Why Intentions Do Not Predict Actions
You fully intend to exercise three times this week. You mean it. You've thought about it, planned mentally, feel motivated. Monday arrives. You're tired from work. "I'll go tomorrow." Tuesday: Unexpected meeting runs late. Wednesday: You do go, feel good. Thursday: Back to "tomorrow." By Sunday, you've exercised once instead of three.
Your intention was real. Your prediction was wrong.
This pattern repeats across domains. You intend to eat healthier (but order dessert). You intend to save money (but impulse-buy). You intend to work on important projects (but respond to email all day). You intend to call your friend (but weeks pass).
Research consistently shows: Intentions are weak predictors of behavior.
The correlation between intention and action is typically r = 0.40–0.50 (explaining only 16-25% of variance). That means 75-84% of what determines whether you act comes from factors other than your intention.
Understanding why intentions fail—and what actually drives behavior—is essential for changing habits, predicting outcomes, and designing interventions that work rather than just making people feel temporarily motivated.
The Intention-Behavior Gap
The Problem
Common belief: If people intend to do something, they'll probably do it
Reality: Most intentions don't become actions
Meta-analysis (Sheeran, 2002):
- Reviewed 47 studies across health behaviors (exercise, diet, condom use, cancer screening)
- Average correlation: r = 0.47 between intention and behavior
- R² = 0.22: Intentions explain only 22% of variance in behavior
- 78% of what determines behavior comes from other factors
Webb & Sheeran (2006):
- Reviewed 47 interventions designed to change intentions
- Successfully increased intentions (medium-to-large effects)
- But: Changes in intention had small-to-medium effect on behavior
- Making people intend something doesn't reliably make them do it
Real-world example (Rhodes & de Bruijn, 2013):
- Physical activity study
- 77% of participants intended to exercise regularly
- 35% actually did
- 42 percentage-point gap between intention and action
Why Intentions Don't Predict Well
1. Habit Strength Dominates
Habits: Automatic responses to cues
Intentions: Deliberate plans requiring conscious execution
In moments of action: Habit usually wins
Mechanism:
Cue encountered →
- Habit response: Automatic, fast, effortless
- Intentional response: Requires remembering intention, overriding habit, executing new behavior
Result: Habit executes before intention engages
Study (Ouellette & Wood, 1998):
- Compared prediction power of:
- Past behavior (proxy for habit)
- Intentions
- Frequent behaviors: Past behavior R² = 0.50, Intentions R² = 0.10
- Infrequent behaviors: Past behavior R² = 0.15, Intentions R² = 0.32
For habitual behaviors, past behavior predicts 5x better than intentions
Example: Morning routine
Intention: "I'll meditate every morning"
Habit: Wake → coffee → check phone → shower → leave
What happens:
- Wake up (cue)
- Automatically reach for phone (habit)
- 20 minutes later, realize you forgot to meditate
- Intention was genuine, habit was stronger
2. Present Bias
Intention formation: Usually thinking about future
Behavior execution: Always in present
Problem: Future self and present self have different priorities
Time structure:
When forming intention (Monday):
- Friday workout seems feasible
- Benefits salient (health, fitness, feeling good)
- Costs abstract (just 30 minutes, no big deal)
- Future self seems motivated
When executing (Friday):
- Immediate costs concrete (tired, couch comfortable, favorite show on)
- Benefits distant (health accumulates slowly)
- Present self wants present comfort
- Intention formed by different person (past self)
Temporal discounting:
- Immediate rewards weighted heavily
- Future rewards discounted steeply
- Pattern: Present desires > future intentions
Result: The you who makes plans isn't the you who executes them
3. Environmental Cues Override Intentions
Behavior is cue-dependent.
Environments contain cues that trigger behaviors automatically.
Intentions don't change environmental cues.
Study (Sheeran et al., 2005):
- Measured intention strength
- Measured environmental supportiveness
- Supportive environments: Strong correlation (r = 0.53) between intention and behavior
- Unsupportive environments: Weak correlation (r = 0.21) between intention and behavior
Environment determines whether intentions matter
Example: Healthy eating intention
Your intention: Eat more vegetables, less junk food
Your environment:
- Break room: Donuts every morning (visible, accessible, free, social)
- Healthy options: Cafeteria (requires leaving building, costs money, takes time)
- Vending machines: Everywhere (convenient, immediate)
- Vegetables: Require meal prep (planning, shopping, cooking, time)
Result: Cues for junk food >> cues for healthy food. Intention battles constant environmental triggers for opposite behavior.
4. Vague Intentions Lack Implementation
Vague intention: "I should exercise more"
When? Unspecified
Where? Unspecified
What? Unspecified
How? Unspecified
Problem: Execution requires answers to these questions
In the moment:
- Must decide when
- Must choose where
- Must select activity
- Must figure out how
Each decision point:
- Requires cognitive resources
- Creates opportunity to defer
- Allows rationalization ("Not ideal time/place/activity")
5. Competing Goals
You don't have one intention. You have dozens.
They compete for limited resources (time, energy, attention).
Example intentions (all genuine):
- Work on strategic project
- Respond to emails promptly
- Exercise regularly
- Spend time with family
- Learn new skill
- Maintain social relationships
- Keep house clean
- Read more books
- Get adequate sleep
Problem: Can't do all. Must choose.
In practice:
- Urgent crowds out important (emails beat strategic work)
- Easy beats hard (social media beats skill development)
- Immediate beats delayed (TV beats reading)
- Default beats novel (existing routines beat new habits)
6. Social Desirability Bias
What people say (intention) ≠ What they actually prioritize
Mechanism:
Stated intentions reflect:
- How you want to be perceived
- Your ideal self-image
- Social norms
- What "should" be valued
Actual behavior reflects:
- Real priorities
- True preferences
- Actual constraints
- What you're willing to trade off
Example:
Survey question: "Do you intend to donate to charity this year?"
Response: 80% say "yes" (genuine intention, socially desirable, reflects values)
Behavior: 15% actually donate when solicited
Gap: Stated intention reflected aspiration and self-image. Behavior reflected actual priorities when faced with trade-off (money to charity vs. keep for self).
What Actually Predicts Behavior
Factors More Predictive Than Intentions
If intentions don't predict well, what does?
1. Past Behavior
Best predictor of future behavior: Past behavior
Especially for frequent, habitual actions
Why:
- Habits persist (automatic responses to cues)
- Situations recur (same cues appear repeatedly)
- Infrastructure exists (you know how, have tools/access)
- Momentum (continuing is easier than starting)
Practical application:
Predicting whether someone will exercise next month:
- How often did they exercise last month? (strong predictor)
- Do they intend to exercise next month? (weak predictor)
Hiring:
- What did they accomplish in past roles? (strong)
- What do they intend to accomplish here? (weak)
2. Implementation Intentions
Bridge from intention to action
Standard intention: "I intend to X"
Implementation intention: "When situation Y occurs, I will perform behavior Z"
Key features:
Specific trigger: "When" (situation/time/place)
Specific action: "I will" (concrete behavior)
If-then structure: Links cue to response
Meta-analysis (Gollwitzer & Sheeran, 2006):
- 94 studies, 8,155 participants
- Implementation intentions increased goal achievement rate by 54% (medium-to-large effect)
- Worked across domains (health, academic, environmental, prosocial)
Why they work:
Automatic activation:
- Cue (if) linked strongly to response (then)
- When situation encountered, response activates
- Don't need to deliberate ("Should I...?")
Reduced cognitive load:
- Pre-decided when/where/how
- Don't decide in moment
- Fewer decision points → fewer opportunities to defer
Cue salience:
- Specific "when" means noticing situation
- Vague intention easy to miss opportunity
- Clear trigger harder to miss
Example:
Vague intention: "I'll eat healthier"
- Must continuously remember
- Must decide what "healthier" means in each situation
- Requires vigilance and willpower
- Fails often
Implementation intention: "When I enter break room and see donuts, I will take an apple from my desk drawer instead"
- Trigger clear (enter break room, see donuts)
- Action specified (take apple from drawer)
- Pre-decided (no in-moment deliberation)
- Much higher success rate
3. Environmental Design
Behavior follows path of least resistance
Design environment → shape behavior
Principles:
Increase friction for unwanted behavior:
- More steps → less likely
- Each obstacle reduces probability ~50%
Decrease friction for wanted behavior:
- Fewer steps → more likely
- Make automatic/default → very high probability
Change defaults:
- Default behavior wins 80%+
- Most people don't opt out
- Opt-in vs. opt-out massive difference
Control cues:
- Remove cues for unwanted (out of sight)
- Add cues for wanted (visible, accessible)
Examples:
| Behavior Goal | Environmental Design |
|---|---|
| Reduce phone use | Charge in other room, turn off notifications, delete apps, grayscale screen |
| Eat healthier | Don't buy junk food, prep vegetables (washed, cut, visible), smaller plates |
| Exercise more | Gym on commute route, clothes laid out, workout partner committed, morning default |
| Save money | Auto-transfer on payday, delete shopping apps, unsubscribe marketing emails |
| Focus better | Close email, block websites, phone away, door closed, visible timer |
Why it works:
- Doesn't rely on willpower (design, not discipline)
- Doesn't require remembering (cues trigger automatically)
- Works when tired/stressed (automatic responses persist)
- Sustainable (doesn't deplete)
4. Immediate Context
Moment-to-moment factors often outweigh stable intentions
Contextual factors:
Mood:
- Bad mood → present comfort (ice cream, TV, avoid effort)
- Good mood → more open to delay gratification
Cognitive load:
- Mental exhaustion → defaults win
- Fresh → can override habits
Social situation:
- Others' behavior influential
- Difficult to deviate from group
Time pressure:
- Rushed → heuristics and habits
- Unhurried → deliberation possible
Decision fatigue:
- Late in day → willpower depleted
- Early → self-control higher
Implication: Same person with same intention behaves differently depending on context in moment
5. Commitment Devices
Pre-commitment that constrains future behavior
Types:
Financial stakes:
- Lose money if don't follow through
- StickK, Beeminder (put money at risk)
- Works because loss aversion (hate losing)
Social accountability:
- Public commitment
- Workout partner (letting them down costs)
- Coach/therapist (appointment scheduled)
Advance commitment:
- Schedule appointment (cancellation fee/social cost)
- Prepay (sunk cost motivates attendance)
- Sign contract (commitment public/recorded)
Access restriction:
- Time-lock safe (can't access until designated time)
- Website blockers (can't access distracting sites)
- Give friend item you're avoiding (can't access without asking)
Why they work:
- Raise cost of not following through
- Make intention-behavior gap costly
- Future self constrained by past self's commitment
Bridging the Gap
Making Intentions More Effective
Can't rely on intentions alone.
But can make them more predictive.
1. Be Specific
Replace: "I should X more"
With: "When [specific trigger], I will [specific action]"
Examples:
| Vague | Specific |
|---|---|
| "Exercise more" | "Monday/Wednesday/Friday 7:00am, gym for 30-min workout" |
| "Eat healthier" | "When ordering lunch, choose salad with protein instead of sandwich" |
| "Save money" | "Automatically transfer 15% of paycheck to savings on payday" |
| "Be productive" | "First hour at work (9-10am), work on most important task before checking email" |
2. Reduce Obstacles
Identify what makes behavior hard
Remove or reduce obstacles
Exercise example:
Obstacles: Don't have gym clothes, gym is out of way, don't know workout routine, tired in evening
Solutions:
- Lay out clothes night before (visual cue, reduced friction)
- Choose gym on commute (no extra trip)
- Hire trainer or use app (routine provided)
- Schedule morning (not tired yet)
3. Increase Obstacles for Unwanted Behavior
Add friction
Examples:
- Want to reduce social media → Delete apps (must re-download, added friction)
- Want to avoid junk food → Don't buy it (not in house, requires trip to get)
- Want to focus → Phone in other room (must get up, walk there)
Each obstacle reduces probability ~50%.
Three obstacles → 87.5% reduction.
4. Build Habits, Not Just Intentions
Habits bypass the intention-action gap
Habit formation:
Cue: Consistent trigger (time, place, preceding action)
Routine: Simple action (don't start with hard)
Reward: Immediate positive feedback (track, feel accomplished)
Repetition: Consistent practice (daily better than weekly)
Timeline:
- 18-254 days to form habit (average 66 days, Lally et al., 2010)
- Initially requires effort and intention
- Gradually becomes automatic
- Eventually occurs without intention/willpower
Once habitual: Past behavior predicts strongly, intentions matter little
5. Track and Adjust
Monitor behavior vs. intention
Identify patterns
Process:
- State specific intention
- Track whether you do it
- When you don't, analyze why (obstacle? competing goal? environmental cue?)
- Adjust strategy (remove obstacle, change environment, different time)
- Repeat
Improvement comes from iteration, not perfect initial intention
Implications
For Individuals
Don't trust your intentions:
- Feeling motivated ≠ will follow through
- Intention is necessary, not sufficient
- Need systems, not just motivation
Plan for lazy future self:
- Present self full of good intentions
- Future self tired, busy, stressed
- Design for future self's constraints
Watch behavior, not intentions:
- What you actually do reveals priorities
- Behavior tracks true preferences
- If say X is priority but don't do it → it's not actually priority (or need better systems)
For Organizations
Don't rely on stated intentions:
- Surveys lie (social desirability)
- What people say they'll do ≠ what they do
- Watch behavior, not reported intentions
Test behavior, not ask:
- A/B test reveals preferences better than survey
- Purchase data > purchase intent
- Actual behavior > predicted behavior
Make desired behavior default:
- Opt-out beats opt-in massively
- Auto-enrollment in retirement savings (90%+ vs. 40-60% opt-in)
- Default settings shape behavior (most don't change)
Reduce friction:
- Every additional step reduces completion significantly
- Simplify processes
- Remove obstacles
For Researchers and Policymakers
Measuring intentions ≠ predicting behavior:
- Need actual behavior outcomes
- Intention measures often misleading
- Gap between intention and action is the phenomenon
Interventions should target behavior, not just intentions:
- Education/persuasion changes intentions (somewhat)
- But intentions weakly predict behavior
- Direct behavior change strategies more effective (environmental design, defaults, commitment devices)
Implementation matters more than motivation:
- Most people already intend to do right things (eat healthy, exercise, save money)
- Problem isn't lack of intention
- Problem is intention-to-action bridge
Conclusion: Intentions Are Necessary But Not Sufficient
You can't change behavior without some level of intention.
But intention alone rarely changes behavior.
Key insights:
- Intentions explain only 20-25% of behavior variance (75-80% comes from other factors)
- Habit strength beats intention strength (past behavior predicts 5x better for frequent behaviors)
- Present bias undermines future intentions (planning self ≠ executing self)
- Environment matters more than motivation (cues and friction shape behavior)
- Vague intentions fail (specific implementation intentions work much better, +54% success)
- Competing goals dilute intentions (can't pursue all, defaults win)
- Social desirability inflates stated intentions (say one thing, do another)
What works better:
Implementation intentions: "When X, then Y" (specific trigger + action)
Environmental design: Remove friction for wanted behavior, add friction for unwanted
Commitment devices: Constrain future self through financial/social stakes
Habit formation: Automate behavior through repetition (cue-routine-reward)
Tracking and iteration: Monitor behavior, identify obstacles, adjust strategy
The path forward:
Form intentions (necessary starting point)
But don't stop there:
- Make them specific (implementation intentions)
- Design your environment (remove obstacles, control cues)
- Build habits (automate through repetition)
- Use commitment devices (constrain future self)
- Track and adjust (iterate based on actual behavior)
You fully intend to follow through.
That's great.
Now build the systems that make it actually happen.
References
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Ouellette, J. A., & Wood, W. (1998). "Habit and Intention in Everyday Life: The Multiple Processes by Which Past Behavior Predicts Future Behavior." Psychological Bulletin, 124(1), 54–74.
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About This Series: This article is part of a larger exploration of psychology and behavior. For related concepts, see [Gap Between Thinking and Behavior], [How the Mind Actually Works], [Why Habits Beat Willpower], and [Implementation Intentions Research].