2025
Meal Planning for Food Security
Team project for HCI 445: User Research Methods @ DePaul University
A mixed-methods study exploring how young adults navigate meal planning — and how a technology-based solution could help reduce food insecurity by meeting users where their real constraints are.
Role
User Researcher
Timeline
10 weeks (Mar 2025 - June 2025)
Primary Methods
Observations
User Interviews
Tools
FigJam
Atlas.ti
Context
A growing problem, a fragmented toolkit
Food insecurity is rising among young adults in the US, not just due to affordability, but because of the cognitive and logistical overhead meal planning creates when layered onto busy schedules. Existing digital tools tend to solve parts of the problem in isolation: one app for recipes, another for grocery lists, another for nutrition tracking.
This study set out to understand the full picture: what does the meal planning process actually look like for young adults today, and where does it break down?
Research Question
How can a technology-based solution help provide meal planning assistance for young adults to help increase their level of food security?
Competitive Review
Two primary existing solutions helped frame the problem space: HelloFresh addresses ingredient delivery but sits behind a paywall and limits flexibility; MealPrepPro handles grocery list generation but lacks cross-device functionality. Neither addresses the full breadth of user needs surfaced in our research.
Methodology and Process
Observations and Interviews
Participants were recruited through the College of Computing and Digital Media and word-of-mouth referrals. Observations and Interviews were moderated over Zoom, with a primary moderator and another teammate for note taking. All participants were screened to ensure that they were a part of a household that shares meals.
8
Observations
8
Interviews
Data Analysis Methods and Output
Affinity Diagrams and Inductive Coding
Following our observations and interviews, I performed inductive coding of interview transcripts. We then created affinity diagrams to cluster common behaviors and barriers participants faced in their meal planning process.
Personas and Experience Maps
With all of our participant data processed, we placed the participants along spectrums to identify common characteristics that informed our personas. Experience maps were made for our personas to visualize the distinct needs and behaviors of each.
Priority Matrix and Design Implications
Based on our interview data and observed pain points, we brainstormed features and assigned them with a priority level, expected impact for users, and feasibility of implementation. We also produced general design implications for a technology-based meal planning solution.
Sequence diagram
Mapping the meal planning process
We built a sequence diagram directly from our observation sessions to map the consistent underlying process, with two main decision points that vary significantly by user type.
Check Schedule
If people have spare time, a specific day is chosen to cook for the week. If not, meals are planned and cooked day by day.
Check Pantry
Take inventory of what's on hand. If there are enough ingredients, some move straight to planning. If not, building a list is the next step.
Build List
The individual makes a grocery list based on a recipe, or staple ingredients they know they will use.
Grocery Shop
Go through aisles and check off the list (or order online). Loop back if something is missing or the budget isn't being met.
Plan the Meal
Finalize what is being cooked, and when. Often, this occurs more last minute despite prior list building and planning efforts.
Cook
This is where plans most often deviate, due to time constraints, missing items, or household conflicts.
Common Patterns and Breakdowns
Busy Schedules · Suburban
Those with busy schedules and those living in suburban environments had overlapping processes: structured weekly plans, cooking ahead of time 1-2x a week, fewer shopping trips, and a longer planning horizon.
Flexible schedules · Urban
Those with more flexible schedules (e.g. students, remote employees) and those living in urban environments usually had looser meal plans, cooking daily as needed. They also made more frequent grocery trips, and improvised from their available ingredients more often.
Breakdown factors
The most common cited painpoints in the meal planning process from observation participants were food waste from unused/forgotten ingredients, skipped meals due to time limitations, resorting to takeout when lacking the energy needed to cook, and household coordination breakdown.
findings
Key Themes and Persona Spectrums
Following our observations and interviews, we conducted inductive coding of interview trascripts, created affinity diagrams to identify clusters of behavior and barriers,
Tool & Resource Limitations
Participants used a fragmented combination of tools (Notes app, spreadsheets, MyFitnessPal, cookbooks, social media), each covering parts of the process but unable to connect in a meaningful way. One participant had built her own spreadsheet system but still couldn't extract the information she needed in the moment.
All 16 participants wanted ingredient-based recipe recommendations to reduce waste and save shopping time
2 participants wanted nutrition tracking integrated with meal planning, instead of siloed separately
Time & Scheduling Limitations
Work and class schedules directly shaped when and how participants could cook. Those working 50+ hours per week reported accidental undereating and expired ingredients from a lack of time to execute plans they'd already made.
Busy participants batch-cook 1-2x per week with fewer shopping trips
Time scarcity leads to takeout, skipped meals, and food going bad before it can be used
Over half wanted shared calendar integration for household coordination
Shopping Habit Differences
Proximity to grocery stores and shopping frequency varied significantly, and this variation directly shaped planning style. Urban participants could improvise daily, while suburban participants needed to plan further ahead to avoid unnecessary trips.
Wholesale shoppers plan further out and have less mid-week flexibility
Urban participants closest to stores were least likely to have structured meal plans
Persona Creation
We mapped the participants along spectrums for cooking frequency, hours worked, household size, and grocery store proximity, which surfaced two distinct behavioral clusters that anchor our design implications.
Gemma
27 · Full-time graduate student · River North, Chicago
Background
~30 hrs/week of coursework. Lives with one roommate, but cooks independently. Within walking distance from grocery stores, she shops daily and improvises her meals with available ingredients. Still working on building her cooking confidence.
Goals
Find recipes she can make with what's already at home
Avoid wasting ingredients before they spoil
Build confidence with skill-appropriate suggestions
frustrations
Trying new recipes that she ends up not liking or doesn't feel confident making
Trouble sourcing cheap ingredients
Loses track of recipes she has made before and where she found them
Christopher
30 · UX Designer and Part-time Student · Niles, IL
Background
Works 60 hours a week between freelancing and school. Lives with 3 roommates who often cook together. Shops at local grocery store chain and H-Mart, both which require a drive. Usually, he prefers to plan and batch-cook meals for the week ahead.
Goals
Coordinate meals with roommates without group chat chaos
Hit fitness and nutrition targets without manual tracking
Spend as little mental energy on planning as possible
frustrations
When he is too busy to cook as planed, he falls back on unhealthy takeout
Difficulty finding recipes that meet his nutrition goals
Roommate taste conflicts derail shared meals at times
Design Implications
Research-Based Design Requirements
Based on our research findings, we developed requirements for a technology-based meal planning solution.
Consolidate the toolkit
As one participant put it: "Putting all of the data points in one place is one thing, but being able to use that efficiently and effectively is another." The solution must connect pantry inventory, recipes, grocery lists, and nutrition, not just put them all in one place.
Make ingredients the primary input
Every participant wanted recommendations based on what they already have. Ingredient availability should be the first signal the system uses, instead of cuisine preference or dietary restrictions.
Adapt to the user's schedule
The system must accommodate structured weekly planning and loose daily cooking. A rigid weekly plan template fails the majority of users who don't operate that way.
Design for shared households first
Over half of the participants shared meal planning responsibilities. Grocery list sharing and collaborative planning features are baseline requirements for the most common household type in the study.
Account for location and proximity
Store proximity fundamentally changes how users plan. Urban participants shop daily and plan loosely, while suburban participants plan further ahead. Features involving grocery shopping should allow users to define their own shopping habits.
Support physical-to-digital transition
Some participants prefer pen and paper for lists. The solution should allow digital copies of physical notes rather than forcing a digital workflow, which should lower the barrier to adoption.
Priority Matrix
Features were ranked across priority, impact for users, and feasibility of implementation. The top-ranked features are those that address the widest range of pain points across both personas.
Ingredient inventory tracking
Recipe recommendations from inventory
Shared grocery lists
Digital notes & recipe storage
Meal calendar with shopping integration
Nutrition information per recipe and ingredient
Grocery budgeting tool
In-app household messaging
Limitations and Next steps
Study Limitations
Most participants were recruited through the DePaul CDM participant pool, which skew toward graduate students in Chicago. The findings likely underrepresent working professionals, families, and adults outside major cities. Further, all interviews were with individuals, which could have limited our findings around collaborative planning needs.
What's Next
These implications haven't been designed and tested. The next phase is to ideate features based on these findings, build low-fidelity concepts, and run usability studies to validate whether the implied solutions actually reduce friction for both user types.
Takeaways
Thinking about the user first
Throughout this project, one of the biggest challenges for me was not jumping to cool features we could implement in a design. Although this course was limited to just user research with no design output, it really helped me focus on understanding the needs of users and the value in conducting in-depth research before jumping to a solution. I have heard the phrase "the user is not like me" countless times, and no matter how much I think I know about meal planning, talking to others and gathering first-hand experiences yields insights that could have never come from assumptions alone.
© Jack Thomson 2026