No. 4, October 2004
Use of the Internet for Health Information by the Chronically Ill
Todd H. Wagner, PhD, Laurence C. Baker, PhD, M. Kate Bundorf, PhD, MBA, MPH, Sara Singer, MBA
Suggested citation for this article: Wagner TH, Baker LC, Bundorf MK,
Singer S. Use of the Internet for health information by the chronically ill.
Prev Chronic Dis [serial online] 2004 Oct [date cited].
Available from: URL:
Chronic conditions are among the leading causes of death and disability in
the United States. The Internet is a source of health information and advice for
individuals with chronic conditions and shows promise for helping individuals
manage their conditions and improve their quality of life.
We assessed Internet use for health information by people who had one
or more of five common chronic conditions. We conducted a national survey
of adults aged 21 and older, then analyzed data from 1980 respondents who
had Internet access and who reported that they had hypertension, diabetes,
cancer, heart problems, and/or depression.
Adjusted rates for any Internet use for health information ranged from 33.8%
(heart problems only) to 52.0% (diabetes only). A sizable minority of
respondents — particularly individuals with diabetes — reported that the
Internet helped them to manage their condition themselves, and 7.9% said
information on the Internet led them to seek care from a different doctor.
Use of the Internet for health information by chronically ill patients is
moderate. Self-reported effects on choice of treatment or provider are small but
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Chronic conditions are among the leading causes of death and disability in
the United States (1) and are responsible for a disproportionately large share
of health care use and cost (2). New technologies frequently target
people with chronic conditions with the hope of increasing system efficiencies
and improving patient quality of life. One particularly promising area of
innovation has been consumer-oriented health information on the Internet.
Certain attributes of the Internet make it particularly appealing for patients
with chronic illnesses. The cost of distributing information on the Web is
extremely low, and people in rural areas and those with disabilities can access
the same information as people in urban areas and those with no disabilities.
Also, compared with printed documents, Internet information can be
easily updated to reflect new scientific findings. This has become particularly
useful for patients looking for cutting-edge treatments and new clinical trials
for chronic illnesses such as human immunodeficiency virus (HIV) and cancer.
While the first few generations of Internet sites offering health information
consisted primarily of digitized copies of printed materials, developers were
quick to exploit the Internet’s interactive capabilities. Consumers can now use
the Internet to search for risk-assessment tools, interactive health advice, and
the latest medical news.
Researchers have begun to examine the potential effects of the Internet on
health issues. The low cost of distributing information on the Internet has
prompted some researchers to test whether the Internet could be used as a
disease-management tool. In two studies, high-quality, disease-specific
information was distributed to randomly selected participants, and participants
in control groups received information in the traditional form of a
health magazine or book (3,4). Study results indicated that the Internet was a
better conduit for providing health information. It is not clear, however, which
characteristics of the Internet drive its effect on patient education. One study
compared a group that received tailored information and personalized feedback
via the Internet with a group that received Internet information only and found
few differences between the two groups (5).
In addition to disease management, two other areas of Internet health
information research have attracted attention. First, studies by Jadad et al
(6), Eysenbach et al (7), and Berland et al (8), among others, have shown that
the Internet is saturated with both good and bad health information and that
consumers are not good judges of quality. Second, studies have described how
people are using the Internet for health information. Although the estimates of
how many people use the Internet for health have been heavily debated (9-12), questions
about how a person’s health affects their use of the Internet have not been
investigated in as much depth. A recurring
finding is that people with depression are more likely than people with other
health conditions to use computers to find health information. This finding was
noted as part of a community-wide intervention that provided participants with
self-care books, a telephone advice line, and computerized health information
(13). Compared with participants without depression, participants with depression
reported a higher probability of using all three media. More recently, Haviland
and colleagues analyzed data from the 2001 Healthcare Market Guide survey and
found that people who reported a psychiatric condition (including depression)
were more likely to use the Internet to access disease/wellness information than
people with no chronic health problem (14). Similarly, a recent national survey
by the Pew Internet and American Life Project found that depression, anxiety, or
mental-health issues were among the 10 most frequent health-related search
topics on the Internet (15). But beyond depression, there is little research
from which to identify other emerging themes.
People with chronic conditions have unique needs; this paper investigates
Internet use among respondents who reported having hypertension, diabetes,
cancer, heart problems, and/or depression. We conducted a nationally
representative survey to assess Internet use for health advice and information
by individuals with these chronic conditions. Our analysis focused on
individuals with at least one of five common chronic illnesses: diabetes,
hypertension, cancer, heart problems, and depression. This study addressed three
issues. First, we assessed the extent to which people with any of the five
chronic illnesses used the Internet for health information. Second, we compared
perceptions of the Internet among participants who have one of the five chronic
illnesses. Third, we examined respondents’ self-reported effects of the
information. The sample used in this analysis represents a sub-population of a
previously published paper (9).
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Survey of health and the Internet
We surveyed a sample representing the entire U.S. population aged 21 years
and older. We drew our sample from a research panel of more than 60,000
households; the panel was developed and maintained by Knowledge Networks (KN), a
survey research firm. Using random-digit dialing, KN contacted potential panel
households, offering them free Internet access in exchange for periodic
participation in short surveys. Participants were informed of their rights as
panel members, including the right not to answer surveys or questions. We then
surveyed a random sample of panel members through the MSN WebTV.
The electronic survey was sent to a specific household member. A light on the
WebTV notified potential participants about the survey. KN formatted the survey
for the WebTV to resemble other surveys it sends to panel members. Item
nonresponse for variables analyzed in this paper was less than 2%.
Institutional Review Boards at Stanford University and Research Triangle
Institute approved the survey protocol. KN sent a consent form and the survey to
a sample of 12,878 panel members in late 2001 and early 2002. Those who did not
respond within three days received an e-mail reminder. Two additional e-mail
reminders were sent to nonrespondents. Of the 12,878 persons who were sent a
survey, 2265 (18%) declined consent, 1678 (13%) did not complete the consent
form, and 8935 (69%) provided informed consent and subsequently completed the
survey. Compared with respondents, people who did not complete the survey were
younger on average (49 versus 54 years; P < .001) and more likely to have
a high school education or less (39% versus 49%; P < .001).
A focus of the survey was to assess how people with chronic illnesses were
using the Internet. In the survey, we asked people about five common chronic
conditions: hypertension, diabetes, cancer, heart problems, and depression. We
selected these conditions based on their prevalence and on research by Berland
et al (8). Of the 8935 respondents, 4990 reported one or more of these
We further narrowed our analytical sample because KN had given Internet
access to most of our respondents for the first time, and previously published studies
on health and the Internet had
sampled only people who had obtained Internet access on their own. Thus, of the 4990
respondents, we analyzed data from only the 1980 respondents who had Internet
access prior to participation in KN. In a separate paper, we reported on how all
people with Internet access prior to participation in KN used the Internet for
health (9). In this paper, we focus on people with chronic conditions.
At the time of our survey, the panel recruitment response rate was 41%,
calculated by standards established by the American Association for Public
Opinion Research (16), and the panel attrition rate was 14%. We independently
investigated the generalizability of the KN dataset by comparing disease
prevalence estimates to the 2000 National Health Interview Survey (NHIS). The
questions on cancer were most similar, and the prevalence estimates were 6.2%
for our sample and 6.8% for NHIS. For diabetes and hypertension, our questions
differed from the NHIS questions: we asked about diabetes along with high blood
sugar and hypertension along with high blood pressure, rather than just about
diabetes and hypertension. Prevalence estimates in our sample were 12.3% for
diabetes and 29.0% for hypertension — each approximately five percentage points
higher than the NHIS survey. We also conducted additional comparisons of the
sample to a range of population benchmarks and found results consistent with the
representativeness of the sample. Details of the KN panel and data
generalizability are reported in a technical
appendix (17), and the
questionnaire is available upon request.
Variables and analysis
We first assessed how frequently subjects had used the Internet for health
information in the last year (more than once a week, about once a week, about
once a month, every two to three months, less than every two to three months,
never in the last year). We asked about the frequency with which they had
searched during the past year, and whether they had used the Internet to
communicate about their illness with doctors, other patients, and family or
friends. For subjects who said they had used the Internet to find health
information, participants were asked to respond “agree,” “disagree,” or “don’t
know” to three statements: “it takes too long to find information on the
Internet,” “I cannot trust information I find on the Internet,” and “I can easily
understand the information I find on the Internet.” We excluded the few (2–6%)
who answered “don’t know.”
We asked questions that referred specifically to one of the respondent’s
chronic illnesses. The questions asked whether using the Internet or e-mail 1)
improved understanding of the illness; 2) improved understanding of possible
treatments for the illness; 3) affected the treatments used for the illness; 4)
improved the ability of respondent to manage the disease on his or her own; 5)
led the respondent to seek care from different doctors or health care providers
than respondent otherwise would have; or 6) affected the way respondent ate or
exercised. None of the questions asked respondents to recall what information
they were seeking. Response categories were “strongly agree,” “agree,” “disagree,” and
“strongly disagree”; we collapsed these four into “agree” and “disagree.” These six
questions were asked only if people reported searching the Internet for health
The independent variable of interest was the subject’s chronic condition. We
asked respondents if a doctor had ever told them that they had 1) high blood
pressure or hypertension; 2) diabetes or high blood sugar; 3) cancer; or 4)
heart problems, such as a heart attack, coronary heart disease, angina, or
heart failure. We also asked whether they had ever had, or had a doctor or other
health care provider tell them that they had, depression. For diabetes,
respondents could answer “yes,” “no,” or “borderline” (we recoded borderline as
“yes”); for other items, they could answer “yes” or “no.”
We used two analytical approaches for comparing the chronic conditions.
First, for the dependent variables that did not refer to a specific condition,
we created a classification system for the chronic conditions. People could
report more than one chronic condition. For most analyses, we classified
respondents into one of seven mutually exclusive study groups: hypertension only
(n = 505), diabetes only (n = 147), cancer only (n = 59), heart problems only (n
= 73), depression only (n = 552), two chronic conditions (n = 451), and three or
more (n = 190). We tried developing categories representing different
combinations of conditions (e.g., diabetes and hypertension), but making more
combinations was intractable and preliminary analysis indicated that doing so
would provide little additional information. We note when significant
differences between other chronic conditions exist.
We used another approach for questions on the effects of Internet use on the
respondent’s chronic condition. For people who had more than one chronic
condition, we chose one of the conditions randomly and asked all questions about
only that one. Again, the chronic condition was the primary variable of
interest. But because the questions specifically referred to a chronic
condition, we compared hypertension, diabetes, cancer, heart problems, and
We oversampled veterans and older adults (aged more than 50). KN calculated
post-stratification sampling weights to reduce the bias due to nonresponse and
to reduce sampling variance for characteristics highly correlated with
demographic and geographic totals. KN calculated these weights so that the
weighted sample cells matched those of the December 2001 U.S. Census Bureau’s
Current Population Survey. The weights were based on age, veteran status,
sex, race/ethnicity, geographic region, metropolitan status, and education.
We weighted all bivariate and multivariate analyses to account for our
oversamples of older adults and veterans. The five chronic conditions differed
by demographic characteristics that were also associated with using the
Internet. Therefore, we used multivariate logistic regression models in which we
controlled for education (high school or less, some college, or some graduate
school), sex, and age (under 50, 50–64, 65–74, or 75+ years). We treated all
control variables as sets of dummy variables to allow for nonlinearities. When
testing for statistical significance, we corrected the standard errors for the
complex design effects. We conducted all analyses in Stata 8 (StataCorp LP,
College Station, Tex).
Although the odds ratios are informative, we were interested in the absolute
and relative differences across the chronic conditions. Therefore, we used the
logistic regressions to compute predicted probabilities, which we then
multiplied by 100 to reflect percentages, using the characteristics of a
respondent who had average values of the control variables. In the tables, we
present the predicted probabilities based on our multivariate models in which we
hold age, education, and sex constant. (The full regression results are
presented in Supplemental Tables.)
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Table 1 shows the summary statistics for the sample. People who reported
depression only were the largest group (27.9% of the sample). People who had
hypertension only constituted the second-largest group (25.5%); people who had
two chronic conditions made up the third-largest group (22.8%). The smallest
group was people who had cancer only (3.0%).
Of the 641 respondents with more than one chronic condition, 201 (31.4%)
reported having hypertension, 171 (26.7%) reported having depression, 116
(18.1%) reported having diabetes, 88 (13.7%) reported having heart problems, and 66
(10.3%) reported having cancer (data not shown). Combinations of two and three chronic conditions
comprised 93.0% of this group; 39 (6.1%) people reported four chronic
conditions, and only six (1.0%) reported having all five conditions.
Frequency of Internet use
Among all individuals who had one or more of the five chronic conditions,
45.9% reported using the Internet to seek health information or advice in the
past year (Table 2). On average, 11.0% reported at least monthly use. Internet
use varied by chronic condition. Those who had hypertension only, cancer only,
or heart problems only reported relatively low use (33.8%–42.9%); those who
had diabetes only, depression only, or two or more chronic conditions were more
likely to use the Internet (47.6%–52.0%).
People with depression only, cancer only, and three or more chronic
conditions were more likely to use e-mail or other Internet-based services to
communicate with heath professionals than people with hypertension only or heart
problems only (P < .05). Using the Internet to communicate with family or
friends was the most common form of communication, ranging from approximately
26.6%–41.7%, except for people with diabetes only (16.6%). People with three or
more chronic conditions or cancer only reported higher rates of communicating
with other patients, compared with people with hypertension only or heart problems
only (P < .05).
Attitudes about the Internet
Among people who used the Internet for health information, 38.7% agreed that
it takes too long to find information on the Internet, 20.7% agreed that they
cannot trust information on the Internet, and 82.6% agreed that the information
on the Internet is easy to understand. There were no statistically significant
differences across study groups, except for the finding that 18.7% of people in
the heart-problems–only group agreed that it takes too long to find information,
compared with diabetes only (48.7%, P < .01), depression only (42.4%, P
< .01), two chronic conditions (40.6%, P < .05), and three or more
chronic conditions (42.1%, P < .05).
When stratified by condition, nearly one half to more than three quarters of
respondents reported that Internet use or e-mail improved their understanding of
their condition(s) (Table 3). Approximately the same percentage of respondents said
that Internet use improved their understanding of possible treatments. People
who had diabetes and heart problems responded positively more frequently than
did those who had hypertension (P < .05).
A much smaller percentage in all groups reported that the Internet affected
the treatment(s) they received for their condition(s). Although 23.5% of people
with diabetes and 26.9% of people with heart problems said Internet use
affected their treatments, only the latter value was marginally statistically
greater than for people who had hypertension (15%, P = .06).
Overall, 28.3% of respondents with one of five chronic conditions reported
that Internet information had improved their ability to manage their condition by
themselves. People who had diabetes reported most frequently that the Internet
had improved their ability to manage their condition (38.4%), and this was
statistically greater than for people with depression (22.3%, P < .01),
but was not greater than for the other chronic condition groups. Fewer than one
in eight reported that the Internet had led them to seek care from different doctors
or providers; there were no significant differences across the conditions. When
we asked about whether the Internet had affected the way that subjects ate or
exercised, 49.2% of those with diabetes said yes, a significantly greater
proportion than the proportion of people who had depression (31.0%, P <
.01) or cancer (29.7%, P < .05).
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People with chronic conditions vary in their use of the Internet for health
information and advice. After adjusting for education, sex, and age, Internet use for health information in the past year clustered at about 33.8% to
42.9% for hypertension only, cancer only, and heart problems only. Rates were
slightly higher (47.6%) for people with any two of the five chronic conditions
and were 51.0% to 52.0% for people with diabetes only, depression only, and
three or more chronic conditions.
People who have depression only and people who have multiple chronic
conditions were among the most frequent users of the Internet for health
information — for overall use and for communicating with health professionals.
Use of the Internet was also common for people with diabetes only, although
these people were less likely to communicate with family and no more or less
likely to communicate with health professionals or other patients than the other
chronic condition groups. These data confirm past reports that people who have
depression are more likely to seek health information than people who have other
chronic conditions (13,18). The higher rates for depression only may reflect
that the disorder still carries some stigma, leading individuals to seek
information outside traditional routes. The higher rates for depression could
also reflect that depression care often has greater limits on mental health care
insurance benefits and higher out-of-pocket expenses. It would be useful to know
whether this association is driven by stigma or by costs. If the association is
driven by stigma, this could identify opportunities for using the Internet to
reach people with stigmatized and potentially communicable chronic conditions
Although a large percentage of people with depression searched the Internet
only for health information, the depression-only group reported one of the
lowest rates for having been affected by Internet use. People who had diabetes,
cancer, or heart problems were more likely to agree that Internet information
improved their understanding of their condition than were people who had
hypertension or depression. More research is needed to determine which type of
information is received by people who have depression and whether they find it
We interpret Internet use among people with chronic conditions as a glass
half empty or half full. We see smaller effects on treatments and providers and
larger effects on self-management, eating, and exercise. Fewer than one in eight
people agreed that the Internet led them to seek care from different health
professionals for their conditions, and fewer than one in four said that the
Internet affected their choice of treatment. These numbers can be viewed as
substantial or meager, depending upon perspective. If these numbers are accurate, the effect of the Internet
on improved understanding is larger than other computerized patient education
interventions, such as the one described in the study by Rostom et al on
decision support for hormone replacement therapy (19) or in the study by Consoli
et al on hypertension (20). Caution must be used in interpreting these responses
because the data are self-reported, and we do not have information about
respondents’ knowledge before they used the Internet and cannot compare these
data to a control group. We also have no way of verifying if the information
they obtained was factually correct.
Attitudes toward health information on the Internet were generally favorable.
Slightly more than one third of the people with one or more of the five chronic
conditions agreed that it takes too long to find information on the Internet,
indicating that search time is an important determinant in using the Internet.
When people do find information, they then have to identify whether it is high
quality and accurate. Approximately one in five people agreed that they cannot trust
Internet health information, but it is unclear how they determine whether they
can trust the information. Other studies have discussed problems with the
quality and coverage of health information on the Internet (6,8,21), and
research has found that people are not particularly good judges for identifying
accurate health information and often forget which sites they searched (7).
Efforts to help people identify high-quality information more quickly could
result in more people using the Internet for health information.
A limitation of this study was that all the data were self-reported. Some
respondents might have avoided labeling themselves as chronically ill,
especially for depression, which is stigmatized. Additionally, the survey
questions required that people reconstruct memories of how they used the
Internet in the past year. This process can be cognitively difficult, especially
when a question asks respondents to remember how they used the Internet and then
to estimate its net effect.
The KN panel has been used in other research studies (22,23). This method of
sampling departs from traditional random-digit dialing. Both methods start with
a sampling frame that consists of U.S. households with telephone access. Both
methods have strengths and weaknesses. The strength of the panel approach is
that people are asked to participate in the panel, and a subset is sampled for a
particular survey. We have information on those who were sent the survey and did
not respond. The weakness is that some people may dislike being on a panel and
opt out when first asked or ask to be removed from the panel over time. KN and
independent researchers have studied these issues and reports are available
online (http://www.knowledgenetworks.com/ganp/reviewer-info.html*). Random-digit
dialing is performed each time a survey is fielded, so it is not susceptible to
panel attrition. At the onset of the call, however, the respondent is told about
the intent of the survey. People then choose whether to complete the survey, and,
typically, little if any information on the non-respondents is collected. Many
national surveys, including the Behavioral Risk Factor Surveillance Survey and
2000 Census, report median response rates below 70%. The latest study on the
Internet and health conducted by Pew Internet and American Life Project reported
a response rate of 32.8% (15). As mentioned earlier, we compared our sample to
other national surveys. Although the results were similar on all the
variables we compared (17), we cannot rule out the existence of potential biases
on other variables, such as Internet use.
This study focuses on common chronic conditions. Perhaps we would see higher
rates of Internet use among people who have rare diseases. There is a substantial amount of
health information available on the Internet (24), and people with rare
illnesses can obtain peer support on the Internet in ways that would not be
possible off-line. Further research could evaluate these matters.
A common perception is that the provision of health information via the Internet
is a “field of dreams” — that is, if we build it, they will come. In the past
decade, public and private investments have poured into Internet sites. Although
the Internet can offer several clear advantages over traditional information
sources, such as very low distribution costs, we found that few people who have
the five common chronic conditions studied use it routinely. When they
do, however, they report notable gains in knowledge and small changes in behavior.
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The Department of Veterans Affairs, Stanford University, and the Center on
the Demography and Economics of Health and Aging at Stanford University, which
is funded by National Institute on Aging (AG17253), provided research funding
for this study. We have no financial or nonfinancial connections with Knowledge
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Corresponding author: Todd H. Wagner, PhD, Veterans Affairs Palo Alto Health
Care System, Palo Alto, Calif, Department of Health Research and Policy,
Stanford University School of Medicine, Stanford, Calif, Center for Health
Policy and Center for Primary Care and Outcomes Research, Stanford University,
Stanford, Calif. Mailing address: 795 Willow Rd, 152-MD, Menlo Park, CA 94025.
Telephone: 650-493-5000 ext 22048. E-mail: firstname.lastname@example.org.
Author affiliations: Laurence C. Baker, PhD, M. Kate Bundorf, PhD, MBA,
MPH, Department of Health Research and Policy, Stanford University School of
Medicine, Stanford, Calif, Center for Health Policy and Center for Primary Care
and Outcomes Research, Stanford University, Stanford, Calif; Sara Singer, MBA, Center for
Health Policy and Center for Primary Care and Outcomes Research, Stanford
University, Stanford, Calif, Harvard School of Business, Cambridge, Mass.
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- Murray CJ, Lopez AD.
Evidence-based health policy — lessons from the
Global Burden of Disease Study. Science 1996;274(5288):740-3.
- Hoffman C, Rice D, Sung HY.
Persons with chronic conditions. Their
prevalence and costs. JAMA 1996;276(18):1473-9.
- Lorig KR, Laurent DD, Deyo RA, Marnell ME, Minor MA, Ritter PL.
Can a back
pain e-mail discussion group improve health status and lower health care costs?:
A randomized study. Arch Intern Med 2002;162(7):792-6.
- Gustafson DH, Hawkins R, Pingree S,
McTavish F, Arora NK, Mendenhall
J, et al.
Effect of computer support on
younger women with breast cancer. J Gen Intern Med Jul
- McKay HG, King D, Eakin EG, Seeley JR, Glasgow RE.
The diabetes network
internet-based physical activity intervention: a randomized pilot study.
Diabetes Care 2001;24(8):1328-34.
- Jadad AR, Gagliardi A.
Rating health information on the Internet:
navigating to knowledge or to Babel? JAMA 1998;279(8):611-4.
- Eysenbach G, Kohler C.
How do consumers search for and appraise health
information on the World Wide Web? Qualitative study using focus groups,
usability tests, and in-depth interviews. BMJ
- Berland GK, Elliott MN, Morales LS,Algazy JI, Kravitz RL, Broder MS, et al.
Health information on the
Internet: accessibility, quality, and readability in English and Spanish. JAMA 2001;285(20):2612-21.
- Baker L, Wagner TH, Singer S, Bundorf MK.
Use of the Internet and E-mail
for health care information: results from a national survey. JAMA May 14
- Taylor H. Cyberchondriacs continued
[Internet]. Rochester (NY): Harris Interactive [cited 2002 Jun 24]. Available
- Fox S, Rainie L. The online health care revolution: how the
Americans take better care of themselves. Washington (DC): The Pew Internet
and American Life Project; 2000.
- Holstein RC, Lundberg GD.
Use of the Internet for health information and
communication. JAMA 2003 Nov 5;290(17):2255.
- Wagner TH, Hibbard JH.
Who uses self-care books, advice nurses, and
computers for health information? Int J Technol Assess Health Care
- Haviland MG, Pincus HA, Dial TH.
Type of illness and use of the Internet
for health information. Psychiatr Serv Sep 2003;54(9):1198.
- Fox S, Fallows D. Internet Health Resources. Washington
Pew Internet and American Life Project; 2003.
- American Association for Public
Opinion Research. Standard definitions: final dispositions of cases and codes
and outcome rates for surveys. Lenexa (KS): The Association; 2004.
- Baker LC, Bundorf MK, Singer S, Wagner TH. Validity of the Survey of
Health and Internet and Knowledge Network's Panel and Sampling [Internet].
Stanford (CA): Health Economics Resource Center. Available from: http://www.herc.research.med.va.gov/wagner_CHI.htm*.
- Roan S. Cyber analysis. Los Angeles Times
2000 Mar 6.
- Rostom A, O'Connor A, Tugwell P, Wells G.
A randomized trial of a
computerized versus an audio-booklet decision aid for women considering
post-menopausal hormone replacement therapy. Patient Educ Couns Jan
- Consoli SM, Ben Said M, Jean J, Menard J, Plouin PF, Chatellier G.
Benefits of a computer-assisted education program for hypertensive patients
compared with standard education tools. Patient Educ Couns
- Biermann JS, Golladay GJ, Greenfield ML, Baker LH.
Evaluation of cancer
information on the internet. Cancer 1999;86:381-90.
- Schlenger WE, Caddell JM, Ebert L,
Jordan BK, Rourke KM, Wilson D, et al.
Psychological reactions to
terrorist attacks: findings from the national study of Americans' reactions to
September 11. JAMA 2002 Aug 7;288(5):581-8.
- Silver RC, Holman EA, McIntosh DN, Poulin M, Gil-Rivas V.
longitudinal study of psychological responses to September 11. JAMA 2002 Sep
- Kleinke JD.
Vaporware.com: the failed promise of the health care
Internet. Health Aff 2000;19(6):57-71.
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