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Framework Overview

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.

88
Study 1 Users
Prototype testing across hydration, posture, mindfulness to understand user needs and behaviors while facing digital nudge designs
38
Study 2 Designers
Mixed-methods questionnaire with semi-structured interviews to understand designer needs and behaviors while using digital nudge in applications
10
Study 3 Practitioners
Co-creation workshop to finding the gaps in Framework v1.0 and then validating Framework v2.0 with designers and experts

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.

Diverge
Discover
1 2
Converge
Define
3 4
Diverge
Develop
5 6
Converge + Loop
Deliver
7 8 9 10
Double Diamond Model

The framework at a glance

Five sections (A–E) form the intellectual backbone. Each step operationalises one or more of them.

SectionPurposeStep(s)
A Behavioral State DiagnosisIdentify the user's cognitive state using the six-mode traffic-light system deck cards.Steps 1,2, 3
B Nudge Type SelectionMatch the diagnosed barrier to Spark, Signal, or Facilitator and select from 23 mechanisms.Steps 4, 5, 6
C Intensity & Ethical ThresholdsLevel 0/1/2 calibration and the five-question Ethics Audit.Step 7
D Dual-Process TargetingAlign the nudge with the user's System 1 / System 2 processing mode.Steps 3, 4, 9
E Health Domain GuidanceDomain-specific barrier profiles (hydration, posture, mindfulness, physical activity, sleep).Steps 2, 9
Why the Miro–Figma split

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.

Getting Started

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

Linear first time
Work through Steps 1–10 in order the first time you apply the framework to a new health product. Each step assumes the outputs of the previous ones.
Loop after launch
After Step 10, evaluation feeds back into Step 2. Subsequent iterations can skip Step 1 onboarding and jump straight into updated journey mapping.
Sprint-compressed mode
When sprint time is tight, run Steps 2–3 as a single one-hour behavioral brief. Step 7 is never skipped, regardless of time pressure.
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Reference while working
The Reference section in the sidebar (mode cards, mechanisms, biases, Figma library) is consultable from any step. Open in a second tab alongside your working board.

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

RolePrimary responsibilityRequired steps
Lead designerFacilitates the full flow; owns the ethics audit sign-offAll steps
UX researcherDrives Step 2 discovery; validates mode diagnosis in Step 3Steps 2, 3, 10
Product manager / ClientStep 8 stakeholder review; receives behavioral design briefStep 1 (onboarding), Step 8
Ethics reviewerSigns off the five-question auditStep 7
Behavioral scientist / consultantAdvises Steps 4–5 bias and mechanism selectionSteps 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.

One principle above all

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.

Step 01 of 10

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.

Platform Miro
Duration30–45 min
OutputShared mental model

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 Evidence

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.
Step 02 of 10

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.

Platform Miro
Duration90–120 min
OutputAnnotated journey map

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 Evidence

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.

MethodTimeWhen to use
Semi-structured interview (3–5 participants)60–90 min eachNew product or unfamiliar domain
Diary study (1 week passive)7 daysHabit-formation / long-form behaviors
Contextual inquiry45–60 minReal System 1/2 transitions observed
Sprint-compressed behavioral brief60 min totalEstablished product or tight sprint
Secondary research2–4 hoursLow-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.
Step 03 of 10

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

Platform Miro
Duration45–60 min
OutputMode-annotated touchpoints

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 Evidence

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.
S1 or S2 — fast heuristic

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.

Step 04 of 10

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.

Platform Miro
Duration60–75 min
OutputBias → Need grid

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 Evidence

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

ModeDominant SystemTypical biasesUnmet need
1 UnawareS1Mere exposure gap; availability deficit; affect heuristic absenceAwareness this behavior is for me
2 UndecidedS1/S2 conflictPresent bias; hyperbolic discounting; ambiguity aversionReason to commit now rather than later
3 Motivated-StuckS2 frustratedDecision fatigue; choice aversion; default-effect absenceRemove friction between intent and action
4 PrimedS2 ready / S1 approaching cueStatus quo bias; salience bias; primingRight cue at the right moment
5 FormingS2 → S1 transitionMere exposure; priming; peak-end effectConsistent reinforcement of the habit loop
6 RetreatingS2 defensiveSelf-serving bias; shame-loss aversion; self-as-failure confirmationIdentity 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.

Attention & salience
Attentional bias Salience bias Priming effect Mere exposure Primacy & recency Spotlight effect
Affect & social
Affect heuristic Halo effect Herd instinct Authority bias Appeal to majority Reciprocity bias Image motivation
Anchoring & framing
Anchoring Default effect Framing effect Contrast effect Decoy effect Status quo bias
Loss & scarcity
Loss aversion Scarcity bias Optimism & overconfidence Hyperbolic discounting Peak-end effect Placebo effect Availability heuristic Accent fallacy

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.

Decision overload
Ambiguity aversion Choice aversion Decision fatigue Decision inertia Information bias Middle-option bias
Commitment & memory
Commitment bias Sunk-cost fallacy Endowment effect Hindsight bias Choice-supportive bias Confirmation bias Selective perception
Temporal & risk
Present bias Procrastination Intertemporal choice Risk aversion Conjunction fallacy Gambler's fallacy Regression to the mean
Reasoning & meta
Correspondence bias Mental accounting Denomination effect Diversification bias Distinction bias Representativeness / stereotypes Messenger effect Social desirability Simulation heuristic Decoupling

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
High-risk biases — carry forward to 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.

Step 05 of 10

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.

Platform Miro
Duration60–90 min
OutputMechanism shortlist + rationale

The selection decision tree

A single diagnostic question at the top routes to one of three branches:

If the primary barrier is…CategoryStart with
Motivation (user does not want to, or does not feel the behavior is for them)SparkIdentity-affirming framing or verified social proof (low risk)
Ability (user wants to but is blocked by friction)FacilitatorDefaults or simplified workflow (lowest risk; highest trust-building)
Trigger (motivation and ability present, no contextual cue)SignalJust-in-time prompts based on behavioral triggers (not fixed intervals)
UncertainFacilitator firstBuilds the trust foundation Signal and Spark later depend on
Study Evidence

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.

23 Nudge Mechanisms

Browse the 23 mechanisms

Filter below by trigger category. Each card shows ethical risk, primary bias target, and the modes where it fits best.

High-risk mechanisms — elevated scrutiny required

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
Step 06 of 10

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.

Platform Figma
Duration90–180 min
OutputDesign variations per mechanism

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 Evidence

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.

Example: Facilitator/ Default

Annotation fieldExample content
Mechanism nameHealthy default: daily goal pre-set
Trigger categoryFacilitator
Primary biasStatus quo bias, default effect
Compatible modesModes 1, 2, 3
Dual-process targetSystem 1 (automation);
System 2 reassured by visible opt-out
Ethical riskLow (if opt-out visible and goal reflects user's stated intention)
Ethical red flagHIGH 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.

See the full Figma library structure

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.
Step 07 of 10

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.

Platform Miro
Duration45–60 min
OutputSigned audit per design
Study Evidence

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.

Q1
Does this nudge serve the user's health goal, or the product's engagement goal?
If engagement-primary, the nudge is extractive. If health-primary (even when engagement benefits as a by-product), it passes.
Q2
Is the opt-out as visible and friction-free as the primary action?
Asymmetric friction between primary and opt-out is sludge. Opt-out must be reachable within the primary view — not buried in settings.
Q3
Is all personalisation data consented to, with clear purpose?
Covert personalisation (using data the user did not realise was informing the nudge) fails this test.
Q4
Would the user, fully informed about the mechanism, endorse this nudge?
The informed-endorsement test. Would a reasonable user, shown the full mechanism including the cognitive bias being leveraged, agree it is for their benefit? Most decisive question.
Q5
Does this preserve the user's sense of autonomous choice?
Autonomy is measurable (Perceived Autonomy Score). Mechanisms producing compliance at the cost of perceived autonomy fail.
Mark all five questions Pass or Fail to see the result.

Intensity calibration

In parallel with the audit, place each design on the four-level intensity ladder.

LevelDescriptionProceed if…
0 — BaselineNo embedded nudgeAlways acceptable as control
1 — Single (DEFAULT)One mechanism, one cognitive pathwayAll five audit questions pass
2 — Multi (staged)Complementary mechanisms, sequential not simultaneousLevel 1 validated; intrusiveness < 2.5/5 in testing
Dark nudgeExploits cognitive vulnerabilitiesNEVER — fabricated urgency, obstructed opt-out, shame framing, competitive comparison
Worked example — countdown timer

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
Step 08 of 10

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.

Platform Miro
Duration60–75 min
OutputSigned stakeholder brief
Study Evidence

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

TemplatePurposePrimary audience
1. Behavioral Design Brief (one-pager)Summarises mode diagnosis, selected mechanism, psychological evidence, ethical rationale, success measure ; in plain languagePM; client lead
2. Nudge Rationale CardPer-feature card specifying why this specific nudge for this specific user state, with one supporting study quoteEngineering; QA; design review
3. Ethics Sign-off DocumentCaptures five-question audit outcome, intensity level, named sign-off rolesEthics reviewer; legal; compliance
4. Dark Pattern Exclusion RecordProfessional 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
Step 09 of 10

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.

Platform Miro
DurationVariable
OutputAnnotated design spec

The synthesis canvas

Each feature-level design decision is a node. Every node carries six required annotations drawn from earlier steps.

AnnotationSourced fromWhat it records
Mode diagnosisStep 3Which of the six modes this feature serves
Bias → NeedStep 4Which bias is operating; what unmet need the feature addresses
MechanismStep 5Which of the 23 mechanisms is implemented and why
Intensity + EthicsStep 7Level 0/1/2 and audit sign-off
Dual-process targetStep 4Respects 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
Step 10 of 10

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.

Platform Miro
DurationOngoing post-launch
OutputNES + adoption decision
Study Evidence

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

NES = (CTR × Conversion × Engagement + Satisfaction) − (Bounce ÷ 100) − (Intrusiveness ÷ 5)
Clicks ÷ impressions
Target actions ÷ sessions
Time (s) × elements (normalised)
Post-task Likert
Sessions < 10s ÷ total
Ceiling < 3.0 for pass
Floor > 3.5 for pass
NES score
Intrusiveness
Ceiling < 3.0
Autonomy
Floor > 3.5

Decision rule

Three conditions, all must hold

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

ConditionContentPurpose
Control (L0)No embedded nudge; plain interfaceBaseline measurement
Treatment A (L1)Single selected mechanism from Step 5Isolate mechanism contribution
Treatment B (L2)Staged multi-mechanism from Step 9Measure incremental benefit (only after L1 validated)

Metrics Collected

CategoryMetricSourceThreshold
EngagementClick-Through Rate (CTR)AnalyticsCompare across conditions
EngagementConversion RateAnalyticsCompare across conditions
EngagementEngagement Score (time × breadth)AnalyticsCompare across conditions
EngagementBounce RateAnalyticsLower is better
BehavioralAdherence RateSelf-report + logsCompare across conditions
BehavioralSustained Use Intention (Likert 5)Post-session questionnaireHigher is better
BehavioralHabit Formation Potential (SRHI-adapted)Post-session questionnaireHigher is better
Perceptual / EthicalPerceived Intrusiveness (Likert 5)Post-session questionnaireCEILING < 3.0 (reverse-coded)
Perceptual / EthicalPerceived Autonomy (Likert 5)Post-session questionnaireFLOOR > 3.5
Perceptual / EthicalSatisfaction Score (Likert 5)Post-session questionnaireHigher 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)
Reference

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.

The five-step cognitive design spine

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).

Reference

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 critical dual-process mapping

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.

Reference

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

Categorical exclusions in health contexts

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).

Reference

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.

Attention & salience
Attentional bias Salience bias Priming effect Mere exposure Primacy & recency Spotlight effect
Affect & social
Affect heuristic Halo effect Herd instinct Authority bias Appeal to majority Reciprocity bias Image motivation
Anchoring & framing
Anchoring Default effect Framing effect Contrast effect Decoy effect Status quo bias
Loss & scarcity
Loss aversion Scarcity bias Optimism & overconfidence Hyperbolic discounting Peak-end effect Placebo effect Availability heuristic Accent fallacy

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.

Decision overload
Ambiguity aversion Choice aversion Decision fatigue Decision inertia Information bias Middle-option bias
Commitment & memory
Commitment bias Sunk-cost fallacy Endowment effect Hindsight bias Choice-supportive bias Confirmation bias Selective perception
Temporal & risk
Present bias Procrastination Intertemporal choice Risk aversion Conjunction fallacy Gambler's fallacy Regression to the mean
Reasoning & meta
Correspondence bias Mental accounting Denomination effect Diversification bias Distinction bias Representativeness / stereotypes Messenger effect Social desirability Simulation heuristic Decoupling
Using the bias library

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.

Reference
Figma Community · CC BY 4.0

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.

Pg
Contents
Instances
Used in step
01
Cover & navigation. Framework overview, component index, domain index, library usage notes.
Step 6 entry
02
Spark components. 8 mechanisms × 4 domain variants = 32 annotated instances. Motivational framing, identity affirmation, social proof, gamification, and others.
32
Step 6
03
Facilitator components. 7 mechanisms × 4 domain variants = 28 annotated instances. Defaults, simplified workflows, autofill, inline scaffolding.
28
Step 6
04
Signal components. 8 mechanisms × 4 domain variants = 32 annotated instances. Behaviorally triggered prompts, ambient cues, progress alerts, warnings, feedback loops.
32
Step 6
05
Worked examples. Ethical vs. dark-pattern side-by-side: countdown timer case, streak-loss case, competitive leaderboard case. Each with mechanism-based analysis.
6 pairs
Steps 6, 7
06
Ideation workspace. Empty canvas with guide-rails and annotation-ready frames for designer customisation.
Step 6

Component annotation schema

Every component carries the same annotation block in the Figma sidebar:

FieldExample
Mechanism nameHealthy default — daily goal pre-set
Trigger categoryFacilitator
Primary biasStatus quo bias, default effect
Compatible modesModes 1, 2, 3
Dual-process targetSystem 1 (automation); S2 reassured by visible opt-out
Ethical riskLow (if opt-out visible and goal reflects user intention)
Study 1 evidenceP61: "It was already set up but I could easily change it. It felt like it respected that I know what I need."
Ethical red flagHIGH 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.

Using the library

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.

Reference

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.

StepFramework sectionStudy 1 linkStudy 2 linkStudy 3 link
1. OnboardingProcedural scaffoldIntentionality GapProcess alignment validation
2. Journey mapA, EDomain-specific barrier profilesDiscovery compressionJourney map as core activity
3. Mode diagnosisAMechanism-state-timing interactionDiagnostic tool absenceTraffic-light card deck (Theme 2)
4. Bias mappingA, DIdentity-threat reactance (mindfulness)Invisible Hand ProblemBias vocabulary translation
5. Nudge selectionBDomain-differentiated trigger preferenceMechanism overestimation correction23-mechanism library structure
6. Figma libraryB, EDomain-specific component variantsTooling gap (Gap 5)Annotation schema validated
7. Ethics auditCPerceived intrusiveness thresholdEthics by IntuitionFive-question checklist (Theme 1)
8. StakeholderToolkitClient Pressure TrapStakeholder template set
9. Design synthesisAllDomain-specific guidanceUser-goal primacyDomain extensions (Theme 3)
10. NES evaluationCNES formula validated empiricallyMeasurement Blind SpotUser-wellbeing integration

Framework statement

The thesis in one sentence

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.