AEJMC Archives

AEJMC Archives


View:

Next Message | Previous Message
Next in Topic | Previous in Topic
Next by Same Author | Previous by Same Author
Chronologically | Most Recent First
Proportional Font | Monospaced Font

Options:

Join or Leave AEJMC
Reply | Post New Message
Search Archives


Subject: AEJ 03 Len-RioM SCI Women Searching the World Wide Web for Health Information: Exploring Thoughts and Information Management
From: Elliott Parker <[log in to unmask]>
Reply-To:AEJMC Conference Papers <[log in to unmask]>
Date:Wed, 1 Oct 2003 07:42:03 -0400
Content-Type:text/plain
Parts/Attachments:
Parts/Attachments

text/plain (902 lines)


Women Searching the World Wide Web for Health Information:
Exploring Thoughts and Information Management


María E. Len-Ríos and Frances Gorman
The University of Kansas


Presented to the Science Communication Interest Group of the Association
for Education in Journalism and Mass Communication, July 2003, Kansas City.

All correspondence to:  Dr. María E. Len-Ríos, Assistant Professor, The
University of Kansas, William Allen White School of Journalism and Mass
Communications, Stauffer-Flint Hall, 1435 Jayhawk Blvd., Room 207D,
Lawrence, KS, 66045-7535, (785) 864-7637, [log in to unmask]  Frances Gorman
is a master's degree student at the same institution,
[log in to unmask]
 Abstract
This study uses think-aloud protocols to explore the thought processes of
12 women as they search the World Wide Web for information about leading
healthier lifestyles.  Normative management of information theory and the
concept of self-efficacy guide our analysis.  Use of the grounded theory
method revealed that women seek information to increase their hope, satisfy
their interests and curiosity, and provide them with
knowledge.  Participants primarily define leading a healthier lifestyle as
weight loss, disease prevention, and good mental health.  Findings also
suggest that self-efficacy, in this context, can be internal and external.
Management of Web Health Information
 Women Searching the World Wide Web for Health Information:
Exploring Thoughts and Information Management
Studies show that women are more likely than men to use the Internet for
health information (McKillen, 2002; Morahan-Martin 1998; Fox et al.,
2000).  However, it is unclear how women search the Internet, use its
information and make decisions about what information to read.  This study
examines how women search the Internet and process information about
leading healthy lifestyles in order to add to theories of information
management and better understand self-efficacy for nutrition and fitness
behaviors.  From a practical standpoint, our study addresses ways to think
about implementing public health campaigns to reduce obesity.
We chose to study how women seek information about living healthier
lifestyles because chronic heart disease, diabetes and obesity are among
the greatest U.S. public health challenges.  Wetter et al., (2001) noted
that health behavior modification programs have been "marginally
successful," with less than one-third achieving the desired results (pp.
S11-S12).  Wetter et al. (2001) wrote, "This situation may be seen as a
'crisis' in the fields of health, exercise, and nutrition science" (p.
S11).  Studying how women seek, process, and filter health information can
help public health communicators better understand how their messages are
received, analyzed, evaluated, and accepted or rejected.
We selected normative information management theory (Brashers, Goldsmith, &
Hsieh, 2002; Brashers et al., 2000) and self-efficacy (Bandura, 1989) as
our guiding theoretical and conceptual foundations.  Normative information
management theory (Brashers et al., 2002) suggests that individuals may
seek to increase or decrease their uncertainty to serve emotional or
informational goals.  One way for people to manage uncertainty is by
seeking or avoiding information.  Therefore, we explore the types of
information women search for and what they omit from their Internet searches.
Self-efficacy is identified as an important concept to consider in the
design of public health campaigns (Ôunpuu, Woolcott, & Rossi, 1999; Rimal,
2001) and to understand how people use the Internet (Fredin,
1997).  Self-efficacy is an individual's belief in his or her capacity to
accomplish a task.
Bandura (1989) has suggested that self-efficacy is also related to how
individuals manage distress.  Bandura noted, "It is not the sheer frequency
of stressful or intrusive cognitions but rather the perceived inefficacy to
turn them off that is the major source of distress" (p. 730).   Managing
the distress of information may affect how women seek information on the
Web.  If women do not possess feelings of self-efficacy to engage in
healthy behaviors, then they may avoid distressful
information.  Conversely, they may seek out information motivating them to
engage in behavior change or behavior that makes them feel better about
their current health and fitness practices.
We employed the think-aloud protocol analysis to explore these
issues.  This method is exploratory and provides data with abundant
detail.  Participant thoughts are recorded while they are engaged in Web
searching, which allows a more accurate understanding of what people think
than that offered by retrospective techniques.
The paper begins with a review of current studies of gender and the
Internet.  This is followed by an elaboration of the normative theory of
information management and the concept of self-efficacy.  We then explain
the method used and outline the procedures we employed to analyze the
data.  Findings and a general discussion are presented at the end.
Literature Review
Internet Use and Gender
A recent survey by Datamonitor, a market research consulting firm, showed a
78% Internet market penetration in the United States (McKillen, 2002), and
a Harris Interactive Poll suggests that 67% of U.S. adults are online
("Those with Internet," 2003).
The Pew Internet & American Life Project (Fox et al., 2000) found that over
half of those with Internet access had sought health information.  Of those
who had, 13% looked for information on nutrition and fitness.
Studies of gender differences in Internet usage indicate that the gap has
narrowed, with women's access equal to or greater than that of men.  Ono
and Zavodny (2003) conducted a secondary analysis of five data sets from
1997 to 2001 and noted that while women appeared to be online more than men
in 2001, men were likely to be online more often and for longer amounts of
time.
Other investigations focus on the gender differences in attitudes toward
technology and the type of content consumed.  Studies have found that
online culture and language have traditionally been male (Morahan-Martin,
1998), that U.S. females perceive a greater societal risk with the
development of technology and science (Hornig, 1992), and that females use
the Web more for e-mail and men read more information on the Internet
(Jackson, Ervin, Gardner, & Schmitt, 2001).  Jackson et al. (2001) argued
that men have a "stronger motive for information," and that females have a
stronger motive for "interpersonal communication"  (¶ 37).
Feminist scholars have studied gendered identities online.  Van Zoonen
(2002) found young heterosexual couples to mutually shape each other into
traditional Internet gender roles within the household, with the computer
and Internet belonging in the male domain.  Women were not passive users,
however and were actively drawn to the Internet, "negotiating the former
exclusively male codes of the PC" (Van Zoonen, 2002, p. 17).
Research also addresses information topics and gender.  Morahan-Martin
(1998) found that men tended to dominate most information-seeking topic
categories except for health and travel.  She attributed this to women's
"traditional caretaker role" (p. 177).  The Pew study (Fox et al., 2000)
also illustrated that, of those with Internet access, women have looked at
health information more than men (63% vs. 46%).   In addition, the authors
(Fox et al., 2000) found that although women sought health information for
children more than men, "men and women were equally likely to be seeking
information on behalf of a parent or other relative" (p. 6).  Another study
by Miller (2001) showed that women were more likely to seek health
information on the Internet, while men sought more science-related information.
Internet use and the normative theory of information management
Use of the Internet is often considered a goal-directed activity whereby
Internet users are active participants in their online experience (McKenna
& Bargh, 2000).  Similarly, when it comes to consumption of health
information, Brashers et al. (2002) suggest that individuals have goals and
manage information for cognitive and emotional reasons.   They suggest that
"information seeking and avoiding may be a balancing act for individuals
who need to achieve multiple goals (e.g., reducing uncertainty, improving
or sustaining health, and maintaining optimism" (p. 261).  Therefore,
health information may serve instrumental or emotional goals.
The medical literature suggests a corresponding interpretation.  A study of
cancer patients found that they avoided information if it undermined their
hope for improvement, but discovered patients may have sought more
information if they believed alternative treatments could help them
(Leydon, Boulton, Moynihan, Jones, Mossman, et al., 2000).  In the same
way, those seeking nutrition or fitness information may select that which
will make them feel better about their behaviors and avoid distressful
information. Information seeking may be limited to situations that accord
individuals the self-efficacy to manage their health.
Although Brashers et al. (2002) largely focused their efforts on studying
information management in interpersonal contexts (i.e., doctor-patient
relationships, patient-family relationships) they also noted that
information from the media and Internet can affect an individual's level of
uncertainty and information balance.  Brashers et al. (2002) suggested that
individuals might encounter certain challenges to their online
informational goals.  They proposed that individuals may feel overwhelmed
by the information, not know the origin of the information, and may lack
the expertise to interpret it.  The credibility of the information
encountered or discovered on the Internet, and an individual's perceived
self-efficacy to interpret and use that information, may pertain to whether
an individual decides to use the information or to avoid it.
Source credibility has long been associated with involvement in message
processing.  For example, Petty and Cacioppo's elaboration likelihood model
(1984) and Chaiken's heuristic systematic model (Chaiken, Liberman, &
Eagly, 1989; Chaiken & Maheswaran, 1994) both suggest that individuals
invoke information processing shortcuts to evaluate persuasive messages.  A
message from a high credibility source or that contains more persuasive
arguments may lead to less message scrutiny for those with low involvement
(Petty & Cacioppo, 1984).
Credibility is comprised of several variables (West, 1994).   It has been
measured by looking at ratings of believability, fairness, accuracy,
thoroughness, comprehensiveness, and bias (Johnson & Kaye, 1998, 2000;
Leshner, 2001).  Johnson and Kaye (1998) defined credibility for online
political information as "the degree to which politically-interested Web
users judge information on the Internet to be believable, fair, accurate,
and in depth" (p. 325).   The credibility of the online sources may affect
how women process and manage health information.
Aldoory (2001) used focus groups and situational theory to explore the
antecedent variables associated with women's involvement in health
messages.  She found that, "In particular, source credibility and trust
were critical to involvement with health information" (p. 177).  The
variables she studied were: "consciousness of everyday
life,"  "self-identity," "source preference," "a consciousness of personal
health," and "cognitive analysis of message content."
Krummel, Humphries, & Tessaro (2002) examined how factors influenced
women's perceived self-efficacy to make nutritional behavior changes.  They
found that "Self-efficacy for behavior change varied and did not depend on
age" (p. 41).  The authors observed that the primary reasons for not
adopting a healthful eating plan were family preferences for unhealthful
foods, cost, time to prepare the food, limited knowledge about nutrition,
and lack of support from family members and friends who invited them to
eat.  Factors that sparked change included emotional scares (when a doctor
diagnoses them with a disease), how they thought about healthy eating, and
knowledge about how to implement change.
In sum, women go online for health information, but we do not know where
women go and how they process information they find.  Normative information
management theory informs us that individuals may use information to
achieve emotional or informational goals and may be affected by
self-efficacy factors.  Research on self-efficacy suggests that the
individuals' self-efficacy for using a computer, understanding information,
and following healthful eating and fitness recommendations may be connected
to how they balance and perceive information.  Studies that explored
involvement with health messages suggest that credibility and personal
relevance are important factors.  The next section outlines our research
questions.
Research Questions
        Based on our review of the literature, we pose three research
questions.  First, although it is known that women search the Internet for
health information, and that 13 percent of those who search the Internet
search for nutrition and fitness information, we wanted to know where women
will search when given a choice and how they will define a healthy
lifestyle.  Therefore, we pose the following research question:
RQ1:  When given a choice, where do women go on the Web to seek information
about leading a "healthier" lifestyle and how do they define a healthier
lifestyle?
        According to normative information management theory, individuals manage
the health information they receive for emotional and informational
reasons.  We wanted to assess whether women identify nutritional
self-efficacy issues when searching for information, and whether women
avoid information that might cause them distress.  To this end, we pose a
second research question:
RQ2:  How do women's thoughts about health information from the Web pertain
to self-efficacy or information avoidance?
        Aldoory (2001) identified multiple factors related to women's involvement
with health messages.  Our third research question relates to whether women
think about these involvement factors while they search the Internet:
RQ3:  Can women's thoughts about health messages on the Web be categorized
according to the involvement variables of source credibility,
self-identity, and self-consciousness of health?
We used verbal reports, or think-aloud protocols, to collect the
data.   The second author transcribed the tapes and both authors then
analyzed the 12 transcripts using a grounded theory method.  Detail about
the method is described in the next section.
 Method
Protocol Analysis
The purpose for using think-aloud protocols is to examine cognitive
processing while an individual is engaged in a task (concurrent), or
immediately following the task (retrospective).  According to Shapiro
(1994) the basis behind the method is that, "As a person does a task, he or
she can report relatively accurately on information passing through
short-term memory (STM)" (p. 2).
The think-aloud technique is used in cognitive psychology, consumer
research (Kuusela & Paul, 2000), education (Smagorinsky, 1989), media
studies (Eveland & Dunwoody, 2000; Light, 1999; Tremayne & Dunwoody, 2001)
and speech communication (Hample, 2000).  Ericcson and Simon (1984)
originally introduced this method of verbal reports to gather data on
people's attitudes, opinions and thought patterns while individuals were
conducting an activity or task.  Automatic processing, such as schema
activation or memory storage, is not recorded with this method.  This is
because, as Nisbett and Wilson (1977) explained, "there is almost no
conscious awareness of perceptual or memorial processes" (p. 232).
Sample sizes for protocol studies generally range from 10 to 30
participants (Eveland & Dunwoody, 2000).  The quantity of data gathered
during a protocol session makes large samples difficult to analyze.
Sample
Twelve female Internet users were recruited in January - February 2003
through two advertisements placed in a local newspaper (circ. 19,200) and
fliers placed at public places throughout the community such as grocery
stores, health clubs, the public library and student health center in a
Midwestern city.
Participants were selected through a screening process.  All participants
reported using the Internet in the past two weeks.  They were selected so
there would be an even split according to exercise habits (exercised three
or more times a week vs. less than three times a week) and primary reliance
on television or newspapers for news information.  Participants could not
be students at the local University or under the age of 18.
The sample is not representative of the general population, but met quota
requirements.  The mean age of participants was 39.4 years old.  Of the 12
participants, the average number of hours spent at home or during personal
time at work on the Internet was 3.57 hours per week (not including time
spent playing games or using e-mail).  Six participants reported being
employed full-time, one part-time and two self-employed.  Three
participants were unemployed at the time.  The six participants who
reported exercising regularly exercised an average of five days each week
and rated their overall health as between good and excellent (M=4.17 on a
5-point scale).  The participants who reported not exercising regularly
exercised an average of 2.83 days each week and rated their overall health
as fair to good (M=3.67 on a 5-point scale).  Participants reported media
Web sites as having health information that was more trustworthy, accurate
and unbiased (M=3.17) than health information found on pharmaceutical
company Web sites (M=2.25).
Equipment
A Macintosh computer with a 14" monitor, a mouse, keyboard, and network
Internet connection was used for this study.  Internet Explorer5 or
Netscape was used depending on the participant's Web browser
preference.  Participants' voices were audio recorded through a microphone
and the Web sites visited were video recorded by a television and VCR.  An
Averkey system and sound managing board connected the computer and
recording equipment.
Pretests
Three volunteers participated in pretests.  The first two pretests revealed
that the Internet browsing time was too long.  We reduced the time 5
minutes for the third pretester who reported 20 minutes was more than
enough time to search the Web.
Procedure
Prior to conducting the study, human subjects permission was received from
the University Human Subjects Committee at a large Midwestern University.
When participants arrived for the study, they were greeted and the purpose
of the study was explained.  Participants were warned that if they grew
silent, they would be reminded, "Please don't forget to verbalize your
thoughts aloud."  Individual sessions took place in a university office and
lasted about 45 minutes to one hour.
Participants engaged in three practice tasks for the think-aloud protocol
to familiarize them with the procedure.  After the practice sessions,
participants were asked to pretend they had made a decision to adopt a
healthier lifestyle.  They were told to search the Web anywhere they chose
for information about living healthier.  Afterwards, participants filled
out a questionnaire of online behavior and health practices and
beliefs.  To conclude the session, participants were debriefed, paid $20,
and thanked for their participation.  Transcripts of the audio portion of
the videotapes and lists of Web sites visited were used for coding purposes.
Data Analysis
We determined where women chose to go on the Internet by viewing the
History folder that was captured by the Web browser and by examining the
transcripts for each participant.  To answer the second two research
questions, we analyzed the transcripts as texts or ethnographic field notes
(Emerson, Fretz, & Shaw, 1995).   Transcripts ranged from 6 to 13
double-spaced pages (M=10.1; Mdn=10).  We began by identifying themes in
the data according to previous literature and by identifying new ones using
a grounded theory approach (Glaser & Strauss, 1967).  After reading the
transcripts and generating the categories, the authors again went through
the transcripts and categorized the thoughts.  A thought was categorized as
a complete idea before taking a pause.  From the thoughts, general themes
were identified to address the research questions.
Results
        To answer RQ1, we examined where women went online to seek information
about leading "healthier" lifestyles.  Those Web sites visited most
frequently were WeightWatchers.com and WebMD.com (see Table
1).   WeightWatchers.com is the informational Web site for the popular
weight loss program.  The site contains an explanation of the program,
community message boards and chat, success stories, news stories, recipes,
products for purchase, and "eTools."  WebMD.com describes itself as "the
leader in providing services that help physicians, consumers, health
providers and health plans navigate the complexity of the healthcare
system."  The Web site offers news stories, message boards, doctor and
clinic searches and a variety of searchable medical and lifestyle health
information.  Participants did visit other commercial, government, and
nonprofit Web sites (see Table 2).
Participants chose to use the Web portals netscape.com and yahoo.com and
the search engine google.com most often to search for health
information.  Five participants searched using google.com, two participants
each used netscape.com and yahoo.com.
The common search terms can be divided into five categories:  fitness,
nutrition, diseases, general health terms and general terms not specific to
a health topic.
The following were fitness search terms:  best exercise, methods of
exercise, exercise, Pilates, yoga, hatha, swimming, fitness, cardio and
walk.  Nutrition search terms were: prepared meals, vitamins, diet,
veganism, macrobiotic, anti veganism, nutrition, low carbohydrates
sandwich, Atkins diet and broccoli recipes.  Disease search terms were:
cancer, diabetes type II, heart disease and obesity in America.
Sometimes general health terms were used, such as:  weight loss, wellness,
body mass, health, weight, weight management, women's health, healthy
lifestyle, dermatology, women health, WeightWatchers, smoking cessation,
mental health, health wellness, health alternative, Health Fitness
Journal.  Other general non-health terms included:  women, 50 and over,
female age 50, research, basic information, Oprah, living better and what is.
Participants chose to define healthier lifestyle primarily in terms of
weight loss, disease prevention and mental health.  Weight loss included
searching for information on diet and fitness.  Participants defined
healthier lifestyle usually within the first few search terms used, such as
Participant 5 who began her search with "The best way to get a healthier
lifestyle, at least for me anyway, is to control my weight."  Participant
11 elected to search for diabetes from the beginning because she stated,
"I'd just like to know what preventative measures can be taken."  Other
participants preferred defining a healthier lifestyle from a mental health
perspective, such as Participant 4 who said "And I'm actually going to type
in mental health because I think that's the most important place to start
any sort of healthy lifestyle."
RQ2 addressed women's thoughts about self-efficacy and information
avoidance.  We found that thoughts about self-efficacy could be internal or
external.  Self-efficacy was defined as the perception that one could
personally change her health.  Internal thoughts about self-efficacy
pertained to their abilities to process, use, and acquire knowledge;
physically engage in exercise and control their behavior.  External
self-efficacy was associated with how women could control their
environment.  No matter the type of self-efficacy, at times participants
felt they had sufficient self-efficacy, while they did not at others.
Participants expressed a lack of self-efficacy to attain knowledge from
information provided by some Web sites.  For instance, Participant 4, while
viewing an article in the Dermatology Online Journal, said, "This is more,
since it's a journal, it's a little more above my level.  I don't know what
any of those words mean, so I don't really feel the need to read
that."  This participant felt she was not able to understand the
information and chose to move on to something she felt was easier.
Sometimes participants lacked the self-efficacy to enact the healthy
behaviors they encountered.  Participant 10 searched for information about
Vegetarian diets and commented, "It'd be hard to eat all those
vegetables."  This participant questioned her self-efficacy to follow a
diet that included eating a variety of vegetables and meat-substitutes.
Self-efficacy was linked to perceived or real physical limitations.  For
example, Participant 1 viewed Priscilla Patrick's yoga videos and
commented, "She's like, already so limber I don't know how I could ever
begin to imitate what she does."  This participant questioned her physical
ability.
Participant 2 was looking at an exercise plan from Prevention Magazine and
said, "Hamstrings…There I don't think I can do that.  I can't do squats, no
way."  In this case, the participant had knee problems and her physical
limitations kept her from doing exercises that might aggravate her knees.
On the other hand, participants also expressed positive self-efficacy
related to acquiring the knowledge necessary to live a healthier
lifestyle.  While searching for fitness information about Pilates,
Participant 1 commented, "Um, trying to find out where I can get more
information on Pilates so I can learn it myself without going to an
instructor."  This participant felt she had the capacity to teach herself
Pilates once she obtained the right information.
Other participants had sufficient self-efficacy to envision preparing
nutritious meals or completing exercise programs.  While looking at healthy
recipes, Participant 5 said, "Looks fairly easy, looks like the kind of
thing I could do at home without a recipe.  Um, not bad for a serving of
calories."  Participant 5 believed she had the self-efficacy to accomplish
this task because she saw it as "easy."
Participant 2, while reading about a fitness program said, "And I've done
that before and I've lost weight."  This participant felt she was capable
of performing this activity and reaching the goal of losing weight.
Additionally, Participant 2 noted, " 'Reducing pounds...a pedometer'  Yeah
, that might be good to use it, because, it's something that's...what's the
word I'm looking for? Tangible.  Something you can feel, something you can
see so that you can see progress," while reading a news article.  She was
evaluating whether she liked the fitness tool and would use it.
Thoughts about external self-efficacy involved thoughts about one's
environment or living situation.  For example, Participant 9 looked at
exercise plans on Reebok.com and commented, "Well let's look under that
because I have a treadmill, so let's look under the walking."  This
participant selected walking information because she owned a treadmill and
could easily participate in that activity.
Other factors about individual's situations and surroundings prevented them
from participating in healthy behaviors.  For example, while viewing
information about a wellness spa, Participant 8 commented, "That seems
pretty interesting.  But really, you need someone to baby-sit your children
while you exercise."  This participant viewed her responsibility to care
for her children as affecting her ability to exercise.
Information avoidance occurred when participants had specific informational
goals defined.  Individuals metaphorically "donned blinders" and focused
intensely on finding the information they wanted, avoiding all other
information.  Others just avoided information if it did not interest them,
arouse their curiosity, required purchase, threatened their "comfort zone,"
or took a lot of work.
Some participants avoided information that went outside their health
boundaries and did not meet their  "comfort zone."  For example,
Participant 6, while viewing an article about improving your sex life, left
the article and commented, "Um, I don't really need that."  Participant 10,
while searching for information on macrobiotic diets, read the introduction
of one Web site and commented. "This isn't going to help," and left the
site.  This participant wanted to know "what do they eat," and when she did
not immediately find the answer, she avoided the information and left the
site.
Lack of interest caused some to avoid information they found.  Participant
6 was reading about treadmills on reebok.com and said, "'Hot spots: Walkers
can suffer from overuse, injuries caused by doing a number of things.'  Um,
I'm going to skip over that.  'How to avoid injury.'  I'm going to skip
over that."  The participant chose not to process this information.
Requests for payment by Web sites drove some participants away.  For
example, Participant 6 read an article about a vitamin supplement for sale
and said "Why do you need to pay for someone to tell you about information
you can easily get anywhere?"  This participant was not interested in
paying just because a product for sale sponsored it.  Participant 5 left
WeightWatchers.com when she clicked on a link that was only accessible to
paying members.  She commented "and they're not willing to give me anymore
unless I pay," as she justified leaving the site entirely.
Some participants avoided information that seemed like a lot of
work.  Participant 1 viewed a Web site about yoga poses and evaluated them
as not very "comfortable."  She left the site shortly after commenting, "I
don't like…I don't really know if this is what I want."  The participant
chose not to pursue this particular Web site because the yoga poses did not
meet her interest or skill-level.
Generally, when individuals elected not to process information they weren't
necessarily trying to maintain or avoid gaining information, the
individuals rather felt that the information was not relevant to them,
their goals or that they were not interested in it.
RQ3 pertained to whether women's thoughts about health messages included
involvement variables such as source credibility, self-identity, and a
personal consciousness of their health practices.
Source credibility was an important involvement variable.  Name recognition
served as an important credibility variable.  If the participants had had
experience with an organization or recognized a name from the media, they
were more likely to ascribe credibility to it.  Also, interpersonal
communications were important "gatekeepers" or sources that lent
credibility to organizations and celebrities.
Participants often evaluated health information based on whether they
recognized the name of the author or site.  For example, Participant 1
examined the credibility of workout videotapes and said, "some of them, I
know people make them with...there are certain people who are name
recognizable people that do Pilates tapes...then you know you're going to
get a good tape."
If the women could not immediately identify the author, they sought further
evidence.  For example, after clicking on a site about becoming Vegan,
Participant 10 commented, "OK, wow, this is personal research.  Donna
Maurer…OK, what else has she done?"  This participant wanted to find out
whether the author of the article was credible before processing the health
information.
Participant 8 had been looking at information at a health clinic Web
site.  She was trying to determine the credibility of the doctor, but
couldn't figure it out based on the information she encountered.  After
getting frustrated she stated, "All right, I'm going to look at something
else.  Because that's just too much work."  The participant chose to not
process any subsequent information because she could not make sense of it.
Sometimes the information source was judged by the quality of the health
information.  For example, Participant 5, when looking at healthy recipes
said, "It has a lot of cheese in it and butter.  So, that doesn't strike me
as the best.  '8.2 grams of fat.'  That's worse than fried broccoli."  This
participant was analyzing the true nutritional value and benefit of the
recipes she was reading to determine if it was a good source for health
information.
Past experience with and organization or product was important for
establishing credibility of information.  For example, Participant 2
identified with a magazine that she subscribed to, "Oh, Prevention.  I get
Prevention. I should go on their Web site. I get their magazine. That's
another one that helps."
Thinking about what to put into a Google.com search, Participant 5 said
"Maybe I should be more specific and search for, Weight Watchers.  It's a
commercial site, but they do, in my experience, offer a little bit more
practical information."  In this instance, satisfactory past experience led
to the attribution of credibility.
Other times, participants relied on opinions of friends and family.  While
reading a story on why it is important to drink eight glasses of water each
day, Participant 12 said, "Oh, yeah, and I like that thing about 'Crystal
Light' and all the flavored waters and people say they do that as a
replacement.  Well, that one guy said to me, 'You don't take a bath in
Crystal Light, why would you drink it?'"  These thoughts show that friends
exert influence over how information gets processed.
Participant 4 used an interpersonal contact as reason for searching for
information on diabetes, "I kind of get interested in this because one of
my good friends is, he's diabetic and he's very involved with the American
Diabetes Association."  In this case her friend acted as a mediator between
the participant and her search for information about a healthier
lifestyle.  Participant 5 chose to enter WeightWatchers.com based on an
interpersonal recommendation, "I have a friend who just signed up for
Weight Watchers online and she was hopeful it would be good for her.  So
I'll check it out too."
Sometimes participants decided not to look at information from unknown
sources.  For example, Participant 1 read a workout DVD description that
included "a 10 minute in depth interview with Anna Cabin," and commented
"Whoever the heck that is."  This participant evaluated that DVD as less
credible.
Overall source credibility depended on past experience with the information
source or Web site.  If sources were unknown to participants but they were
still interested in the information, they searched for other recognizable
indicators of credibility.  In sum, source credibility was associated with
message acceptance and involvement and appeared to be mediated by
interpersonal communication.
Self-identity was particularly important to involvement for those who
viewed healthier lifestyles as disease prevention.  Also, some individuals
had family histories of heart disease or diabetes.  For them, how they
viewed their own health history affected what information they viewed.  For
example, Participant 11 started to search for diabetes information and
noted, "The reason I looked on diabetes is there is a history of diabetes
in my family."  She knew she had a family history of diabetes and wanted to
learn more about it.
Participant 9 determined she was overweight based on a WeightWatchers.com
chart.  She then took this information and began searching for fitness
information with the comment, "Well, we know what I'm supposed to
weigh.  Let's look at maybe some sort of other exercise thing."  This
participant became involved after identifying herself as overweight.
Most of the identity thoughts related to being a woman, a vegetarian, a
cook, a lover of french fries, or a treadmill owner.
Women's consciousness of their own physical health practices also affected
how they sought health information.  Participant 2 was looking at exercise
programs on a Web site and said, "OK, I do these, but I don't do these in
the morning. These are like the Richard Simmons tape.  I do the lateral
raise, I do the abs, I do the triceps...standing curl."  She was comparing
the workout on the Web page to her personal health habits and exercise
routine.
Also, Participant 3 had just finished examining different yoga poses and
said, "And I do yoga, and I sort of think that helps with your women's
health."
Participant 7 searched for information about cancer causes and said, "It's
more, that's what I think I did, when I lifted those heavy boxes, I used to
rest them on my chest tissue... I think I damaged tissue..."  This
participant was analyzing her own current health condition compared to the
information she was reading on the Web.  Other thoughts reflected the
current health status of the participants, such as "I'm not losing my
hair," and past or current risky health behaviors, such as "I don't monitor
myself like I should."  Other thoughts about personal health risks were
"which I used to smoke," and "I don't go out into the sun."
Other thoughts pertained to participants' personal wishes and desires for
their health. Participant 10 searched the Web for information about
changing her diet and said, "I don't eat meat, I want to change from
Vegetarian to Vegan, so…" This participant wanted to change her dietary
behaviors and searched for information on how to go about meeting her goal.
Participant 7 looked for information about her condition of diabetes and
said, "OK, this is what I need to watch are my carbs, cut down on my
carbs."  The participant wanted to find information on how she could better
monitor her diet while living with her condition.
Curiosity also led to involvement—even though some of the participants
didn't plan to act on the information.  One participant noted, "I'm going
to check that out even though I'm not going to do it."   An interest in
reading the personal stories of those who had improved their health also
attracted the women in our study.  For example, Participant 8 who said, "I
wonder if they have any testimonials? I just want to hear people's stories."
Source credibility, self-identity, consciousness of one's health practices
and curiosity all appeared to lead to involvement.
Discussion
This study examined where women go on the Internet to find information
leading them to "healthier" lifestyles.  Our results showed that among our
group of participants, there was a preference for the big name Web sites,
WebMD.com and WeightWatchers.com.  This is not surprising as Webster and
Lin (2002) discovered that Web sites may also be subject to the Pareto's
Law—that the majority of the Web audience visits a small number of Web
sites.  Health Web sites may well fall under this rule.  We also explored
what search terms were used, and exercise and health were commonly
found.  When it came to leading a "healthier lifestyle," definitions
typically were about weight loss, disease prevention, and mental health.
We also explored how women's thoughts pertained to self-efficacy and
information avoidance in their Web searches.  It did appear that women
searched for information that would give them hope.  This was similar to
findings from Brashers et al. (2000) and Leydon et al (2000) who found that
individuals wanted to manage uncertainty by discovering information that
provided them with reasons for optimism.  Women did tend to avoid
information that did not pertain to their interests.  This was not the same
type of avoidance found in the aforementioned studies.  This is because the
study samples were quite different as Brashers et al. examined AIDS/HIV
patients and Leydon studied cancer patients.  Similarly, however, we found
that if women felt low self-efficacy for accomplishing a behavior, they
might avoid seeking further information.
More importantly, our findings suggest there are numerous kinds of
self-efficacy for finding online information to lead a healthier
lifestyle.  Our participants identified internal and external
types.  Internal forms included:  knowledge about nutrition and fitness,
comfort with using the Internet, perceived and real physical ability, and
self-control over eating behaviors.  External self-efficacy pertained to
their living environment, family, time and fitness equipment.  Both of
these forms of self-efficacy also appeared to have an emotional component
attached to them.
        Contrary to findings by Aldoory (2001), we did not find that
"consciousness of everyday life" had a large influence on these women's
thoughts.  This is partly due to differences in operationalization and the
methods used.  We did find that credibility was important to the likelihood
that women would process information.  Recognition and experience with the
Web site were key factors.  Credibility served as a heuristic cue for
evaluating the source expertise or trustworthiness.  Interpersonal
communication appeared to work as a mediating factor in message
evaluation.  Self-identity also led women to search for health information
that pertained to their specific needs.  Messages that addressed the
self-identities of participants captured their attention.
        It must be noted that our findings are exploratory and based on a quota
sample.  The volunteers were in their mid- to late-30s and from the
Midwest.  Findings from different sample populations may offer distinct
results.  In addition, the presence of the research administrator may have
affected participant willingness to express some
thoughts.  Notwithstanding, this study contributes valuable insight into
the minds of women as they search the Web for health information.  It
provides the rich description not available through traditional survey
techniques.
Our results suggest that future studies should account for the varieties of
self-efficacy that operate when women process nutrition and fitness
information on the Web.  This research would allow public health officials
to target campaigns at different levels of self-efficacy (high vs. low) by
the different forms of self-efficacy (nutrition, fitness, knowledge, and
environmental).  More exploration might be done on the emotional dimensions
associated with self-efficacy.    Furthermore, our findings support the
idea that interpersonal communication performs an important role in
mediating information from media sources.  It also may be that certain
health topics lend themselves more to interpersonal mediation than
others.  This deserves further exploration.

 References
Aldoory, L.  (2001).  Making health messages meaningful to women:  Factors
that influence involvement.  Journal of Public Relations Research, 13, 163-185.
Bandura, A.  (1989).  Regulation of cognitive processes through perceived
self-efficacy.  Developmental Psychology, 25, 729-735.
Brashers, D. E., Goldsmith, D. J., Hsieh, E.  (2002).  Information seeking
and avoiding in health contexts.  Human Communication Research, 28, 258-271.
Brashers, D. E., Neidig, J. L., Haas, S. M., Dobbs, L. K., Cardillo, L. W.,
& Russell, J. A.  (2000).  Communication and the management of
uncertainty:  The case of persons living with HIV or AIDS.  Communication
Monographs, 67, 63-84.
Chaiken, S., Liberman, A., & Eagly, A.H.  (1989).  Heuristic and systematic
information processing within and beyond persuasion context.  In J. S.
Uleman & J. A. Bargh  (Eds.), Unintended Thought  (pp.  212-252).  New
York: The Guilford Press.
Chaiken, S., & Maheswaran, D.  (1994).  Heuristic processing can bias
systematic processing:  effects of source credibility, argument ambiguity,
and task importance on attitude judgment.  Journal of Personality and
Social Psychology, 66, 460-473.
Emerson, R. M., Fretz, R. I., & Shaw, L. L.  (1995).  Writing ethnographic
fieldnotes.  Chicago:  The University of Chicago Press.
Ericsson, K. A., & Simon, H. A.  (1984).  Protocol analysis:  Verbal
reports as data.  Cambridge, MA:  The MIT Press.
Eveland, W. P., Jr., & Dunwoody, S.  (2000).  Examining information
processing on the World Wide Web using think aloud protocols.  Media
Psychology, 2, 219-244.
Fox, S., Rainie, L, Horrigan, J., Lenhart, A., Spooner, T., Burke, M.,
Lewis, O., & Carter, C.  (2000, November 26).  The online health care
revolution:  How the Web helps Americans take better care of
themselves.  Retrieved from March 18, 2003, from http://www.pewinternet.org/.
Fredin, E. S.  (1997).  Rethinking the news story for the
Internet:  Hyperstory prototypes and a model of the user.  Journalism &
Mass Communication Monographs, 163, 1-47.
Glaser, B. G., & Strauss, A. L.  (1967).  The discovery of grounded
theory:  Strategies for qualitative research.  Chicago:  Aldine Publishing Co.
Hample, D.  (2000).  Cognitive editing of arguments and reasons for
requests:  Evidence from think-aloud protocols.  Argumentation and
Advocacy, 37, 98-108.
Hornig, S.  (1992).  Gender differences in responses to news about science
and technology.  Science, Technology, & Human Values, 17, 532-542.
Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N.  (2001,
March).  Gender and the Internet:  Women communicating and men
searching.  Sex Roles:  A Journal of Research, 44, 363-379.   Retrieved
August 27, 2002, from Expanded Academic ASAP database.
Johnson, T. J., & Kaye, B. K.  (1998).  Cruising is believing?:  Comparing
Internet and traditional sources on media credibility measures.  Journalism
& Mass Communication Quarterly, 75, 325-340.
Johnson, T. J., & Kaye, B. K.  (2000).  Using is believing:  The influence
of reliance on the credibility of online political information among
politically interested Internet users.  Journalism & Mass Communication
Quarterly, 77, 865-879.
Krummel, D. A., Humphries, D., & Tessaro, I.  (2002).  Focus groups on
cardiovascular health in rural women:  Implications for practice.  Journal
of Nutrition Behavior and Education, 34, 38-46.
Kuusela, H., & Paul, P.  (2000).  A comparison of concurrent and
retrospective verbal protocol analysis.  American Journal of Psychology,
113, 387-404.
Leshner, G.  (2001).  Critiquing the image:  Testing image adwatches as
journalistic reform.  Communication Research, 28, 181-207.
Leydon, G. M., Boulton, M. Moynihan, C., Jones, A., Mossman, J., Boudioni,
M., & McPherson, K.  (2000).  Faith, hope, and charity:  An in-depth
interview study of cancer patients' information needs and
information-seeking behavior.  Western Journal of Medicine, 173, 26-31.
Light, A.  (1999).  Fourteen users in search of a newspaper:  The effect of
expectation on online
behaviour.  [On-line].  Available:
http://www.cogs.susx.ac.uk/users/annl/Expectations.htm.
McKenna, K. Y. A., & Bargh, J. A.  (2000).  Plan 9 from cyberspace:  The
implications of the Internet for personality and social
psychology.  Personality and Social Psychology Review, 4, 57-75.
McKillan, D.  (2002).  The IMPACT of Internet penetration.  Medical
Marketing and Media, 37, 12.
Miller, J. D.  (2001).  Who is using the Web for science and health
information?  Science Communication, 22, 256-273.  Retrieved March 31, 2003
from OCLC FirstSearch database.
Morahan-Martin, J.  (1998).  Males, females, and the Internet.  In J.
Gackenbach (Ed.), Psychology and the Internet:  Intrapersonal,
interpersonal and transpersonal implications (pp. 169-197).  San
Diego:  Academic Press.
Nisbett, R. E., & Wilson, T. D.  (1977).  Telling more than we can
know:  Verbal reports on mental processes.  Psychological Review, 84, 231-259.
Ôunpuu, S., Woolcott, D.M., & Rossi, S. R.  (1999).  Self-efficacy as an
intermediate outcome variable in the transtheoretical model:  Validation of
a measurement model for applications to dietary fat reduction.  Journal of
Nutrition Education, 31, 16-22.
Petty, R. E., & Cacioppo, J. T.  (1984).  The effects of involvement on
responses to argument quantity and quality:  Central and peripheral routes
to persuasion.  Journal of Personality and Social Psychology, 46, 69-81.
Rimal, R. N.  (2001).  Perceived risk and self-efficacy as
motivators:  Understanding individuals' long-term use of health
information.  Journal of Communication, 51, 633-654.
Shapiro, M.  A.  (1994).  Think-aloud and thought-list procedures in
investigating mental processes.  In. A. Lang (Ed.), Measuring psychological
responses to media  (pp. 1-14). Hillsdale, NJ: Lawrence Erlbaum.
Smagorninsky, P.  (1989).  The reliability and validity of protocol
analysis.  Written Communication, 6, 463-479.
"Those with Internet access to continue to grow, but at a slower rate," PR
Newswire.  Retrieved March 31, 2003, from Lexis-Nexis database.
van Zoonen, L.  (2002).  Gendering the Internet:  Claims, controversies and
cultures.  European Journal of Communication, 17, (1), 5-23.
West, M. D.  (1994).  Validating a scale for the measurement of
credibility.  Journalism Quarterly, 71, 159-168.
Wetter, A. C., Goldberg, J. P., King, A. C., Sigman-Grant, M., Baer, R.,
Crayton, E., Devine, C., Drewnowski, A., Dunn, A., Johnson, G., Pronk, N.,
Saelens, B., Snyder, D., Walsh, K., and Warland, R.  (2001).  How and why
do individuals make food and physical activity choices.  Nutrition Reviews,
59 (3), S11-S20.
 Table 1
Time Spent on Web Sites by Participant
Participant
Searching
WebMD
Weight Watchers
Most Time Spent
1
4:53
Google.com (4:53)
2
4:33
ivillage.com (13:36)
3
3:15
3:30
health.netscape.com (7:44)
4
5:04
search.netscape.com (5:04)
5
2:36
10:02
weightwatchers.com (10:02)
6
1:56
oprah.com (11:27)
7
5:14
about.com (7:16)
8
6:44
2:09
google.com (6:44)
9
10:56
weightwatchers.com (10:56)
10
5:11
healthywomen.org (5:37)
11
2:28
10:07
webmd.com (10:07)
12
6:19
3:36
gulfmd.com (6:36)














 Table 2
Female Participants Sites Visited
Participant #1:
google.com
stottpilates.com
quakeroatmeal.com
ageless.com
healthandfitness.com
health-fitjrnl.com
personalhealthcare.com
yogaone.com
Participant #5:
weightloss-index.com
google.com
weightwatchers.com
broccoli.com
allrecipes.com
Participant #9:
weightwatchers.com
reebok.com
health.com
Participant #2:
ivillage.com
weightwatchers.com
prevention.com
Participant #6:
google.com
healthexpo.org
oprah.com
yahoo.com
health.yahoo.com
shopping.yahoo.com
Participant #10:
vegan.org
vrg.org
www.google.com
macrobioticcooking.com
imss.macrobiotic.net
mercola.com
veganoutreach.org
4woman.gov
healthywomen.org
Participant #3:
netscape.com
health.netscape.com
allhealthy.com
weightwatchers.com
Participant #7:
digitaljayhawk.com
diabetes.about.com
nutrition.about.com
search.msn.com
howstuffworks.com
Participant #11:
webmd.com
health.msn.com
Participant #4:
home.netscape.com
search.netscape.com
mentalhealth.org
samhsa.gov
quitnet.com
lungusa.org
families-first.com
cdc.gov
diabetes.org
fda.gov
dermatology.cdlib.org
nutrition.org
Participant #8:
microsoft.com
google.com
global-fitness.com
edietstar.com
wellness-fitness.com
webmd.com
momentum98.com
goldberg.getwebspace.com
Participant #12:
yahoo.com
gulfmd.com
webmd.com
2stepweightloss.com
www.swanson.com

Back to: Top of Message | Previous Page | Main AEJMC Page

Permalink



LIST.MSU.EDU

CataList Email List Search Powered by the LISTSERV Email List Manager