1/ I've been having a lot of discussions about getting started with familiarisation & coding in reflexive thematic analysis recently. So here's a 🧵 with the highlights. Familiarisation is about getting to know the contents of your data - if you interacted with participants to... 2/ generate them & you transcribed them this gives you a head start. It's also about starting to engage with your data analytically - what's going on here? & reflecting on your emotional responses to the data/participants - how do you feel when you read them/certain participants?

1/ The language & concepts of nonpositivist/Big Q qualitative research - what do we take from quantitative/positivist research, what do we rework, what do we leave behind?

A 🧵 of musings starting with generalisability - a term often associated solely with quant. 2/ I have often equated generalisability with statistical generalisability & argued that it's a concept that doesn't hold relevance for qual. But this paper by @BrettSmithProf convinced me that generalisability is a broader concept & can be reworked: tandfonline.com/doi/abs/10.108…

1/ @ginnybraun & I made it to the Build-a-Bear Workshop in Bristol! Here's why we think it works as a great 'metaphor' for thematic analysis & for challenging common misconceptions of TA. We mentioned this in our webinar yesterday eve which you can watch on YouTube (link below). 2/ People often assume that TA can only be used for basic descriptive/summative analyses, that it's atheoretical like qualitative content analysis often claims to be or only realist/essentialist, lacking the sophistication of grounded theory or IPA. Students often contact us...

1/ I didn't link to *that* paper because of prudishness - I have led/taught on a module on sexuality since the early 2000s & give lectures on explicit topics including masturbation... I didn't link to it for several reasons including not want to encourage nudge nudge "humour"... 2/ which communicates discomfort with the topic... there is a role for humour in talking about sex but not here, not now. The topic is distressing in various ways and doesn't need air time on Twitter. The primary concerns are ethics, why this research was allowed to go ahead...

1/ A thread on piloting data generation "tools" in qually research & different ways of thinking about piloting in small q & Big Q qually. First up, what's small q and Big Q qually? Small q is where qually is defined by collecting & analysing qual data but the underpinning values 2/ default to disciplinary norms - typically positivism. It seems to be most often practiced unknowingly - the assumption is that this is what constitutes good practice & there isn't an awareness of other possibilities for qual. Big Q qual involves both qual techniques & the

1/ A thread on ensuring/assessing quality in qualitative research & whether checklists/guidelines that aspire to be universally applicable have a role to play.
The first problem with universal guidelines is that there isn't a widely agreed on definition of what qually research is 2/ A - over simplified - definition of qually research (well any research) is that it involves tools & techniques for collecting & analysing data & research values (paradigms, 'ologies) that tell you what the data represent, what you can access through them: contextually situated

1/ I'm just a thematic analysis author standing in front of a qualitative researcher and asking them to bloody read Braun & Clarke 2006 before citing it...

Honestly the things people claim @ginnybraun and I say that we don't. A short thread of some prize winners... 2/ A read a few weeks ago that apparently we don't provide a "plan" for analysis in Braun & Clarke 2006 - the author presented this as a justification for using grounded theory coding techniques to do TA... A) The paper is literally setting out a "plan"; B) We are expressly

1/ A thread about how to judge if your qualitative data are rich (& what does that mean?!) & some tips for what to do if they aren't. Let's imagine a qualitative study using qualitative surveys & thematic analysis. If you've not seen a qual dataset before - or a particular kind 2/ of qual dataset it can be really difficult to judge if the data are good quality & good enough for a more interpretative analysis like reflexive TA. This is why my & my students' judgements can differ because I've seen lots of datasets over the years. So one tip is to check

1/ A posted a thread a while back of my criticisms of the COREQ checklist - I've been digging around for published critiques & wanted to share what I've found & ask if anyone knows things I've missed. Starting with this fab paper: sciencedirect.com/science/articl… 2/ The authors attempted to replicate COREQ using the authors' account of their process & couldn't. They powerfully argue that the development of COREQ was not trustworthy and therefore it's not a credible tool to evaluate the reporting of qualitative research.

1/ A thread on why I find the COREQ 32-item checklist reporting criteria for qualitative research so problematic. You can read the paper outlining the consolidated criteria for reporting qualitative research here: academic.oup.com/intqhc/article… 2/ If you use COREQ please read this attempt to replicate the development of the checklist - it's pretty damning and raises serious questions about why it continues to be promoted: sciencedirect.com/science/articl…

1/ Head on over to my YouTube channel for new lectures on Thematic Analysis, the Foundations of Qualitative Research & Qualitative Research Design created by me, @drnikkihayfield & @ginnybraun with narration by me (& occasionally my cat!) - please share!: youtube.com/channel/UCLBw6… 2/ We will add the slides & handouts to thematicanalysis.net as soon as we get a chance. There are two - 3 part - lectures on the Foundations of Qual Research. Foundations 1 is a gentle introduction for those new(ish) to qual, starting w/ what is qual?:

1/ To follow up on yesterday's small q/Big Q thread here are the things I'm making a note of to emphasise in this year's qually res methods teaching to help students avoid appearing to be confused about their Q when they come to write their dissertation/thesis. First is research

https://twitter.com/drvicclarke/status/1444258228439764993

2/ questions - we see a lot of qual questions that are thinly disgused quant questions (how does A relate to B) in ethics apps. I'm going to give students egs of qually research questions - including the typology from Successful Qualitative Research: uk.sagepub.com/en-gb/eur/succ…

1/ A thread on the Big Q/small q qualitative distinction & why I find it so helpful for "mapping" different approaches to qual research. It's what informs @ginnybraun & my writing on qual research & @drnikkihayfield & my shaping of the qual res methods curriculum @PsychUWEBristol 2/ First point is it's not our distinction - it comes from this chapter by Kidder & Fine (although I LOVE Michelle Fine's writing on qually I have to say that students don't generally find this chapter that helpful in developing their understanding) - onlinelibrary.wiley.com/doi/abs/10.100…

1/ At the start of a new academic year, a thread for folk supervising qually projects using TA. You read B&C 2006 ages ago - what's changed? What common problems do you need to watch out for in student work? 10 things you need to know - w/ readings for those w/ a bit more time! 2/ Number 1 - we now call our approach reflexive TA to acknowledge that TA is a diverse family of methods & our approach centres the reflexive & "artfully interpretive" researcher (Finlay, 2021). Read more here: tandfonline.com/doi/abs/10.108…

1/ A thread about Harvard referencing style. My message for students is always use whatever Harvard style you like just use it consistently. What I've realised is that students struggle with the consistently bit because they haven't been taught where the choices are. So here's a 2/ thread on some of these choices. First up Harvard is a generic style where you cite author name(s) + publication date in the main text & then have a separate list of references at the end. There are lots of different versions of Harvard - APA, lots of unis have their own

1/ Themes don't emerge but themes can be emergent?! What? Eh? A quick thread on the differences between emerge(d) & emergent. @ginnybraun & I bang on about themes not emerging. We are critical of the phrase "3 themes emerged..." etc for 2 reasons. First, it can imply themes are 2/ ontologically real things that exist in data independent of a researcher's engagement with the data. If themes are real the researcher's role becomes one of extraction or discovery. In our reflexive TA approach themes aren't real! They're not in data fully formed. Instead,

1/ @ginnybraun & I have written a lot about TA since our first paper Using Thematic Analysis in Psychology in 2006. Here's a thread of things we have written since then, starting with a paper on what constitutes quality practice in TA & 10 common problems: tandfonline.com/doi/abs/10.108… 2/ Unsure if TA is the right method for your project? And when & why you'd use TA & not IPA, or qualitative content analysis or grounded theory or discourse analysis... then this paper is for you (free to read online right now): onlinelibrary.wiley.com/doi/epdf/10.10…

1/ A thread on why I think collecting demographic data is important in qualitative research (& research more broadly) & a request for your thoughts on this. Am I alone in thinking this is important? I seem to be... based on experiences of ethics scrutiny this yr #AcademicChatter 2/ I get the sense that some researchers - esp those researching students - implicitly imagine their potential participants as the "usual suspects" (white, straight, nondisabled, middle class etc)... I've scrutinised several studies where disability (cog fog etc) would confound

1/ A thread with some tips on writing qualitative research dissertations - esp those using thematic analysis - including common problems to avoid (prompted by marking student projects). First tip - as @ginnybraun & I always say check local requirements! Broadly speaking, there 2/ are two styles of qual research reporting: 1) "add qual and stir" - default quant conventions slightly tweaked for qual: finding & filling the "gap" introduction & rationale, methodological critique of existing studies, separate "results" & discussion... 2) qual centric. The

1/ To all those advocating saturation as *the* criterion for determining qual "sample" size (instead of Gender & Society's positivist qual 35 int minimum) please note that saturation has been critiqued for bloody decades as realist/positivist & not working for all qual. Here's 2/ Ian Dey in 1999 - yep over 20 years ago! - describing saturation as an "unfortunate metaphor": books.emeraldinsight.com/page/detail/gr…

1/ A thread providing an overview of my & @ginnybraun's latest paper on #thematicanalysis - Conceptual & Design Thinking for Thematic Analysis in the APA journal Qualitative Psychology - I will link to an open access version at the end of the thread: psycnet.apa.org/record/2021-45… 2/ Why this paper? Because TA is closer to a method (trans theoretical technique) rather than a methodology (theoretically informed & delimited framework for research) researchers need to engage in careful conceptual & design thinking to produce coherent research.