• Well-being apps play an important role in supporting mental health and behavior change, but many of these apps struggle to maintain long-term user engagement and cultivate sustainable habits.
• Focusing on the psychology of habit formation can help well-being apps maintain user engagement by creating experiences that feel naturally rewarding and self-sustaining.
• Personalizing app experiences to individuals—rather than overwhelming users with generic options—ensures interventions better align with users’ evolving needs and intrinsic motivations.
• Well-being apps should encourage reflective goal-setting, promote emotional regulation, and support setbacks to avoid setting unrealistic expectations and creating disappointment.

Well-being apps promise to make us happier, less stressed, more productive, and overall better at handling our crazy lives. Their growing presence in the market has led to a surge in popularity, with over 56 million worldwide users generating $950 million in revenue in 2023 alone.² As demand for in-person therapy outpaces the capacity of conventional treatments, more and more people are turning to wellness apps to fill the gap. Popular apps like Headspace, Calm, BetterMe, Fabulous, and BetterSleep offer users an affordable, accessible alternative to traditional mental health care—and even with monthly subscription fees, they often cost significantly less than one-on-one therapy. Plus, research suggests they have serious potential to improve well-being and help users manage conditions like depression and anxiety.⁴ 

While growth has slowed slightly after a spike in app installs during COVID-19—driven by elevated anxiety and restricted access to conventional mental health support—global usage remains strong. The market is projected to continue expanding, particularly in the Asia Pacific region, where growing awareness around mental and physical well-being is driving demand for convenient and accessible wellness solutions.² 

Despite their widespread popularity, well-being apps struggle with user retention, with the vast majority abandoning apps within a few weeks time.¹  The unfortunate reality is that while many mental health platforms are fun to use and engaging at first, they often fail to address real problems that prevent users from forming sustainable habits.⁴ A lack of motivation, loss of interest, and the ongoing search for more suitable tools are key drivers of app abandonment.³  

This begs the question: how can app designers harness the momentum of initial downloads to keep users engaged long enough to create meaningful, lasting change? The key lies in understanding the behavioral patterns that stand in the way of habit formation. By addressing the cognitive biases that influence user behavior and applying proven behavior change strategies to drive engagement, well-being apps can become even more effective at supporting mental and physical wellness. Throughout this article, we’ll explore the key success barriers facing well-being apps and explain how insights from behavioral science can lead to better user outcomes.

High customer churn is a problem for users and app companies alike, where short usage windows are not long enough to meaningfully impact mental health or change lifestyle habits. Many app designers try to combat this engagement problem by investing in usability improvements—but even the most well-designed apps struggle to keep users around. In fact, research suggests that providing a good user experience does not predict long-term app use.⁵ Why are users dropping these apps before they see results?

Bridging the Intention-Action Gap: Why Gamification Falls Short

Drop-offs in engagement can be in part explained by the intention-action gap, where users often intend to build better habits but struggle with follow-through. This gap exists because people are motivated by immediate rewards more than internal values, attitudes, or intentions. For instance, we may know that meditating consistently can help reduce stress over time, but sitting on the couch and watching TV is rewarding right now.

To supplement this lack of immediate gratification, app designers rely on gamification tactics like daily streaks, in-app rewards, and badges to reward users for performing target wellness behaviors. While these can be incredibly engaging at first, they rely on extrinsic motivation, a form of motivation driven by external rewards or punishments that can diminish over time. Intrinsic motivation, on the other hand, comes from internal incentives, such as genuine interest or enjoyment in the activity itself, and tends to be self-reinforcing.⁶ 

Self-determination theory suggests that intrinsic motivation makes our behaviors feel internally meaningful, giving us a greater sense of autonomy and competence when pursuing our goals. These feelings are crucial for sustaining long-term motivation. Meanwhile, when people rely solely on external incentives, they tend to give up on their habits once these incentives start to feel arbitrary and meaningless. For example, someone might initially feel motivated to use a wellness app daily so they can earn points or badges, but this motivation comes from a desire to maintain a streak rather than an intrinsic motivation to actually meditate to practice deep breathing. As a result, they end up quitting when in-app rewards lose their novelty because they have not developed an inherent desire to perform the activity itself. 

Bridging the gap between intention and action involves helping app users form connections between their extrinsic and intrinsic motivations over time. The real challenge is keeping app users engaged long enough that their target behaviors become intrinsically motivating. Fortunately, insights from behavioral science suggest that habit formation strategies—such as habit loops and variable reinforcement—can be highly effective at encouraging long-term behavior change. Let’s explore what these strategies look like and how they can drive lasting engagement in well-being apps.

Designing well-being apps from a behavioral standpoint can help users develop habits that are automatic and intrinsically motivated, removing the requirement that users exert willpower to overcome immediate gratification. The idea is to structure app features as habit-formation tools rather than engagement tricks. One of the most effective frameworks for this is Nir Eyal’s hook model, a product development framework used to create engaging products that keep users hooked.⁷ It involves moving users through a cycle of four phases:

1. Trigger: A prompt that drives the user to take an action.
2. Action: A target behavior prompted by the trigger.
3. Reward: An unpredictable incentive offered to the user as a result of performing the behavior.
4. Investment: The time and effort the user puts into the product, increasing their commitment.

How does the hook model work from a behavioral standpoint? First, triggers are intentionally designed so that the user begins to associate them with certain internal cues, such as feelings of stress or anxiety. For example, a trigger could be a push notification that says, “Feeling overwhelmed? It’s time for some deep breathing.” Over time, users begin to subconsciously connect these triggers with how they’re feeling, and eventually, their internal cues alone prompt engagement with the app.

Next, actions are intended to be as simple as possible for the user to perform—especially at the beginning when they are just becoming acquainted with both the action and the interface. This characteristic of the action phase is inspired by the Fogg behavior model, which posits that a behavior can only occur when a person is motivated to perform an action and has the ability to perform it. Reducing the number of steps needed to perform the target behavior increases the likelihood that someone will do it—think one-question check-ins or guided meditation sessions that start as soon as someone taps the notification prompt. Implementing immediate, low-effort actions that give users a quick sense of progress can also help them overcome the intention-action gap. For instance, Duolingo encourages new users to try a five-minute lesson right away, closing the distance between the user’s intention to learn a language and the act of actually practicing. 

The reward phase is one of the most powerful components of the hook model. The key here is variable reinforcement, or switching up the reward to keep it unpredictable and exciting. This is precisely what makes slot machines so addictive—when wins are delivered at variable intervals, players stay hooked on the possibility of a big payout. When thoughtfully applied to well-being apps, this strategy could be used to reinforce positive behaviors like participating in CBT exercises or gratitude journaling. In this case, variable reinforcement could take the form of unexpected badges, surprise challenges, new features, or even exclusive mental health content. Social rewards tend to be particularly rewarding because they tap into our innate need for connection.⁸ For example, Strava, the social cycling app, encourages users to share their routes publicly or compare their times against other users after completing a ride.

Finally, investments serve as a self-reinforcing mechanism that keeps the habit loop going by delivering more value with every use of the app. In other words, putting effort into logging behavior or customizing goals should directly return an increase in value to the user. They should feel that their personal investments in the app have made it a better product for them, just as shopping on Amazon leads to increasingly tailored product recommendations over time. In a well-being app, this might mean offering more personalized exercises or targeted coping strategies as the user logs their daily moods or sleep habits. The idea is to have the user’s interactions shape their future experiences so that the more they contribute, the more they feel like the app was designed specifically for them. All of these phases work to replace external motivations with internal habit loops, keeping users engaged until they see real benefits.

Another challenge with well-being app design is creating solutions that adequately meet the needs of a wide range of diverse users. Although some apps strive for personalization, they tend to make assumptions about what users want; for example, those downloading a CBT app must be ready to dive into a CBT exercise and people downloading a sleep tracking app must be ready to monitor their sleep. But designing apps with these assumptions means they often don’t align with the specific needs of individual users. Let’s look a little closer at why these generic approaches often fall short.

Well-Being Apps Overlook Stages of Change

One reason why there’s so often a disconnect between users’ needs and app-based wellness interventions is that apps rarely assess people’s readiness to change. Behavioral science tells us that change is a gradual process, but well-being apps often assume that everyone is ready to take action the moment they sign up. The transtheoretical model (TTM) is one way to explore the basic stages of change people go through when preparing to commit to new habits: pre-contemplation, contemplation, preparation, action, and maintenance. Apps with rigid structures tend to start everyone in the action stage, assuming that users are ready to commit to new habits. But what about people who are in earlier stages and not quite ready to make a move?

Without considering whether users are ready to change, apps risk pushing users into habits before they are ready, increasing the chance that they’ll abandon the intervention altogether. One study found that a TTM-based health app significantly improved health outcomes for patients over those who only received routine care, suggesting that matching interventions to people’s stage of change is beneficial for encouraging lifestyle modification.⁹ Similarly, incorporating the TTM into well-being apps could be a great way to serve the diverse needs of users better.

One-Size-Fits-All Apps Overwhelm Users

Many well-being apps attempt to cater to diverse user needs with an overwhelming number of features, complex tracking systems, or data-heavy reports. However, users often report that one-size-fits-all well-being apps have too many things going on, causing confusion and overwhelm.³ While these tools are designed to provide value, they often end up contributing to information overload, a common issue in today’s digital world. This sense of digital overwhelm has become a pressing problem all over the world—in one German survey, for example, 22% of respondents said that information overload was their most frequent stressor.¹⁰ Instead of simplifying and supporting people’s wellness journeys, content-rich apps can place additional strain on people’s already-stressed cognitive resources. 

Apps that provide users with a lot of information—without offering clear, actionable guidance—can leave users feeling stuck rather than supported. Take sleep-tracking apps, for example. Many of these apps give users detailed sleep reports but fail to offer recommendations beyond “Try to get more sleep” or “Go to bed earlier tomorrow.” To truly engage users and drive behavior change, well-being apps need to go beyond blanket approaches with actionable, personalized insights that help users tackle their unique challenges.

For well-being apps to be effective at helping users with a wide range of goals, they have to be dynamic, adapting to users' changing needs in real-time. For example, giving users a brief onboarding survey when they first launch the app could be a great way to assess someone’s readiness to change before recommending a starting point, ensuring the app meets users where they are. The Calm app gets this right, asking new users what prompted them to try the app and whether they’re simply curious about mindfulness or ready to start building daily habits. 

When doing this, it’s important to pre-select a starting point for users rather than presenting them with a generic “most popular” option. Why? People tend to go with the status quo when presented with pre-set options, even if other options are better for them. Selecting personalized defaults for each unique user can be very effective at ensuring app users start out with interventions that are most likely to resonate with them. For instance, if someone indicates in the onboarding survey of a CBT app that they are struggling with job-related burnout, the app might automatically suggest a thought-reframing exercise focused on workplace challenges. 

Motivational Matching to Align Messages with User Intentions

Motivational matching can be useful for personalizing the app experience throughout the user journey. This is a strategy that involves tailoring messages so they align with the intrinsic motivations, goals, needs, and values of the user.¹¹ Robust research shows that motivational matching is about twice as effective as other personalization methods, including the common practice of tailoring content based on demographics or user behavior.¹¹ Motivational matching works best when it is aligned with situational factors—such as the user’s current mood or immediate environment—and not just broad personality traits. This ensures messaging feels personally relevant and actually speaks to the internal motivations that drive individual users. 

Matching is also key to creating personalized nudges that align with users’ real-time needs. Instead of a generic nudge like “Don’t forget to meditate today,” motivational matching could be used to tailor nudges based on what actually drives the user. For example, if the user values social connection, it might say, “Take a moment to breathe with your community.” If the user is goal-oriented and short on time, it might say, “Take five minutes to clear your mind so you can get back at it.” This form of choice architecture reduces decision fatigue by presenting users with the right messaging at the right time instead of throwing everything at them all at once. 

Learning from User Behavior to Improve Engagement

Using machine learning, well-being apps can learn about the intrinsic motivations of users from activity logs and check-in surveys, but also by tracking how they interact with features over time. For example, if a user frequently follows guided meditations for stress relief but ignores meditations to improve productivity, it’s likely they are more motivated by emotion regulation than goal-setting. In this way, AI-driven personalization can be helpful for minimizing unnecessary decision-making steps while ensuring users receive highly relevant suggestions.¹²

Some well-being apps already do this really well. For example, Endel creates personalized sound environments that adapt to the user’s heart rate and local weather. Similarly, Headspace offers a “Today” tab with dynamic pre-selected content that changes based on the time of day and past usage habits. While still giving users the autonomy to select the tools that best suit their needs, these apps update dynamically based on user behavior to reduce information overload and minimize decision-making friction.

One final challenge with well-being apps is getting users excited about their goals without setting them up for disappointment. According to goal-setting theory, having individuals set specific and challenging goals can improve performance—but these goals must be achievable. Research on goal-setting indicates that failing to achieve unrealistic or overly ambitious goals can reduce motivation and may also cause individuals to disengage from challenging tasks.²² 

Unfortunately, even highly motivated users struggle to set realistic goals without structured guidance. The planning fallacy describes how we tend to underestimate the amount of time and work involved in completing a task, often believing we can make progress much faster than we really can. At the same time, the optimism bias can make us overestimate how easily we can achieve goals while underestimating the probability of facing setbacks along the way. Due to these biases, individuals often benefit from some guidance when it comes to goal-setting, but this is where many well-being apps fall short. At the same time, apps can also set unrealistic emotional expectations, causing users to overestimate the well-being outcomes they can realistically achieve. 

Apps Provide Few Opportunities for Reflection

While some well-being apps incorporate goal-setting features, research shows that many fail to provide structured opportunities for users to reflect on their goals—which is essential for ensuring goals are realistic, achievable, and aligned with people’s capabilities.¹³ When people are given free rein to create their own goals without any direction or chance at reflection, they risk creating goals that are too vague to be motivating or too difficult to achieve. When these goals inevitably fall short, users are likely to wind up discouraged, disappointed, and disengaged. Consider a mindfulness app that asks users to set a goal for the number of days they wish to meditate per week. Without prompting the user to reflect on their previous meditation habits or providing guidance on what an adequate number of days might actually look like, the user risks setting an ambitious goal that is incompatible with their current lifestyle—like committing to daily 30-minute meditation sessions when they’ve never meditated before.

Apps Often Prioritize Happiness as a Key Wellness Outcome

Similarly, well-being apps often cause users to have excessively high expectations about their personal happiness. Apps that focus on promoting happiness and productivity risk stigmatizing negative emotions, implying that they are undesirable or problematic. This approach can make people feel shame for feeling bad—even though negative feelings are completely normal and acceptable. Besides feeling bad for feeling bad, studies show that the relentless pursuit of happiness can lead to disappointment when our actual emotional state falls short.¹⁴ In fact, the more people pursue happiness, the less likely they are to experience feelings of happiness. This paradox highlights the problem of setting impossibly high emotional standards among app users. 

On top of this, apps that focus on happiness as a critical wellness metric sometimes fail to provide effective guidance on managing inevitable negative emotions. One large review of mental health apps found that very few specifically support emotional regulation, despite research showing that this is an important mechanism for apps intent on improving people’s well-being.¹⁵ This suggests that designing well-being apps that help people work their way through setbacks could be an excellent way to fill a key gap in the market.

Creating realistic expectations is important for ensuring people feel competent in their abilities to reach their well-being goals. According to self-determination theory, autonomy and competence are critical components of motivation, meaning that feeling in control of one’s behavior and feeling capable of achieving one’s goals is important for sustaining commitment. If users frequently find that they are crushing their goals and overcoming challenges, they’ll generate a greater sense of autonomy and competence throughout their habit-change journey—and apps will enjoy more sustained motivation as a result. To facilitate this, well-being apps should encourage reflective goal-setting and create contingency plans to help users weather setbacks. 

Encourage Users to Reflect on Their Goals

Research shows that people are more likely to set realistic goals when they take the time to envision their objectives alongside possible obstacles that might pop up along the way.¹³ As app users set their initial goals, messaging can encourage them to reflect on how long each goal will take and how difficult it will be to achieve. Even a brief period of reflection during goal-setting can help users overcome the planning fallacy with more realistic goals. At the same time, apps can prompt users to recall past successes and failures. When people have proof of what they can realistically accomplish, they’re more likely to feel competent setting goals that align with their abilities.¹⁶ 

Having users recount their usual behavior also capitalizes on the anchoring effect by helping them set goals that are more in line with their existing habits. This is a technique TDL employed in partnership with the McGill University Health Centre while designing the MyHeart Counts Canada (MHCC) app. The MHCC app was intended to help get Canadians moving, but to do this, the McGill team needed to understand the behavioral barriers facing their target audience. After robust user research and testing, TDL recommended several evidence-based solutions to reduce friction for app users. One of these solutions was employing the anchoring effect by asking users to self-report their current activity levels before setting activity goals. This works to subtly nudge users toward goals that are closer to their current activity “anchors,” setting them up for success and alleviating the feelings of guilt that come with setting overly ambitious goals and falling short.

During reflection, apps could also encourage users to limit the scope of their goals. Chunking goals into smaller components makes it much easier to work out exactly what you need to do next.¹⁷ Breaking goals down also creates small wins to produce a regular sense of accomplishment and build confidence. This can go a long way toward increasing the user’s sense of self-efficacy: the belief that one is able to accomplish specific tasks. Higher self-efficacy is linked to greater resilience and persistence in the face of challenges. One recent study in Western China found a significant connection between self-efficacy and resilience in the context of job burnout.¹⁸ By helping app users build self-efficacy, they’ll be better prepared to handle setbacks along their behavior change journey.

Build Emotional Resilience to Support Users Through Setbacks

Building resilience among app users is crucial for helping people make it through setbacks and maintain engagement so they can reach their long-term goals. Research suggests that many well-being apps don’t provide structured plans for people who fall short of their goals, and few offer support for users in times of crisis.¹⁹ While some well-being apps like Headspace provide access to mental health coaches or links to crisis resources, many fail to equip users with tools or techniques to navigate inevitable setbacks along their habit-change journey. Teaching emotional management during periods when users are experiencing stagnation or backsliding into unwanted habits could be a great opportunity to help discouraged users turn things around. At the same time, features like daily emotional check-ins or guided reflections can help users build emotional granularity—the ability to identify and describe one’s emotions. Research shows that interventions aimed at increasing people’s emotional knowledge significantly improve their ability to address their feelings.²⁰ 

In fact, building emotional self-awareness through reflection and mood tracking is a key feature of the PocketWell app, a collaborative project between TDL and some of Canada's leading mental health organizations. Based on evidence highlighting the important connection between emotional self-awareness and well-being, we helped design the app’s Mood Meter, a mood-tracking tool that encourages users to pause and reflect on their feelings. We worked closely with clinical psychologists in the design of the Mood Meter to ensure the available emotional options were comprehensive without being overwhelming. In the end, we recruited hundreds of participants to test the Mood Meter and ensure it was delivering real emotional benefits to users.

Caveats to Consider

Whether designing new well-being apps or updating existing ones, implementing the above solutions comes with a few important caveats. First, many of these app functionalities rely on machine learning to deliver personalized, targeted experiences, but this introduces ethical concerns around behavior tracking, data security, and user autonomy. Lack of respect for user privacy is a common concern among mental health app users, especially since well-being apps are not subject to healthcare privacy legislation.⁴ Balancing personalization with privacy through strict data protections—and making these privacy policies available to users—is crucial for building trust and ensuring users feel safe. Visible app features that prioritize data security can also help settle user concerns about privacy. For example, apps can require clear authentication processes like multi-factor authentication and biometric logins, provide regular prompts encouraging users to review and update their security settings, and limit requests for unnecessary permissions. 

Along these lines, ensuring the ethical use of behavioral science is also incredibly crucial. Building trust with users means avoiding misleading design techniques that trick users into making unintended decisions or tactics that keep people hooked for the sake of engagement rather than real user benefits. The main goal should be to help users build habits so they see real improvements in their mental, emotional, and physical well-being. 

This is one reason why tracking engagement alone is not a comprehensive measure of app success. While engagement metrics like session length provide useful insights, they don’t always reflect meaningful behavior change. By integrating well-being outcomes into performance tracking, companies can focus on driving both business success and real-world impact. Research into mental health app engagement suggests that tracking outcomes is also important for discovering optimal engagement patterns that result in real well-being improvements among users.²¹

Paving the Way for Impactful Well-Being Apps

Building well-being apps that drive real improvements in user wellness is no easy feat. Even the most popular, well-designed platforms on the market struggle to maintain long-term engagement and promote lasting behavior change in users. Apps can get closer to this ideal by fostering habit formation rather than solely delivering external rewards, personalizing experiences that align with users’ real-time needs, and establishing realistic expectations that normalize setbacks to reduce disappointment and frustration. Across these strategies, behavioral science principles related to habit formation, intrinsic motivation, and personalization are essential for making a lasting positive impact on app users. 

When well-being apps support long-term behavior change, they become truly valuable tools for mental health and overall wellness. Several studies suggest that mental health apps have tremendous clinical potential.⁴ As such, many therapists are already incorporating these apps into their practice, using them as a supplement to therapy and an unobtrusive avenue for mental health monitoring. Around 10% of telehealth psychologists (treating patients either partially or fully remotely) currently use digital mental health tools or apps alongside one-on-one therapy.²³ As our lives become increasingly digitized, it’s likely that well-being apps will be even more closely integrated into existing healthcare models.

These apps are uniquely positioned to help tackle the global mental health crisis by making support more accessible to people all over the world who might not have access otherwise. Recognizing this potential, many global organizations have introduced initiatives aimed at enhancing well-being apps and integrating these tools into existing healthcare systems. For example, the World Health Organization’s (WHO) Global Strategy on Digital Health aims to link cutting-edge innovations with digital health tools to support “equitable and universal access to quality health services,” engaging multiple stakeholders, from government officials to ethics committees. These global initiatives are paving the way for well-being apps to become more than just self-improvement tools but to be fully integrated into mainstream healthcare. Of course, for well-being apps to reach their full potential, they need to be genuinely effective at driving behavior change and fostering the development of lasting, transformative habits.

At The Decision Lab, we specialize in leveraging behavioral science to improve mental health and well-being through evidence-based digital interventions. By combining research with human-centered design, we help companies create apps that drive engagement, foster lasting behavior change, and produce measurable outcomes. Partner with us and leverage behavioral science to create impactful digital wellness solutions.

Thinking Outside the App

Creating good user experiences isn’t just about perfecting in-app functionality but involves considering the user journey that takes place in the real world. This article provides several examples of popular apps that effectively bridge the gap between digital and physical user journeys by addressing pain points in the users’  environment.

Designing a Cutting-Edge Health App to Get Canadians Moving

In this case study, TDL worked with McGill University Health Centre to launch a consumer-facing cardiovascular health app to get people moving. We share all the fascinating ways we leveraged behavioral science to uncover the motivations of different app users, address individual behavioral barriers, and drive engagement.

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