Getting the Message Across
Running head: OLDER ADULTS AND HEALTHCARE DECISION-MAKING
Getting the Message Across:
Examining Information Presentation and
Healthcare Decision Making Among Older Adults
Andrea Shamaskin
Cornell University
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Getting the Message Across
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Abstract
Previous research has demonstrated that the valence of healthcare messages influences
attitudes, and that the processing of valenced information changes with age (Carstensen &
Mikels, 2005; Levin, Schneider, & Gaeth, 1998). Study 1 examined differences in health
opinions and memory by presenting twenty-five older adults (M = 74.5 years) and twenty-four
younger adults (M = 20.3 years) positively and negatively framed messages in healthcare
pamphlets. Older adults rated positive pamphlets more informative than negative pamphlets and
remembered positive versus negative messages better than younger adults. There were no age
differences in health attitudes between positive and negative pamphlets. Study 2 replicated Study
1 using physician vignettes rather than pamphlets, yielding results trending in the predicted
direction with positive physicians rated more informed than negative physicians. These findings
demonstrate a positive bias in older adult memory, as well an influence of valence on their
perceptions of informative value.
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Getting the message across:
Examining information presentation and healthcare decision making among older adults
People are bombarded with messages about their health; television commercials, radio
advertisements, and even billboards contain information persuading people to buy a certain
product or talk to their doctor about an issue. Considering the vast amounts of money and time
spent creating these messages, one wonders about the actual impact of this information. The
purpose of the present study was to explore whether message effectiveness and memory for
messages varies across different populations, in particular between older and younger adults. A
secondary goal of this study was to explore message effectiveness in a social context, using
physicians as an information source.
Older adults, generally considered those aged 60 or older, are more likely than younger
age groups to face medical issues and, as such, make decisions about their healthcare more
frequently. Several decades ago, healthcare decision making among older adults focused on
managing illness and “damage-control,” but considering increasing life expectancies, healthcare
messages today have the opportunity to influence older adults’ preventative behaviors for certain
illnesses as well. In order to persuade people to perform risk-reducing and health-promoting
behaviors, it is crucial to understand how to present information to older adults in the most
effective way.
Methods of Information Presentation
There are several common varieties of healthcare advertisements, including before-andafter photographs, statistics of treatment outcomes, or statements addressing healthcare
behaviors. One way to change how this information is presented is through message framing.
Framing effects demonstrate that people’s preferences for a particular choice can be shifted
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depending on how the information is presented, even if the options are objectively identical
(Tversky & Kahneman, 1981). For example, risky-choice framing influences people’s risk
preferences, as people tend to choose a sure outcome when information is framed positively,
whereas negatively framed information influences people to choose a more risky option.
Tversky and Kahneman’s (1981) “Asian disease problem” is the classic example of risky-choice
framing. In this paradigm, the researchers found that the majority of subjects chose the certain
outcome when the situation was presented in positive terms (a guarantee of saving of one-third
lives), however they chose the risky option when the situation was presented in negative terms (a
one-third chance of losing no lives and a two-thirds chance of losing all the lives). From this
noteworthy study, researchers have pursued how framing a problem can influence decision
making through a variety of contexts and differing types of frames (for a review see Levin,
Schneider, & Gaeth, 1998).
Many health-related messages use a particular type of framing, known as goal framing, to
focus on people’s health related behaviors. Goal framing emphasizes performing a particular
behavior to either receive a benefit or avoid a negative consequence. For example, a positive
frame might read, “You can gain several potential health benefits by talking to your doctor about
high cholesterol. Take advantage of this opportunity.” Conversely, the negative frame would
read, “You can lose several potential health benefits by failing to talk to your doctor about high
cholesterol. Don’t fail to take advantage of this opportunity.” Both of these statements target the
same behavior (i.e. talking to a doctor about high cholesterol), however they have clearly
opposite emotional tones. This type of frame is unique because both the positive and negative
frames are aimed at encouraging the same end result—the difference between frames is whether
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it emphasizes receiving a health benefit of a behavior or avoiding a loss by performing the same
behavior.
Meyerowitz and Chaiken (1987) demonstrated the effect of goal framing in a study that
examined framing influences on women’s likelihood to engage in breast self-examinations
(BSE). They found that the women were more motivated to perform BSE through a negative
goal frame than they were to do BSE through a positive goal frame. They explained these
findings in that negative information has a more powerful effect on judgment and behavior than
positive information (i.e., a negativity bias). Other research on goal framing has shown that
when health information is processed deeply, negatively framed messages have a stronger impact
on behavior than positively framed messages (Block & Keller, 1995). Levin, Schneider, and
Gaeth (1998) argued for the same conclusion in their review of numerous goal-framing studies.
Some studies, however, have suggested differing results based on participant level of
involvement and perception of the addressed behavior as risky or not (Maheswaran & MeyersLevy, 1990; Rothman, Salovey, Antone, Keough, & Martin,1993). While these reevaluations of
goal framing studies focus on nuances such as preventative or detection based behaviors and
participant self-involvement in the targeted behavior, most of the research has not used agespecific participant populations to investigate age-differences in goal framing.
Nonetheless, there has been some research examining general framing effects between
younger and older adults. Kim, Goldstein, Hasher, and Zacks (2005) found that older adults
show increased framing effects as compared to younger adults for two risky-choice problems.
On the other hand, another study discovered limited differences in framing between older and
younger adults, again presenting participants with several risky-choice scenarios (Mayhorn, Fisk,
& Whittle, 2002). Lastly, recent research found that the influence of frame does change with
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age, as older adults were less risk-seeking (or less biased) in the loss frame than younger adults
(Mikels & Reed, in press). While these studies present somewhat conflicting results, a crucial
point and common thread between all three is that the studies focus only on framing with risky
decision-making. Within risky-choice framing, the positive frame describes options in terms of
gains. The negative frame instead focuses on an option in terms of loss. In a sense, this type of
frame asks people to make an objective decision and choose between two options, with these
options being essentially equal in value but presented in a positive or negative way. Goalframing influences people’s choices and decisions in an inherently different way than riskychoice framing. With goal-framing, both the positive and negative frames target the same
behavior, and the difference between frames refers to individual consequences from performing
or not performing the behavior (Levin, Schneider, & Gaeth, 1998).
There is good reason to believe that goal-framing might function differently between
older and younger adults. In the context of goal-framed healthcare information, participants are
assessing a message that relates to their own health and informs them of the consequences or
benefits for their bodies. These goals are very emotionally salient, and one could expect that
these frames would prompt an emotional response in older adults, more so than with risky-choice
framing. This idea is also supported by socioemotional selectivity theory (Carstensen,
Isaacowitz, & Charles, 1999), which proposes that as people age they are more motivated to
pursue emotionally meaningful goals. Based on this theory, a frame that evokes a more
emotional response or processing would presumably function differently between older and
younger adults because of these variations in motivational goals and emotion.
Age Differences Regarding Positive and Negative Information
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In contrast to the existing literature on goal-framing effects (Block & Keller, 1995;
Levin, Schneider, & Gaeth, 1998), an emerging body of research suggests that the relative
influences of positive and negative information shifts as people age, with older adults showing a
preference for positive versus negative information (Carstensen & Mikels, 2005). The positivity
effect is a developmental trend that demonstrates a shift in preferences, with younger adults
favoring negative information followed by a shift in adulthood in which older adults prefer
positive information. The positivity effect shows that older adults attend to emotionally positive
information, are able to keep it in mind, and remember it better than negative and neutral
information.
There has been a variety of research examining the positivity effect in regard to older
adults’ memory for positive and negative information. Charles, Mather, and Carstensen (2003)
found that while there was an overall decrease in image recall with age, the ratio of positive to
negative images recalled increased with age, the highest ratio being with older adults. Mikels,
Larkin, Reuter-Lorenz, and Cartensen (2005) discovered this bias with working memory,
demonstrating that older adults remembered positively valenced emotional information better
than negative emotional information. Other research found this effect even in older adults’
construction of the past, as older adults remembered the past more positively than they originally
reported several years earlier (Kennedy, Mather, & Carstensen, 2004). Lastly, recent research
has supported this suggestion through findings that older adults recalled more false positive than
false negative memories in three different recall tasks (Fernandes, Ross, Wiegand & Schryer,
2008). These authors note that false-memory data in older adults reflects strongly on the
positivity effect, in that older adults recreate the past to emphasize the positive. Overall, these
findings suggest a potential bias or even systematic distortion in the type of information that
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older adults remember. Considering these intriguing results, one might expect that when older
adults are drawing upon their cognitive resources to make a decision, positive information would
be more readily recalled or have a stronger influence than negative information.
This shift in preference for positive information as people age is based on the concept
that people’s emotional experiences and goals change as they age. Carstensen, Isaacowitz, and
Charles (1999) proposed that people’s goals and motivations are based in a temporal context,
with younger adults usually having a more open time perspective and older adults having a
limited time perspective. People with an open-ended time perspective are motivated to seek out
information and create novel relationships, in preparation for future life experiences where this
knowledge would be important. Those with a limited time perspective, as the theory posits, are
more focused on achieving emotionally meaningful goals and investing in emotional aspects of
their lives. They have a sense of the boundaries on their time, and as such, strive to fulfill
emotionally meaningful relationships and feel connected with others. Since the foundation for
this theory is in motivation towards emotion regulation, goal-framing is certainly appropriate
because it manipulates the consequence or goal of a certain personal behavior and influences
people at an emotional level to consider their own outcome.
Purpose of Study
The purpose of the current study was to examine how framing health information in
emotionally positive ways or emotionally negative ways may lead to different attitude and
memory outcomes between older and younger adults. Essentially, this is an investigation of the
interaction between the positivity effect and framing effects, particularly the emotionally salient
goal-framing. By implementing the positivity effect through the context of goal-framing, we can
better understand the strength of its influence in the health domain, as well as the factors that
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might weaken the effect. This experiment followed Meyerowitz and Chaiken’s (1987) model of
goal-framing, in which they presented information in pamphlet form in distinct positive and
negative frames. After developing our own pamphlets, we gathered information about attitudes,
intent to perform certain health behaviors, and informative value of the pamphlets. These postexperimental questions were adapted from measures used in three different studies that examined
goal-framing with health information (Block & Keller, 1995; Meyerowitz & Chaiken, 1987;
Rothman et al., 1993). Finally, participants completed a surprise statement recognition task
regarding the information presented.
This final memory task was intended to assess if there was an age-related difference in
delayed memory of the framed messages. In real-world situations, people are often provided
information about a healthcare issue but then must rely on their memory as they make a decision
days, weeks, or months later. This last portion of the experiment investigated whether positive
or negative information was remembered differently after a delayed period of time. Although
the current study used a statement recognition task rather than a memory recall task, it forced
participants to rely on their memory regarding information they read in the pamphlets. As the
memory feature of the experiment was completed several minutes after reading the pamphlets,
we expected this task to be moderately difficult. This delayed memory task presumably caused
participants to choose based on what they believe they remembered, thus creating an opportunity
to observe older adults’ preferences in information valence.
Based on the previous literature on goal framing and the positivity bias seen in older
adults, there were two major hypotheses for this portion of the experiment. First, it was expected
that older adults would be more influenced in their overall attitudes and intentions to perform
prevention/detection behaviors regarding health issues from a positive frame than a negative
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frame. Second, it was predicted that older adults would better remember positively framed
messages from the information pamphlets than negative messages. We expected that this effect
to manifest itself in that older adults’ proportion of positive to negative statements remembered
would be higher than the relative proportion for younger adults.
The goal of this investigation was to contribute new research examining lifespan
differences in framing effects, as evaluated through the lens of the positivity effect.
Additionally, we hoped to support the current research on emotion and memory across the
lifespan by demonstrating that older adults’ memory for positive information is better than
negative information. In another direction, if objectively negative information is systematically
remembered as positive, this pattern of results could demonstrate a memory distortion. These
findings would have implications for developing strategies of information presentation with
older adults. A piece of information may vary in its degree of influence depending on whether
decisions are made immediately after the information is presented or after a delayed period of
time.
Method
Participants
Twenty-five older adults ranging from 64 to 86 years of age (M = 74.52 years, SD = 6.01
years; 16 females & 9 males) and twenty-four Cornell University undergraduates ranging from
18 to 23 years of age (M = 20.27 years, SD = 1.24 years; 13 females & 11 males) participated in
this experiment. Older adults were recruited from the Ithaca, NY community and were
compensated $30 for their participation. Younger adults received course credit for their
participation.
Materials
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Pamphlet. Participants read four pamphlets that provided information about different
healthcare issues. Although realistically most health issues are more significant for older adults,
we chose particular health issues that would be matched on salience between older and younger
adults. The four health domains selected were influenza, cholesterol, skin cancer and sexually
transmitted diseases. These domains were also chosen in an effort to balance the saliency of the
health issue, with influenza and sexually transmitted diseases presumed to be more relevant to
younger adults and cholesterol and skin cancer more significant for older adults. Each pamphlet
focused on one of these health domains, and they were designed to look very similar to a
pamphlet or brochure that might be found in a physician’s office (See Figures 1 and 2 for
examples of pamphlet designs). They included general information about a particular health
domain, which was gathered from a reputable online health database (Centers for Disease
Control and Prevention; “Cholesterol”, 2007; “Key Facts About Seasonal Influenza (Flu)”, 2008;
“Basic Information About Skin Cancer”, 2008; “STD-Health Communication-Fact Sheets”,
2008).
Each pamphlet contained four statements that referred to actions or behaviors a person
could perform regarding their personal health with the disease or illness described. These
statements were modeled after Meyerowitz and Chaiken’s (1987) BSE study. As in their
experiment, statements were manipulated through the context of goal-framing to create two
pamphlets for each health domain, one including four positively framed statements and one with
four negatively framed statements. Pamphlets within each domain were identical except for
these four statements. For example, participants viewing the positive skin cancer pamphlet read:
“People who routinely check their own skin for changes or new growths are more likely to notice
potential signs of skin cancer”. Another participant viewing the negative skin cancer pamphlet
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read: “People who fail to routinely check their own skin for changes or new growths are less
likely to notice potential signs of skin cancer”.
Procedure
The design of this experiment used E-Prime experimental software which assigned each
participant to read four pamphlets, with a counter-balanced assignment for two pamphlets to
include negative framing and two to include positive framing. The program also controlled for
order effects between participants, with the four pamphlets read in a randomized order.
Instructions for the experiment were presented on a desktop computer screen, however a
researcher was in the room throughout the experiment to answer any questions. Before reading
the pamphlets, participants were asked if they had a history of any of the four health domains
that would be used in the study. Participants then read one pamphlet at a time, and were given
an unlimited amount of time to read each pamphlet. When participants finished reading one
pamphlet, they returned the pamphlet to the researcher conducting the experiment. Participants
were instructed that they would answer several questions on the computer about the pamphlet
they had previously read. They responded to five questions that asked about their attitudes,
perceived vulnerabilities and intended health behaviors regarding the health issue, as well as the
informative value of the pamphlet they just read. These questions were modeled from the postexperimental questions used in three goal-framing healthcare studies (Block & Keller, 1995;
Meyerowitz & Chaiken, 1987; Rothman et al., 1993) (See Appendix A).
All questions asked participants to respond on a 7-point Likert-type scale. This process
was repeated for all four pamphlets. After reading and rating the pamphlets, participants
completed a surprise statement recognition task, intended to evaluate their memory of the
information provided in the pamphlets. In total up to this point, each participant had viewed 16
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framed statements (4 statements in each pamphlet X 4 domain-specific pamphlets). In this final
portion of the experiment, participants viewed a pair of statements, containing one statement that
they saw in one of the pamphlets they read, while the other statement was informationally
equivalent but oppositely-valenced. For example, in one of the 16 recognition trials, a
participant were presented two statements on the computer screen:
“Research shows that people who regularly check their cholesterol levels have an
increased chance of recognizing their risks for other related health issues.” [positive frame]
“Research shows that people who do not regularly check their cholesterol levels have a
decreased chance of recognizing their risks for other related health issues.” [negative frame]
Participants were asked to identify which statement they remembered reading in the
pamphlet. This process continued for the 16 pairs of statements. The order that the statements
were presented was counter-balanced by statement valence. The positive statement appeared
first for half of the pairs and the negative statement first for the other half in order to avoid any
response biases in consistently choosing the first statement. Additionally, the order of the
statement pairs regarding domain was randomized in an attempt to control for primacy or
recency effects. Finally, participants were debriefed on the experiment and thanked for their
participation. The approximate time of the experiment was 25-30 minutes.
Results
Post-pamphlet questions 1 through 5 conceptually measured different constructs
regarding attitudes toward the health issue, intended behaviors, and the informative value of each
pamphlet. Predictably, the reliability between these outcome scores was moderately low
(Chronbach’s alpha = 0.61). Therefore, we conducted our analyzes on each individual question.
There was a significant effect of gender for Question 5, with females reporting across domains
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that the pamphlets were more informative (M = 5.39, SD = 0.27) than males (M = 4.38, SD =
0.33), F (1, 47) = 5.51, p < .05. The scope of this study, however, does not address gender
differences, and this result will not be discussed further. It also is worth noting that the gender
effect could be attributable to having nearly twice as many female as male participants.
Preliminary analyses revealed no effects for pamphlet order. Thus in the following
analyses, we assume no order-effects or effects from participant fatigue. The data were analyzed
in a mixed-model Analysis of Variance (ANOVA), with age, valence, domain, and personal
history as fixed factors and subject as a random factor.
Pamphlet Ratings
There was a main effect of age for three of the five post-pamphlet questions. Older
adults had higher ratings than younger adults for Question 1, Question 3, and Question 5 (See
Table 1). There was an effect of pamphlet valence for Question 5, in which the positive
pamphlets were rated more informative (M = 5.18, SD = 0.21) than the negative pamphlets (M =
4.80, SD = 0.21, F (1, 135) = 8.60, p < .05. There were no effects of pamphlet valence on any of
the other post-pamphlet questions.
Interaction Effects
There were no significant interactions between age and valence, F (1, 135) = .01, ns, for
four of the five post-pamphlet questions. There was an interesting interaction between age and
valence for Question 5, which asked participants how informative they believed the pamphlet
was, F (1, 135) = 7.83, p < .05 (See Figure 3). Older adults reported that positive pamphlets
were more informative (M = 6.01, SD = 0.29) than the negative pamphlets (M = 5.34, SD =
0.29), while younger adults did not differ in this rating (M = 4.28, SD = 0.29 for positive
pamphlets, M = 4.27, SD = 0.29 for negative pamphlets). There was also a three-way interaction
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between age, valence, and domain for Question 5 (F (1, 86.92) = 2.98, p < .05), in which across
all four health domains, older adults rated the positive health pamphlets as more informative than
the negative health pamphlets. This difference, however, did vary somewhat between health
domains, with larger differences between the positive and negative cholesterol and skin cancer
pamphlets than between the influenza and sexually transmitted diseases pamphlets.
Pamphlet Domain and Participant History
There was a main effect of pamphlet domain across all five post-pamphlet questions (See
Table 2). However, since there were no predictions regarding differences in pamphlet domain,
this result will not be discussed further.
There was a cross-over interaction between the participant age and personal history for
three of the five post-pamphlet questions (See Table 3). Across all domains, older adults who
confirmed they had a history of the health issue responded higher on scales measuring intentions
to perform health behaviors and the informative value of the pamphlet than those who reported
no history. Younger adults, on the other hand, showed an opposite effect. Those who
confirmed that they had a history of the health issue responded lower on these scales than those
who had no history of the issue. We also note that there was an interaction between age and
personal history for Question 1, however this was not in the predicted direction.
Recognition Performance
For the statement recognition task, responses were coded for accuracy (0 = incorrect, 1 =
correct) based on whether participants chose the proper statement from the particular pamphlet
they read. As explained in the methods section, each participant saw four pamphlets total, two as
negatively framed and two as positively framed. They responded to 16 statement recognition
tasks (four statements in four pamphlets). These data were analyzed through a Generalized
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Estimating Equation (GEE), which can be used for within-cluster correlations in regression
models with binary outcomes. For this portion of the experiment, the GEE is an appropriate
analysis because it takes into consideration that every subject was repeatedly measured on 16
trials, and these responses were binomially distributed. We also analyzed accuracy in a t-test
against the value 0.5 so as to determine an effect that is significantly different from chance (50%
accuracy).
There was no significant difference in accuracy between the two age groups, ² (1, N =
784) = 1.746, ns. Of the 16 recognition tasks, younger adults chose the correct statement 64% of
the time (SD = 0.03), as compared to older adults who were accurate 58% of the time (SD =
0.03).
Positive statements were more accurately recognized than negative statements for all
participants, ² (1, N = 784) = 29.286, p < .001. For trials where a positive statement should
have been chosen, participants had an accuracy rate of 80% (SD = 0.02). When a negative
statement should have been recognized, participants were accurate on 41.3% of the trials (SD =
0.03).
There was a significant interaction between age and valence for accuracy of statement
recognition, ² (1, N = 784) = 4.607, p < .05 (See Figure 4). Younger adults were more accurate
in their positive statement recognition tasks (M = .78, SD = 0.03) than negative statement
recognition tasks (M = .50, SD =0.05). For the negative statements, younger adults were at
chance for accuracy, recognizing approximately half of the negative statements correctly t (191)
= .000, ns. Their accuracy for recognizing positive statements was significantly higher than
chance t (191) = 9.402, p < .001.
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Older adults also were more accurate in recognizing positive statements (M = 0.83, SD =
0.03) than negative statements (M = 0.33, SD = 0.05). A one-sample t-test demonstrates that
their accuracy for recognizing positive statements was significantly higher than a value of 0.5, t
(199) = 12.066, p < .001. Interestingly, older adults’ accuracy for recognizing negative
statements was significantly lower than chance (t (199) = -5.271, p < .001), indicating that for
the negative recognition statements, older adults are not simply guessing. For a significant
portion of statement recognition tasks in which older adults should have chosen the negative
statement, they instead chose the positive statement that was never actually presented to them.
Discussion
For Study 1, our first hypothesis was rooted in socioemotional selectivity theory and the
positivity effect, both of which suggest that older adults would be more influenced by positively
framed messages in the personally salient healthcare domain. This hypothesis was partially
supported by the results from Question 5, in that the frame of the pamphlet influenced
participant’s reported informative value of each pamphlet. There were no significant interactions
between age and pamphlet valence for the other four post-pamphlet questions. This combination
of findings is meaningful in that the effect of frame does not seem to influence people’s opinions
about particular health issues, however the frame does affect people’s more general evaluation of
the information source.
There are several potential explanations for why we did not find the expected result for
the four questions that targeted attitudes and intended behaviors about each health domain. First,
the manipulation might have simply not been sufficiently strong; the positive and negative
statements may not have been powerful enough to alter participants’ attitudes about the
healthcare issues. One challenge to choosing an experimental domain is that participants need to
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care enough about the issue to pay attention to the information provided, however not be so
invested in the issue that their opinions cannot be changed. We chose healthcare as a general
domain to ensure that participants would have some personal interest in the information. In
order to prevent any one domain as being too personally relevant to an individual participant, we
included the four different health domains in the experiment. Although we attempted to find a
balance between salience of issue and malleability of participant’s attitudes, this balance may
have been too subtle, and as such, rendered our manipulation only partially successful.
The pamphlets themselves did contain a significant amount of information, and this may
have discouraged older adults from fully engaging in the task or thinking deeply about the
healthcare issues presented. We attempted to account for this in our experimental design by
counterbalancing the order and valence of pamphlets presented and giving participants an
unlimited amount of time to read each pamphlet. Unfortunately, it is difficult to completely
control for these potential confounds, which may have influenced our results. In addition, our 7point scale used to measure the outcome variables may not have been sensitive enough to detect
the differences in manipulation.
There were significant results in the statement recognition task. Older adults accuracy
rates for positive and negative statement recognition were significantly higher and lower than
chance, respectively. This result suggests that older adults have some bias or systematic
distortion in the valence of information they recognize during a memory task. Younger adults
had similar accuracy rates to the older adults for the positive statements. This overall positive
bias may have been because the positive statements were easier to recognize, as several of the
negatively framed statements included double-negative language emphasizing a behavior that
avoided a loss. The strongest and perhaps most interesting result appears when comparing
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younger and older adults on negative statement recognition. Younger adults had a 50% accuracy
rate for the negative statements, which is what one would expect if participants were randomly
guessing which of the statements they recognized. On the contrary, older adults had a 33%
accuracy rate for the negative statements. This result indicates that on approximately 67% of the
recognition trials where older adults should have chosen the negative statement, they responded
that they saw the positive statement instead. If older adults were simply guessing or did not
remember which statement they read, one could expect a 50% accuracy rate, similar to the
younger adults. Our results, on the other hand, demonstrate that there is some bias in the
information older adults are remembering or that they are distorting their memory for
information in an increased positivity/reduced negativity manner.
This interesting finding supports the positivity effect in a particular way. As has been
noted in previous literature, one way to examine the positivity effect is by considering the ratio
of positive to negative information recalled between older and younger adults (Charles, Mather,
& Carstensen, 2003). In our study, both younger and older adults showed an overall bias in the
positive direction, however the ratio of positive to negative messages recognized increased with
age. We must note that while this result lends support for the positivity bias, our experimental
design did not allow for more exact identification of the mechanism underlying this effect with
older adults. Since the statement recognition task involved a forced-choice measure, we cannot
determine if older adults were avoiding the negative statements in favor of the positive (i.e.
decreased negativity bias), or if they were actually distorting their memories for the statements
(i.e. increased false positive memories). Nevertheless, this finding is important for research
examining how to best present healthcare information to older adults because they often rely on
their memory when making a medical decision. It is rare for people to gather information about
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a health issue or the risks and benefits of a treatment, and then immediately make a decision
regarding that issue. Therefore, this research is significant because it demonstrates that it is not
necessarily older adults’ immediate impressions of a health issue that is important, but instead
what information they remember when making a later decision.
There were a few unexpected results from Study 1, which fostered ideas for follow-up
studies and future experiments. Personal history appears to have a large impact on how people
evaluate a health issue, and this effect operates in an opposing manner between older and
younger adults. For older adults with a history of an illness, they responded with higher scores
(as compared to older adults without a history) to questions that targeted intentions to perform
health behaviors and the informative value of the pamphlet. On the contrary, younger adults
with a history of illness or disease reported lower scores to these questions than younger adults
without a history. This interesting effect suggests that older adults who have experienced an
illness become more aware of its seriousness and act with proactive health behaviors. Younger
adults with a history of the illness instead appear to downplay its seriousness, believing that it is
unimportant to proactively avoid the illness in the future. These results match with the concepts
of adolescent invulnerability (Lapsley, 1993), where perhaps these younger adults who have
experienced an illness feel more confident about their future vulnerability.
Another unanticipated finding from this study is that older adults rated the pamphlets
with positively-framed messages as more informative than those with negatively-framed
messages. It seemed that when judging the overall informative value of the pamphlet, older
adults again demonstrated a positive bias. In real-world situations, older adults often take advice
or guidance regarding healthcare decisions from their physicians. Throughout these interactions,
older adults are presumably making evaluations and judgments about their physician’s
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competence and persuasiveness, similar to the construct targeted by Question 5 in Study 1. If
older adults are evaluating a pamphlet as more informative because it contains more positive
statements, would this effect manifest itself in older adults’ evaluations of their physicians?
Study 2
Study 2 sought to further explore the relationship between positive pamphlets and their
perceived informative value. However, we wanted to replicate this finding in a more social
context. Physicians are a much more naturalistic healthcare information source for older adults
than health pamphlets. One study found that 75% of people aged 65 and older stated that they
would first seek out their personal healthcare provider when searching for information about
cancer (Hesse, Nelson, Kreps, Croyle, Arora, Rimer, et al., 2005). Other research suggests that
older adults form social impressions differently than younger adults. Specifically, older adults
are better able to discriminate between the more and less informative aspects of individuals’
behaviors (Hess & Auman, 2001; Leclerc & Hess, 2007). These studies support the idea that
increased age reflects an increase of social expertise resulting from the accumulation of social
experiences, which would certainly play a role in older adults’ judgments of their physicians.
Considering that socioemotional selectivity theory is based on people’s motivation to
pursue emotionally-meaningful experiences and emotional satisfaction as they age, perhaps older
adults would place more value on a physician who carries a positive, optimistic attitude versus a
negative attitude. This question is important to examine because patient-physician
communication is a critical aspect of older adults’ health. Understanding the mechanisms that
influence how older adults evaluate their physicians has implications for patient satisfaction and
adherence to treatments. Exploring from the results of Study 1, the purpose of Study 2 was to
further understand how positive and negative information influences older adults’ attitudes and
Getting the Message Across
22
impressions in a more social, less cognitively complex task. We hypothesized that older adults
would rate physicians who provide health advice using positively-framed statements as more
informative and persuasive than physicians who use negatively-framed statements.
Method
Participants
Seventy-eight older adults ranging from 61 to 90 years of age (M = 74.25 years, SD =
7.35 years; 48 females & 30 males) and eighty younger adults ranging from 18 to 23 years of age
(M = 19.86 years; SD = 1.16 years; 55 females & 25 males) participated in this experiment.
Older adults were recruited from the Ithaca, NY community and were compensated $10 for their
participation. Younger adults were recruited from Cornell University and received course credit
for their participation.
Measures
We developed a short questionnaire that provided brief dialogues from four different
doctors, each addressing a different health domain. We chose four common last names to create
the physicians’ names (Smith, Williams, Jones, and Miller). Each doctor, however, was only
referred to as “Dr. ______” in order to avoid any suggestion of the doctor’s gender. For
continuity purposes, the four health domains chosen were the same as in Study 1: influenza,
cholesterol, skin cancer, and sexually transmitted diseases. The brief dialogues from each doctor
were composed of the same four positive or negative statements used in the pamphlets from
Study 1. The statements were slightly modified grammatically to make the dialogue seem as if
were spoken to the participant. (See Appendix B for an example of a positive-physician
vignette).
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23
This measure also included a questionnaire following each physician vignette. The
questionnaire asked participants to rate on a ten point Likert-type scale their impressions about
how informed and persuasive they believed the physician to be. For continuity, we also included
questions from Study 1 regarding participants’ attitudes and beliefs about the healthcare issue
(See Appendix C). In Study 1, the majority of participants rated their opinions about the
healthcare issues on the higher end of the scale, many within the 5, 6, and 7 range. This trend
may have been one of the reasons for few significant effects in Study 1; participants’ ratings,
regardless of the pamphlet valence, were very close together. In Study 2, we chose to use a ten
point scale in hopes that a larger scale would make the effects of valence easier to distinguish.
Procedure
This portion of the study involved a 2 (age) X 2 (valence) between-subjects design.
Participants were randomly assigned to either the positive or negative condition and received the
corresponding questionnaire. After reading the instructions page, participants were given the
opportunity to ask the experimenter any questions before proceeding to the actual questionnaire.
Each questionnaire contained the brief physician dialogue and attitude/opinion questions for all
four healthcare domains. The order of these domains was randomized as each packet was
assembled. At the end of the questionnaire, participants indicated “yes” or “no” to whether they
had participated in our previous pamphlet study (Study 1). The amount of time required to
complete this questionnaire was approximately 15 minutes.
Results
For the purposes of this study, the main interest focused on examining how valence
influenced participants’ impressions of how informed and persuasive they believed their
physician to be. Therefore, the analyses only included the questions that targeted these specific
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24
factors. The analysis conducted was a mixed-model ANOVA, because each participant had
ratings for four different doctors; this analysis designates age and valence as fixed variables and
subject as a random variable. Additionally, a composite variable was developed to identify the
overall impression of the physician. Question 1 targeted how informed participants believed the
physician to be, while Question 2 asked how persuasive the physician was in the vignette. The
reliability between these two variables was very high (Chronbach’s alpha = 0.89), therefore the
analyses could collapse responses to these questions within each physician vignette.
There was a main effect of age on the participants’ ratings of the composite variable, F
(1, 153) = 10.62, p < .05. Older adults overall rated physicians as more informed and persuasive
(M = 7.05, SD = 0.17) than the younger adults did (M = 6.26, SD = 0.17). However, there was
no effect of physician valence on the participants’ composite evaluations of the physicians (F (1,
153) = 2.75, ns). There was no significant interaction between age and valence for participants’
ratings on the composite informed/persuasive variable, F (1, 153) = 1.57, ns. Participant ratings
did trend in the predicted direction, with older adults rating positive physicians as higher (M =
7.43, SD = 0.24) than the negative physicians (M = 6.67, SD = 0.24). Younger adults did not
appear to differ in their evaluations between positive physicians (M = 6.31, SD = 0.24) and
negative physicians (M = 6.21, SD = 0.24). To explore this result further, we analyzed the
specific pairwise comparison between positive and negative physicians within only the older
adult group, which was marginally significant, F (1, 75.28) = 3.36, p = .07 (positive physician,
M = 7.43, SD = 0.24; negative physician, M = 6.67, SD = 0.24) (See Figure 5).
Discussion
Study 2 sought to expand a finding from Study 1, in which valence influenced older
adults’ evaluations of the informative value of a particular source. In Study 1, this health
Getting the Message Across
25
information source was a pamphlet, whereas Study 2 used a physician as the source for health
information. We did not find a statistically significant difference between older adults’ ratings of
physicians based on the valence of the vignette. These ratings did trend in the predicted
direction, and perhaps with a larger sample size, the effect would become significant. Younger
adults, on the other hand, did not appear to be influenced by physician valence when evaluating
the persuasiveness and informative value of a physician. These results suggest that there is some
change as people age in the ways that they evaluate their physicians. Within the older adult
group, this effect appears to be influenced by the positive or negative tone of the physician.
General Discussion
These studies examined the strength of positively and negatively framed information as
an influence on older and younger adults’ opinions, attitudes, and memory for particular health
issues. Previous literature on typical framing effects and the positivity bias in old age indicate
two conflicting predictions regarding information presentation to older adults. Goal-framing
research has shown that negative frames more strongly influence people in regards to proactive
health behavior and opinions. The positivity effect, on the other hand, theorizes that processing
emotional information changes with age, and older adults seek out positive information and
remember it better than negative information. Within the goal-framing literature, no studies to
our knowledge have used age-specific populations, and the existing research examining aging
and framing have used only risky-choice paradigms. This study attempted to distinguish
between these opposing predictions and add to existing knowledge in the aging and decisionmaking field in an area that has not been previously investigated. It is important to note that this
research project was relatively exploratory in nature. Both the framing and positivity effect
literature recognize that the effects can be subtle or easily influenced by a variety of factors.
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26
Research on persuasion even suggests that time of day can have a strong influence on whether
older adults implement a central or peripheral processing strategy (Yoon, Lee, & Danziger,
2007). Central and peripheral processing are inherently different processing strategies, with one
focusing on the content of the information and the other on superficial factors, respectively. This
finding by Yoon, Lee and Danziger (2007) demonstrates that older adult decision-making can be
easily affected by seemingly trivial factors, such as time of day. The field of cognitive and
emotive processing with older adults contains complex and sensitive processes that are still not
fully understood. This research, however, hopes to contribute to the field by testing theories in a
practical context that easily applies and translates into the healthcare domain.
There are several major strengths to Study 1, including the experimental design and
various controlled factors. The positive and negative pamphlets were very comparable, as they
used the exact same physical design and color scheme, and they contained the same bulleted lists
of information about the healthcare issue. The only areas that differed between the pamphlets
were the four framed statements, which were bolded in both the positive and negative pamphlets.
This equivalence allowed us to conclude that any differences in outcome variables from Study 1
were due to differences in pamphlet valence and not other uncontrolled factors. Another strength
of this study is that it implemented several different healthcare domains. It is probable that
healthcare issues are a more salient topic to older adults in general. However, by using a variety
of health issues, we eliminated the potential confounds of one highly salient domain (e.g., skin
cancer) or one less significant domain (e.g., sexually transmitted diseases).
The pamphlets themselves appeared similar to pamphlets found in a physician’s office,
and they contained health information from a national health database. These factors lend
support to the ecological validity of this study. Although it would be nearly impossible to evoke
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27
the same emotional response in participants as if they were in an actual healthcare setting, the
pamphlets looked relatively realistic and presumably induced some genuine emotions and
thoughts about the presented healthcare issues. Additionally, most previous studies of the
positivity effect have used stimuli such as emotional pictures (Charles, Mather, & Carstensen,
2003; Mikels, Larkin, Reuter-Lorenz, & Carstensen, 2005) or faces (Mather & Carstensen,
2005). Our experiment tested the positivity effect using pamphlets and valenced healthcare
messages, a realistic and practical medium that is easily translated into the healthcare domain.
Another major strength regarding the relationship between Study 1 and Study 2 lies in the
comparability of the valenced statements. The vignettes in Study 2 contained the same
statements used in the pamphlets and statement recognition task of Study 1. In this sense, we
were able to transform Study 1 into Study 2 by essentially personifying the pamphlets, targeting
the social aspects of information processing between older and younger adults. Additionally,
altering the scale from Study 1 to Study 2 allowed clearer observation of the effects on outcome
measures. In Study 1, a majority of participants chose ratings on the higher end of the 7-point
scale. The marginally significant results from Study 2 (which used a ten-point scale) suggest that
a larger scale would have been useful in Study 1. Lastly, considering the experimental design of
the Study 1, it was beneficial to implement valence as a within-subjects factor across several
different domains. This design compensated for our small number of participants by enhancing
the power in our analyses.
One limitation of Study 1 is that it used a relatively small subject pool from a
homogeneous convenience sample. Although we tried to offset the effects of a small sample by
implementing a within-subjects factor, the limited number of participants potentially contributed
to the insignificant results from Study 1. It is possible that a larger sample would detect the
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28
predicted differences between age groups and responses to emotionally positive or negative
healthcare information. Additionally, we only used one question per construct in the postpamphlet measures, which made it difficult to ensure construct validity or improve statistical
power in these responses.
This experiment examined people’s immediate opinions of health issues and intended
behaviors, however to enhance the ecological validity of the studies, it would be important to
observe peoples’ actual behaviors. Future studies expanding on this experiment would benefit
from a longitudinal design for several reasons. First, it would be important to follow up with
participants’ actual behaviors, for example observing if people actually wore sunscreen more
frequently after reading a skin cancer pamphlet. Second, the memory task from Study 1
demonstrated a bias in the type of information that older adults remembered, however this delay
was approximately 15 minutes long. To gain a better understanding of the pervasiveness of this
effect, it would be important to conduct memory tasks with the participants days, weeks, or even
months later. This extended duration of “delayed decision-making” is more realistic considering
the time frame when people are presented information and when they must recall the same
information to make a health-related decision.
These studies present a new perspective on how older and younger adults differ in their
emotional processing as it relates to health related decisions and perceptions. The effectiveness
of providing healthcare information to older adults can vary based on several factors, including
health domain, personal history, and the emotional tone of the information source. Our results
demonstrate that emotion plays a role in the type of information that older adults remember,
indicating that positively-framed healthcare information may have stronger long-term
effectiveness than negatively-framed messages. Lastly, these trends can have applications in
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broader health contexts, including patient-physician communication, the patient-physician
relationship, and other concepts in the emerging field of patient-centered medicine (Stewart,
Brown, Weston, McWhinney, McWilliam, & Freeman, 2003). With the increasing older
population, these topics become even more important to consider. It is critical to better
understand how older adults view and process health issues so that we can provide them the
optimal information for their important health-related decisions.
29
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30
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Author Note
I would like to thank Dr. Joseph Mikels for his guidance and encouragement with this
project. I would also like to thank Dr. Marianella Casasola and Andrew Reed for their support
and feedback throughout the course of the entire research process. This research was conducted
as fulfillment of the undergraduate honors program. Partial funding was provided by the Human
Ecology Alumni Association Student Grant, College of Human Ecology, Cornell University.
Correspondence concerning this article should be addressed to Andrea M. Shamaskin,
Department of Human Development, Cornell University, Ithaca, NY 14850.
Email: [ams357@cornell.edu]
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Appendix A
Question 1: Do you think influenza is a serious health problem?
─−1─−2─−3─−4─−5─−6─−7─−
Not at all
Extremely
Question 2: What do you think is your likelihood of contracting influenza?
─−1─−2─−3─−4─−5─−6─−7─−
Not at all
Extremely
Question 3: How likely are you to get the influenza vaccine and practice preventative
behaviors?
─−1─−2─−3─−4─−5─−6─−7─−
Not at all
Extremely
Question 4: How likely are you to see your doctor if you notice symptoms of influenza?
─−1─−2─−3─−4─−5─−6─−7─−
Not at all
Extremely
Question 5: How informative was this pamphlet?
─−1─−2─−3─−4─−5─−6─−7─−
Not at all
Extremely
Concepts intended to measure per question:
Question 1: Attitude toward health issue
Question 2: Perceived vulnerability
Question 3: Intention to perform preventative behaviors
Question 4: Intention to perform detection behaviors
Question 5: Informative value of pamphlet
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35
Appendix B
Imagine you are meeting with a new doctor, Dr. Smith, to talk about a cholesterol issue. Dr.
Smith tells you:
By asking me about your cholesterol levels, you can take a proactive approach to regulating your
overall health. Research shows that people who are aware of their cholesterol levels have an
increased chance of recognizing their risks for other related health issues. By watching your diet
and exercising regularly, you can maintain control over your cholesterol levels. You can gain
several potential health benefits by practicing healthy lifestyle behaviors. Take advantage of this
opportunity.
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Appendix C
Please read the following questions and CIRCLE your number choice on the
scale.
After meeting with Dr. Smith, how informed do you think Dr. Smith is about cholesterol?
1--------2--------3--------4--------5--------6--------7--------8--------9--------10
Dr. Smith knows
nothing about cholesterol
Dr. Smith is the leading
expert on cholesterol
How persuasive do you find Dr. Smith?
1--------2--------3--------4--------5--------6--------7--------8--------9--------10
Not at all persuasive
Extremely persuasive
Do you think cholesterol is a serious health problem?
1--------2--------3--------4--------5--------6--------7--------8--------9--------10
Not at all
Extremely
What do you think is your likelihood of developing high cholesterol?
1--------2--------3--------4--------5--------6--------7--------8--------9--------10
Not at all likely
Extremely likely
How likely are you to change your diet or amount of exercise in order to adjust your
risks for high cholesterol?
1--------2--------3--------4--------5--------6--------7--------8--------9--------10
Not at all likely
Extremely likely
How likely are you to get a blood test in order to check for high cholesterol?
1--------2--------3--------4--------5--------6--------7--------8--------9--------10
Not at all likely
Extremely likely
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37
Table 1
Responses to post-pamphlet questions by age group
Older Adult
Mean (SD)
Younger Adult
Mean (SD)
Question 1
5.21 (0.16)
4.38 (0.16)
F (1, 45) = 10.61, p < .01*
Question 2
3.59 (0.17)
3.67 (0.17)
F (1, 45) = 0.12, ns
Question 3
5.75 (0.24)
4.48 (0.25)
F (1, 45) = 13.51, p < .01*
Question 4
4.89 (0.22)
4.30 (0.23)
F (1, 45) = 3.41, ns
Question 5
5.68 (0.28)
4.28 (0.29)
F (1, 45) = 12.38, p < .01*
The rightmost column presents results from a mixed model Analysis of Variance (ANOVA)
* p < .01.
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Table 2
Responses to post-pamphlet questions by health domain
Influenza
Cholesterol
Skin Cancer
6.00 (.19)
Sexually
Transmitted
Diseases
6.08 (.19)
Question 1
4.75 (.19)
5.83 (.19)
F (3,135) = 17.55 *
Question 2
3.96 (.21)
3.92 (.21)
2.19 (.21)
4.44 (.27)
F (3,135) = 25.1 *
Question 3
4.55 (.26)
4.81 (.26)
5.89 (.26)
5.21 (.26)
F (3, 135) = 6.51 *
Question 4
4.86 (.25)
5.30 (.25)
3.42 (.25)
4.82 (.25)
F (3, 135) = 13.86 *
Question 5
4.70 (.22)
5.21 (.22)
4.83 (.22)
5.17 (.22)
F (3, 135) = 4.58 *
The rightmost column presents results from a mixed model Analysis of Variance (ANOVA)
* p < .01.
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Table 3
Responses to post-pamphlet questions by age and personal history
OA-history
Mean (SD)
OA-no history
Mean (SD)
YA-history
Mean (SD)
YA-no history
Mean (SD)
Question 1
5.85 (.27)
6.26 (.25)
3.66 (.35)
5.48 (.22)
F (1, 144.9) = 11.35*
Question 2
4.47 (.27)
2.85 (.28)
4.52 (.41)
3.48 (.18)
F (1, 167.7) = 1.05
Question 3
6.02 (.35)
5.49 (.31)
3.34 (.48)
4.72 (.26)
F (1, 153.7) = 9.26*
Question 4
5.52 (.35)
4.29 (.30)
3.87 (.51)
4.42 (.25)
F (1, 160.9) = 6.67*
Question 5
5.84 (.32)
5.61 (.31)
3.52 (.35)
4.42 (.29)
F (1, 136.4) = 12.50*
Note: OA = Older adult, YA = Younger adult
The rightmost column presents results from a mixed model Analysis of Variance (ANOVA)
* p < .05.
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Figure Captions
Figure 1. Pamphlet design of positive Skin Cancer pamphlet.
Figure 2. Pamphlet design of negative Skin Cancer pamphlet.
Figure 3. Response to Question 5 by Age and Valence.
Figure 4. Accuracy on memory recognition task by Age and Valence. The dashed line
represents an “at-chance” accuracy rate.
Figure 5. Participant ratings on physician informed/persuasive score by Age and Valence.
40
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Figure 1.
41
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Figure 2.
42
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Figure 3.
Valence
Neg
Pos
Mean Q5
6
4
6
5.34
4.229
2
0
Older
Younger
Age
Error bars: +/- 1 SE
4.292
43
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Figure 4.
44
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Figure 5.
45