Qualitative Research - Science method

Among the books that cover this subject, I prefer Rubin & Rubin, The Art of Hearing Data.

Are you looking for repositories that make qualitative data available for secondary analysis? If so, you might consider the Qualitative Data Repository at Syracuse University.

There is a current trend towards including "positionality" statements in articles that used qualitative research. I have not see any consensus on where such statements should be placed, however.

Identify first the variables (experiences, challenges, joys) you will study to decide which approach fits (Phenomenology, Case Study, etc.)

You could look at The Qualitative Data Repository at Syracuse University.

Nghiên cứu được chia thành hai loại chính: nghiên cứu định lượng và nghiên cứu định tính. Dưới đây là sự khác nhau giữa hai loại nghiên cứu này:

Tuy hai loại nghiên cứu này có phương pháp thu thập và phân tích dữ liệu khác nhau, nhưng thực tế thường có sự kết hợp giữa các phương pháp và kỹ thuật của cả hai trong nhiều nghiên cứu. Sự lựa chọn giữa nghiên cứu định lượng và nghiên cứu định tính phụ thuộc vào mục tiêu nghiên cứu, câu hỏi nghiên cứu, và tính chất của dữ liệu được thu thập.

I will humbly offer my own book, Basic and Advanced Focus Groups (2019). Sage.

i would love to

Thank you so much - very helpful.

My very thanks to you Dear Dr. Seyyed Masih Rajaei-Almousavi

If you are trying to download the book from its publisher, Sage, they are only give you a sample chapter, rather than free copy of the whole book. But if you search the internet, you may well find a "pirated" copy -- which is, of course, illegal.

Hello, I am a PhD scholar working in the area of inclusive education but not exactly your research topic. I would love to collaborate to you.

Case report is qualitative study but every qualitative study is not case report

Qualitative Reliability

Reliability is more difficult to assess in qualitative research, because the goal of developing and describing categories, rather than counting behaviors in those categories, precludes rigorous measurement procedures. Although replication at a second data site might be considered to be like test-retest reliability, strict replication is generally considered impossible by ethnographers because of the lack of standardized controls and because the behavior of people is never static (LeCompte & Preissle, 1993, p. 332). In addition, each site studied to some extent is unique. Multiple sites produce different data sets, which may reveal much about the variability of behavior and the range of contexts but less about reliability.

The concern for convergence (reliability) within the quantitative paradigm can be contrasted with the desire for divergence (developing many categories and elaborating or refining them) within the qualitative paradigm. The empirical world is in constant flux, individuals within it are continually creating and recasting events experienced within ever-changing perceptual and conceptual frameworks (Blumer, 1969b, p. 23). Different persons--including different researchers-- construct the world in distinct ways, thus limiting inter-observer reliability; likewise, any one researcher can change constructions within a short time, decreasing intraobserver reliability--indeed, this is a goal of qualitative research. Reliability describes the consistency of the measuring instrument, and the instrument in qualitative research is the researcher. Likewise test-retest reliability can only be approximated because the test instrument--again, the researcher--is not exactly the same at two points in time (Lincoln & Guba, 1985, pp. 298-299).

A paradox of qualitative research is when the researcher is maximally changing ways of looking at things because of the data observed, reliability as traditionally understood is minimized. It is minimal not because observation is less trustworthy, but because observed data make a difference in how perceptions are conceptualized. It might even be argued that consistencies between observations are more likely to be due to consistent researcher bias rather than to the data being consistently observed. More important than reliability, therefore, is the issue of validity.

However, some qualitative researchers suggest that a degree of reliability is desirable. Reliability is fostered by using low-inference descriptors; comparing multiple observers viewing the same events, which is inter-rater reliability; using research assistants; asking peers to examine findings; or mechanically recording data (LeCompte & Preissle, 1993, pp. 338-340). Reliability could also be represented in terms of the consistency in sorting behaviors into categories or consistency in designating behaviors by function.

In my own dissertation study qualitative reliability is fostered both interpersonally and mechanically. My two sons developed and revised major categories of events and behaviors listed by children interviewed in my hallway study. In the process the boys and I discussed these categories at length, particularly in relation to what activities belonged to which categories. After numerous discussions and changes in categories, over several days' time, we eventually achieved complete agreement in categorizing the behaviors and events within categories.

In addition qualitative reliability is addressed mechanically through the use of videotaping observations and audiotaping interviews. These have not yet been analyzed for reliability through complete transcription; partial transcription procedures were used, but several transcriptions of the same tapes using multiple transcribers is anticipated in the future. Some qualitative methodologists suggest that strict measures of qualitative reliability are impossible and thus rely on indications of validity because the presence of validity implies reliability (Benson, 1994; Lincoln & Guba, 1985, p. 316). Lincoln and Guba (p. 317) also suggest that overlapping findings from different methods of research also indicate reliability, which is a procedure used occasionally in this research study. However, this is perhaps better understood as an indication of convergent validity rather than a measure of reliability, to be considered shortly.

Internal Validity

Internal validity is a major strength in qualitative research (LeCompte & Preissle, 1993, p. 341), evidenced in several ways. Lincoln and Guba (1985, pp. 301-304) emphasize the importance of a lengthy stay in a naturalistic setting, allowing for extended engagement with persons that can reveal the researcher's distortions and selective perceptions. An extended time in the field also allows patterns of behavior to stabilize, which is essential for reliability as well as validity. A lengthy stay also provides informants the opportunity to develop trust in the researcher, imperative for revelation of perspectives. Persistent observation in the research context also provides depth and focus, as more attention is given to multiple influences that surface and detailed analysis is given to those factors that are most relevant or salient while avoiding premature closure. Persistence takes place with an attitude of skepticism, as premature closure on an issue may result in the easy acceptance of deception or pretense to be socially acceptable. The depth resulting from persistent observation balances the breadth that a lengthy stay in the field produces, Lincoln and Guba emphasize. In addition to a lengthy stay with persistent observation, validity is enhanced by reliance on informant interviews for data and by the researcher's constant self-monitoring (LeCompte & Preissle, 1994, pp. 342-348).

I studied the school in my dissertation over a four month period, which can be considered a lengthy period of time. Throughout that time I continually monitored my perceptions and impressions through personal notes and theoretical notes, which are considered in detail in later chapters. This self- monitoring, as well as the extended period of observing allowed me to correct misconceptions and observe the many varieties of the social formations considered. Some of these misconceptions and self-corrections are considered in Chapter Five. I also note in several places my surprise at certain findings, another indication of self-monitoring and thus internal validity. In addition, the several sessions of interviews allowed time for trust to develop with children, evidenced by describing behavior in which they participated that was forbidden and punished; they would be unlikely to do so with other adults in the school due to lack of trust. The depth and breadth of the study are indicated by the description of findings in Chapters Five through Eleven of my dissertation (available on ResearchGate).

Triangulation also helps establish the validity of qualitative research. Triangulation involves obtaining multiple perspectives of the same event; when those perspectives coincide or are similar, this suggests some degree of validity. Several forms of triangulation for establishing validity have been suggested (Patton, 1990, pp. 464-470; Lincoln & Guba, 1985, pp. 305-307). When both qualitative and quantitative procedures produce equivalent results, this is a form of source triangulation. Within the quantitative paradigm, this might be considered convergent validity, without a coefficient, comparing multiple methods in the multitrait-multimethod approach to validity (see Crocker & Algina, 1986, pp. 232-235). Although Lincoln and Guba suggest that discrepant findings between qualitative and quantitative methods indicate the likelihood of error in one of the methods, Patton believes that discrepancies may reflect different kinds of questions being answered as well as the difficulties involved in determining convergence.

Source triangulation is evidenced by the use of both qualitative and quantitative procedures in my study. For example, my impression that phalanxes were more common than clusters, recorded in field notes during observations, was confirmed by quantitative measurement using videotapes. Other examples of convergence between qualitative and quantitative procedures are considered in later chapters on findings.

A second variety is method triangulation, comparing the results of different qualitative procedures. Again, Patton emphasizes that discrepant findings do not necessarily indicate invalid results; rather they may reflect the need to discover why and when those differences occur--different methods may capture different aspects of behavior. In addition multiple investigators or data analysts can be triangulated to determine consistencies, although this requires close communication so that both observers or analysts are studying the same thing.

Several interactive and non-interactive methods were used in my study, which converged occasionally. Many of the comments of children were consistent with what I had observed earlier, even though I purposefully framed questions to them that would not be leading. However, consistent with Patton's comment, there were also differences, particularly in that children described a wider variety of activities than what I observed. This underscored my preoccupation with social formations, which is consistent with my theoretical framework, but also indicated that I overlooked many specific hallway events, such as children sharing food with one another, while doing earlier observations. It is also likely that some of these activities children described were hidden from me during observations but willingly explicated after trust had developed during interviews.

During my research, I asked the undergraduate student who helped with videotaping to keep a record of trends she observed. I gave her no guidelines in this respect. She only jotted a few comments, but these underscored several trends I had observed earlier. Teacher comments during interviews at the conclusion of the study could also be considered multiple investigator triangulation, and convergence between these comments and my findings from observations and interviews of children are noted in later chapters. The videotapes and cassettes recorded potentially allow further triangulation by others in the future.

Lincoln and Guba do not favor the use of theoretical triangulation because they believe that multiple theories explaining the same phenomenon do not indicate evidence for the existence of the phenomenon. Patton, in contrast, emphasizes the value of theory triangulation because this process reveals how different premises and assumptions influence interpretation. I used a limited degree of theoretical triangulation by relating some findings to the two theories that framed the study, theories by Hall and Blumer.

Benson and Hagtvet (in preparation) use theory differently to establish validity. They suggest that multiple studies reflect different aspects of a given theory. These studies can produce results consistent with predictions by different aspects of the theory. The congruities between divergent theoretical predictions and empirical findings constitute a "nomological network" variety of construct validity. This nomological network can be conceptualized as triangulating multiple studies within different aspects of a theoretical framework. Benson and Hagtvet apply this form of validity analysis for quantitative data, but it might be adapted for qualitative validity as well, a possibility I wish to investigate in the future.

LeCompte and Preissle (1994, pp. 341-348) emphasize that qualitative validity is enhanced by the researcher who stays open by means of self-monitoring and the active search for negative cases; this is also emphasized by Lincoln and Guba (1985, pp. 309-313) and Patton (1990, pp. 463- 464). Mehan (1979, p. 20) notes that the search for negative cases helps accomplish the goal of accounting for all incidents, as he does in his three step analysis of teacher-student interaction. The search for negative cases was used in my data analysis, as detailed in Chapter Five of my dissertation, although I note that accounting for every case can be an ideal not always reached.

Interview data are likely to counteract preconceived notions, assuming interviews are open- ended and not unduly influenced by the researcher's constructs, suggest LeCompte and Preissle. My interviews were to some extent open-ended, as I allowed and sometimes encouraged students to discuss related and even tangential issues, and I attempted to avoid leading probes. I encouraged openness rather than premature closure; for example, several times a member of a group would make a comment, to which others agreed, and I would inject a discrepant comment made by a child in another group to encourage discussion of different viewpoints. Yet it is possible that I unconsciously encouraged some reactions by unconscious body language. Some of my questions were clearly related to what I had observed earlier and a-priori theoretical concerns, but I attempted to encourage children to contradict my views if they wished. To some extent the degree of open- endedness and researcher construct contamination may be evaluated by examining interview protocols in Appendix A and my interview approach described in Chapter Four of my dissertation.

Member checks, in which a sample of those studied and others who share the context of the study are asked to verify, dispute, or revise categories and other emergent findings, can also contribute to conclusions on validity, though this procedure is not without its difficulties (Lincoln & Guba, 1985, pp. 314-316). Blumer (1969b, p. 22) similarly speaks of those being studied "talking back" to the researcher, correcting unrealistic portrayals of their views. Member checks were used throughout interviews, as I sometimes paraphrased what one or more children had said previously, either within the group or from another group, and asked if my understanding was accurate. I also used summary member checks of both children and teachers at the conclusion of the study, and both convergent and divergent results are reported in later chapters.

Ultimately, concludes Patton (pp. 468-469), qualitative validity is established by evidence of believability of findings such as including sufficient raw data in the report, such as quotations from participants, and remaining open-ended so that readers are allowed to reach conclusions on their own and develop at least some of their own generalizations. I provide numerous citations of children in later chapters, raw data as evidence for my conclusions. I also encouraged children to make some generalizations during interviews, again evidenced by protocols in appendix A.

Another means of confirming the trustworthiness of qualitative research is through the use of an "audit trail" (Lincoln & Guba, 1985, pp. 319-320), which involves the researcher archiving research materials. These include raw data in the form of videotapes or handwritten field notes, the products of data reduction and analysis such as theoretical notes, indications of data synthesis and reconstruction such as reports and descriptions of category structure development, notes on the process of research such as methodological notes, documents that reflect dispositions and intentions such as personal notes and the research proposal, and information about instruments used such as forms and schedules. These can then be made available for an external audit. The "audit trail" is valuable for both qualitative and quantitative research, Lincoln and Guba claim. I have archived hundreds of pages of notes, as well as many hours of videotape and cassette tapes, which constitute an audit trail that can be examined. Some of these notes are included in later chapters, which constitute a partial audit trail.

In conclusion, it can be noted that internal validity is addressed in many different ways by qualitative researchers. Several of these are considered in my research. The establishment of internal validity involves the degree of confidence placed upon findings, not absolute determination.

External Validity

LeCompte and Preissle (1993, pp. 349) describe external validity as the degree to which a research site is typical, and the likelihood of generalizing results. The credibility of applying findings to alternate sites is affected by the selection of persons studied, the setting in which they are studied, the distinct historical background and situation at the time of the study, and the degree to which the constructs defined are shared across people, settings, and time.

Ethnographic researchers often perceive external validity differently than those scholars operating from the quantitative perspective. In qualitative research, establishing applicability to other sites is considered a joint venture of the researcher and the one making the application. It is important that researchers fulfill their obligations in establishing external validity by describing those studied, the context, and other aspects of the research process, but just as important is the task of the individual who wishes to apply findings to an alternate site. The qualitative researcher provides the data from which generalization is possible, but specific application to other contexts requires knowledge of the second context, which the researcher does not possess (Lincoln & Guba, 1985, p. 316).

I directly addressed external validity in my dissertation study to only a minor extent. This was done by comparing the lower elementary wing of Pellegrini elementary with the main site studied, the upper elementary wing of the same school. Convergent comparisons with other schools cited from the literature can also be considered a way of addressing external validity. More important, I describe in detail numerous aspects of the school environment and surrounding community in the next chapter, providing the basis for future attempts at generalization to other schools. Someone who wishes to make generalizations can compare these characteristics with those of the site to which findings are to be generalized to determine the degree of similarity and thus generalizability. In the next chapter I will make the case that a greater number and greater diversity of constructs emerge from an ideal site like Pellegrini elementary than would be found at a more typical site, thus the likelihood of generalizing certain constructs is greater at an ideal rather than typical site. Finally, I hope that other researchers will study additional sites that are very different from Pellegrini elementary to determine the commonalities across divergent contexts. Commonalities found across very different kinds of contexts suggest the likelihood of greater generalizability.

Summation

Validity and reliability are important in qualitative research, often discussed under the rubrics of credibility or trustworthiness. As noted, some of the qualitative validity issues raised here are more specifically addressed in later chapters on setting, participants, and methodology, although not always overtly linked with the topic of validity.

Although quantitative reliability is addressed in this study by using percentage of agreement and kappas, quantitative validity is not as well addressed in the dissertation as the qualitative equivalent. Because multiple sites have not been investigated and the sampling of quantitative data herein is quite limited and less than random, conclusions about quantitative data must remain suggestive and tentative. However, to the degree that those conclusions coincide with qualitative data, the possibility of validity can be inferred by considering triangulation to be a form of convergent validity between quantitative and qualitative approaches. Perhaps some of the hypotheses suggested will, with further study in other contexts, become theories that can be tested through the nomological network form of construct validity.

For full reference details, see my dissertation which is posted on ResearchGate.

Edim Eka James I look forward to learning from the contributors here. Cheers.

Have a look at this pepar and may be you'll be able to find one.

I am not sure what your questions is, because qualitative interviews are always composed of a series of open-ended questions. Can you tell us more about your research questions and goals?

You will chapters on this in most of the major textbooks on grounded theory, such as Birks and Mills, Grounded Theory: A Practical Approach, and Charmaz, Constructing Grounded Theory.

Thank you Mr Barry, for your answer. I would like to send you three more...

1) How can we be sure, that the data, which is obtained, through complex algorithms, does not involve human error or human influence?

2)The Management of Crisis, usually works in the following ways: Rational Management. Emotional Management. Artificial Management (Rational + Emotional). Which way would you trust, and why?

3)Why is imperative, to have legislative regulation, in applications that use (AI)?

I appreciate your help.

With regards,

Kopitsa K.P.

Hello

My expertise and field of activity is sociological issues in sports and I am working on a review article. If it helps you, I will send you the articles in the field of sports.

Psychological effects of COVID -19 we studied in UK.

Frontline Healthcare Professional’s Acute Stress Disorder during Covid-19

In quantitative research, reliability and validity apply to concerns about measurement, but in qualitative research we do not measure anything, so reliability and validity are not nearly as relevant. Indeed, many qualitative researchers refuse to accept this terminology and you may find yourself in trouble with reviewers if you do use it.

The basic reasoning behind this is that qualitative research is inherently subjective and interpretive, so there is no reason to expect another researcher to come to the same conclusions. Commonly used alternatives (especially to validity) are trustworthiness and credibility.

academic research

There is quite a bit of debate about whether the terms reliability and validity are appropriate for qualitative research. ss far as I can tell, however, the majority opinion is that they are not.

For example, reliability in quantitative research is based on the idea that two different measurements of the same phenomenon should return equivalent results. But in qualitative research we do not measure things, and we recognize that the subjectivity of the researcher can often lead to different insights when examining any aspect of social life.

For validity, in quantitative research, one common formulation is that we measure what we intend to measure in a way that minimizes bias. But in qualitative research, we are far more likely to be exploratory, with a goal of describing something in a meaningful way, other than separating out "true scores" from sources of bias.

In terms of how these terms are replaced in qualitative research, one of the most influential treatments is in Lincoln and Guba's 1985 book, Naturalistic Inquiry. You can find a nice summary of their ideas at:

In addition to what David Coker suggests, you might consider dyadic interviews where you bring pairs of experts together to compare there experiences and perceptions. This can work especially well for online interviews.

This kind of design is sometimes referred to as "embedding" and I have attached an article that uses this approach. My personal opinion is that most of the designs I have seen with clinical trials fall into two of the classic categories in mixed methods, either exploratory sequential (qual --> QUAN) or explanatory sequential (QUAN --> qual). In the first case, qualitative methods are used to help create aspects of the trial. In the second case, aspects of the trial are followed by qualitative methods to help understand the outcomes of the trial.

Dear Doctor

Go To

"Shulman (1986) asserts that no single approach can capture the full set of educational events and implies that the insufficiencies of particular programs can be overcome through proper blending with the insufficiencies of other programs. It seems that maybe the results from a qualitative study can lead to the quantification of certain components in order to conduct a quantitative study for a better understanding and evaluation,, or a small component of a cause and effect quantitative study can be qualitatively studied to result in a better understanding of the cause and effect results of a quantitative study. A quantitative study can be conducted along with a qualitative study, or qualitative with quantitative, but each approach should not be analyzed and judged by the criteria associated with the other approach. There can be basketball or football, or football and basketball, but not football on a basketball court, nor basketball on a football field. The essence of the game would be lost just like the essence of a research study would be compromised if it were to be conducted outside its own context. "

I have just published an article (attached) that examines the use of ChatGPT for qualitative data analysis. In my opinion it would be difficult to use this approach for what Braun and Clarke (2022) now call Reflexive Thematic Analysis, because they rely heavily on an initial process of open coding, whereas ChatGPT uses a query and response format that addresses the content of the data more generally.

If you could use AI strictly for coding, then I suspect it would be much less disruptive than using it to replace coding. For two attempts at this latter strategy, you can look at the contrasting implementations of ChatGPT in ATLAS.ti and MAXQDA.

ATLAS.ti attempts to automate the entire coding process by using a single command from ChatGPT to generate a complete set of codes. I have tried this, as have several of my colleagues, and all of us came away disappointed at best. The problem is that the program generates hundreds of codes which then need to be checked and categorized by hand.

MAXQDA takes a very different approach by using ChatGPT to summarize various aspects of the coded data, such as all the content associated with a given code. The obvious limitation here is that you have to have your data fully coded before you can apply ChatGPT.

Maybe someone will find a use for ChatGPT in the coding process, but so far I have not heard of it.

RV Krejcie and DW Morgan,Educational and Psychological Measurement, 1970,30:607-610, gave a table to choose sample size. Also MA Hertzog ,Research in zNursing and Health,2008,31:180-191. Suggested that sample sizes should be higher that 40. REGARDS.

If you are indeed planning on shifting your methods, one of the key things I would highlight about quantitative research is that is typically much more expensive than qualitative research. In particular, survey research requires large, high quality samples that are difficult to gather without external funding.

You are indeed addressing an issue that is not formally codified in empirical qualitative social research.

David L. Morgan rightly points out the important argument: If 'n' (number of subjects in the survay) is very small, an indication of the number or percentage suggests an empirical and/or statistical representation that is not considered scientifically valid compared to the corresponding population. Do not be so impressed by the positions of your reviewers - they seem to disagree on this point as well. From this point of view, deal with the issue offensively: Explain how you proceed and why. And then you can use terms like 'one', 'half' or 'almost all'.

When discussing numbers and percentages, we should not ignore the essential underlying meaning of qualitative methods. Especially in the course of explorative research, qualitative methods are used to identify possible casual references in the first place and to initiate a process of theory building. In this way, theoretical approaches and empirical findings can later be coordinated and aggregated at a higher level. Only on such a basis does it make sense to use quantitative methods and to report formal numbers and percentages.

Where i can see your tools? Thank you.

Your efforts are appreciated

Your efforts are appreciated

The very simple way to understand that you have collected sufficient data is that when you got the same answer from the respondent again and again, i mean you are not getting any new information form sespondents.

Kurt Engelhart email: [email protected]

Dear Abhishek Kumar Pandey,

did a similar research for my PhD and published an article about the methodology used:

All the best,

Tomaž

Thematic analysis is all about the analysis of textual data, emphasizing such processes as reading the data for familiarization, coding the data to highlight similar content, grouping codes into larger themes, etc. I cannot imagine a parallel process for quantitative data.

I am a student of Qualitative methods. My own dissertation was Qualitative and I have since supported many Qualitative students through their own dissertations. Speaking from my personal experience in dissertation writing, I had not been prepared to be knowledgeable about all of the qualitative methods available, thus I selected the most obvious and my Chair supported me. His support was invaluable! Having had that experience myself, I encourage my students to explore the various ways in which qualitative research can be accomplished, select two or three that are appealing to them and that reflect a path for what they want to know, and present those options to me in a discussion (always remote). Then, together we will decide on the appropriate path. I rarely change the path the student has chosen, particularly if the student has a good argument for their choice, but I will explore other options they have mentioned if I see a stronger opportunity for them to accomplish their goal. There are two learnings from this process for me. First, it requires the student to explore their options and have a voice in their chosen approach to the research, which causes them to work harder to have it work. Second, since we have discussed and agreed that the process chosen is appropriate for the topic under study, it requires me to be available to support the student as needed, determined by their progress and learnings. I often find that students expect their Qualitative study to be easier than a quantitative study would be. If you are a statistician, that will probably be true. However, if you are not a statistician it definitely will not be. For those who think Qualitative study is a walk in the park, getting the student(s) to interact with me can be challenging and I sometimes have to require it of them. Others who understand that I do have both personal and vicarious experience with the ins and outs of qualitative research welcome my insights and tips. Finally, I have had more than one student choose to do a mixed-methods study (both quantitative and qualitative). One of their reasons is to become more capable in quantitative research. Knowing that quantitative is not my strong suit, I encourage such students to identify a quantitative expert to be a member of their Committee. This has worked well for everyone concerned.

You are correct: structural equation modeling is a statistical technique that typically requires a large sample.

Various versions of this questions have been asked before on RG, and the typical consensus is that your choice of methods depends on your research question. In other words, different methods have different strengths, so one is only "better" than another when you are referring to a specific goal that you want to reach.

Writing a research paper typically involves a series of steps, from selecting a research topic to submitting the final paper for publication. Here are the general steps you can follow:

Remember that the specific steps and requirements may vary depending on the field of study, the type of research paper (e.g., empirical, review, theoretical), and the publication outlet. Always consult the guidelines provided by your institution or the target journal/conference for detailed instructions.

If you can do correlations with measures of "other established tools," then that is all you need for discriminant validity and convergent validity, as well as other aspects of construct validity.

Given your small sample size, you might consider using a p value cut-off of .10 instead of .05

Thanks dear Chuck A Arize for your suggestion. I'm currently using MAXQDA.

Thank you for the article recommendations

I have recently been experimenting with artificial intelligence for the interview of qualitative data via ChatGPT, and I am very impressed with the results. In particular, I started by re-analyzing data from two of my previous studies, and I was surprised by how rapidly the program produced the main concepts from those studies.

Just asking a few general questions produced the important key dimensions, and asking follow-up questions gave more detailed information about each of those dimensions. Of course, the program cannot literally "interpret" the results for you, but it certainly could replace a laborious coding process as a tool for locating the core content that you need to interpret.

Like any other approach to qualitative analysis, it does require familiarity with your data (you can't just throw anything at it), but beyond that, the program has a strong potential for being an alternative to existing techniques for the initial stages of working with qualitative data.

My personal opinion is that there is not much difference. Lincoln and Guba (1985) were the originators of the paradigm framework, along with their chapters over the years in the various editions of the Denzin & Lincoln handbook, and they always referred to Constructivism. I do, however, have an impression that Interpretivisim might be more commonly used in Britain while Constructivism is favored in the U.S.

Qualitative approaches do not generally use the language of variables, and many of them would not agree with using pre-conceived concepts as your starting point. In contrast, quantitative research frequently "operationalizes" concepts into measurable variables.

I think you need to be clear about what your goals are before you reach the point of considering concepts versus variables. For example, are you testing hypotheses or generating them?

What we do with the demographic data will determine whether you have a qualitative approach towards it or a quantitative one. Of course, your research question will also determine the direction of your research and what you would like to do with the data. For instance, If you are searching for a cause and effect/ impact from the demographics, it is a quantitative approach you are bent towards.

Moreover, mixed methods recommend various designs, including a sequential path you may want to refer to. Several research papers in this domain may help you decide how to take this further.

All research has, at some level, interpretivism (though many deny it). You can apply interpretivism at a micro and macro level. Having two groups with different situations, like one group who graduated college and one group who dropped out, is frequently used (you could have more groups). A caveat: Don't assume super homogeneity. Talk about the outliers, the stubs of data that do not fit, and group overlap.

The big four in types of qualitative research are Ethnography, Phenomenology, Grounded Theory and Historical case studies. These also have subtypes and/or different researchers approach to them. They also are quite different in their goals and approaches. Other types now that are more recent include Narrative research and Action research. Good luck with your project.

Dear Frank,

as long as you have at least two cases that differ on at least one exogenous variable and one endogenous variable, you can use QCA (Thiem 2014, 2022). As long as you have this minimal degree of variation on your 8 cases, you should be fine.

Best wishes

Alrik

References

Thiem, Alrik. 2014. "Navigating the Complexities of Qualitative Comparative Analysis: Case Numbers, Necessity Relations, and Model Ambiguities." Evaluation Review 38 (6):487-513.

Thiem, Alrik. 2022. "Qualitative Comparative Analysis (QCA)." In Handbook of Research Methods in International Relations, ed. R. J. Huddleston, T. Jamieson and P. James. Cheltenham: Edward Elgar. Open access at:

How about calling it a "longitudinal case study"?

It sounds like you are doing something related to cognitive interviewing. If so, this is widely accepted research procedure that does not need to be justified according to any particular set of philosophical assumptions.

A qualitative research methodology is a systematic approach to gathering and analyzing non-numerical data to understand people's experiences, perspectives, and social phenomena. It involves techniques such as interviews, observations, and document analysis to uncover underlying meanings and patterns. Qualitative research provides a detailed and context-specific understanding, contributing to a more profound knowledge of individuals, groups, and social dynamics. Here are some helpful textbooks.

Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry & research design: Choosing among five approaches (4thed.). SAGE. https://us.sagepub.com/en-us/nam/qualitative-inquiry-and-research-design/book246896

Marshall, C., Rossman, G. B., & Blanco, G. L. (2022). Designing qualitative research (7th ed.). SAGE. https://us.sagepub.com/en-us/nam/designing-qualitative-research/book274291

Good luck,

I will use JBI because is more robust the the others like CASP

"Qualitative Inquiry in Education". Esta revista se dedica específicamente a promover la investigación cualitativa en el ámbito educativo, incluyendo enfoques y metodologías relacionadas con la evaluación.

There are many options for qualitative research among the geriatric population. Some of the most common methods include:

You seem to have used one of the less common mixed methods research designs: quan --> QUAL. Due to its relative rarity, it does not have an agreed upon name, and there isn't any consensus on how to report it. I do devote a chapter to it in my book, Integrating Qualitative and Quantitive Methods, if that is any help.

Content analysis and thematic analysis are two widely used methods of qualitative data analysis in research . While they can be used for similar data sets, there are distinct differences between the two methods.

Content analysis is a systematic approach to analyzing the content of text-based data. This method involves organizing and categorizing data into specific codes or categories based on predetermined criteria. Content analysis can be either quantitative or qualitative, but it is commonly used for quantitative research. The aim is to identify and quantify patterns, themes, or trends in a large amount of data.

On the other hand, thematic analysis is a method of analyzing qualitative data. This method involves identifying and analyzing patterns or themes that emerge from the data itself. Unlike content analysis, thematic analysis does not rely on predetermined categories and codes. It is a more flexible and inductive approach to data analysis, allowing themes to emerge directly from the data. Thematic analysis is a more interpretive and nuanced approach to data analysis, with a greater emphasis on the context in which the data was produced.

Overall, the main difference between content analysis and thematic analysis is that content analysis is more focused on quantifying patterns and trends in data , while thematic analysis is more focused on understanding the meaning and context of the data.

If these theoretical issues did not influence either your data collection or your analysis, then you do not need to mention them in your earlier chapters. This early chapters should, however, make it clear that you are doing things this way. In particular, you can say that you are beginning with an exploratory approach, and that you will compare to eating theories after you complete your exploration.

Thank you. I agree. Great book.

First, there is no point in reporting counts of themes when you have an N of only eight. Second, "negative emotions" its very descriptive -- are your sub-themes more interpretive?

As for including a table, that can be a useful introduction to the Results chapter. The usual format is to list the themes in a set of rows on the left, and then have columns for the definition of each theme and couple of brief examples.

Beyond that, the classic format for presenting themes and sub-themes as Results is to use an outline format, where in this case each sub-theme would be the equivalent of a heading in the outline.

It can be mixed either qualitative first and then quantitative and vice versa.

Qualitative research as to do with trying to understand respondent perception about a particular focus of study. Meaning is open ended in nature. While the quantitative research is restricted to the researcher line of design. It is closed ended in nature and number driven.

You have posed an interesting bunch of queries. The essence of reflexivity in qualitative/ethnographic research is that rather than removal but it is essential to reflect upon one's biases, exposing the journey of the ethnographic navigation. You may like to go through my reflective account of doing ethnographic research in Nepal (through the following book chapter published in The Palgrave Handbook of Social Fieldwork (2023).

After completing a PHD, it is highly likely that one would end up as an Academic at a Higher Education or Research Institution. This can include Lecturer, Researcher, Mentoring etc. However there can be opportunities in Industry as well such as working in the Research and Development department, Consulting, Analyst, and any role that involves critical thinking. Seniority in positions will increase based on experience.

Also, immediately after completing PHD some students opt for what is known as a 'Post Doc' contract either at their university or another. This allows for them to gain academic experience whilst also being paid a salary.

Dear Vladimir,

It's interesting to hear your perspective on the use of qualitative and quantitative research methods. I agree that qualitative analysis can provide a valuable foundation for quantitative research, particularly in terms of establishing a "coordinate system" for the data. However, I would argue that qualitative research also has its own unique strengths and can provide valuable insights that may be missed with a purely quantitative approach.

For example, qualitative research can allow for a more in-depth exploration of the attitudes, beliefs, and experiences of participants, which may not be fully captured by quantitative measures alone. Additionally, qualitative research can help identify new and unexpected research questions that may not have been initially considered in the design of a quantitative study.

With that said, I do agree that quantitative research is important for providing reproducible and generalizable results, particularly in fields where empirical evidence is crucial for informing policy or practice.

My question for you is: In what ways do you think researchers can balance the strengths of qualitative and quantitative research methods in order to maximize the benefits of both?

Can you share more details on the Phase I of the study coz in Phase II for F.A, you need to do EFA and CFA on different sample data to explore the factors and confirm the fit of the model. Connect for further discussion.

Many great answers. Photo elicitation is one method, which Samuel Adeyemo mentions above. Be systematic, but also define the use of posters. Are posters the primary source? Much more common is posters/visuals are artifacts to get interviewees talking, create a stop in time to compare to later events.

The other main idea: Pictures/visuals are taken/made for a specific viewpoint and presentation. The people who wanted to present a slice of their perspective--as well as what was left out--are just as important.

Harrison, B. (2002). Photographic visions and narrative inquiry. Narrative inquiry, 12(1), 87-111.

Adeyo Samuels has a lot of great ideas. Define your population, sample, and size. Bigger is not always better. Fewer, more indepth questions and a follow up is better.

All unstructured/semistructured interviews or first focus groups? Decide on what you want to know. All these issues go back to your aims and methodology (e.g., a grounded theory study will be vastly different than a phenomenology study, etc.)

By perceptions, what do you want to know? Look both at the COVID-education literature and the broader field.

Pilot your interview questions after carefully crafting them [can include initial analysis of the practice interview to see if you get the information you want and if questions are clear]. Consider techniques to improve the questions, such as the Delphi technique, interviewing/reviewers of outside experts, etc. Chenille has other ideas. I will review your guide if you asked.

Here could be the simple way to start. "Tell me about teaching during COVID." Then ask probing questions and inquire about best/worst experiences and "tell me more." Avoid why questions!

Congratulations on pursing your gradulate degree. The constructivists theory certainly could fit. it says that people construct knowledge from what is happening to them, added to their own lived experience. I guess I would ask what is the aim of your research? What are you setting out to accomplish? What is the Nursing Problem that you are studying, and how does it impact Nursing Knowledge? your theory, methodology, and analysis are dependent upon what you are trying to find out to some degree.

Since you are working with open-ended questions, you could develop a coding system that specifies what kind of answers justify a Yes or No response to your filter question. That would allow you to exclude answers that do not match your specifications. Note that most of the above responses to do not take into account the availability of qualitative data to interpret your responses.

It is important to note that there is no hard and fast rule for which qualitative data analysis method to choose, as it ultimately depends on the research question, the data collected, and the researcher's own preferences and training. However, in general, the Framework method is considered a deductive approach, while Interpretive Phenomenological Analysis is considered an inductive approach.

Regarding your question about using the Framework method as a guide for the qualitative analysis stage of your mixed-method study, even if it is not the primary approach you are using, this can be a reasonable way to structure your analysis. You can use the stages of the Framework method as a guide for organizing your data and for generating a set of themes, but still approach the coding process in an inductive way. Later, after the Matrix is built, you can use a theoretical framework to interpret and contextualize your findings.

Dear Natha Mohamed Do mention that this a ChatGPT generated answer. I inserted the above question on the site and receive the following answer:

Congratulations on completing your PhD and publishing your meta-synthesis! With your background in qualitative research and focus on breast cancer and social support, there are several pathways you can consider to continue your research journey.

Ultimately, the pathway you choose will depend on your personal interests, skills, and career goals. Consider exploring each of these options to determine which one aligns best with your interests and aspirations. Good luck with your future research endeavors!

Dear Lalithambigai Rajagopal Back on topic. I think one of the options you might consider is to search for a post-doc or post-doc fellowship position (abroad). This a good way to direct your career towards research. See for a good read here:

In short, there are numerous ways to search for this:

1. In the ‘ideal’ world your supervisor might be helpful to introduce you in his/her network

2. Universities and research institutes like EMBO have special programs for this, see for example: https://www.embo.org/funding/fellowships-grants-and-career-support/

3. Obviously ‘just’ search in Google

Wish you all the best with your pursuit for the best next step in your career.

Best regards.

It is important in any research study to clearly identify and justify the sample population that you have chosen to study. In the case of your undergraduate dissertation, you have chosen to focus on female university students aged 18-23 and examine the reasons for their choice of "feminine" degree choices. Your justification for this population could be that this age range represents a key developmental period in terms of decision-making around education and career choices. Additionally, exploring the reasons behind these choices for female university students in particular is important in today's society where there is increasing emphasis on gender equality and closing the gender gap in various fields. Finally, this age range is representative of a key demographic within the university student population and therefore can shed light on trends and patterns within this group.

grounded theory is an approach that is used in qualitative research such as ethnographies, and related studies. It enables expansion of ideas, using a suitable paradigm.

The appropriate research design for a qualitative research study on the topic of "4 out of 13 children under age 5 do not have health cards" would depend on the specific research questions, objectives, and context of the study.

Another major factor would be the extent to which your research contributes new knowledge to a topic of interest to your field. This would be important for how you write up your "problem statement" in your introduction and how your frame the need for your research in your literature review.