The BPS Community Psychology Festival: not your everyday academic event

This is a brief review of the 3rd BPS Community Psychology Festival held in Bristol from 15th – 16th September 2017. A longer review of the event will appear in the next QMiP bulletin

From the minute I arrived at Bristol’s Arnolfini and donned my entrance wristband, the Community Psychology Festival felt friendly and relaxed. As I took my seat for the welcome talk I was approached by a woman equipped with glitter and glue, who introduced herself as Sally and asked if I would like my face painted – not your everyday academic event experience. This lovely lady turned out to be Sally Zlotowitz, Chair of the BPS Community Psychology section.

Getting into the festival spirit!

The conference opened with welcomes from Sally Zlotowitz and organiser Miltos Hadjiosif as well as a talk from Asher Craig, Bristol’s Deputy Mayor on Bristol’s whole city approach to mental health and wellbeing. The fun, festival feel did not in anyway detract from the varied social issues that had brought everyone to the event.

Pressing global and local social issues were at the fore of every talk and workshop which only made the methodological and theoretical elements more engaging as I found myself asking “how did you help to tackle that problem?” rather than “what did you do with that method or apply that theory?”. Compared to many other psychology events, the talks here were longer, more interactive and most definitely more critical. The fact that the afternoon sessions on the final day were over-subscribed was a testament to how engaging the event was as whole.

My personal highlights were talks by: Carl Walker, questioning ‘Are we critical enough?’ as community psychologists; Lucy Johnstone on alternative ways of understanding mental health ‘disorders’ and also the moving performance by the Housing, Austerity and Mental Health network.

The multiple streams of talks and workshops made it impossible to attend everything of interest though the closing activity facilitated by the UWE Music Therapy Team brought everybody back together into the same space.

An energetic end to the Festival and a chance to reflect.

Fueled by liquid nitrogen based ice cream (thanks to Bristol based twins ‘Brozen‘) we were led into some energetic singing, stomping, clapping and instrument playing. I’ve never spent so much time on my feet at a psychology event and certainly never played a maraca at one before! When asked to contribute lyrics to sum up the event, delegates suggested ‘Weltschmerz’ (the topic of Amelia Ince’s earlier talk, a German word which roughly translates to ‘feeling the world’s pain’) ‘inter-dependent not independent’ and ‘solidarity’. A good choice of words to capture what I too felt the Festival highlighted.

Thanks to all involved for making the festival so welcoming and for facilitating a space to discuss issues that matter (and ways to address those) with a shared enthusiasm and passion!

Six time management tips and tricks

Time management skills are a byproduct of being an academic. Juggling research, teaching, admin and other and having done a PhD over four to five years lead you to acquire ways of managing your time more efficiently. If you’re a PhD student, assuming you’re not lab-based or doing extensive group work, you’ll spend a lot of time on your own with few set structured tasks to do. Even those who meet very regularly with supervisors and devise lengthy plans will spend time thinking about how to break bigger tasks down into daily or hourly tasks.

In the early weeks and months (maybe longer) of my PhD research, I was hopeless at time management. At around the mid-point in my PhD I realised that every job I had completed so far had taken roughly three times longer than I’d anticipated. Whether it be sending emails to local community organisations, writing reports, collecting data – it all took three times longer than planned. In the later years of my PhD when time was really squeezed due to the looming final deadline, job applications, day job, casual work and inevitable ‘life stuff’, good time management became crucial. I upped my game. Mostly this meant hour by hour planning, daily for several months with way too much ‘overtime’. I’m not recommending that but I am recommending trialing some of the following techniques, all of which got me through different points of my PhD and most of which I continue to use now.

1) Work backwards from a deadline


This is actually a technique I picked up long before the PhD when I was a door-to-door sales rep. I’ve used it ever since. Here’s how it works. If you have a deadline (either fixed or a personal deadline) for a particular task (finishing a paper, chapter, completing a report) then think about the thing that needs to be done immediately before that deadline in order for you to reach it. For example, if you want to finish a thesis or book chapter by 1st December then the thing needed to be done immediately before might be to proof-read the chapter. Taking into account all other commitments, think about how much time you will need for this task. I could say that I want to allow 3 days for proof-reading and editing of the chapter.  My ‘deadline’ for that task would therefore be 27th November. You then repeat this, thinking about the thing that needs to be done immediately before that (e.g. organise reference list, check structure of chapter, update literature search) and set a deadline for this task …and the next one …and the next one.

I’ve found that this strategy does help you to spot unrealistic personal deadlines. If you find that you’re working backwards from a particular date and get to the present day with several tasks still to complete, you’ve not allowed enough time.

2) Colour coded calendars

google calendar

As simple as it sounds. Colour code blocks of time in your calendar to correspond to different tasks and always block out time for things. I regularly block out an hour or two for “admin” if I have a lot of emails and small tasks to catch up on.


mytomatoes is a very simple no-frills online time management page based on the pomodoro technique. For those tasks which require time, focus and motivation (I can think of few that don’t!) I cannot recommend this simple technique enough.

The basic principle is that you engage in 25 minutes of focused work (no distractions) followed by a 5 minute break. also allows you to write a few words about what you achieved after each 25 minute work period a.k.a. tomato.

One thing these brief notes taught me early in my PhD were just how much time I spent on things that I figured would take much less time (mostly emails and form filling). Not only did this technique motivate me to work through the use of a HUGE timer counting down to a break on the screen front of me, it taught me to be more efficient in certain tasks.

Yes, it’s very primitive and no, we shouldn’t need timers to tell us when to work and when to take breaks but unfortunately many of us do, including me suffer from getting distracted too easily (also see below!)

4) Shut up and write

lesson 1b

I have the Thesis Whisperer to thank for this one! During my PhD I shared an office with 4 to 7 others at varying points. We all got on incredibly well and this was often problematic for  our work. Shut and write sessions were a fantastic way to get together, be productive and then celebrate over a bit of lunch.

To test the water I created an anonymous survey to scope out interest in ‘shut up and write’ sessions as well as mutually ideal days and times. A similar principle to the pomodoro technique but with others!

5) Start your day early

early bird

I’m not embarrassed to admit that when I’m working from home I’ll often start work in my PJs and slippers after a quick breakfast. There is something very satisfying about getting half of a to do list ticked off by mid-morning.

6) Blocking out distractions

Lesson 2

I’m definitely not one of those people who feels compelled to reply to texts, tweets or Facebook messages straight away and my closest friends know this! Many days I’ll put my phone on silent or switch it off and then reply with a “sorry I was working…”. If I’m working on research, I won’t have email notifications on so that I can only check them when I have time. Switching off from social media and personal messages (patience of friends and family permitting) definitely grants a new level of focus.


NVivo, Word or good old-fashioned pen & paper: pros and cons of three qualitative data analysis tools

This post is similar to the previous one in that it is my attempt to pass on nuggets of wisdom gained through trial and error. The last post was very broad whereas this one will only be of interest to those qualitative researchers weighing up which tool to use in their analysis. The idea for this post came to me following a conversation with a research assistant. Over the summer I’ve been fortunate enough to have an internally funded RA working for 8 weeks full time on the OPEN project. Like many qualitative researchers (including myself post-PhD study 2), my RA was transcription weary after many days spent in headphones in front of ExpressScribe ready to get stuck into the nitty gritty of data analysis. “Which method should I use?” and “Can I use NVivo?” were two questions of hers and also mine a few years earlier. The discussion we had around my thoughts on the pros and cons of different data analysis tools was very much informed by my experience, having trialled all three of the methods mentioned in the title of this post. Here are some pros and cons of each, based on my experiences.


Pro: NVivo is an amazing program and you can do (what feels like) millions of different things with your data!

nvivo 10

I’m by no means an NVivo expert. I’ve used the programme on three different projects to date, two of my own and one I was employed on as a research associate. The range of functions available on NVivo is massive. I’ve likely only used 10% of the program’s functionality. NVivo is not restricted to textual data, you can analyse images, videos, web sources and (probably) much more. In terms of the nitty gritty of data analysis, NVivo is great because your codes are clearly labelled, code labels can be edited, codes can be moved around, deleted or merged into others, whilst at the same time NVivo recorded the date, time and author of any new codes so that you can re-trace steps. Within seconds you can produce ‘reports’ of data relating to particular codes or themes, frequency counts, word clouds or coverage statistics.

For me to provide a review of everything possible on NVivo would probably mean an entire new blog in itself. The point I’m trying to make here, I guess, is that NVivo is a flexible and sophisticated tool for handling and analysing qualitative data.

Pro: NVivo is fantastic for collaborative work


Collaboration is easy with NVivo for a number of reasons. Because NVivo records the author, time and data of any changes to codes and coding, collaborators can easily trace their steps (and others). Because data sources are neatly stored together in project folders, collaboration can be a simple as ensuring that the NVivo file being worked on is the most recent one.

Con: NVivo is inaccurately heralded as the best way to analyse qualitative data

NVivo meme

With its many functions and means of presenting data and coding, NVivo is often heralded as the best tool for conducting qualitative data analysis. Often this is seen more implicitly in methods sections of papers with only one or two sentences about data analysis which include “All data was analysed using NVivo 10” with little other detail. Of course this may be due to restrictive word limits particularly for qualitative empirical articles. My interpretation is that this is also due to the illusion that NVivo is doing more than it actually is. NVivo is ultimately a data management tool. It provides a means to store, code and report data. It does not analyse data – well not in a qualitative way at least. Stating that NVivo was used to analyse data is no more informative than stating that Sony recording devices were used to record your interviews. So for those of you who haven’t yet dabbled in NVivo – don’t worry, it is one way of analysing data but certainly not the only or the best way.

Con: NVivo makes it too easy to disengage from your data


Those new to qualitative data analysis often mistakenly imagine NVivo is a qualitative equivalent to SPSS. Enter the data. Click. Click. Check box. Select ‘options’. Check another box. Check one more box. “Run”. And in seconds, data is analysed and ready for interpretation. As stated, when it comes to qualitative data, NVivo is predominately a data management tool. The danger with NVivo, particularly for novice researchers, is in it’s ability to disengage the analyst from the meanings within the data. Coloured sections of text are compelling and coding can easily become like a game of Tetris, an attempt to keep clicking until you get to the bottom of a transcript. This tendency can be combated and indeed most researchers do use NVivo to enhance their data management and analysis.

Con: NVivo takes a little time to learn to use

Time for that

Like any unfamiliar program, a first look at NVivo can be overwhelming. Even navigating the basic functions can take some time. Many people, myself included, have attended training courses. There are also tons of useful videos on YouTube and lots of other guidance across the web. Getting your head around the language of NVivo is all part and parcel of your induction. Learning about parent, child and sibling nodes, external and internal sources and reports. All of this takes additional time that you wouldn’t have to invest if you were using a data analysis tool that you were already familiar with.

Microsoft Word

Pro: You don’t have to spend hours learning to use a new program

On the flip side to the above, using Microsoft word to analyse data has the benefit that you don’t have to translate NVivo’s terms. You don’t have to locate functions and spend hours generally learning how to use a program. Word’s review tab allows data analysts to perform many of the functions available on NVivo – coding, coloured highlights, text search, author identification. With just the use of the comments function and text highlight, Word offers an accessible way of analysing data electronically.

Con: Word lacks the sophistication of NVivo

microsoft office paperclip

If you’re going to analyse data electronically then NVivo offers a far greater range of options for storing, coding, locating and presenting data. You may however, not need all of that sophistication and functionality. If you have a small data set, are working solo, have text only data or are conducting a semantic level thematic analysis or something similar, Word may do the trick just fine. You may just find that you need to reassess your comments or colour coding intermittently and would probably want to use a different document, program or pen and paper when it comes to searching for themes in your data.

Good old-fashioned pen and paper

Pro: Pen and paper ‘feels’ more engaged

I hate reading articles from a screen. During my undergraduate degree I started using a Kindle to store and read articles, which helped with printing costs too! Having your data in front of you in hard copy, just feels different. It feels more engaged, more like you yourself are doing the analysis. Reading through the data physically and coding physically with highlighters and hand-written comments, feels satisfying and methodical. You can’t see word counts, node counts or the percentage of data coded but you can see and feel the dog-eared pages of data and your hands dotted with fluorescent ink. And I don’t think I’m just being nostalgic. When analysing data by hand you can flip back to a code you noted a couple of transcripts ago with ease, rather than fumbling over files or waiting for your PC to open a document. The hand written thematic diagrams and lists that accompany your colourful pages of data serve to ice the data cake.

Con: Pen & paper based analysis is not flexible

bad hand writing

The satisfaction that comes with the methodical nature of analysing data by hand can be disrupted when codes need to be merged or re-coded. When themes don’t quite fit or the input from a second researcher sheds doubt on your interpretation, pen and paper is more problematic. Most forms of qualitative data analysis are iterative, they require the researcher to move back and forth between steps in analysis, refining and re-interpreting as they go. All of this can be done electronically with ease but when your pages of data are already crammed with annotations, ink smudges and post-its, your analysis begins to look messy. On top of that, if your handwriting isn’t the best, your colleagues/supervisors patience may wear thin when attempting to give you input.

So, which tool should I use?

I use NVivo now and probably will from now on. This is because I’ve invested time in learning how to use it and I like the range of functions on offer. For me, good old-fashioned pen and paper has just a few too many cons. Word is an excellent best of both worlds for those who can’t or don’t want to navigate a new program in order to analyse their data.


Doing a PhD: Six things I’ve learned

A few months ago I gave a keynote talk at my department’s 4th annual postgraduate psychology conference. This was a real pleasure (and a little surreal) as it was Jenny Taylor and I who set up the first of those annual events four years earlier. 

I was asked to do a talk on ‘my PhD journey’. This was terrifying daunting for two reasons.

Reason 1: Up until then I’d given lots of talk on lots of different aspects of my work but never given a talk about myself. Even where I’d talked of research challenges and even reflexivity, the presentation was always about my work and not about me.

Reason 2: My prospective audience was to include not only current postgraduates but prospective PhD students, current colleagues, mentors and my PhD supervisors; a consequence of returning to work in the department where I did my PhD.

Though apprehensive about talking about myself and doing so in front of my peers, I decided to embrace the challenge. I prefaced my talk with an explanation of how it would be an open, honest account of my experience rather than a sales pitch to attract PhD applicants. I also sourced some anonymous quotes from friends and colleagues about their experiences. The following is taken from the content of my talk titled “Doing a PhD: Six things I’ve learned” in the hope that others might learn from it.

Lesson 1 – Get involved in everything and anything*


I remember being told once by a senior academic that a PhD is more of “an apprenticeship in academia” than anything else. Though my PhD was full-time, I tried to squeeze in as many different academic experiences as possible (partly because I had difficulty saying no to opportunities). These included:

  • Research assistant opportunities
  • Volunteer opportunities
  • Organising and chairing conferences
  • Open days and community days
  • Research networks
  • School initiatives
  • Teaching

*but remember to prioritise your PhD (not always easy!)

Lesson 2 – Engage in your field in different ways

Lesson 2





I separated out lessons one and two for a reason. As important as it is to get involved in activities in your school or the university more widely, it is equally important to get involved in your field. There may only be one or two academics in your department or university that are experts in the same specific thing that you are becoming an expert in. Find others like you. The internet is wonderful for this. Things I did or wish I had done:

  • Attended conferences
  • Published
  • Attended research meetings and events
  • Reviewed articles
  • Joined twitter chats
  • Followed and contributed to blogs
  • Read, read and read some more

Lesson 3 – Talk about your work and your ideas

Lesson 3

Yes, because conference presentations help to build your CV but talking about your work helps in so many ways. Talking about my work helped me to:

  • Make sense of my ideas, especially in the early days
  • Get feedback from others
  • Look at my work from a different perspective
  • Place my work in the context of my discipline
  • Meet other academics

Lesson 4 – Listen to your supervisor*

Lesson 4

Stress does weird and interesting things to us. When stressed, our supervisor’s constructive criticism can feel more cutting and we can take comments too personally or get overly defensive. Remember that your supervisor’s job is to help you grow as an academic and sometimes this means nudging you out of your comfort zone or requesting a fifth re-write of that chapter. Some things I learned:

  • Get feedback on your writing early
  • Expect them to challenge you
  • Communicate and meet regularly
  • Talk through your work and ideas

*but also be proactive and take initiative

Lesson 5 – Look after yourself

Lesson 5







During the course of my PhD I moved house five times, experienced a family bereavement, health issues and other general life stresses. I had to remind myself to:

  • Take breaks
  • Make times for the things I enjoy and the people I care about
  • Speak with other PhD students. They are a great source of support

“Life if what happens when you’re busy doing other things”

Lesson 6 – Enjoy it and celebrate successes – big and small!


Your PhD project is yours and yours alone and that sense of ownership (despite bringing pressure) is an amazing thing! Enjoy it, remind yourself of what you are doing and why and celebrate every little achievement. Things I celebrated included:

  • Finishing a chapter
  • Passing progression
  • Collecting my first piece of data
  • Finishing transcription
  • Getting my progress report
  • A successful meeting with project partners or my supervisor
  • Writing 500 words on a chapter I’d been struggling with
  • Organising my literature
  • Finishing my Appendixes

These were my lessons learned, feel free to share yours in the comments section…

Sun, strawberries, and social representations theory: ISCHP 2017

This week I attended my second International Society of Critical Health Psychology Conference – a good time for a first blog post!

It had been four years since my last ISCHP. Back then I was in the early days of my PhD research and the Bradford conference opened my eyes to a world of passionate critical health psychologists. I was very much looking forward to Loughborough 2017 and it certainly didn’t disappoint. From arriving on a sunny Sunday afternoon to a reception of bangers and mash, and strawberries and cream, to the final (and very inspirational) keynote on the Wednesday by Dave Harper  the whole 3 days were just fantastic. Unlike many other conferences where I feel very much on the margins as a critical social psychologist, I feel at home at ISCHP. My impression of ISCHP is that it is a critical space through and through, embracing scholars from many different theoretical and methodologically orientations and addressing a HUGE range of social and health concerns. There appears to be an understanding across the board that the most popular way of doing things is not necessarily the best or most effective one.

Scanning through the conference programme was not a case of locating where ‘my kind of talks’ were on and when but instead (refreshingly) having to face tricky decisions about what to attend and what to miss out on. Two of this events themes (‘diversity and inclusivity’ and ‘ageing’) summed up much of my research and interests, adding to dilemmas over which talks to attend. I thoroughly enjoyed talks on ageing and issues such as social inclusion, physical activity and sexual health. Many of the diversity and inclusivity talks touched upon the challenges of conducting good quality, ethical co-produced research with ‘disadvantaged’ or marginalised communities – these were most definitely relatable.

Presenting in one of two symposia on the theory of social representations was a personal highlight. For me this was an opportunity to position my work in the context of this fascinating and evolving theoretical framework. Between the two symposia, eight scholars (including colleagues at Keele: Michael Murray and Jenny Taylor) presented research on innovations in theory and methodology. It was inspiring to see SRT used to underpin novel methodologies such as film analysis and also to see people exploring different theoretical combinations to better understand social issues.

I came away from ISCHP 2017 feeling inspired, energised and motivated to crack on with the paper I’m currently working on! On top of that I met many friendly like-minded academics who I hope to cross paths with in the future. Already looking forward to ISCHP 2019!