Segmenting Adult Web Users into
Meaningful Age Categories
Robert W. Bailey, Ph.D.
Computer Psychology, Inc.
bob@webusability.com
801-201-2002
What are the 4 Most Useful Age
Categories?
The Problem
• Virtually every study separates adult participants
differently, i.e., designates different age segments
• Without reading each individual study, practitioners do
not know how old "old" is for each researcher
• The goal is to have all researchers, who are doing work
on ‘aging,’ use the same age categories
• Example
–
–
–
–
Young: 20-35
Middle-aged: 36-55
Old: 56-75
Old-old: 76 and over
• What age segments are most useful to practitioners?
How Old is Old?
• It is rumored that Otto von Bismark, Prime
Minister of Prussia in the 1860’s introduced
old age pensions
• In preparation, he asked the mathematicians
to determine the average age of death
• They found that it was “55”
• He said, “We’ll pay pensions at 65”
How Old is Old?
• One prominent medical doctor recently made
these observations on aging
• “Aging begins at 30”
– Organs begin to lose their function
– Increase of heart disease, diabetes, arthritis, etc.
– Bones begin to become brittle
• “Many practicing physicians now refer to the
elderly as those 75 and older, and the ‘old-old’
as those 85 and older”
The Influence of Age and Experience
on Data Entry
Czaja and Sharit, 1997
• Past research - Young people perform reliably better
than older people on speed-related tasks
– Data entry
– File modification
– Inventory management
• This study - Participants were 110 people who performed
a data entry task for three days
– Young - Mean of 29.8 years
– Middle - Mean of 49.4
– Old - Mean of 66.5 (Reliably less computer experience)
• Results
– Young and middle-aged users entered reliably more data than
old users (p<.001)
– No age-related differences with errors
Age, Luminance and Print Legibility
Charness and Dijkstra, 1999
• To survey homes, offices and public places
– To determine existing ambient light levels
– To assess whether ambient light levels in homes vary
with the occupant’s age
• To determine whether making changes to
ambient light levels might improve the reading
performance of older adults (intervention)
PAST RESEARCH
• Study 1 - Older adults (aged 60-83)
– Read serif fonts (Roman) 6% faster than sans serif fonts
– The best reading speeds were attained with 14-point type
• Study 2 - Older adults with an average age of 75
– Read using 14-point Times Roman and 9-point Helvetica
– 14-point times was superior
• Study 3 - Adults over age 50 were more strongly
affected by low light levels than were people
under 50 years of age
Study 1
• Participants were 98 Tallahassee residents
– 31 young (20-38, average 29)
– 33 middle-aged (39-58, average 47)
– 34 older (over 58, average 69)
• Performed five reading tasks
• Results
– The older group
• Used reliably higher light levels
• Read reliably slower than the younger groups
– Adding lighting improved reading speed for all groups
Study 2
• Method
– Visited 51 businesses
– Measured the light level in work areas
– Tested two people with reading tests
• One over 40
• One under 40
• Results
– Offices generally had adequate light levels
– Only older users benefited from increasing the
light level
Study 3
• Method
– Visited 51 public places
– Measured the light level in areas where people
would read
– Tested two people with reading tests
• One over 50
• One under 50
• Results
– The light levels in 71% of the locations were too
low
– Participants over age 50 read slower than those
under 50
“Old” Defined
•
Past research
– 60-83
– Average of 75
– Over age 50
•
These studies
1.
2.
3.
4.
Mean of 66.5
Over age 58 with an average of 69
Over age 40
Over age 50
Cognitive and Perceptual Training
by Older and Younger Adults
Mead and Fisk, 1997
• Investigated the type of information that
should be presented during training
– Young adults - Range of 18-30 (mean = 20)
– Older adults - Range of 64-80 (mean = 69.9)
• The groups showed no reliable differences
on
– Simple reaction time tests
– Corrected vision tests
Young vs. Older Users
• Young adults
– Were more likely to have used an ATM (p<.0001)
– Used computers more often (p<.0001)
– Had higher scores on
•
•
•
•
Perceptual speed (p<.0001)
Reading rate (p<.05)
Reading comprehension (p<.0001)
Working memory capacity (p<.0001)
– Had faster choice reaction times (p<.0001)
• Older adults
– Were better educated (p<.05)
– Had higher vocabulary scores (p<.05)
How Old are Your Participants?
An Investigation of Age
Classifications
Timothy A. Nichols, Wendy A. Rogers,
Arthur D. Fisk, and Lacy D. West
Georgia Institute of Technology
Proceedings of the Human Factors and
Ergonomics Society 45th Annual Meeting
2001
Introduction
• Designers should try to account for age-related
differences in their user populations
• Gathered reported age data from all articles from
two journals
– Human Factors Journal: 1998-2000
– Psychology & Aging: 1995-1999
• Attempted to determine how researchers
segmented their participants by age
Human Factors Journal
• Human Factors Journal reported 131
empirical articles
– 49 (37%) provided no age data at all
– 64 (51%) supplied some information
– 18 (14%) listed a mean, standard deviation
and age ranges
• Psychology & Aging reported 202
empirical articles
Results
Classification
Older
Middle-aged
Young
HF
58-76
40-59
19-35
P&A
62-82
41-57
19-30
Longitudinal vs. Cross-Sectional
Studies
Chronological Age
• Cannot “cause” anything
• Can help in defining the probability of
occurrence of certain events
Age and Experience Relationships
Sri Kurniawan, Jason Allaire and Darin Ellis,
1999
• Examined the relationships among age, web
experience and web ability
• Participants were 600 older adults (average age
of 44.3 years)
• About 45% of the variance in Web ability was
explained by the user’s age and experience
– Web experience - 28% of the variance
– Age - 9% of the variance
– Shared age and experience - 8% of the variance
Longitudinal vs. Cross-Sectional
Studies
• Longitudinal - Compare the same
individuals over time (historical effects)
• Cross-sectional – Individuals are
compared within their age groups
– May belong to different age cohorts
– May have had different life experiences
• The findings from the two types of studies
do not always agree
Cross-Sectional vs. Longitudinal
Studying the Effects Aging
• Longitudinal
– Measures the changes in one group of people over time
– Usually considered superior to cross-sectional
– Can be confounded by
•
•
•
•
Selection bias
Selective attrition
Retest familiarization
‘Historical’ effects (see ‘world record’ times)
• Cross-sectional
– Evaluates for differences across the different age groups
– Can be confounded by
•
•
•
•
Older adults being more cautious (work slower)
Major educational and experience differences
Slowing of the central nervous system over a certain age
Some differences can be the result of testing only survivors (those who have
not yet died)
World Record Times
personal.rdg.ac.uk
1912
1920
1924
1928
1932
1936
1948
1952
1956
1960
1964
10.5 seconds
10.5
10.2
10.2
10.2
10.2
10.2
10.1
10.1
10.0
10.0
1968
1972
1976
1980
1984
1988
1992
1996
2000
2004
9.95 seconds
9.95
9.95
9.95
9.93
9.86
9.86
9.84
9.79
9.78
Abilities and Age
• Data from longitudinal studies will better
measure age changes for those in
– Good health, and
– Stimulating environments
• Data from cross-sectional studies tend to
over estimate loss of most abilities
• Cohort effects (e.g., differences in the
amount of education) usually accounts for
more variance than age-related factors
Six Ages of Humans
Pirow, 1994
• Birth
• Starting age - The earliest age at which a
measured activity can take place
• Competence - The age at which a person has
acquired the skill to perform well
• Optimal - The age at which the person will
perform optimally at the task
• Initial decrease - The age at which the
performance will start to decrease linearly
• Rapid decrease - The age after which the
performance will decrease at an increasing rate
Running Example
Starting
Competence
Optimal
Initial decrease
Rapid decrease
Female Male
2 years 2 years
9
10
22
24
24
29
59
66
Correlation of Track and Field
Performance with Chronological Aging
Fung and Ha, 1994
400 meters
1500 meters
200 meters
800 meters
5000 meters
100 meters
High jump
Discus
Shot put
Javelin
Correlation
Female Male
.98
.98
.97
.96
.95
.97
.94
.98
.94
.96
.92
.94
.88
.91
.83
.78
.81
.79
.74
.94
General Decline in Older Adults
•
•
•
•
Sensitivity of most sensory organs
Attention capacities
Working memory
Speed of motor performance
Abilities and Age
Woolf, 1998
• Reliable decrements can not be found for all
abilities for all persons (until very late in life)
• Decline is most evident where ‘speed of
response’ is involved
• Declines will be evident in most abilities
– For those in their 50s and 60s who live in deprived
environments, and
– For individuals of any age who have severe central
nervous system disease (e.g., Alzheimer’s)
Common Age-Related Changes in
Vision
• Decreased sharpness of vision (visual acuity)
• Decreased ability to focus on near objects
• Decreased ability to focus on objects at varying distances (visual
accommodation)
• Decreased ability to discriminate between certain color intensities
– Especially in the blue-green end of the color spectrum
– The "yellowing" of the lens with age makes blues and greens appear
"washed out" or faded
• Decreased ability to perceive or judge depth
• Decreased ability to focus in low light levels
• Slow responsiveness to changes in light levels (dark to light, and
light to dark)
• Increased sensitivity to glare
• Decreased ability to accurately judge distances
• Increased need for light needed to see objects clearly
Age-Related Changes in Vision
Comfortable Listening Levels
Coren, 1994
• The number of people who have difficulty hearing and
understanding voices increases with age
– General conversations
– Voices on
•
•
•
•
The phone
Television
Radio
Computer
• Procedure
– Used 799 subjects, ranging in age from 17 to 92
– Each
• Listened to a running speech signal
• Identified the level preferred for listening
Results
• The average `most comfortable listening level'
for all participants was 63.4 dB
• They found
– No differences between left and right ears
– No differences between male and female
• Before the age of 40, the most comfortable
listening level increased about 1/3 dB per year
• After the age of 65, the most comfortable
listening level increased about 1/2 dB per year
Hearing Comfort Level by Age
90
Decibels (dB)
85
80
75
70
65
60
55
50
15
20 25
30
35 40
45
50 55
Age
60
65 70
75
80 85
90
Primary Mental Abilities
Schaie, 1958
Primary Mental Abilities
Shaie, 1972
Reaction Time
Fozard, 1990
• Shortens from infancy into the late 20s
• Increases slowly until the 50s and 60s
• Lengthens faster as a person gets into the 70s and
beyond
• Becomes more variable with age
• When troubled by a distraction, older people tend to
devote their exclusive attention to one stimulus and
ignore another (attention)
Normal Distributions by Age
Normal Distributions by Age
Slower Means
Normal Distributions by Age
Slower Means and More Variability
Longitudinal Analysis of AgeRelated Slowing
Fozard, et.al., 1990
• The Baltimore Longitudinal Study of Aging has
been gathering data since 1959
– 1300 adults from 20 to 96 years of age
– Continually evaluated using different measures
• Biographical
• Physiological
• Psychological
• One measure is reaction times
– Simple – Responded to both high (1000 Hz) and low
(250 Hz) tones presented for 3 seconds at 62 dBA
– Disjunctive (choice) – Responded only to high tones
Results
• Reaction time increases with age
– Constant rate of slowing over the adult life
span – appears linear
– Slows from 10-20 milliseconds per decade (12 milliseconds per year)
– Men remain reliably faster than women
• There seems to be a general slowing of
central nervous system functions with
aging
Aging and Computer-based Task
Performance
Sharit and Czaja, 1994
• Of particular interest are age-related changes in
information processing abilities, including the
– Senses
– Cognition processors
– Responders
• There seems to be a general overall slowing in
cognitive tasks
• The hypothesized `slowing factor' for cognitive
tasks is 1:1.6 (young vs. old)
Cognitive Abilities and Job
Performance
• There is little evidence that job
performance declines with age
• Age alone is not a significant predictor of
performance in most actual work activities
• Age effects are
– Smaller for tasks where knowledge is an
important aspect of the task
– Larger for tasks where successful
performance is primarily dependent on speed
Performance on Choice Reaction
Time and Typing Tasks
Aging and Errors
Rabbitt, 1990
• Used a two-choice reaction time task
• Four age groups
–
–
–
–
19-30
50-59
60-69
70-79
• Conditions
– No response to errors
– Corrected each detected error
– Signaled that an error was made (no correction)
Results
• All age groups
– Made the same percentage of errors
– Were equally proficient at ‘automatic’ error detection
– Underestimated the number of errors made (after the
test)
• The 70-79 group ‘signaled’ reliably fewer errors
• The ability to remember errors after the test
declined with age – beginning at age 50
100 Meters Record by Age
Age
10
0
95
90
85
80
75
70
65
60
55
50
45
40
rd
40
35
30
25
20
15
10
5
0
Re
co
Seconds
world-masters-athletics.org
Mile Run Records by Age
Age
80
75
70
65
60
55
50
45
40
rd
9
8
7
6
5
4
3
2
1
0
Re
co
Minutes
home.hetnet.nl
High Jump Records by Age
Age
90
85
80
75
70
65
60
55
50
45
40
9
8
7
6
5
4
3
2
1
0
Re
co
rd
Height (feet)
world-masters-athletics.org
Shot Put Records by Age
Age
10
0
95
90
85
80
75
70
65
60
55
50
45
40
rd
80
70
60
50
40
30
20
10
0
Re
co
Distance (feet)
world-masters-athletics.org
Common Web-based Tasks
•
•
•
•
•
•
•
•
Typing
Mousing
Linking
Paging
Using widgets
Scrolling
Reading
etc.
Comparing Age Groups
Koyani, Bailey, Ahmadi, Changkit and Harley, 2002
Ages 20-30 with Ages 71-80
140
120
Seconds
100
80
20-30
60
71-80
40
20
0
Links
Paging
Widgets
Common Web Activities
Scrolling
Comparing Age Groups
20-30, ‘61-70’, 71-80
140
120
Seconds
100
20-30
80
61-70
60
71-80
40
20
0
Links
Paging
Widgets
Common Activities
Scrolling
Interventions
•
•
•
•
•
•
•
•
Eyeglasses, contact lens, hearing aids
Recall vs. recognition memory
Length and type of training
TFT vs. CRT screens
Intensity (loudness) of auditory signals
Shape of the cursor
Time of day
Accessibility features
Mechanisms of Human Aging
Cognitive Correlates of Human
Brain Aging
Coffey, et al., 2001
• Collected MRI data from 320 volunteers (ages
66-90)
• Compared the results with performance on
– Attention
– Information processing speed, and
– Memory
• The findings suggest a relationship between
age-related changes in brain structure and
declines in attention, psychomotor speed and
memory
Age-Related Gray and White
Matter Changes – Longitudinal
•
•
•
•
Resnick, et al., 2003
Conducted MRIs on 92 non-demented
older adults aged 59-85
Used the baseline, 2 year and 4 year
follow-ups in the BLSA
Found reliable age decreases in both gray
and white matter
There seemed to be slower rates of brain
atrophy in individuals who remained
medically and cognitively healthy
Brain’s Gray and White Matter
Brain’s Gray and White Matter
Determining Gray vs. White Matter
Age-Related Gray and White
Matter Changes – Cross-Sectional
Ge, et al., 2002
• 54 healthy volunteers aged 20 to 86 were
given MRIs
• Findings
– The percent of gray matter and white matter
were reliably less in older (over age 50) adults
– The percent of gray matter decreased linearly
with age – beginning with the youngest
participants
– There was no difference between sexes
Gray Matter
Does Loss of Brain Tissue
Accelerate as People Get Older?
sciencedaily.com, 1998
• Divided patients into three age groups:
– Young-old: 65-74 years old
– Middle-old: 75-84 years old
– Oldest-old: 85-95 years old
• Measured the changes in brain volume with
magnetic resonance imaging (MRI) scans
• The loss of tissue among patients was a
constant 1% or less per year
• Dementia is related to a more rapid brain tissue
loss
Is Cognitive Decline Normal?
Haan, et al., 1999
• Tracked changes in cardiovascular health, diabetes and
cognitive function over a 7-year period
• The people were all 65 or over when recruited
• 70% of the individuals showed no significant decline in
cognitive function (Modified Mini-Mental State Exam)
• The greatest loss of cognitive ability occurred in people
who had
– High levels of atherosclerosis or diabetes, and
– The apolipoprotein E4 gene (ApoE4)
• They were 8 times more likely to show a decline in
cognitive function
Chromosomes
• Humans have 23
chromosomes
• Twenty-two are
numbered in order of
size
– Largest (number 1)
– Smallest (number 22)
Chromosomes
Genes
• Each chromosome
contains genes
• Genes are stretches of
(deoxyribonucleic acid)
DNA that comprise the
recipes for proteins
Damaged Genes = Cognitive Decline
Lu, et al., 2004
• Damaged genes can start in the late 30s and early 40s
in some individuals (i.e., functioning at a reduced level)
• Evaluated patterns of gene expression in postmortem
samples
– Collected from 30 individuals
– Ranged in age from 26 to 106
• Found two groups of genes with altered expression
levels
– Those related to learning and memory
– Those related to gene repair mechanisms
• Conclusion: DNA damage may reduce the expression of
certain vulnerable genes involved in learning, memory
and neuronal survival
Proposed Age Categories
•
•
•
•
Old-old: 75 and older
Older: 60-74
Middle-aged: 40-59
Young: 18-39
Possibly More Important
• Overall level of cognitive activity
• Severe nervous system diseases
– Alzheimer’s
– Parkinson’s
• Circulation-related diseases
– Atherosclerosis
– Diabetes
• Certain medications
• Deprived environment
• Seriously hampered senses
–
–
–
–
Cataracts
Glaucoma
Macular degeneration
Diabetic retinopathy
• Defective genes (DNA)