The Walking Dead Genealogy: Unsubstantiated Criticisms of Qualitative Data Analysis Software (QDAS) and the Failure to Put Them to Rest

Jackson, Kristi; Paulus, Trena M.; Woolf, Nicholas H.

doi:10.46743/2160-3715/2018.3096

Cited by 10 publications

(5 citation statements)

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“…Analytic methodology limitations exist in terms of the use of set lists of stop words, manually handling misspellings/typos, and using the full written word over the root words (e.g., "abnormality" has the root abnormal). In contrast, our analytic approach was able to use a large quantity of data consisting of people expressing similar sentiments repetitively, and give an overarching summarization of the responses and themes efficiently (Jackson et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

No one listens to us, we know this, so we participated: Qualitative evidence from menstruation research during the COVID-19 pandemic

Junkins¹,

Lee²,

Clancy³

2023

Preprint

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Introduction: It can be challenging for clinical trials to achieve external validity, meaning the studied effects within a trial are generalizable to other contexts or the broader population (Averitt et al., 2020; Carroll et al., 1999; Kennedy-Martin et al., 2015). However, the people with the lowest chance of inclusion are often the ones at greatest risk of disease and poor health (Howcutt et al., 2018). The current study used data from a survey that was built in response to anecdotal observations of changes in menstrual bleeding after being vaccinated for COVID-19 that recruited people who are often excluded from health research, including gender diverse people, minority ethnicities or racial identities in the U.S., postmenopausal people, and people with reproductive conditions. We analyzed survey items regarding how people heard about the study and why they chose to participate, identifying themes and categorizing motivations to participate in unpaid health research. Open-ended responses were compared and contrasted among demographic subgroups to more closely attend to the diversity of responses and to avoid an overfocus on the majority responses.Methods: The data came from a large, online mixed methods study of menstrual and other symptoms after receiving COVID-19 vaccines in 2021. Survey items analyzed here include demographics (age, gender, race, and ethnicity) and two open-ended text responses. The sample was limited to people in the U.S. who wrote in English (N = 22,737). The analysis approaches were conducted using computer-assisted qualitative data analysis software packages in R. Results: Our results show that people largely found the survey through trusted sources or online outlets. People’s motivations to participate included the following themes: vaccine effects and women’s/people’s health, personal experiences, and interest in and need for research. Our themes reflected multiple types of altruism (e.g., political, experiential, and community). Across each analysis, we found largely consistent results for these questions in each demographic subgroup. Conclusions: Based on our study, we recommend more responsive, flexible post-clinical trial research to reach historically marginalized groups. In order to do this, scientific communities need to build credibility and create online presences to engender trust with the groups with whom they seek to work.

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Section: Discussionmentioning

confidence: 99%

No one listens to us, we know this, so we participated: Qualitative evidence from menstruation research during the COVID-19 pandemic

Junkins¹,

Lee²,

Clancy³

2023

Preprint

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“…Unfortunately, researchers rarely include details as to how QDAS was used for a study (Woods et al, 2016). This lack of explanation contributes to persistent misconceptions of how QDAS works such as the mistaken notion that software use inherently improves a study’s rigor (Jackson et al, 2018). Paulus, Woods, Macklin and Atkins (2017) advise researchers to report which version of the software was used since features change with each update.…”

Section: How Can Qdas Be Used To Support My Research Study?mentioning

confidence: 99%

“…While digital tools and spaces have long been integrated into qualitative research designs, the appropriate use of qualitative data analysis software (QDAS) has been up for debate (Jackson et al, 2018). Researcher concerns and distrust of these platforms have at times been the result of misconceptions about how they function, such as the belief that the software replaces the researcher during the analysis process.…”

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confidence: 99%

Using Qualitative Data Analysis Software to Support Digital Research Workflows

Paulus

2022

Human Resource Development Review

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While software packages such as NVivo are typically considered useful for qualitative data analysis, in actuality they are powerful and flexible enough to serve as the central component of a robust digital research workflow. Various features of these packages can be used across the entire research process from reviewing the literature to writing up the study’s findings. This article provides an overview of available qualitative data analysis software (QDAS) packages, including how to: use software tactics to enact research design strategies; select an appropriate QDAS package; report the use of software in the research report; and consider implications of QDAS use for human resource development scholars.

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“…The above possibilities and limitations of CAQDA software are not exhaustive, however, they give a general view of the range of possibilities offered by such tools and doubts that their use brings (Jackson et al, 2018;Paulus et al, 2018). Above all, however, as we always try to draw the attention of both readers and participants of our workshops, it is crucial to be fully aware of the supporting nature of the software used.…”

Section: What We Should Know Before We Become Caqdas Users -Possibili...mentioning

confidence: 99%

Exploring CAQDAS - How to Support a Novice User of Computer Aided Qualitative Data Analysis Software

Niedbalski

Ślęzak

2021

Advances in Intelligent Systems and Computing

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During our classes with students, doctoral students, or while taking part in methodological workshops, we often hear some repeated questions: "Is it worth using the computer-aided qualitative data analysis software and why?" and "Which program should I choose?" Having gathered sizable experience in the field, we can answer these questions by saying that the use of CAQDAS (Computer-Assisted Qualitative Data Analysis Software) makes the process of data analysis more systematic and transparent, and this "forces" to think about data and supports in-depth analysis. The use of CAQDAS requires a certain amount of effort and work due to the need to learn about the environment of a software, but also (or maybe first) to change the perspective, and often some habits concerning how a researcher's workshop is organized. The choice of appropriate software is highly individual and it requires a thorough consideration from its future user. Therefore, the primary objective we set as the authors of this paper is to present the perspective taken by qualitative researchers who use selected free CAQDAS applications. Our paper is intended mainly for novice CAQDAS users who we would like to advise on how to select appropriate software and familiarize them with the specifics of CAQDAS.

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The Walking Dead Genealogy: Unsubstantiated Criticisms of Qualitative Data Analysis Software (QDAS) and the Failure to Put Them to Rest

Cited by 10 publications

References 0 publications

No one listens to us, we know this, so we participated: Qualitative evidence from menstruation research during the COVID-19 pandemic

No one listens to us, we know this, so we participated: Qualitative evidence from menstruation research during the COVID-19 pandemic

Using Qualitative Data Analysis Software to Support Digital Research Workflows

Exploring CAQDAS - How to Support a Novice User of Computer Aided Qualitative Data Analysis Software

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