• Sam Daviau

The Art of Labeling Your Feelings

Updated: Jul 19

Feelings are hard. They are hard to control. They are hard to understand. They are hard to label.


After conducting 100’s of user interviews asking people about mental health challenges and the behaviours that cause them, we’ve learned that just about everyone has trouble translating their feelings into words. Most people, when asked to describe their mental health, describe a unique life situation that caused them duress. When pushed to label that situation with a feeling, 95% of people that we met characterized their feelings as either “anxious” or “stressed”.


One of our core beliefs at UpBeing is that there is a fundamental relationship between your behaviours and feelings and that understanding that relationship is the key to being able to improve your wellbeing. Because of this relationship, we believe that gaining control over your behaviour can help you to gain control over your wellbeing, a concept that is grounded in both centuries of mindfulness practices and


The key to modifying behaviours in order to improve wellbeing is to understand what behaviours cause what feelings. In order to do this, we first have to be able to articulate how we are feeling.

As such, the question of “how do people reflect on how they are feeling?” has been critical for us while developing the UpBeing application.


The dichotomy between accurately and efficiently labeling your feelings


Our second core belief pertains to the emotional intelligence of software. Imagine for a moment a world where people had no ability to understand or respond to the emotional needs of others. It would be cold, isolating, and incredibly difficult to navigate. While this may seem completely alien, it essentially describes the current state of modern technology. As AI systems and software continue to gain increasing ubiquity, their lack of emotional intelligence will cause the world to feel increasingly inhuman.


UpBeing is going to be among the first in a new class of Emotionally Intelligent software. In order to do this, it will need to understand how its users are feeling, which initially, will require user check-ins. The check-ins need to strike a balance between two things:

  1. They need to be be sufficiently robust so as to allow users to accurately label their feelings.

  2. They need to be as streamlined as possible so that users don’t get irritated or distracted when completing them.

These two objectives can be at odds with one another. For example, a 50-point questionnaire may be more accurate, but it carries a significant overhead.


In order to design an optimal check-in solution, we will need to be in constant dialog with our users. We will need rapid implementation of feedback, honest evaluation of our designs, and constant iteration. However, as a starting point, there are a variety of existing frameworks that can be leveraged.


Frameworks on how to label your feelings


Through a combination of research and discussions with experts, we identified a variety of frameworks that we could base a check-in solution on. These included a Likert scale, an emoticon response, a mood wheel and a Valence Chart. I’ll briefly describe what each are:


  • Likert scale survey question: A 5 or 7-point scale, sometimes referred to as a satisfaction scale, that ranges from one extreme attitude to another. Typically, the Likert survey question includes a moderate or neutral option in its scale.


  • Emoticon: This is like a likert scale but instead of points on a scale, you have emoticons that visualize a feeling. It adds a visual element that users can identify with beyond a number.

  • Mood Wheel: A visual representation of primary emotions, displaying the varying degrees and complexities of different feelings. As a tool, it can help people grapple with, put a name to, and come to terms with their emotions in many different contexts, including simply developing greater self-awareness.

  • Valence-Arousal Scale or Chart: Valence is positive or negative affectivity, whereas arousal measures how calming or exciting the information is. The Valence-Arousal Scale (in short the Valence chart) is a framework for dealing with emotional experience characterized in a two-dimensional chart. Valence ranges from highly negative to highly positive, and arousal ranges from calming/soothing to exciting/agitating.

After consultation, we decided to test the Valence chart approach in our pilot. We simplified the language of the scale, but otherwise felt this approach was a good first step because it allowed us to get a quantitative ranking of feelings (on both an energy and attitude scale) and it was quick and easy (with a single question for users to complete).


Labeling your feelings as a way to build EI skills


What we learned surprised us. We expected users to input their feelings because they understood that by doing so, they would get insights. We thought of it as an administrative activity the user had to perform and so we built the check-in feature to be quantitative but quick. We expected feedback on the experience related to how long the check-in took and whether users felt it accurately reflected their current feelings. While we got valuable feedback like this, overwhelmingly the feedback from users was that the experience of checking-in had value in itself. We heard feedback from multiple users saying something along the lines of: “I don’t take the time to actually think about my feelings, this forced me to do that in a way that made me more conscious of my current feelings, which made me feel like I understood myself, which made me feel better.”


With this feedback in mind, we took another look at research we did a few weeks ago, specifically on Mark Brackett’s mood meter and his RULER approach that was originally designed as an evidence-based approach to social and emotional learning (SEL) in schools. We realized that through the check-in system we could do so much more than just record data, we could actually help people build their emotional intelligence skills interactively. This spoke to the reason Mark created the mood meter in the first place. RULER is an acronym for the five skills of emotional intelligence: 1. Recognizing emotions in oneself and others, 2. Understanding the causes and consequences of emotions, 3. Labeling emotions with a nuanced vocabulary, 4. Expressing emotions in accordance with cultural norms and social context, 5. Regulating emotions with helpful strategies. In just a minute or two a day the Check-In feature, modelled after the mood meter, combined with other UpBeing features can help build all these skills:

RULER Framework


UpBeing Feature


Recognize


Check-in: The act of reflecting

Understand

Insights: Relating behaviours and their influence on feelings

Label

Check-in: The act of putting words to a plot on the Valence chart

Express

Support Network: Sharing and discussing your feelings with your closest network

Regulate

Primer Activities and Behavioural Interventions: to influence mood in the moment and change behaviours in the long term

Viewing the Check-In feature and the application within the RULER framework really helps to articulate one of our value propositions to users - i.e to teach users to be more emotionally intelligent.


Clarity on how we label feelings


In summary, with a clear value proposition and ensuing framework, the challenge for us became the following: how do we build an accurate and quick-to-use Check-In feature that helps users build their emotional intelligence skills? Before we had internalized this, the mood meter was a cool valence chart comparable, we are now looking at it beyond the check-in purpose and as a tool to actually build emotional intelligence in itself. In fact, the RULER approach and the value proposition of building tactical emotional intelligence skills, is a really interesting way to assess and think about all features within UpBeing.


We encourage everyone to think about the RULER approach and, whether you use UpBeing or not, how you can proactively build your emotional intelligence skills through that framework. It’s tried and true and used in classrooms across North America.


The Check-In feature is something that we feel has become much clearer through a combination of research, conversations with experts, and user feedback from our pilot. We hope to find the same level of clarity on other features we are developing and testing over the coming weeks and months.


Look out for more updates like this, summarizing our key learnings in the pursuit of crystallizing the UpBeing application. If this was interesting to you and you want to be part of the UpBeing journey, we encourage you to join the waitlist. It's the best way to help shape the future of UpBeing!


With gratitude,


Sam & Sean



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