Gamification and Patient Adherence: Designing Health Apps Patients Can Sustain

Wanting to be healthy and wanting to log your food, track your hydration, or record symptoms every day are two different things. Patients can value their treatment while still finding the daily busywork of managing it tedious. A health app that assumes patients are already motivated to complete its task list is solving the wrong problem.

Points don’t fix this. They reward completion, but once the novelty fades, patients are left with the same unrewarding task and one less reason to bother. A sturdier approach gives patients different ways to engage: making sense of their symptom history, building a manageable routine, prepping for a consultation, or learning from other patients. People need room to choose their own approach, within whatever boundaries the care programme requires.

Find the barrier before picking an incentive

The World Health Organization’s 2003 report on adherence to long-term therapies put average adherence among people with chronic diseases in developed countries at roughly 50 percent — and pinned part of the responsibility on providers and health systems, not just patients.

Forgetting and being unable to act are not the same problem. The Fogg Behavior Model holds that behavior only happens when motivation, ability, and a prompt line up together. A reminder helps someone who forgot but is otherwise willing and able. It does nothing for a patient who can’t afford a refill, doesn’t understand the instructions, or is dealing with side effects that need medical attention.

More importantly, the Fogg Behavior Model assumes that motivation is a given, which of course is not the case. Even if people are motivated to get healthy or take their medication, it doesn’t mean that motivation will last.

The model assumes that habits will naturally flow from making the ability to do the action very high and creating good triggers, but that is not enough by itself. There are many health apps that have an abundance of triggers and have even incorporated some habit formation theory, but they still cannot solve the main user engagement problem.

Why a Duolingo-style streak does not work

Picture a Duolingo user who genuinely enjoys picking up new vocabulary. A streak gives that person an extra reason to keep coming back to something they already find interesting. Pairing the same mechanic with a food log the patient experiences as pure chore is a different bet entirely.

Yu-kai Chou’s Octalysis Framework breaks motivation into eight Core Drives, and the useful question is always: what’s actually prompting the action? A streak counter might push someone toward a milestone (Development & Accomplishment) or simply make them afraid to lose what they’ve built (Loss & Avoidance). Often it’s doing both at once.

Loss & Avoidance sits in Octalysis’s Black Hat category, alongside Scarcity & Impatience and Unpredictability & Curiosity. Black Hat doesn’t mean “not intrinsic” curiosity, for instance, can be genuinely enjoyable on its own. Back to Duolingo: streaks and rewards can layer on top of real interest, but they can’t manufacture that interest, and they’re no substitute for actual practice.

A learner can protect a streak for months by replaying easy exercises without ever advancing. So a streak proves engagement, not proficiency: it can’t tell you whether someone is closer to fluency, let alone “PhD-level” language skill. That’s a limit on what the metric shows, not a knock on the app. The same mistake shows up in health apps when repeated check-ins get treated as proof of better self-management or better outcomes.

Give patients real choices and progress they can read

For Development & Accomplishment, reward progress patients can actually make sense of: finishing an educational module, prepping questions for an appointment, hitting a rehab milestone their clinician agreed to. Label things honestly: a badge for opening the app measures attendance, not adherence. And don’t hand out “success” badges purely for good lab results, since those often depend on factors outside a patient’s control.

For Empowerment of Creativity & Feedback, give patients meaningful choices and strategies that matter to them and that fit their motivational make up.  Let them pick when to log symptoms, show them when they actually did it, and let them adjust the schedule. That loop — choose, see the result, adjust — is what makes this Core Drive work. Picking an app color doesn’t count, as this doesn’t give any feedback on your chosen strategy and therefore has nothing to do with your intrinsic motivation to master a skill..

Match the support to the obstacle and the person. Someone new to a routine may need step-by-step guidance; a longtime patient may just want fast entry and a clear summary. Offer peer support to patients who want it, and don’t force it on those who don’t. Make these options changeable, then check whether they’re actually reducing friction around the behavior that matters.

Match the mechanic to the stage patients are in

The same motivation-first thinking should carry across every phase of the Octalysis journey. In Discovery, be clear about which problem the programme solves. In Onboarding, help the patient pick a goal and a support style that fits them. A good first session shows the patient a use for what they’ve entered, like generating questions for their next appointment, rather than just teaching them to check boxes.

In Scaffolding, use feedback to help patients adjust their routines and get back on track after a lapse. In Endgame, give experienced patients quick access to their history and let their support needs shift, instead of recycling beginner content. Periodically ask what still needs daily attention,  if a routine has become second nature, fewer check-ins may be fine, as long as you can still tell whether the underlying behavior is holding up.

Not every personal health goal is Epic Meaning & Calling. That drive is about purpose beyond yourself, not a private routine. Helping a newcomer through an optional peer contribution might qualify; hitting your own step count is closer to Development & Accomplishment. Ask what actually makes the activity feel worthwhile before you file it under a Core Drive.

For Social Influence & Relatedness, pick a specific social function,  practical advice, recognition, mentorship, rather than social features for their own sake. Don’t rank patients against each other when their clinical situations differ. Offer private or read-only participation where it makes sense, moderate medical claims carefully, and keep patient experience clearly separate from clinical guidance before you start rewarding people for posting more.

What the Pfizer Sidekick case actually shows

The Octalysis Group’s Pfizer patient adherence and habit formation case study covers its work on Sidekick, an app for people living with ulcerative colitis and Crohn’s disease. The app touches sleep, nutrition, emotional wellbeing, accessible education, customizable goals, and peer support: a good illustration of the differentiated approach: patients can engage through goal-setting, learning, or connecting with others, on top of medication support.

The case study ties patient-set goals to Empowerment of Creativity & Feedback and peer/mentor connections to Social Influence & Relatedness. It also uses Unpredictability & Curiosity through rotating tips and stories. If you’re borrowing that mechanic, vary the optional content while keeping the actual treatment instructions stable and easy to find.

The published numbers: a 30 percent drop in dropouts, triple the goal achievement rate, and 68 percent of users still daily active at six months.

Measure the actual behavior, and the cost to patients

The Pfizer numbers need the same scrutiny as the Duolingo comparison. Dropout, goal achievement, and daily activity are three different measurements.Nail down each one’s denominator, comparison point, and time window before treating it as a target. For medication specifically, pick an adherence measure with clinical input. A refill shows access to medication; a self-report shows what a patient says they did. Neither confirms the dose was actually taken.

Test whether a differentiated approach actually helps. Try comparing a patient-chosen logging schedule against the default one, and track usable records, recovery after gaps, and reported burden. Set your observation window and success criteria before you look at results, and use a comparison group where you can more usage alone doesn’t mean self-management improved.

Watch for distorted data when rewards hinge on completion. Ask patients directly whether they logged something to keep a streak, earn a reward, or avoid feeling like they failed. Look for changes in missing-data patterns or suspiciously uniform entries. If completion goes up but the data gets less trustworthy, that’s a reason to rework the incentive even if you hit your engagement numbers.

Measure burden directly: patient feedback, how long tasks take, requests to dial back reminders. Break these results out by patient group, so a strong average doesn’t hide a flow that’s genuinely hard for people who are fatigued, less digitally confident, or need accessibility support. Clinical outcomes need their own measurement and study design engagement metrics can’t stand in for them.

When reviewing a product through this lens, write down what motivation each task assumes, what alternatives patients actually have, and what evidence would justify keeping each mechanic.

Sounds really complicated? Don’t worry, it is. The Octalysis Group has spent the last 14 years perfecting the art of optimizing design for human motivation. Contact us and we can explore together how the group can help you and your company create truly long-term engagement for your patients and well-being users.