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
- 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.
- 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:
-
The peak moment (most intense)
-
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.
- 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.
- 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:
Condition Description
Clear goals Know what success looks like
Immediate feedback See results of actions
Challenge-skill balance Task matches ability
Sense of control Autonomy over actions
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.
- 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:
Type Description Reducible?
Intrinsic Complexity inherent to the task No (task-dependent)
Extraneous Load from poor presentation Yes (design target)
Germane Load that aids learning Desirable
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.
- 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.
- 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).
- 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.
- 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:
Law Principle Evidence Level
Hick's Law Decision time increases with options [Research]
Fitts's Law Larger, closer targets are easier to hit [Research]
Miller's Law ~7±2 items in working memory [Research] (with caveats)
Jakob's Law Users expect familiar patterns [Expert] NNg
Aesthetic-Usability Pretty things seem more usable [Research]
Postel's Law Be liberal in input, strict in output [Expert]
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?