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Segmenting Adult Web Users into Meaningful Age Categories
Segmenting Adult Web Users into Meaningful Age Categories
What are the 4 Most Useful Age Categories
What are the 4 Most Useful Age Categories
The Problem
The Problem
How Old is Old
How Old is Old
How Old is Old
How Old is Old
The Influence of Age and Experience on Data Entry Czaja and Sharit,
The Influence of Age and Experience on Data Entry Czaja and Sharit,
Age, Luminance and Print Legibility Charness and Dijkstra, 1999
Age, Luminance and Print Legibility Charness and Dijkstra, 1999
PAST RESEARCH
PAST RESEARCH
Study 1
Study 1
Study 2
Study 2
Study 3
Study 3
Old Defined
Old Defined
Cognitive and Perceptual Training by Older and Younger Adults Mead and
Cognitive and Perceptual Training by Older and Younger Adults Mead and
Young vs
Young vs
How Old are Your Participants
How Old are Your Participants
Introduction
Introduction
Human Factors Journal
Human Factors Journal
Results
Results
Longitudinal vs
Longitudinal vs
Chronological Age
Chronological Age
Age and Experience Relationships Sri Kurniawan, Jason Allaire and
Age and Experience Relationships Sri Kurniawan, Jason Allaire and
Longitudinal vs
Longitudinal vs
Cross-Sectional vs
Cross-Sectional vs
Studying the Effects Aging
Studying the Effects Aging
World Record Times personal
World Record Times personal
Abilities and Age
Abilities and Age
Six Ages of Humans Pirow, 1994
Six Ages of Humans Pirow, 1994
Running Example
Running Example
Correlation of Track and Field Performance with Chronological Aging
Correlation of Track and Field Performance with Chronological Aging
General Decline in Older Adults
General Decline in Older Adults
Abilities and Age Woolf, 1998
Abilities and Age Woolf, 1998
Common Age-Related Changes in Vision
Common Age-Related Changes in Vision
Age-Related Changes in Vision
Age-Related Changes in Vision
Comfortable Listening Levels Coren, 1994
Comfortable Listening Levels Coren, 1994
Results
Results
Hearing Comfort Level by Age
Hearing Comfort Level by Age
Primary Mental Abilities Schaie, 1958
Primary Mental Abilities Schaie, 1958
Primary Mental Abilities Shaie, 1972
Primary Mental Abilities Shaie, 1972
Segmenting Adult Web Users into Meaningful Age Categories
Segmenting Adult Web Users into Meaningful Age Categories
Reaction Time Fozard, 1990
Reaction Time Fozard, 1990
Normal Distributions by Age
Normal Distributions by Age
Normal Distributions by Age Slower Means
Normal Distributions by Age Slower Means
Normal Distributions by Age Slower Means and More Variability
Normal Distributions by Age Slower Means and More Variability
Longitudinal Analysis of Age-Related Slowing Fozard, et
Longitudinal Analysis of Age-Related Slowing Fozard, et
Results
Results
Aging and Computer
Aging and Computer
Cognitive Abilities and Job Performance
Cognitive Abilities and Job Performance
Performance on Choice Reaction Time and Typing Tasks
Performance on Choice Reaction Time and Typing Tasks
Aging and Errors Rabbitt, 1990
Aging and Errors Rabbitt, 1990
Results
Results
100 Meters Record by Age world-masters-athletics
100 Meters Record by Age world-masters-athletics
Mile Run Records by Age home
Mile Run Records by Age home
High Jump Records by Age world-masters-athletics
High Jump Records by Age world-masters-athletics
Shot Put Records by Age world-masters-athletics
Shot Put Records by Age world-masters-athletics
Common Web-based Tasks
Common Web-based Tasks
Comparing Age Groups Koyani, Bailey, Ahmadi, Changkit and Harley, 2002
Comparing Age Groups Koyani, Bailey, Ahmadi, Changkit and Harley, 2002
Comparing Age Groups 20-30, 61-70, 71-80
Comparing Age Groups 20-30, 61-70, 71-80
Interventions
Interventions
Mechanisms of Human Aging
Mechanisms of Human Aging
Cognitive Correlates of Human Brain Aging Coffey, et al
Cognitive Correlates of Human Brain Aging Coffey, et al
Age-Related Gray and White Matter Changes  Longitudinal Resnick, et
Age-Related Gray and White Matter Changes Longitudinal Resnick, et
Brains Gray and White Matter
Brains Gray and White Matter
Brains Gray and White Matter
Brains Gray and White Matter
Determining Gray vs
Determining Gray vs
Age-Related Gray and White Matter Changes  Cross-Sectional Ge, et al
Age-Related Gray and White Matter Changes Cross-Sectional Ge, et al
Gray Matter
Gray Matter
Does Loss of Brain Tissue Accelerate as People Get Older
Does Loss of Brain Tissue Accelerate as People Get Older
Is Cognitive Decline Normal
Is Cognitive Decline Normal
Chromosomes
Chromosomes
Chromosomes
Chromosomes
Genes
Genes
Damaged Genes = Cognitive Decline Lu, et al
Damaged Genes = Cognitive Decline Lu, et al
Proposed Age Categories
Proposed Age Categories
Possibly More Important
Possibly More Important

: Segmenting Adult Web Users into Meaningful Age Categories. : Bob Bailey. : Segmenting Adult Web Users into Meaningful Age Categories.ppt. zip-: 815 .

Segmenting Adult Web Users into Meaningful Age Categories

Segmenting Adult Web Users into Meaningful Age Categories.ppt
1 Segmenting Adult Web Users into Meaningful Age Categories

Segmenting Adult Web Users into Meaningful Age Categories

Robert W. Bailey, Ph.D. Computer Psychology, Inc. bob@webusability.com 801-201-2002

2 What are the 4 Most Useful Age Categories

What are the 4 Most Useful Age Categories

3 The Problem

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

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

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 Entry Czaja and Sharit,

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

7 Age, Luminance and Print Legibility Charness and Dijkstra, 1999

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 occupants age To determine whether making changes to ambient light levels might improve the reading performance of older adults (intervention)

8 PAST RESEARCH

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

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

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

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

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 Adults Mead and

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

14 Young vs

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)

15 How Old are Your Participants

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

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

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

Results

Classification HF P&A Older 58-76 62-82 Middle-aged 40-59 41-57 Young 19-35 19-30

19 Longitudinal vs

Longitudinal vs

Cross-Sectional Studies

20 Chronological Age

Chronological Age

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

21 Age and Experience Relationships Sri Kurniawan, Jason Allaire and

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 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

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

Cross-Sectional vs

Longitudinal

24 Studying the Effects Aging

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 Times personal

World Record Times personal

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

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 Humans Pirow, 1994

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

28 Running Example

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 Aging

Correlation of Track and Field Performance with Chronological Aging

Fung and Ha, 1994

Correlation Female Male 400 meters .98 .98 1500 meters .97 .96 200 meters .95 .97 800 meters .94 .98 5000 meters .94 .96 100 meters .92 .94 High jump .88 .91 Discus .83 .78 Shot put .81 .79 Javelin .74 .94

30 General Decline in Older Adults

General Decline in Older Adults

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

31 Abilities and Age Woolf, 1998

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., Alzheimers)

32 Common Age-Related Changes in Vision

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

Age-Related Changes in Vision

34 Comfortable Listening Levels Coren, 1994

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

35 Results

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

Hearing Comfort Level by Age

37 Primary Mental Abilities Schaie, 1958

Primary Mental Abilities Schaie, 1958

38 Primary Mental Abilities Shaie, 1972

Primary Mental Abilities Shaie, 1972

39 Segmenting Adult Web Users into Meaningful Age Categories
40 Reaction Time Fozard, 1990

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)

41 Normal Distributions by Age

Normal Distributions by Age

42 Normal Distributions by Age Slower Means

Normal Distributions by Age Slower Means

43 Normal Distributions by Age Slower Means and More Variability

Normal Distributions by Age Slower Means and More Variability

44 Longitudinal Analysis of Age-Related Slowing Fozard, et

Longitudinal Analysis of Age-Related 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

45 Results

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

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)

47 Cognitive Abilities and Job Performance

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

Performance on Choice Reaction Time and Typing Tasks

49 Aging and Errors Rabbitt, 1990

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)

50 Results

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 Age world-masters-athletics

100 Meters Record by Age world-masters-athletics

org

52 Mile Run Records by Age home

Mile Run Records by Age home

hetnet.nl

53 High Jump Records by Age world-masters-athletics

High Jump Records by Age world-masters-athletics

org

54 Shot Put Records by Age world-masters-athletics

Shot Put Records by Age world-masters-athletics

org

55 Common Web-based Tasks

Common Web-based Tasks

Typing Mousing Linking Paging Using widgets Scrolling Reading etc.

56 Comparing Age Groups Koyani, Bailey, Ahmadi, Changkit and Harley, 2002

Comparing Age Groups Koyani, Bailey, Ahmadi, Changkit and Harley, 2002

Ages 20-30 with Ages 71-80

57 Comparing Age Groups 20-30, 61-70, 71-80

Comparing Age Groups 20-30, 61-70, 71-80

58 Interventions

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

Mechanisms of Human Aging

60 Cognitive Correlates of Human Brain Aging Coffey, et al

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

61 Age-Related Gray and White Matter Changes  Longitudinal Resnick, et

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

62 Brains Gray and White Matter

Brains Gray and White Matter

63 Brains Gray and White Matter

Brains Gray and White Matter

64 Determining Gray vs

Determining Gray vs

White Matter

65 Age-Related Gray and White Matter Changes  Cross-Sectional Ge, et al

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

66 Gray Matter

Gray Matter

67 Does Loss of Brain Tissue Accelerate as People Get Older

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

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

Chromosomes

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

70 Chromosomes

Chromosomes

71 Genes

Genes

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

72 Damaged Genes = Cognitive Decline Lu, et al

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

73 Proposed Age Categories

Proposed Age Categories

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

74 Possibly More Important

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)

Segmenting Adult Web Users into Meaningful Age Categories
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