lives. They did not hope to be perceived differently or receive special treatment; rather, they valued living an ordinary life as at home. A substantial number of indexed narratives in our study attested to children’s wish for an ‘ordinary life’, indicating its essential value to paediatric cancer patients. A study on advance care planning among adolescents and young adults undergoing bone marrow transplants also showed the value placed on normal, everyday life with their families and friends at home. 16 Pursuing normality was also a common theme in a study of children with life-limiting conditions. 25

Child-centred care must be directed by these children’s perspectives, 25 however, many researchers have stressed the still-inadequate involvement of children in paediatric care. 26 27 Because of a research gap, the effects of shared decision-making has yet to be proven. 7–9 28 At present, a model to promote participatory decision-making reflects adults’ fixed views of the children’s interests without exploring their variety. 29 Paediatric medicine should promote patient participation while incorporating patients’ diverse views and opinions following their developmental maturation. 30

Our study necessarily reflects the culturally unique medical system in Japan, where long-term hospitalisation is the norm for paediatric cancer treatment. Patient–health professional relationships emerge from clinical communication in such a medical system. Research on the experiences of paediatric patients in other countries could inform a more complex and comprehensive argument about paediatric shared decision-making.

Participatory observational studies informed by the framework of anthropology value naturalistic observation and minimum interruption of people’s ordinary lives. Accordingly, rather than using multiple interviewers and data coders, we relied on the PI’s expertise in remembering material, writing, and analysing the text. This is a potential study limitation.

This long-term observational study of children undergoing cancer therapy clarified that the children created and maintained a forward-looking attitude toward understanding cancer, accepting treatment and looking forward to the future. Their positive cognitions and attitudes may have resulted from creating reliable relationships with health professionals. These findings have valuable implications for better clinical practice in child-centred care in paediatric oncology. The rich human relationships that are established in the paediatric ward should be enhanced further by understanding and respecting the development and expression of children’s feelings.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the Institutional Research Review Board of Sapporo Medical University Hospital on 16 November 2015 (approval number: 272-69). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

We thank Edanz ( https://jp.edanz.com/ac ) for editing drafts of this manuscript. The manuscript contents are solely the responsibility of the authors and do not necessarily represent the official views of Sapporo Medical University, Sapporo Medical University Hospital or any of the other funding agencies.

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Contributors All authors contributed to the project. RM and HT jointly conceived the study, and MY, KI, YS, YA, DY, AT, TM and TT contributed as coinvestigators. MY, KI, YS, YA, DY, AT, TM, HT and TT helped with the acquisition, analysis or interpretation of data for the work. RM drafted the manuscript, and HT, MY and TT critically revised it for scientific quality. KI, YS, YA, DY, AT and TM contributed to important intellectual content. HT, TT and MY supervised the study processes. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The author RM takes full responsibility for the content and serves as the guarantor for the work.

Funding This study was supported by JSPS Grant-in-Aids for Scientific Research (18K02487, 21K02409) and Sapporo Medical University Grants for Programmes Promoting Academic Advancements (1900048, 2000192 and 2100207).

Competing interests No competing interest.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

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