Psychology Foundations

Understanding why patterns work lets you apply them to new situations. These are the research foundations beneath UX practice.

About This Skill

This skill contains research-backed principles only. Each concept includes:

• The original researcher(s)
• Year of key publication(s)
• What the research actually showed
• Limitations or caveats where relevant

1. Dopamine and Anticipation

Researchers: Wolfram Schultz (1990s), Robert Sapolsky Field: Neuroscience

What Research Shows

Dopamine neurons fire in response to prediction of reward, not reward itself. When a reward is expected and received, dopamine levels don’t spike at reward time—they spike at the cue predicting the reward.

Schultz’s experiments with monkeys showed:

• Unexpected reward → dopamine spike at reward
• Expected reward (after learning) → dopamine spike at predictor, not reward
• Expected reward that doesn’t come → dopamine dip (disappointment)

UX Implication

Progress indicators work because they signal approaching reward. The anticipation phase is neurologically active.

Source: Schultz, W. (1998). Predictive reward signal of dopamine neurons. Journal of Neurophysiology.

2. Peak-End Rule

Researchers: Daniel Kahneman, Barbara Fredrickson Field: Behavioral economics, Psychology Recognition: Nobel Prize in Economics (2002)

What Research Shows

In studies of colonoscopies and other experiences, participants rated overall experience based on:

1. The peak moment (most intense)
2. The end moment

Duration had little effect (“duration neglect”). A longer painful experience ending gently was rated better than a shorter one ending abruptly.

UX Implication

• Create one memorable positive peak
• End interactions well
• A graceful error recovery can redeem a frustrating experience

Source: Kahneman, D. et al. (1993). When more pain is preferred to less. Psychological Science.

3. Loss Aversion

Researchers: Daniel Kahneman, Amos Tversky Field: Behavioral economics Recognition: Foundational to Prospect Theory (Nobel Prize 2002)

What Research Shows

Losses loom larger than gains. In experiments, losing $10 felt roughly 2x as bad as gaining $10 felt good. This asymmetry affects decision-making: people take irrational risks to avoid losses.

UX Implication

• Data loss is disproportionately frustrating
• Auto-save, undo, and preservation matter more than features
• Frame choices in terms of what users might lose

Source: Kahneman, D. & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica.

4. Flow State

Researcher: Mihaly Csikszentmihalyi Field: Positive psychology Timeline: Research from 1970s, book Flow published 1990

What Research Shows

Csikszentmihalyi interviewed hundreds of experts (artists, athletes, surgeons, chess players) about their optimal experiences. Common characteristics:

When conditions are met, people report:

• Deep concentration
• Loss of self-consciousness
• Distorted time perception
• Intrinsic reward from the activity itself

Limitations

• Original research was qualitative (interviews, experience sampling)
• “Challenge-skill balance” is hard to operationalize
• Neurophysiological validation is still emerging

Source: Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience.

5. Cognitive Load Theory

Researcher: John Sweller Field: Educational psychology Timeline: Theory developed 1988

What Research Shows

Working memory has limited capacity. Sweller identified three types of cognitive load:

Instructional design should minimize extraneous load to free capacity for intrinsic and germane processing.

UX Implication

• Reduce visual clutter
• Group related information
• Use familiar patterns
• Don’t make users remember across screens

Source: Sweller, J. (1988). Cognitive load during problem solving. Cognitive Science.

6. Miller’s Law (Working Memory Limits)

Researcher: George Miller Field: Cognitive psychology Year: 1956

What Research Shows

Miller’s famous paper “The Magical Number Seven, Plus or Minus Two” found people can hold approximately 7±2 “chunks” in working memory.

Limitations

Important: Modern research suggests the number may be closer to 4±1 chunks for novel information (Cowan, 2001). Miller’s “7” applies to well-practiced, chunked material.

UX Implication

• Limit simultaneous options
• Group items into meaningful chunks
• Don’t rely on users remembering many items

Sources:

• Miller, G.A. (1956). The magical number seven. Psychological Review.
• Cowan, N. (2001). The magical number 4 in short-term memory. Behavioral and Brain Sciences.

7. Serial Position Effect

Researcher: Hermann Ebbinghaus Field: Memory research Year: 1885

What Research Shows

When recalling lists, people remember:

• First items (primacy effect) — transferred to long-term memory
• Last items (recency effect) — still in working memory
• Middle items are poorly recalled

UX Implication

• Put important items first or last
• Don’t bury critical information in the middle
• First impressions and final interactions matter most

Source: Ebbinghaus, H. (1885). Über das Gedächtnis (On Memory).

8. Zeigarnik Effect

Researcher: Bluma Zeigarnik Field: Gestalt psychology Year: 1927

What Research Shows

Interrupted tasks are remembered better than completed ones. The mind keeps incomplete tasks “open” in memory.

Limitations

Caution: Replication studies have been mixed. The effect appears real but smaller and more context-dependent than originally claimed.

UX Implication

• Progress indicators leverage incompleteness
• Unfinished onboarding motivates return
• But: incomplete tasks also create cognitive burden

Source: Zeigarnik, B. (1927). Über das Behalten von erledigten und unerledigten Handlungen. Psychologische Forschung.

9. Choice Overload (Paradox of Choice)

Researchers: Sheena Iyengar, Mark Lepper Field: Decision-making psychology Year: 2000

What Research Shows

The famous “jam study”: shoppers shown 24 jam varieties were less likely to purchase than those shown 6 varieties. More choice led to decision paralysis.

Limitations

Important: Meta-analyses (Scheibehenne et al., 2010) found the effect is smaller and more context-dependent than popularized. Choice overload occurs under specific conditions:

• Unfamiliar domain
• Difficult to compare options
• No clear preference
• High decision stakes

UX Implication

• Reduce options when users lack expertise
• Provide smart defaults
• But: experts may want more choices

Sources:

• Iyengar, S. & Lepper, M. (2000). When choice is demotivating. Journal of Personality and Social Psychology.
• Scheibehenne, B. et al. (2010). Can there ever be too many options? Journal of Consumer Research.

Laws of UX (Quick Reference)

These are practitioner heuristics with varying levels of research backing:

Source: Laws of UX

Key Sources

• Schultz, W. (1998). Predictive reward signal of dopamine neurons.
• Kahneman, D. & Tversky, A. (1979). Prospect Theory.
• Kahneman, D. (1993). When more pain is preferred to less.
• Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience.
• Sweller, J. (1988). Cognitive load during problem solving.
• Miller, G.A. (1956). The magical number seven.
• Cowan, N. (2001). The magical number 4 in short-term memory.
• Ebbinghaus, H. (1885). Über das Gedächtnis.
• Iyengar, S. & Lepper, M. (2000). When choice is demotivating.
• Scheibehenne, B. et al. (2010). Can there ever be too many options?