A ten-step guideline for ethical, evidence-based nudge design in health applications.
Nudge effectiveness is not a function of mechanism sophistication alone. It is the interaction between the mechanism, the user's cognitive state, and the timing of delivery. This guide operationalises that principle across Miro and Figma.
Rooted in PhD research done by Shahrzad Jafari, University of Tehran, Kish campus 2021-2026 and with three studies.
How the ten steps map to the Double Diamond
The Double Diamond model (Design Council, 2005) structures design as four phases. The ten steps of this framework map onto those phases (based on designer answers and usage in design process and familirity with the model), creating an experiential alignment between process and subject matter.
Click any step number to jump to its page.
The framework at a glance
Five sections (A–E) form the intellectual backbone. Each step operationalises one or more of them.
| Section | Purpose | Step(s) |
|---|---|---|
| A Behavioral State Diagnosis | Identify the user's cognitive state using the six-mode traffic-light system deck cards. | Steps 1,2, 3 |
| B Nudge Type Selection | Match the diagnosed barrier to Spark, Signal, or Facilitator and select from 23 mechanisms. | Steps 4, 5, 6 |
| C Intensity & Ethical Thresholds | Level 0/1/2 calibration and the five-question Ethics Audit. | Step 7 |
| D Dual-Process Targeting | Align the nudge with the user's System 1 / System 2 processing mode. | Steps 3, 4, 9 |
| E Health Domain Guidance | Domain-specific barrier profiles (hydration, posture, mindfulness, physical activity, sleep). | Steps 2, 9 |
Steps 1–5 and 7–10 run in Miro because diagnostic and evaluative work benefits from low-fidelity, group-level, asynchronous collaboration.
Product managers, researchers, clinicians, and ethics reviewers all contribute without needing design-tool fluency.
Figma is used only at Step 6, where cognitive strategy becomes concrete visual artefact. Gating Figma behind Step 5 prevents premature jumps to interface craft — the dominant failure pattern identified in Study 2.
How to use this guide.
Three things to know before you start: how the steps connect, what to prepare, and when to use the reference library.
Navigating the steps
Who does what
Every step has a recommended primary role, but collaboration is encouraged throughout. The lead designer should facilitate the full flow and own the ethics audit sign-off, but UX researchers, product managers, ethics reviewers, and behavioral scientists can all contribute at different stages.only one designer also can do all the steps individually based on project scope and budget availability
| Role | Primary responsibility | Required steps |
|---|---|---|
| Lead designer | Facilitates the full flow; owns the ethics audit sign-off | All steps |
| UX researcher | Drives Step 2 discovery; validates mode diagnosis in Step 3 | Steps 2, 3, 10 |
| Product manager / Client | Step 8 stakeholder review; receives behavioral design brief | Step 1 (onboarding), Step 8 |
| Ethics reviewer | Signs off the five-question audit | Step 7 |
| Behavioral scientist / consultant | Advises Steps 4–5 bias and mechanism selection | Steps 4, 5 (optional) |
Track your progress
Each step page has a "Mark complete" checkbox. Your progress is stored locally in your browser, so returning to the guide picks up where you left off. The progress bar in the top navigation reflects your current state.
Never apply a cognitively demanding intervention on a user in System 1 mode. And never apply a pure System 1 cue (silent default, one-tap automation) to a user who needs the System 2 deliberation that genuine commitment requires.
If you remember nothing else from this guide, remember this.
example: A user is presented with a default option that requires minimal cognitive effort to select.
Onboarding: framework walkthrough
Before the team applies any framework tool, every participant should share a mental model of the process they are about to navigate. Step 1 is the team-level equivalent of onboarding.
Purpose
Give every team member an annotated Double Diamond with all ten steps overlaid in their correct phase, showing handoffs, platform shifts (Miro → Figma → Miro), and feedback loops. The activity is deliberately lightweight; its function is alignment, not instruction.
Study 2 — The Intentionality Gap: 76.3% behavioral awareness vs 28.9% intentional application. Designers need a visible procedural scaffold to convert awareness into intentional practice.
Study 3: Workshop participants unanimously reported that structuring evaluation around the Double Diamond gave them "an embodied understanding of how the framework operates as a process tool."
Miro board setup
Figjam (Figma collaborative Board) is also other option if the team prefer it.
- Board name:
00 — Framework Overview - Central canvas: Double Diamond diagram with all ten step-cards positioned in the correct phase zone
- Four phase zones: Discover, Define, Develop, Deliver — each as a framed region
- Step-cards are clickable and link to their respective boards (01–08)
- Sidebar frame with glossary: Fogg terms (Spark / Signal / Facilitator), System 1/2 notation, six mode names
Facilitation activity
Walk the group around the diamond in sequence, spending two minutes on each step. For every step, surface two questions:
(1) what output does this step produce?
(2) what decision does that output unlock in the next step?
The goal is not to teach the framework in depth (that happens step by step later) but to make the overall arc visible so no one is later confused about why, for example, Figma is gated until Step 6.
Outputs
- Shared mental model of the ten-step flow
- Explicit team commitment to staying in Miro for Steps 1–5 (no premature Figma jumps)
- Named owner for each step
Common pitfalls
- Skipping onboarding because "everyone knows the Double Diamond." The framework-specific overlay is the value ,NOT the Double Diamond itself.
- Treating this step as a presentation rather than a dialogue. Questions here prevent confusion in Steps 2–5.
Research: behavioral journey mapping with cognitive annotations.
A standard journey map tracks touchpoints, emotions, and pain points. A behavioral journey map adds three annotation layers at every touchpoint: motivation, ability, triggr. These annotations are the raw material for Steps 3 and 4.
Purpose
Produce a journey map where each touchpoint carries seven data points: user action, emotion, motivation level (−2 to +2), ability level (−2 to +2), trigger level (−2 to +2). Without these annotations, downstream mode diagnosis becomes guesswork.
in next step we use all findings from last map in category (under fogg component) board and we can list all related cognitive biases which ended to that pain point.
Study 1: Domain-differentiated trigger preferences (Signal dominant in hydration and posture; Spark dominant in mindfulness) show nudge effectiveness is context-specific. Mapping the journey with cognitive annotations surfaces the domain barrier profile.
Study 2 — Agile Compression of Discovery: Behavioral research is the first victim of sprint compression. This step provides a defensible, time-boxed discovery activity.
Study 3: Participants reported journey mapping was the most valuable activity because it "made the cognitive state question visible" (P08).
Method options
Select one or more based on time available. Use the sprint-compressed one-hour behavioral brief (from Study 3 Theme 4) when discovery time is limited.
| Method | Time | When to use |
|---|---|---|
| Semi-structured interview (3–5 participants) | 60–90 min each | New product or unfamiliar domain |
| Diary study (1 week passive) | 7 days | Habit-formation / long-form behaviors |
| Contextual inquiry | 45–60 min | Real System 1/2 transitions observed |
| Sprint-compressed behavioral brief | 60 min total | Established product or tight sprint |
| Secondary research | 2–4 hours | Low-budget validation |
Miro board setup
- Board name:
02 — Behavioral Journey Map - Horizontal swim-lane template, seven rows: touchpoints, actions, emotions, motivation (−2 to +2), ability (−2 to +2), trigger (−2 to +2)
- Evidence sidebar: verbatim quotes as sticky notes attached to each touchpoint
- Unvalidated flag: amber sticky on any annotation based on intuition rather than evidence
Outputs
- Fully annotated behavioral journey map
- Ranked list of "critical touchpoints", where motivation, ability, or trigger is deficient
- Evidence citations for each annotation
Common pitfalls
- Confusing journey mapping with persona writing. Personas are static archetypes; behavioral journeys are sequences of cognitive states over time.
Cognitive state diagnosis: the traffic-light card deck.
The framework's core diagnostic act. Map each critical touchpoint to one of six cognitive modes using a triage-style card deck
Purpose
Collapse the complexity of COM-B, Fogg, TTM, and dual-process theory into a single rapid classification : the "good enough fast enough" triage principle proposed by P01 during the Study 3 workshop, drawing on emergency response system design.
Study 1: Core finding: nudge effectiveness is determined by mechanism-state-timing interaction (not mechanism alone). State diagnosis is the most critical step.
Study 3 Theme 2: Cognitive state diagnosis ranked #1 priority (8 of 10 participants). Without the card deck, the full diagnostic took 8+ minutes per touchpoint; three times the available sprint budget.
The six modes
Each card is A6 format, colour-coded red / amber / green using the triage metaphor. Click any card below to jump to its full reference entry.
Facilitation activity
For each critical touchpoint from Step 2, the team collectively drags the matching mode card onto the touchpoint. Disagreements are valuable ,they surface ambiguous evidence. Where the team cannot agree within two minutes, the touchpoint is flagged "needs more research" and returned to Step 2. This avoids the Study 2 pattern of forced stage assignments producing unstable downstream design.
Miro board setup
- Board name:
03 — Cognitive State Diagnosis & 3-traffic-light card deck. - Six mode cards as draggable Miro components (template library provided)
- Journey map from Step 2 imported as background layer
- Disagreement zone: parking area for contested touchpoints
Outputs
- Every critical touchpoint annotated with mode (1–6)
- Each mode tagged with nudge entry point (Facilitator / Spark / Signal / excluded)
- Contested touchpoints flagged for return to Step 2
Common pitfalls
- Annotating System 1/System 2 from memory of Kahneman. Use the heuristic: if the user would stop and think, it is S2; if they would act without thinking, it is S1.
If the user would stop and think, it's System 2. If the user would act without thinking, it's System 1. Mixed states (e.g., opening an app you know well vs. making a new goal) get a striped annotation.
Bias mapping: the cognitive under-layer and problem-need linkage.
Modes diagnose the "what" of the user's state. Biases diagnose the "why." Surface the specific cognitive biases operating beneath each diagnosed mode and connect them to the unmet user need.
Purpose
The same mode can have different underlying biases in different domains. Mode 3 Motivated-Stuck in hydration is often attentional (salience deficit); in exercise it is present bias; in medication adherence it can be optimism bias ("I'll remember"). Different biases call for different mechanisms in Step 5. Without the bias layer, mechanism selection is mis-targeted.
Study 1: The identity-threat reactance finding in the mindfulness domain (P52: "If it comes when I am in the middle of typing, it feels aggressive") shows that the bias beneath a mode is domain-dependent. Identity-threat is a distinct reactance mechanism requiring different treatment than friction-based reactance.
Study 2, The Invisible Hand Problem: Designers apply mechanisms without recognising the biases they exploit, making ethical evaluation impossible. Step 4 forces the bias to be named.
Canonical bias-per-mode starting points
| Mode | Dominant System | Typical biases | Unmet need |
|---|---|---|---|
| 1 Unaware | S1 | Mere exposure gap; availability deficit; affect heuristic absence | Awareness this behavior is for me |
| 2 Undecided | S1/S2 conflict | Present bias; hyperbolic discounting; ambiguity aversion | Reason to commit now rather than later |
| 3 Motivated-Stuck | S2 frustrated | Decision fatigue; choice aversion; default-effect absence | Remove friction between intent and action |
| 4 Primed | S2 ready / S1 approaching cue | Status quo bias; salience bias; priming | Right cue at the right moment |
| 5 Forming | S2 → S1 transition | Mere exposure; priming; peak-end effect | Consistent reinforcement of the habit loop |
| 6 Retreating | S2 defensive | Self-serving bias; shame-loss aversion; self-as-failure confirmation | Identity repair before behavior re-entry |
System 1 biases (fast / intuitive / automatic)
Operate under cognitive absorption, time pressure, or low deliberation. Triggered by salience, affect, or pattern-matching to prior cues.
System 2 biases (slow / deliberative / effortful)
Operate under explicit reasoning, analysis, and choice evaluation. Often produce errors of over-analysis, choice overload, or delayed consequence weighting.
Facilitation activity
For each mode-annotated touchpoint, pull 2–4 bias cards into the per-touchpoint grid.
Constraint: S1-dominant modes draw from the S1 bias set; S2-dominant modes from S2; mixed modes draw from either with justification.
For each bias, write one sentence on why it operates here (drawing on Step 2 evidence), then one sentence stating the unmet need it creates. The triple bias, why, unmet need is the decision-unlocking artefact for Step 5.
Miro board setup
- Board name:
04 — Bias Map - Bias card library grouped into System 1 and System 2 frames (see Bias Library in sidebar reference)
- Per-touchpoint grid: three columns : Bias | Why it operates here | Unmet need it creates
- Identity-threat watch-zone: explicit callout for mindfulness or self-concept-sensitive touchpoints
Outputs
- Bias-need mapping per critical touchpoint
- Flagged high-risk biases (loss aversion in Mode 6, scarcity in any vulnerable state) carried forward as ethics-audit concerns for Step 7
Any high-risk bias flagged here (loss aversion in Mode 6, scarcity in any vulnerable state, competitive comparison in identity-sensitive domains) becomes an ethics audit concern for Step 7. Mark these explicitly on the Miro board.
Nudge selection: Spark / Signal / Facilitator and the 23 mechanisms.
Translate the diagnostic work of Steps 2–4 into a shortlist of candidate nudge mechanisms. The selection logic is deliberately simple so it can be applied under sprint pressure.
The selection decision tree
A single diagnostic question at the top routes to one of three branches:
| If the primary barrier is… | Category | Start with |
|---|---|---|
| Motivation (user does not want to, or does not feel the behavior is for them) | Spark | Identity-affirming framing or verified social proof (low risk) |
| Ability (user wants to but is blocked by friction) | Facilitator | Defaults or simplified workflow (lowest risk; highest trust-building) |
| Trigger (motivation and ability present, no contextual cue) | Signal | Just-in-time prompts based on behavioral triggers (not fixed intervals) |
| Uncertain | Facilitator first | Builds the trust foundation Signal and Spark later depend on |
Study 1 — Domain-differentiated preferences: Signal dominant in hydration (47.3%) and posture correction (47.0%); Spark dominant in mindfulness (41.2%); Facilitator consistently low in user selection (23.6–29.8%) but highest in ethical acceptability.
Study 2: Designers systematically overestimate Facilitator default effectiveness and underestimate Signal timing-sensitivity. Step 5 corrects for this by anchoring selection in evidence.
Browse the 23 mechanisms
Filter below by trigger category. Each card shows ethical risk, primary bias target, and the modes where it fits best.
Loss Aversion (Spark): Maintenance mode (Mode 5) only. Never for Modes 1, 2, or 6.
Scarcity / Urgency (Spark): Acceptable only when the constraint is genuine and verifiable. Manufactured countdown timers are categorical dark nudges.
Competitive Social Comparison: Categorically excluded from all health contexts. Increases cortisol, reduces intrinsic motivation.
Miro board setup
- Board name:
05 — Nudge category selection - Decision tree at top (primary barrier → trigger category)
- Three mechanism card library frames (23 cards total, downloadable as templates)
- Per-touchpoint shortlist canvas: 2–4 selected cards with written rationale linking each to mode, bias, and unmet need from Step 4
- High-risk mechanism flag zone
Outputs
- Candidate mechanism shortlist per critical touchpoint (typically 2–4 mechanisms)
- Written rationale linking each mechanism to mode, bias, and unmet need
- High-risk mechanism flags carried forward to Step 7 for ethics audit
Figma ideation: Nudge component library
The only step that leaves Miro or Figjam (collaborative boards). The switch is deliberate, this is where cognitive strategy becomes concrete visual artefact.
Purpose
Designers open the pre-built Nudge Component Library (a Figma Community file) and use it to ideate concrete interface treatments for each mechanism shortlisted in Step 5. Keeping visual tools isolated to one step prevents designers from jumping to interface craft before the behavioral and ethical work is done.
Study 2 Gap 5 (Tooling and Resources): 78.9% of designers reported lacking a shared component library for behavioral design. The library directly addresses this gap.
Study 3: P06 proposed that each component carry its ethical-risk annotation and compatible-mode tag inline ; a pattern now built into every library component.
Component annotation schema
Every component in the library carries a standardised annotation block visible in the Figma sidebar. The annotation is the translation layer between cognitive strategy and interface implementation.
| Annotation field | Example content |
|---|---|
| Mechanism name | Healthy default: daily goal pre-set |
| Trigger category | Facilitator |
| Primary bias | Status quo bias, default effect |
| Compatible modes | Modes 1, 2, 3 |
| Dual-process target | System 1 (automation); System 2 reassured by visible opt-out |
| Ethical risk | Low (if opt-out visible and goal reflects user's stated intention) |
| Ethical red flag | HIGH RISK if default reflects commercial rather than user interest |
we have 23 different digital nudge mechanisms which has underlayers in cognitive bias, dula system thinking and ethics
Activity
For each mechanism on the Step 5 shortlist, duplicate the component from the library into the ideation workspace, customise to the specific product context: brand typography, domain-specific copy (hydration vs mindfulness, for example), integration with surrounding interface. Produce 2–3 variations per mechanism. These will be evaluated in Step 7 (ethics) and Step 8 (stakeholder alignment) before final design synthesis.
The Figma Library reference page in the sidebar shows the full file architecture: 6 pages covering Spark (32 instances), Facilitator (28), Signal (32), worked ethical vs. dark-pattern examples, and an ideation workspace.
Outputs
- 2–3 Figma design variations per shortlisted mechanism
- Annotated component instances showing which parameters were customised
- Export-ready frames for import back into Miro (Step 7 operates on these frames)
Common pitfalls
- Treating Step 6 as the whole design process. It is ideation only. Final feature design happens in Step 9 after ethics and stakeholder review.
- Ignoring the library's built-in annotations. Stripping them converts an evidence-based component into a decoration.
Ethics audit
Before any design leaves ideation, every shortlisted nudge passes through the five-question ethics audit. This step converts the abstract principles into a documentable, defensible, sprint-compressed protocol.
Study 2; Ethics by Intuition: 76.3% of designers cited ethical uncertainty as their primary professional challenge. The dominant response to "how do you determine ethical acceptability?" was intuition ("it just feels wrong").
Study 3 Theme 1: The abstract criteria of Framework v1.0 produced inconsistent adjudication of the countdown timer case , all four tests passed, yet moral discomfort persisted. P09 proposed the five-question replacement, adopted verbatim.
Run the audit
Try it below with a design you are considering. Mark each question Pass or Fail. Any single Fail halts progression, the design must be revised before proceeding to Step 8.
Intensity calibration
In parallel with the audit, place each design on the four-level intensity ladder.
| Level | Description | Proceed if… |
|---|---|---|
| 0 — Baseline | No embedded nudge | Always acceptable as control |
| 1 — Single (DEFAULT) | One mechanism, one cognitive pathway | All five audit questions pass |
| 2 — Multi (staged) | Complementary mechanisms, sequential not simultaneous | Level 1 validated; intrusiveness < 2.5/5 in testing |
| Dark nudge | Exploits cognitive vulnerabilities | NEVER — fabricated urgency, obstructed opt-out, shame framing, competitive comparison |
A fitness app displays "6 hours left to complete today's challenge!" All four abstract v1.0 tests pass (goal-aligned, opt-out present, data consented, autonomy nominal). Yet moral discomfort persisted. The v2.0 mechanism criterion resolves the case: the countdown timer manufactures artificial scarcity to exploit scarcity bias; the mechanism activates cognitive states non-conducive to autonomous decision-making regardless of whether the goal is health-beneficial.
Verdict: categorical dark nudge. The mechanism, not the goal, determines ethical status.
Outputs
- Signed audit per design element (designer, product owner, ethics lead)
- Any design failing an audit question returned to Step 6 for redesign
- Audited designs tagged with intensity level for Step 9 synthesis
Stakeholder and business alignment.
An ethically audited, evidence-grounded nudge is useless if the designer cannot defend it to a product manager asking for something extractive. Step 8 converts behavioral rationale into stakeholder language.
Study 2; The Client Pressure Trap: Nearly half of participants described commercial contexts where clients explicitly requested manipulative design features. Without evidence-based professional authority, designers felt unable to resist.
Study 3: P06 (03:31) — "I need a one-page template that says: here's the user mode I diagnosed, here's why I chose this mechanism, here's the psychological evidence, here's why it's ethically sound. In language a product manager can read without a behavioral science background."
The four stakeholder templates
| Template | Purpose | Primary audience |
|---|---|---|
| 1. Behavioral Design Brief (one-pager) | Summarises mode diagnosis, selected mechanism, psychological evidence, ethical rationale, success measure ; in plain language | PM; client lead |
| 2. Nudge Rationale Card | Per-feature card specifying why this specific nudge for this specific user state, with one supporting study quote | Engineering; QA; design review |
| 3. Ethics Sign-off Document | Captures five-question audit outcome, intensity level, named sign-off roles | Ethics reviewer; legal; compliance |
| 4. Dark Pattern Exclusion Record | Professional advocacy instrument, documents what was proposed, why excluded, evidence-based rationale. Used for pushing back on extractive requests. | Designer (internal); design lead |
Facilitation activity
Populate each template from the work produced in Steps 3, 4, 5, and 7. The behavioral design brief is always mandatory. Schedule a 30–45 minute stakeholder review — not as a presentation but as a shared artefact inviting stakeholder modification within ethical thresholds. Proposed modifications that would violate Step 7 thresholds are met with the dark pattern exclusion record.
Miro board setup
- Board name:
08 — stakeholder and business alignment. - Four template frames (one per template), auto-populated from upstream boards where possible
- Business-goal vs. user-goal alignment grid: explicit trade-offs with a "no dark pattern" watermark
- Decision log: timestamped record of stakeholder modifications and ethical pushbacks
Outputs
- Signed stakeholder brief
- Business-alignment adjustments documented (within ethical thresholds)
- Any dark-pattern proposals formally excluded with evidence-based rationale
Interface design synthesis.
The synthesis point where everything produced in Steps 1–8 converges into the production-ready interface specification. Return to Figma for execution but use Miro as the brief.
The synthesis canvas
Each feature-level design decision is a node. Every node carries six required annotations drawn from earlier steps.
| Annotation | Sourced from | What it records |
|---|---|---|
| Mode diagnosis | Step 3 | Which of the six modes this feature serves |
| Bias → Need | Step 4 | Which bias is operating; what unmet need the feature addresses |
| Mechanism | Step 5 | Which of the 23 mechanisms is implemented and why |
| Intensity + Ethics | Step 7 | Level 0/1/2 and audit sign-off |
| Dual-process target | Step 4 | Respects S1/S2 mode; what is avoided to prevent reactance |
Outputs
- Annotated Miro synthesis canvas
- Final Figma spec with per-feature annotation (mode, mechanism, bias, intensity, dual-process)
- Design review sign-off incorporating Step 7 ethics outcome and Step 8 stakeholder brief
Evaluation: A/B testing and the Nudge Effectiveness Score.
Conventional A/B testing measures whether a change increased a metric. It does not measure whether that increase came at the cost of user autonomy. Step 10 closes the measurement blind spot. we can consider this step for our later work, as it is more relevant for post-launch evaluation rather than the design process itself.
Study 1: NEM (Nudge Effectiveness Metric) and NES (Nudge Effectiveness Score) operationalised sand validated across 88 users × three domains. The formula discriminated between mechanisms with low-ethical-cost engagement and those with high-ethical-cost engagement.
Study 2: Interview Participant 7 (Design Lead, 10 years) — "We A/B test CTR and session length. We never test whether the nudge was actually good for the user." Step 10 operationalises the answer.
Try the NES calculator
Enter per-condition metrics below. The formula penalises engagement achieved at the cost of intrusiveness; a nudge with high clicks but high perceived intrusiveness scores lower than a quieter nudge with modest clicks and low intrusiveness. we can not calculate the long term effecticvenss as it might have some different variable envolved
Decision rule
A treatment is adopted only if (1) NES exceeds Control by a practically meaningful margin, (2) Perceived Intrusiveness stays below 3.0/5, and (3) Perceived Autonomy stays above 3.5/5.
A condition that scores highest on NES but violates (2) or (3) is rejected, engagement was achieved at the cost of user wellbeing. This rule operationalises the framework's central thesis: effectiveness is a mechanism-state-timing-ethics product, not a mechanism property.
A/B test protocol
| Condition | Content | Purpose |
|---|---|---|
| Control (L0) | No embedded nudge; plain interface | Baseline measurement |
| Treatment A (L1) | Single selected mechanism from Step 5 | Isolate mechanism contribution |
| Treatment B (L2) | Staged multi-mechanism from Step 9 | Measure incremental benefit (only after L1 validated) |
Metrics Collected
| Category | Metric | Source | Threshold |
|---|---|---|---|
| Engagement | Click-Through Rate (CTR) | Analytics | Compare across conditions |
| Engagement | Conversion Rate | Analytics | Compare across conditions |
| Engagement | Engagement Score (time × breadth) | Analytics | Compare across conditions |
| Engagement | Bounce Rate | Analytics | Lower is better |
| Behavioral | Adherence Rate | Self-report + logs | Compare across conditions |
| Behavioral | Sustained Use Intention (Likert 5) | Post-session questionnaire | Higher is better |
| Behavioral | Habit Formation Potential (SRHI-adapted) | Post-session questionnaire | Higher is better |
| Perceptual / Ethical | Perceived Intrusiveness (Likert 5) | Post-session questionnaire | CEILING < 3.0 (reverse-coded) |
| Perceptual / Ethical | Perceived Autonomy (Likert 5) | Post-session questionnaire | FLOOR > 3.5 |
| Perceptual / Ethical | Satisfaction Score (Likert 5) | Post-session questionnaire | Higher is better |
Feedback loop
Post-test, document lessons in the learning log and feed them back to Step 2 for the next design cycle. The framework is explicitly iterative, the NES informs the next journey map, which informs the next diagnosis, and so on.
Outputs
- NES per condition, documented
- Adoption decision with full evidence trail
- Lessons-learned log feeding the next design cycle (close the loop)
Framework action points
The Digital Nudging Framework v2.0 has some key action points. Each one operationalised in specific steps of the ten-step implementation.
Action A — Behavioral State Diagnosis
Six-mode diagnostic organised around the traffic-light card deck. Modes map onto TTM stages while incorporating dual-process annotations absent from standard TTM applications.
- Mode 1 Unaware (red, S1 dominant) — no schema
- Mode 2 Undecided (amber, S1/S2 conflict) — ambivalence
- Mode 3 Motivated-Stuck (amber, S2 frustrated) — friction-blocked
- Mode 4 Primed (green, S2 ready) — both motivation and ability present
- Mode 5 Forming (green, S2→S1) — habit consolidating
- Mode 6 Retreating (red, S2 defensive) — post-lapse reactance
Action B — Nudge Type Selection with Psychological Evidence
All 23 digital nudge mechanisms organised by Fogg trigger type. Each annotated with primary cognitive bias target, compatible modes, ethical risk rating, and health app example.
Selection logic: motivation absent → Spark; ability constrained → Facilitator; motivation and ability present but cue absent → Signal; uncertain → Facilitator first.
Action C — Intensity Calibration and Ethical Thresholds
Four-level intensity ladder (0/1/2/Dark) with cognitive load profile and ethical acceptance criteria per level. NES formula specified as the quantitative instrument. Five-question Ethics Audit converts abstract principles into pre-launch, documentable protocol. Dark nudge exclusion list: fabricated urgency, obstructed opt-out, shame-based framing, competitive social comparison, bait-and-switch defaults, negative self-image exploitation.
Action D — Dual-Process Targeting
Three cognitive mode profiles — System 1 (automatic), System 2 (deliberate), Transitional (mixed / stress-disrupted / novelty-demanding). For each: contextual description of when active in health app use, aligned nudge strategy, theoretical basis, and explicit guidance on what to avoid. Transitional profile specified with particular care — the state where reactance and self-efficacy damage risk is highest.
Action E — Health Domain Guidance
Domain-specific cognitive barrier profiles and nudge sequence recommendations for hydration, posture, mindfulness (Study 1 empirical, n=88 per domain) plus physical activity and sleep (Study 3 practitioner-validated, W notation). Each domain entry specifies characteristic cognitive barrier profile, empirically recommended nudge sequence, domain-specific design considerations, and representative participant voice.
Within the ten-step implementation, the framework's intellectual spine is a five-step cognitive design process. Use it as a sprint-compressed mental checklist when the full ten-step flow is not possible:
1. Diagnose the state (which mode?) → 2. Select the trigger (Spark / Facilitator / Signal) → 3. Check processing mode (S1 / S2?) → 4. Calibrate intensity ethically (Level 0/1/2 + audit) → 5. Evaluate with the user in mind (NES).
The six modes — full reference.
The traffic-light card deck. Click any card to navigate to Step 3, where the deck is used in context. Print versions are A6 format for physical workshops.
The S1/S2 boundary does not run horizontally through the FBM at a fixed motivation level — it is contextually determined. Modes 1 and 5 sit in S1 territory (absent vs. consolidating). Mode 6 appears in S1 territory on the motivation axis but is actually S2 defensive — the most important exception. Modes 2, 3, 4 involve varying degrees of S2 engagement.
Never apply an S2-demanding intervention (long-form goals, detailed dashboards, reflective journaling) to a user in S1 mode. Never apply a pure S1 cue (silent default, one-tap automation) to a user who needs S2 deliberation for genuine commitment.
23 nudge mechanisms.
Caraban et al.'s taxonomy of digital nudges, organised by Fogg trigger type. Filter by category, then match each mechanism to your diagnosed barrier.
Risk legend
Low risk — safe in most contexts · Medium — condition-dependent · High — conditional or categorical exclusion
Competitive social comparison (upward comparison increases cortisol, reduces intrinsic motivation), Placebo / illusory progress signals (hollow reinforcement), Manufactured scarcity / urgency (exploits scarcity bias without genuine constraint).
Bias library.
Cognitive biases organised by the dual-process system they operate within. S1-dominant modes should draw from the S1 set; S2-dominant modes from S2. Mixed modes may draw from either with explicit justification.
System 1 biases (fast / intuitive / automatic)
Operate under cognitive absorption, time pressure, or low deliberation. Triggered by salience, affect, or pattern-matching to prior cues.
System 2 biases (slow / deliberative / effortful)
Operate under explicit reasoning, analysis, and choice evaluation. Often produce errors of over-analysis, choice overload, or delayed consequence weighting.
This list is illustrative, not exhaustive. For a diagnosed mode, pull 2–4 candidate biases from the relevant system set. For each, ask: does this bias plausibly operate here, given the evidence from Step 2? Biases that cannot be evidenced should not be used to justify mechanism selection.
The Nudge Component Library.
A six-page Figma file containing all 23 mechanisms as production-ready components, each annotated with trigger category, primary bias, compatible modes, dual-process target, ethical risk, and Study 1 evidence quote.
File architecture
Each mechanism ships with four domain variants (hydration, posture, mindfulness, general). Worked ethical-vs-dark-pattern comparisons are on a separate page for reference during Step 7 audits.
Component annotation schema
Every component carries the same annotation block in the Figma sidebar:
| Field | Example |
|---|---|
| Mechanism name | Healthy default — daily goal pre-set |
| Trigger category | Facilitator |
| Primary bias | Status quo bias, default effect |
| Compatible modes | Modes 1, 2, 3 |
| Dual-process target | System 1 (automation); S2 reassured by visible opt-out |
| Ethical risk | Low (if opt-out visible and goal reflects user intention) |
| Study 1 evidence | P61: "It was already set up but I could easily change it. It felt like it respected that I know what I need." |
| Ethical red flag | HIGH RISK if default reflects commercial rather than user interest |
Distribution
Published to Figma Community under CC BY 4.0. A companion GitHub repository contains the ethics audit checklist as a downloadable PDF and the NES Evaluation Worksheet as a fillable form. Feedback is collected through an embedded Google Form linked from the Figma Community publication.
Duplicate a component into the ideation workspace (page 06). Customise brand typography and domain-specific copy. Preserve the annotation block — it travels with the component as metadata and will be referenced in Step 9 design synthesis.
Study traceability matrix.
Each of the ten steps is connected to at least one empirical finding from the three-study research programme. This matrix is the framework's transparency guarantee.
| Step | Framework section | Study 1 link | Study 2 link | Study 3 link |
|---|---|---|---|---|
| 1. Onboarding | Procedural scaffold | — | Intentionality Gap | Process alignment validation |
| 2. Journey map | A, E | Domain-specific barrier profiles | Discovery compression | Journey map as core activity |
| 3. Mode diagnosis | A | Mechanism-state-timing interaction | Diagnostic tool absence | Traffic-light card deck (Theme 2) |
| 4. Bias mapping | A, D | Identity-threat reactance (mindfulness) | Invisible Hand Problem | Bias vocabulary translation |
| 5. Nudge selection | B | Domain-differentiated trigger preference | Mechanism overestimation correction | 23-mechanism library structure |
| 6. Figma library | B, E | Domain-specific component variants | Tooling gap (Gap 5) | Annotation schema validated |
| 7. Ethics audit | C | Perceived intrusiveness threshold | Ethics by Intuition | Five-question checklist (Theme 1) |
| 8. Stakeholder | Toolkit | — | Client Pressure Trap | Stakeholder template set |
| 9. Design synthesis | All | Domain-specific guidance | User-goal primacy | Domain extensions (Theme 3) |
| 10. NES evaluation | C | NES formula validated empirically | Measurement Blind Spot | User-wellbeing integration |
Framework statement
Digital nudge effectiveness in health application contexts is not a function of mechanism sophistication alone, but of the alignment between nudge design and the cognitive, emotional, and motivational state of the user at the moment of nudge encounter.
This ten-step guide operationalises that alignment as a collaborative, auditable, ethically principled design process distributed across Miro and Figma — validated through Study 3 co-creation workshop, open-access under CC BY 4.0.