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Moodbot

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Chatbot therapist using biofeedback.

How can people suffering from internalized mental health stigma be empowered to find the help they need?

 

Moodbot is a chatbot that uses biofeedback in order to help people suffering from internalized mental health stigma learn how to feel better about themselves and to feel comfortable seeking the help they need.

 
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Role: User Experience Design, User Interface Design, Programming, Physical Computing
Tools Used: Sketch, XCode, Arduino, Node.js, DialogFlow
Final Prototype: iOS app connected to an Arduino and a heartrate sensor

 

Project Context

Mental health stigma is prevalent in society. Our culture is steeped with negative connotations towards mental illnesses, creating inherent biases that are subconsciously perpetuated by the general public. In order to avoid labels, people who would otherwise benefit from mental health services choose not to partake in them.

Nearly one in five American adults will experience a mental health disorder in a given year. Yet only 25 percent of people with a psychological condition feel that others are understanding or compassionate about their illness.

This project aims to empower and encourage people who suffer from internalized stigma (self-stigma) in order to help them feel better about their mental illnesses and seek the support they need.

Research

When I delved into the research for this project, I buried myself in research papers pertaining to mental health stigma. I was surprised and saddened by the information I found -- for example, people with mental illnesses are frequently unable to find safe housing or obtain jobs because of the prejudice of employers and landlords. These harmful ways cause people with mental illnesses to conceal and avoid their stigmas by “staying in the closet”, thus impeding on proper care.

As it turns out, self-stigma diminishes a person’s self-esteem, self-efficacy, and confidence to achieve life goals. “...people who internalize the stigma of mental illness worsen the course of their illness because of the harm of the internalized experience” writes Corrigan and Rao. As they internalize the prejudice reinforced by society (“I am incompetent” or “I am dangerous”), their view on themselves and their lives worsens, all in conjunction with avoiding the help they need.

Solutions to stigma

So what can we do about these internalized perceptions of mental health stigma?

In my research, I found that personal empowerment is a way to improve self-stigma in persons with mental illnesses. Personal empowerment encourages people to live out their life goals, and can be achieved by disclosure or group identification.

In addition, cognitive behavioural therapies (CBTs) help people challenge their self-deprecating thoughts and behaviours by asking people to recast their negative thoughts in a more objective light. Irrational self statements like “I must be a stupid person because I get depressed” are challenged with assertions like “Most other people do not think depressed people are stupid”. These challenges lead to counters that people can use each time they find themselves thinking self-stigmatizing thoughts.

 

 Early notes on design question, criteria, and users.

Early notes on design question, criteria, and users.

 
 Precedents I looked at while working on the project; I tried to cover all of my domains: mental health, stigma, empowerment, therapies.

Precedents I looked at while working on the project; I tried to cover all of my domains: mental health, stigma, empowerment, therapies.

 

Ideation

The form of the project changed multiple times while I was working on it. In my final design, I chose the form of a chatbot. A chatbot provides privacy and safety for people who don't want to reveal their illnesses to the public by attending public support groups or visiting the therapist. A chatbot is also able to respond immediately to someone who is in need of emotional relief.

The chatbot will encourage and nurture them using CBT aimed to lessen stigma, and direct them on a path of empowerment and seeking help publicly. It will intervene by detecting when the user feels most anxious or stressed using biofeedback. The goal is to help the user employ cognitive behavioural skills in those moments when challenging negative thoughts about oneself is essential.

 

 This project aims to intervene at the problem point of where a person is unable to seek treatment because of their self-stigma. In order to help alleviate the internalized stigma, the app will work on the user's negative and self-diminishing thoughts using biofeedback and cognitive behavioural therapy.

This project aims to intervene at the problem point of where a person is unable to seek treatment because of their self-stigma. In order to help alleviate the internalized stigma, the app will work on the user's negative and self-diminishing thoughts using biofeedback and cognitive behavioural therapy.

 
 Storyboard sketch on user flow.

Storyboard sketch on user flow.

 
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Sketching

Drawing out simple wireframes of the app and what some of Moodbot's responses are, as well as including an Insights section. Insights are useful in providing observations detected by algorithms that would otherwise not have been noticed by the human eye.

Wireframes

After sketching, I moved into Sketch to mockup some low fidelity wireframes.

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High-fidelity Mockup

 A mockup of the main chat window and MoodBot's insights screen, where the chatbot identifies thought patterns and user tendencies over time.

A mockup of the main chat window and MoodBot's insights screen, where the chatbot identifies thought patterns and user tendencies over time.

 

Implementation Prototype

A sensor that detects anxiety or stress uses heart rate, breath, and skin conductance data. For the scope of this project, a heart rate sensor connected to an Arduino was used to show a proof of concept. The chatbot app was coded in XCode. It was my first time learning Swift, so it was a rewarding experience getting it to communicate with the Dialog Flow API, as well as figuring out how the sensor would interface with the app. It 'twas many long nights of coding.

 

 Architecture diagram of the project and how it works currently.

Architecture diagram of the project and how it works currently.

 

Dialog

MoodBot’s personality is encouraging, comforting, and nurturing. As it talks to the user, all of its responses aim to be informative and directed towards reducing personal stigma. While Facebook’s Woebot helps users process thoughts in a general way, MoodBot has a more targeted focus: alleviating internalized stigma.

 

 Screens of MoodBot's current working dialog.

Screens of MoodBot's current working dialog.

 

Machine Learning

Incorporating machine learning into MoodBot is an important step. Having the bot learn a user’s tendencies and detect invisible patterns over time can provide a truly customized and personal experience.

 

Scope and limitations

This project does not aim to replace therapists. It helps a person struggling with internalized stigma feel more empowered and better about their illness, in hopes to encourage them to seek help publicly. Due to the time constraints of the project, I wasn't able to do experience testing, but I would definitely aim to do this as a next step!

Conclusions

The intent of this project is to create a solution that helps people suffering from mental health stigmatization. Mental illnesses are one of the leading diseases in the world, yet so many avoid receiving treatment. Stigmatization is one reason, and it should be worked on and corrected in society. My hope is to be able to help and encourage people with mental illnesses to achieve their life goals, and urge them to get the care they need. To do this, cognitive behavioural therapy was a core aspect of treating internalized stigma in the project. Although this project is still in its infancy, it is an important stepping stone to tackling the larger issue of mental health stigma.