In August, the 160 Characters Project workshop was held in London. The project is an innovative model for analysing text message support data using a ‘six voices’ framework; combining insights from medical science, literature, socio-cultural, implementation, technology and participatory. Experts from the ‘six voices’ framework analysed the text messages shared between the participants. The workshop created intense debate on what is good communication and how does each discipline measure successful interaction in the lives of people living with HIV. In the workshop, it became clear the echoes between disciplines; voices re-shaped and reiterated ideas expressed by other disciplines, yet each new formulation brought rich divergences in understanding the data, its limitations, and the future for better implementation of the technology.

Following the success of this dialogue, we have collected a series of blog posts from each of the six voices. This will provide an insight into the findings of the workshop, as well as foregrounding the potential of each discipline for thinking through the key questions of what is good communication, how can technology be used to create supportive communication and can this be leveraged to help improve the lives of people living with HIV.

For the fourth instalment, Product Consultant, Ursule Kajokaite, gives us her view on the Khuluma text message data.

By Ursule Kajokaite:

It was a pleasure to bring in a voice of product design and technology to this workshop. I currently spend most of my days working with great organisations and individuals to build solutions that accelerate social impact, together with our amazing team at Super Being Labs. It involves a lot of research, co-creation and testing with people we are designing for.

The role I see design-thinking take in this project is helping to ensure that the ideas remain focused on the Khuluma participants and we don’t build in complexity. Because simple, intuitive solutions are always better than something unnecessarily complex.

Overall, I found the workshop fascinating. Having different perspectives in the room helped us reflect on and appreciate the complexity of human interactions. What stood out for me in particular was the importance of going beyond semantics when analysing the Khuluma text message data. As we communicate, each word carries an emotional load and meaning that is largely dependent on our individual circumstances. To reveal and understand this individual meaning that words have to someone, we have to go beyond what appears to happen on the group chat screen. For example, while a definition of ‘hi’ is a simple greeting, for the Khuluma participants that might feel isolated, sending and receiving such a message might carry emotional significance. Or, someone might appear to be disengaged from the group with regards to the number of messages sent, but actually they might be actively reading the messages and listening in. This poses a challenge for bringing in technology in such data analysis - how can we get a machine to pick on these subtle nuances of human interactions, if at all?

For me, other interesting insights came from understanding how interactions that took place in the Khuluma groups were different from interactions in real life. If we understand how these interactions are different, we can then see how these gaps should - if at all - be bridged. It can then lead us to ask, ‘how can we design a digital platform that would facilitate effective interactions?’

In essence, we can break down a real-life interaction between two people into three parts:

1. Person A speaking
2. Person B speaking
3. A sense in-between

This is where it gets interesting. While not an explicit and obvious part to the conversation, the latter is the most important part of an interaction. In real life, you don’t always need a person to respond, as you already have the value of being listened to. Non-verbal cues play an important role in this – gesture, facial expression, movement of eyes, physical touch - as well as the listener’s sheer physical presence. And so, we could say that the primary value of a conversation is a feeling of being listened to. Secondary values could be actions that follow from that interaction, e.g. starting to do something differently based on what you discussed.

This ‘space in-between’ is very different in an online setting. The cues we normally use are not there. In most messaging communication channels, we see whether someone is online, whether they have read our message, but there is no other way of providing an adequate response other than sending a message back. This can change the nature of an interaction quite drastically. It also poses another challenge - how do we measure this space in between, whether it is in online or offline conversations?

And so, when I looked at the text message data to see how participants engaged differently to real life conversations, the patterns I saw led me to two key insights:

• As discussed above, only a verbal acknowledgement from another person could create an impression that the group listened and cared. This led me to ponder, how do we create something that makes users feel listened to, independent from verbal responses from other participants?

• The conversations were like Pick & Mix, where the participants actively chose when and which conversations to participate in. This selective nature of engagement made the conversations act like double-edged swords - as everyone has the freedom to participate only when they want, there is no guarantee there will be someone out there when you need them. Having said that, it was interesting to observe that there was some sort of a social contract in place - messages that involved emotions or disclosure encouraged the greatest response and engagement, while more simple messages and everyday questions went unanswered more often. These observations led me to play a number of questions in my head, including ‘how do we create an environment where participants would always support each other?’ and ’how do we create a setting where all participants can engage in ways that suit them?’

There is not a single tech tool that would allow us to answer these questions and make adjustments to how the conversations take place in the online groups. More research and thinking is needed, so that we can decide where we go next. There is so much potential for this project – the potential to reach more adolescents; the potential to adapt the support model for other populations; the potential to have greater engagement from the current participants. A good place to start might be choosing a single, high-level problem that we want to solve. For example, if we decide that the intervention is effective and we now want to scale it, then we would look at how we can scale the technology. Or, if we think that the problem is that participants do not engage enough, we would look at how we could build something that engages the participants more.

It can feel overwhelming, with the amount of data and insights we have. In the ideal world, we would have enough time and financing to look at a number of different problems and opportunities we identify. But if we start by focusing on one direction, it will give us a strong base. We have to start somewhere, and it is exciting to think where the project will take us.

Text: Ursule Kajokaite

Illustration: Maggie Li; maggie.li

Published on: 26-10-2018