Google Equitable Design Fellowship

How can we leverage design as a force for good, ensuring products cater to all users?

We designed two meditation apps. During the creation of one app, we incorporated equitable design methods. We then comparison tested the apps to evaluate the effect of equitable design.

Role: Product Design Lead (Team: Nadia, Bri & Isa)

Mentors: Zena (IDEO), Google’s PI&E Team, Vince (Berkeley)

Timeline: 4 months

Methods: A/B testing, co-creation workshop, design thinking, UI/UX design

Tools: Figma, Qualtrics, Google Forms

Summary

The fellowship was structured as two 6-week sprints:

Sprint 1 Traditional Design: App #1

We created ShhShh… a meditation app for all.

Sprint 2 Equitable Design: App #2

We created FreeMind: a meditation app for formerly incarcerated individuals. This phase added co-design workshops and risk analysis.

Analysis Survey: App #1 versus App #2

We concluded that equitable design, though more complex and time-intensive, resulted in a product that was more responsive to specific user needs.

Traditional Design Process vs. Equitable Design Process

Why a meditation app?

Although meditation apps are proven to alleviate mental health challenges, they are used by a narrow demographic of users.

The meditation market is projected to expand 2.5x by 2027— it is essential we understand how to create equitable platforms to welcome more diverse audiences to access the health benefits.

Hypothesis

The equitable design process app will appeal to a broader audience than the traditional design process app.

Phase 1: Traditionally Designed App

Design Research | Discovery interviews

  • Question: How do people perceive ‘Mindfulness’? Do they practice it?

  • Participants: Recruitment survey distributed to Berkeley community

  • Method: Five 1-hour interviews with participants representing each level of meditation experience (Never meditated before —> I meditate daily)

Insights

  • Traditional meditation is perceived to be difficult

  • Routine activities can feel meditative (walk, shower)

  • Meditative activities are learned via social media

Synthesis & Design | Mid-fidelity Prototype

We developed two prototypes addressing the insights:

Problem 1: Mindful social media content is mixed with anxiety-inducing content (doom scroll)

Solution 1: Social media with only mindful content

Problem 2: Its difficult to remember find time to meditate

Solution 2: App assists you to find time for meditation on-the-go

Test | A/B test

To test the two prototypes, we stationed in a high traffic area and lured participants with pizza (!!)

We recorded notes (key quotes, behavioral observations, and suggestions) and compiled them in a FigJam board. We then synthesized insights into categories with guidance from Zena, our IDEO mentor.

Refine | High-Fidelity Prototype

Most preferred the ShhShh concept because it ‘felt familiar’ and offered something they desired to replace tiktok with.

We adjusted the ShhShh app based on user feedback.

Phase 2: Equitable Design App for the formerly incarcerated

Why design for the formerly incarcerated?

This underserved audience could benefit from mental health support

Design Research | Discovery SME interviews

  • Question: What are formerly incarcerated individuals’ relationship to Mindfulness?

  • Participants: People in the formerly incarcerated community (former inmates, social workers)

  • Method: Five 1-hour interviews

Insights

  • Support groups improve reintegration to society

  • Meditation is perceived to be a luxury for ‘others’

  • Religious books offer 24/7 support

Synthesis & Design | Co-design prototype

Nadia and I synthesized insights into sketches to spark conversation during a 2-hour co-design

We presented the traditional prototype to get into a feedback mindset & learn about the co-design users’ needs

Paper sketches helped launch into co-designing a new meditation app

Co-Design

Refine | Mid-fidelity prototype

Insight: “You leave prison with nothing”

Feature: Immediate support

Insight: “Talking to peers was instrumental in my recovery”

Feature: Peer support network

Insight: “My motivation came from podcasts”

Feature: Success stories from likeminded people

Test & Refine | Guerilla user testing

To test the prototype, we solicited feedback from six people from the formerly incarcerated community in 1:1 interviews. During the interviews, we also led participants through an “unintended consequeces” analysis of the app.

We compiled notes in FigJam and synthesized insights with Zena.

Refine | High-Fidelity Prototype

We adjusted the final prototype based on user feedback and risk factors.

Evaluation

15 likert scale questions:

  • Product stickiness and engagement: Did they like it? How often would they use it?

  • Trust and customer loyalty: Referral rates, expected use long term

  • Market differentiation: Uniqueness from alternatives

Traditional vs. Equitable Design | Survey

100 Respondents:

  • 56% white

  • 74% attended some college

  • 56% ages 18-34

ShhShh (Traditional)… Won! BUT all co-designers preferred FreeMind (Equitable).

58% preferred ShhShh overall… even when we subtracted respondents who self-identified as white.

Survey feedback was interpretable because the traditional and equitable design processes yielded apps that served different purposes.

Even if people preferred ShhShh, it may not be as effective as FreeMind in helping formerly incarcerated individuals reintegrate to society (or similar use cases). Our overall recommendation is to design equitably first, and then scale.

Reflection

This project had a massive scope, meaning we had to derive meaning from subjective results.

Insight: Comparing two design processes is challenging due to the variability of outputs. During the Equitable phase, we spent more time on collaborative ideation, leaving less time to develop the high-fi prototype. Perhaps participants preferred the Traditional prototype because we had more time to refine its final form and flow.

With more time: It would have been interesting to adapt the Equitable app based on feedback from non-target users. I wonder if an adapted iteration would outperform the Traditional app.