Optimize Your Health Tech: 6 Cognitive Concepts for Powerful Product Design

In digital health, we're constantly seeking to improve user engagement and drive meaningful behavior change. Despite the allure of high user retention metrics, it's important to remember that our goal is to facilitate positive health outcomes, not to create app addiction. The line between engagement and compulsion is often blurry, and digital health companies have a responsibility to cruise this territory carefully.

Every interaction with an application – each click, swipe, and keystroke – begins with a journey of neural information. Our brains control how we perceive, process, and engage with our devices. By drawing on insights from psychology and neuroscience relevant to user interaction and decision-making, we can create digital health solutions that are effective and ethical, helping us design products that support genuine behavior change.

1. Neural Variability: Adapt designs to accommodate diverse user behaviors

Certain features of brain processing are generally conserved across individuals, which allows us to make some broad assumptions about user behavior and cognitive processing, but our brains are still unique. The brain drives behavior, and neural variability results in a high degree of behavioral variation both within and between subjects. Thus, properly identifying and controlling for the sources of variability can promote adoption across a larger population and enhance utility at the individual level.

Neural variability can be classified into:

• Between-subject variability refers to factors that influence different people in different ways. This means that what motivates one user might frustrate another, and what seems intuitive to one might be confusing to another.
• Within-subject variability refers to factors that differentially influence the same person at certain times. This means that the same user may interact with your app differently depending on their levels of tiredness, stress, hunger, and physical activity.

An appreciation of neural variability is crucial for creating more inclusive and effective digital health products. By designing flexible products for diverse cognitive profiles, designers can accommodate varying attention spans, memory capacities, and processing speeds of users. Allowing users to customize text size, color schemes, or information density can significantly improve usability. As such, neural variability is not something that should be feared in app design, but instead leveraged where possible to promote better health outcomes for a diverse user base.

2. Attention Mechanisms: Optimize information presentation for user focus

Attention can dictate what information users process and how well they retain it. Though this is typically considered an oversimplification, attention can be driven via both top-down and bottom-up mechanisms.

Attention mechanisms can be divided into:

• In bottom-up attention: our sensory systems guide our focus subconsciously. Contrasting colors, fast-moving objects, and sudden noises are examples of this. Regions such as our primary sensory cortices, thalamus, and superior colliculus guide our attention (and often our behavior) before we consciously realize it. Visual hierarchies, color contrasts, and app tutorials that use moving visual components can help drive bottom-up attention to promote initial engagement.
• Top-down attention: refers to a more goal-directed control of our focus. This occurs when we are carefully reading a document, listening to a conversation, or searching for a lost item. This form of attention relies on activity across networks including the fronto-parietal network, the default mode network, and the salience network, allowing us to tune out distractions and focus on a task at hand. Top-down attention can be engaged by instantiating both short-term and long-term goals for users.

3. Cognitive Load: Balance complexity to enhance user comprehension

Cognitive load refers to the amount of mental effort required to process information and perform tasks. It's a critical concept in digital health product design, as it directly impacts user experience, information retention, and the likelihood of users following through with health-related tasks.

Cognitive load theory distinguishes between three types:

• Intrinsic: effort that is inherent to the task
• Extraneous: unnecessary cognitive effort due to poor design
• Germane: effort that contributes to learning

In the brain, cognitive load is primarily managed by the prefrontal cortex and parietal lobe, which are also key components of the working memory system.

Managing cognitive load is crucial while developing digital health solutions, particularly for effective information delivery and user engagement. Too little cognitive load may result in an app that fails to effectively convey important health information or motivate behavior change. On the other hand, excessive cognitive demands can lead to mental fatigue, reduced comprehension, and decreased user satisfaction.

Importantly, cognitive load is not always detrimental. Some level of cognitive engagement is necessary for learning and behavior change, and peak performance is usually associated with moderate levels of arousal (see Yerkes-Dodson Law and McEwen’s allostatic load model). The key is to find the right level of arousal or cognitive engagement. Proper management of cognitive load can enhance learning, decision-making, and adherence to health recommendations.

Digital health product strategists, developers, and designers can minimize extraneous cognitive load through clear, intuitive interfaces and by breaking complex tasks into manageable steps. Techniques like progressive disclosure, where information is revealed gradually, can help manage intrinsic load. Germane load can be optimized by providing relevant examples, analogies, or visualizations that aid in understanding health concepts. By carefully considering cognitive load in product design, developers can improve not only the immediate user experience but also enhance the long-term impact of the product on users' health behaviors and outcomes.

4. Habit Formation: Implement strategies to foster sustained user engagement

Habits are automatic behaviors triggered by specific cues in our environment, formed through repetition and reinforcement. In the brain, habit formation primarily involves the basal ganglia, particularly the striatum, which works in concert with the dopamine system. This neural circuitry allows for the gradual shift from goal-directed actions to automatic behaviors, a process known as chunking.

For digital health UX/UI designers and developers, leveraging habit formation principles can enhance app effectiveness. For instance, apps can use push notifications as cues to prompt desired behaviors, while in-app rewards or progress tracking can provide extra reinforcement for habit consolidation.

The principles of habit formation can be conceptualized under the following framework:

• Initiation: A behavior is first performed in response to a specific stimulus or context.
• Repetition: The behavior is consistently repeated in the same context, often driven by rewards or valuable outcomes.
• Association: The link between the stimulus/context and the response strengthens, reducing reliance on conscious decision-making.
• Automaticity: The behavior becomes an automatic reaction to the stimulus, requiring minimal cognitive effort.

Obviously, extensive targeting of habit formation in digital products comes with potential problems. Over-reliance on extrinsic rewards can lead to decreased intrinsic motivation for users, potentially undermining long-term behavior change. Additionally, habit-forming features can contribute to app addiction or compulsive checking behaviors. To mitigate these risks, developers should focus on creating habits that genuinely contribute to users' health goals and provide users with control over their app interactions. Through this balance, digital health applications can drive positive health outcomes while respecting user autonomy and well-being.

💡How dopamine really works: Understanding the complex nature of dopamine signaling has important implications for digital health product design. Contrary to popular belief, dopamine doesn’t simply signal the consumption of reward. Instead, dopamine is involved in predicting rewards (as well as aversive events). In cued reward learning paradigms, dopamine release initially occurs during reward presentation, but as learning progresses, the dopamine release shifts to the predictive cue. When a reward is fully predictable, dopamine release occurs only during the cue and not during the reward. For digital health applications, this means that while immediate rewards can drive initial engagement, the real power lies in creating reliable associations between app interactions and anticipated positive outcomes. However, it's crucial to maintain the integrity of these predictive relationships to avoid disappointing users and potentially disrupting their motivation.

5. Emotional Processing: Leverage affective responses to boost user retention

Emotional processing is another important construct that can impact user motivation, decision-making, and overall experience. Emotions are complex psychological and physiological states that color our perceptions and guide our actions. In the brain, emotional processing involves the amygdala, insula, and ventromedial prefrontal cortex. Many regions involved in emotional regulation are also involved in memory, highlighting why memories are often linked to strong emotions.

Understanding and leveraging emotional processing can significantly enhance digital health products and app effectiveness. Positive emotions can increase user engagement, improve information retention, and boost motivation for health behavior change. Strategies that evoke positive emotions, such as personalized encouraging messages, celebration of milestones, or social sharing features, can activate the brain's reward circuitry and reinforce continued usage and adherence. This PNAS study found that self-affirmation exercises prior to viewing health messages increased activity in the prefrontal cortex and led to greater behavior change.

6. Disengagement and Self-regulation: Design features that promote healthy app usage patterns

Eventually, users decide to put their phone down or close the app. This is where behavioral regulation and disengagement come into play. Understanding how these "braking" systems work can help developers and designers create apps that respect our brains’ natural cycles of engagement and disengagement and provide natural stopping points that align with users' cognitive rhythms.

Disengagement can occur either gradually or rapidly:

• In gradual disengagement, our minds wander to other thoughts or plans. Gradual disengagement is characterized by heightened activity of our default mode network (DMN). In rapid disengagement, our interaction with the application is quickly suppressed. Rapid disengagement is driven by a process called response inhibition. This lets us quickly stop an ongoing action, such as scrolling through a feed and is controlled by the right inferior frontal gyrus, which allows us to switch gears and move to another activity.

Concluding remarks

In conclusion, there is enormous potential to develop more efficient, interesting, and customized health interventions at the nexus of neuroscience and digital health product design.

Utilizing our understanding of how the brain processes information, forms memories, and responds to emotional stimuli, we can develop apps that not only capture users' attention but also drive meaningful behavior change.

As digital health continues to evolve, it's imperative that product owners, designers, developers, health professionals, and researchers collaborate to apply these neuroscientific insights. By doing so, we can create tools that not only inform but truly transform health behaviors, improving health outcomes across all walks of life. The future of digital health lies in brain-aware design – let's embrace this knowledge to build smarter, more impactful health applications.