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?