Redesign Health Apps Around How People Actually Think and Act

The Decision Lab is a behavioral science firm that helps digital health organizations redesign health apps around user psychology. We identify the behavioral barriers that cause people to disengage, then redesign onboarding, goal setting, habit loops, navigation, and care pathways to improve patient engagement, retention, adherence, and health outcomes. Our work includes the Government of Canada-funded PocketWell app, MyHeart Counts Canada, Kids Help Phone, and a health app used by 60 million people.

A 2019 study in the Journal of Medical Internet Research tracked 93 mental health apps. About 7 in 10 users who opened an app on the day they installed it came back the next day, but a median of only about 1 in 30 were still opening it 30 days later.

Our teams combine behavioral science, user research, experimentation, and service design to find and fix the moments where users drop off.

User psychology is the set of mental and emotional factors that shape what someone does inside an app. It covers motivation, attention, cognitive load (how much mental effort a screen demands), emotional response, identity, stigma, self-efficacy (a person's confidence that they can succeed), habit formation, and the context in which each decision is made. Health apps are especially exposed to it, because people often open them while anxious or unwell.

People abandon health apps for reasons that have little to do with features. Guilt, overload, stigma, and unrealistic goals do more damage than missing functionality, and none of them show up in a feature roadmap.

Our digital health product design work targets those causes directly. We change live product experiences: onboarding screens, goal-setting flows, trackers, navigation, and the copy that holds them together. Behavior change and patient engagement are the outcomes we design for, and healthcare user journeys are the unit we redesign, from first download to the point where someone needs more support than an app can give.

• Onboarding and goal-setting. The first minutes in an app set expectations that shape whether people stay. For MyHeart Counts Canada, we redesigned goal-setting so users started from realistic targets.
• Habit-forming features. Trackers and check-ins only help if people return to them. In PocketWell, we designed the Mood Meter around the science of habit formation.
• Navigation and access to care. People in distress have less capacity to search, and a platform full of resources can overwhelm them. We redesigned the Kids Help Phone and Wellness Together Canada platforms to make support easier to find.
• The handoff from digital to in-person care. For UC Berkeley, we worked on a mental health portal meant to make it easier for students to move from online support to face-to-face treatment.
• New health features, validated before they are built. For a global consumer electronics company, every target behavior for a new mindfulness service was tested before production code was written, according to the published case study.
• Copy, choice architecture, and friction. Small wording and layout decisions change what people do next, so we treat them as behavioral design decisions.

A behavioral science firm adds the most when the problem is how people behave inside the app. Common signs include:

• Users download the app but do not return after the first week.
• Patients set goals they cannot sustain.
• Users struggle to find support or their next step.
• Engagement metrics show where people drop off but not why.
• The team needs to validate behavior-change assumptions before development.

The Decision Lab works with digital health teams when product engagement depends on changing how users behave.

• Behavioral diagnosis through user research. Interviews and usage analytics tell us why people stop, before we propose anything.
• Anchoring and goal-setting. Asking people about their current behavior before they set a goal keeps goals within reach.
• Habit formation. Features are designed to attach to routines people already have.
• Choice architecture and reducing overload. Fewer, clearer options help people who arrive stressed or unsure what they need.
• Designing for autonomy. Users keep control over the kind and level of support they choose.
• Behavior change techniques. We map specific barriers and enablers to evidence-based techniques, as we did for more than 30 recommendations in our work with Health Canada.
• Addressing stigma around help-seeking. Our work with the Indiana National Guard examined the culture of silence that keeps at-risk people from seeking treatment.
• Simulation-first validation and experimentation. Design decisions are tested in dry-run simulations and experiments before development begins.

1. Diagnose the behavioral barriers in the current app and patient journey.
2. Identify the moments where a redesign would change the most behavior.
3. Prototype new flows and messaging for those moments.
4. Test with users and measure behavioral outcomes, not stated intentions.
5. Scale the changes that improve engagement or care outcomes.

Each case below follows the same structure: the behavioral barrier, the redesign, the outcome, and how that outcome was measured or supported. Outcomes come from each project's own measurement as reported in the published case studies, and we label intended outcomes where no result has been published.

A mindfulness service for a health app used by 60 million people

Behavioral barrier: the client's digital health team, at a global consumer electronics company, designed consumer health features on intuition and only learned whether they changed behavior after launch, when changing course is expensive.

Redesign: we built a repeatable behavioral design process and ran it on a new mindfulness service, six self-guided tools designed to integrate with the wider health app and its wearable devices. We coached the team through the method using dry-run simulations of real design decisions, and the published case study reports that every target behavior was tested before production code was written.

Outcome: design time fell by three-quarters compared with the team's previous process, even though the new process added research steps. In the project team's before-and-after self-assessment, confidence in design decisions doubled. The service moved into the product roadmap for launch alongside the client's next generation of wearables.

Evidence: project measurement reported in the published case study, with confidence measured by pre- and post-engagement self-report.

Onboarding that avoids the guilt spiral: MyHeart Counts Canada

Behavioral barrier: in MyHeart Counts Canada, a fitness app, unrealistic activity goals set during onboarding triggered guilt, and guilt led users to avoid the app and eventually uninstall it.

Redesign: users report their current activity level right before choosing a goal. The anchoring effect keeps the new target close enough to existing habits to be achievable, while still pushing people.

Intended outcome: more attainable goals, less avoidance, and longer engagement. No outcome figures have been published.

Evidence: our user research identified the pattern from guilt to avoidance to uninstall.

Making reflection a habit: PocketWell

Behavioral barrier: reflection and mood-tracking tools only help if people come back to them regularly, and a one-off check-in does little for emotional self-awareness.

Redesign: for PocketWell, a Government of Canada-funded companion app to Wellness Together Canada, we led research and product design. Its Mood Meter uses the science of habit formation to help users log their moods, reflect on what is behind them, and revisit past entries.

Intended outcome: regular reflection that builds emotional self-awareness. The published case study does not report app-level engagement figures. The wider Wellness Together Canada platform has been accessed more than 3.5 million times since launch, a platform figure rather than a result of the app redesign.

Evidence: large-scale user testing from discovery through to the app's launch, which Health Canada announced in January 2022.

Youth mental health access: Kids Help Phone

Behavioral barrier: young people in distress had to find the right level of support among a very large amount of information, across an audience ranging from elementary school-aged kids to young adults.

Redesign: Kids Help Phone asked us to rethink how youth access mental health support through its website, and we led the redesign from inception to launch.

Intended outcome: faster access to the right kind and level of support for each young person. No outcome figures have been published.

Evidence: research with hundreds of youth across Canada, interviews with staff across the organization, analysis of web analytics, and an audit of the existing site.

In the same JMIR study, app opens fell by more than four-fifths between the first and tenth day after install. A feature that only pays off after a month of use is built for people most of these apps had already lost.

Can a behavioral science firm help redesign an existing health app?

Yes. A behavioral science firm can diagnose why users disengage from an existing app, find the moments in the user journey where a change would matter most, prototype behavioral interventions, and test whether the redesign improves engagement, adherence, or access to care. The Decision Lab has used this approach with health apps and public mental health platforms.

Can behavioral science improve a health app?

Yes. Most health apps lose users within days, and the reasons are usually psychological: guilt, overload, stigma, unclear next steps. In the 2019 study of 93 mental health apps, tracker and peer-support apps kept more users at 30 days than breathing-exercise apps. That suggests design choices, not just the condition an app targets, shape how long people stay.

How do you redesign a health app to improve patient engagement?

Start by finding out why people stop, through interviews and usage data, before changing features. Then redesign the specific moments where people drop off. For MyHeart Counts Canada, that moment was goal-setting during onboarding, where unrealistic goals led to guilt and uninstalls.

What behavioral science methods improve medication adherence?

Adherence is often a habit problem more than a knowledge problem. Two methods that apply directly are tying each dose to a routine the person already has, and cutting the steps between a reminder and the action itself. Whichever methods you use, test them against a comparison group, because stated intentions to adhere rarely predict behavior.

How can digital health companies increase app retention?

Focus on the first week. In the 2019 study of mental health apps, app opens fell by more than four-fifths between the first and tenth day after install, so onboarding and the first habit loop matter more than later features. Achievable goals and check-ins tied to existing routines both target that early window.

What is behavioral design in healthcare?

Behavioral design in healthcare applies research on how people make decisions to the design of health products and services. At The Decision Lab, it means diagnosing why patients or users do not take a recommended action, then redesigning the experience around those barriers and testing whether behavior changes.

How do you test whether a health-app redesign changes behavior?

Measure what people do, not what they say they will do, and compare against a group that did not get the change. Testing can also start before launch: for a health app with 60 million users, the target behaviors were validated through simulations and experiments before development began.