Segmenting Adult Web Users into Meaningful Age Categories

1
Segmenting Adult Web Users into Meaningful Age
Categories

• Robert W. Bailey, Ph.D.
• Computer Psychology, Inc.
• bob_at_webusability.com
• 801-201-2002

2
What are the 4 Most Useful Age Categories?
3
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?

4
How Old is Old?

• It is rumored that Otto von Bismark, Prime
  Minister of Prussia in the 1860s 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, Well pay pensions at 65

5
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

6
The Influence of Age and Experience on Data
EntryCzaja 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 (plt.001)
• No age-related differences with errors

7
Age, Luminance and Print LegibilityCharness 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 occupants age
• To determine whether making changes to ambient
  light levels might improve the reading
  performance of older adults (intervention)

8
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

9
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

10
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

11
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

12
Old Defined

• Past research
• 60-83
• Average of 75
• Over age 50
• These studies
• Mean of 66.5
• Over age 58 with an average of 69
• Over age 40
• Over age 50

13
Cognitive and Perceptual Training by Older and
Younger AdultsMead 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

14
Young vs. Older Users

• Young adults
• Were more likely to have used an ATM (plt.0001)
• Used computers more often (plt.0001)
• Had higher scores on
• Perceptual speed (plt.0001)
• Reading rate (plt.05)
• Reading comprehension (plt.0001)
• Working memory capacity (plt.0001)
• Had faster choice reaction times (plt.0001)
• Older adults
• Were better educated (plt.05)
• Had higher vocabulary scores (plt.05)

15
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
16
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

17
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

18
Results

• Classification HF PA
• Older 58-76 62-82
• Middle-aged 40-59 41-57
• Young 19-35 19-30

19
Longitudinal vs. Cross-Sectional Studies
20
Chronological Age

• Cannot cause anything
• Can help in defining the probability of
  occurrence of certain events

21
Age and Experience RelationshipsSri 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 users age and experience
• Web experience - 28 of the variance
• Age - 9 of the variance
• Shared age and experience - 8 of the variance

22
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

23
Cross-Sectional vs. Longitudinal
24
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)

25
World Record Timespersonal.rdg.ac.uk

• 1912 10.5 seconds
• 1920 10.5
• 1924 10.2
• 1928 10.2
• 1932 10.2
• 1936 10.2
• 1948 10.2
• 1952 10.1
• 1956 10.1
• 1960 10.0
• 1964 10.0

• 1968 9.95 seconds
• 1972 9.95
• 1976 9.95
• 1980 9.95
• 1984 9.93
• 1988 9.86
• 1992 9.86
• 1996 9.84
• 2000 9.79
• 2004 9.78

26
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

27
Six Ages of HumansPirow, 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

28
Running Example

• Female Male
• Starting 2 years 2 years
• Competence 9 10
• Optimal 22 24
• Initial decrease 24 29
• Rapid decrease 59 66

29
Correlation of Track and Field Performance with
Chronological AgingFung and Ha, 1994

• 
  Correlation
  Female Male400
  meters .98
  .981500 meters
  .97 .96200 meters
  .95 .97800
  meters .94
  .985000 meters
  .94 .96100 meters
  .92 .94High jump
  .88
  .91Discus
  .83 .78Shot put
  .81 .79Javelin
  .74
  .94

30
General Decline in Older Adults

• Sensitivity of most sensory organs
• Attention capacities
• Working memory
• Speed of motor performance

31
Abilities and AgeWoolf, 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., Alzheimers)

32
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

33
Age-Related Changes in Vision
34
Comfortable Listening LevelsCoren, 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

35
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

36
Hearing Comfort Level by Age
37
Primary Mental AbilitiesSchaie, 1958
38
Primary Mental AbilitiesShaie, 1972
39
(No Transcript)
40
Reaction TimeFozard, 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)

41
Normal Distributions by Age
42
Normal Distributions by AgeSlower Means
43
Normal Distributions by AgeSlower Means and More
Variability
44
Longitudinal Analysis of Age-Related
SlowingFozard, 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

45
Results

• Reaction time increases with age
• Constant rate of slowing over the adult life span
  appears linear
• Slows from 10-20 milliseconds per decade (1-2
  milliseconds per year)
• Men remain reliably faster than women
• There seems to be a general slowing of central
  nervous system functions with aging

46
Aging and Computer-based Task PerformanceSharit
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 11.6 (young vs. old)

47
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

48
Performance on Choice Reaction Time and Typing
Tasks
49
Aging and ErrorsRabbitt, 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)

50
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

51
100 Meters Record by Ageworld-masters-athletics.o
rg
52
Mile Run Records by Agehome.hetnet.nl
53
High Jump Records by Ageworld-masters-athletics.o
rg
54
Shot Put Records by Ageworld-masters-athletics.or
g
55
Common Web-based Tasks

• Typing
• Mousing
• Linking
• Paging
• Using widgets
• Scrolling
• Reading
• etc.

56
Comparing Age GroupsKoyani, Bailey, Ahmadi,
Changkit and Harley, 2002Ages 20-30 with Ages
71-80
57
Comparing Age Groups20-30, 61-70, 71-80
58
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

59
Mechanisms of Human Aging
60
Cognitive Correlates of Human Brain AgingCoffey,
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

61
Age-Related Gray and White Matter Changes
LongitudinalResnick, 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

62
Brains Gray and White Matter
63
Brains Gray and White Matter
64
Determining Gray vs. White Matter
65
Age-Related Gray and White Matter Changes
Cross-SectionalGe, 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

66
Gray Matter
67
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

68
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

69
Chromosomes

• Humans have 23 chromosomes
• Twenty-two are numbered in order of size
• Largest (number 1)
• Smallest (number 22)

70
Chromosomes
71
Genes

• Each chromosome contains genes
• Genes are stretches of (deoxyribonucleic acid)
  DNA that comprise the recipes for proteins

72
Damaged Genes Cognitive DeclineLu, 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

73
Proposed Age Categories

• Old-old 75 and older
• Older 60-74
• Middle-aged 40-59
• Young 18-39

74
Possibly More Important

• Overall level of cognitive activity
• Severe nervous system diseases
• Alzheimers
• Parkinsons
• Circulation-related diseases
• Atherosclerosis
• Diabetes
• Certain medications
• Deprived environment
• Seriously hampered senses
• Cataracts
• Glaucoma
• Macular degeneration
• Diabetic retinopathy
• Defective genes (DNA)