Conscious | Mitigating Fatigue for Shift Workers
Project type: University Project (University of Sydney)
Role: User Research & Product Design
Tools: Figma
Duration: 8 weeks
Introduction
My project partner and I tackled a common issue faced by shift workers: fatigue. Following the Double Diamond framework, we moved through four key phases. In the Discover phase, we conducted both qualitative and quantitative research to explore the root causes of fatigue. In the Define phase, we synthesized our insights and reframed the problem to focus on the most critical needs. During the Develop phase, we brainstormed ideas, built quick prototypes, and iterated based on user feedback. Finally, in the Deliver phase, we refined our solution into a high-fidelity mockup and presented our final report to the class.
Understanding the problem
Shift workers in Australia often face extreme fatigue due to irregular, late, and extended working hours that disrupt natural sleep cycles and social routines. This disruption can lead to Shift Work Disorder, a condition characterized by insomnia, excessive sleepiness, and reduced alertness. Over time, these issues can result in serious health consequences including substance dependency, poor nutrition, and increased risks of chronic illnesses such as cardiovascular disease, gastrointestinal issues, and cognitive decline (Pacheco et al., 2020).
Adequate sleep is crucial for maintaining reaction time, emotional regulation, and cognitive clarity. Without it, shift workers face a significantly higher risk of workplace accidents and injuries (Newsom et al., 2021).
Recognising the long-term impact fatigue has on the health and safety of shift workers, we set out to address this issue through a digital solution—designed to promote healthier lifestyles and adapt to the unpredictable nature of shift work.
Research Goals
Understand the daily routines and challenges of shift workers
Identify current coping mechanisms and tools used.
Understand the emotional and social impact of fatigue.
Explore digital habits and technology access.
Identify opportunities for intervention through digital means.
Research Approach
To understand the experiences of shift workers and explore the impact of fatigue on their health, safety, and quality of life, we used a mixed-methods research strategy:
12 In-Depth User Interviews – to uncover personal stories, pain points, and behaviours.
2 Online Surveys – with 158 participants to validate and quantify common experiences.
Online Ethnography – observing conversations across 3 Facebook groups dedicated to shift workers.
In-Person Observations – conducted at 3 different locations to capture context and environmental factors in real time.
This approach helped us gather both qualitative depth and quantitative scale, ensuring our insights were grounded in real, lived experiences.
Key Findings
Our research revealed three core themes that deeply informed our problem framing and design direction:
Theme 1: Shift workers need longer recovery time between shifts
Participants consistently described feeling burnt out due to back-to-back shifts, irregular hours, and insufficient time to recover between workdays. This disrupted their ability to maintain routines, social connections, and self-care due to persistent fatigue.
“On your days off you’re just recovering, you don’t actually have energy to go out and do something fun.”
“When you have 4 shifts in a row, it takes at least 24 hours to get back to normal sleep patterns.”
Theme 2: Fatigue is a Serious Safety and Health Risk
Many participants shared how fatigue directly affected their performance, safety, and long-term health. From making simple mistakes to experiencing serious health issues like insomnia, migraines, and even autoimmune conditions, the physical and mental toll of shift work fatigue was clear.
“Very easy to make mistakes when you’re sleep deprived.”
“I’ve developed migraines from fatigue.”
“When you’re a bit tired you’re not as aware… more likely to get injuries.”
Theme 3: A Lack of Communication Between Employees and Employers
Despite the severity of their fatigue, most shift workers chose not to disclose it to their employer. Fatigue was often viewed as a sign of weakness, and workers feared judgement or repercussions.
54% had left work early due to fatigue
Yet 66% had never told their employer they were fatigued
66% believed the employer was responsible for managing worker fatigue
This highlights a communication gap and the need for better awareness, policies, and cultural support around managing fatigue in the workplace.
Framing the problem
Despite existing tools for rostering and communication, shift workers continued to experience fatigue—largely due to poorly timed, back-to-back shifts. Our research revealed that workers rarely voiced these concerns, making it difficult for management to respond effectively. We realised the issue wasn’t just about tools or communication—it was about control. Instead of relying on top-down scheduling, we proposed a platform that empowers shift workers to collaboratively build and manage their own rosters.
Problem Reframed:
Shift workers need a flexible, energy-aware rostering system that supports their wellbeing by adapting to their recovery needs and giving them greater control over their schedules.
Persona’s
We developed two persona’s to help guide our design decisions during our prototyping phase.
👩⚕️ Persona 1: Maria – The Overnight Nurse
Age: 33
Occupation: Emergency Room Nurse
Location: Sydney, NSW
Work Schedule: 4x 10-hour night shifts per week
Goals:
Stay alert and focused during long night shifts
Avoid burnout and stay healthy
Have quality time with her family during off hours
Frustrations:
Difficulty falling asleep during the day
Lack of consistent meal and hydration habits
Always feels behind on life admin and errands
Tech Habits:
Uses a Fitbit and a sleep tracker
Checks apps like Headspace and Calm
Reluctant to try new apps unless they’re very intuitive
Quote:
"I love helping people, but the exhaustion builds up. Sometimes I feel like I’m running on autopilot."
👨🔧 Persona 2: Sam – The Early Morning Warehouse Worker
Age: 41
Occupation: Logistics Operator at a distribution center
Location: Western Suburbs, VIC
Work Schedule: 5:00 AM – 1:00 PM, alternating weekends
Goals:
Wake up easily and feel energized in the morning
Find a balance between work, exercise, and rest
Avoid injuries and stay sharp on the job
Frustrations:
Struggles with early morning wake-ups
Feels groggy at work, especially mid-week
Difficult to maintain a consistent sleep routine
Tech Habits:
Uses a basic smartphone (Android)
Watches YouTube for tips on productivity and sleep
Doesn’t trust overly complex tech or paid subscriptions
Quote:
"I’m not lazy — I just can’t get into a rhythm. Every week throws something new at me."
Develop - Ideation and Prototyping
Paper Prototype
To kick off prototyping, we created a paper prototype to quickly visualise and test our core concept. Our initial idea centred around a mobile app that could intelligently roster shift workers, track fatigue levels in real time, and provide tools for flexible shift management.
Users would begin by signing up and entering personal information such as age, health factors, job type, and other relevant data. This information would feed into an algorithm designed to optimize rostering across the cohort, aiming to minimize collective fatigue.
We also introduced a feature allowing workers to manage their own schedules through two key actions:
Shift Swapping – Workers could offer one of their shifts in exchange for another worker’s shift.
Shift Covering – Workers could request another to take over a shift without requiring a trade.
Alongside rostering, we designed a community-driven feedback board where users could anonymously raise and vote on concerns related to their schedules. The system would monitor this board to identify recurring issues, updating its rostering logic over time based on the most upvoted concerns.
Shift Swapping & Covering
Additional features
Fatigue-Based Shift Locking: The system automatically locks shifts for users who have worked too many back-to-back (B2B) shifts, to help prevent burnout.
Fatigue Visibility: Each user’s fatigue level is visualised, so workers can make smarter decisions when requesting covers or swaps.
Raising Issues
Additional features
Upvote Limit: Users can upvote up to 4 issues at a time to help the system focus on the most important problems.
Duplicate Detection: When posting a new issue, the system suggests similar existing issues to avoid duplicates and keep the feedback board clean and efficient.
Think Aloud
To validate our paper prototype, we conducted a think aloud session with three shift workers. Participants were asked to navigate through the prototype while verbalising their thoughts and reactions in real time.
This helped us uncover several valuable insights:
Shift Swapping and Covering
Users valued the ability to swap and cover shifts, but many felt uncomfortable sending requests to a single coworker. They worried it put pressure on that individual and could cause guilt if the request was declined. Several participants suggested allowing requests to be sent to multiple coworkers to avoid singling anyone out.Fatigue Score Visualisation
Some participants misunderstood the fatigue score visualisation, interpreting it as a progress bar. This confusion indicates a need to simplify the design and make the fatigue metric more intuitive and self-explanatory.Issue Board
The issue board feature was positively received—especially the upvote functionality. However, most users were unaware of the 4-vote limit, suggesting a need for clearer onboarding or visual cues. Additionally, users mistakenly believed management, rather than the system’s AI, would review their rostering concerns.Fatigue-Based Shift Locking
This feature was poorly received. All participants found it too restrictive and unrealistic for real-world use.
Overall, these insights helped us prioritise refinements for the next design iteration and validated that we were addressing a meaningful problem for shift workers.
Wireflow
Based on insights from our think-aloud testing, we created a refined wireflow to map key user interactions and system logic. This wireflow allowed us to visualize user navigation through the app and identify opportunities for improvement based on early feedback.
Key updates included:
Shift Swapping and Covering
Users can now send a single request to multiple coworkers at once, instead of selecting just one person. This reflects the reality of unpredictable availability and improves the chances that someone will accept the request.Fatigue Score Visualisation
We simplified the fatigue display by introducing three clear labels and visual indicators. This makes it easier for users to quickly understand how fatigued each coworker is before sending a request.Issue Board
We updated the wording and improved the UI of the issue board to make it easier to post and upvote issues.Fatigue-Based Shift Locking
This feature was removed.
This wireflow served as a foundation for our high-fidelity designs and ensured that every screen and interaction supported a smooth and user-centered experience.
Requesting to Cover/Swap
Raising Issues
Think Aloud
After updating the prototype based on our first round of feedback, we ran a second think aloud session with five participants to validate our refined user flows and improved UI. Participants were again asked to complete tasks while narrating their thoughts, helping us observe how intuitive the experience felt.
Here’s what we learned:
Shift Swapping and Covering
While users appreciated the ability to send cover requests to multiple coworkers, most expressed a desire to send the request to all coworkers at once. This highlighted the need for an additional “Select All Coworkers” option.Swap Requests
The distinction between cover and swap requests was much clearer in this version, thanks to the added icon. Users understood the difference and appreciated the added control and clarity.Issue Board
All users assumed the issue board submissions were being sent to a human manager, rather than informing the system. To address this, we planned to improve the wording and visual cues to clarify that submitted and upvoted issues help shape decisions made by the automated rostering system.General Usability
Navigation was generally smooth, but users took longer to complete tasks due to the high number of clicks required. Reducing the number of interactions needed to complete key actions was to be a top priority in our high-fidelity prototype.
This round of testing confirmed that we were moving in the right direction, while also highlighting areas for small refinements to improve clarity and reduce friction.
Deliver - High Fidelity Prototype
In our high-fidelity prototype, we aimed to establish a design language that communicated trust, vibrancy, and usability. We chose a bold, high-contrast color palette to give the interface a modern, energetic feel—instilling confidence that the platform is reliable enough for company-wide rostering.
To reinforce a clean and contemporary look, we used sans-serif fonts Roboto and Inter, known for their readability and modern aesthetic.
We also prioritized accessibility and ease of use:
Buttons were made larger than standard to support tired or older shift workers, making them easier to find and tap.
All color combinations meet at least AA contrast standards, ensuring legibility for users of all abilities.
Onboarding Form
Swap / Cover Page
When signing up for the Conscious app, shift workers are asked to complete a form that collects key personal information. This data helps the system categorize each user and estimate recovery time between shifts, based on factors such as sleep schedule, other commitments, age, gender, and more.
If we had more time for this project, we would have liked to conduct additional research to better understand how different demographics and lifestyle factors influence the ideal duration between shifts and overall shift length. This would allow us to refine our recommendations and ensure they’re grounded in evidence-based insights.
The Cover Request page is designed to make sending cover requests quick and intuitive. Users can select specific coworkers to send requests to, with the list automatically sorted by energy level—those with the highest energy appear at the top, helping users make more informed decisions.
Based on feedback from our think-aloud sessions, we added a “Send to all coworkers” checkbox, allowing users to instantly select all available employees for that shift with a single tap.
We also streamlined the page layout, making it easier to switch between shifts and request types for a smoother, more user-friendly experience.
Similarly, when creating a swap request, the dropdown list of available coworker shifts is automatically sorted by fatigue level, with the least fatigued users appearing first to help users choose the most suitable swap options.
Swap Requests
When users open the Conscious app, they’re presented with all incoming and outgoing shift requests on a single, easy-to-scan screen.
In our high-fidelity prototype, we introduced filter options—‘All’, ‘Swaps’, ‘Covers’, and ‘Sent’—to help users refine the list and focus on specific types of requests, improving clarity and ease of use.
Building on feedback from our think-aloud testing, we retained the arrow icons that distinguish between swap and cover requests, as users found these helpful. We extended this visual language to also indicate whether a request was incoming or outgoing, reinforcing clarity through consistent iconography.
We also introduced color-coding, inspired by the Beem payment app:
Purple indicates requests that have been resolved
White (empty) signals requests that are still pending action
This visual system allows users to quickly scan the screen and understand the status of each request at a glance.
Calendar
Inspired by Apple Calendar and Microsoft Teams, the Conscious Calendar offers users a clear, intuitive view of their roster, with their own shifts visually highlighted for easy reference.
Users can:
Tap their own shift to open the swap/cover request page.
Tap another user’s shift to initiate a swap request with one of their own.
Or press ‘+ Add Request’ to start a new request from scratch.
We also refined the fatigue level visualisation, simplifying the icons to create a cleaner, more modern interface that aligns with the overall aesthetic of the app.
Cover Requests
Our main focus for the Issue Board was to improve clarity around its purpose. To help new users understand that feedback is directed to the system’s AI—not a human manager—we added a sparkle icon (commonly associated with AI features) alongside a clear message: “Upvoted issues guide how the system adjusts the roster.”
To further support transparency, we displayed the number of remaining votes prominently in the top left corner. As users cast votes, the number visibly decreases, making the voting limit intuitive and easy to track.
We also improved the upvoting flow by reducing the number of clicks and scrolls required. Now, as users begin typing their issue, similar existing issues automatically appear. This allows users to quickly identify and upvote a matching issue, simplifying the process and reducing friction.
Issue Board
Future Steps and Considerations
Overall, we developed a strong concept for a rostering system optimized around worker fatigue. If we had more time, I would have liked to deepen our research and ideation around how fatigue-based automation could actually function—particularly on the technical side.
Since the brief didn’t require a feasibility study, we defaulted to the idea that this logic would be handled by AI. However, it would have been valuable (and exciting) to explore alternative approaches, or even investigate which AI models or data inputs could realistically support this kind of optimization.
In addition, it would’ve been beneficial to prototype the concept more holistically—creating a more complete click-through experience and clearly defining how the onboarding flow integrates with the rest of the app.
Lastly, it would have been great to develop mockups for the manager-facing experience, including how managers might override, guide, or set constraints for the AI system. This would help round out the concept into a full, end-to-end solution.