The potentials and pitfalls of using Skype for qualitative (longitudinal) interviews

The use of digital communication technologies has become increasingly commonplace in social research. Yet, sparse attention has been paid to the potential of such technologies in Qualitative Longitudinal Research (QLR). This paper explores the implications of introducing one such technology, internet video calls (e.g. Skype, FaceTime, Google Hangouts), as a new mode of data collection into an established QLR study that has primarily generated data using biographical interviews conducted in participants’ homes. The paper draws on the ‘Your Space’ project; a decade-long study following the lives of up to 52 young people from across Britain. Funded as one of eleven ESRC National Centre for Research Method’s ‘Methodological Innovation Projects’ the most recent phase of the project investigates the implications of shifting from physical co-present interviewing to remote modes on key issues for QLR research such as sample maintenance, research relationship continuity, and rapport. In doing so, it assesses whether internet video calls might be a useful means of conducting short ‘catch-up’ interviews between the main waves of data collection, or as an alternative way of carrying out case study intensive interviews

Theory and the breadth-and-depth method of analysing large amounts of qualitative data:A research note

This research note builds on a previously published discussion of the ‘breadth-and-depth’ method for working with extensive amounts of secondary qualitative data, to consider the way that theory can be used and developed as part of this method. We illustrate potential deductive, inductive, and abductive logics of the relationship between theory and data that can be pursued using the method, but note that in reality research analysis rarely proceeds along such clear categorical lines. Rather, qualitative researchers are more likely to pursue an approach akin to a retroductive logic and analytic practice, which the breadth-and-depth method also can accommodate

Genomic data: building blocks for life or abstract art?

The genes found in the genetic code (genome) are sometimes called the “building blocks for life” but knowing how they impact human health can be more complicated than it sounds. This article aims to show how difficult it can be to understand how our genes can affect our health, and why it is not always easy to work out a patient’s result from genetic tests. We follow the story of Ben, whose muscles have been getting weaker for a few years. To find out why, Ben has had his genetic code sequenced, and we will walk you through a process by which his results can be analyzed. Through this activity, we will show you that analyzing patients’ genome tests is a bit like interpreting abstract art, in which different people might see and value different things

Analysing large volumes of complex qualitative data:Reflections from a group of international experts

This working paper brings together the reflections of a wide range of international researchers to explore, showcase and reflect critically on the potentials and challenges of analysing large volumes of complex qualitative, and qualitative longitudinal (QLR) data, including archived material. Big Qual analysis is a new area for qualitative work and there is little guidance on how best to work with masses of qualitative material. The working paper comprises a set of blogs housed in the ‘Big Qual Analysis Resource Hub’ (http://bigqlr.ncrm.ac.uk/). We created this website to map the progress of our ESRC National Centre for Research Methods research project ‘Working across qualitative longitudinal studies: a feasibility study looking at care and intimacy’ (2015-2019). As part of the project we developed procedures for working with multiple sets of in-depth temporal qualitative data (see Davidson et al. 2019; Edwards et al. 2019 for discussion of our methodological findings). We have gathered together and made available the 27 blog post reflections from 32 authors in this working paper form because accounts of data management and analysis in qualitative research are often sanitised by the time they reach academic journals. Here, our contributors document and share publicly the trials and tribulations, intellectual commitments, contingencies and decision-making processes underlying such analysis, contributing to debates around good practice. We hope that this collection of reflections will promote further conversations about analysis/secondary analysis across large scale and/or multiple qualitative data sets. With guest posts from international scholars, from early career through to established researchers, on topics as varied as the ethics of using Big Qual data, using secondary qualitative material and computer-assisted qualitative data analysis software, this collection of reflections profiles the diversity of work taking place internationally

Disciplinary perspectives on archiving qualitative data

This webinar was organised by QUEST (Qualitative Expertise at Southampton) in collaboration with the National Centre for Research Methods and the South Coast Doctoral Training Partnership. It was held on 23 June 2022. The speakers were: Dr Rachel Ayrton (chair), Carolynn Low, Dr Susie Weller and Professor David Zeitlyn

Developing pedagogy for 'Big Qual' methods: teaching how to analyse large volumes of secondary qualitative data

The sharing and re-use of data is encouraged by major research funding bodies in the UK as a way of maximising its value and as vital to accountability and transparency. The creation of repositories, such as the UK Data Archive which houses over 1,000 qualitative and mixed methods datasets, offers qualitative researchers and students many opportunities to re-use data. However, the practice of moving beyond the reuse of one or two datasets to working across multiple small-scale archived qualitative studies remains under developed. This represents a challenge, both for researchers seeking to develop their skills and for methods teachers tasked with developing research capacity. This working paper describes the work of a unique collaboration between researchers of methods for analysing large volumes of qualitative data, ‘big qual’, and researchers of social science research methods pedagogy to develop big qual methods teaching and open educational resources. Using reflective and evaluative methods, the combined team completed three cycles of action and reflection based upon the teaching of big qual analysis using an innovative breath-and-depth method for working across multiple archived qualitative data sets. This paper reports key messages for teachers of big qual and related innovative methods, identifying the importance of teachers’ pedagogic reflection across their approaches, strategies, tactics and discrete in-class tasks, and other key pedagogic resources that are necessary to develop teaching and learning. These resources respond to particular challenges for interdisciplinary and innovative methods teaching. They include modes of teaching through data, the use of worked examples and metaphors for articulating and structuring the acquisition of new concepts and knowledge, and the use of peer-learning to enrich learning and manage diversity. Lastly the paper links to an extensive suite of Open Educational Resources for the teaching of big qual analysis at the ESRC National Centre for Research Methods

Research priorities for children's cancer : a James Lind Alliance Priority Setting Partnership in the UK

OBJECTIVES: To engage children who have experienced cancer, childhood cancer survivors, their families and professionals to systematically identify and prioritise research questions about childhood cancer to inform the future research agenda. DESIGN: James Lind Alliance Priority Setting Partnership. SETTING: UK health service and community. METHODS: A steering group oversaw the initiative. Potential research questions were collected in an online survey, then checked to ensure they were unanswered. Shortlisting via a second online survey identified the highest priority questions. A parallel process with children was undertaken. A final consensus workshop was held to determine the Top 10 priorities. PARTICIPANTS: Children and survivors of childhood cancer, diagnosed before age 16, their families, friends and professionals who work with this population. RESULTS: Four hundred and eighty-eight people submitted 1299 potential questions. These were refined into 108 unique questions; 4 were already answered and 3 were under active study, therefore, removed. Three hundred and twenty-seven respondents completed the shortlisting survey. Seventy-one children submitted questions in the children's surveys, eight children attended a workshop to prioritise these questions. The Top 5 questions from children were taken to the final workshop where 23 questions in total were discussed by 25 participants (young adults, carers and professionals). The top priority was 'can we find effective and kinder (less burdensome, more tolerable, with fewer short and long-term effects) treatments for children with cancer, including relapsed cancer?' CONCLUSIONS: We have identified research priorities for children's cancer from the perspectives of children, survivors, their families and the professionals who care for them. Questions reflect the breadth of the cancer experience, including diagnosis, relapse, hospital experience, support during/after treatment and the long-term impact of cancer. These should inform funding of future research as they are the questions that matter most to the people who could benefit from research

Big data, qualitative style:A breadth‑and‑depth method for working with large amounts of secondary qualitative data

Archival storage of data sets from qualitative studies presents opportunities for combining small-scale data sets for reuse/secondary analysis. In this paper, we outline our approach to combining multiple qualitative data sets and explain why working with a corpus of 'big qual' data is a worthwhile endeavour. We present a new approach that iteratively combines recursive surface thematic mapping and in-depth interpretive work. Our breadth-and-depth method involves a series of steps: 1) surveying archived data sets to create a new assemblage of data; 2) recursive surface thematic mapping in dialogue with 3) preliminary ‘test pit’ analysis, remapping and repetition of preliminary analysis; and 4) in-depth analysis of the type that is familiar to most qualitative researchers. In so doing, we show how qualitative researchers can conduct ‘big qual’ analysis while retaining the distinctive order of knowledge about social processes that is the hallmark of rigorous qualitative research, with its integrity of attention to nuanced context and detail

The potentials and pitfalls of using Skype for qualitative (longitudinal) interviews The potentials and pitfalls of using Skype for qualitative (longitudinal) interviews

Abstract The use of digital communication technologies has become increasingly commonplace in social research. Yet, sparse attention has been paid to the potential of such technologies in Qualitative Longitudinal Research (QLR). This paper explores the implications of introducing one such technology, internet video calls (e.g. Skype, FaceTime, Google Hangouts), as a new mode of data collection into an established QLR study that has primarily generated data using biographical interviews conducted in participants' homes. The paper draws on the 'Your Space' project; a decade-long study following the lives of up to 52 young people from across Britain. Funded as one of eleven ESRC National Centre for Research Method's 'Methodological Innovation Projects' the most recent phase of the project investigates the implications of shifting from physical co-present interviewing to remote modes on key issues for QLR research such as sample maintenance, research relationship continuity, and rapport. In doing so, it assesses whether internet video calls might be a useful means of conducting short 'catch-up' interviews between the main waves of data collection, or as an alternative way of carrying out case study intensive interviews.