Software for Qualitative Research: 2. Some Thoughts on ‘Aiding’ Analysis

1997 ◽  
Vol 29 (6) ◽  
pp. 1109-1124 ◽  
Author(s):  
S J Hinchliffe ◽  
M A Crang ◽  
S M Reimer ◽  
A C Hudson
Keyword(s):  
Qualitative Research ◽  
Qualitative Data ◽  
Computer Software ◽  
The Body ◽  
Analysis Software ◽  
Means And Ends ◽  
Software Packages ◽  
Computer Aided ◽  
Outright Rejection ◽  
Qualitative Data Analysis Software

In this paper we reject accounts which portray computer aided qualitative data analysis software (CAQDAS) as neutral and benign. We argue that applying computer software to qualitative projects raises a number of important issues that go to the heart of ethnography. Although we initially work with a distinction between tactile and digital ethnographics, the issues that we raise are not unique to computer-aided analyses. Indeed, we argue that the adoption of computers marks a useful moment in which to think critically about the means and ends of qualitative analysis. In this paper we urge qualitative researchers to avoid both an outright rejection and an unquestioning adoption of computer software packages. Rather, we work towards a ‘crafty’ approach to ethnography where computers are incorporated into the body of research in a critically reflexive and creative manner. We end the paper with some thoughts on the potential of such incorporation.

Building Transparency and Trustworthiness in Inductive Research Through Computer-Aided Qualitative Data Analysis Software

2019 ◽  
Vol 24 (1) ◽  
pp. 104-139 ◽  
Author(s):  
Paula O’Kane ◽  
Anne Smith ◽  
Michael P. Lerman
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Building Blocks ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Inductive Research ◽  
Computer Aided ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in mystery. We suggest that computer-aided/assisted qualitative data analysis software (CAQDAS) can support qualitative researchers in their efforts to present their analysis and findings in a transparent way, thus enhancing trustworthiness. To this end, we propose, describe, and illustrate working examples of six CAQDAS building blocks, three combined CAQDAS techniques, and two coder consistency checks. We argue that these techniques give researchers the language to write about their methods and findings in a transparent manner and that their appropriate use enhances a research project’s trustworthiness. Specific CAQDAS techniques are rarely discussed across an array of inductive research processes. Thus, we see this article as the beginning of a conversation about the utility of CAQDAS to support inductive qualitative research.

scholarly journals Organisational Problems and Solutions in Oncology: A Content Analysis of the Narratives of Italian Cancer Unit Professionals

2017 ◽  
Author(s):  
Simone Cheli ◽  
Luca Pezzullo ◽  
Francesco Velicogna
Keyword(s):  
Qualitative Research ◽  
Organizational Climate ◽  
Interpersonal Communication ◽  
Qualitative Data ◽  
Group Cohesiveness ◽  
Analysis Software ◽  
Action Research Project ◽  
Computer Aided ◽  
Problems And Solutions ◽  
Qualitative Data Analysis Software

The aim of this qualitative research is to explore the perception of the organizational climate in Italian cancer units. The survey was the first step of a two year action-research project, involving 14 hospitals and different professions (n=475). We report the methodology and the thematic clusters that emerged in analysing the answers to three questions: (i) perceived problems with colleagues, (ii) perceived problems with patients and their relatives, and (iii) coping strategies. Narratives were analysed through computer aided qualitative data analysis software. The results identify two main significant issues in describing problems and solutions: interpersonal communication and group cohesiveness.

scholarly journals O USO DE PROGRAMAS DE COMPUTADOR NA ANÁLISE QUALITATIVA: OPORTUNIDADES, VANTAGENS E DESVANTAGENS.

2007 ◽  
Vol 12 (2) ◽  
pp. 56 ◽  
Author(s):  
Daniel Augusto Moreira
Keyword(s):  
Qualitative Research ◽  
Grounded Theory ◽  
Data Analysis ◽  
Data Storage ◽  
Qualitative Data ◽  
Computer Software ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

Qualitative Data Analysis Software is not extensively used in Brazil; also, misconceptions about qualitative research are still common. This study presents the main functions of Qualitative Data Analysis Software or, more properly, CAQDAS - Computer Aided Qualitative Data Analysis Software, as it is well known in the academic world. The relationship of CAQDAS with grounded theory is stressed, and so is text coding, as the central operational issue in grounded theory. Vantages and advantages of using software packages are analyzed. However their huge potential for facilitating data storage, manipulation and retrieval, their use is not always necessary or even recommended. As the packages are not neutral concerning theory, the analyst has to decide if and when to use a computer program and, if the package is in order, which one to use. Key words: Data analysis. Computer software. Qualitative research.

scholarly journals O uso do computador na análise de dados qualitativos: questões emergentes

2008 ◽  
Vol 9 (4) ◽  
pp. 75-98 ◽  
Author(s):  
Maria Campos Lage ◽  
Arilda Schmidt Godoy
Keyword(s):  
Data Analysis ◽  
Qualitative Data ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Computer Aided ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

A sigla CAQDAS (Computer Aided Qualitative Data Analysis Software) designa softwares criados para auxiliar na análise de dados qualitativos. Alguns autores possuem opiniões favoráveis acerca da utilidade, eficácia e facilidade de uso desses softwares, outros demonstram dúvidas em relação aos benefícios conseguidos, gerando polêmica e tornando oportuna a criação de um espaço para discussão do tema. O objetivo deste trabalho é apresentar e analisar os principais aspectos envolvidos nesse debate, levando em consideração as opiniões e os argumentos "favoráveis" e "contrários" ao uso de CAQDAS. Para atender a esse propósito, foi realizada uma revisão bibliográfica centrada na análise de quatro aspectos: a utilidade do gerenciamento de dados pelo computador, a possibilidade de maior interação do pesquisador com seus dados, a facilitação do processo de comunicação entre pesquisadores e a existência de viés no processo analítico. Discutem-se também algumas experiências nacionais recentes de uso de CAQDAS em pesquisas na área de administração.

scholarly journals Structuring a Team-Based Approach to Coding Qualitative Data

2020 ◽  
Vol 19 ◽  
pp. 160940692096870
Author(s):  
Lindsay Giesen ◽  
Allison Roeser
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Reference Materials ◽  
Qualitative Data ◽  
Research Process ◽  
Lessons Learned ◽  
Analysis Software ◽  
Management Structure ◽  
Qualitative Data Analysis Software ◽  
Supportive Management

Improvements to qualitative data analysis software (QDAS) have both facilitated and complicated the qualitative research process. This technology allows us to work with a greater volume of data than ever before, but the increased volume of data frequently requires a large team to process and code. This paper presents insights on how to successfully structure and manage a team of staff in coding qualitative data. We draw on our experience in team-based coding of 154 interview transcripts for a study of school meal programs. The team consisted of four coders, three senior reviewers, and a lead analyst and external qualitative methodologist who shepherded the coding process together. Lessons learned from this study include: 1) establish a strong and supportive management structure; 2) build skills gradually by breaking training and coding into “bite-sized” pieces; and 3) develop detailed reference materials to guide your coding team.

Improving outcomes with Qualitative Data Analysis Software: A reflective journey

2017 ◽  
Vol 18 (3) ◽  
pp. 436-442 ◽  
Author(s):  
Austin G Oswald
Keyword(s):  
Qualitative Research ◽  
Social Work ◽  
Data Analysis ◽  
Qualitative Data ◽  
Research Process ◽  
Digital Tools ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Social Work Research ◽  
Qualitative Data Analysis Software

Now more than ever, qualitative social work researchers are being called upon to conduct increasingly complex, multifaceted, and intersectional research. Given the heightened complexity of social work research, it is necessary that scholars learn strategies to streamline the research process and digital tools for qualitative research are a mechanism to do so. In this paper, I share insights gleaned from personal experience working with Qualitative Data Analysis Software, specifically MAXQDA 12, to support a larger study that explored the social lives of older gay men. This paper highlights the various functions of MAXQDA 12 and how qualitative social work researchers can use the program to improve the research process and outcomes. Despite the rapid growth in production of digital tools for qualitative research there remains a dearth in studies that explicitly address how digital tools are used in the extant literature on qualitative research. This paper sheds light on this noted gap in the literature by exploring the functionality of MAXQDA 12 and how it can be applied to improve qualitative social work research.

scholarly journals Building criteria to evaluate qualitative research papers: a tool for peer reviewers

2019 ◽  
Vol 53 ◽  
Author(s):  
António Pedro Costa ◽  
Maria Cecília de Souza Minayo
Keyword(s):  
Qualitative Research ◽  
Qualitative Data ◽  
Review Process ◽  
Research Evaluation ◽  
Evaluation Tool ◽  
Analysis Software ◽  
Research Papers ◽  
Peer Reviewers ◽  
Qualitative Data Analysis Software ◽  
New Criteria

ABSTRACT Objective: To present some criteria, many of which were created in the form of a checklist of items to be considered throughout the review process. Furthermore, we present a study whose main objective was to build (and validate) a review instrument by specialists that is clear, comprehensive, concise and consistent with the highest standards of excellence. Method: We use a survey to collect data (123 answers). To analyze the open answers we use the technique of content analysis through the Qualitative Data Analysis Software. Results: Besides the creation of new criteria with a focus on methodological dimensions based on 12 items, the involvement of the Ibero-American Congress on Qualitative Research scientific committee in the validation of this instrument. Conclusion: This option, in line with the others described, will allow to implement improvements to the editions of the events using the Qualitative Research Evaluation Tool in 2018.

scholarly journals Utilizing Microsoft® Office to Produce and Present Recursive Frame Analysis Findings

2014 ◽  
Author(s):  
Ronald Chenail ◽  
Maureen Duffy
Keyword(s):  
Grounded Theory ◽  
Data Analysis ◽  
Conversation Analysis ◽  
Qualitative Data ◽  
Frame Analysis ◽  
Computer Assisted ◽  
Analysis Software ◽  
Software Packages ◽  
Qualitative Descriptive ◽  
Qualitative Data Analysis Software

Although researchers conducting qualitative descriptive studies, ethnographies, phenomenologies, grounded theory, and narrative inquiries commonly use computer-assisted qualitative data analysis software (CAQDAS) to manage their projects and analyses, investigators conducting discursive methodologies such as discourse or conversation analysis seem to find such software packages not as useful. In our work with Recursive Frame Analysis (RFA), a systemic approach to the analysis of text and talk, we have taken a slightly different route by utilizing Microsoft® Office applications to produce and present our RFA findings. In the paper we describe RFA, explain how we use Word and PowerPoint to carry out RFA's semantic, sequential, and pragmatic analyses, and illustrate our work with some examples from a recent study.

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