#TBI: How do Traumatic Brain Injury communities communicate and network in Twitter?

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mbrunner_assbi-2017-hashtag-tbi_poster-v3.png
Poster presentation at ASSBI, 1-3 June 2017.

Twitter is used by millions of people worldwide as a micro-blogging social networking site. We don’t have much information on how people with traumatic brain injury (TBI) use Twitter or who they connect with. This study looked at TBI-related tweets to get an understanding of how Twitter is being used to share information about TBI.

Tweets that were tagged with TBI-related terms (#hashtags) were captured in Twitter every day for one month (March 2016) and then analysed using multiple methods.

tweets captured

In March 2016, thousands of TBI-related tweets were used to discuss and share information around: (i) health issues; (ii) awareness; (iii) life experiences after TBI; (iv) recovery and rehabilitation; (v) popular issues surrounding sport and TBI; and (vi) inspiration.

Key Findings:

  • Twitter is used for a variety of purposes and by a large number of Twitter users to talk about TBI
  • Several people who were tweeting shared that they had a TBI
  • Twitter is an important yet under‐utilised form of communication technology in TBI rehabilitation
  • Using Twitter could help people with TBI to find information about TBI
  • Using Twitter could help people with TBI connect with other people with TBI online.

Topic categories of what was said in the tweets

categories

Listening to the personal stories and inspirational tweets by people with TBI could be useful in understanding their experiences and views of living with TBI. This could help to (a) guide conversations to develop person‐centred rehabilitation goals; or (b) stimulate further discussions on ‘living well with TBI’.

Reading tweets tagged with #TBI‐related hashtags could give clinicians and researchers insight into the lived experiences of people with a TBI, as well as the opportunity to engage with a wide TBI community in research and knowledge translation.

Further research is needed to determine the experiences and views of people with TBI using Twitter, to identify and supports that need to be provided for people with TBI to engage in Twitter communities.

Read the full article (Brunner M, Hemsley B, Dann S, Togher L, Palmer S (2018). Hashtag #TBI: A content and network data analysis of tweets about Traumatic Brain Injury. Brain Injury, 32(1), 49-63).

abstract

This research was presented at international and national conferences in 2017:

  • Brunner M, Hemsley B, Togher L, Dann S, Palmer S (2017). #Hashtag TBI: Communication and networking in Twitter by Traumatic Brain Injury communities. Datablitz oral and poster presentation at the Australasian Society for the Study of Brain Impairment (ASSBI) Conference, 1-3 June 2017, Melbourne, Australia.
  • Brunner M, Hemsley B, Togher L, Dann S, Palmer S (2017). A Hashtag Study: How do Traumatic Brain Injury communities communicate and network in Twitter? Oral Presentation at the Speech Pathology Australia National Conference, 28-31 May 2017, Sydney, Australia.
  • Brunner M, Hemsley B, Togher L, Dann S, Palmer S (2017). Hashtag TBI: How do Traumatic Brain Injury communities communicate and network in Twitter? Oral presentation at the International Cognitive-Communication Disorders Conference, 19-21 January 2017, Orange California, USA. SlideShare
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Using technology in rehabilitation with people after traumatic brain injury (TBI) for cognitive-communication skills

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MBrunner_ASSBI 2017 TBI & Tech_poster v3Brunner M, Hemsley B, Palmer S, Togher L (2017). Using Technology in Rehabilitation after TBI for Cognitive-Communication Skills. Datablitz oral and poster presentation at the Australasian Society for the Study of Brain Impairment (ASSBI) Conference #ASSBI2017, 1-3 June 2017, Melbourne VIC, Australia.

Read the full article (Brunner M, Hemsley B, Togher L, & Palmer S (2017). Technology and its role in rehabilitation for people with cognitive-communication disabilities following a Traumatic Brain Injury (TBI). Brain Injury. Published online: 04 May 2017). A copy of the accepted manuscript is available on the University of Newcastle’s repository here.

Here are some of my tweets about the implications for rehabilitation (I tweet as @LissBEE_CPSP however I was also a guest curator for the @WeSpeechies handle in May 2017):

CaptureCapture 2Capture 3Capture 4Capture 5Capture 6Capture 7Capture 8Capture 9Capture 10Capture 11Capture 12Capture 13Capture 14Capture 15

appstrainingtraining 2learningsupportsupport 2social mediasocial media 2social media 3social media 4social media 5LingoLingo 2summary 1summary 2summary 3summary 4summary 5summary 6summary 7summary 8summary 9

Technology in rehabilitation after TBI poster in PDF format

#TwitterMind: Study 1 & 2 – recruiting now!

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Twitter Mind picture

TwitterMind Study 1 and Study 2: Twitter use by people with communication disabilities after traumatic brain injury (TBI) 

Investigators: Ms Melissa Brunner (PhD Student, The University of Newcastle)
A/Prof Bronwyn Hemsley (Primary Supervisor, The University of Newcastle)
Prof Leanne Togher (The University of Sydney)
A/Prof Stuart Palmer (Deakin University)
Dr Stephen Dann (Australian National University)

We are interested in finding out:
a) How people with TBI currently use social networking sites including Twitter
b) The nature and extent of any problems experienced in learning to use Twitter
c) If training in Twitter can help people with communication disabilities to access and use Twitter to exchange information.

We are interested in finding people who are willing to take part in research about the use of social media:

We are inviting teenagers or adults (aged 16 years and over), along with their family members/ partners/carers, who experience communication difficulties as a result of a traumatic brain injury (TBI) and who are able to give their own consent to take part.

We will initially be running two (2) studies:
– Study 1 is an interview where we ask people to talk to us about their use of Twitter as well as to share their Twitter use for analysis.
– Study 2 is a survey where we ask people to talk to us about their use of social media.

Please note: Participants in Study 1 can also take part in Study 2.

The information gained from these studies will inform future research plans to develop social media training (starting with Twitter) for people with a TBI (which will be conducted subject to receiving ethical approval).

We are recruiting people to take part in Study 1 & Study 2 now.

Further details regarding Study 1 can be found on the TwitterMind Study 1 Participant Information Sheet (version 3, 9-9-16).

Further details regarding Study 2 can be found on the TwitterMind Study 2 Participant Information Sheet (version 3, 9-9-16).

If you are interested in taking part or know someone who might be, please contact Melissa here.

Do I have a ‘Twitter voice’ & what is it like?

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Blog photo Twitter voice April 2015 I always think, if I’m going to ask someone to do something, I’d better try to do it myself first. Clinically, this was the norm for me. If I was going to ask someone to eat puree, drink thickened fluid, draw/write with their non-dominant hand (and the list goes on!), then I should be prepared to do the same. So over the years I’ve ‘enjoyed’ plenty of puree meals, drunk a significant amount of thickened fluids to ‘assuage’ my thirst, and ‘refined’ my skill in drawing and writing with my left hand. In doing so, I learnt more about these things and my own personal preferences. It strengthened the concept of how important the role of the person is in decision making and this has helped to further shape my interactions with people when discussing swallowing and communication as well as making decisions when it comes to my own health.

Before asking other people to reflect on their use of Twitter, I therefore really wanted to look at my own Twitter use and think about my experiences of using Twitter (TwitterMind Study 1 will analyse publicly available Tweets of consenting participants and ask them to reflect on their use of Twitter). Over a period of 3 months, I captured two snapshot datasets of all of my Tweets (all Tweets, Retweets, Replies, and Mentions for @LissBEE_CPSP, captured on the 18/02/2015 and 02/04/2015). Using NCapture, NVivo, Excel, and Gephi software, I was able to look at how much I was Tweeting, at which level I was Tweeting at, what types of Tweets I was sending out, and who I was communicating with.

To start off with I looked at the basics:

Basic data graph

Certainly the amount of Tweets that I generated differed over the two snapshots with over double the amount of Tweets sent out in the first time period as compared to the second time period sampled.

Next I wondered who I might be reaching and how my Tweets were seen in Twitter…

Bruns and Moe (2013) propose that there are three distinct structural layers to be found within communications over Twitter. In structural layers of communication on Twitter they outline the three types of Tweets that compose these layers of communication: the Micro, Meso, and Macro levels.

Caroline Bowen (@speech_woman) has also recently written about strategic tweeting and provides some great examples of Tweets found at the Micro, Meso, and Macro levels.

In essence, I think of it like this:

Structural layers Twitter drawing_4

The Micro level’s reach is small – similar to a face-to-face conversation between yourself and a friend that no one is likely to overhear (i.e., communication with one specific Twitter user). By having @user at the start of the Tweet, generally it will only capture the attention of that @user.

Tweet Micro

The Meso level has the potential to be overheard by everyone in the room (i.e., your followers network). By having . (or any other character) before @user at the start of the Tweet, generally it will capture the attention of those who follow you.

Tweet Meso

The Macro level uses the Meso level type of Tweet and adds in #hashtags which has the potential to reach a much wider audience, like using a loudspeaker in a public space might do in real life. By having . (or any other character) before @user at the start of the Tweet and adding #hashtags, a Tweet has the potential to reach a much broader audience.

Tweet Macro

Across the two snapshots of Twitter data, my use of the differing macro/meso/micro layers changed…

Structural layers data

I was using more Tweets targeting the Macro layer in the second time period and less frequently connecting at the Micro level.

Then, I wondered… What sort of stuff I was Tweeting about?

Stephen Dann’s work has led to a Twitter content classification system that allows us to determine what type of information our Tweets are sharing with the Twittersphere. His work identified six broad categories (with 23 specific sub-categories within them) that Tweets can be classified as: Conversational; Status; News; Pass Along; Phatic; and Spam.

Dann defines each of these broad categories, and has further refined them since this publication (2015) however for the purposes of this blog post I examined Tweets according to the 2010 definitions, as follows:

Conversational – ‘Uses an @statement to address another user’

Tweet conversational

Status – ‘An answer to “What are you doing now?”‘

Tweet Status

News – ‘Identifiable news content that is not UGC’ (UGC: user-generated content)

Tweet News

Pass Along – ‘Tweets of endorsement of content’

Tweet Pass along

Phatic – ‘Content independent connected presence’

Tweet phatic

Spam – ‘Tweets generated without user consent’

Looking at the data it was clear that over time, the type of Tweets I sent out also changed…

Classification data

While I certainly like to Pass Along information over the two time periods, there was a noticeable shift between Conversational Tweets and News Tweets.

And then it was time to create pretty pictures:

Using visualisation techniques previsouly applied to Twitter data (outlined by Stuart Palmer 2013), the graphics below show all of the Twitter data captured across the two time periods sampled. The lines represent Twitter communication travelling in a clockwise direction (from sending @user to receiving @user). A thin line indicates limited interaction, whereas a thicker line represents more frequent communication between the sending @user and receiving @user.

@LissBEE_CPSP gephi_2

By viewing the Twitter data this way, it can be seen that there was heavy traffic from @LissBEE_CPSP to a specific @user in the first time period sampled. Although this also seems to be a trend in the second time period sampled, there is communication across a wider network (i.e., between @LissBEE_CPSP and more @users) than in the first time period (note the change in the number of nodes/circles between the graphics).

So what does this all mean?!

Well, it would seem that across these two time periods sampled, my ‘Twitter voice’ changed across all of the markers that I’ve discussed. Given that this was purely across two samples and a limited time, these results may not be truly representative of my ‘Twitter voice’ overall.

Subjectively, I feel that I am interacting with different @users in different ways more now than when I first joined Twitter as an individual and I still feel that I’m learning how to be a part of the Twittersphere. There is so much that I like about Twitter – those @users that I follow don’t have to follow me, and I also don’t have to follow every @user who follows me. I still ‘hear’ what is said. The flow of information, ideas, and opinions is easily accessible. More importantly, I don’t necessarily need to see or know people in real life (IRL) in order to have connection, whether it be socially or professionally.

On reflection, my ‘Twitter voice’ somewhat reflects my ‘everyday communication voice IRL’. Some days, I like to talk. Some days, I like to listen. Other days, I like to do both. I guess this may also be true for my interactions on Twitter. Sometimes, I Lurk. Sometimes, I Tweet. Sometimes I do both! (If you want to read more on the pros and cons of Tweeting and Lurking, check out the storify of the recent #WeSpeechies debate “Lurking is Better than Tweeting”). The variability and complexity of how we communicate with one another is a large part of what drew me to speech-language pathology originally. It’s interesting that regardless of mode (real life versus online communication), my interactions are changing, evolving, and transitioning over time.

References:

Bowen, C (2015) Webwords 51: Taking Twitter for a twirl in the diverse world of rotational curation – March 2015. Journal of Clinical Practice in Speech-Language Pathology, 17(1):51-53. 

Bruns, A & Moe, H (2013). Structural layers of communication on Twitter. In Weller, Katrin, Bruns, Axel, Burgess, Jean, Mahrt, Merja, &Puschmann, Cornelius (Eds.) Twitter and Society. Peter Lang, New York, pp. 15-28.

Dann, S. (2010). Twitter content classification. First Monday, 15(12). doi:10.5210/fm.v15i12.2745

Palmer, S. (2013). Characterisation of the use of Twitter by Australian Universities. Journal of Higher Education Policy and Management, 35(4), 333-344. doi: 10.1080/1360080X.2013.812029

2014 – the year of culling, culling, culling…

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So much of my 2014 was filled with culling. Trawling through long lines of titles and abstracts in a very, very large EndNote file. Constantly searching for those citations relevant to traumatic brain injury (TBI) and social media –  it certainly brought back memories from my speechBITE work days!

Culling started with 11,673 citations which eventually dwindled to 16 relevant papers. Of course, along the way my Twitter feed was filled with my comments, progress and interesting finds. There were so many papers that captured my eye, even though they weren’t relevant to both TBI and social media, they were relevant to use of social media in healthcare. Being able to share these little discoveries in real time on Twitter also now means that I also have a clear (and public) record of my finds.

Capturing highlights of the arduous process and summing up my 2014 – here is my year of culling in Tweets:

Culling 1 (2) Culling 2 Culling 3 Culling 5 Culling 6 Culling 7 Culling 8 Culling 9 Culling 10 Culling 11 Culling 12 Culling 13a Culling 13b Culling 13c Culling 13d Culling 13e

 

Who cares about Evidence? How do we find it? And then – what do we do with it?! #WeSpeechies

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Come and join me as the #RoCur on #WeSpeechies again this week #slpeeps and #slp2bs! It’s time to talk EVIDENCE BASED PRACTICE and what it means to you in clinical practice.

#WeSpeechies Chat 19 with Melissa Brunner

Date: Tuesday 8 July 2014
Time: 8:00pm AEST for one hour
Time Zone: Australian Eastern Standard Time (Brisbane, Canberra, Hobart, Melbourne, Sydney) | YOUR TIME ZONE
This week’s curator: Melissa Brunner @LissBEE_CPSP

Topic: Looking for evidence and using EBP

Who cares about Evidence? How do we find it? And then – what do we do with it?!

As speech language pathologists/speech and language therapists we recognise the importance of using research evidence to inform our clinical practice when making decisions with our clients about interventions. Increasingly, we are asked to ‘defend’ what we are doing, and the time that it takes for us to do it, by managers and administrators – as well as clients and families.

The time that we are allocated to spend with clients for different treatments seems to be unrelated sometimes to the evidence saying that treatment should be intensive or more frequent, or of longer duration. Sometimes families ask for ‘more therapy’, despite the evidence showing that it will not necessarily help.

How do we resolve this by ‘finding the evidence’ and using it to improve our practice and make sure it is the best for the client? How do we actually go about finding evidence while busy with our daily roles in actually implementing the evidence?

Over this week on #WeSpeechies, we will talk all things EBP including (but not limited to):

  • Finding research evidence that helps to address the ‘clinical question’ (what kind of treatment is needed, and how much of it will help?
  • Tips and strategies for searching for the best available evidence.
  • How to evaluate the quality of the evidence you’ve found for one treatment against other treatments
  • How we go about using the best evidence available in clinical practice? Are our service models conducive to actually implementing what the research says would be best?
  • Discussing evidence with healthcare consumers – how do we raise the ‘uncertainties’ and ‘limitations’ in research findings – when limited findings can still be promising?
  • Informed decision making and goal setting with consumers – how can clients and families also be involved in critically reviewing the evidence, to make informed decisions?
  • Resources that we’ve found useful in reviewing evidence
  • How technology can help us out – including use of social media (of course!).

Questions

Welcome

Q1 Do you love or loathe searching for evidence? Tell us why! #WeSpeechies

Q2 What are the barriers and facilitators in finding treatment evidence & using it in clinical practice? #WeSpeechies

Q3 Are there any hot tips or resources that you find invaluable when finding evidence or putting it into clinical practice? #WeSpeechies

Q4 How can we assist & engage consumers to make informed decisions about their healthcare? #WeSpeechies

Chat Concludes

Chat Transcript

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