Rotational Focus Strategies

Most ADHD productivity advice focuses on finding a single 'best' strategy, but people with ADHD often experience diminishing returns when a technique becomes repetitive or stale. I wanted to explore whether deliberately rotating strategies could better support attention by leveraging novelty-seeking tendencies. Conducting this kind of multi-day behavioral study required software that could manage onboarding, randomized assignments, time-based scheduling, and structured data collection without constant manual oversight. Most ADHD productivity tools struggle not just with effectiveness, but with user adoption and sustained engagement. Many tools are abandoned within days, making retention itself a core design challenge.

I designed and implemented a full-stack application that managed the entire experiment workflow. Participants created accounts, selected three out of eight research-backed focus strategies, and completed daily surveys consisting of Likert scales, short-response prompts, and yes/no questions. During the four-day strategy phase, the system randomly assigned one of the user's chosen strategies each day, ensuring regular rotation. Custom scheduling logic enforced the study protocol: users could only complete the correct survey for their current phase (baseline, strategy use, or exit), once per day, and only for the appropriate number of days. All data was stored in a PostgreSQL database on Supabase, using a schema I designed specifically for this study.

To accelerate development and focus effort on study design and user experience, I built the system on top of a Next.js dashboard template, adapting it to support custom scheduling logic, randomized strategy assignment, and longitudinal data collection. This allowed me to prioritize rapid iteration, usability, and reliability over reinventing standard interface patterns.

Before launching the full study, I piloted the system with three users to validate onboarding, survey flow, and scheduling logic. Feedback from this pilot phase surfaced usability issues and edge cases that would have undermined participation, including confusing instructions, friction in daily check-ins, and minor system bugs.

I used rapid, iterative prototyping to address these issues—deploying fixes, refining copy, and simplifying flows between sessions. This process significantly improved clarity and reduced user friction prior to the full deployment.

This project was completed as part of a graduate course focused on experimental design and execution. As a result, the study was intentionally short in duration and limited in scope. These constraints shaped the design toward clarity, reliability, and fast iteration—prioritizing execution quality and participant experience over scale.

The platform supported a real longitudinal study with five participants, three of whom completed the full seven-day protocol. While the sample size was intentionally small, maintaining over 50% retention across a multi-day study with participants who have ADHD is notable, given the high abandonment rates typical of productivity tools in this space.

By automating participant management, randomized strategy rotation, and daily scheduling, the system minimized coordination overhead and reduced points of friction that commonly lead to disengagement. Survey data was exported for qualitative and quantitative analysis, providing insight into how structured rotation affected perceived focus and productivity over time.

This project reinforced the importance of designing systems that people will actually continue to use—especially when working with cognitively demanding workflows. I gained practical experience balancing experimental rigor with real-world constraints, designing for retention, and shipping reliable software under tight timelines.

It also deepened my understanding of how small UX decisions—clear instructions, predictable flows, and forgiving validation—directly impact participant compliance and data quality in research-driven applications.