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Qualitative research is a method of inquiry employed in many different academic disciplines, traditionally in the social sciences, but also in market research and further contexts. Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior. The qualitative method investigates the why and how of decision making, not just what, where, when. Hence, smaller but focused samples are more often used than large samples.
In the conventional view, qualitative methods produce information only on the particular cases studied, and any more general conclusions are only propositions (informed assertions). Quantitative methods can then be used to seek empirical support for such research hypotheses.
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In the early 1900s, some researchers rejected positivism, the theoretical idea that there is an objective world which we can gather data from and "verify" this data through empiricism. These researchers embraced a qualitative research paradigm, attempting to make qualitative research as "rigorous" as quantitative research and creating myriad methods for qualitative research. In the 1970s and 1980s, the increasing ubiquity of computers aided in qualitative analyses, several journals with a qualitative focus emerged, and postpositivism gained recognition in the academy. In the late 1980s, questions of identity emerged, including issues of race, class, and gender, leading to research and writing becoming more reflexive. Throughout the 1990s, the concept of a passive observer/researcher was rejected, and qualitative research became more participatory and activist-oriented. Also, during this time, researchers began to use mixed-method approaches, indicating a shift in thinking of qualitative and quantitative methods as intrinsically incompatible. However, this history is not apolitical, as this has ushered in a politics of "evidence" and what can count as "scientific" research in scholarship, a current, ongoing debate in the academy.
Qualitative researchers face many choices related to data collection ranging from grounded theory practice, narratology, storytelling, classical ethnography, or shadowing. Qualitative methods are also loosely present in other methodological approaches, such as action research or actor-network theory. The most common method is the qualitative research interview, but forms of the data collected can also include group discussions, observation and reflection field notes, various texts, pictures, and other materials.
Qualitative research often categorizes data into patterns as the primary basis for organizing and reporting results. Qualitative researchers typically rely on the following methods for gathering information: Participant Observation, Non-participant Observation, Field Notes, Reflexive Journals, Structured Interview, Semi-structured Interview, Unstructured Interview, and Analysis of documents and materials.
The ways of participating and observing can vary widely from setting to setting. Participant observation is a strategy of reflexive learning, not a single method of observing. In participant observation researchers typically become members of a culture, group, or setting, and adopt roles to conform to that setting. In doing so, the aim is for the researcher to gain a closer insight into the culture's practices, motivations and emotions. It is argued that the researchers' ability to understand the experiences of the culture may be inhibited if they observe without participating.
The data that is obtained is streamlined to a definite theme or pattern. This is further worked on and alternative research hypothesis is generated which finally provides the basis of the research statement.
Some distinctive qualitative methods are the use of focus groups and key informant interviews. The focus group technique involves a moderator facilitating a small group discussion between selected individuals on a particular topic. This is a particularly popular method in market research and testing new initiatives with users/workers.
One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items. Survey items are piloted on study participants to test the reliability and validity of the items.
There are several different research approaches, or research designs, that qualitative researchers use. In the academic social sciences, the most frequently used qualitative research approaches include the following points:
10. Visual methods of data collection, including photo voice, photo elicitation, collaging, drawing and mapping have been used extensively as a participatory qualitative technique and to make the familiar strange 
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The most common analysis of qualitative data is observer impression. That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form.
Coding is an interpretive technique that both organizes the data and provides a means to introduce the interpretations of it into certain quantitative methods. Most coding requires the analyst to read the data and demarcate segments within it, which may be done at different times throughout the process. Each segment is labeled with a "code" – usually a word or short phrase that suggests how the associated data segments inform the research objectives. When coding is complete, the analyst prepares reports via a mix of: summarizing the prevalence of codes, discussing similarities and differences in related codes across distinct original sources/contexts, or comparing the relationship between one or more codes.
Some qualitative data that is highly structured (e.g., close-end responses from surveys or tightly defined interview questions) is typically coded without additional segmenting of the content. In these cases, codes are often applied as a layer on top of the data. Quantitative analysis of these codes is typically the capstone analytical step for this type of qualitative data.
Contemporary qualitative data analyses are sometimes supported by computer programs, termed Computer Assisted Qualitative Data Analysis Software. These programs do not supplant the interpretive nature of coding but rather are aimed at enhancing the analyst’s efficiency at data storage/retrieval and at applying the codes to the data. Many programs offer efficiencies in editing and revising coding, which allow for work sharing, peer review, and recursive examination of data.
A frequent criticism of coding method is that it seeks to transform qualitative data into empirically valid data, which contain: actual value range, structural proportion, contrast ratios, and scientific objective properties; thereby draining the data of its variety, richness, and individual character. Analysts respond to this criticism by thoroughly expositing their definitions of codes and linking those codes soundly to the underlying data, therein bringing back some of the richness that might be absent from a mere list of codes.
Some qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized; those summaries are then further summarized and so on. The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation.
A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data. While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary.
Some techniques rely on using computers to scan and reduce large sets of qualitative data. At their most basic level, mechanical techniques rely on counting words, phrases, or coincidences of tokens within the data. Often referred to as content analysis, the output from these techniques is amenable to many advanced statistical analyses.
Mechanical techniques are particularly well-suited for a few scenarios. One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain. Another scenario is when the chief value of a dataset is the extent to which it contains "red flags" (e.g., searching for reports of certain adverse events within a lengthy journal dataset from patients in a clinical trial) or "green flags" (e.g., searching for mentions of your brand in positive reviews of marketplace products).
A frequent criticism of mechanical techniques is the absence of a human interpreter. And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the "analysis" is still nonhuman. Analysts respond by proving the value of their methods relative to either a) hiring and training a human team to analyze the data or b) by letting the data go untouched, leaving any actionable nuggets undiscovered.
Contemporary qualitative research has been conducted from a large number of various paradigms that influence conceptual and metatheoretical concerns of legitimacy, control, data analysis, ontology, and epistemology, among others. Research conducted in the last 10 years has been characterized by a distinct turn toward more interpretive, postmodern, and critical practices. Guba and Lincoln (2005) identify five main paradigms of contemporary qualitative research: positivism, postpositivism, critical theories, constructivism, and participatory/cooperative paradigms. Each of the paradigms listed by Guba and Lincoln are characterized by axiomatic differences in axiology, intended action of research, control of research process/outcomes, relationship to foundations of truth and knowledge, validity (see below), textual representation and voice of the researcher/participants, and commensurability with other paradigms. In particular, commensurability involves the extent to which paradigmatic concerns "can be retrofitted to each other in ways that make the simultaneous practice of both possible". Positivist and post positivist paradigms share commensurable assumptions but are largely incommensurable with critical, constructivist, and participatory paradigms. Likewise, critical, constructivist, and participatory paradigms are commensurable on certain issues (e.g., intended action and textual representation).
Qualitative research in the last ten years also has been characterized by concern with everyday categorization and ordinary storytelling. This "narrative turn" is producing an enormous literature as researchers present sensitizing concepts and perspectives that bear especially on narrative practice, which centers on the circumstances and communicative actions of storytelling. Catherine Riessman (1993) and Gubrium and Holstein (2009) provide analytic strategies, and Holstein and Gubrium (2012) present the variety of approaches in recent comprehensive texts. Relatedly, narrative practice increasingly takes up the institutional conditioning of narrative practice (see Gubrium and Holstein 2000).
In quantitative studies, this is referred to as 'validity'. A central issue in qualitative research is trustworthiness (also known as credibility and/or dependability). There are many different ways of establishing trustworthiness, including: member check, interviewer corroboration, peer debriefing, prolonged engagement, negative case analysis, auditability, confirmability, bracketing, and balance. Most of these methods are coined, or at least extensively described by Lincoln and Guba (1985)
By the end of the 1970s many leading journals began to publish qualitative research articles and several new journals emerged which published only qualitative research studies and articles about qualitative research methods. In the 1980s and 1990s, the new qualitative research journals became more multidisciplinary in focus moving beyond qualitative research’s traditional disciplinary roots of anthropology, sociology, and philosophy.
Wilhelm Wundt, the founder of scientific psychology, was one of the first psychologists to openly conduct qualitative research as part of his series of experiments. Early examples of his qualitative research were published in 1900 through 1920, in his 10-volume study, Völkerpsychologie (translated to: Social Psychology). Wundt advocated the strong relation between psychology and philosophy. He believed that there was a gap between psychology and quantitative research that could only be filled by conducting qualitative research. Qualitative research dove into aspects of human life that could not adequately be covered by quantitative research; aspects such as culture, expression, beliefs, morality and imagination.
There are records of qualitative research being used in psychology before World War II, but at the time these methods were viewed as invalid forms of research. Due to the lack of acceptance, many of the psychologists who practiced qualitative research denied the usage of such methods or apologized for doing so. It was not until the late 20th century when qualitative research was becoming widely accepted in the world of psychology. The excitement about the groundbreaking form of research was short-lived since many of the pioneering studies with qualitative research had already been conducted. This left many psychologists without the recognition they deserved for their significant work in the field of research.
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