Rethinking screen time.

What if tech encouraged self-reflection?

TLDR;

TLDR;

Intent was my capstone project at Parsons, born out of a growing discomfort with how digital products demand constant attention. I wanted to explore how design could do the opposite, help people reclaim it. Through research, interviews, and prototyping, I built a tool that surfaces usage patterns and nudges users toward healthier tech habits - without guilt or restriction.

TEAM

Solo project under faculty guidance

MY ROLE

Concept, Research, Strategy, Product Design

DURATION

4 months (Feb 2025 - May 2025)

Challenge

Challenge

When most apps are designed to capture attention, how can we create ones that encourage a healthier relationship with our devices?

Deeper context of the challenge

Deeper context of the challenge

The average person checks their phone over 150 times a day. But how many of those are conscious choices?

Most apps are built to capture attention, not to respect it.
They thrive on habit loops, infinite scrolls, and persuasive design tactics that keep us on autopilot.

This creates a gap:
Where are the tools that help us pause, reflect, and use our devices more intentionally?

Intent was born to explore that question—by reimagining screen time as a space for self-awareness, not shame.

Here’s my screen time from a random Monday. It’s actually lower than my usual (somehow). Go check yours too!

Here’s my screen time from a random Monday. It’s actually lower than my usual (somehow). Go check yours too!

Design Opportunity

Design Opportunity

01
A personalized feedback system

that transforms screen time data into simple, human-readable insights, helping users reflect on their patterns and intentions.

02
A layered intervention model

combining gentle in-the-moment nudges and interactive learning tools to build awareness, reduce autopilot use, and encourage healthier digital habits.

Let's understand how this works. From insight to intention.

App Bucketing,
User-defined Baseline

Users begin by sorting their top 10 most-used apps into two buckets:

  • Intentional (used with purpose)

  • Not Sure (used passively or uncertainly)

This act of labeling sets a personal baseline, allowing the system to tailor its response based on how the user feels about each app—not just how much they use it.

Daily Reflections,
Emotional Awareness

At the end of each day, users respond to a simple question:
“How did your screen time feel today?”
This helps users evaluate usage through a qualitative lens—adding emotional context to raw data.

The system uses this input to detect friction points and patterns over time.

Analytics,
Meaningful Metrics

Screen time is reframed—not just as total hours, but as a balance of purposeful vs. habitual time.
A dynamic Focus Score tracks progress, encouraging growth through insight rather than shame.

Contextual Nudges,
Adaptive Intervention

When a user opens a “Not Sure” app, Intent gently interrupts the pattern with a nudge.


These nudges are:

  • Subtle and easily dismissible

  • Timed based on usage habits

  • Focused only on apps the user flagged as uncertain


Over time, the system learns when to nudge and when to stay silent—becoming smarter, not stricter.

How the Intent System Learns

How the Intent System Learns

Not a collection of features, but an invisible, evolving system that works beneath the surface — personal, quiet, and constantly learning.

Hey! Got a laptop nearby?

Hey! Got a laptop nearby?

The full scoop (including the non-linear process - real product, real people, real designs) lives on the web version of this portfolio!

Bucketing

You label apps as Intentional or Not Sure

The system learns what matters to you

Reflection

You log how your day felt

The system learns emotional patterns

Analytics

You see your Focus Score and trends

The system learns your habit shifts over time

Nudges

You get subtle prompts when needed

The system adapts in real time

Sets your

personal baseline

Adds depth

beyond data

Gives meaningful

feedback

Learns when

to step in (or not)

SYSTEM LEARNS

USER ACTIONS

BEHIND THE SYSTEM, THE PROCESS

This wasn’t a linear UX journey—because real behavior isn’t linear either. It unfolded through questions, contradictions, false starts, and quiet realizations that shaped what Intent became.

Want to look at the full thing - here's a deck!

growth and reflections

Future Development

Deeper emotional mapping using journaling or sentiment analysis

  • Adaptive nudges powered by time-of-day and mood trends Integrations with existing screen time APIs across platforms

  • A minimal wearable extension for real-time reflection cues

Business Model

Rather than monetizing attention, Intent could operate on a donation-supported model.

  • Freemium model with advanced pattern analysis for subscribers

  • B2B partnerships with schools, wellness platforms, or HR tools

Market Opportunity

As attention becomes a new currency, systems like Intent are redefining what healthy tech looks like—from the inside out. With rising awareness of digital fatigue, attention hijacking, and ethical tech, people are looking for tools that empower, not control.