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APPLIED RESEARCH
SUMMARY
rPresents a new set of 20 heuristics for
evaluating Web sites for older adults users
rPresents a new, more richly nuanced model of
older adults as Web users and a new
methodology of persona-based, task-based
heuristic review
New Heuristics for
Understanding Older
Adults as Web Users
DANA E. CHISNELL, JANICE C. (GINNY) REDISH, AND AMY LEE
INTRODUCTION
As we think about accessibility issues, we must
also consider that if we are lucky, we will live
long enough to encounter at least some of the
limitations that come with age. Although we
know that being an older adult is much more than the sum
of one’s disabilities, we know, too, that age-related
changes in vision, coordination, and cognition do influence
the ease or difficulty with which people are able to use
technologies such as the World Wide Web.
According to the Pew Internet and American Life
Project, in 1996, only 2 percent of American adults 65 and
older were online, as were 58% of people ages 50 to 64. By
2003, those numbers had gone up to 32% and 61%, respec-
tively. In the U.S., the percentage of people 65 and older
who go online jumped by 47% between 2000 and 2004
(Fox 2004).
The figures in Canada are similar: as of 2003, about 25%
of households with people 65 and older and 59% of house-
holds with people 55–64 were online. The percentage of
Canadians age 65 and older who are online has more than
doubled in the past four years (Statistics Canada 2004).
Similar shifts are going on all over the world. Accord-
ing to a 2003 report by Forrester Research, about 20 percent
of European seniors had access to the Web at the time of
their survey. In addition, the number of people age 55 and
older going online increased 50% from mid-2000, up from
about 10 million to more than 15 million at the end of 2002
(Reitsma, Torris and vanKruijskik 2003). Older adults in
France and Spain seemed to be holding back compared
with those in Sweden, where about 50% are online; the
Netherlands, with about 40%; and the United Kingdom,
with about 29% online (Reis 2005).
As the Web-using population grows, many people in
Web audiences may be older than we realize. Most have
special needs, whether they admit it or not. And the re-
search we reviewed shows that this audience is highly
diverse in terms of ability, Web expertise, life experience,
and attitude—much more so than younger audiences
(Chisnell and Redish 2004; Chisnell and Redish 2005a).
But Web sites that these older adults go to are usually
developed by people who are much younger, who have
had greatly different experiences both offline and online,
who have learned about the Web at a different time in life
and in greatly different ways. So an important question to
ask is, How well do typical Web sites that older adults go
to work for them? That was the overarching question that
drove the study we are reporting here.
THE PROJECT
In 2004, AARP (a nonprofit, nonpartisan organization with
more than 35 million members in the United States for
people age 50 and over) commissioned an expert review of
50 Web sites to learn how well they support older adults.
AARP’s mission statement says that it is “dedicated to en-
hancing quality of life for all as we age, leading positive
social change and delivering value to members through
information, advocacy and service” (http://www.aarp.org/
about_aarp/aarp_overview/a2002–12-18-aarpmission.html). For
the purposes of our research and this article, “older adult” and
“older user” refer to people who are age 50 and older.
The first two authors of this article were co-principal
Manuscript received 16 April 2005; revised 31 July 2005;
accepted 2 August 2005.
Volume 53, Number 1, February 2006
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investigators of the study; the third author was the AARP
project monitor and reviewer.
The goals for the project included the following.
rSee how typical Web sites are working for older us-
ers.
rIdentify common usability and design issues specific
to older users.
rShow examples of designs or design elements that
work well and that do not work well for older users.
rProvide guidance to designers and developers of
Web sites who have older users in their audiences.
We did this study in three phases.
rWe reviewed recent research literature (2000–2004)
from many fields related to user experience, interac-
tion design, information architecture, visual design,
information design, and usability studies. We also
reviewed articles about aging and cognition that in-
cluded important research about memory loads and
mental models and the ways that those areas relate
to human factors. All of the literature we reviewed
focused specifically on older adults, although they
differed in their definitions of “older adult.”
rWe developed heuristics, personas, and tasks for the
review, and a method for doing persona-based, task-
based heuristic review that would allow us to evalu-
ate many sites in a relatively short time in a highly
realistic way.
rWe used the personas, tasks, and heuristics to re-
view 50 Web sites. Our goal was to review sites that
many older adults use regularly, but that were not
designed specifically for older adults. Only one of
the sites was developed specifically for older adults,
in that case (http://www.medicare.gov) for people
65 and older.
THE CHALLENGES
The goal of reviewing 50 Web sites to evaluate how well
they worked for older adults seemed straightforward
enough. But there were several constraints and challenges
we had to deal with throughout the project.
Current models of older adults focus specifically on
age, occasionally controlling for poor vision, loss of mem-
ory, and physical difficulty with motor control. That’s not a
rich enough model to account for the reality of the great
diversity within the older population.
Existing heuristics and guidelines didn’t take into ac-
count factors important to improving the performance and
experience of older adults as they use the Web. Some of
the heuristics that practitioners have been using to evaluate
Web sites were created to evaluate software. Most of the
heuristics available don’t take into account people with
different abilities. For example, Nielsen’s “Ten usability
heuristics” (Nielsen and Molich 1990) seem to assume that
all users are fit physically and cognitively as they focus on
basic, high-level user interface issues. On the other hand,
Morrell and colleagues (2003) have created guidelines that
assume that all older adults are limited by some level of
disability. And the guidelines we found for evaluating Web
sites for older adults concentrated on Web sites developed
specifically for older adults rather than sites for general
audiences that include older adults.
Traditional heuristic evaluation uses a checklist ap-
proach, asking whether a site complies with the require-
ments of each heuristic in a list. The method typically
uncovers many, many minor problems and does not pro-
vide an easy way to separate major problems from minor
ones. The problem is that people don’t use sites in this way.
We had to come up with an efficient, valid, and defensible
method for reviewing 50 Web sites without exhaustively cat-
aloging every issue on every page of every one of the sites.
Time and budget were limited. Although we all believe
strongly that the only way to really know whether a site
works well for a given group of users is to have represen-
tatives of that group try out the site through usability test-
ing, neither time nor budget allowed us to do usability
testing for such a large group of sites. We had to find a
methodology that would approximate as closely as possi-
ble the user-based, task-based emphasis of usability testing
with us (the usability specialists) “channeling” the users
(that is, making observations through personas).
In fact, we had done earlier usability testing for AARP.
In 2003 and 2004, we met more than 90 older adults in
various AARP usability tests. We published the findings
from those tests at the STC Annual Conference in 2004 in a
session called “Communicating with older audiences” (Lee
and Chisnell 2004). The research that we reviewed for the
2004–2005 project confirmed and clarified the patterns of
behavior and performance that we had seen in those tests.
What we learned in the usability tests and in our review of
the research informed our work in this project, for which
time and budget did not allow us to do usability testing.
THE AARP MODEL FOR SEGMENTING OLDER ADULT AUDIENCES
As we started reviewing the research, it became clear that
there are many definitions for “older adult.” In the dozens
of books, studies, presentations, papers, and articles that
we reviewed, there was no agreement on who comprises
this population. The ages included varied considerably.
The level of age-related problems in vision, memory, and
other abilities of the people in the studies also varied
widely. Researchers controlled—or tried to control—for
different variables, and many realized the difficulty of
achieving those controls.
The diversity of an audience that ranges in age from 50
into the 90s is huge. The differences in terms of ability are
extremely difficult to categorize since there are many ways
APPLIED RESEARCH
New Heuristics for Understanding Older Adults as Web Users Chisnell, Redish, and Lee
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Volume 53, Number 1, February 2006
in which vision, cognition, and motor skills diminish with
age. And we know that although many older adults
(“older” meaning 50–74) and those described as “old-old”
(age 75) are just now coming online, many who are 50
have been using computers for years for both personal and
professional purposes. Several of the authors in our litera-
ture review commented on the issues of studying and
designing for such a diverse audience.
Stereotyping older adults and oversimplifying by de-
signing or writing to the least able does not always benefit
all users (Battle and Hoffman 2004; Hawthorn 2003; Lip-
pincott 2004; Theofanos and Redish 2005; White, Jerrams-
Smith, and Heathcote 2001) and could alienate some (Haw-
thorn 2003; Morrell and colleagues 2003). As Hawthorn
(2003) found,
Firstly, it is almost impossible to gain properly represen-
tative samples. In fact, given the variability inherent in
the older population, techniques that produce average
results misrepresent rather than inform. (39)
Wright (2000) concurs, concluding, “When conducting user
tests it is not necessarily the case that age is the most
important characteristic on which people should be
matched” (41).
Developing a new model with four dimensions
From the research that we reviewed and our own experi-
ences in usability studies, we realized that issues encoun-
tered by older adults were not specific only to their age.
The chronological measure “age” was not necessarily mean-
ingful alone. A more relevant model of older users situates
users along four dimensions: age, ability, attitude, and apti-
tude. Thus, we propose a model, which we call the AARP
model, with a scale for each of four attributes (see Figure 1).
Age This dimension includes both chronological and
experiential age, along with maturity level, life events and
experiences (for example, various jobs, not just the most
recent; military service; marriage, divorce, and children;
places lived), and education level (including when it was
achieved).
Ability This dimension considers degrees of physical
and cognitive limitations or restrictions, ranging from those
requiring little remediation up to needing assisted living
care (Theofanos and Redish 2005; Jacko and colleagues
2002).
Ap tit ud e This dimension addresses expertise with com-
puters and the Web, which is more relevant than straight
measures of experience (Chadwick-Dias, McNulty, and
Tullis 2003; Chadwick-Dias, Tedesco, and Tullis 2004).
Attitu d e This dimension is measured between positive
and forward looking, risk-taking and experimental; and
negative, fearful, or diffident. It conisiders confidence lev-
els and emotional need for support from another human
being (Gregor, Newell and Zajicek 2002; Hawthorn 2003;
Kantner and Rosenbaum 2003).
Placing personas in the AARP model
AARP had previously developed eight personas, based on
data from its marketing, knowledge management, and user
experience groups. These personas represent different
groups within AARP’s 35 million members. In this project,
we used two of AARP’s eight personas: Matthew and Edith.
We chose these two because they represented a broad
range of age, abilities, and Web expertise. Figure 2 details
Matthew’s and Edith’s characteristics.
When we situate Matthew and Edith in the AARP
model, we see dramatically how they differ. Figure 3 shows
the two personas on the four dimensions of the model.
Ideally, perhaps in another project, we would create
specific assessments for each of the factors to add rigor to
the model. For now, we have placed our personas intu-
itively, based on the information in the personas.
Matthew is more able than Edith, so sites that are
complex may be easier for Matthew to use than they are for
Edith. Some sites may be much more difficult for Edith if
they don’t follow conventional interaction practices or if
they use computer and Web jargon. Edith’s generally pos-
itive attitude may help her cope, however: she may be
willing to explore a little bit to find what she needs. Mat-
thew is confident enough to experiment with trying differ-
ent links, but he isn’t a patient person.
The AARP model that we developed acknowledges the
diversity of the older adult population. Many different re-
search studies pointed us to aspects that should be in-
cluded in this model, but no one had yet put them all
together into a model that could be used for assessing the
older adult Web-using audience, for designing Web sites
Figure 1. Four attributes for segmenting “ older users” into
more realistic groups for Web site design.
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with them in mind, or for planning usability studies. We
suggest that this model can help others better understand
their older adult users and thus help them make wise
choices about appropriate content and functionality for
their Web sites.
This model is important to the methodology we ap-
plied in the project because it helped us predict how the
personas we used would behave and perform on the Web
Figure 2. Characteristics of the personas used in the study.
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sites we wanted to review, and more importantly, how the
two personas’ experiences would be different. (For more
about the AARP model and how to use it, see Chisnell and
Redish 2005b.)
We turn now to the focus of this article: the heuristics
that we derived from our literature review and the way that
we applied the heuristics in this study.
THE HEURISTICS
Concluding that the older adult audience is highly diverse
in terms of age, ability, aptitude, and attitude, we wanted to
create heuristics that practitioners could use to evaluate
Web sites with the four factors in mind on any Web site.
What are heuristics?
Jakob Nielsen and Rolf Molich originated the methodology
for heuristic evaluation (1990). According to Niel-
sen’s www.useit.com,
Heuristic evaluation is a usability engineering method
for finding the usability problems in a user interface
design so that they can be attended to as part of an
iterative design process. Heuristic evaluation involves
having a small set of evaluators examine the interface
and judge its compliance with recognized usability
principles (the “heuristics”).
Wikipedia (2005) provides an excellent summary of the
concept:
Heuristic is the art and science of discovery and inven-
tion. The word comes from the same Greek root
(‘
) as “eureka,” meaning “to find”. A heuristic
for a given problem is a way of directing your attention
fruitfully to a solution. It is different from an algorithm
in that it merely serves as a rule of thumb or guideline,
as opposed to an invariant procedure. Heuristics may
not always achieve the desired outcome, but can be
extremely valuable to problem-solving processes. Good
heuristics can dramatically reduce the time required to
solve a problem by eliminating the need to consider
unlikely possibilities or irrelevant states....
In psychology, heuristics are simple, efficient rules of
thumb that people use to make decisions, typically when
facing complex problems or incomplete information.
Heuristic evaluation of the sort we did differs from an
“expert review,” which is a well-established and much
older method in which experts review using the heuristics
in their heads. Here we make the heuristics and underlying
questions overt. In doing this review, we limited ourselves
to the issues raised in our heuristics. We might have made
many other comments about the sites if we had been in
“expert review” mode.
Why did we create a new set of heuristics?
As we designed the project, we informally gathered sets of
heuristics and guidelines that we already knew about. We
found that
rAvailable heuristics and guidelines didn’t take into
account factors important to improving the perfor-
mance and experience of older adults as they use
the Web.
rSome of the heuristics that practitioners have been
using to evaluate Web sites were created for soft-
ware. For example, there are software heuristics for
implementing accelerators (ways to speed up inter-
action for advanced users) and for including help
and documentation. Neither of these applies to most
public Web sites.
rMost of the heuristics available don’t really take into
account people with different abilities. Since older
adults have a wide range of physical and cognitive
abilities that may or may not limit their use of, en-
joyment of, and success with Web sites, it is impor-
tant to consider those issues as well as their exper-
tise with computers and the Web.
rOther guidelines we found for evaluating Web
sites for older adults concentrated on Web sites
for which older adults are the target audience. We
focused instead on sites for general audiences that
include older adults. There are, of course, many
more of these sites than those that focus exclu-
sively on older adults. If they are not easy for
older adults to use, those potential users are miss-
ing out—and the organizations are missing a huge
potential market. We wanted heuristics that we
could apply to all sites where older adults might
be relevant users.
Figure 3. Two personas along each of the four dimensions.
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How do these heuristics differ from others?
Our heuristics are focused on usability and performance
issues that older adults often have when using Web sites.
We looked at several other sets of heuristics to get ideas
about workable models
rNielsen’s “Ten usability heuristics” (http://www.
useit.com/papers/heuristic/heuristic_list.html)
rTec-Ed’s heuristics for evaluating user interfaces (un-
published)
rRedish’s heuristics for information-rich Web sites
(unpublished)
rThe National Institute on Aging and the National
Library of Medicine’s checklist, “Making your Web
site senior friendly” (http://www.usability.gov/check-
list.pdf; http://www.nlm.nih.gov/pubs/staffpubs/od/
ocpl/agingchecklist.html)
rCzaja and Lee’s summary of interface design guide-
lines for older adults (Czaja and Lee 2003)
We borrowed elements of these ways of presenting heu-
ristics to develop the form of our heuristics.
Most heuristics and guidelines are too broad or too
general. To actually use them, we must know more about
what to look for. Therefore, in our heuristics set, each
statement (for example, “Use adequate white space”) is
followed by operationalizing questions (for example, “Is
there line space of at least 2 pixels between clickable
items?” and “Is body text broken up with appropriate and
obvious headings?”). We discuss all of our heuristics and
their operationalizing questions in the next section, “Heu-
ristics for evaluating design for older adults.”
We found this approach of elaborating the general
heuristics with specific questions to be especially useful
because we were developing and using heuristics that
apply to an audience with diverse skills and abilities. The
questions point to the specific issues that the research
shows or predicts older adults will have.
What caveats should you keep in mind?
We offer three caveats for our heuristics.
1. Our focus is not on Web sites designed specifi-
cally for and about seniors. It is on Web sites of all
types, from search engines to e-commerce sites, that
older adults are likely to visit but that were not specifi-
cally developed only for older adults.
2. We are focused on older adults, but many of our
heuristics may be important for all users. As we drew the
heuristics from research about older adults, we noticed
that many of the issues raised were important to all users
and show up often in lists of general heuristics for good
design. Thus, our findings may illuminate areas where
good design for older adults is good design for everyone.
However, that would remain to be tested with real users
of all age groups.
3. Our heuristics are not a complete set of require-
ments for good design. We concentrated on issues that
the research indicates are of particular importance to
older adults. We did not include heuristics relating to all
issues that might be important to all users. Thus, in eval-
uating or developing any specific site, you should use
the heuristics in this document in conjunction with other
heuristics and guidelines, especially those that are spe-
cialized for the type of site you are working on (for ex-
ample, Web application/software, information-rich Web
sites, e-commerce sites, and so on).
HEURISTICS FOR EVALUATING DESIGN FOR OLDER ADULTS
Our heuristics were derived from our review of the re-
search on Web site design and older adults (Chisnell and
Redish, 2004). We summarized our review from several
fields into four areas for our heuristics: interaction and
navigation, information architecture, presentation or visual
design, and information design.
Note that this list does not include heuristics about
trust, security, credibility, privacy, and other affective is-
sues. Although these are important issues for older adults,
we did not focus on them in our review of the literature,
and so, we did not include them in our heuristics.
Interaction design: Designing the
way users work with the site
The navigation schema for a Web site and its information
architecture are tightly bound. Both are driven by designers
understanding clearly who the users are and what tasks
they want to accomplish on the site. Any processes repre-
sented in the navigation of the site must match how users
think of that process. Placement and labels of navigation
elements must feel “natural” and come to hand at the time
that the user expects to use them to perform a step in the
process. In addition, these elements or “widgets” must behave
predictably, consistently. Unfortunately, some consistency in
interaction design has been purposely ignored for the sake of
“design” on many, many Web sites. A notable case in point is
violating the convention of underlining links.
The following are the heuristics we derived in the
category of interaction design.
1. Use c on v en ti on a l in te r act io n e lem en t s.
1.1. Does the site use standard treatments for links?
1.2. Is link treatment the same from section to section
within the site?
2. Mak e o bvi ou s wh at is c lic ka bl e an d w h at is n o t.
2.1. In lists of bulleted links, are the bullets clickable?
2.2. Are command and action items presented as but-
tons?
2.3. Do buttons and links show that they have been
clicked?
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2.4. Are buttons clearly labeled?
2.5. If there is an image on a button or icon, is it
task-relevant?
2.6. Do graphic buttons avoid symbols that will be
unfamiliar to older adults who have low computer
and Web expertise?
2.7. Is there a visible change (other than the cursor
changing) when the user “points” to something
clickable with his or her mouse?
3. Mak e cl ick ab le i tem s ea sy t o ta rget a n d h it .
3.1. Are buttons large enough to easily see the image
or text on them—at least 180 22 pixels?
3.2. Is the area around buttons clickable?
3.3. Is there enough space between targets to prevent
hitting multiple or incorrect targets?
3.4. Do buttons and links enlarge when the rest of the
text size is increased?
4. Min im iz e ve rtic al s cr o llin g ; e lim in at e h o r izo n ta l
sc r o lli n g.
4.1. Does the site work at the resolution at which the
user would typically view the site without hori-
zontal scrolling?
4.2. Do pop-ups and secondary windows open wide
and long enough to contain the content without
the need for scrolling?
4.3. For scrolling lists, for example, a list of all the states:
rAre checkboxes used rather than drop-down
(a menu that drops down when requested
and stays open without further action until the
user closes it or chooses a menu item) or
pull-down menus (a menu that is pulled
down and that stays available as long as the
user holds it open)?
rIf not, are drop-down menus used rather than
pull-down menus?
5. En su r e th a t th e Ba ck b u tto n b eh a ves p r e dic ta bl y.
5.1. Does the Back button appear on the browser
toolbar on every page?
5.2. Does clicking the Back button always go back to
the page that the user came from?
6. Let th e use r sta y i n con t r ol.
6.1. Is there no rolling text that goes by automatically?
6.2. Does the site use static menus (a click leads to
another page) rather than “walking menus” (ex-
posing a sub-menu on hovering the mouse over
the label)?
6.3. If there are walking menus, do they expand on a
click (rather than a hover)?
6.4. Are the sub-menus timed to stay open for at least
5 seconds or until they’re clicked?
7. Pr o vi d e cle a r fe e db a ck o n a ct io n s .
7.1. Are error pages descriptive, and did they provide
a solution to the user?
7.2. Are confirmation pages clear?
8. Provid e feed b ac k in oth e r m o d es in a d dition to
visu al.
8.1. Are captioning and/or meaningful alternative text
provided for images, video, and animation?
8.2. Does the site support haptic pointing devices
(such as the Logitech iFeel mouse that vibrates
when the cursor goes over user interface elements
such as links)?
Information architecture: Organizing the content
Lou Rosenfeld and Peter Morville (2002) define informa-
tion architecture as:
1. The combination of organization, labeling, and
navigation schemes within an information system.
2. The structural design of an information space to
facilitate task completion and intuitive access to con-
tent.
3. The art and science of structuring and classifying
Web sites and intranets to help people find and manage
information.
4. An emerging discipline and community of practice
focused on bringing principles of design and architec-
ture to the digital landscape. (4)
Much of information architecture concerns taxono-
my—dividing and classifying content into categories—
but the issues of information architecture are larger than
that.
There are two common questions about information
architecture that affect all users but affect older adults with
cognitive limitations most severely.
rShould a Web site’s organization of topics (its hierar-
chy) be broad (lots of top level options) or deep
(few top level options that have many available cate-
gories within)? This question touches on the user’s sense
of orientation while navigating through a Web site.
rIs redundancy in links good? That is, are more
choices in a cross-linked hierarchy helpful for find-
ing entry points to content?
These questions are answered in heuristics we derived
in the category of information architecture.
9. Mak e th e str u ct ur e of th e Web site a s visible as
p o ss ib le .
9.1. Does the site use a directory list format (a list of
links) for listing topics (such as Yahoo!, http://
www.hhs.gov, or http://www.firstgov.gov do)?
9.2. Does the site use cross-references to related topics
and redundant links?
9.3. Is the site hierarchy as broad and shallow as pos-
sible?
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10 . Cle a r ly la b el co n t en t ca te go r ie s; a ss is t r e co gn i-
ti o n a n d r e tr i ev al r a th e r th a n r e ca ll .
10.1. Are labels descriptive enough to make it easy to
accurately predict what the content will be under
each topic category?
10.2. Do labels and links start with different, distinct,
and relevant key words?
10.3. Are labels useful and understandable each on
their own?
10.4. Do labels reflect language that older adults are
familiar with?
11 . Im p le m en t t h e s h al lowe st p o ss ib le in fo r m at ion
h i er a r ch y .
11.1. Are important, frequently needed topics and
tasks closer to the surface of the Web site?
11.2. Are related topics and links grouped and la-
beled?
11.3. Do labels and category names correspond to
users’ tasks and goals?
11.4. Do paths through the information architecture
support user’s tasks and goals?
11.5. Is the path for any given task a reasonable length
(2–5 clicks)?
11.6. Is the path clear of distractors and other obstacles
to reaching task goals?
11.7. Are there a few, helpful cross-referenced links
that are related to the current task goal?
11.8. Do redundant links have the same labels?
12 . In cl ud e a s ite m ap a n d l in k t o it fr o m ev er y p a ge.
12.1. Is there a site map?
12.2. Is the site map linked from every page?
12.3. Does the site map provide a quick overview of
the whole site (rather than descriptions of the top
level choices, a rehash of the main navigation or
a list of every single topic on the site)?
Visual design: Designing the pages
Designing the visual aspects of a Web site takes into ac-
count form, content, arrangement, light (or contrast), and
color. It includes all of the visual elements on a page.
Effective visual design depends on the context of the user
and the context within the Web site. According to the
Microsoft Software Developers Network (Microsoft 2004)
design specifications and guidelines, “a graphic element
and its function are completely interrelated. A graphical
interface must function intuitively—it should look the way
it works and work the way it looks.”
Some of the recent and relevant research about visual
design for older adults centers on type size and legibility
but there is also much here about layout and visual search-
ing. The research is important to Web designers, technical
communicators, accessibility experts, and user experience
professionals because the compensation measures for one
part of the older adult audience may not work for other
parts of the older audience –or for younger audiences.
Here are the heuristics we derived in the category of
visual design.
13 . Mak e p a ge s e as y to sk im o r sc an .
13.1. Are pages clean looking and well organized (ver-
sus cluttered or busy)?
13.2. Is there a clear visual “starting point” to the page?
13.3. If pages are dense with content, is content grouped
or otherwise clustered to show what is related?
13.4. Is it easy to tell what is content and what is
advertising?
13.5. Do task-supporting keywords stand out?
13.6. Are images relevant to, and supportive of, the
text content?
13.7. If there are videos or animated sequences, do
they support specific goals or tasks?
14 . Make e le m e n ts on th e p a ge e asy to rea d .
14.1. Is the default type size 12-point or larger?
rIf not, is there an obvious way on the page
to increase the type size?
rIf not, does changing the type size in the
browser enlarge all of the text?
14.2. Is the type size on pull-downs and drop-down
menus the same size as the text content? Does it
change when the user increases the type size?
14.3. Are headings noticeably larger than body con-
tent (18- or 24-point)?
14.4. Is sans serif type used for body content?
14.5. Are headings set in a typeface that is easy to
read?
14.6. Are there visual cues to direct users’ attention to
important items that are in the left and right
columns?
15 . Visu a lly g r ou p r e la te d to p i cs .
15.1. Is the amount of information—sparse, dense, or
in between—appropriate for the audience and
type of site?
15.2. Are the most important and frequently used top-
ics, features, and functions, close to the center of
the page rather than in the far left or right mar-
gins?
15.3. Are task-related topics grouped together?
15.4. Are frequently used topics, actions, and links
“above the fold”?
16 . Mak e s u r e te x t an d b a ck gr o u n d c o lo r s co n t r as t.
16.1. Are text and interaction elements a different color
from the background (not just a different hue)?
16.2. Do the colors that are used together make infor-
mation easy to see and find?
16.3. Are clickable items highlighted differently from
other non-clickable highlighted items?
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16.4. Are multiple types of highlighting minimized on
each page?
17 . Use ad equ a te w h ite sp ac e.
17.1. Are there visual cues in the layout of the page that
help users know there is more content “below the
fold”?
17.2. Is there at least 2 pixels of line space between
clickable items?
17.3. Is body text broken up with appropriate and
obvious headings?
Information design: Writing
and formatting the content
Saul Carliner (2002) tells us that information design is the
act of “preparing communication products so that they
achieve performance objectives established for them.” He
continues:
Although graphic design and document design are im-
portant aspects of it, information design has a much
broader focus than the appearance of information. Its
ultimate focus is on the effectiveness of that information.
That’s why human factors and usability, as well as
human performance technology, are fundamental is-
sues in this discipline.
Although the Pew Internet and American Life Project
(Fox 2004) reports that more than half of the older adult
Web users they surveyed said they have gone online for no
particular reason (54%), they also report that older adults
who use the Web do product research (66%), purchase
items (47%), make travel reservations (41%), visit govern-
ment Web sites (60%), look up religious and spiritual in-
formation (26%), and do banking online (20%). They have
tasks and goals in mind when they log on.
We derived the following heuristics in the category of
information design.
18 . Mak e it e as y t o fin d t h in gs o n th e p a ge q ui ck ly.
18.1. Is the amount of text minimized; is only neces-
sary information present?
18.2. If there are introduction paragraphs, are they
necessary?
18.3. Are instructions and messages easy to recognize?
18.4. Is there liberal use of headings, bulleted lists, and
links to assist skimming?
18.5. Do bulleted lists have the main points and im-
portant keywords at the beginning of each item?
18.6. Do links have meaningful labels?
18.7. Are buttons labeled clearly and unambiguously?
18.8. Do button and link labels start with action words?
19 . Focu s th e wr itin g o n au dien c e an d p ur p os e.
19.1. Is the content written in active voice, directed to “you”?
19.2. Are sentences short, simple, and straightforward?
19.3. Are paragraphs short?
19.4. If humor is used, is it appropriate?
19.5. Are headings, labels, and captions descriptive of
associated content?
19.6. Are conclusions and implications at the top of a
body of text, with supporting content after? (in-
verted pyramid)
20 . Use th e u se r s’ la n guage ; m i n im ize jar go n an d
te ch n ica l ter m s.
20.1. Does the site use words that most older adults
know?
20.2. If there are technical words or jargon, are they
appropriate for the level of domain expertise that
the audience has?
20.3. If there are new or technical terms, does the site
help users learn what the terms mean?
20.4. Are concepts and technical information (such as
safety and effectiveness information about a pre-
scription drugs) written in plain language?
20.5. Are instructions written in plain language?
20.6. Is the reading level appropriate for the capabili-
ties of the audience and their literacy in the topic
area? Is it easy to draw inferences and to under-
stand the implications of text?
THE METHODOLOGY: HOW WE USED THE HEURISTICS
Typically, heuristic evaluations are conducted using the
heuristics as a checklist against which products are as-
sessed. We took a different approach. We reviewed the
sites through personas who represent major parts of the
older adult audience and performed tasks that they would
be likely to do.
In the checklist methodology, on every page of a Web
site, evaluators look for violations of each heuristic. The
evaluators generally don’t take into account the abilities
and expertise of the users or of different types of users.
Often, evaluators don’t take typical tasks into account. A
heuristic evaluation can be system-oriented rather than
task- and user-oriented.
In our methodology, we made observations “through”
our two personas while we performed tasks as though we
were the people the personas represented. Our methodol-
ogy is based on a deep understanding of users (as perso-
nas) and their goals. It is more realistic than the checklist
methodology because people who go to a Web site don’t
audit it; they use it to do tasks.
Using personas keeps the evaluators user-centered,
whereas typical heuristic evaluations often become system-
focused or rule-focused. After assuming the character of
one of the personas to do tasks on Web sites, we then as
usability specialists reviewed the observations made “by”
the persona to see how those comments related to each
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heuristic. With our approach to heuristic evaluation, eval-
uators can feel more confident that they are evaluating the
correct functionality at the right level and not focusing on
many minor issues that are not going to significantly affect
users.
Letting the personas drive the detailed tasks
Instead of assigning specific tasks as in a typical usability
test or the types of tasks we usually agree on with the
client in a heuristic evaluation of one specific site, we let
the personas select the tasks within broad categories and
within our list of 50 sites. Thus, our technique had
elements of the broad, open-ended usability testing that
Jared Spool and others use in some of their usability
research.
We used this more open-ended task-based technique
because we were reviewing 50 sites, not just one, and we
had to do it within a limited time and budget. It also has the
advantage of being realistic. Our personas acted as real
users probably would, moving from task to task and site to
site based on individual goals, individual needs, and ele-
ments of sites that attracted their interest.
The heuristics came into play as we (as our usability
specialist selves) went back through the observations
that the personas made as they performed tasks, noting
which heuristics were relevant to the observation and
how the persona would score the observation for those
heuristics.
“Channeling” the personas
The personas, Matthew and Edith, were much richer than
the typical user profiles we have worked with in the past.
Using the characteristics we knew about each of them, we
tried to think like them as we reviewed the sites. The
observations we recorded in our data sheets are written in
the voice of the persona, not the voice of the usability
specialist. In the guise of our personas, we made observa-
tions that were much like the “think aloud” verbal com-
mentary that we typically get from participants in a usabil-
ity test, thus, “channeling” the personas. Matthew and Edith
became real personalities with relationships, habits, and
emotions beyond what was scripted in their original per-
sona descriptions.
As we worked in the guise of our personas, we ex-
tended the personas in an organic way. For example, Mat-
thew visited Weather.com because he had plans at his
country house on the weekend and wanted to know
whether he would be able to be outdoors. Edith lives in
Florida and was not as concerned about weather-
dependent activities outside of hurricane season. Edith
went to genealogy sites because that’s one of her interests.
Matthew’s leisure time, trip planning, and shopping re-
volved around his interest in bird watching.
The methodology
In summary, we followed these steps in our process:
1. Create personas. We selected and ex-
panded two of AARP’s existing eight personas.
2. Assess where the personas fall on the
AARP model. Making this assessment helps evalua-
tors understand how much complexity a persona can
tolerate and how much training and support older adults
might need on a particular Web site.
3. Define high-level tasks that the personas
will perform on different Web sites. We selected five
high-level tasks, which previous research indicated were
common activities for older adults:
rStart the day.
rDo some research about options my doctor has
given me.
rPlan a trip.
rDo the monthly household bookkeeping.
rPlan and do a project, including shopping online
and following up on leisure activities or hobbies.
4. Select Web sites to evaluate that are appro-
priate for the personas to use to carry out the high-level
tasks. We selected 50 Web sites in eight categories that
came from comments participants made in our usability
studies and from research that we reviewed:
rHealth information
rTravel
rShopping
rHealth insurance and prescription drugs
rNews
rSearch engines and portals
rHobbies and interests
rFinancial services and planning
We chose most of the sites for review based on what
participants had told us in earlier usability testing. We also
chose a few of the sites from results of Google searches. As
the study continued, the personas substituted two or three
sites.
5. Perform tasks and record observations.
“Channel” the persona to do tasks that are realistic for
that persona, and as the evaluator keep the heuristics in
mind while recording positive and negative observations
about the site being used. Figure 4 shows the spread-
sheet we used to capture data. Figure 5 shows part of the
spreadsheet with observations recorded. (In step 6, we
reviewed the observations and rated them against the
heuristics.)
As an example of tasks that the personas did, consider
how the persona Edith did the “Start the day” task. She
went to AOL, checked her e-mail, and then went to
CNN.com and checked the news headlines; she also
checked out BBCnews.com because she wanted to know
the British perspective on the U.S. election; and so on.
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6. Rate observations against the heuristics
and questions using a worksheet like the one in Figure
6. Use the questions within each heuristic to specify what
the issues and the successes are. Note that for any given
observation, you may rate it against only one or several of
the heuristics. Table 1 shows the four levels at which we
could rate each observation for the relevant heuristics.
Realistically, people in usability studies notice different
things and have different types of problems. We didn’t run
a usability test, but the personas we used did “notice”
different things sometimes, and they had similar problems
but to different degrees. To measure these levels of perfor-
mance issues, we rated the observations against the heu-
ristics.
After we had each done the first high-level task, each
as a different persona, we reviewed the observations and
ratings from that task to gauge how similar our observa-
tions had been. We found that we had made similar obser-
vations and that we had used a similar approach to work-
ing through the personas and recording comments. Our
ratings were sometimes different, but even that fact was
realistic because the personas were different. As with real
users, the severity of the problems was different for the two
users. For example, Matthew, who is younger and more
computer savvy, might have rated an issue as a serious
problem because he could get past an obstacle or recover
more easily from an error than Edith. Edith, who is older and
much less computer savvy, might have rated the same issue a
task failure because she didn’t know what to do to move on.
Figure 6 shows observations for Matthew as he re-
searched a health condition that he had.
FINDINGS FROM THE HEURISTIC REVIEW OF 50 WEB SITES
All of the findings are reported in Chisnell and Redish
2005a. We selected findings to include here that we
thought would be interesting and useful to the Technical
communication audience.
Understanding the findings
Between them, our two personas used 50 sites, but they did
not both visit all those sites. Edith went to 32 sites; Matthew
to 30 sites. There were 11 sites that they both used. Even on
those 11 sites, however, they did not perform the same
detailed tasks using the same pages and the same steps.
Each of us took a persona through an entire high-level task.
Table 2 shows who acted for which persona in each task.
Figure 4. Data capturing spreadsheet before starting a review.
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Edith worked at a screen resolution of 800 600,
sometimes on a 15-inch flat panel monitor and sometimes
on a 19-inch flat screen monitor. Matthew worked at a
screen resolution of 1,024 768 on both monitors. Edith
used AOL and its browser on the “Start the day” task; Edith
and Matthew both used Internet Explorer for the remaining
tasks.
General findings
Clearly, the Web is a friendlier place to more able, more
expert users like our persona Matthew than it is to people
with visual and motor limitations and less expertise on
computers and the Web like our persona Edith. We had
expected that the same types of sites might be more diffi-
cult for Edith than for Matthew because of her lack of
expertise with computers and the Web, and because of
some age-related ability problems due mostly to having
arthritis in her hands. Those expectations were indeed the
case.
By the end of the first task, “Start the day,” it was clear
that Matthew could perform tasks such as checking e-mail
and reviewing the day’s news headlines on a variety of sites
with relative ease. Edith had much more difficulty. For
example, Edith had a tough time determining what was
clickable and what was not, and found scrolling to be a
problem (perhaps because she set her screen at a lower
resolution).
There was one exception: Health insurance Web sites.
Edith is 73, giving her the privilege of being enrolled in
Medicare. Her experience using Medicare.gov was perhaps
the best of the 32 sites she used. It was the only situation in
which she encountered no task failures and had more
positive observations by proportion than Matthew did on
his equivalent site.
It is important to remember that while each of the
personas evaluated about the same number of Web sites,
they did not evaluate all of the same sites; neither did they
do all of the same tasks on the same types of sites. They did
the tasks they “wanted” to do, so the findings are not
strictly comparable. The outcomes of our methodology
shouldn’t be used as a “report card.” Instead, they should
be used (like a usability test) to provide insight into how a
site is used and to predict where different types of users are
likely to succeed and where they are likely to have prob-
lems.
HOW WELL DO WEB SITES SUPPORT OLDER ADULTS?
Some of the sites included in the study seem to be paying
attention to the older adults in their audiences. Information
Web sites related to health concerns are the most tuned in.
We think that people like Edith and Matthew will find sites
that are like the health information sites we reviewed to be
useful and usable.
Many of the other types of sites were at best difficult,
and at worst agonizing, for Edith, our older, less Web-
expert persona. In her “best” experiences, she had serious
problems or task failures only about a third of the time. For
example, the home page of Chevychasebank.com pre-
sented several issues for Edith. She had extreme difficulty
managing the floating, moving navigation menus, which
she rated as a “serious problem” (see Figure 7).
She also encountered unconventional and inconsistent
link treatments and sometimes low contrast between back-
ground and text. For Edith, unconventional link treatments
like the ones on this site meant that she could not tell what
was clickable, and that fact prevented her from even start-
ing some tasks. On average, on the rest of the sites, Edith
met with serious problems or task failures half of the time.
This level of difficulty diminishes the usefulness and desir-
ability of doing things online like shopping, paying bills,
reviewing retirement accounts, or looking deeper than
news headlines.
Although some types of sites do well at supporting
older adults, these sites are generally those that think of
older adults as a large part of their audience. For example,
health information and prescription drug sites probably
Figure 5. Observations as they are entered in the
spreadsheet.
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expect that most of their visitors are age 50 or older be-
cause that is when many of the conditions they cover begin
to set in. Health information and sites about prescription
drugs represent only 16% of the sites we reviewed (8 of 50).
Types of sites with audiences in a wider age range,
such as travel (7 sites reviewed), shopping (10 sites), and
financial services (8 sites) could do more to support older
adults while still making their sites easier for younger
people, too. For example, implementing consistent link
treatments within sites, including Close buttons on pop-up
windows, and taking a minimalist approach to layout and
content would help older adults avoid confusion and use
sites more efficiently. The same is probably true for
younger users as well.
Younger users are more familiar with the vocabulary of
the Web than older adults are. This fact becomes important
as older adults encounter labels on navigation elements,
buttons, fields, and links that use language that is unfamil-
iar to them and prevents them from inferring what the next
content or step might be if that interaction “widget” is
clicked. (For example, “Bookstore” as a navigation item
when you are already at a bookstore’s Web site; “Add
Drug” when it is unclear what the drug is being added to.)
But the full age range of users for travel, shopping, and
TABLE 1: RATINGS TO MEASURE WHETHER SITES MET HEURISTICS
4No problem Satisfies the heuristic
3Minor hindrance Possible issue, but probably will not hinder this persona/user
2Serious problem May hinder this persona/user
1Task failure Prevents this persona/user going further
Figure 6. Data capturing spreadsheet with observations and ratings against heuristics.
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financial sites would be helped by clearer instructions and
error and confirmation messages, minimizing introduction
text (which studies show, and we have observed, users
rarely read), and task-oriented headings, rather than
Figure 7. Some of the issues that Edith encountered on one banking site were rated “serious problems.” (Screens captured
11 November 2004.)
TABLE 2: WHICH EVALUATORS PERFORMED WHICH TASKS WITH WHICH PERSONAS
Task
Persona/Evaluator
Edith Matthew
Sta r t th e d ay Researcher 1 Researcher 2
Res ea r ch ab o ut m e di cal / h ea lth o p tio n s Researcher 1 Researcher 1
Pl an a t r ip Researcher 1 Researcher 1
Do m o n th ly b oo kk e ep in g Researcher 2 Researcher 1
Leis ur e a cti vit ies o r h o b bies , s h op p in g Researcher 2 Researcher 1
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marketing- or organization-oriented headings. Focusing on
users’ tasks and goals is the best kind of marketing.
Key findings
We have written the findings as if a real person performed
each of the tasks. Keep in mind, however, that Edith and
Matthew are fictional representatives of composite user char-
acteristics. It was simply easier to write the findings as if the
evaluators had observed the personas performing the tasks.
Th e We b is v er y d iffic ul t f or th e le as t e x per t a m on g
old er ad u lts. Although Edith had a high proportion of
positive comments about the travel sites she used—nearly
67% of her observations about travel sites were positive—
there were still three points at which she could not com-
plete tasks on these sites.
Other sites that older people often use, such as search
engines and portals, shopping, news, and financial ser-
vices, all rated low for Edith in terms of positive versus
negative observations. It was on those sites that she had the
most problems. Financial services and planning sites were
the least supportive of Edith’s ability and aptitude. If her
experience reflects the type of issues that others like her
have, it’s a wonder anyone at Edith’s place on the four-
attribute AARP model does their banking online.
An d it is s ti ll fr u s tr a ti n g fo r u se r s w it h m o r e e x p er -
tise . Matthew came on 20 points of task failure and 171
serious problems over 30 sites he used. There were too
many places where Matthew got stuck or gave up—nearly
one for each site he used (0.7). And, although Matthew had
more experience with computers and the Web than Edith,
his lower tolerance for difficulty showed in that he met
with 5 or 6 serious problems on average at each site he
used (5.7). Table 3 shows these figures.
Alth o ugh s ite s a re d oi n g s om e go o d t h in gs , t h er e a r e
st il l t oo m an y o p p o r tu n i ti es f or se r io u s p r o b lem s
an d ta sk failu r es. As Table 4 shows, on 22 of the sites,
neither persona encountered task failures, but on 28 sites
(56%), either one or both of the personas were unable to
complete what they wanted to do.
Only three sites—all of them shopping sites—had no
task failures and no serious problems: Amazon.com,
eToys.com, and LLBean.com. Matthew used Amazon.com
and LLBean.com; Edith used eToys.com. It would be inter-
esting to see whether people like Edith would also have the
same level of success with Amazon.com and LLBean.com.
As Table 5 shows, of Edith’s observations, just over
50% were positive. Of Matthew’s observations, about 73%
were positive. These facts mean that many of the sites
satisfied many of the heuristics for these personas at par-
ticular points in the tasks they did. We did, however, see
issues that made sites or parts of sites difficult and in some
cases impossible for one or both of our personas to work
with successfully.
Many of the sites scored both positively
and negatively on the same heuristic.
A very important and interesting result is that the sites did
not always score consistently across observations and heu-
ristics, even for the same user. We have both positive and
negative observations and scores for the same site for the
same heuristic.
A site may have used industry conventions for showing
unused links, but then not indicate which links have been
clicked. A site may have used industry conventions for
showing links in one part but not in another part. A site
may have had clear writing in one part but not in another.
A site may have provided a clear pathway for the user task
in one section but stymied the user with unclear navigation
in another section.
Here are some specific examples.
rTravel sites grouped and highlighted navigation links
well at the beginning, making it easy to get started.
However, the sites presented search results that
sometimes made it difficult to distinguish content
from advertising. The icons on the home page were
obvious, but on internal pages, there were non-obvi-
ous icons with no help or labeling.
TABLE 3: TASK FAILURES AND PROBLEMS TOTALED
AND THEN AVERAGED PER SITE VISITED
Edith Matthew
Total task
failures
Total serious
problems
Total task
failures
Total serious
problems
113 243 20 171
Aver a ge p e r si te 3.5 7.6 0.7 5.7
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rFinancial services sites provided explanations on some
pages that were plain and simple. In other sections of
the same site, the Web writers assumed more knowl-
edge on the part of the user about the domain.
These types of inconsistencies may come from the
ways that organizations produce and manage their sites,
with different departments permitted to develop their own
Web pages and with no overall editing or requirements for
consistency. Because of these inconsistencies, a site that is
included in the successes for a heuristic in the following
tables may also be included in the failures.
Another interesting result of this study is that while
many sites succeeded at a given heuristic, many did not.
Because our personas did tasks at 50 Web sites, we saw
both successes and failures for many of the heuristics, so
you will see some of the same heuristics in both the success
TABLE 4: NUMBER OF SITES WITHOUT TASK FAILURES
Sites without
task failure
Number of sites
in this category
He a lth i n fo r m a ti on 3 5
He a lth i n su r a n c e an d p r e sc r ip t io n d r ug s 2 6
Tr av el 4 7
New s 0 5
Fin a n cia l s er vi ces an d p lan n in g 3 8
Sh o p p in g 6 10
Po r t als 1 4
Ho b by a n d in t er es ts 3 5
Total 22 50 44%
TABLE 5: TOTAL OBSERVATIONS ACROSS ALL SITES
Ratings
Edith Matthew
Observations Total Percent Observations Total Percent
4 - No p r o b le m 263 343
3 - Min o r h in d r an c e 122 178
To tal fo r 4 a n d 3 385 52.0 521 73.2
2 - Ser i ou s p r o b le m 243 171
1 - Tas k f ail u r e 113 20
To tal fo r 2 a n d 1 356 48.0 191 26.8
To ta l o b s er va t io n s 741 712
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and the failure tables below.
Suc ce sse s a n d s at isf act io n s The most frequently satis-
fied heuristic was number 13, “Make pages easy to skim or
scan.” Twenty-eight sites (although not necessarily the
same 28 sites) satisfied heuristic 14, “Make elements on the
page easy to read,” and heuristic 18, “Make it easy to find
things on the page quickly.” Figure 8 and Table 6 summa-
rize main areas in which sites satisfied the heuristics.
Pr o b le m s a n d fa il u r es Heuristic 14, “Make elements
on the page easy to read,” was one of the most frequently
satisfied, but it was also the most likely to not be met.
Thirteen of the sites failed to satisfy heuristic 14 and heu-
ristic 20, “Use the users’ language; minimize jargon and
technical terms” (which also ranked among the successes).
Figure 9 and Table 7 summarize main areas in which sites
failed the heuristics.
What have we learned?
It is safe to say that most Web sites seeking to serve a wide
audience encompassing many ages, abilities, and aptitudes
fail to support older adults like Edith most of the time. For
people like Matthew, the sites also fall short. Matthew was
more successful than Edith, but he also often met with
difficulties on several types of Web sites.
In this evaluation of sites, we have counted multiple task
failures in types of sites. In several cases, there were multiple
task failures on a single Web site. Our personas were persis-
tent because they were part of a study. But real users probably
encounter one task failure and abandon a site. They may go
to a different site or to the phone. Or they may just give up.
It is difficult to imagine the pain that many older adults
must tolerate to use the Web since Edith encountered 113
task failures and 243 serious problems in the 32 Web sites
that she used. That’s 3.5 times on average per site that Edith
got stuck, met a dead end, or gave up in confusion or
frustration. And 7.6 times on every site—perhaps sepa-
rately from the task failures, perhaps contributing to the
task failures—that Edith had serious problems.
Conclusions
Co n sid er th e d iv er si ty of you r a ud ie n ce . Most of us
think of “diversity” as it relates to ethnicity and culture, but
different age groups have their cultures, too. And your
audience, no matter the age range, has a variety of atti-
tudes, skills, and abilities. You may want to use a model
like the AARP model formally or informally to help you get
a handle on who is using what you produce and how they
might use it.
Pu t y ou r s el f i n t h e p la ce o f y ou r u se r . If you know
enough about the types of users and readers there are in
your audience, you can see through their eyes. Develop
personas that have traits, habits, and personalities. Try your
best to “be” the persona as you evaluate your work and you
will learn how different you are from your users. Just by
writing down observations about Web sites from the point
of view of your user, you should begin to be able to
identify hindrances, problems, and failures, as well as pos-
itive aspects of the site you are reviewing.
Eva lu ate t h e si te by fo llo w in g tas k p a th s. When you
perform real tasks the way a real user would, you follow
paths that most designers don’t think about. For example,
you might not start from the home page, but from a search
engine. Observe how you’re thinking about the task and
how it changes as you progress. Observe how the site
points you in the right or the wrong directions and how
well it supports your expectations. Note where you had
problems and what they were. Then step back and think
about why it might be that you (as your user) got stuck.
Lear n a n d u n d er st an d h e ur is tic s an d gui de lin e s.
Having in your back pocket sets of guidelines and heuris-
tics that are supported by research and are in wide use will
help you support your user-based observations. Heuristics
can help you understand what might be going wrong (or
right) with a site. You can also use these guidelines to test
your observations against when you can observe real users
trying out your work.
Figure 8. Heuristics most frequently satisfied by number of
Web sites.
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TABLE 6: HEURISTICS THAT WERE MOST FREQUENTLY SATISFIED
This
heuristic
Was satisfied on
this number of sites. Notes on the successes
13 33 Pages w ere easy to s k im a n d sca n because they were
well organized, had clear starting points, grouped or
clustered content on the page, and clearly distinguished
advertising from content. Any images included were
relevant to the content and animations and videos
supported user goals and tasks.
14 28 Elem en ts o n th e p age w ere ea sy to r ead because the
type was large and sans serif. In many cases, while there
was no obvious way on the page to change the type size,
changing it in the browser increased the size throughout the
page and across the site. Headings were set in large,
readable type.
18 28 I t w as e as y t o fin d th i n gs o n p ages q u ick ly . The
amount of text was minimal, instructions and messages
were easy to recognize, and headings, lists, and links were
used liberally to assist skimming. Links were labeled well,
as were buttons and fields.
125 Lin ks we r e p re se n te d co n ve n tio n al ly and consistently
throughout the site.
19 22 Wr it in g was fo cu sed o n th e a u die n ce a n d p ur po se,
using active voice, short, simple and straightforward
sentences, and was directed to “you.” Paragraphs were
short. Headings, labels, and captions were descriptive of
their associated content.
10 21 Co n t en t c at eg or i es w e r e cl ea r ly la b el ed to match user
tasks and goals. The labels were descriptive enough to help
the user predict the underlying content, and they were
useful and understandable on their own. The labels also
match language that most older adults are familiar with.
919 Th e st r uc tu re o f th e We b si te w as h igh ly visi bl e. Either
directory-list formats were used, or in hierarchical sites, the
site implemented cross-reference and redundant links
appropriately.
219 It w as o bvio us wh a t was c licka bl e a n d w h at w as n o t.
717 Th er e w as c lear fe ed ba ck o n ac tio n s th e use r to o k.
Error messages and pages were descriptive and provided
solutions that were understandable. Confirmation messages
were useful and clear.
20 14 Sit es s p ok e to u ser s u si n g th eir o wn l an gu ag e,
minimizing jargon and technical terms. They assumed an
appropriate level of domain knowledge, explained new or
technical terms, and expressed concepts or complex
information in plain language.
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Lea r n fr o m t h e m i st ak e s ( an d s u cc es se s) o f o th e r s.
Think about looking at the work of others who are in the
same industry you work in, but also look outside your
sector for examples of work that you can learn from and
borrow from. The full report of this study (Chisnell and
Redish 2005a) shows many examples of successful and
unsuccessful design and content for our older adult audi-
ence that may work for your users, too. You can download
a free copy at http://www.aarp.org/olderwiserwired.
T
C
ACKNOWLEDGMENTS
The authors would like to thank Saul Carliner for very early
feedback on the scope and direction of the article and Susan
Becker for her thoughtful and thorough editing.
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DANA E. CHISNELL, the co-principal investigator and lead
researcher on the project, is an independent user researcher
and usability consultant operating UsabilityWorks in San Fran-
cisco, CA. She has been doing usability, user interface design,
and technical communications consulting and development
since 1982. She is a senior member of the Usability Profession-
als Association, an associate fellow of the STC, and a member
of the San Francisco STC community as well as the Usability
and User Experience and the AccessAbility virtual communi-
tites. She is the assistant to the president for virtual communi-
ties for 2005–2006. Contact: dana@usabilityworks.net.
JANICE C. (GINNY) REDISH is president of Redish &
Associates, Inc. in Bethesda, MD. She helps corporations and
government agencies solve problems in document design and
usability. She is coauthor of A practical guide to usability test-
ing (revised ed., 1999) and User and task analysis for interface
design. A fellow of STC, she is a member of the Washington,
DC community, the Usability and User Experience community,
and several other virtual communities. Contact:
ginny@redish.net.
AMY LEE is the director of customer experience for AARP’s
Web site, http://www.AARP.org. She oversees the overall visual
design and usability of a site that is uniquely targeted to serving
adults over 50. She was co-founder in 1995 of one of Balti-
more’s first Web site design companies. She has been a guest
lecturer at University of Maryland, the University of Baltimore,
and Loyola College in Baltimore, and presented at the 51st STC
Annual Conference in 2004 with Dana Chisnell on “Communi-
cating with older adults.” Contact: ALee@aarp.org.
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