Ramya Yerramilli
A student trying Wellnut in VR for the first time
UX Researcher + Project Coordinator · Jarvis Innovation Challenge 2025

Wellnut
A nutshell to express yourself

A VR companion that gives students a private, judgment-free space to pause, talk, and breathe — no appointment, no stigma, no waiting list.

Role
UX Researcher + Project Coordinator
Duration
6 Months · Nov 2024 – May 2025
Team
UX Research · Unreal Dev · Environment Art · Character Art · Audio
Tools
Unreal Engine · Maya · Google Forms · Perforce

61%

of students who need mental health support never reach out

33

Students surveyed, across 6 academic disciplines

4

Research phases, 6 months to showcase

Early concept visual: how can Wellnut help?

The Problem

Campus mental health services exist. Students don’t use them.

The problem isn’t a shortage of resources — it’s that stigma, time, and awareness create a gap between students in distress and support that’s already free.

Students wish schools could proactively check in with them — not wait for them to come forward.

Secondary research finding — Student Voice Survey synthesis, DePaul 2024

Free help already exists. Almost no one asks for it.

  1. 01 · The Scale — Unused

    58% of students with chronic stress have never accessed an on-campus mental health service, despite it being free.

  2. 02 · The Barrier — Independence

    67% prefer handling things on their own. 48% cite no time. Stigma and trust issues compound both.

  3. 03 · The Opening — Already there

    71% specifically saw value in VR-based meditation — before any product existed to try.

The Stakes

Help already exists. The barrier isn't access — it's the moment before someone asks.

Research Process

Four phases. Mixed-methods throughout.

  1. Wks 1–4 · Secondary Research

    Literature review of the mental health crisis, existing interventions, and the VR + meditation evidence base.

  2. Wks 5–10 · Primary Research — Survey

    33 students surveyed across 6 disciplines on mental health need and VR receptiveness, then mapped into barriers.

  3. Wks 11–14 · Expert Consultation

    Licensed therapist interview — built the empathy-language framework and ethical guardrails.

  4. Wks 15–26 · Scope, Build, Showcase

    MVP scope defined, avatar and environment built in Unreal Engine, dialogue branches designed, shown at Jarvis Innovation Showcase.

Mixed methods, not sequential

The survey told us what students needed. The therapist told us how to deliver it. Neither alone was enough.

The numbers that shaped every decision.

64%

Rated academic adjustment moderately to extremely challenging

61%

Rarely or never seek mental health support, despite experiencing need

71%

Saw value in VR meditation for exam stress and performance

58%

Open or maybe open to using VR wellness tools regularly

61% of students who experience a mental health need rarely or never seek support — yet 71% said VR meditation could help them.

Primary research synthesis — 33-participant student survey, Dec 2024

Methodological limitation

Participants were self-selected students from a single institution — findings are directional, not generalizable. A next step: a broader, multi-institution sample, including students who've actively sought support.

Expert Consultation

Designing for psychological safety.

The avatar should model a healthy relationship — providing space, listening, and validation — while maintaining appropriate boundaries. It should feel like someone who cares, without replacing human connection.

Licensed therapist interview, Dec 2024

What changed after the interview

Before: the avatar offered meditation right after the user picked an emotion. After: a validation step first — acknowledge, then guide. One principle drove the change: never skip acknowledgement.

  1. Trust building

    Set clear expectations upfront — session duration, confidentiality, what the avatar can and can't do. Uncertainty breeds anxiety.

  2. Active listening cues

    Pick up the user's own keywords and mirror their language. If they say "stressed," the avatar uses "stress." Pauses simulate thought.

  1. Validate, then act

    "That sounds really challenging" before "Let's try breathing." Never skip acknowledgement — it's what makes a response feel human.

  2. Ethical guardrails

    Limit session availability to prevent dependency, and include gentle prompts toward professional help. Never promise what the system can't keep.

Design Rationale

Three decisions, backed by research.

  1. Why VR — privacy without stigma

    A physically enclosed space nobody else can see into. Directly answers the 67% who'd rather stay independent than seek help in public.

  2. Why an avatar — connection without commitment

    Instantly available — no booking, no commute, no waiting list — for the 48% who cite no time for traditional support.

  3. Why talk, then meditation — acknowledge, then guide

    Students need to feel heard before they can receive guidance. Conversational support first, technique second.

Scoped for depth, not breadth

One exceptional, research-grounded experience over five half-finished features. Voice AI, biometric sensors, and mood tracking are roadmap — not v1.

Unreal Engine build — Lonely or Stressed emotion bubbles in the forest
Unreal Engine editor — emotion bubble blueprint system

In the editor

Emotion-bubble blueprints branch the dialogue tree live in Unreal — the same system built the emotion-bubble forest on the left.

Wellnut — a nutshell to express yourself, brand poster

The Solution

One polished experience beats five unfinished ones.

A forest environment and meditation cave in Unreal Engine, an avatar with two emotion-based dialogue branches, a guided meditation, a personalized greeting, and a blue-green palette chosen for psychological calm.

Watch It Work

Three moments from a six-month build.

Building the forest, in the editor

Setting up for showcase night

Guiding a first-time user in

Team at the Jarvis Innovation Showcase 2025
Wellnut presented to a full room at the showcase
Wall of Feedback — real sticky notes left by showcase attendees

Jarvis Innovation Showcase · 2025

Live feedback, in real time.

Attendees tried the live prototype and left sticky notes on a Wall of Feedback — “loved it,” requests for meditative background audio, one asking for Wellnut to “have emotes.”

This feels like talking to someone who actually cares.

Attendee feedback — Jarvis Innovation Showcase, May 2025

Research that built something real.

5 → 0

Team members onboarded to Unreal Engine — none had prior experience

71%

Pre-validated VR demand, before the product existed

6 mo

From first literature review to live showcase

  1. Dec 2024 – Jan 2025

    Primary Research — 33 Students Surveyed

    Mixed-methods survey across 6 disciplines validated the problem and revealed 71% VR receptiveness — directly informing the platform choice before any code was written.

  2. Feb 2025

    Licensed Therapist Interview — Empathy Framework Created

    A structured expert interview produced a reusable empathetic dialogue framework and ethical guardrails for avatar-based mental health interactions.

  3. May 2025

    Jarvis Innovation Challenge Showcase

    Prototype exhibited to students, faculty, and industry guests. Live feedback collected via a Wall of Feedback.

What Wellnut taught me.

  1. Mixed methods work together

    The survey showed what students needed. The therapist interview showed how to deliver it. Neither alone was enough.

  2. Scope is a research decision

    Choosing what not to build was as important as what to build — one polished MVP over five unfinished features.

  1. Domain experts accelerate design

    One structured therapist interview gave us an entire empathy framework and ethical guardrails — months of iteration compressed into one session.

  2. Technology serves the human need

    We chose VR because the research pointed there, not because VR is exciting — private, available, judgment-free support was the actual goal.

Now

The roadmap picks up where the six-month scope had to stop.

Real-time AI and voice interaction, biometric sensor integration, more environment options, and a weekly check-in system are next — alongside testing with a broader, multi-institution sample and students who’ve actively sought support, to move the findings from directional to representative.

ASAP, an AI-scaffolded academic planner