A Software-Assisted Qualitative Content Analysis of News Articles: Example and Reflections

Purpose This chapter aims to explicate the use of computer software for qualitative data analysis. Drawing on both a review of relevant literature and a reflexive commentary on an ongoing ethnography, this chapter argues that the use of computer software for qualitative data analysis facilitates rigour and reliability in research, whilst also contributing to wider debates regarding the distinctions made between different research paradigms. Design/methodology/approach The chapter is divided into two sections. In the first, a review of literature pertaining to the use of computer software for qualitative data analysis is reported. The key themes to emerge from this review are then explored in the second section, which consists of a reflexive commentary on the use of computer software for qualitative data analysis within an ongoing three-year Canadian/UK research project. Findings The chapter concludes firstly by foregrounding the methodological benefits of using computer software for qualitative data analysis, and secondly by commenting on wider debates relating to the historical distinctions between quantitative and qualitative research paradigms. Practical implications The chapter suggests that the uptake of computer software for qualitative data analysis should be considered as an integral element of the research design process. Originality/value The originality of this chapter rests in its focus on methodology rather than method, on a reflexive discussion of the place of computer software within the research process rather than a technical description of how software should be used. This chapter is of value not only to researchers who are using or considering using software for their research, but also to researchers who are engaged in wider methodological discussions relating to qualitative and quantitative research paradigms, and to research quality and generalisability.

Qualitative data analysis software (QDAS) packages that support live data extraction are a relatively recent innovation. Little has been written concerning the research implications of differences in such QDAS packages’ functionalities, and how such disparities might contribute to contrasting analytical opportunities. Consequently, early-stage researchers may experience difficulties in choosing an apt QDAS for Twitter analysis. In response to both methodological gaps, this paper presents a software comparison across the four QDAS tools that support live Twitter data imports, namely, ATLAS.ti™, NVivo™, MAXQDA™ and QDA Miner™. The authors’ QDAS features checklist for these tools spotlights many differences in their functionalities. These disparities were tested through data imports and thematic coding that was derived from the same queries and codebook. The authors’ resultant QDAS experiences were compared during the first activity of a broad qualitative analysis process, ‘organising data’. Notwithstanding large difference in QDAS pricing, it was surprising how much the tools varied for aspects of qualitative research organisation. Notably, the quantum of data extracted for the same query differed, largely due to contrasts in the types and amount of data that the four QDAS could extract. Variations in how each supported visual organisation also shaped researchers’ opportunities for becoming familiar with Twitter users and their tweet content. Such disparities suggest that choosing a suitable QDAS for organising live Twitter data must dovetail with a researcher’s focus: ATLAS.ti accommodates scholars focused on wrangling unstructured data for personal meaning-making, while MAXQDA suits the mixed-methods researcher. QDA Miner’s easy-to-learn user interface suits a highly efficient implementation of methods, whilst NVivo supports relatively rapid analysis of tweet content. Such findings may help guide Twitter social science researchers and others in QDAS tool selection. Future research can explore disparities in other qualitative research phases, or contrast data extraction routes for a variety of microblogging services.

The last decades have shown large progress in the elaboration of procedures for qualitative data analysis and in the development of computer programs to support this kind of analysis. We believe, however, that the link between methodology and computer software tools is too loose, especially for a novice qualitative researcher. It is very unclear to select the proper functions and tools as a support in a specific phase of analysis. In texts, you will find a description of the steps of qualitative analysis, and in separate texts computer tools are presented, but what function or tool to use in what phase of analysis is hardly discussed. In this article, we will elaborate the phases of the grounded theory approach and indicate which of the tools of the computer program Kwalitan is to be used in each of the steps and procedures. We will also show how the functions of the computer program may be used when doing a qualitative analysis according to three other approaches, namely summarizing analysis, ethnographic analysis and narrative analysis.

In this introduction to the KWALON Experiment and related conference, we describe the motivations of the collaborating European networks in organising this joint endeavour. The KWALON Experiment consisted of five developers of Qualitative Data Analysis (QDA) software analysing a dataset regarding the financial crisis in the time period 2008-2009, provided by the conference organisers. Besides this experiment, researchers were invited to present their reflective papers on the use of QDA software. This introduction gives a description of the experiment, the rules, research questions and reflective points, as well as a full description of the dataset and search rules used, and our reflection on the lessons learned. The related conference is described, as are the papers which are included in this FQS issue.

Developments during the 1990s in the use of computer software for qualitative data analysis are surveyed. Salient trends are identified as are wider issues associated with software use. Also listed are some of the resources now available to potential and actual users of computer-assisted qualitative data analysis software (CAQDAS).

PurposeIn this study, the concept of organizational stupidity (OS) and different aspects of the OS is analyzed, and a conceptual model for the OS is proposed.Design/methodology/approachThe data for the OS study were collected by interviewing the employees of the Iran Revenue Agency (IRA), Isfahan Province Branch. The snowball method was used for sampling and data collection. The data collected from interviews are analyzed using MAXQDA (a software for qualitative data analysis).FindingsAfter analyzing the data, a conceptual model for the OS is proposed using the grounded theory (GT). The proposed model contains all factors influencing the OS and the relationship among them. The accuracy of the proposed OS model is confirmed using structural validity, external validity, descriptive validity and interpretive validity. The reliability of the proposed OS model is approved using the Holstie, Miles and Huberman reliability equation. The proposed model shows the casual conditions, interfering factors, contextual factors and main phenomena leading to OS and predicts the strategies and consequences of the OS.Originality/valueThis model can be used to plan strategies for managing and reducing OS in organizations.

IntroductionChimeric antigen receptor T-cell (CAR T) therapy offers a potentially curative option for patients with relapsed and refractory hematologic malignancies, including diffuse large B-cell lymphoma (DLBCL). Patient-reported experiences with CAR T therapy are limited and have not been well characterized. The purpose of this qualitative study was to explore patient descriptions of key domains of health-related quality of life (HRQoL) in DLBCL patients treated with CAR T therapy.MethodsA targeted literature review was initially conducted to inform the development of the interview guide comprising predetermined open-ended questions. Two focus groups were conducted with a total of 18 patients with DLBCL identified from patient advisory boards. Focus group sessions were recorded and transcribed verbatim. MAXQDA 18.2.0 qualitative data analysis software was utilized to facilitate a constant-comparative coding process to identify key concepts.ResultsEight domain impairments (social functioning, emotional functioning, fatigue, physical functioning, cognitive functioning, role functioning, sleep, and pain/discomfort) were identified from the qualitative analysis and endorsed by DLBCL patients treated with CAR T. Compared with before CAR T therapy, patients reported increased impairment in every domain during or immediately after CAR T therapy. This impairment improved for each domain 6 months after CAR T therapy except for pain/discomfort. Compared with before CAR T therapy, improvement in impairment for each domain was observed 6 months after CAR T therapy except for fatigue, sleep, and pain/discomfort.ConclusionThis study provides meaningful information regarding the impact of CAR T therapy on HRQoL in patients with DLBCL throughout their treatment journey. Health care professionals and investigators can utilize these data in examining existing patient-reported outcome (PRO) measures that are used in DLBCL clinical trials and to better understand the needs of DLBCL survivors.

The world decided in December 2015 to take actions to reduce global warming. To contribute toward this goal, this research examines possible policy levers for inclusion in the climate change ratification plan. A case study of the measures taken by the Republic of Singapore, a low-lying 719.2 km2 island without natural resources in Asia, is conducted. Being vulnerable to climate change impact and yet having to balance her people’s needs and economic progress with limited resources, the measures taken by this small country could offer policy insights for small states and states without access to alternative energy sources. This research analyzes the online policy documents posted by eleven organizations to answer the main research question of identifying policy levers as theoretical constructs to form a framework that can be used to study climate change policies. A qualitative data analysis software, QSR NVivo 10, is used to classify the proposed nodes developed by the researchers using a system perspective integrating the insights from the key international climate change frameworks with the theoretical concepts from the model of pro-environmental behavior. The findings can offer insights toward developing a new contextual influence framework, which can help strengthen policy development and outcome measurement.

Human perception is strongly influenced by communication. In the context of natural hazards, perception plays a crucial role in the resilience of affected populations. This is particularly true for people's perceptions of phenomena related to climate change (CC). Given this, it is essential to effectively calibrate communication, especially digital communication, which has significantly transformed how information is shared. Moreover, digital communication is the primary channel for younger generations, often labeled “digital natives.” However, the preferences of young people regarding digital communication tools have not been sufficiently explored.In this study, in the framework of the Italian NRRP Tech4You Project, we examine the digital communication tools preferred by students from an Italian scientific high school. A questionnaire was administered to 74 students, asking them to select from various digital communication tools related to CC topics. Additionally, an open-ended question encouraged the students to explain their choices briefly. The communication preferences were analyzed via SPSS statistical software, whereas the comments were analyzed via the qualitative data analysis software AtlasTi.The results highlight a preference for communication that is concise, simple, and similar to the content young people usually engage in. With respect to the proposed content, videos and images are preferred over explicating texts. These findings, which shed light on students' preferences for internet digital tools related to CC, offer valuable insights for better calibrating digital communication in the field of climate change adaptation (CCA), which involves young citizens.This study provides a good basis for enhancing young people's access to information through digital communication, which could significantly improve their social resilience to CC-related events. This improvement is crucial, as the information of today's youth contributes to building more resilient adult citizens in the future.

The progressing digitalization is increasingly permeating all spheres of life: also science. It has reached not only natural sciences, but also the humanities, such as qualitative educational research. For example, for the analysis of qualitative data in educational science researchers are increasingly using computer-assisted tools. This so-called QDA (qualitative-data-analyses) software was developed in the early 1980s in the course of the spreading digitalization to support the category based analyzes of qualitative research. Providing an overview about the current literature situation regarding QDA software and the issues addressed a systematical bibliographic research in pertinent databases were conducted. As a result, five different types of literature could be identified. Even though all categories are demonstrated only one is presented in detail. The paper focus on the category in which methodological issues are negotiated and illustrates the therein addressed arguments. Possibilities and limitations of QDA software for educational research are illustrated and past and present discussions regarding this software are outlined. In particular, it is emphasized that so far limitations of QDA software are rarely addressed. In order to deal with this void in the future more comprehensively a set of questions is proposed, which allows to reflect the use of QDA software in a specific research project in an extensive manner. Concluding further questions are raised and it is discussed if also sequential analyzes can be carried out with current QDA software or if they need new digital tools.

As the use and availability of qualitative software analysis tools increase, so does ambiguity regarding the choice of the most appropriate software in sport management research. This paper uses NVivo and Leximancer to analyse the same set of data derived from interviews with sport management experts on high performance sport to showcase the differences in findings depending on the type of software used. The findings alert sport management and social science researchers to the importance of closely examining the choice of software for qualitative data analysis. Researchers may base their decision on aspects such as the type and size of data set, their competence and skills in data interpretation and the level of engagement with data analysis they plan on undertaking. This paper discusses the implications for researchers in the sport management field using these tools for data analysis and highlights the value that software can add to the research effort.

BackgroundOccupational skin diseases (OSD) in the form of hand eczema (HE) are a common work-related disease. Illness perceptions as presented in Leventhal’s Common-Sense Model (CSM) are important for patients’ self-management of diseases. Understanding these illness perceptions is essential for patient communicating. No quantitative or qualitative studies which investigated subjective illness perceptions in patients with occupational HE utilized the CSM as theoretical framework. The Objective of this study is to investigate illness perceptions of patients with occupational hand eczema (HE) using the CSM.MethodsWe applied an exploratory qualitative approach and conducted purposive sampling. Thirty-six patients with occupational HE were interviewed using an interview guide based on the dimensions of the CSM, including coherence and emotional representation. All participants participated in a three-week inpatient program at a clinic specialized on occupational dermatology. One interview had to be excluded before analysis, since one participant’s diagnosis was retrospectively changed from ICD to tinea and hence did not match the inclusion criteria. Thirty-five interviews were transcribed verbatim and analyzed. Data was analyzed deductively and inductively using qualitative text analysis. MAXQDA 2018 (Verbi, Berlin, Germany), a software for qualitative data analysis, was applied for coding and summarizing of results. All dimensions of the CSM were explored for occupational HE.ResultsSeveral sub-categories could be identified. Participants named a variety of causes in different areas (e. g. external irritants and other hazardous factors, psycho-social factors, allergies, having a ‘bad immune system’ or lifestyle). The great impact of the disease on the participants’ life is shown by the wide range of consequences reported, affecting all areas of life (i. e. psychological, physical, occupational, private). Considering coherence, an ambivalence between comprehensibility and non-comprehensibility of the disease is apparent.DiscussionThe complexity of illness perceptions presented in this paper is relevant for those involved in HE patient education and counseling, e. g, health educators, dermatologists, and, occupational physicians. Future research might further investigate specific aspects of illness perceptions in patients with occupational HE, especially considering the complexity of coherence and overlapping dimensions (i. e. emotional representation and psychological consequences).

Determinants of family support for older patients with chronic non-communicable diseases (chronic diseases) are largely unknown. This study aimed to identify the factors related to family support for older patients in Guangzhou, focusing on solitary living conditions and societal expectations to inform future interventions. The quantitative stage included a sample of 227 people, and the qualitative stage included a sample of 9 people residing alone. Data were collected between December 2021 and December 2022 using the Personal Information Form, the Family Caregiving Index, the Family Support Scale, and the Semi-Structured Interview Form. Descriptive statistics, independent sample t test, one-way analysis of variance (ANOVA), and multiple linear regression analyses were used for quantitative data analysis. Content analysis was performed using the Nvivo12 software for qualitative data analysis. Of the older patients with chronic diseases, 83.7% had good family function, as indicated by an APGAR score of 9 (interquartile range 7–10) or higher. The median self-rating score for family support was 13 (interquartile range 11–14), with 75.8% reporting high family support. After adjusting for sex, age, education level, family type, family power structure, perceived marital quality, perceived filial support, and frequency of contact with children, several factors were found to be significantly associated with poorer family outcomes. For family function, perceived marital quality as average or poor (β = − 1.30, 95% CI: − 2.37 to − 0.24, P = 0.018), having no children (β = 6.35, 95% CI: 2.04 to 10.66, P = 0.005), and low-frequency contact with children (β = − 7.76, 95% CI: − 11.54 to − 3.98, P < 0.001) were significantly associated with lower family function scores. Similarly, for family support, perceived marital quality as average or poor (β = − 1.76, 95% CI: − 3.24 to − 0.28, P = 0.021), no spouse (β = − 2.01, 95% CI: − 3.34 to − 0.68, P = 0.003), no children (β = 8.58, 95% CI: 2.63 to 14.54, P = 0.006), and low-frequency contact with children (β = − 10.06, 95% CI: − 15.30 to − 4.81, P < 0.001) were significantly associated with poorer family support. Qualitative analysis revealed living conditions, family and societal support, and expectations and needs for medical services among solitary older adults. Poor perceived marital quality, lack of spousal support, low filial support from children, and infrequent contact with children are risk factors for poor family functioning and low support among older patients with chronic diseases. Enhanced societal and familial support mechanisms are crucial, especially for older adults living alone.

Background:The infants, hospitalized in the neonatal intensive care unit (NICU), engage with problems from admission to discharge, exploring of which ensures their safe transition. The purpose of this study was to identify the factors that influence infant's transition from the NICU to home.Materials and Methods:A qualitative study was used for identifying the factors that affect infant's transition. Data were gathered by interviewing 16 nurses and physicians in NICUs of university hospitals in Iran; and were analyzed by qualitative content analysis method. MAXQDA, MAX Qualitative Data Analysis, is a software which has been developed in Berlin, Germany. software, the qualitative data analysis package, was used for coding and categorizing.Results:There are 10 categories that affect infant's transition, as revealed in data analysis. These categories were delineated into three themes: Cognition of infant's needs, effectiveness of trainings, and organizational context.Conclusion:The results of this study further disclosed the factors that facilitate or hinder infant's transition from the NICU to home. The aspects of correct cognition along with more effective trainings must be fully introduced to the staff to meet infant's needs. Also, authorities are better to make policies to decrease organizational barriers. Therefore, it is suggested that applying developmental care can ease infant's transition.

Background: Prior research by the authors studied the objective impact on medical students’ academic course, the perceived cognitive load, quantified subjective feedback while teaching using AnaVu, a low resource stereoscopic projection system. The qualitative data from opinions, and comparative educational results reported by undergraduate medical students following their participation in stereoscopic (AnaVu) and monoscopic learning sessions are explored in this study. This study was done to evaluate and compare the effectiveness of stereoscopic and monoscopic teaching methods in enhancing spatial understanding of anatomical structures among first-year undergraduate medical students using AnaVu. Methodology: This research study was conducted as a three-limb randomized controlled trial. Among those who provided informed consent, a sample of MBBS students from the 2022 cohort was chosen at random. Following a one-hour brainstem introduction lecture and a dissection session, students were assigned at random to one of three groups: S for stereo; M for mono; or C for control. A 20-minute stereoscopic demonstration of the brainstem module in AnaVu has been delivered to S. The identical presentation, albeit in monoscopic mode, was delivered to M. Diagrams drawn on a whiteboard were used to instruct the C group. Pre-intervention and post-intervention tests were given in four domains: basic recall, analytical, radiological anatomy and diagram-based questions. Finally, the groups were swapped – S→M, M→S and C→S, and they were asked to compare the modes. Data were processed using RQDA (R package for Qualitative Data Analysis). Theme identification and analysis of the qualitative data was done using the thematic analysis. Results: 152 students participated in the study. Five themes and fourteen subthemes were identified. General advantages included size comparisons, software features, and improved attention, while specific benefits for learning radiological and sectional anatomy were noted. Disadvantages included eye strain, software glitches, costs, and concerns about teacher adaptation. Conclusion: The findings of this study emphasize the potential of AnaVu in enhancing anatomical and radiological education, while highlighting key disadvantages to help teachers and students make informed choices between stereo and mono display methods.