Applying a mixed methods design to test saturation for qualitative data in health outcomes research

Saturation, a core concept in qualitative research, suggests when data collection might end. It is reached when no new relevant information emerges with additional interviews. The aim of this research was to explore whether a mixed methods design could contribute to the demonstration of saturation. Firstly, saturation was conceptualized mathematically using set theory. Secondly, a conversion mixed design was conducted: a set of codes derived from qualitative interviews were quantitized and analyzed using partial least squares (PLS) regression to document whether saturation was reached. A qualitative study conducted by other researchers prior to this work (i.e. none of the present authors was involved in this study) was used to test saturation using PLS regression. This illustrative qualitative study aimed to investigate the impact of Clostridium difficile infection (CDI) on nurses’ work in the hospital and the results were published elsewhere (Guillemin et al. 2015). Semi-structured interviews were conducted with 12 nurses. Saturation was characterized by the cumulative percentage of variability accounted for by PLS factors. After 12 interviews, this percentage was 51% which suggests that saturation was achieved at least on main themes. Two main themes identifying similarities in the experience of nurses caring for patients with CDI were identified: Organization/Coordination of the working day and Time-consuming work. Although dependent on the coding of qualitative data, PLS regression of quantitized data from qualitative interviews generated useful information for the determination of saturation

Waiting in the wings : a study of early career academic researchers in Australia

In commissioning this project, the Australian Research Council has begun to respond to the needs ofthose academics finding it difficult to tap the resources necessary to become established in a research career. We have appreciated the support and encouragement ofmembers ofthe steering committee and the discipline panels during the course of our investigations, and anticipate their continued interest in facilitating equitable access to funding by early career researchers

Trivial and normative? Online fieldwork within YouTube’s beauty community

In this article, I discuss methodological understandings around qualitative research and online ethnographic practice to bring forward a reflexive account on the particularities of doing fieldwork on YouTube. I draw from a multiyear ethnographic examination of YouTube’s beauty community that sought to understand online popularity framed by local norms and practices and shed light into the local significance of knowledge, expertise, and self-development. I argue for an epistemological perspective that acknowledges the diversity of viable, conceivable fieldwork experiences while distancing from prescriptive modes of argumentation. I propose seeing fieldwork in and through its richness and predicaments, persistently naturalistic while interpretive. I approach online popularity, fandom, and even YouTube itself from a perspective that tolerates ambivalence, contradictions, and embraces the complexity of social worlds and human interaction

'Excellence' and exclusion:the individual costs of institutional competitiveness

A performance-based funding system like the United Kingdom’s ‘Research Excellence Framework’ (REF) symbolizes the re-rationalization of higher education according to neoliberal ideology and New Public Management technologies. The REF is also significant for disclosing the kinds of behaviour that characterize universities’ response to government demands for research auditability. In this paper, we consider the casualties of what Henry Giroux (2014) calls “neoliberalism’s war on higher education” or more precisely the deleterious consequences of non-participation in the REF. We also discuss the ways with which higher education’s competition fetish, embodied within the REF, affects the instrumentalization of academic research and the diminution of academic freedom, autonomy and criticality

Mixed methods in management research : implications for the field

Mixed methods approaches to research have been widely adopted in social sciences and professional studies disciplines. Using a combination of methods is assumed to offer the promise of greater flexibility in undertaking research, of generating better supported arguments from research data, and of increased relevance to a wider circle of stakeholders, claims that are at least partially supported by evidence of higher journal citation rates for mixed than monomethod articles. A review of eighty-three articles published eight years apart in the Academy of Management Journal (AMJ) and Administrative Science Quarterly (ASQ) suggests that organizational and management researchers have been slow to adopt mixed methods approaches to research. Articles for both periods and in both journals were clearly dominated by studies that employed statistical analyses of archival, database, experimental or survey data, with little change over the period. These results reflect those found in other studies. This review of articles raised wider issues. 1) Difficulty was experienced in classifying studies, leading to a refinement in emphasis for a definition of mixed methods. 2) Management researchers as a whole, as reflected in the style and referencing of these articles, have thorough training in the fine details of statistical methods of analysis; understanding of qualitative analysis is weaker and restricted to a few; and none appears to have any awareness of a growing literature on mixed methods, nor did any discuss the kinds of issues typically covered in qualitative and mixed methods articles in other journals. The results of this review have implications for the training of management and organization studies researchers who currently appear to have a quite limited repertoire of non-statistical methods on which to draw when undertaking research

Analysing mixed methods data

The primary focus of the chapter is on strategies for analysis in mixed methods research. Analysing mixed methods data generally assumes competence in analysing, separately, both quantitative (statistical) and qualitative (textual) data. No attempt is made, in this chapter, to develop these specific competencies. Rather, the objective is to stimulate thinking about more effective ways to apply these skills in making use of the multiple data sources you may have gathered, to genuinely integrate the findings of these, and to provide some practical guidance on how this might be done so that you can enrich the analyses you undertake

Constructing an argument through data analysis

Many researchers working with qualitative data stop at providing a simple descriptive account of the key (or interesting) points or themes identified in their data. While description is a necessary starting point in reporting research results, in many cases it is just that-a starting point to provide necessary context and the parameters of the concepts and ideas with which the research is concerned. My goal in this chapter is to encourage researchers using qualitative data to use, and then go beyond categories and themes to build an argument grounded in their data that could: - establish understanding - explain a (causal) process - be relevant to theory and practice, and - convince an audience. Only then will researchers working with qualitative data gain the respect as well as the publishing and funding opportunities afforded to those who work with hard numbers and "real" data. And for those in practice, it is no longer sufficient to act on the basis of tradition and handed-down wisdom. The demand, now, is to provide evidence in support of practice-an ability to justify (argue for) practice choices and procedures on the basis of research data and analyses. On the personal side, developing a strong argument and perhaps an iliuminating model, in contrast to simply reporting themes, provides deep intellectual satisfaction as does being able to convincingly pass on wisdom to others

Conceptualising research performance

In a context of increasing emphasis on academic performance and accountability, data from a structured survey in which academics elaborated on eight different attributes of high-performing researchers were used to build a conceptual model of research performance. Research performance was seen to comprise two basic components, with six secondary level dimensions and a range of potential indicators. Four essential (necessary and sufficient) dimensions, relating to the research activity component of research performance, were: engagement, task orientation, research practice and intellectual processes. Two alternative dimensions (of which at least one is necessary) relating to the performance, or making research visible, component of research performance were dissemination and collegial engagement. Research performance was seen to occur within conditions provided by an institutional context (education and training; opportunity and resources), and to bring about a range of outcomes (product, impact and reputation)