theory in empirical qualitative research

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Qualitative data analysis and the use of theory.

• Carol Grbich Carol Grbich Flinders University
• https://doi.org/10.1093/acrefore/9780190264093.013.554
• Published online: 23 May 2019

The role of theory in qualitative data analysis is continually shifting and offers researchers many choices. The dynamic and inclusive nature of qualitative research has encouraged the entry of a number of interested disciplines into the field. These discipline groups have introduced new theoretical practices that have influenced and diversified methodological approaches. To add to these, broader shifts in chronological theoretical orientations in qualitative research can be seen in the four waves of paradigmatic change; the first wave showed a developing concern with the limitations of researcher objectivity, and empirical observation of evidence based data, leading to the second wave with its focus on realities - mutually constructed by researcher and researched, participant subjectivity, and the remedying of societal inequalities and mal-distributed power. The third wave was prompted by the advent of Postmodernism and Post- structuralism with their emphasis on chaos, complexity, intertextuality and multiple realities; and most recently the fourth wave brought a focus on visual images, performance, both an active researcher and an interactive audience, and the crossing of the theoretical divide between social science and classical physics. The methods and methodological changes, which have evolved from these paradigm shifts, can be seen to have followed a similar pattern of change. The researcher now has multiple paradigms, co-methodologies, diverse methods and a variety of theoretical choices, to consider. This continuum of change has shifted the field of qualitative research dramatically from limited choices to multiple options, requiring clarification of researcher decisions and transparency of process. However, there still remains the difficult question of the role that theory will now play in such a high level of complex design and critical researcher reflexivity.

• qualitative research
• data analysis
• methodologies

Theory and Qualitative Data Analysis

Researchers new to qualitative research, and particularly those coming from the quantitative tradition, have often expressed frustration at the need for what appears to be an additional and perhaps unnecessary process—that of the theoretical interpretation of their carefully designed, collected, and analyzed data. The justifications for this process have tended to fall into one of two areas: the need to lift data to a broader interpretation beyond the Monty Pythonesque “this is my theory and it’s my very own,” to illumination of findings from another perspective—by placing the data in its relevant discipline field for comparison with previous theoretical data interpretations, while possibly adding something original to the field.

“Theory” is broadly seen as a set of assumptions or propositions, developed from observation or investigation of perceived realties, that attempt to provide an explanation of relationships or phenomena. The framing of data via theoretical imposition can occur at different levels. At the lowest level, various concepts such as “role,” “power,” “socialization,” “evaluation,” or “learning styles” refer to limited aspects of social organization and are usually applied to a specific group of people.

At a more complex level, theories of the Middle Range, identified by Robert Merton to link theory and practice, are used to build theory from empirical data. These tend to be discipline specific and incorporate concepts plus variables such as “gender,” “race,” or “class.” Concepts and variables are then combined into meaningful statements, which can be applied to more diverse social groups. For example, in education an investigation of student performance could emphasize such concepts as “safety,” “zero bullying,” “communication,” and “tolerance,” with variables such as “race” and “gender” to lead to a statement that good microsystems and a focus on individual needs are necessary for optimal student performance.

The third and most complex level uses the established or grand theories such as those of Sigmund Freud’s stages of children’s development, Jean Piaget’s theory of cognitive development, or Urie Bronfenbrenner’s ecological systems, which have been widely accepted as meaningful across a number of disciplines and provide abstract explanations of the uniformity of aspects of social organization, social behavior, and social change.

The trend in qualitative research regarding the application of chosen levels of theory has been generally either toward theory direction/verification or theory generation, although the two are often intertwined. In the first, a relevant existing theory is chosen early and acts as a point of critical comparison for the data to be collected. This approach requires the researcher to think theoretically as s/he designs the study, collects data, and collates it into analytical groupings. The danger of theory direction is that an over focus on a chosen theoretical orientation may limit what the researcher can access or “see” in the data, but on the upside, this approach can also enable the generation of new theoretical aspects, as it is rare that findings will fall precisely within the implications of existing statements. Theory generation is a much looser approach and involves either one or a range of relevant levels of theory being identified at any point in the research process, and from which, in conjunction with data findings, some new combination or distillation can enhance interpretation.

The question of whether a well-designed study should negate the need for theoretical interpretation has been minimally debated. Mehdi and Mansor ( 2010 ) identified three trends in the literature on this topic: that theory in qualitative research relates to integrated methodology and epistemology; that theory is a separate and additional element to any methodological underpinnings; and that theory has no solid relationship with qualitative research. No clear agreement on any of these is evident. Overall, there appears to be general acceptance that the process of using theory, albeit etically (imposed) or emically (integrated), enhances outcomes, and moves research away from being a-theoretical or unilluminated by other ideas. However, regarding praxis, a closer look at the issue of the use of theory and data may be in order. Theoretical interpretation, as currently practiced, has limits. To begin with, the playing field is not level. In the grounded theory tradition, Glaser and Strauss ( 1967 ) were initially clear that in order to prevent undue influence on design and interpretation, the researcher should avoid reviewing the literature on a topic until after some data collection and analysis had been undertaken. The presumption that most researchers would already be well versed in theory/ies and would have a broad spectrum to draw on in order to facilitate the constant comparative process from which data-based concepts could be generated was found to be incorrect. Glaser ( 1978 ) suggested this lack could be improved at the conceptual level via personal and professional reflexivity.

This issue became even more of a problem with the advent of practice-led disciplines such as education and health into the field of qualitative research. These groups had not been widely exposed to the theories of the traditional social sciences such as sociology, psychology, and philosophy, although in education they would have been familiar with John Dewey’s concept of “pragmatism” linking learning with hands-on activity, and were more used to developing and using models of practice for comparison with current realities. By the mid- 20th century , Education was more established in research and had moved toward the use of middle range theories and the late 20th-century grand theorists: Michel Foucault, with his emphasis on power and knowledge control, and Jurgen Habermas, with his focus on pragmatism, communication, and knowledge management.

In addition to addictive identification with particular levels of theory and discipline-preferred theories and methods, activity across qualitative research seems to fall between two extremes. At one end it involves separate processes of data collection and analysis before searching for a theoretical framework within which to discuss the findings—often choosing a framework that has gained traction in a specific discipline. This “best/most acceptable fit” approach often adds little to the relevant field beyond repetition and appears somewhat forced. At the other extreme there are those who weave methods, methodologies, data, and theory throughout the whole research process, actively critiquing and modifying it as they go, usually with the outcome of creating some new direction for both theory and practice. The majority of qualitative research practice, however, tends to fall somewhere between these two.

The final aspect of framing data lies in the impact of researchers themselves, and the early- 21st-century emphasis is on exposing relevant personal frames, particularly those of culture, gender, socioeconomic class, life experiences such as education, work, and socialization, and the researcher’s own values and beliefs. The twin purposes of this exposure are to create researcher awareness and encourage accountability for their impact on the data, as well as allowing the reader to assess the value of research outcomes in terms of potential researcher bias or prejudice. This critical reflexivity is supposed to be undertaken at all stages of the research but it is not always clear that it has occurred.

Paradigms: From Interactionism to Performativity

It appears that there are potentially five sources of theory: that which is generally available and can be sourced from different disciplines; that which is imbedded in the chosen paradigm/s; that which underpins particular methodologies; that which the researcher brings, and that which the researched incorporate within their stories. Of these, the paradigm/s chosen are probably the most influential in terms of researcher position and design. The variety of the sets of assumptions, beliefs, and researcher practices that comprise the theoretical paradigms, perspectives, or broad world views available to researchers, and within which they are expected to locate their individual position and their research approach, has shifted dramatically since the 1930s. The changes have been distinct and identifiable, with their roots located in the societal shifts prompted by political, social, and economic change.

The First Wave

The Positivist paradigm dominated research, largely unquestioned, prior to the early 20th century . It emphasized the distancing of the researcher from his/her subjects; researcher objectivity; a focus on objective, cause–effect, evidence-based data derived from empirical observation of external realities; experimental quantitative methods involving testing hypotheses; and the provision of finite answers and unassailable future predictions. From the 1930s, concerns about the limitations of findings and the veracity of research outcomes, together with improved communication and exposure to the worldviews of other cultures, led to the advent of the realist/post-positivist paradigm. Post-positivism, or critical realism, recognized that certainty in proving the truth of a hypothesis was unachievable and that outcomes were probably limited to falsification (Popper, 1963 ), that true objectivity was unattainable and that the researcher was most likely to impact on or to contaminate data, that both qualitative and quantitative approaches were valuable, and that methodological pluralism was desirable.

The Second Wave

Alongside the worldwide political shifts toward “people power” in the 1960s and 1970s, two other paradigms emerged. The first, the Interpretivist/Constructivist, focused on the social situations in which we as humans develop and how our construction of knowledge occurs through interactions with others in these contexts. This paradigm also emphasized the gaining of an understanding of the subjective views or experiences of the participants being researched, and recognized the impact of the researcher on researcher–researched mutually constructed realities. Here, theory generation is the preferred outcome to explain the what, how, and why of the findings. This usually involves the development of a conceptual model, forged from both the data gained and from the application/integration of relevant theory, to provide explanations for and interpretations of findings, together with a new perspective for the field/discipline.

The second paradigm, termed the Critical/Emancipatory, focused on locating, critiquing, and changing inequalities in society. The identification of the location of systemic power discrepancies or systematic power misuse in situations involving gender, sexuality, class, and race is expected to be followed by moves to right any oppression discovered. Here, the use of theory has been focused more on predetermined concept application for “fit.” This is because the very strong notion of problematic societal structures and power inappropriately wielded have been the dominant underpinnings.

In both the Interpretive and Critical paradigms, researcher position shifted from the elevated and distant position of positivism, to one of becoming equal with those being researched, and the notion of researcher framing emerged to cover this shift and help us—the readers—to “see” (and judge) the researcher and her/his processes of data management more clearly.

The Third Wave

In the 1980s, the next wave of paradigmatic options—postmodernism and poststructuralism—emerged. Postmodernism, with its overarching cultural implications, and poststructuralism, with its focus on language, severely challenged the construction, limitations, and claims to veracity of all knowledge and in particular the use of theory derived from siloed disciplines and confined research methods. Regardless of whether the postmodern/poststructural label is attached to grounded theory, ethnography, phenomenology, action, or evaluative designs, one general aspect that prevails is a focus on language. Language has become viewed as dubious, with notions of “slippage”—the multiple meanings of individual words, and “difference”—the difference and deferral of textual meaning (Derrida, 1970 , 1972 ), adding complexity. Double coding, irony, and juxtaposition are encouraged to further identify meaning, and to uncover aspects of social organization and behavior that have been previously marginalized or made invisible by existing discourses and discursive practices. Texts are seen as complex constructions, and intertextuality is favored, resulting in multiply constructed texts. The world is viewed as chaotic and unknowable; individuals are no longer seen as two dimensional—they are viewed as multifaceted with multiple realities. Complex “truths” are perceived as limited by time and context, requiring multiple data sets and many voices to illuminate them, and small-scale focused local research is seen as desirable. The role of researcher also changed: the politics of position and self-reflexivity dominate and the researcher needs to clearly expose past influences and formerly hidden aspects of his/her life. S/he inhabits the position of an offstage or decentered facilitator, presenting data for the reader to judge.

Theory is used mainly at the conceptual level with no particular approach being privileged. The researcher has become a “bricoleur” (Levi-Strauss, 1962 ) or handyman, using whatever methods or theories that are within reach, to adapt, craft, and meld technological skills with mythical intellectual reflection in order to create unique perspectives on the topic. Transitional interpretations dominate, awaiting further challenges and deconstruction by the next researcher in the field.

The need for multifaceted data sets in the 1990s led inevitably to a search for other research structures, and mixed and multiple methods have become topical. In crossing the divide between qualitative and quantitative approaches, the former initially developed its own sub-paradigms: pragmatist (complimentary communication and shared meanings) and transformative/emancipatory (inequalities in race, class, gender, and disability, to be righted). An increasing focus on multiple methods led to the advent of dialectics (multiple paradigm use) and critical realism (the acceptance of divergent results) (Shannon-Baker, 2016 ). The dilemmas of theory use raised by these changes include whether to segregate data sets and try to explain disparate outcomes in terms of diversity using different theories; whether to integrate them through a homogeneous “smoothing” process—one theory fits all, in order to promote a singular interpretation; or whether to let the strongest paradigm—in terms of data—dominate the theoretical findings.

The Fourth Wave

During the early 21st century , as the third wave was becoming firmly established, the Performative paradigm emerged. The incorporation of fine art–based courses into universities has challenged the prescribed rules of the doctoral thesis, initially resulting in a debate—with echoes of Glaser and Strauss—as to whether theory, if used initially, is too directive, thereby potentially contaminating the performance, or whether theory application should be an outcome to enhance performances, or even whether academic guidelines regarding theory use need to be changed to accommodate these disciplines (Bolt, 2004 ; Freeman, 2010 ; Riley & Hunter, 2009 ). Performativity is seen in terms of “effect,” a notion derived from John Austin’s ( 1962 ) assertion that words and speech utterances do not just act as descriptors of content, they have social force and impact on reality. Following this, a productive work is seen as capable of transforming reality (Bolt, 2016 ). The issue most heard here is the problem of how to judge this form of research when traditional guidelines of dependability, transformability, and trustworthiness appear to be irrelevant. Barbara Bolt suggests that drawing on Austin’s ( 1962 ) terms “locutionary” (semantic meaning), “illocutionary” (force), and “perlocutionary” (effect achieved on receivers), together with the mapping of these effects in material, effective, and discursive domains, may be useful, despite the fact that mapping transformation may be difficult to track in the short term.

During the second decade of the 21st century , however, discussions relating to the use of theory have increased dramatically in academic performative research and a variety of theoreticians are now cited apart from John Austin. These include Maurice Merleu-Ponty ( 1945 and the spatiality of lived events; Jacques Derrida ( 1982 ) on iterability, simultaneous sameness, and difference; Giles Deleuze and Felix Guatarri ( 1987 ) on rituals of material objects and transformative potential; Jean-Francois Lyotard ( 1988 ) on plurality of micro narratives, “affect,” and its silent disruption of discourse; and Bruno Latour ( 2005 ) with regard to actor network theory—where theory is used to engage with rather than to explain the world in a reflective political manner.

In performative doctoral theses, qualitative theory and methods are being creatively challenged. For example, from the discipline of theater and performance Lee Miller and Joanne/Bob Whalley ( 2010 ) disrupt the notion of usual spaces for sincere events by taking their six-hour-long performance Partly Cloudy, Chance of Rain , involving a public reaffirmation of their marriage vows, out of the usual habitats to a service station on a highway. The performance involves a choir, a band, a pianist, 20 performers dressed as brides and grooms, photographers, a TV crew, an Anglican priest, plus 50 guests. The theories applied to this event include an exploration of Marc Auge’s ( 1992 ) conception of the “non-place”; Mikhail Bakhtin’s ( 1992 ) concepts of “dialogism” (many voices) together with “heteroglossia” (juxtaposition of many voices in a dialogue); and Ludwig Wittgenstein’s ( 1953 ) discussion of the “duck rabbit”—once the rabbit is seen (participatory experience) the duck (audience) is always infected by its presence. This couple further challenged the guidelines of traditional doctoral theses by successfully negotiating two doctoral awards for a joint piece of research

A more formal example of a doctoral thesis (Reik, 2014 ) using traditional qualitative approaches has examined at school level the clash of paradigms of performative creative styles of teaching with the neoliberalist focus on testing, curriculum standardization, and student outcomes.

Leah Mercer ( 2012 ), an academic in performative studies, used the performative paradigm in her doctoral thesis to challenge and breach not only the methodological but also the theoretical silos of the quantitative–qualitative divide. The physics project is an original work using live performances of personal storytelling with video and web streaming to depict the memories, preoccupations, and the formative relationship of two women, an Australian and an American, living in contemporary mediatized society. Using scientific theory, Mercer explores personal identity by reframing the principles of contemporary physics (quantum mechanics and uncertainty principle) as aesthetic principles (uncertainty and light) with the physics of space (self), time (memory), light (inspiration), and complementarity (the reconciliation of opposites) to illuminate these experiences.

The performative paradigm has also shifted the focus on the reader, developed in postmodernism, to a broader group—an active audience. Multi-methods have been increased to include symbolic imagery, in particular visual images, as well as sound and live action. The researcher’s role here is often that of performer within a cultural frame, creating and investigating multiple realities and providing the link between the text/script and the audience/public. Theory is either minimized to the level of concepts or used to break through the silos of different disciplines to integrate and reconcile aspects from long-lasting theoretical divides.

In these chronological lines of paradigm shifts, changes in researcher position and changes in the application of theory can clearly be seen. The researcher has moved out of the shadows and into the mainstream; her/his role has shifted from an authoritarian collector and presenter of finite “truths” to a creator and often performer of multiple and disparate data images for the audience to respond to. Theory options have shifted from direction and generation within existing perspectives to creative amalgamations of concepts from disciplines previously rarely combined.

Methodologies: From Anthropology to Fine Arts

It would be a simple matter if all the researcher had to contend with was siting oneself in a particular paradigm/s. Unfortunately, not only have paradigms shifted in terms of researcher position and theoretical usage but so also have methodological choices and research design. One of the most popular methodologies, ethnography, with its roots in classical anthropology and its fieldwork-based observations of action and interaction in cultural contexts, can illustrate the process of methodological change following paradigm shift. If a researcher indicates that he/she has undertaken an ethnographic study, the reader will be most likely to query “which form?”: classical?, critical?, auto?, visual?, ethno drama?, cyber/net?, or performative? The following examples from this methodology should indicate how paradigm shifts have resulted in increasing complexity of design, methods, and interpretive options.

In c lassical ethnography the greatest borrowing is from traditional anthropology in terms of process and tools, and this can be seen with the inclusion of initial time spent in the setting to learn the language of the culture and to generally “bathe” oneself in the environment, often with minimal data collection. This process is supposed to help increase researcher understanding of the culture and minimize the problem of “othering” (treating as a different species/alien). Then a fairly lengthy amount of time is usually spent in the cultural setting either as an observer or as a participant observer to collect as much data as is relevant to answer the research question. This is followed by a return to post-check whether the findings previously gathered have stood the test of time. The analytical toolkit can involve domain analysis, freelists, pilesorts, triads and taxonomies, frame and social network, and event analysis. Truncated mini-ethnographies became more common as time became an issue, but these can still involve years of managing descriptive data, often collected by several participating researchers as seen in Douglas, Rasmussen, and Flanagan’s ( 1977 ) study of the culture of a nudist beach. Shorter versions undertaken by one researcher, for example Sohn ( 2015 ), have explored strategies of teacher and student learning in a science classroom. Theoretical interpretation can be by conceptual application for testing, such as Margaret Mead’s ( 1931 ) testing of the concept of “adolescence”—derived from American culture—in Samoan culture, or, more generally, by concept generation. The latter can be seen in David Rozenhan’s ( 1973 ) investigation of the experience of a group of researcher pseudo-patients admitted to hospitals for the mentally ill in the United States. The main concepts generated were labeling, powerlessness, and depersonalization.

De-colonial ethnography recognizes the “othering” frames of colonial and postcolonial research and takes a position that past colonial supremacy over Third World countries persists in political, economic, educational, and social constructions. Decolonizing requires a critical examination of language, attitudes, and research methods. Kakal Battacharya ( 2016 ) has exposed the micro-discourses of the continuing manifestation of colonial power in a parallel narrative written by a South Asian woman and a white American male. Concepts of colonialism and patriarchy, displayed through the discourses exposed, provide a theoretical critique.

Within critical ethnography , with its focus on power location and alleviation of oppression, Dale Spender ( 1980 ) used structured and timed observations of the styles, quality, and quantity of interaction between staff and students in a range of English classrooms. The theory-directive methodological frames of feminism and gender inequality were applied to identify and expose the lesser time and lesser quality of interaction that teachers had with female students in comparison with that assigned to male students. Widespread distribution of these results alerted education authorities and led to change, in some environments, toward introducing single-sex classrooms for certain topics. This was seen as progress toward alleviating oppressive behaviors. This approach has produced many excellent educational studies, including Peter Willis ( 1977 ) on the preparation of working-class kids for working-class jobs; Michele Fine ( 1991 ) on African American and Latino students who dropped out of a New York high school; Angela Valenzuela ( 1999 ) on emigrant and other under-achievers in American schools; Lisa Patel ( 2013 ) on inclusion and exclusion of immigrants into education; and Jean Anyon ( 1981 ) on social stratification of identical curriculum knowledge in different classrooms

A less concept-driven and more descriptive approach to critical ethnography was emphasized by Phil Carspecken’s hermeneutic approach ( 1996 ), which triggered a move toward data-generated theoretical concepts that could then be used to challenge mainstream theoretical positions.

Post-critical ethnography emphasizes power and ideology and the social practices that contribute to oppression, in particular objectivity, positionality, representation and reflexivity, and critical insufficiency or “antipower.”

Responsibility is shifted to the researcher for the world they create and critique when they interpret their research contexts (Noblit, Flores, & Murillo, 2004 ).

Autoethnography emerged from the postmodern paradigm, with its search for different “truths” and different relationships with readers, and prompted an emphasis on personal experience and documentation of the self in a particular cultural context (Ellis, 2004 ). In order to achieve this, the researcher has to inhabit the dual positions of being the focus of activities, feelings, and emotions experienced in the setting while at the same time being positioned distantly—observing and recording the behaviors of the self in that culture. Well-developed skills of critical reflexivity are required. The rejection of the power-laden discourses/grand theories of the past and the emphasis on transitional explanations has resulted in minimal theorizing and an emphasis on data display, the reader, and the reader’s response. Open presentations of data can be seen in the form of narrative storytelling, or re-presentations in the form of fiction, dramatic performances, and poetry. Carolyn Ellis ( 2004 ) has argued that “story is theory and theory is story” and our “making sense of stories” involves contributing to a broader understanding of human existence. Application/generation of concepts may also occur, and the term “Critical Autoethnography” has been used (Hughes & Pennington, 2017 ), particularly where experiences of race, class, or gender inequality are being experienced. Jennifer Potter ( 2015 ) used the concept “whiteness of silence” to introduce a critical race element into her autoethnographic experience of black–white racial hatred experiences within a university class on African American communication in which she was a student.

Visual ethnography uses a variety of tools, including photography, sketches, movies, social media, the Web and virtual reality, body art, clothing, painting, and sculpture, to demonstrate and track culture. This approach has been available for some time both as a methodology in its own right and as a method of data collection. An example of this approach, which mixes classical and visual ethnography, is Philippe Bourgois and Jeff Schonberg’s 12-year study of two dozen homeless heroin injectors and crack smokers living under a freeway overpass in San Francisco ( 2009 ). Their data comprised extensive black and white photos, dialogue, taped conversations, and fieldwork observation notes. The themes of violence, race relations, family trauma, power relations, and suffering were theoretically interpreted through reworked notions of “power” that incorporated Pierre Bourdieu’s ( 1977 , 1999 ) concepts of “symbolic violence”—linking observed practices to social domination, and “habitus”—an individual’s personal disposition comprising unique feelings and actions grounded in biography and history; Karl Marx’s “lumpen” from “lumpenproletariat” ( 1848 ), the residual class—the vagrants and beggars together with criminal elements that lie beneath the labor force; and Michel Foucault’s “biopower” ( 1978 , 2008 )—the techniques of subjugation used by the state on the population, and “governmentality” ( 1991 )—where individuals are disciplined through institutions and the “knowledge–power” nexus. The ideas of these three theorists were used to create and weave a theory of “lumpen abuse” to interpret the lives of the participants.

Ethno Drama involves transforming the results from an ethnographic study into a performance to be shared, for example the educational experiences of children and youth (Gabriel & Lester, 2013 ). The performance medium can vary from a film (Woo, 2008 ), an article presented in dramatic form (Carter, 2014 ), or more usually a play script to be staged for an audience in a theater (Ethno Theater). One of the main purposes is to provide a hearing space for voices that have been marginalized or previously silenced. These voices and their contexts can be presented by research participants, actors, or the research team, and are often directed at professionals from the field. Audience-based meetings to devise recommendations for further action may follow a performance. Because of the focus on inequality, critical theory has been the major theoretical orientation for this approach. The structure of the presentation invites audiences to identify situations of oppression, in the hope that this will inform them sufficiently to enable modification of their own practices or to be part of the development of recommendations for future change.

Lesnick and Humphrie ( 2018 ) explored the views of identity of LGBTQ+ youth between 14 and 24 years of age via interviews and online questionnaires, the transcriptions of which were woven into a script that was performed by actors presenting stories not congruent with their own racial/gender scripts in order to challenge audience expectations and labels. The research group encouraged the schools where they performed to structure discussion groups to follow the school-located performances. The scripts and discussions revealed and were lightly interpreted through concepts of homelessness, racism, and “oppression Olympics”—the way oppressed people sometimes view one another in competition rather than in solidarity. These issues were found to be relevant to both school and online communities. Support for these young people was discovered to be mostly from virtual sources, being provided by dialogues within Facebook groups.

Cyber/net or/virtual ethnographies involve the study of online communities within particular cultures. Problems which have emerged from the practice of this approach include; discovery of the researcher lurking without permission on sites, gaining prior permission which often disturbs the threads of interaction, gaining permission post–data collection but having many furious people decline participation, the “facelessness” of individuals who may have uncheckable multiple personas, and trying to make sense of very disparate data in incomplete and non-chronological order.. There has been acceptance that online and offline situations can influence each other. Dibbell ( 1993 ) demonstrated that online sexual violence toward another user’s avatar in a text-based “living room” reduced the violated person to tears as she posted pleas for the violator to be removed from the site. Theoretical interpretation at the conceptual level is common; Michel Foucault’s concept of heterotopia ( 1967 , 1984 ) was used to explain such spatio-temporal prisons as online rooms. Heterotropic spaces are seen as having the capacity to reflect and distort real and imagined experiences.

Poststructural ethnography tracks the instability of concepts both culturally and linguistically. This can be demonstrated in the deconstruction of language in education (Lather, 2001 ), particularly the contradictions and paradoxes of sexism, gender, and racism both in texts and in the classroom. These discourses are implicated in relations of power that are dynamic and within which resistance can be observed. Poststructuralism accepts that texts are multiple, as are the personas of those who created them, and that talk such as that which occurs in a classroom can be linked with knowledge control. Walter Humes ( 2000 ) discovered that the educational management discourses of “community,” “leadership,” and “participation” could be disguised by such terms as “learning communities” and “transformational leadership.” He analyzed the results with a conceptual framework derived from management theory and policy studies and linked the findings with political power.

Performative ethnography , from the post-postmodern paradigm, integrates the performances of art and theater with the focus on culture of ethnography (Denzin, 2003 ). A collaborative performance ethnography (van Katwyk & Seko, 2017 ) used a poem re-presenting themes from a previous research study on youth self-harming to form the basis of the creation of a performative dance piece. This process enabled the researcher participants to explore less dominant ways of knowing through co-learning and through the discovery of self-vulnerability. The research was driven by a social justice-derived concern that Foucault’s notion of “sovereignty” was being implemented through a web of relations that commodified and limited knowledge, and sanctioned the exploitation of individuals and communities.

This exploration of the diversity in ethnographic methods, methodologies, and interpretive strategies would be repeated in a similar trek through the interpretive, critical, postmodern, and post-postmodern approaches currently available for undertaking the various versions of grounded theory, phenomenology, feminist research, evaluation, action, or performative research.

Implications of Changes for the Researcher

The onus is now less on finding the “right” (or most familiar in a field) research approaches and following them meticulously, and much more on researchers making their own individual decisions as to which aspects of which methodologies, methods and theoretical explanations will best answer their research question. Ideally this should not be constrained by the state of the discipline they are part of; it should be equally as easy for a fine arts researcher to carry out a classical ethnography with a detailed theoretical interpretation derived from a grand theorist/s as it would be for a researcher in law to undertake a performative study with the minimum of conceptual insights and the maximum of visual and theoretical performances. Unfortunately, the reality is that trends within disciplines dictate publication access, thereby reinforcing the prevailing boundaries of knowledge.

However, the current diversity of choice has indeed shifted the field of qualitative research dramatically away from the position it was in several decades ago. The moves toward visual and performative displays may challenge certain disciplines but these approaches have now become well entrenched in others, and in qualitative research publishing. The creativity of the performative paradigm in daring to scale the siloed and well-protected boundaries of science in order to combine theoretical physics with the theories of social science, and to re-present data in a variety of newer ways from fiction to poetry to researcher performances, is exciting.

Given that theoretical as well as methodological and methods’ domains are now wide open to researchers to pick and choose from, two important aspects—justification and transparency of process—have become essential elements in the process of convincing the reader.

Justification incorporates the why of decision-making. Why was the research question chosen? Why was the particular paradigm, or paradigms, chosen best for the question? Why were the methodology and methods chosen most appropriate for both the paradigm/s and research question/s? And why were the concepts used the most appropriate and illuminating for the study?

Transparency of process not only requires that the researcher clarifies who they are in the field with relation to the research question and the participants chosen, but demands an assessment of what impact their background and personal and professional frames have had on research decisions at all stages from topic choice to theoretical analysis. Problems faced in the research process and how they were managed or overcome also requires exposition as does the chronology of decisions made and changed at all points of the research process.

Now to the issue of theory and the question of “where to?” This brief walk through the paradigmatic, methodological, and theoretical changes has demonstrated a significant move from the use of confined paradigms with limited methodological options to the availability of multiple paradigms, co-methodologies, and methods of many shades, for the researcher to select among Regarding theory use, there has been a clear move away from grand and middle range theories toward the application of individual concepts drawn from a variety of established and minor theoreticians and disciplines, which can be amalgamated into transitory explanations. The examples of theoretical interpretation presented in this article, in my view, very considerably extend, frame, and often shed new light on the themes that have been drawn out via analytical processes. Well-argued theory at any level is a great enhancer, lifting data to heights of illumination and comparison, but it could equally be argued that in the presence of critical researcher reflexivity, complex, layered, longitudinal, and well-justified design, meticulous analysis, and monitored audience response, it may no longer be essential.

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5 Philosophical Approaches to Qualitative Research

Renée Spencer, School of Social Work, Boston University

Julia M. Pryce, School of Social Work, Loyola University, Chicago

Jill Walsh, Department of Sociology, Boston University

• Published: 04 August 2014
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This chapter reviews some of the major overarching philosophical approaches to qualitative inquiry and includes some historical background for each. Taking a “big picture” view, the chapter discusses post-positivism, constructivism, critical theory, feminism, and queer theory and offers a brief history of these approaches; considers the ontological, epistemological, and axiological assumptions on which they rest; and details some of their distinguishing features. In the last section, attention is turned to the future, identifying three overarching, interrelated, and contested issues with which the field is being confronted and will be compelled to address as it moves forward: retaining the rich diversity that has defined the field, the articulation of recognizable standards for qualitative research, and the commensurability of differing approaches.

Much ink has been spilled in what have been called the “paradigm wars,” or battles within psychology and related disciples about how we know—and who judges—what is real. Efforts to establish the legitimacy of qualitative research have often taken the form of vociferous arguments for the merits of qualitative approaches, typically cast in terms of the contrasts between these and the more widely accepted quantitative approaches to knowledge production. More recently, even as the push toward evidence-based practice gains momentum and predictably lists the field toward greater uniformity in acceptable approaches to establishing what can be deemed credible evidence, qualitative approaches have continued to strengthen in presence and broaden in reach. Once a seeming fledging movement, despite its long but sometimes forgotten history ( Wertz et al., 2011 ), qualitative research in psychology appears to have come of age. This maturity is reflected in the wide variety of philosophical approaches to qualitative research that have now firmly taken root.

In this chapter, we review some of the major overarching philosophical approaches to qualitative inquiry and include some historical background for each. Here, we offer a “big picture” view and leave it to other chapters in this section (on interpretive, critical, feminist, and indigenous approaches) to take a more fine-grained look at some of the particular fields of thought within these. Described by Denzin and Lincoln (2013) as “a field of inquiry in its own right” (p. 5), qualitative research cuts across disciplines and is represented in many areas of scholarship. We focus here on psychology, but recognize the substantial work done in related fields such as sociology, anthropology, social work, social policy, humanities, and the health sciences, in particular nursing. We cannot possibly do justice to the work that has been done in this arena in this one chapter. Entire volumes (c.f., Denzin & Lincoln, 2013 ) are devoted to introducing researchers to these issues. We offer here what we hope is a concise and practical overview of some of the major philosophical assumptions that undergird qualitative research and shape its implementation today.

Once dominated by quantitative methods anchored in positivistic and post-positivistic research paradigms, a greater balance in the use of methodological and philosophical approaches is now being utilized in psychological research ( Ponterotto, 2005 ; Rennie, Watson, & Monteiro, 2002 ). The importance of qualitative research has long been justified by many on the basis of Dilthey’s argument that the distinctive natures of natural science and human science called for different approaches: “We explain nature, but we understand psychic life” (1894/1977, p. 27; as cited in Wertz et al., p. 80). Today, qualitative methods are viewed as being particularly well-suited to addressing some of our most pressing issues and concerns, such as the influence of culture on psychological development and its role in psychological interventions ( Ponterotto, Casas, Suzuki, & Alexander, 2010 ). The rise of participatory action research (PAR), with its emphasis on social change and the empowerment of community participants ( Kemmis & McTaggart, 2005 ), has also required employing a range of qualitative approaches (i.e., focus groups, interviews, participant observation, photo-voice, and storytelling) to collecting data that contribute to the development of the kind of deeper understandings of the experiences of the participants needed to effect meaningful change.

The diversity of qualitative approaches can be dizzying and makes agreement about their appropriate use, in what forms, and according to what standards difficult, if not impossible. It can be challenging for “insiders” to navigate these issues, let alone the novice researcher wading into this terrain. Seemingly simple questions about sample size and composition or the specific steps one should take in data analysis and how to achieve reliable findings can provoke lengthy discussion and even heated debates, with researchers take opposing positions and rooting their justification for these in foundational principles of qualitative research. Even more maddening for some, such questions may simply yield a repeated singular and highly unsatisfying response of “it depends.”

This seeming confusion can stem in part from differences in the purpose or aims of the research and in beliefs associated with core philosophies of science embedded within the varying approaches, namely ontology, epistemology, and axiology ( Creswell, 2007 ; Hays & Singh, 2012 ; Ponterotto, 2005 ). At its core, psychological research may be carried out with markedly distinct purposes, such as explaining and predicting aspects of the human experience, increasing our understanding of the lived experiences of different groups of people, or critiquing and changing the current conditions within which we live and strive to grow ( Lincoln, Lynham, & Guba, 2013 ). These different aims may also be carried out using approaches to research that rest on differing foundational assumptions about the nature of our world (ontology) and our knowledge about it (epistemology), as well as the role of values in the process of knowledge production (axiology), that are conceptualized by Hays and Singh (2012) as falling along separate continuums of beliefs.

Ontology is the study of the nature of reality. Within the context of qualitative research, ontology is discussed in terms of beliefs about the existence of some “universal truth” and about objectivity. At one end of the spectrum is a belief that reality is objective and that there are universal truths about reality that can be known. At the other end is a belief that reality is subjective and contextual, and a universal understanding of psychological experiences cannot be obtained because they must always be understood within the contexts within which they are embedded ( Hays & Singh, 2012 ). The crux of these viewpoints is also represented in the terms “emic” and “etic,” which are often used in anthropology and cultural psychology. These terms have been used to capture the distinction between experience-near understandings of culture and human experience, or what an insider within a local context would recognize and resonate with, and more experience-distant conceptualizations or abstractions about cultural processes (e.g., Geertz, 1983 ). Etic can also be thought of as generalizations about human behavior that are universally true and emic as those that are contextually situated and not generalizable, such as local customs ( Ponterotto, 2005 ).

Epistemology is the study of the process of knowing or “how we know what we know” (Guba & Lincoln, 2008; Ponterotto, 2005 ). It is concerned with how we gain knowledge of what exists and the relationship between the knower—in this case the researcher—and the world. The researcher and research participant may be considered independent of one another. In this view, researchers can use rigorous, systematic approaches to studying participants objectively or without researcher bias. This results in much attention being paid to rigor in research, particularly in the form of strict adherence to generally accepted systematic approaches to enhancing objectivity and reducing researcher bias. On the other side of the continuum is an understanding of knowledge as being actively constructed by the researcher and participant, who exert mutual influence on one another. Rather than removing or guarding against researcher bias, the dynamic interaction between the researcher and participant is viewed as central to capturing the inherently contextualized experiences of the participant. Issues of rigor remain but take on different meanings and forms. The goal here is not to eliminate bias—because that would be futile—but rather to enhance the trustworthiness of the findings by including and documenting multiple perspectives on the focus of the inquiry. In some cases, this might mean demonstrating that the researcher became immersed enough in the participants’ experiences so as to credibly represent and interpret them. In others, this might involve triangulating the data sources and/or the investigators.

Axiology is concerned with how values and assumptions of the researcher influence the scientific process, as well as what actions the researcher takes with the research produced ( Lincoln et al., 2013 ). What place do the emotions, expectations, and values of the researcher have in the research process? Should systematic steps be taken to ensure that the process is kept free of these so that they do not influence the participants and the results? Or is such a pursuit futile and the best a researcher can do is identify, describe, or even attempt to “bracket” ( Wertz, 2011 ) his or her values? Much qualitative research today rests on the assumption that research is “radically relational” and is inevitably shaped, and even intentionally informed, by the researcher’s orientation, values, and personal qualities ( Wertz et al., 2011 , p. 84). In research that seeks to change the status quo with regard to the unequal distribution of power and resources, such as in PAR, the researcher’s experience is central to the process and may be key to achieving the intended outcomes of the research ( Ponterotto, 2005 ). With regard to action, the positions range from researcher as distant observer of the study participants to researcher as change agent who is deliberately striving to achieve social justice through the work produced.

In some cases, the assumptions of a researcher may align more neatly along one side of these continuums. For example, a feminist researcher may hold that there are multiple truths and that knowledge is constructed in relationship with study participants, with the values and assumptions of the researcher integral to the construction of this knowledge. In others, the assumptions may be more mixed, such as a researcher who endorses a constructivist view of reality but views researcher reflexivity as less central to the research process. When these differing ontological, epistemological, and axiological stances go unacknowledged, the differences among qualitative approaches can seem as vast as those between quantitative and qualitative methods. As Camic, Rhodes, and Yardley (2003) , among many, have argued, the principle that should unify us is the need for coherence between the nature of our questions and the methodological and philosophical approach taken to answering them.

In the next sections, we review the following major overarching philosophical approaches that guide and structure qualitative research: post-positivism, constructivism, critical theory, feminism, and queer theory. We offer a brief history of each of the approaches; consider the ontological, epistemological, and axiological assumptions on which they rest; and detail some of the distinguishing features while also attempting to capture some of the diversity within them. We also touch on some prominent applications of these approaches to qualitative research in psychology. We recognize that these approaches have been grouped and defined in varying ways and that they defy this sort of tidy categorization. Still, we draw some lines here in an effort to highlight distinctive ideas within each. Also included are discussions of applications of each of the approaches.

Philosophical Approaches

Post-positivism.

Post-positivism grew out of the positivist view of science, and together these have dominated research in psychology for much of the field’s history ( Packer, 2011 ). Positivism rests on the ontological assumption that some objective truth or reality exists that is independent of our beliefs and constructions and can be ascertained through direct observation and experience. The efforts of science, thus, are put toward establishing universal laws of nature and, within psychology, universal laws of human development and experience. The attainment of this knowledge and our confidence in it depends on following systematic procedures through which claims about truth can be verified. Hypothesis generation and testing using valid measures of operationally defined variables are primary tools, and the goal is to be able, with confidence, to generalize the knowledge obtained to some larger general population. Post-positivism introduces the idea that hypotheses can never actually be proven beyond any doubt and that theory should tested in order to be falsified as well as verified. Issues of validity and reliability are of central importance in research within this paradigm, as are considerations of credible alternative hypotheses to explain the phenomenon being studied.

Post-positivism is rooted in logical positivism, a term coined by a group of scientists, mathematicians, and philosophers in the early 1900s known as the Vienna Circle. Building on the “positive philosophy” of Auguste Comte, but also emphasizing the importance of formal logic in scientific investigation, these thinkers determined that science required a systematic way of organizing our direct observations of experience and sought to inductively build laws of the natural world based on the construction of meaningful and unambiguous logical statements ( Packer, 2011 ). Only statements of fact that could be verified in some way or tested empirically were considered to be meaningful in the scientific endeavor.

Karl Popper (1934/1959 ) objected to the idea that this kind of inductive construction and confirmation of factual, logical statements that were purportedly free from personal and theoretical bias could lead to certainty about the natural world. Instead, he argued that the laws of science had to be built through a process of falsification or testing of hypotheses. He argued that data disproving hypotheses are more definitive than those supporting them, as in any given study there is always the risk that the data gathered do not accurately or fully represent the real world being studied. The disconfirming case or cases may simply have not made it into the sample drawn for study.

Foundational Assumptions

Post-positivism retains the belief in an observable external reality and the existence of universal truths but contends that a fully accurate representation of them can never be achieved with certitude ( Popper, 1934/1959 ). Although things exist beyond our experience of them, it is recognized that our knowledge of this world is socially constructed. Bias is unavoidable. All observations are fallible because they are inherently laden with our individual and cultural biases. Although we can never get to the truth with any certainty, post-positivists contend that we should continually strive to come as close as we possibly can. Because all measurement is biased and introduces error, issues of reliability and validity are paramount. Great attention is paid to reducing or controlling for bias through the design of the research and the use of clearly defined techniques such as controls groups and multiple forms of measurement or triangulation. This attempt to remove or at least reduce bias extends to the subjectivity of the researcher as well as to the intentions of the research. The researcher is to remain as neutral as possible throughout the research process and should not engage in research in the service of advocacy for any particular position within their field.

From a post-positivist perspective, the existence of multiple worldviews does not extend into a belief in complete relativism and an incommensurability of perspectives—the belief that our differences in experiences and culture mean that we can never understand each other. Whereas we may never achieve objectivity in the true sense of the word, we can employ systematic ways of checking our biases both individually and collectively through engaging in the scientific enterprise within a community of people who critically review one another’s work.

Implications for Research Methods

Research rooted in post-positivism aims to explain psychological phenomenon by identifying factors that predict particular outcomes and the relationships between them. A priori theory about how things are related is used to guide the research, which then seeks to verify or falsify these theory-based ideas. Having confidence in the findings from such research rests on the rigor with which systematic steps in the research process are employed. Multiple levels of data analysis and taking steps to ensure validity contribute to the rigor of the research, and the results of these studies are typically written in the form of scientific reports similar in structure to that used for the reporting of quantitative studies.

Application

Grounded theory , a now widely used approach to qualitative research, as traditionally constructed aligns most closely with positivistic and post-positivistic assumptions ( Bryant & Charmaz, 2010 ). It was first developed by Glaser and Strauss (1967) in response to what they considered to be an overemphasis on hypothesis testing and the verification of theory in sociological research. They argued that the work of theory generation could not be complete and that all human experience was unlikely to be captured and accounted for by the existing grand theories of the time. They put forth grounded theory as a systematic approach to qualitative data collection and analysis to be carried out with the explicit purpose of discovering new theory from data or building new theory from the ground up, rather than by logical deductions from a priori assumptions. Although grounded theory turned the process of scientific inquiry in the post-positivist tradition on its head by beginning with the collection of data to use to ultimately build theory rather than collecting data to prove or disprove existing theory, the foundational assumptions on which traditional grounded theory rests are largely rooted in post-positivism. That said, constructive approaches to grounded theory have also been articulated and widely implemented (e.g., Charmaz, 2006 ), and others have argued that grounded theory techniques can be implemented using a variety of philosophical approaches ( Birks & Mills, 2011 ).

Traditional grounded theory “accepts that there is an external world that can be described, analyzed, explained and predicted: truth, but with a small t ” ( Charmaz, 2000 , p. 524). Part of the intent of grounded theory was to codify qualitative research methods and put forth a systematic set of explicit strategies for carrying out the research process, with the assumption being that following a systematic set of methods would lead to the discovery of real phenomena and the development of verifiable “theories” of them ( Strauss & Corbin, 1998 ). Such work, however, requires getting out into the field to collect rich data on which to build these theories. Some of the defining features of a grounded theory approach are (a) simultaneous data collection and analysis, (b) the development of codes from the data rather than from theory, (c) constant comparison of data at all levels of the data collection and analytic process, (d) theoretical sampling to serve the purpose of theory generation rather than representativeness of the sample, and (e) memo writing to define and elaborate on emerging categories and the relationships among them ( Glaser & Strauss, 1967 ; Strauss & Corbin, 1998 ).

Social Constructionism

The tenets of the discipline throughout the twentieth century tended to place social constructionism at the opposite pole of experimental social psychology ( Jost & Kruglanski 2002 ), with the idea being that work in social psychology should fall on either end of the spectrum: you either do quantitative experiments or you engage in qualitative studies that are undergirded by a social constructionist paradigm. Although the two extremes have begun to meet in the middle in recent years, it is important to examine the role that the social constructionist perspective has played in shaping our thinking and work in the field of psychological research.

The notion of social construction first gained popularity in the United States after the publication of Berger and Luckmann’s (1966) seminal book, The Social Construction of Reality. Relying on the work of Schutz, Berger and Luckmann argued that all of our understandings and knowledge are socially constructed. The idea is that we create our own reality through social interactions, relationships, and experiences. From the ontological perspective, reality is context- and socially relative, and therefore many realities can exist simultaneously ( Berger & Luckmann, 1966 ; Gergen, 1996 ). If our reality is constructed, then, too, our knowledge and meanings are derived from social interactions. Individuals hold them in their minds, but the epistemological notion of reality and meanings are not individual in nature but instead are constantly “negotiating meaning” ( Gergen, 1996 ).

This has significant implications for both how we analyze the findings from past research in the field as well as how we shape future research projects. As Gergen (1996) states, “research findings don’t have any meaning until they are interpreted” and interpretations “result from a process of negotiating meaning in the community (119).” The data do not reveal anything in or of themselves; instead, it is the way that psychologists utilize and interpret the data that reveals meaning. But again, it is not a truth that is revealed, or rather it is a truth, the truth that the researcher, given his or her experiences and knowledge, created while interacting with the social environment. Diverse and influential work, such as Milgram’s (1974) experiment and Burr’s (1998) work on the social construction of gender, illustrates the power of social interactions to frame and influence our understandings and realities.

Perhaps most importantly for our purposes, social construction highlights the social creation of identity. Identity creation and maintenance is work that we are constantly engaged in as individuals; we use Goffmanian (1955) performances and props to test how others interpret our identities, which then impacts how we think of our identity. This is also true for the related notion of self-worth. In an interesting study examining the social construction of identity among the homeless in Austin, Texas, Snow and Anderson (1987) found that there can be both a social identity (the identity that society gives you) and a personal identity (the identity you hold in your mind). Traditionally, these would be thought to align, but through a social construction approach Snow and Anderson (1987) argued that there are cases in which people cannot easily reconcile the public and personal. This has obvious implications for the field of social psychology and identity research.

Social construction, as defined by Berger and Luckmann (1966) , suggests that reality is constantly in flux as it is negotiated and renegotiated through our experiences social worlds. From this core idea, other branches of social construction, such as symbolic interaction, phenomenology, and ethnomethodology, have evolved. Because they all fall under the social construction umbrella, it can be difficult at times to determine their differences. How does symbolic interactionism really differ from phenomenology, for example? The following sections lay out these three offshoots of social construction and attempt to present both their historical precedence as well as their current engagement with the discipline.

Symbolic Interactionism

The symbolic interactionist approach was first developed in the early 1900s by George Herbert Mead (1913) at the University of Chicago. He was a member of the eminent group of sociologists (loosely termed at the time because he also taught philosophy) working as part of the Chicago School in the early to mid-1900s. The Chicago School came to be known in particular for the development of the symbolic interactionist approach to studying daily life. Mead argued that society and all its component parts—structures, interactions, and meanings—are developed through social interactions, thus macroanalyses can and should really be reduced to their smaller microlevel interactions. The theory was popular during the time of the Chicago School and was then expanded and adapted by Herbert Blumer in 1960s. Blumer did not like the emphasis placed on macrolevel structures that dominated most of the sociological research at the time and thought that symbolic interactionism offered an alternative theoretical framework. Blumer’s work (1969) was resurrected as an empirical framework in the 1980s, and its popularity has ebbed and flowed since. One of the most renowned sociologists utilizing symbolic interactionism today is Sheldon Stryker at Indiana University.

Although Mead did not refer to the theory as such, symbolic interactionism is based on the overarching premise that all aspects of society are socially constituted. From macrolevel power structures to microlevel daily interactions, all are created through social interactions at various levels. Embedded in this perspective is the notion that meanings (about these power structures, interactions, etc.) are derived from social interactions. For both Mead and Blumer, the unit of analysis is the individual, not society or institutions. They were both reacting against the notion that social structures (i.e., socioeconomic stats) explain outcomes. Structures, according to symbolic interactionists, are just groups of people repeatedly engaged in interaction.

Our social interactions lead us to develop “shared meanings” ( Sandstrom, Martin, & Fine, 2006 ); through our interactions with others, we take on common definitions of emotions, experiences, and ways of acting. Thus, for example, gender norms may be taught, both consciously and unconsciously from early childhood; in this way, a female understands what it “means” to be a woman in her society without ever being explicitly told. A girl does not learn this in a bubble; rather, it is through her social interactions with others that she comes to understand what constitutes appropriate behavior, dress, appearance, and the like. She learns this through her experiences and the responses she gets from others.

Symbolic interactionism “stresses that people create, negotiate, and change social meanings through the process of interaction” ( Sandstrom et al., 2006 , p. 1). The key point here, for Blumer and others, is that meanings are constantly evolving. So, to follow the example just mentioned, our understanding of gender is not a fixed fact (because it might be different in different regions, religions, and time periods) but the result of previously experienced gendered interactions in our past. We take our previous interactions with us and apply them to the next interaction. Interactions, even with people we have just met, are not completely insulated events. Rather, each person brings to the interaction all of his or her previous interactions and meanings. Thus, a man and a woman in conversation will bring to this exchange all of their previously held ideas about femininity and masculinity, which they will use as a guide for navigating this new interaction. And of ultimate importance is Goffman’s (1959) notion of the feedback loop; you act based on your prior understandings, receive feedback from your new partner, and then take this new feedback with you into your future interactions. As this process continues, you may alter your meanings, and potentially your behavior, over time. It is a process, not a set plan.

Because behavior and meaning are social constituted, so, too, is the self. Most symbolic interactionists would argue that there is no core/true individual identity. Rather, we engage in identity work in which take on different identities to manage the diversity of our social interactions. So, for example, in the classroom setting, one takes on the role of either professor or student. Out of this context, we may take on an entirely different identity, such as mother. None of these identities represents our “true self,” but rather they are all appropriate context-specific roles. We base these roles on what Goffman (1959) called “the generalized other” or the group/people we interact with. So, we base our mothering role on our interactions with our children, our experiences with our own parents, friends, and media/cultural influences. As the “generalized other” changes, so do our identities. As a result of the primacy of social interactions, Mead’s original theory is a very fluid one. Meanings are iterative because they are informed by our ongoing interactions.

The legacy of symbolic interactionism for research in psychology is an important one. First, the notion that all behaviors, from internal thoughts to outward interactions, are socially constituted has an impact on the psychological discourse. For researchers, this means that the participant cannot be looked at simply as an individual but rather as an individual in the social context. Thus, a person’s thoughts and judgments are not solely the product of his or her own mind, but rather of his or her understandings based on social interactions ( Sandstrom et al., 2006 ). And, additionally, one of the byproducts of social interaction is feedback about ourselves; we internalize others’ perceptions of us, which can in turn influence our self-concept ( Cook & Douglas 1998 ). This has significant implications for any researchers studying mental health because it means that the mind is no longer a solely internal, individual unit of analysis. Our thoughts, ideas, hopes, and fears are all rooted in the social world and therefore have both social causes and consequences. Therefore, the “social act” should be the unit of analysis ( Sandstrom et al., 2006 ).

Symbolic interactionists also highlight individual agency to form and change the world around us. Individuals “designate meanings, define situations and plan lines of action. In so doing, they actively construct the reality of their environment and exercise a measure of control over it” ( Sandstrom et al., 2006 , p. 6). We do this through the process of interacting, reflecting on, and evaluating interactions, and acting. This process is dynamic and, at least to some degree, controlled by the individual. There is no right or set meaning or type of interaction. Instead, we each create our own realities based on our understandings and meanings. Thus, it is still possible for two people to react to the same interaction very differently because each will bring his or her own history of social interactions and meanings to this experience.

Rooting the theory in individual meanings and experiences has implications for the types of research methods symbolic interactionists will utilize. The most commonly utilized approaches are ethnography, grounded theory, and narrative analysis because these methods allow the themes to emerge from the data, thereby preserving the individual experiences and realities. These methods more readily address the question of how people make meaning out of experiences in their lives and do not allow the researcher’s assumptions and own set of meanings to dictate the findings that emerge from the data.

The border between social psychology and sociology is often blurred by researchers in both disciplines’ use of symbolic interactionism. In particular, Stryker (1987) argued that the movement in psychology away from behaviorism and toward a value placed on subjective experience is the result of the use of symbolic interactionism as a lens through which to examine psychological research. Thus, it is fair to say that the scope of symbolic interactionism’s influence is far reaching within the field. One interesting study that took a symbolic interactionist approach is Ponticelli’s (1999) study of former lesbians who, due to religious involvement in an ministry that does not acknowledge homosexuality, must reframe their sexual identities to align with their newly acquired religious beliefs. Ponticelli’s research method involved eight months of participant observations, interviews, and material analysis, and her goal was to understand the ways that the ex-lesbians in her study construct a narrative of their sexuality. Symbolic interactionism lends itself well to this kind of study because it brings participants’ own understandings and narratives to the study rather than the researcher’s personal assessment of the participants’ stories. Additionally, Ponticelli’s study also incorporates a symbolic interactionist approach in its attempt to focus on the ways that meaning is created and adjusted over time.

Phenomenology

Phenomenology was first established by Edmund Husserl in the early 1900s. It has subsequently been used as an approach within psychology as well as in other disciplines in the social sciences. Husserl’s original goal was to find a way to conduct objective scientific analysis of subjective topics, such as emotion. Phenomenology, along with the ideologically similar symbolic interactionism, has been an important philosophical approach underpinning much of psychological research. In particular, phenomenology has influenced the Duquesne School as well as the experimental approaches utilized in psychological research. In spite of the influence of phenomenology within the field of psychology, over time, its theoretical premise has been challenged by some of the field’s giants: James, Skinner, and Watson have at various times all challenged phenomenology and advocated a more scientific approach to the discipline of psychology. The debate continues today, and many researchers still question what constitutes phenomenological research as well as its merits as a philosophical framework.

Phenomenology is rooted in the notion that all of our knowledge and understanding of the world comes from our experiences ( Hein & Austin, 2001 ). At their core, there are significant similarities between phenomenology and symbolic interactionism in that both focus on the ways our engagement with society affects our worldviews. However, whereas symbolic interactionism focuses on the ways that social interactions affect our meaning, phenomenology takes the broader aim of studying experiences (phenomena). But, like symbolic interactionism, the focus is not on the events themselves, but rather on the ways in which we experience things and the meanings these experiences create for us. As Kockelmans (1973) writes, it is “bringing to light the usually hidden meanings which motivate the concrete modes of man’s orientation toward the world” (p. 274). As such, those who utilize the phenomenological approach seek to make explicit the “taken-for-grantedness” assumptions that guide our experiences ( Hein & Austin, 2001 , p. 6). In essence, there is no objective reality, but rather it is our experiences and our perceptions of these experiences (i.e., our lived experiences) that are our reality. Given that the meanings we create from our experiences are largely based on the social context ( Smith, 2011 ), there is a clear link to symbolic interactionism.

Additionally, phenomenologists believe that behavior is a reflection of our previous experiences; we act in response to our temporal and spatial memories of past experiences or, as Keen (1975) writes, “behavior is an expression of being in the world” (p. 27). Thinking about behavior as a product of our past experiences forces us to consider action and individual agency as embedded in a broader social context. Related to this question of behavior is the notion of intentionality; namely, the idea that every experience is in response to or connected to some past experience. Thus, attempting to examine the experience as “in the moment” is, from a phenomenological perspective, missing the unique understandings the individual brought to the current experience.

As a research method, phenomenology involves studying how we make sense of our experiences or “participant perspectives” ( Bogdan & Biklen, 1998 , p. 26). Therefore, as researchers, we cannot assume that we know what meanings people make of certain events. For example, even though we may think the standard response is to be sad after the death of a parent, we cannot presume that a participant in our study feels this or any other emotion. The job of the researcher is to uncover what it is people take for granted (i.e., what they might not even think to tell us in an interview and what we might not think to ask because we assume they think like we do). To do this, the researcher must first come to understand the assumptions and biases he or she brings to the research. Underlying phenomenological research is the notion of bracketing assumptions, which is the idea that, before we can conduct any analysis of our data, we must first explore our own biases or the “taken-for-grantedness” ( Hein & Austin, 2001 , p. 6) that make up our unique perspectives. Of course, there is no way we, as researchers, can operate outside of our assumptions and experiences. However, the self-reflection for which phenomenologists advocate does at least charge the researcher with keeping these biases in mind when conducting analysis.

Approaching a research question with the assumption that experience forms the basis for behavior and understanding fundamentally lends itself to certain research methods. In particular, utilizing methods that emphasize gathering data on lived experience from the participant’s perspective is essential. To that end, methods such as ethnomethodology, ethnography, and narrative analysis are particularly relevant for researchers utilizing the phenomenological approach because all of these methods focus on uncovering the meanings individuals give to their experiences.

A great deal of the research in psychotherapy is rooted in the phenomenological approach because many scholars in this field see as their goal “discovering psychological meanings by identifying the essential psychological structure of an interviewee’s description of an experience” ( Camic et al., 2003 , p. 8). A concrete example of this comes from Carl Rogers’s client-centered therapy (1951). Rogers found that many of his patients struggled not with what actually happened—that is, the “in the moment” reality—but with their perceptions and feelings about what happened. As a result, therapy must be targeted to address the individual’s set of perceptions and understandings. To follow up with the example of a person dealing with the death of a parent, a therapist cannot follow a preset protocol for helping the client because each patient’s experiences and feelings about death will be different.

From the perspective of social psychology, the phenomenological approach has implications for how we conduct and think about research on identity. In its most general sense, phenomenology de-emphasizes the self as a unique individual, which has implications for the types of research questions we ask, as well as for the methods we utilize. A phenomenological study of identity allows for open-ended questions that allow participants to present, through the construction of a narrative for example, what identity means to them and how it functions in their lives. This is especially relevant for factors such as gender, race and ethnicity, and socioeconomic status, which, depending on our context, can constrain or enhance our experiences and interactions. One example of this type of work is Friedman, Friedlander, and Blustein’s (2005) study that used a phenomenological approach to develop an understanding of how Jews construct their collective religious and ethnic identity as a highly assimilated but still distinct population within the United States.

A well-defined method with some roots in phenomenology (among other approaches) is consensual qualitative research (CQR; Hill, Knox, Thompson, Williams, Hess, & Ladany, 2005 ; Hill, Thompson, & Williams, 1997 ). It is a method for interview research that has been used in numerous studies in psychology, especially within counseling psychology. Consensual qualitative research is actually constructivist in ontology, in that it assumes multiple realities, and in epistemology because the researcher experience matters and informs interview question development. However, it also has post-positivistic leanings, with its emphasis on consensus among a team of researchers in the construction of findings, close adherence to a systematic approach, and interest in generalization and ( Hill et al., 2005 ).

In CQR, consistent data are collected across participants through semistructured interviews and then analyzed by multiple “judges” who must come to a consensus about the meaning of the data. At least one “auditor” also checks the “primary team of judges” to work against the potential for groupthink. Data analysis is carried out in three steps. First, participant responses to the open-ended interview questions are divided into domains or topic areas. Then, core ideas, which are abstracts or brief “summaries of the data that capture the essence of what was said in fewer words and with greater clarity” are constructed within each domain for each individual case ( Hill et al., 2005 , p. 200). Finally, cross-case analysis is carried out by developing categories that describe the common themes reflected in the core ideas within domains across cases.

Consensus is at the core of the CQR method, with the assumption being that consideration of multiple perspectives brings us closer in our approximation of the “truth” and reduces the influence of researcher bias ( Hill, Thompson, & Williams, 1997 ). Using teams of three to five analysts, coders first look at the data independently and then come together to discuss their ideas until consensus about the single best representation of the data is reached. The goal here is not what is typically thought of as interrater reliability, wherein preagreement about how to code data is established and then carried out with the goal of achieving the highest levels of accuracy in agreement in coding. Rather, it is expected, and even hoped, that team members will begin with different ideas about the data so that the final product reflects and integrates multiple perspectives and is less fraught with individual bias. The potential for groupthink is minimized through the use of one or two additional team members who serve as auditors to review and check the primary team’s interpretations and judgments. The auditors review the work of the primary team once the core ideas for each domain have been established consensually and then again when the cross-case categories have been determined. At each of these stages, the auditors review the raw material and provide comments back to the primary team who must then carefully consider each comment and determine through discussion whether to accept or reject each one.

Critical Theory

Critical theory as an approach represents a key postmodern paradigm and offers alternatives to the postmodernist and constructivist lenses. In the context of research, the application of critical theory emphasizes the ways by which the values of the researcher and those studied impact the social world. This point of view contributes to a larger shift in research over the past several decades ( Kidd & Kral, 2005 ), one that privileges meaning and requires a rethinking of knowledge ( Goodman & Fisher, 1995 ).

Critical theory has had many distinct historical phases that cross several generations. The birth of this paradigm is considered to have taken place through the Institute for Social Research at the University of Frankfurt am Main during 1929–1930. During this time, the arrival of the “Frankfurt School” philosophers and social theorists ( Creswell, 2007 ), including Max Horkheimer, Theodor Adorno, and Herbert Marcuse, marked an idealistic, utopian vision that stretched beyond the more customary “positivist” tradition of the time. This emergence offered criticism to the status, structure, and goal of the traditional social sciences ( Adorno et al., 1969 ). The German philosophers and social theorists of the Frankfurt School were influenced by the barbarism of World War I and what was perceived as the inhumanity of post-war capitalism so widespread in Europe at the time. During World War II, several key contributors to the School moved to the United States in an effort to escape the war. Once in the United States, these thinkers were struck by the gulf between the stated progressive agenda within the United States and the very real differences between races and social classes present, in large part due to discrimination ( Ponterotto, 2005 ).

According to these theorists, “critical” theory may be distinguished from “traditional” theories to the extent that it seeks human emancipation and a disruption of the status quo. Ontologically, critical theory challenges the idea that reality is natural and objective because reality is shaped by social, political, cultural, economic, ethnic, and gender-based forces into social structures. Instead, critical theorists assume that reality can only come to be known through a subjective frame and as shaped by values and mediated by power relations that are socially and historically constituted.

More recently, Jurgen Habermas’s (1988 ; 1990 ) work on communicative reason and linguistic intersubjectivity has represented iconic work in critical theory in the more modern era. Habermas’s work has enabled strategies of community building and social movements based on his work in communication. This work has not taken place without scrutiny, however. Theorists such as Nikolas Kompridis have opposed some of Habermas’s ideas ( Kompridis, 2006 ), claiming that these recent approaches have undermined the original aims of social change espoused by critical theory, particularly in terms of the critique of modern capitalism.

According to Horkheimer, a critical theory is adequate only if it is explanatory, practical, and normative (1972). In other words, it has to address what is wrong with current social reality, identify the actors to change it, provide clear norms for criticism, and identify practical goals for social transformation. The orientation of this theory is toward transformation, traditionally of capitalism into a “real democracy”.

Foundation ideals are based on a fundamental struggle for equality and social justice. Knowledge is used to emancipate the oppressed, and “validity is found when research creates action” ( Lincoln, Lynham, & Guba, 2011 , p. 114). Given this definition, a number of “critical theories” have been developed to demonstrate differences in power in the areas of gender, race and ethnicity, class, sexual orientation, and disabilities, many of which have emerged in connection with the social movements associated with these areas, particularly in the United States. In short, a critical theory provides the basis and groundwork for research aimed at decreasing domination and increasing freedom.

Critical theory by and large rejects the assumption that a scientific or objective basis of criticism needs to be grounded in a grand theory. Rather, epistemologically, critical theory privileges agents’ own knowledge and understandings, with an assumption that these understandings can be a basis for social criticism in themselves. In other words, theories can have “a relative legitimacy” ( Habermas, 1988 , p. 3). Habermas also argues that, relative to other existing theories, the role of critical theory is to unify these multiple theories, considering their varied methods and presuppositions ( Habermas, 1988 ). Given this role, it stands to reason that any social scientific method or explanation-producing theory can be potentially critical.

Similarly, in critical theory, the relationship between researcher and participant is transactional, subjective, and dialectic. In other words, what can be known is inextricably tied to the interaction between an investigator and an object or group. Insofar as one can separate oneself from marginalized groups in an effort to remain “objective,” one removes oneself from one’s “share” of the social condition studied, likely perpetuating the inequalities that contribute to the adverse social conditions often of interest to social scientists.

Researchers who employ critical theory take values a step further than constructivists do in that they hope and expect their value biases to influence the research process and outcome. More specifically, because critical theory concerns itself with unequal distributions of power and the resultant oppression of subjugated groups, a preset goal of the research is to empower participants to transform the status quo and emancipate themselves from ongoing oppression. Thus, critical theorist researchers acknowledge at the outset that they expect results to document the high levels of stress or disadvantage of the group under study. Beyond this, such researchers aim to use the results and report of the study in some way to advocate for improvement of the examined group.

Critical theorists, given their stance on the importance of researcher–participant interaction and the significance of understanding values as influencing the reality under study, more often use naturalistic designs in which the researcher is engaged in the daily life of participants. Critical theoretical approaches tend to rely on dialogic methods, which may combine data collection methods (e.g., participant observation, in-depth interviewing, first-person written reports) with opportunity for reflection. This approach intentionally invites a questioning of the “natural” status quo and order and an exploration of the tensions that characterize the social issue under exploration. Inherently challenging, this approach values transparency and welcomes opportunities for alternative paradigms to be considered as part of the learning process itself.

Methodologically, contexts are not merely conceptualized as “variables,” but as essential parts of subjectivity according to critical theory. In terms of the field of psychology, this approach invites us to consider the role of research in terms of how liberation might take shape across the lifespan. Qualitative approaches in which a researcher’s social justice values help direct inquiry, such as PAR ( Kidd & Kral, 2005 ), provide ample example of critical theory at work in the research context.

Application in the Field

Participatory action research is a form of action research anchored in the belief that the research process itself serves as a mechanism for social change. Participatory action research is an approach focused on critical theory because, at its core, PAR is geared toward empowerment of participants that leads to emancipation from oppression and enhanced quality of life. In laypersons’ terms, “you get people affected by a problem together, figure out what is going on as a group, and then do something about it” ( Kidd & Kral, 2005 , p. 187).

According to Kemmis and McTaggart (2005) , PAR often involves a cycle of self-reflection and action in addressing a community problem. Participants and researchers establish a collaborative relationship as they ask critical questions about the current life situation. This dialogue moves the group to action as they develop knowledge and further explore the problem and how it can be addressed. In this way, collaborators using PAR begin to set a stage of social action to instigate change.

The process of change emerges and shifts as part of the self-reflective cycles, but typically is not predetermined by a clear series of procedural and analytic steps. Instead, during the reflective and action spiral, PAR investigators rely on a wide variety of methods and procedures as they gradually better understand the needs of the community. As such, many studies that use PAR take on varied methods such as storytelling, sharing experiences, individual and focus group interviews, participant observation, drawings, and even the more structured qualitative interview or quantitative survey as the need merits.

When engaged in a PAR process, study participants are expected to participate fully. However, the creation of such participatory contexts is very challenging and time-consuming, and is not the norm ( Kidd & Kral, 2005 ). Disempowered groups are seldom given the opportunity and at times are discouraged from this type of action. Further compounding this problem is the tendency for established forums (e.g., academia) to claim exclusive ownership of methods of knowledge gathering and avenues for change. All of these challenges further lend the process of PAR to be informed by critical theory. As a specific example, Dentith, Measor, and O’Malley (2012) outline the practice of using critical theory across three separate research projects involving young people facing various life difficulties and vulnerabilities. In so doing, they highlight the dilemmas they face in doing so within the context of more traditional, positivist approaches frequently favored in academic research settings.

Participatory action research is somewhat new to the field of psychology and has not historically been utilized frequently in this field. This is likely at least in part due to the axiology of PAR as a critical theory method that advocates a value-directed (rather than value-neutral post-positivism or value-bracketed constructivism) stance. Traditionally trained psychologists may be made initially uncomfortable by research that is value mediated because psychological training often conceives of research as objective, in which participants are studied without changing them or the researchers.

Feminist Theories

Feminist theories are used to frame and understand research approaches across a range of disciplines and social problems. They developed in part in response to prevailing ideas that more traditional scientific inquiry tended to exclude women from inquiry and deny women epistemic authority ( Anderson, 1995 ). They are often associated with critical theory, although they have been considered by some to be separate ( Crotty, 1998 ), yet closely related, within the epistemological continuum.

Informed by the political ideologies of the 1970s women’s movement, feminist scholars sought to reinterpret and modify concepts within the philosophy of science to create feminist approaches to research. Originally fueled by activism, feminism as an academic focus has developed significantly from the 1980s until the present. According to feminist paradigms, the traditional philosophy of science has tended to produce theories that represent women (or their activities and interests) as inferior to their male counterparts. Further, “feminine” cognitive styles and modes of knowledge have been denigrated by traditional inquiry ( Anderson, 1995 ), producing knowledge that is not relevant to people in subordinate positions and/or that reinforces unequal power dynamics, particularly as it relates to gender.

Feminist theories “place gender at the center of inquiry,” and yet “increasingly incorporate multiple... intersectionalities of identity,” including sexuality, race, religion, and social class ( Marshall & Rossman, 2010 , p. 27). Similar to critical theory, the larger aim of feminist theories is to turn thought into action ( Marshall & Rossman, 2010 ), in this case by focusing on the issues faced by women and other often marginalized groups.

Epistemologically, feminist theories focus on the accounts of women (and other historically marginalized groups) as legitimate and core sources of knowledge. Of note, feminist theories are not distinguished so much by their substantive topic (e.g., women’s issues, gender, reproductive rights, etc.) or by the gender of the researcher (i.e., male or female) but rather by their orientation and guiding philosophy on epistemology and research creation (e.g., methodology).

Over the past two decades, feminist scholars have developed alternative epistemologies to guide the process of doing research. Feminist methodologies attempt to eradicate sexist bias in research while capturing women’s voices, particularly those consistent with feminist ideals. Epistemologically, feminist theories privilege women’s experiences as not only legitimate, but also as important and revealing bases of knowledge. Work guided by feminist theories often aims to employ qualitative methodologies toward the exploration of power imbalances, starting with that between the researcher and researched ( Marshall & Rossman, 2010 ), so as to engender trust and collect accurate data. Research informed by feminist theory, like critical theory more broadly, also challenges academia traditionally due to its value of application of research to lived experiences ( Smart, 2009 ), particularly among those who are oppressed. Thus, feminist theories mirror the core values of critical theory in emphasizing the mutual learning between the researcher and the researched, an exchange that is critical to the emancipation of disenfranchised or overlooked groups.

Feminist research has emphasized the importance of exploring the day-to-day experiences of marginalized groups, particularly women. Qualitative approaches are particularly well-suited to capturing the “messiness” of these daily experiences because these methods can account for emotions, as well as for other less tangible aspects of experience, in data collection. Often, feminist theories invite more traditional forms of qualitative data collection (e.g., interviewing, focus groups, ethnography) to be adapted to be more consistent with feminist ideology.

As referenced earlier, a feminist approach to research can be employed across the social as well as physical sciences and beyond. For the most part, researchers employing this approach attempt to eradicate sexist bias in research while seeking to capture women’s voices, particularly as they apply to the day-to-day experiences of everyday life. This angle lends itself well to studies such as those examining the experiences of domestic workers and domestic violence. Core to the use of feminist theory is the understanding that ways of knowing, or epistemologies, are constantly evolving as knowledge grows and as the “knowers” expand in scope. Thus, bodies of research, as they make use of a feminist lens, may find that the social problem under study increases the complexity of the problem under study. This is characteristic of feminist methodologies. However, such an approach is also characterized by reducing the hierarchical relationship between researchers and their participants to facilitate trust and disclosure and recognizing and reflecting on the emotionality of women’s lives.

Queer Theory

With the rise of the gay liberation movement in the post-Stonewall era, gay and lesbian perspectives began to contribute to politics, philosophy, and social theory. Initially, these were often connected to feminist ideology. However, in the late 1980s and early 1990s, queer theory was developed as its own framework. The term “queer,” as opposed to “gay and lesbian,” also distinguished the theory from those that preceded it, specifically gay liberation theories. Similar to feminist theories, queer theory was accompanied by social movements, and its emergence evolved in part as a reaction to the marginalization of the LBGTQ community and the ways by which “science” had historically been used against them ( Minton, 1997 ).

Queer theory found a more natural home in qualitative research because this form had historically been less focused on objective reality and more on subjective experiences ( Downing & Gillett, 2011 ). However, its emergence has occurred within an ongoing evolution in terms of how we consider sexuality and marginalization in research and in society at large. In the early 1900s, the scientific examination of those who were in same-sex relationships was perpetually challenged by the stigma and silence faced by this group. In short, this population was hard to identify and find, much less research. The second half of the twentieth century, however, shifted this as lesbian and gay studies expanded exponentially ( Gamson, 2000 ), focusing explicitly on the lives of those who identify as gay or lesbian. Queer theory, a more recent arrival on the scene, has introduced a post-structuralist critique by suggesting that the self cannot and should not be identified by sexuality or sexual orientation by itself, thereby challenging the importance of studying sexuality as a “subject” of inquiry. Although the tension proposed by these shifts is often applauded within the qualitative research world (e.g., Gamson, 2000 ), it is this context in which queer theory has emerged.

Queer theory was separate from gay liberation theories in several ways. First, queer theory defined itself as not specific only to sexuality. Instead, queer theory does not refer to a nature, be it sexual or otherwise, but rather as a relational construct. “Queer” refers specifically to being “outside the norm”; this norm can vary relative to context. In other words, “Queer is... whatever is at odds with the normal, the legitimate, the dominant. There is nothing in particular to which it necessarily refers . It is an identity without an essence” ( Halperin, 1995 , p. 62; emphasis in the original).

Because queer theory does not suggest a specific nature or essence, it therefore is inclusive of those who may express themselves outside any norm, including that of the gay and lesbian community. In other words, sadomasochism, perhaps marginalized by some constructs, is not so according to queer theory. Additionally, this lack of focus on a specific essence allows gays and lesbians to identify by their sexuality or by any other aspect of their identity, thereby placing the focus on personal meaning, as opposed to societally ascribed labels.

A central claim of queer theorists, which is that identity is understood exclusively as a social construct (rather than given by nature), significantly affects how research is carried out within this approach. Most immediately, it implies that research needs to be evaluated for biases that privilege heterosexuality ( Butler, 1990 ; 1993 ), however subtle. Based on the concern that queer theory places on false dichotomies (e.g., “closeted” and “out,” etc.), this theory also is critical of other dichotomies implied in research, particularly as it relates to assumptions regarding what is natural or artificial and what is masculine versus feminine. Instead, queer theory emphasizes the importance of understanding categories more fluidly, an approach that lends itself more toward qualitative methods, which seek to explore social phenomena with an eye toward complexity rather than standardization.

Queer theory has been applied to multiple social problems and developmental issues. However, it is most often applied to questions concerning empowerment, resistance to domination (e.g., heterosexism, homophobia), gender identity and marginalization due to gender, sexual orientation, or sexual behavior. Because queer theory is concerned with the nonessential nature of sexual identity, this theory pushes the field to consider identity from multiple perspectives, and invites cultural as well as race-related inquiry.

Conclusion and Future Directions

It is impossible to fully represent the richness of any one of these philosophical approaches in a chapter such as this one. We have instead tried to convey a sense of the breadth of the field and to illuminate at least some of the meaningful distinctions in the major approaches to qualitative research in psychology today. In this last section, we turn our attention to the future and identify three overarching, interrelated, and contested issues with which the field is being confronted and will be compelled to address as we move forward: retaining the rich diversity that has defined the field, the articulation of recognizable standards for qualitative research, and the commensurability of differing approaches. The contested nature of these issues stems in part from the very diversity of philosophical approaches that has defined the field. Here, again, we cannot possibly represent the considerable thought behind and debate around each of these matters. Rather, we simply raise and mark them at this time.

The diversity of approaches represented in the field of qualitative research today speaks to the strength of the movement and bodes well for our efforts to both advance and deepen our understanding of the psychological world. As Ann Hartman (1990) wrote many years ago, “each way of knowing deepens our understanding and adds another dimension to our view of the world” (p. 3). Just as no single research design or data collection method can adequately capture the multidimensional nature of human psychology, no one philosophical approach can suitably guide our efforts to address the full range of questions that need to be pursued to develop the knowledge needed “to benefit society and improve people’s lives” ( American Psychological Association, 2013 ).

However, this diversity in approaches to qualitative research also creates significant tensions and makes attempts to “define” the field quite challenging. Despite the substantial work done by many scholars (c.f. Denzin & Lincoln, 2013 ) to delineate these contrasting perspectives and approaches, a lack of awareness remains, especially (but not exclusively) among those not well-versed in qualitative methods. The predictable misunderstandings and strong differences in beliefs about what is “credible” research that can result continue to plague those of us who practice qualitative research as we strive to get our work funded and published more widely. Peer reviews of our work can often be riddled with contradictory assessments of its rigor and even of its basic value or contribution. (c.f. Ceglowski, Bacigalupa, & Peck, 2011 ).

Continued efforts to make clear the diversity of approaches, the philosophical assumptions guiding these, and the particular contributions the differing approaches make to our understanding of psychology are critical. We must be cautious about making general claims about rigor and the “right” way to do qualitative research that are actually framed within our own narrower terms or experience with certain approaches. Keeping the richness of the field alive will require discipline on all of our parts to respond to questions about how best to go about engaging in high quality qualitative research or evaluating the quality of the work of others by first acknowledging “it depends” and then inquiring about the philosophical approach, aims, and context of the work.

One of the biggest challenges before us is the continued articulation of recognizable standards for qualitative research that represent, and which ideally can be applied to, the full range of approaches. The very differences in purpose and aims and in philosophical approaches that comprise the rich field of qualitative research today makes such efforts seem impossible. However, ignoring this task in the era of what has been called the scientifically based research movement ( National Research Council, 2002 ; Torrance, 2008 ), defined largely in terms of experimental design and methods and with randomized controlled trials heralded as the “gold standard,” leaves the array of approaches that do not readily fit this mold highly vulnerable. But what is the best way to address these complex and high-stakes issues?

Researchers taking a more post-positivistic approach have argued that there are separate but parallel sets of standards for validity and reliability in qualitative and quantitative research (e.g., Hammersley, 1992 ; Kuzel & Engel, 2001 ). Some constructivists have put forth that a common set of standards can be established but because the foundational philosophical approaches between post-positivism and constructivism are so different, a separate and distinct set of criteria need to be applied. Models using concepts such as trustworthiness, transferability, and authenticity have been developed (e.g., Guba & Lincoln, 1989 ), and it is estimated that more than 100 quality appraisal forms have been put forth ( Saini & Shlonsky, 2012 ). Unfortunately, most do not make clear the philosophical assumptions that undergird them ( Saini & Shlonsky, 2012 ), which unfortunately further muddies the water. Moreover, other adherents to constructivist approaches hold that the contextual and relational nature of knowledge construction precludes the possibility of establishing such standards (e.g., Lincoln, 1995 ; Schwandt, 1996 ). Finally, many working from within critical theory and related approaches suggest that such standards are inevitably formed by the power structures in which they are housed, thereby potentially further perpetuating the inequalities the research aims to address or study (e.g., Garrett & Hodkinson, 1998 ). Furthermore, they assert that the quality of the research should be based on an assessment of whether it empowered participants to effect meaningful and lasting changes ( Correa, 2013 ).

Some have tried to resolve these tensions by suggesting guidelines they believe account for and are applicable across the diversity of approaches to qualitative research (e.g., Drisko, 1997 ; Saini & Shlonsky, 2012 ; Tracy, 2010 ). These guidelines focus on the different components of the research process, such as clear identification of philosophical approach and aims of the research, specification of methods and congruence between these and the stated philosophical approach and aims, and transparency and clarity in sampling, data collection, and data analytic procedures. Although the imperative to tackle these issues is clear, the way forward to doing this is less so. Should we push further toward agreeing on a shared set of standards that can be applied across traditions, or invest in more localized ones tailored specifically to particular approaches (e.g., narrative analysis) and developed by scholars practicing these ( Preissle, 2013 ), or both? How might the myriad elements of research, including the many gatekeeping activities in the research and scholarship enterprise from funding through publication of research findings, address and accommodate these standards in their expectations and processes? What is clear is that the diversity of approaches to qualitative research must be fully represented in any efforts to further define and move the field forward on this front.

Embracing and fully representing the diversity of approaches and coming to terms with standards for them stills leaves unaddressed a third concern for the field moving forward, namely what has been referred to as the commensurability of approaches . That is, whether approaches rooted in the differing philosophical approaches can be “retrofitted to each other in ways that make the simultaneously practice of both possible” ( Lincoln et al., 2013 , p. 238). Some, such as critical and feminist theorists, have argued that epistemological differences between methods can render research paradigms incompatible ( Lincoln et al., 2013 ). Others have dismissed assertions about irreconcilable differences between philosophical approaches and research paradigms and argue for what they call a “pragmatic” approach, particularly in the service of carrying out mixed-methods research (e.g., Creswell, 2009 ; Creswell & Clark, 2007 ; Maxcy, 2003 ). Lincoln, Lynham, and Guba (2013) take a middle position and offer a “cautious” endorsement of the commensurability of approaches. They assert that some approaches share some elements that are similar or strongly related and therefore can be effectively and meaningfully combined, whereas others are more “contradictory and mutually exclusive” (p. 239). Preissle (2013) , in her consideration of the future of the field, makes a pragmatic argument of a different sort for commensurability. Citing the work of her students that has combined approaches in unconventional yet highly productive ways, she observes that the novice scholars of today are “challenging, even transgressing, epistemological and theoretical boundaries” that will ultimately move research forward in unexpected ways” (p. 536).

There is nothing new about these questions. They have been debated for decades now, and clarity seems no nearer. What has changed is the climate. It is at once more open to qualitative methods than ever before and less accommodating of the rich diversity among the approaches taken to this work. Increasing numbers of graduate students are being trained in multiple methodologies. Although, unfortunately, there does not yet appear to be a cry for purely qualitative studies on the horizon, most major funding sources are at least indicating a preference for the use of multiple methods, in some cases even quite strongly so. Qualitative studies can be found in journals of differing ilk, not just within the confines of those dedicated to publishing qualitative research. However, what is deemed acceptable or “credible” qualitative research is narrowing. In the parlance of the old expression “a little knowledge is a dangerous thing,” the widening exposure and reach of qualitative work means that many more scholars are encountering and engaging with it in some way; these scholars often do not realize that what they know is but a small slice of a now large and longstanding field. Researchers outside the field of qualitative research who participate in setting the standards for research more broadly may be friendly to particular kinds of approaches, such as seeing a place for qualitative work only in the exploration of new areas of inquiry to offer “thick description” and examples or to complement or round out the quantitative findings, but much less so to stand-alone work or work aimed at explicating processes and mechanisms at work in human psychology. Scholars from within who are joining in the work of setting the standards of research can sometimes allow certain kinds of qualitative research to stand for the field, which can serve to belie and even shut out other, often more transgressive forms. These perhaps seemingly old and familiar questions about philosophies of science, rigor, and commensurability are alive and well, taking new forms, and they are, in some ways, more important now than ever before.

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Empirical Research: Quantitative & Qualitative

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Introduction: What is Empirical Research?

Quantitative methods, qualitative methods.

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Empirical research  is based on phenomena that can be observed and measured. Empirical research derives knowledge from actual experience rather than from theory or belief. 

Key characteristics of empirical research include:

• Specific research questions to be answered;
• Definitions of the population, behavior, or phenomena being studied;
• Description of the methodology or research design used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys);
• Two basic research processes or methods in empirical research: quantitative methods and qualitative methods (see the rest of the guide for more about these methods).

(based on the original from the Connelly LIbrary of LaSalle University)

Empirical Research: Qualitative vs. Quantitative

Learn about common types of journal articles that use APA Style, including empirical studies; meta-analyses; literature reviews; and replication, theoretical, and methodological articles.

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Quantitative Research

A quantitative research project is characterized by having a population about which the researcher wants to draw conclusions, but it is not possible to collect data on the entire population.

• For an observational study, it is necessary to select a proper, statistical random sample and to use methods of statistical inference to draw conclusions about the population. 
• For an experimental study, it is necessary to have a random assignment of subjects to experimental and control groups in order to use methods of statistical inference.

Statistical methods are used in all three stages of a quantitative research project.

For observational studies, the data are collected using statistical sampling theory. Then, the sample data are analyzed using descriptive statistical analysis. Finally, generalizations are made from the sample data to the entire population using statistical inference.

For experimental studies, the subjects are allocated to experimental and control group using randomizing methods. Then, the experimental data are analyzed using descriptive statistical analysis. Finally, just as for observational data, generalizations are made to a larger population.

Iversen, G. (2004). Quantitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.), Encyclopedia of social science research methods . (pp. 897-898). Thousand Oaks, CA: SAGE Publications, Inc.

Qualitative Research

What makes a work deserving of the label qualitative research is the demonstrable effort to produce richly and relevantly detailed descriptions and particularized interpretations of people and the social, linguistic, material, and other practices and events that shape and are shaped by them.

Qualitative research typically includes, but is not limited to, discerning the perspectives of these people, or what is often referred to as the actor’s point of view. Although both philosophically and methodologically a highly diverse entity, qualitative research is marked by certain defining imperatives that include its case (as opposed to its variable) orientation, sensitivity to cultural and historical context, and reflexivity. 

In its many guises, qualitative research is a form of empirical inquiry that typically entails some form of purposive sampling for information-rich cases; in-depth interviews and open-ended interviews, lengthy participant/field observations, and/or document or artifact study; and techniques for analysis and interpretation of data that move beyond the data generated and their surface appearances. 

Sandelowski, M. (2004).  Qualitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.),  Encyclopedia of social science research methods . (pp. 893-894). Thousand Oaks, CA: SAGE Publications, Inc.

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1.2: Theory and Empirical Research

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This book is concerned with the connection between theoretical claims and empirical data. It is about using statistical modeling; in particular, the tool of regression analysis, which is used to develop and refine theories. We define theory broadly as a set of interrelated propositions that seek to explain and, in some cases, predict an observed phenomenon.

Theory: A set of interrelated propositions that seek to explain and predict an observed phenomenon.

Theories contain three important characteristics that we discuss in detail below.

Characteristics of Good Theories Coherent and internally consistent Causal in nature Generate testable hypotheses

1.2.1 Coherent and Internally Consistent

The set of interrelated propositions that constitute a well-structured theory are based on concepts . In well-developed theories, the expected relationships among these concepts are both coherent and internally consistent. Coherence means the identification of concepts and the specified relationships among them are logical, ordered, and integrated. An internally consistent theory will explain relationships with respect to a set of common underlying causes and conditions, providing for consistency in expected relationships (and avoidance of contradictions). For systematic quantitative research, the relevant theoretical concepts are defined such that they can be measured and quantified. Some concepts are relatively easy to quantify, such as the number of votes cast for the winning Presidential candidate in a specified year or the frequency of arrests for gang-related crimes in a particular region and time period. Others are more difficult, such as the concepts of democratization, political ideology or presidential approval. Concepts that are more difficult to measure must be carefully operationalized , which is a process of relating a concept to an observation that can be measured using a defined procedure. For example, political ideology is often operationalized through public opinion surveys that ask respondents to place themselves on a Likert-type scale of ideological categories.

Concepts and Variables

A concept is a commonality across observed individual events or cases. It is a regularity that we find in a complex world. Concepts are our building blocks to understanding the world and to developing theory that explains the world. Once we have identified concepts we seek to explain them by developing theories based on them. Once we have explained a concept we need to define it. We do so in two steps. First, we give it a dictionary-like definition, called a nominal definition. Then, we develop an operational definition that identifies how we can measure and quantify it.

Once a concept has been quantified, it is employed in modeling as a variable . In statistical modeling, variables are thought of as either dependent or independent variables. A dependent variable , Y, is the outcome variable; this is the concept we are trying to explain and/or predict. The independent variable(s) , X, is the variable(s) that is used to predict or explain the dependent variable. The expected relationships between (and among) the variables are specified by the theory.

Measurement

When measuring concepts, the indicators that are used in building and testing theories should be both valid and reliable . Validity refers to how well the measurement captures the concept. Face validity, for example, refers to the plausibility and general acceptance of the measure, while the domain validity of the measure concerns the degree to which it captures all relevant aspects of the concept. Reliability, by contrast, refers to how consistent the measure is with repeated applications. A measure is reliable if, when applied to the repeated observations in similar settings, the outcomes are consistent.

Assessing the Quality of a Measure

Measurement is the process of assigning numbers to the phenomenon or concept that you are interested in. Measurement is straight-forward when we can directly observe the phenomenon. One agrees on a metric, such as inches or pounds, and then figures out how many of those units are present for the case in question. Measurement becomes more challenging when you cannot directly observe the concept of interest. In political science and public policy, some of the things we want to measure are directly observable: how many dollars were spent on a project or how many votes the incumbent receives, but many of our concepts are not observable: is issue X on the public’s agenda, how successful is a program, or how much do citizens trust the president. When the concept is not directly observable the operational definition is especially important. The operational definition explains exactly what the researcher will do to assign a number for each subject/case.

In reality, there is always some possibility that the number assigned does not reflect the true value for that case, i.e., there may be some error involved. Error can come about for any number of reasons, including mistakes in coding, the need for subjective judgments, or a measuring instrument that lacks precision. These kinds of error will generally produce inconsistent results; that is, they reduce reliability. We can assess the reliability of an indicator using one of two general approaches. One approach is a test-retest method where the same subjects are measured at two different points in time. If the measure is reliable the correlation between the two observations should be high. We can also assess reliability by using multiple indicators of the same concept and determining if there is a strong inter-correlation among them using statistical formulas such as Cronbach’s alpha or Kuder-Richardson Formula 20 (KR-20).

We can also have error when our measure is not valid. Valid indicators measure the concept we think they are measuring. The indicator should both converge with the concept and discriminate between the concept and similar yet different concepts. Unfortunately, there is no failsafe way to determine whether an indicator is valid. There are, however, a few things you can do to gain confidence in the validity of the indicator. First, you can simply look at it from a logical perspective and ask if it seems like it is valid. Does it have face validity? Second, you can see if it correlates well with other indicators that are considered valid, and in ways that are consistent with theory. This is called construct validity. Third, you can determine if it works in the way expected, which is referred to as predictive validity. Finally, we have more confidence if other researchers using the same concept agree that the indicator is considered valid. This consensual validity at least ensures that different researchers are talking about the same thing.

Measurement of Different Kinds of Concepts

Measurement can be applied to different kinds of concepts, which causes measures of different concepts to vary. There are three primary levels of measurement ; ordinal, interval, and nominal. Ordinal level measures indicate relative differences, such as more or less, but do not provide equal distances between intervals on the measurement scale. Therefore, ordinal measures cannot tell us how much more or less one observation is than another. Imagine a survey question asking respondents to identify their annual income. Respondents are given a choice of five different income levels: $0-20,000, $20,000-50,000, $50,000-$100,000, and $100,000+. This measure gives us an idea of the rank order of respondents’ income, but it is impossible for us to identify consistent differences between these responses. With an interval level measure, the variable is ordered and the differences between values are consistent. Sticking with the example of income, survey respondents are now asked to provide their annual income to the nearest ten thousand dollar mark (e.g., $10,000, $20,000, $30,000, etc.). This measurement technique produces an interval level variable because we have both a rank ordering and equal spacing between values. Ratio scales are interval measures with the special characteristic that the value of zero (0) indicates the absence of some property. A value of zero (0) income in our example may indicate a person does not have a job. Another example of a ratio scale is the Kelvin temperature scale because zero (0) degrees Kelvin indicates the complete absence of heat. Finally, a nominal level measure identifies categorical differences among observations. Numerical values assigned to nominal variables have no inherent meaning, but only differentiate one type" (e.g., gender, race, religion) from another.

1.2.2 Theories and Causality

Theories should be causal in nature, meaning that an independent variable is thought to have a causal influence on the dependent variable. In other words, a change in the independent variable causes a change in the dependent variable. Causality can be thought of as the motor" that drives the model and provides the basis for explanation and (possibly) prediction.

The Basis of Causality in Theories

• Time Ordering: The cause precedes the effect, X→Y
• Co-Variation: Changes in X are associated with changes in Y
• Non-Spuriousness: There is not a variable Z that causes both X and Y

To establish causality we want to demonstrate that a change in the independent variable is a necessary and sufficient condition for a change in the dependent variable (though more complex, interdependent relationships can also be quantitatively modeled). We can think of the independent variable as a treatment, τ, and we speculate that τ causes a change in our dependent variable, Y. The gold standard’’ for causal inference is an experiment where a) the level of ττ is controlled by the researcher and b) subjects are randomly assigned to a treatment or control group. The group that receives the treatment has outcome Y 1 and the control group has outcome Y 0 ; the treatment effect can be defined as τ=Y 1 -Y 0 . Causality is inferred because the treatment was only given to one group, and since these groups were randomly assigned other influences should wash out. Thus the difference τ=Y 1 -Y0 can be attributed to the treatment.

Given the nature of social science and public policy theorizing, we often can’t control the treatment of interest. For example, our case study in this text concerns the effect of political ideology on views about the environment. For this type of relationship, we cannot randomly assign ideology in an experimental sense. Instead, we employ statistical controls to account for the possible influences of confounding factors, such as age and gender. Using multiple regression we control for other factors that might influence the dependent variable. 1

1.2.3 Generation of Testable Hypothesis

Theory building is accomplished through the testing of hypotheses derived from theory. In simple form, a theory implies (sets of) relationships among concepts. These concepts are then operationalized. Finally, models are developed to examine how the measures are related. Properly specified hypotheses can be tested with empirical data, which are derived from the application of valid and reliable measures to relevant observations. The testing and re-testing of hypotheses develops levels of confidence that we can have for the core propositions that constitute the theory. In short, empirically grounded theories must be able to posit clear hypotheses that are testable. In this text, we discuss hypotheses and test them using relevant models and data.

As noted above, this text uses the concepts of political ideology and views about the environment as a case study in order to generate and test hypotheses about the relationships between these variables. For example, based on popular media accounts, it is plausible to expect that political conservatives are less likely to be concerned about the environment than political moderates or liberals. Therefore, we can pose the working hypothesis that measures of political ideology will be systematically related to measures of concern for the environment – with conservatives showing less concern for the environment. In classical hypothesis testing, the working hypothesis is tested against a null hypothesis . A null hypothesis is an implicit hypothesis that posits the independent variable has no effect (i.e., null effect) on the dependent variable. In our example, the null hypothesis states ideology has no effect on environmental concern.

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Empirical Research: Definition, Methods, Types and Examples

Content Index

Empirical research: Definition

Empirical research: origin, quantitative research methods, qualitative research methods, steps for conducting empirical research, empirical research methodology cycle, advantages of empirical research, disadvantages of empirical research, why is there a need for empirical research.

Empirical research is defined as any research where conclusions of the study is strictly drawn from concretely empirical evidence, and therefore “verifiable” evidence.

This empirical evidence can be gathered using quantitative market research and  qualitative market research  methods.

For example: A research is being conducted to find out if listening to happy music in the workplace while working may promote creativity? An experiment is conducted by using a music website survey on a set of audience who are exposed to happy music and another set who are not listening to music at all, and the subjects are then observed. The results derived from such a research will give empirical evidence if it does promote creativity or not.

LEARN ABOUT: Behavioral Research

You must have heard the quote” I will not believe it unless I see it”. This came from the ancient empiricists, a fundamental understanding that powered the emergence of medieval science during the renaissance period and laid the foundation of modern science, as we know it today. The word itself has its roots in greek. It is derived from the greek word empeirikos which means “experienced”.

In today’s world, the word empirical refers to collection of data using evidence that is collected through observation or experience or by using calibrated scientific instruments. All of the above origins have one thing in common which is dependence of observation and experiments to collect data and test them to come up with conclusions.

LEARN ABOUT: Causal Research

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

• Quantitative research : Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables . These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
• Qualitative research:   Qualitative research methods are used to gather non numerical data.  It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Data collected from these will need to be analysed. Empirical evidence can also be analysed either quantitatively and qualitatively. Using this, the researcher can answer empirical questions which have to be clearly defined and answerable with the findings he has got. The type of research design used will vary depending on the field in which it is going to be used. Many of them might choose to do a collective research involving quantitative and qualitative method to better answer questions which cannot be studied in a laboratory setting.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

• Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.

Previously, surveys were taken face to face only with maybe a recorder. However, with advancement in technology and for ease, new mediums such as emails , or social media have emerged.

For example: Depletion of energy resources is a growing concern and hence there is a need for awareness about renewable energy. According to recent studies, fossil fuels still account for around 80% of energy consumption in the United States. Even though there is a rise in the use of green energy every year, there are certain parameters because of which the general population is still not opting for green energy. In order to understand why, a survey can be conducted to gather opinions of the general population about green energy and the factors that influence their choice of switching to renewable energy. Such a survey can help institutions or governing bodies to promote appropriate awareness and incentive schemes to push the use of greener energy.

Learn more: Renewable Energy Survey Template Descriptive Research vs Correlational Research

• Experimental research: In experimental research , an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.

For example: A particular product company is trying to find what is the reason for them to not be able to capture the market. So the organisation makes changes in each one of the processes like manufacturing, marketing, sales and operations. Through the experiment they understand that sales training directly impacts the market coverage for their product. If the person is trained well, then the product will have better coverage.

• Correlational research: Correlational research is used to find relation between two set of variables . Regression analysis is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.

LEARN ABOUT: Level of Analysis

For example: Higher educated individuals will get higher paying jobs. This means higher education enables the individual to high paying job and less education will lead to lower paying jobs.

• Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.

For example: A research to find out benefits of exercise. The target is asked to exercise everyday for a particular period of time and the results show higher endurance, stamina, and muscle growth. This supports the fact that exercise benefits an individual body.

• Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause and effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.

For example: A medical study to find the prevalence of under-nutrition disorders in kids of a given population. This will involve looking at a wide range of parameters like age, ethnicity, location, incomes  and social backgrounds. If a significant number of kids coming from poor families show under-nutrition disorders, the researcher can further investigate into it. Usually a cross sectional study is followed by a longitudinal study to find out the exact reason.

• Causal-Comparative research : This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

For example: A researcher measured the productivity of employees in a company which gave breaks to the employees during work and compared that to the employees of the company which did not give breaks at all.

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Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive analysis form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research methods are used to derive a conclusion to support the theory or hypothesis being studied.

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• Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.

For example: A report mentioning the solution provided by a company to its client. The challenges they faced during initiation and deployment, the findings of the case and solutions they offered for the problems. Such case studies are used by most companies as it forms an empirical evidence for the company to promote in order to get more business.

• Observational method:   Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational research method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.

For example: setting up a research to observe a particular animal in the rain-forests of amazon. Such a research usually take a lot of time as observation has to be done for a set amount of time to study patterns or behavior of the subject. Another example used widely nowadays is to observe people shopping in a mall to figure out buying behavior of consumers.

• One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

For example: A one-on-one interview with the finance minister to gather data on financial policies of the country and its implications on the public.

• Focus groups: Focus groups are used when a researcher wants to find answers to why, what and how questions. A small group is generally chosen for such a method and it is not necessary to interact with the group in person. A moderator is generally needed in case the group is being addressed in person. This is widely used by product companies to collect data about their brands and the product.

For example: A mobile phone manufacturer wanting to have a feedback on the dimensions of one of their models which is yet to be launched. Such studies help the company meet the demand of the customer and position their model appropriately in the market.

• Text analysis: Text analysis method is a little new compared to the other types. Such a method is used to analyse social life by going through images or words used by the individual. In today’s world, with social media playing a major part of everyone’s life, such a method enables the research to follow the pattern that relates to his study.

For example: A lot of companies ask for feedback from the customer in detail mentioning how satisfied are they with their customer support team. Such data enables the researcher to take appropriate decisions to make their support team better.

Sometimes a combination of the methods is also needed for some questions that cannot be answered using only one type of method especially when a researcher needs to gain a complete understanding of complex subject matter.

We recently published a blog that talks about examples of qualitative data in education ; why don’t you check it out for more ideas?

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyse it. This will enable the researcher to resolve problems or obstacles which can occur during the experiment.

Step #1: Define the purpose of the research

This is the step where the researcher has to answer questions like what exactly do I want to find out? What is the problem statement? Are there any issues in terms of the availability of knowledge, data, time or resources. Will this research be more beneficial than what it will cost.

Before going ahead, a researcher has to clearly define his purpose for the research and set up a plan to carry out further tasks.

Step #2 : Supporting theories and relevant literature

The researcher needs to find out if there are theories which can be linked to his research problem . He has to figure out if any theory can help him support his findings. All kind of relevant literature will help the researcher to find if there are others who have researched this before, or what are the problems faced during this research. The researcher will also have to set up assumptions and also find out if there is any history regarding his research problem

Step #3: Creation of Hypothesis and measurement

Before beginning the actual research he needs to provide himself a working hypothesis or guess what will be the probable result. Researcher has to set up variables, decide the environment for the research and find out how can he relate between the variables.

Researcher will also need to define the units of measurements, tolerable degree for errors, and find out if the measurement chosen will be acceptable by others.

Step #4: Methodology, research design and data collection

In this step, the researcher has to define a strategy for conducting his research. He has to set up experiments to collect data which will enable him to propose the hypothesis. The researcher will decide whether he will need experimental or non experimental method for conducting the research. The type of research design will vary depending on the field in which the research is being conducted. Last but not the least, the researcher will have to find out parameters that will affect the validity of the research design. Data collection will need to be done by choosing appropriate samples depending on the research question. To carry out the research, he can use one of the many sampling techniques. Once data collection is complete, researcher will have empirical data which needs to be analysed.

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Step #5: Data Analysis and result

Data analysis can be done in two ways, qualitatively and quantitatively. Researcher will need to find out what qualitative method or quantitative method will be needed or will he need a combination of both. Depending on the unit of analysis of his data, he will know if his hypothesis is supported or rejected. Analyzing this data is the most important part to support his hypothesis.

Step #6: Conclusion

A report will need to be made with the findings of the research. The researcher can give the theories and literature that support his research. He can make suggestions or recommendations for further research on his topic.

A.D. de Groot, a famous dutch psychologist and a chess expert conducted some of the most notable experiments using chess in the 1940’s. During his study, he came up with a cycle which is consistent and now widely used to conduct empirical research. It consists of 5 phases with each phase being as important as the next one. The empirical cycle captures the process of coming up with hypothesis about how certain subjects work or behave and then testing these hypothesis against empirical data in a systematic and rigorous approach. It can be said that it characterizes the deductive approach to science. Following is the empirical cycle.

• Observation: At this phase an idea is sparked for proposing a hypothesis. During this phase empirical data is gathered using observation. For example: a particular species of flower bloom in a different color only during a specific season.
• Induction: Inductive reasoning is then carried out to form a general conclusion from the data gathered through observation. For example: As stated above it is observed that the species of flower blooms in a different color during a specific season. A researcher may ask a question “does the temperature in the season cause the color change in the flower?” He can assume that is the case, however it is a mere conjecture and hence an experiment needs to be set up to support this hypothesis. So he tags a few set of flowers kept at a different temperature and observes if they still change the color?
• Deduction: This phase helps the researcher to deduce a conclusion out of his experiment. This has to be based on logic and rationality to come up with specific unbiased results.For example: In the experiment, if the tagged flowers in a different temperature environment do not change the color then it can be concluded that temperature plays a role in changing the color of the bloom.
• Testing: This phase involves the researcher to return to empirical methods to put his hypothesis to the test. The researcher now needs to make sense of his data and hence needs to use statistical analysis plans to determine the temperature and bloom color relationship. If the researcher finds out that most flowers bloom a different color when exposed to the certain temperature and the others do not when the temperature is different, he has found support to his hypothesis. Please note this not proof but just a support to his hypothesis.
• Evaluation: This phase is generally forgotten by most but is an important one to keep gaining knowledge. During this phase the researcher puts forth the data he has collected, the support argument and his conclusion. The researcher also states the limitations for the experiment and his hypothesis and suggests tips for others to pick it up and continue a more in-depth research for others in the future. LEARN MORE: Population vs Sample

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There is a reason why empirical research is one of the most widely used method. There are a few advantages associated with it. Following are a few of them.

• It is used to authenticate traditional research through various experiments and observations.
• This research methodology makes the research being conducted more competent and authentic.
• It enables a researcher understand the dynamic changes that can happen and change his strategy accordingly.
• The level of control in such a research is high so the researcher can control multiple variables.
• It plays a vital role in increasing internal validity .

Even though empirical research makes the research more competent and authentic, it does have a few disadvantages. Following are a few of them.

• Such a research needs patience as it can be very time consuming. The researcher has to collect data from multiple sources and the parameters involved are quite a few, which will lead to a time consuming research.
• Most of the time, a researcher will need to conduct research at different locations or in different environments, this can lead to an expensive affair.
• There are a few rules in which experiments can be performed and hence permissions are needed. Many a times, it is very difficult to get certain permissions to carry out different methods of this research.
• Collection of data can be a problem sometimes, as it has to be collected from a variety of sources through different methods.

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Empirical research is important in today’s world because most people believe in something only that they can see, hear or experience. It is used to validate multiple hypothesis and increase human knowledge and continue doing it to keep advancing in various fields.

For example: Pharmaceutical companies use empirical research to try out a specific drug on controlled groups or random groups to study the effect and cause. This way, they prove certain theories they had proposed for the specific drug. Such research is very important as sometimes it can lead to finding a cure for a disease that has existed for many years. It is useful in science and many other fields like history, social sciences, business, etc.

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With the advancement in today’s world, empirical research has become critical and a norm in many fields to support their hypothesis and gain more knowledge. The methods mentioned above are very useful for carrying out such research. However, a number of new methods will keep coming up as the nature of new investigative questions keeps getting unique or changing.

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Qualitative and Quantitative Research

What is "empirical research".

• empirical research
• Locating Articles in Cinahl and PsycInfo
• Locating Articles in PubMed
• Getting the Articles

Empirical research  is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions  to be answered
• Definition of the  population, behavior, or   phenomena  being studied
• Description of the  process  used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology:  sometimes called "research design" --  how to recreate the study -- usually describes the population, research process, and analytical tools
• Results : sometimes called "findings"  --  what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies
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Qualitative Methods in Health Care Research

Vishnu renjith.

School of Nursing and Midwifery, Royal College of Surgeons Ireland - Bahrain (RCSI Bahrain), Al Sayh Muharraq Governorate, Bahrain

Renjulal Yesodharan

1 Department of Mental Health Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Judith A. Noronha

2 Department of OBG Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Elissa Ladd

3 School of Nursing, MGH Institute of Health Professions, Boston, USA

Anice George

4 Department of Child Health Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Healthcare research is a systematic inquiry intended to generate robust evidence about important issues in the fields of medicine and healthcare. Qualitative research has ample possibilities within the arena of healthcare research. This article aims to inform healthcare professionals regarding qualitative research, its significance, and applicability in the field of healthcare. A wide variety of phenomena that cannot be explained using the quantitative approach can be explored and conveyed using a qualitative method. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research. The greatest strength of the qualitative research approach lies in the richness and depth of the healthcare exploration and description it makes. In health research, these methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

Introduction

Healthcare research is a systematic inquiry intended to generate trustworthy evidence about issues in the field of medicine and healthcare. The three principal approaches to health research are the quantitative, the qualitative, and the mixed methods approach. The quantitative research method uses data, which are measures of values and counts and are often described using statistical methods which in turn aids the researcher to draw inferences. Qualitative research incorporates the recording, interpreting, and analyzing of non-numeric data with an attempt to uncover the deeper meanings of human experiences and behaviors. Mixed methods research, the third methodological approach, involves collection and analysis of both qualitative and quantitative information with an objective to solve different but related questions, or at times the same questions.[ 1 , 2 ]

In healthcare, qualitative research is widely used to understand patterns of health behaviors, describe lived experiences, develop behavioral theories, explore healthcare needs, and design interventions.[ 1 , 2 , 3 ] Because of its ample applications in healthcare, there has been a tremendous increase in the number of health research studies undertaken using qualitative methodology.[ 4 , 5 ] This article discusses qualitative research methods, their significance, and applicability in the arena of healthcare.

Qualitative Research

Diverse academic and non-academic disciplines utilize qualitative research as a method of inquiry to understand human behavior and experiences.[ 6 , 7 ] According to Munhall, “Qualitative research involves broadly stated questions about human experiences and realities, studied through sustained contact with the individual in their natural environments and producing rich, descriptive data that will help us to understand those individual's experiences.”[ 8 ]

Significance of Qualitative Research

The qualitative method of inquiry examines the 'how' and 'why' of decision making, rather than the 'when,' 'what,' and 'where.'[ 7 ] Unlike quantitative methods, the objective of qualitative inquiry is to explore, narrate, and explain the phenomena and make sense of the complex reality. Health interventions, explanatory health models, and medical-social theories could be developed as an outcome of qualitative research.[ 9 ] Understanding the richness and complexity of human behavior is the crux of qualitative research.

Differences between Quantitative and Qualitative Research

The quantitative and qualitative forms of inquiry vary based on their underlying objectives. They are in no way opposed to each other; instead, these two methods are like two sides of a coin. The critical differences between quantitative and qualitative research are summarized in Table 1 .[ 1 , 10 , 11 ]

Differences between quantitative and qualitative research

Qualitative Research Questions and Purpose Statements

Qualitative questions are exploratory and are open-ended. A well-formulated study question forms the basis for developing a protocol, guides the selection of design, and data collection methods. Qualitative research questions generally involve two parts, a central question and related subquestions. The central question is directed towards the primary phenomenon under study, whereas the subquestions explore the subareas of focus. It is advised not to have more than five to seven subquestions. A commonly used framework for designing a qualitative research question is the 'PCO framework' wherein, P stands for the population under study, C stands for the context of exploration, and O stands for the outcome/s of interest.[ 12 ] The PCO framework guides researchers in crafting a focused study question.

Example: In the question, “What are the experiences of mothers on parenting children with Thalassemia?”, the population is “mothers of children with Thalassemia,” the context is “parenting children with Thalassemia,” and the outcome of interest is “experiences.”

The purpose statement specifies the broad focus of the study, identifies the approach, and provides direction for the overall goal of the study. The major components of a purpose statement include the central phenomenon under investigation, the study design and the population of interest. Qualitative research does not require a-priori hypothesis.[ 13 , 14 , 15 ]

Example: Borimnejad et al . undertook a qualitative research on the lived experiences of women suffering from vitiligo. The purpose of this study was, “to explore lived experiences of women suffering from vitiligo using a hermeneutic phenomenological approach.” [ 16 ]

Review of the Literature

In quantitative research, the researchers do an extensive review of scientific literature prior to the commencement of the study. However, in qualitative research, only a minimal literature search is conducted at the beginning of the study. This is to ensure that the researcher is not influenced by the existing understanding of the phenomenon under the study. The minimal literature review will help the researchers to avoid the conceptual pollution of the phenomenon being studied. Nonetheless, an extensive review of the literature is conducted after data collection and analysis.[ 15 ]

Reflexivity

Reflexivity refers to critical self-appraisal about one's own biases, values, preferences, and preconceptions about the phenomenon under investigation. Maintaining a reflexive diary/journal is a widely recognized way to foster reflexivity. According to Creswell, “Reflexivity increases the credibility of the study by enhancing more neutral interpretations.”[ 7 ]

Types of Qualitative Research Designs

The qualitative research approach encompasses a wide array of research designs. The words such as types, traditions, designs, strategies of inquiry, varieties, and methods are used interchangeably. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research.[ 1 , 7 , 10 ]

Narrative research

Narrative research focuses on exploring the life of an individual and is ideally suited to tell the stories of individual experiences.[ 17 ] The purpose of narrative research is to utilize 'story telling' as a method in communicating an individual's experience to a larger audience.[ 18 ] The roots of narrative inquiry extend to humanities including anthropology, literature, psychology, education, history, and sociology. Narrative research encompasses the study of individual experiences and learning the significance of those experiences. The data collection procedures include mainly interviews, field notes, letters, photographs, diaries, and documents collected from one or more individuals. Data analysis involves the analysis of the stories or experiences through “re-storying of stories” and developing themes usually in chronological order of events. Rolls and Payne argued that narrative research is a valuable approach in health care research, to gain deeper insight into patient's experiences.[ 19 ]

Example: Karlsson et al . undertook a narrative inquiry to “explore how people with Alzheimer's disease present their life story.” Data were collected from nine participants. They were asked to describe about their life experiences from childhood to adulthood, then to current life and their views about the future life. [ 20 ]

Phenomenological research

Phenomenology is a philosophical tradition developed by German philosopher Edmond Husserl. His student Martin Heidegger did further developments in this methodology. It defines the 'essence' of individual's experiences regarding a certain phenomenon.[ 1 ] The methodology has its origin from philosophy, psychology, and education. The purpose of qualitative research is to understand the people's everyday life experiences and reduce it into the central meaning or the 'essence of the experience'.[ 21 , 22 ] The unit of analysis of phenomenology is the individuals who have had similar experiences of the phenomenon. Interviews with individuals are mainly considered for the data collection, though, documents and observations are also useful. Data analysis includes identification of significant meaning elements, textural description (what was experienced), structural description (how was it experienced), and description of 'essence' of experience.[ 1 , 7 , 21 ] The phenomenological approach is further divided into descriptive and interpretive phenomenology. Descriptive phenomenology focuses on the understanding of the essence of experiences and is best suited in situations that need to describe the lived phenomenon. Hermeneutic phenomenology or Interpretive phenomenology moves beyond the description to uncover the meanings that are not explicitly evident. The researcher tries to interpret the phenomenon, based on their judgment rather than just describing it.[ 7 , 21 , 22 , 23 , 24 ]

Example: A phenomenological study conducted by Cornelio et al . aimed at describing the lived experiences of mothers in parenting children with leukemia. Data from ten mothers were collected using in-depth semi-structured interviews and were analyzed using Husserl's method of phenomenology. Themes such as “pivotal moment in life”, “the experience of being with a seriously ill child”, “having to keep distance with the relatives”, “overcoming the financial and social commitments”, “responding to challenges”, “experience of faith as being key to survival”, “health concerns of the present and future”, and “optimism” were derived. The researchers reported the essence of the study as “chronic illness such as leukemia in children results in a negative impact on the child and on the mother.” [ 25 ]

Grounded Theory Research

Grounded theory has its base in sociology and propagated by two sociologists, Barney Glaser, and Anselm Strauss.[ 26 ] The primary purpose of grounded theory is to discover or generate theory in the context of the social process being studied. The major difference between grounded theory and other approaches lies in its emphasis on theory generation and development. The name grounded theory comes from its ability to induce a theory grounded in the reality of study participants.[ 7 , 27 ] Data collection in grounded theory research involves recording interviews from many individuals until data saturation. Constant comparative analysis, theoretical sampling, theoretical coding, and theoretical saturation are unique features of grounded theory research.[ 26 , 27 , 28 ] Data analysis includes analyzing data through 'open coding,' 'axial coding,' and 'selective coding.'[ 1 , 7 ] Open coding is the first level of abstraction, and it refers to the creation of a broad initial range of categories, axial coding is the procedure of understanding connections between the open codes, whereas selective coding relates to the process of connecting the axial codes to formulate a theory.[ 1 , 7 ] Results of the grounded theory analysis are supplemented with a visual representation of major constructs usually in the form of flow charts or framework diagrams. Quotations from the participants are used in a supportive capacity to substantiate the findings. Strauss and Corbin highlights that “the value of the grounded theory lies not only in its ability to generate a theory but also to ground that theory in the data.”[ 27 ]

Example: Williams et al . conducted a grounded theory research to explore the nature of relationship between the sense of self and the eating disorders. Data were collected form 11 women with a lifetime history of Anorexia Nervosa and were analyzed using the grounded theory methodology. Analysis led to the development of a theoretical framework on the nature of the relationship between the self and Anorexia Nervosa. [ 29 ]

Ethnographic research

Ethnography has its base in anthropology, where the anthropologists used it for understanding the culture-specific knowledge and behaviors. In health sciences research, ethnography focuses on narrating and interpreting the health behaviors of a culture-sharing group. 'Culture-sharing group' in an ethnography represents any 'group of people who share common meanings, customs or experiences.' In health research, it could be a group of physicians working in rural care, a group of medical students, or it could be a group of patients who receive home-based rehabilitation. To understand the cultural patterns, researchers primarily observe the individuals or group of individuals for a prolonged period of time.[ 1 , 7 , 30 ] The scope of ethnography can be broad or narrow depending on the aim. The study of more general cultural groups is termed as macro-ethnography, whereas micro-ethnography focuses on more narrowly defined cultures. Ethnography is usually conducted in a single setting. Ethnographers collect data using a variety of methods such as observation, interviews, audio-video records, and document reviews. A written report includes a detailed description of the culture sharing group with emic and etic perspectives. When the researcher reports the views of the participants it is called emic perspectives and when the researcher reports his or her views about the culture, the term is called etic.[ 7 ]

Example: The aim of the ethnographic study by LeBaron et al . was to explore the barriers to opioid availability and cancer pain management in India. The researchers collected data from fifty-nine participants using in-depth semi-structured interviews, participant observation, and document review. The researchers identified significant barriers by open coding and thematic analysis of the formal interview. [ 31 ]

Historical research

Historical research is the “systematic collection, critical evaluation, and interpretation of historical evidence”.[ 1 ] The purpose of historical research is to gain insights from the past and involves interpreting past events in the light of the present. The data for historical research are usually collected from primary and secondary sources. The primary source mainly includes diaries, first hand information, and writings. The secondary sources are textbooks, newspapers, second or third-hand accounts of historical events and medical/legal documents. The data gathered from these various sources are synthesized and reported as biographical narratives or developmental perspectives in chronological order. The ideas are interpreted in terms of the historical context and significance. The written report describes 'what happened', 'how it happened', 'why it happened', and its significance and implications to current clinical practice.[ 1 , 10 ]

Example: Lubold (2019) analyzed the breastfeeding trends in three countries (Sweden, Ireland, and the United States) using a historical qualitative method. Through analysis of historical data, the researcher found that strong family policies, adherence to international recommendations and adoption of baby-friendly hospital initiative could greatly enhance the breastfeeding rates. [ 32 ]

Case study research

Case study research focuses on the description and in-depth analysis of the case(s) or issues illustrated by the case(s). The design has its origin from psychology, law, and medicine. Case studies are best suited for the understanding of case(s), thus reducing the unit of analysis into studying an event, a program, an activity or an illness. Observations, one to one interviews, artifacts, and documents are used for collecting the data, and the analysis is done through the description of the case. From this, themes and cross-case themes are derived. A written case study report includes a detailed description of one or more cases.[ 7 , 10 ]

Example: Perceptions of poststroke sexuality in a woman of childbearing age was explored using a qualitative case study approach by Beal and Millenbrunch. Semi structured interview was conducted with a 36- year mother of two children with a history of Acute ischemic stroke. The data were analyzed using an inductive approach. The authors concluded that “stroke during childbearing years may affect a woman's perception of herself as a sexual being and her ability to carry out gender roles”. [ 33 ]

Sampling in Qualitative Research

Qualitative researchers widely use non-probability sampling techniques such as purposive sampling, convenience sampling, quota sampling, snowball sampling, homogeneous sampling, maximum variation sampling, extreme (deviant) case sampling, typical case sampling, and intensity sampling. The selection of a sampling technique depends on the nature and needs of the study.[ 34 , 35 , 36 , 37 , 38 , 39 , 40 ] The four widely used sampling techniques are convenience sampling, purposive sampling, snowball sampling, and intensity sampling.

Convenience sampling

It is otherwise called accidental sampling, where the researchers collect data from the subjects who are selected based on accessibility, geographical proximity, ease, speed, and or low cost.[ 34 ] Convenience sampling offers a significant benefit of convenience but often accompanies the issues of sample representation.

Purposive sampling

Purposive or purposeful sampling is a widely used sampling technique.[ 35 ] It involves identifying a population based on already established sampling criteria and then selecting subjects who fulfill that criteria to increase the credibility. However, choosing information-rich cases is the key to determine the power and logic of purposive sampling in a qualitative study.[ 1 ]

Snowball sampling

The method is also known as 'chain referral sampling' or 'network sampling.' The sampling starts by having a few initial participants, and the researcher relies on these early participants to identify additional study participants. It is best adopted when the researcher wishes to study the stigmatized group, or in cases, where findings of participants are likely to be difficult by ordinary means. Respondent ridden sampling is an improvised version of snowball sampling used to find out the participant from a hard-to-find or hard-to-study population.[ 37 , 38 ]

Intensity sampling

The process of identifying information-rich cases that manifest the phenomenon of interest is referred to as intensity sampling. It requires prior information, and considerable judgment about the phenomenon of interest and the researcher should do some preliminary investigations to determine the nature of the variation. Intensity sampling will be done once the researcher identifies the variation across the cases (extreme, average and intense) and picks the intense cases from them.[ 40 ]

Deciding the Sample Size

A-priori sample size calculation is not undertaken in the case of qualitative research. Researchers collect the data from as many participants as possible until they reach the point of data saturation. Data saturation or the point of redundancy is the stage where the researcher no longer sees or hears any new information. Data saturation gives the idea that the researcher has captured all possible information about the phenomenon of interest. Since no further information is being uncovered as redundancy is achieved, at this point the data collection can be stopped. The objective here is to get an overall picture of the chronicle of the phenomenon under the study rather than generalization.[ 1 , 7 , 41 ]

Data Collection in Qualitative Research

The various strategies used for data collection in qualitative research includes in-depth interviews (individual or group), focus group discussions (FGDs), participant observation, narrative life history, document analysis, audio materials, videos or video footage, text analysis, and simple observation. Among all these, the three popular methods are the FGDs, one to one in-depth interviews and the participant observation.

FGDs are useful in eliciting data from a group of individuals. They are normally built around a specific topic and are considered as the best approach to gather data on an entire range of responses to a topic.[ 42 Group size in an FGD ranges from 6 to 12. Depending upon the nature of participants, FGDs could be homogeneous or heterogeneous.[ 1 , 14 ] One to one in-depth interviews are best suited to obtain individuals' life histories, lived experiences, perceptions, and views, particularly while exporting topics of sensitive nature. In-depth interviews can be structured, unstructured, or semi-structured. However, semi-structured interviews are widely used in qualitative research. Participant observations are suitable for gathering data regarding naturally occurring behaviors.[ 1 ]

Data Analysis in Qualitative Research

Various strategies are employed by researchers to analyze data in qualitative research. Data analytic strategies differ according to the type of inquiry. A general content analysis approach is described herewith. Data analysis begins by transcription of the interview data. The researcher carefully reads data and gets a sense of the whole. Once the researcher is familiarized with the data, the researcher strives to identify small meaning units called the 'codes.' The codes are then grouped based on their shared concepts to form the primary categories. Based on the relationship between the primary categories, they are then clustered into secondary categories. The next step involves the identification of themes and interpretation to make meaning out of data. In the results section of the manuscript, the researcher describes the key findings/themes that emerged. The themes can be supported by participants' quotes. The analytical framework used should be explained in sufficient detail, and the analytic framework must be well referenced. The study findings are usually represented in a schematic form for better conceptualization.[ 1 , 7 ] Even though the overall analytical process remains the same across different qualitative designs, each design such as phenomenology, ethnography, and grounded theory has design specific analytical procedures, the details of which are out of the scope of this article.

Computer-Assisted Qualitative Data Analysis Software (CAQDAS)

Until recently, qualitative analysis was done either manually or with the help of a spreadsheet application. Currently, there are various software programs available which aid researchers to manage qualitative data. CAQDAS is basically data management tools and cannot analyze the qualitative data as it lacks the ability to think, reflect, and conceptualize. Nonetheless, CAQDAS helps researchers to manage, shape, and make sense of unstructured information. Open Code, MAXQDA, NVivo, Atlas.ti, and Hyper Research are some of the widely used qualitative data analysis software.[ 14 , 43 ]

Reporting Guidelines

Consolidated Criteria for Reporting Qualitative Research (COREQ) is the widely used reporting guideline for qualitative research. This 32-item checklist assists researchers in reporting all the major aspects related to the study. The three major domains of COREQ are the 'research team and reflexivity', 'study design', and 'analysis and findings'.[ 44 , 45 ]

Critical Appraisal of Qualitative Research

Various scales are available to critical appraisal of qualitative research. The widely used one is the Critical Appraisal Skills Program (CASP) Qualitative Checklist developed by CASP network, UK. This 10-item checklist evaluates the quality of the study under areas such as aims, methodology, research design, ethical considerations, data collection, data analysis, and findings.[ 46 ]

Ethical Issues in Qualitative Research

A qualitative study must be undertaken by grounding it in the principles of bioethics such as beneficence, non-maleficence, autonomy, and justice. Protecting the participants is of utmost importance, and the greatest care has to be taken while collecting data from a vulnerable research population. The researcher must respect individuals, families, and communities and must make sure that the participants are not identifiable by their quotations that the researchers include when publishing the data. Consent for audio/video recordings must be obtained. Approval to be in FGDs must be obtained from the participants. Researchers must ensure the confidentiality and anonymity of the transcripts/audio-video records/photographs/other data collected as a part of the study. The researchers must confirm their role as advocates and proceed in the best interest of all participants.[ 42 , 47 , 48 ]

Rigor in Qualitative Research

The demonstration of rigor or quality in the conduct of the study is essential for every research method. However, the criteria used to evaluate the rigor of quantitative studies are not be appropriate for qualitative methods. Lincoln and Guba (1985) first outlined the criteria for evaluating the qualitative research often referred to as “standards of trustworthiness of qualitative research”.[ 49 ] The four components of the criteria are credibility, transferability, dependability, and confirmability.

Credibility refers to confidence in the 'truth value' of the data and its interpretation. It is used to establish that the findings are true, credible and believable. Credibility is similar to the internal validity in quantitative research.[ 1 , 50 , 51 ] The second criterion to establish the trustworthiness of the qualitative research is transferability, Transferability refers to the degree to which the qualitative results are applicability to other settings, population or contexts. This is analogous to the external validity in quantitative research.[ 1 , 50 , 51 ] Lincoln and Guba recommend authors provide enough details so that the users will be able to evaluate the applicability of data in other contexts.[ 49 ] The criterion of dependability refers to the assumption of repeatability or replicability of the study findings and is similar to that of reliability in quantitative research. The dependability question is 'Whether the study findings be repeated of the study is replicated with the same (similar) cohort of participants, data coders, and context?'[ 1 , 50 , 51 ] Confirmability, the fourth criteria is analogous to the objectivity of the study and refers the degree to which the study findings could be confirmed or corroborated by others. To ensure confirmability the data should directly reflect the participants' experiences and not the bias, motivations, or imaginations of the inquirer.[ 1 , 50 , 51 ] Qualitative researchers should ensure that the study is conducted with enough rigor and should report the measures undertaken to enhance the trustworthiness of the study.

Conclusions

Qualitative research studies are being widely acknowledged and recognized in health care practice. This overview illustrates various qualitative methods and shows how these methods can be used to generate evidence that informs clinical practice. Qualitative research helps to understand the patterns of health behaviors, describe illness experiences, design health interventions, and develop healthcare theories. The ultimate strength of the qualitative research approach lies in the richness of the data and the descriptions and depth of exploration it makes. Hence, qualitative methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

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