Aug 08

Forthcoming event: Approaches to Analysing Qualitative Data, 18th October 2016

On the 18th October 2016 we will be hosting a seminar at The Foundling Museum in London, ‘Approaches to Analysing Qualitative Data: Archaeology as a Metaphor for Method’.

The seminar will ask the question, how can we ‘dig down’, and where do we dig, to get an analytic grip when working with large and complex bodies of qualitative data? The metaphor of archaeology enables qualitative analysts to think about what lies ‘underneath’ the corpus of material being analysed, working extensively and intensively to identify and excavate meaning. Researchers working with different bodies of qualitative materials will be discussing how they approached their analysis, from a range of methodological perspectives. The seminar is likely to be of interest and use to researchers with a range of qualitative analytic skills and experience, from postgraduate to senior.

Our speakers include:

Professor Emeritus Clive Seale (Brunel University) : An archaeological approach working with keyword analysis of a large corpus of qualitative data

Professor Maria Tamboukou (University of East London) : Archaeology of knowledge and working in the archives

Dr. Susie Weller (University of Southampton) and Dr. Emma Davidson (University of Edinburgh) : A layered archaeological approach to analysis across multiple sets of qualitative longitudinal data

For full details and booking, visit the ‘Training and Events’ page on NCRM website. We look forward to welcoming you there!

 

Aug 01

Guest post #5, Sue Bellass: The challenges of multiple perspectival QL analysis

 

IMG_7916-Edit-800x800Our guest post today is by Sue Bellass, a PhD student in the School of Nursing, Midwifery, Social Work and Social Sciences at the University of Salford. Her thesis, which she is due to submit in August, has been exploring how intergenerational families are affected by young onset dementia over time.

In this post, Sue shares in detail her approach to analysing data over time, from multiple perspectives. The process has been complex and challenging, but has also brought creativity and freedom – and ultimately a deeper understanding of the lived experience of young onset dementia.

If you would like to know more about Sue’s research, contact her by email: s.bellass@edu.salford.ac.uk.

The challenges of multiple perspectival qualitative longitudinal (QL) analysis: a strategy created for an intergenerational study of young onset dementia

Although dementia is often perceived to be a condition that occurs in later life, around 1 in 20 people with dementia are below the age of 65 (Alzheimer’s Society, 2015). Over the last two decades there has been increasing interest in developing qualitative understandings of the experience of the condition in younger people; however, almost without exception existing studies have used cross-sectional designs, providing only a snapshot of life with an unpredictable, dynamic condition. For my PhD I decided to use a QL methodology to explore relationality over a twelve-month period by following five intergenerational families where one person had received a diagnosis of young onset dementia.

Since people with dementia are a marginalised, negatively positioned group (Sabat et al., 2011), I felt it was appropriate to democratise the research process to enable my participants to choose their preferred means of engaging with the study. This choice included the method of data collection (ethical approval was gained for interviews, audio/ video diaries, blogs and tweets) and, if participants opted for interviews, which family members would participate and where the interviews would take place.  Ultimately, 18 participants chose to be interviewed, 16 of whom were interviewed in pairs or larger family groups, with two preferring individual interviews. Interviews were conducted in three waves at months 0, 6 and 12.

Analysing the data set has been a challenging process. As Henderson et al. (2012) note, despite increasing interest in QL methods, methods of analysing and representing complex QL data sets have rarely been explicated. I experienced this as a mixed blessing; on the one hand, there is space for creativity, flexibility and freedom, on the other, there is room for doubt to flourish!  I have attempted to slice the data in different ways in order to interrogate the data set to best effect.  Inspired by Thomson (2010, 2014), I treated each family as a unique case and also aimed to create a cross-case analysis across the four generations represented in the families.

Example QL matrices

matrix_example

Initially I attempted to analyse the group interviews at the ‘family’ level, however it quickly became apparent that divergent accounts were being obscured.  Subsequently I took a multiple perspectival approach (Ribbens McCarthy et al., 2003), teasing apart individual experiences within the families, viewing them as cases within a case. For each person, I induced categories of experience then, to permit holistic re-engagement, organised the raw data in a time-ordered matrix across the three waves.

Then, again for each person, I created a longitudinal matrix adapted from Saldana (2003) to look for transitions and continuities, using motif coding, a form of coding which draws attention to recurring elements in experiences, and describing through-lines, a crystallisation of a participant’s change over time. Although it could be argued that such an approach may disguise intersubjective creation of meaning, I consciously retained a focus on relationality, creating spaces within the matrix to capture data on meaning-making processes over time. Finally I created an intergenerational matrix, organising the data by generation to look for patterns and themes, setting the data against the backdrop of the recent increasing public, policy and research interest in dementia to try and interweave biographical, generational and historical timescapes.

Qualitative research has faced criticism for lack of clarity regarding the relationship between theory and data, and this, I argue, is an important area to address as we continue to develop the contours of QL research. My own perspective has been influenced by Mills (1959), who describes a ‘shuttle back and forth’ between theory and data. I have utilised such an iterative approach, and have drawn on theory from the sociology of chronic illness and family and relationship sociology to develop understandings of the intergenerational experience of young onset dementia.

References:

Alzheimer’s Society (2015). Dementia 2015: Aiming higher to transform lives. London: Alzheimer’s Society.

Henderson, S., Holland, J., McGrellis, S., Sharpe, S., & Thomson, R. (2012). Storying qualitative longitudinal research: sequence, voice and motif. Qualitative Research, 12(1), 16-34.

Mills, C.W. (1959). The sociological imagination. London: Penguin.

Ribbens McCarthy, J., Holland, J., & Gillies, V. (2003). Multiple perspectives on the ‘family’ lives of young people: methodological and theoretical issues in case study research. International Journal of Social Research Methodology, 6(1), 1-23.

Sabat, S.R., Johnson, A., Swarbrick, C., & Keady, J. (2011). The ‘demented other’ or simply ‘a person’? Extending the philosophical discourse of Naue and Kroll through the situated selfNursing Philosophy, 12(4), 282-292.

Saldaña, J. (2003). Longitudinal qualitative research: analyzing change through time. California: Alta Mira Press.

Thomson, R. (2010). Creating family case histories: subjects, selves and family dynamics. In Thomson, R. (Ed.) Intensity and insight: qualitative longitudinal methods as a route to the psycho-social. Timescapes Working Paper Series No.3.

Jul 26

Research team blog 2: NCRM Research Festival

We recently had the pleasure of presenting our work at the 7th ESRC Research Methods Festival, hosted by the University of Bath. And what an event it was! Over three days we joined social scientists from a huge range of disciplines and sectors and at different points in their research careers.

Wine reception

Wine reception

It was great to find that many of the methodological issues being discussed ‘spoke’ to our own research. Big Data, longitudinal methods and the qualitative / quantitative divide were all hotly debated. Jane Elliott’s keynote addressed the term ‘Big Data’, the digital revolution and the computational techniques being developed to analyse large corpuses of unstructured data. Jane highlighted the possibilities machine learning can bring to Big Data analysis, but also the important role of the researcher in determining clear research questions, and validating outputs. She concluded that rather than dividing qualitative / quantitative research further, computer-assisted methods can empower, and bring both groups together.

Time was also a focus: from Bartlett’s look at the diary methods as a means of capturing lives as they are lived; Gershuny’s and Sullivan’s consideration of time use diaries for understanding the rhythms and patterns of everyday activities; and Goodman’s work on tracking, over time, the experiences of those living and dying with dementia in care homes. Technologies are advancing many of these methods, and researchers are being afforded greater access to longitudinal datasets. CLOSER Discovery was one resource promoted at the Festival, an online resource enabling researchers to view and appraise data from eight of the UK’s leading longitudinal studies.

So where does our research fit with these issues? We presented with Anna Tarrant, Leverhulme Fellow at the University of Leeds. Anna’s work has featured on our site before (check it out here), and together we outlined our ongoing strategies for working with combined qualitative longitudinal datasets.

As we detailed in our presentation, we are likening our work to the stages of an archaeological excavation and are finding this helpful in thinking about how we access the data at different levels and in different ways. This is a rather apt metaphor for interrogating the large and complex ‘field’ of QLR since it invokes the notion of understanding the layers of the past, excavating the past through waves of data, and across the lifecourse.

This approach has taken several stages, with each ‘digging’ further into the dataset. We began with explorations akin to a ‘surface survey’ to evaluate the breadth and nature of the archive, and to organise it into a composite dataset. We then used ‘geophysical surveys’ to explore the landscape of the data without penetrating the surface. Here we employed a range of computer-assisted technologies to examine word frequencies; words or phrases that often used with other words or phrases; and word clusters. Using the outcomes of our different ‘surveys’, we identified ‘cases’ for further testing. In these shovel test pits we were able to use example cases to simultaneously compare computer-assisted corpus-oriented analyses with more conventional in-depth explorations.

Our next step is to move onto ‘deep excavations’. These will use the outcomes of our ‘surveys’ and ‘test pits’ to inform where and how we delve deeper into the detail of selected cases, with a focus on change and continuity across layers of time. It is here, as Jane suggests, that we will start to ask specific and focused questions of our data.

We have found that while quantitative methods for analysing large corpuses can provide insight into the texture of a qualitative dataset, concurrent ‘thick’ readings can be used productively to expand meaning and understandings. ‘Big’ qualitative data analysis necessitates a combination of interpretive techniques and, with this, has the potential to bring qualitative and quantitative approaches into conversation. We hope to continue this conversation as we progress our research.

We hope those who attended our session enjoyed it: we are looking forward to sharing our work further. One such event will be an NCRM short course, which we hope to publicise soon. In the meantime, the National Centre for Research has a wide range of training and events to choose from across the UK.

Jun 27

Guest post #4, Libby Bishop: Data from the past and for the future – Qualitative longitudinal data available at the UK Data Service

We are pleased to have Dr Libby Bishop contribute as a guest blogger. Libby Bishop (Ph.D.) is Manager for Producer Relations at the UK Data Archive (University of Essex).  She provides support and training on data management toLibby Bishop researchers and data producers, with specialisation in ethics of data use: consent, confidentiality, anonymization and secure access to data.  She also teaches workshops on secondary analysis of qualitative data. Libby worked as a Senior Research Archivist at the University of Leeds, where she was responsible for creating and managing the Timescapes archives and providing support for those using the data. Libby has published individually, and with others, on data management, qualitative secondary analysis and the ethical issues associated with big data. Her work has been critical in supporting the sharing and re-use of qualitative data, and advancing a more nuanced understanding of secondary data analysis.

In this post, Libby explains how a data archive is the perfect starting point for those new to qualitative longitudinal research.  

Data from the past and for the future: Qualitative longitudinal data available at the UK Data Service

You may already be a member of the tribe of qualitative longitudinal (QL) researchers if you are reading this.  But what if you are just starting out? You might be curious about how others have done QL projects.  Of course, there are published articles to look at, and there are many to choose from now. But wouldn’t it be helpful to actually look at the data other researchers have used? To read in some detail what strategies were used to maintain contact between interviews? To read transcripts to discover, for example, exactly how the interviewer gently guided the respondent back to topics from the previous contact, without losing the thread of more recent events? All this, and more, is possible by looking at qualitative longitudinal data collections available for research at the UK Data Service.Time-Background-Clock-Public-Domain

Below I provide a brief introduction to just a few of these collections, of which we have dozens. These are available to be downloaded and used by researchers (after having registered with the Service). Two of these studies are about older age, and another is on a timely issue: elections.

SN 851919 Maintaining Dignity in Later Life: A Longitudinal Qualitative Study of Older People’s Experiences of Supportive Care

The aim of this study was to examine preparations for the end of life made by older people with supportive care needs and the factors that support or undermine a sense of dignity. Thirty-four participants in Bristol and Nottingham were recruited via GPs and day centres. All had health problems that required support and care to varying degrees, including family care and support, medical treatment, community nursing, home care services and moves to care homes. They were interviewed face-to-face on four occasions (on average) between June 2008 and January 2011 and contacted by telephone between interviews. Face-to-face interviews were recorded and transcribed verbatim.

SN 5237 Adding Quality to Quantity: Quality of Life in Older Age, 2000-2002

The broad aim of the study was to define the constituents of quality of life in older age. The research questions were twofold: how do older people define and prioritise quality of life, and how do they feel it can be improved? This study represented a unique multidisciplinary and mixed methods collaboration between investigators with backgrounds in sociology, psychology, social gerontology, transport planning and clinical epidemiology. Following the fielding of the questionnaire, 80 respondents were selected for an in-depth interview to probe factors further affecting quality of life.

SN 6861 Qualitative Election Study of Britain, 2010

This research project recorded the views and concerns of Britons before and after the 2010 General Election. By conducting 14 focus groups with people in England, Scotland and Wales the project investigated, qualitatively, pre- and post-election views. The aim was to generate data that: 1) provided insights into the views and perceptions of citizens on politicians, party leaders, and political issues (e.g. civic duty, political alienation, political activism) before and after the general election; 2) allowed for analysis of the meaning that underlies their assessments, uncover sources of normative values, and make explicit the tacit assumptions participants use to reach their judgements. Three additional focus groups were conducted on the night of the first ever Leaders’ Debates and the transcripts record people’s expectations in advance of the debates and their reactions afterwards. As well as the focus group transcripts, the collection includes a quantitative file of results from the pre-focus group questionnaire given to participants.

And watch this space – comparable data from the 2015 UK elections will be arriving shortly.

What could be better than QL data? Getting funded to do research with QL data! The ESRC has a programme, the Secondary Data Analysis Initiative, which does just that. It offers funding for up to 18 months and £200,000 for research that collects no new data, but uses data from selected existing resources. One of the designated resources is Timescapes, a rich lode of QL data.  Another, the Qualitative Archives on Ageism and Conflict, is held at the Northern Ireland Qualitative Archive.

As always, if you want any help getting starting or looking for data, just get in touch.

Jun 08

Guest post #3, Prof Rachel Thomson: Case histories in QLR

rachelthomsonRachel Thomson, Professor of Childhood & Youth Studies at the University of Sussex, writes our third guest post. Rachel is also one of the directors of the Sussex Humanities Lab. She has been involved in several qualitative longitudinal studies and has co-edited two special issues of the International Journal of Social Research Methodology on the topic in 2003 (6:3) and 2015 (18:3). She blogs at http://blogs.sussex.ac.uk/everydaychildhoods/ and https://newfrontiersqlr.wordpress.com/

In this post Rachel explores case histories in QLR. We too have been contemplating different understandings of ‘the case’ and Rachel’s post has encouraged us to re-think what we consider to constitute a case and how we might go about analysing cases across an archived dataset that comprises six QLR studies. We found her thoughts on the fluidity of cases and practices of casing very insightful. Rachel and colleagues will be running a two-day training course on Case Histories in Qualitative Longitudinal Research’ at the University of Sussex on 6-7th October 2016. We welcome your comments and ideas. 

Case histories in qualitative longitudinal research – some thoughts

Questions of scale

Qualitative longitudinal research can play around with our ideas of scale. A study can seem to be ‘small’, following 6 cases for example, yet at the same time can be ’big’, or perhaps a better word is ‘deep’ in collecting many instances of data for that case over an extended or just intensive period of time. Discussing this point Lyne Yates (2003) makes a case for QLR having a different kind of ‘warrant’ – or relationship with validity –moving us away from ideas of cases as being ‘representative’ in an abstract way –be that they are typical or that they may provide insight into a wider population through the operations of probability sampling. By following just cases over a period of 10 years (as we have in an ongoing study) we are able to understand relationships, sequences, consequences and antecedents in a concrete way- exploring the relationship between what we say and do, and between what we want and what we get – as researchers and as participants. More recently Liz Stanley has challenged the qualitative quantitative distinction on her work using collections of letters showing that in an era of digital data qualitative material and quantity and quantification are not mutually exclusive (Stanley 2015). Rather we might think of scale in terms of a zooming in and zooming out of perspective, and the potential to combine the affordances of the microscope and macroscope. Debates about scale within QLR parallel debates about scale within ‘big data’ and the kinds of digital tools that can be used to explore patterns, to zoom in for the close-up and to zoom out for the landscape or the map.

From cases to casing

QLR can be designed in different ways in order to reveal different kinds of cases. At the most basic level we might think of the case as a unit of analysis that we follow over time. So for example in our project Making Modern Mothers, the unit of analysis was women about to have their first baby. Yet cases are not stable, especially when pregnant and in this study we expanded our case to include significant others (especially grandmothers) and children when they were born. These children are now the focus of a follow-on project that explores digital childhoods, yet the backstory of the family is a vital part of the case and family members play a key part in narrating the case of the child who is the focus and who as we watch moves from being a ‘case’ of a child into a teenager and an adult. Analytically we can also think of the case in other ways, for example thinking about all of the urban families together and considering their affinities and their difference from the rural families. We might also think of the case of social class, or cutting the data set in the opposite direction, from the diachronic to the synchronic, considering how the families responded to a key external event such as the ‘credit crunch’ that turned into the extended period of austerity through which we continue to live. Rather than thinking of cases as stable and defined simply through existence we might follow Charles Ragin (1992) to think about practices of ‘casing’ in social enquiry, a flexible analytic practice that pays due respect to the complexity of the social realm and which in linking ideas and evidence had the potential for the testing and emergence of theory.

The case history and the archive

The ‘case’ itself is an object and genre with a history linked to practices of natural history, collecting, sorting and narrating and reflections. Butterflies were collected and displayed in a case long ago in a way that has parallels with the ways that doctors and lawyers began to conceptualise case histories and case law. A special issue ‘On the case’ of the journal Critical Inquiry helps us as social scientists understand our practices in historical and cultural context as well as helping us see the kinds of spillages that echoes that may travel between medical, legal, scientific and literary uses (Berlant 2007).There is no definitive way of constructing or telling a case, yet we may find ourselves being drawn into particular tropes taking up associated forms of authority. When telling the story of an individual over time it may be hard to escape the perspective of the doctor or the social worker who is able to see and describe underlying causes or pathologies. Perhaps we need to deliberately disrupt these well-worn narrative tendencies by reading materials against the grain, changing the direction of our analysis, or moving between individual and collective or conceptual cases self-consciously in order to find new perspectives.

In earlier work I suggested that we might make use of the notion of the archive more fully in our work learning from the critical work that has been done of reading the archive (Thomson 2007, McLeod & Thomson 2009, Thomson 2011). If we think of our data sets as archives, which can be organised into all sort of cases (individuals, institutional, geographical, temporal), we can also think about the kinds of stories that can be told from the archive, putting material together in a particular way will enable a particular history. Yet this is not definitive or exclusive. That material could be told in different ways by different analysts without taking away from the ‘validity’ of the material itself. Digital information systems allow individuals to build their own archives, copying and linking data from public collections and potentially making their own archives available to others. Sociological data sets are also made available to and interrogated by secondary analysts and there is a compelling case for social scientists to build on the lessons of historical and literary scholars about archival methodologies and epistemologies as well as understanding the new methodologies of the digital humanities. Having my data used by secondary analysts encourages me to believe that the potentials of this area are just beginning to be explored by sociologists – see for example http://www.whiteswritingwhiteness.ed.ac.uk/blog/archive-project-sendoff/

An event

The more I think about the case, case studies and case histories, the more I feel that they lie on the emergent boundaries of new kinds of sociology – even though the case study is associated with the very birth of the discipline and the Chicago School. On October 6th and 7th my Australian colleague Professor Julie McLeod and I will be teaching a 2 day advance methods course for the NCRM, based in the Mass observation Archive at the University of Sussex . The course responds to the request for more focus on methods of analysing QLR data among the participants at our 2015 course ‘Affective methods: capturing everyday temporalities with QLR’. In this course we will be exploring what it might mean to make a case from data archives, both those we generate from primary research, those we find in archives, and those we construct from a range of heterogeneous sources. The course will explore methodologies of the boundaries of history and sociology and between scientific and humanities paradigms. Please join us. http://www.ncrm.ac.uk/training/show.php?article=6361

References

Berlant, L. (2007) ‘On the case’ Critical Inquiry: special issue 33 (4)

McLeod, J. & Thomson (2009) Researching Social Change: qualitative approaches, Sage.

Ragin, C. (1992) ‘”Casing” and the process of social inquiry’ in Ragin & Becker (eds) What is a case: exploring the foundations of social inquiry, Cambridge University Press.

Stanley, L. (2015) ‘Operationalizing a QLR project on social change and whiteness in South Africa, 1770s – 1970s” International Journal of Social Research Methodology 18:3, 251-65.

Thomson, R. (2007) ‘The qualitative longitudinal case history: practical, methodological and ethical reflections’ Social Policy and Society, 6(4): 571-582.

Thomson, R. (2011) Unfolding lives. Youth, gender and change. Policy Press

Thomson, R., Hadfield, L., Kehily, M.J. and Sharpe, S. (2010) ‘Family fortunes: an intergenerational perspective on recession’ 21st Century Society 5 (2): 149-157

Thomson, R Thomson, R. (2014) Generational research: Between historical and sociological imaginations, International Journal of Social Research Methods, 17 (2) 147-156

Yates, L.(2003) ‘Interpretative claims and methodological warrant in small number qualitative longitudinal research’, International Journal of Social Research Methodology 6 (3): 223-32.

 

 

Apr 25

Guest post #2: Dr Fiona Shirani: Visual approaches in QLR

Our second guest post is written by Dr Fiona Shirani, a Research Associate at Cardiff University. She will be leading a qualitative longitudinal work package as part of the interdisciplinary FLEXIS programme, which seeks to investigate how flexible energy systems can meet modern-day energy challenges.

In this post, Fiona reflects on the intersection between QLR and visual methods, reflecting on both her current research and the qualitative longitudinal “Men as Fathers” project, part of the UK-wide Timescapes network. This project explored the transition to fatherhood in both the immediate (over the first year) and longer term (8 years post-birth). One of the many questions Fiona’s work has provoked for us as a team is how to incorporate visual data into our dataset, and the reasons why visuals (and their meaning) can feel more ‘distant’ in secondary analysis than the written word. We welcome your comments and ideas. 

Time to be engaging? Multimodal methods in QLR

Both qualitative longitudinal research (hereafter QLR) and visual methods have seen a surge in interest in recent years, yet relatively little attention has been given to the intersection of the two. This is perhaps surprising given many of the arguments in support of visual or multimodal methods take on a particular resonance in the context of QLR. In this short blog, I draw on my experience of designing and undertaking visual activities in two QLR projects (Energy Biographies and Timescapes) to highlight some relevant issues.

Methodological innovation is an important element of research, and visual approaches have been key to enhancing creativity in qualitative work. QLR provides greater scope for methodological innovation and experimentation due to the extended timescales and flexible nature of the approach. For example, an activity that would take up too much time for a one-off study represents a smaller proportion of a QLR project. There is also time and space for reflection between interviews, giving the researcher an opportunity to hone and adapt activities for later waves of data collection.

Beyond methodological innovation, an advantage of incorporating a range of activities is the potential to make the research experience more engaging for participants. QLR requires a significant commitment from participants and maintaining the sample over time is an important concern. Whilst some participants enjoy the format of a qualitative interview, others may relish the opportunity to direct conversation through a photo-elicitation exercise, for example. Activities can also be conducted between interviews, serving as opportunities to both maintain contact and collect further data.

In both Timescapes and Energy Biographies we used visual activities to encourage participants to talk across extended time frames, thinking about their past memories and anticipated futures. Thinking temporally is a particular concern of QLR research yet can prove challenging for participants. Having a tangible reference point in the form of a visual representation can help anchor discussions.

Alongside these benefits, consideration must be given to some of the challenges arising from using multimodal approaches in QLR. Most notably, whilst accumulation of information about the individual is a strength of QLR, it also raises issues around anonymity and confidentiality. Adding visual data further complicates this issue and requires careful thought about how visual artefacts produced during the research should be analysed and presented, as well as challenges for archiving and data re-use.

In our Timescapes and Energy Biographies projects we have primarily used images as a means of eliciting talk; therefore analysis has focused on pictures and their accompanying text. We have found that narratives often go beyond what is represented in the image and therefore have argued the importance of attending to both talk and text. However, there are many possibilities for the analysis and creative presentation of multimodal data, and participant-generated images also inspired some elements of our public engagement exhibition. We also explored the possibility of working with images alone during a multimodal workshop with academic colleagues, where feedback indicated that the everyday nature of the images made them accessible for people to imbue with their own interpretations. However, there are clearly important ethical issues to consider in presenting images without the contextual information of their production and asking others to engage creatively with them.

Visual or multimodal approaches have much to offer QLR and combining the two could provide multiple benefits to future research.

See our paper in the International Journal of Social Research Methodology for more detail.

Mar 21

Forthcoming event: BIG QUALIDATA, 9th May 2016

BIG QUALIDATA: Tackling Analysis of Very Large Volumes of Qualitative Data in Social Science Research

Monday 9th May 1-4pm, University of Edinburgh, Manchester and Southampton.

Can social researchers scale up techniques of working with qualitative data and meaningfully analyse massively more text than they can possibly read? Our forthcoming seminar will seek to explore this question with three researchers using different types of software: R, Leximancer and NVivo.

You can join the event in Edinburgh: Staff Room 6th Floor Chrystal Macmillan Building, 15a George Square EH8 9LD or join interacting audiences watching on screen and able to ask questions in Manchester (Room 2.07, Humanities Bridgeford Street building) & Southampton (Room 58/2097, Murray Building, Highfield Campus).

Our speakers include:

  • Professor Ken Benoit, Professor of Political Science Research Methodology, LSE

Using R in analysis of news media and political discourse

  • Dr Elena Zaitseva, Teaching and Learning Academy, Liverpool John Moores University

Using Leximancer to analyse written feedback from the Postgraduate Taught Experience Survey (feedback from students in 100 Higher Education Institutions).

  • Professor Wendy Olsen, Professor of Socio-Economics, Manchester University, with Samantha Watson and John McLoughlin

Keyness and Discourse Intertextuality in Qualitative and Mixed Methods Research (Using NVivo with the British National Corpus)

Mar 09

Guest post #1, Dr Anna Tarrant: Reflections from the Men, Poverty and Lifetimes of Care study

This is our first guest post, written by Dr Anna Tarrant. Anna is currently working as a Leverhulme Trust Early Career Research Fellow at the University of Leeds. She is leading a research project called ‘Men, poverty and lifetimes of care’ that qualitatively explores how men negotiate their care responsibilities in low-income localities. As part of the study she will be conducting qualitative secondary analysis of two datasets from the Timescapes archive. Susie and I recently met Anna to chat about our respective projects. While their aims are different, they share many methodological and conceptual issues. How, for instance, should we define a case? How does our epistemological positioning shape our approach to QL data analysis? Should qualitative secondary data analysts forge relationships with the primary researchers? How can we keep a strong purchase on time and temporality when looking across different projects? And can software help us? We hope Anna will be kind enough to blog again at a later stage in her project to reflect on some of these questions. In the meantime, you can follow Anna’s own wonderful blog here.

Assessing the feasibility of secondary analysis within and across two qualitative longitudinal datasets; reflections from the MPLC studyAnna image

Like the NCRM project that Susie and Emma are leading, the Leverhulme Trust funded ‘Men, Poverty and Lifetimes of Care’ (MPLC) study has facilitated important opportunities for reflection on key methodological questions about the feasibility of working with multiple qualitative longitudinal datasets. Qualitative secondary analysis (or the re-use of qualitative data in it’s simplest form) is a relatively novel approach in the context of the much wider spread re-use of quantitative data, yet it has already provoked a great deal of debate, particularly in relation to issues of epistemology, ethics and context (see Irwin, 2013). An emerging area of concern within these debates focuses on the possibilities and pitfalls associated with bringing multiple datasets into analytic conversation and whether or not this is possible or even desirable.

In the first year of the MPLC study, I conducted a qualitative secondary analysis on two datasets from the Timescapes archive, allowing me to reflect on some of these questions. At the outset of the proposed study, which aimed to explore men’s care responsibilities in low-income localities, I identified the Following Young Fathers (FYF) and Intergenerational Exchange (IGE) studies (see the Timescapes website for more information about both studies) as possible resources for exploring key themes in relation to this substantive area of focus. For the purposes of rigor, I employed a three stage methodological strategy that was attentive to the principles of the ‘stakeholder ethics’ model (Neale, 2013) including:

  1. Familiarisation with the datasets (by having individual conversations with available members of the original research teams and reading project outputs),
  2. Holding a data sharing workshop to:
    1. Consolidate the familiarisation process and,
    2. To facilitate a more collaborative mode of working with the original project teams by bringing the datasets into analytic conversation with a focus on the broad themes of men and care,
  3. The Qualitative Secondary Analysis itself.

These processes are discussed in much greater depth in a Timescapes Working Paper.

QSA across multiple datasets has been really insightful and productive. While a time-consuming and difficult process (particularly in becoming familiar with data generated by others), it has fed directly into the design and conduct of the second empirical phase of the MPLC study, for which, I am interviewing men living in low-income localities. In combination, the FYF and IGE datasets have also provided a sampling framework for the MPLC study. Since September 2015, I have focused on recruiting men living in low-income circumstances of different age groups, in order to explore men’s trajectories and their care responsibilities over time. I have also been able to recognise the importance of men’s wider interdependencies in low-income localities and this has prompted me to ask the participants in the MPLC study, specific questions about the significance of their wider support networks. In terms of substantive outcomes, I have gained greater insight into men’s experiences of living on a low-income over time and how gendered inequalities mediate these processes. While the datasets are not directly comparable, the participants in both studies live in contemporaneous times and there are remarkable similarities across the datasets with regards to how men experience low-income life. In bringing the datasets into conversation, it has been possible to test my emerging theories with empirical data from both datasets.

For more information about the MPLC study please follow the study on Twitter @menpovcare and the study website http://menandcare.org.uk

Mar 07

Research team blog 1: Getting started

Susie and I both began working on the project as part-time research fellows at the end of May 2015. Now as we go into our tenth month we would like to share with you some of the key pieces of work completed so far.

Our first few months were spent conducting the usual organisational activities required for a project of this length: developing a timeline of our planned activities, submitting our ethics applications, examining key readings, writing our impact pathway and importantly, getting access to our data via the Timescapes project archive.

In total, we are including six of the Timescapes projects in our project (Siblings and Friends; The Dynamics of Motherhood; Masculinities, Identities and Risk; Work and Family Lives; Intergenerational Exchange and; The Oldest Generation). Unfortunately, Youth Lives and Times is currently being updated and wasn’t available. Together this amounts to approximately 1,000 files, 165 cases (we plan to blog soon about what constitutes a ‘case’) and 1,873,553 words. Visual data in the form of activity sheets and photos adds further to the volume of data, and its complexity. Even from the beginning we could see the challenges of scaling up at this level.

Of course, we wanted to get straight into the analysis but we also knew (from experience!) that being able to find and categorise files was critical. We spend a considerable time re-labelling our data so that it had a common filing system across all six projects. All the data was uploaded to an Nvivo server project (a decision which will be another future post) and attributes attached to the data. This would enable us, we hoped, to query the data by characteristics such as age, gender, interview ‘wave’, household type or martial status at a later stage.

Although we were accessing the Timescapes data as secondary researchers, we should say that as a team we have a personal relationship to part of the data. Ros and Susie managed the Siblings and Friends project, while Lynn was responsible for Work and Family Lives. Not only has this connection to the data helped us understand better its origins, but it has also facilitated the many queries made to the original researchers (who have been very kind in answering). This has been invaluable in helping us resolve issues around missing and mis-labelled data – however, we also recognise that not all secondary qualitative researchers would benefit from this contact.

Once the datWord clouda was organised, we moved on to scope out different approaches that we might take to analysing the data – what we have called a ‘test pit’ approach. We will discuss some of these in more detail in later posts, but our main interest has been in thinking about the ways in which care and intimacy might be identified and recognised within large volumes of qualitative data. We recognised that our usual approaches to analysis – in-depth narrative or biographical analysis – would not be possible given the sheer volume of the textual data. We therefore looked to keyword analysis as a means of getting, what Clive Seale (2013) calls, an “ariel view” of the data. Seale suggests that once complete, keyword analysis can then be used as a means for more detailed analytical work.

To explore this we have run several ‘tests’ including:

  • An analysis of word frequencies across all six projects, including a detailed comparison of the most popular words across the data sets.
  • Searches for the collocation of words and the presence of specific phrases.
  • A comparison of the entire corpus of data with a pre-defined list of intimacy and care key words.
  • Conducting in-depth readings of a selection of cases. This more conventional approach to qualitative data analysis was then compared to the results from computer-assisted keyword analysis to determine the extent more implicit discussions of instances of intimacy and care are identified through keywords.

There is not space in this blog to discuss the findings in-depth. However, our initial foray into keyword analysis has drawn several conclusions. First, and not surprisingly, much of the “ariel view” generated is shaped by the focus of the project and resultant direction of the questions (i.e. friendship is obviously central to Siblings and Friends, while work is central to Work and Family Lives). Second, while keywords may refer to component parts of intimacy they are not necessarily sufficient conditions for intimacy. Our detailed case file review revealed that intimacy is often discussed far more implicitly (or are unsaid), and also in a way unique to the individual participant. And finally, how can keyword analysis effectively help us capture time and the cumulative nature of intimacy? So far, temporality seemed difficult to hold onto in the analysis process.

As we now move onto the next phase of the research, we are considering ways in which we can focus our analysis onto one particular aspect of care and intimacy as a means of gaining greater theoretical purchase on the datasets. We will continue to update you as the study progresses on this blog. Please do follow our work and provide your comments and ideas.

Mar 07

Welcome to the project

Welcome to the ‘Working Across Qualitative Longitudinal Studies’ blog. Here you will be able to follow our research process, the team discussions (and debates) and our findings as they evolve. We are very aware that accounts of qualitative research – especially the process of data management and analysis – are often sanitised by the time they reach academic journals. We also know that qualitative longitudinal research (QLR) has the capacity to add new layers of complexity to qualitative data analysis. This not only comes from the volume of data that QLR can generate, but also the disciplinary requirement to engage with temporality in all its forms across and between data sources.

One of the core elements of our project is to contribute to good practice in analysing large scale QLR, both within and across projects. It is incredibly important that our own analytical processes are not kept in a ‘black box’, shrouded in mystery. Rather, over the next two years, the project team (Emma, Lynn, Ros and Susie) will share our own struggles, deliberations and successes. We hope that by doing this we can enrich the landscape of QLR, and support other researchers as they journey through their own projects.

This blog will also include the experiences of others exploring the challenging world of qualitative longitudinal research. With guest posts from early career researchers, to international experts, on topics as varied as the ethics of using big qualitative data, using secondary qualitative data and computer-assisted qualitative data analysis software, we will profile the diversity of QLR taking place in the UK, and beyond.

If you would like to write for us as a guest contributor, please email us on qlr@ncrm.ac.uk to discuss.

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