Why Some Mental Health Apps Stick While Others Don’t: Lessons from People Using PolarUs for Bipolar Self‑Management

When Help Fits in Your Pocket but Life Gets in the Way

Mobile apps promise support for people living with bipolar disorder—tools to track mood, spot early warning signs, and practice coping strategies. Yet many of us download an app, try it for a week, and then forget it exists. That drop-off matters. For bipolar disorder, consistent self-management can reduce relapses, improve daily functioning, and offer a sense of control. The research paper What influences engagement with a bipolar disorder self-management app? A qualitative investigation of use of the PolarUs app asks a simple, crucial question: what keeps people using an app like PolarUs—and what gets in the way?

In this qualitative study, 25 adults with bipolar disorder used the PolarUs self-management app for three months, then took part in in-depth interviews about their experiences. Instead of tracking only how often people logged in, the team listened to what it actually felt like to engage with the app during real life. Their analysis surfaced three direct drivers of engagement—Motivations, Salience, and Perceived effort—and four contextual forces shaping those drivers: the smartphone ecosystem, daily life, mood symptoms, and being in a study. Together, these themes reveal why the same app can be helpful one week and invisible the next.

Why does this matter beyond one app? Because the patterns uncovered here extend to many digital health tools. By understanding the obstacles and cues that shape engagement, clinicians, designers, and people with bipolar disorder can make smarter choices—turning good intentions into repeatable habits.

What Kept People Tapping—and What Made Them Stop

First, Motivations fluctuated. People were more likely to open PolarUs when they had a clear goal—such as tracking sleep to prepare for a psychiatry appointment or monitoring early warning signs after a stressful event. During calmer periods, motivation dipped; the app felt less urgent. One participant might check in daily while adjusting medication, then taper off once things stabilized.

Second, Salience—how “top of mind” the app felt—was key. Visual cues like placing the app on the home screen or getting timely reminders nudged people to use it. When reminders landed at busy times (like rush hour or school pick-up), they were swiped away and forgotten. Small design choices, such as a clean notification with a simple action, made a difference in whether the app felt present or faded into the background.

Third, Perceived effort either greased the wheels or slowed everything down. People engaged more when tasks felt quick and manageable—think one-tap mood check-ins rather than lengthy questionnaires. If opening the app led to multiple steps, reading dense text, or waiting for screens to load, that friction piled up. On a low-energy day, even tiny hassles felt like big barriers.

Four contextual forces shaped these drivers. The smartphone ecosystem competed for attention: social media notifications, work emails, and other apps often won the tap. Daily life rhythms—work schedules, caregiving duties, errands—made certain times better (or worse) for app use. Mood symptoms mattered, too. In depression, low energy and concentration made engaging hard; in hypomania or mania, goal-directed behavior sometimes increased use, but distractibility could derail it. Finally, being part of a research study nudged some people to keep going—out of commitment to the team or the hope of helping others—even when personal motivation waned.

Motivation Meets Friction: Why Small Barriers Matter in Bipolar Self-Management

The findings map neatly onto well-known behavior models. The Fogg Behavior Model suggests that action happens when three things converge: motivation, ability (low effort), and a prompt. PolarUs users described all three: motivation spiked around clear goals; perceived effort (ability) made or broke follow-through; and salient prompts got them to open the app—if they arrived at the right moment. The COM-B model (Capability, Opportunity, Motivation) tells a similar story: depressive symptoms may reduce capability; a chaotic day limits opportunity; and both shape motivation.

Self-Determination Theory also helps explain why engagement rose when the app supported autonomy (choosing what to track), built competence (seeing progress), and fostered relatedness (feeling part of a study or care plan). When these needs were met, people returned more often. When the app felt burdensome or irrelevant, motivation dipped.

The smartphone context mattered more than many researchers acknowledge. Competing alerts, dopamine-rich platforms, and endless scrolls pull attention away from health tasks. A quick check-in can vanish beneath a pile of “urgent” notifications. This lines up with prior work on attentional capture and the “hassle factor”—tiny frictions that cumulatively deter follow-through. In bipolar disorder, where energy, focus, and executive function can swing, those frictions hit even harder.

Consider two common days. On a stable, structured Tuesday, a lunch-break reminder lands, the check-in takes 20 seconds, and a small insight—“better sleep after walking”—reinforces use. On a Saturday marked by a depressive slump, the same check-in feels heavy; even opening the app seems daunting. Or in a hypomanic upswing, someone might set ambitious tracking goals in the morning, then abandon them by afternoon as plans mushroom. The study’s take-home message: engagement is state-dependent and context-sensitive, not a fixed quality of the person or the app.

This aligns with broader mental health app research: initial curiosity is common, sustained use is hard. What this study adds is nuance about the levers to pull—especially reducing effort, timing prompts, and designing for fluctuating capacity—so that good days build momentum and hard days aren’t derailed by avoidable friction.

Design Moves and Daily Habits That Boost Staying Power

For designers and clinicians, the message is practical. Reduce perceived effort with one-tap mood logs, smart defaults, and short check-ins that expand only if the user wants more. Offer just-in-time prompts that adapt to routines—morning coffee, lunch, bedtime—so reminders land when people can act. Make salience work for users: pin the app to the home screen, use clear, respectful notifications, and show small wins (e.g., “You logged three evenings this week”).

Build for mood variability. When energy is low, provide ultra-light options: a quick emoji, a yes/no sleep check, a single breathing exercise. In higher-energy states, let users set flexible goals or explore deeper content without punishing them later with streak losses. Consider integrating clinician dashboards or printable summaries so app use feels tied to real conversations, not a private chore.

For individuals and families, start small and make it visible. Pair a daily check-in with something you already do—after brushing teeth or before starting the car. Place PolarUs on the first home screen. Turn off non-essential notifications that routinely steal your attention. When you notice warning signs—sleep shifts, rising stress—set a short-term goal, like logging for the next three days, and tell a supporter so there’s gentle accountability.

Health systems and employers can help by normalizing digital self-management in care plans. Offer brief coaching on setting cues, choosing realistic goals, and preparing a “mood shift plan” for periods when engagement will dip. Remember, the question is not “Will people use the app?” but “How can we make using it the easiest next step in the moments that matter?” Insights from this research paper make that path clearer.

The Takeaway: Engagement Is a Moving Target, Not a Trait

The core insight from What influences engagement with a bipolar disorder self-management app? A qualitative investigation of use of the PolarUs app is both simple and profound: people engage when they’re motivated, reminded, and unhindered—and those levers shift with mood and context. Design choices that lower effort and raise salience, paired with routines that fit real lives, can turn a promising app into a steady ally. The question for all of us—developers, clinicians, and users alike—is not how to create perfect motivation, but how to make the help easiest to reach when motivation is fragile. If we build for fluctuation, not perfection, how many more people will keep the tools that help them within one easy tap?

Data in this article is provided by PLOS.

Tagged Apps, Behavior, Bipolar disorder, Cell phones, Cognitive psychology, Cognitive science, Communication equipment, Computer software, Depression, Educational status, Equipment, Mental health and psychiatry, Mood disorders, Motivation, Neuroscience, Population groupings, Qualitative studies, Research design, Software engineering, Undergraduates