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Influence of sad mood and old age schema on older adults' physical symptoms processing

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Influence of sad mood and old age schema on older adults' physical symptoms processing

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Content INFLUENCE OF SAD MOOD AND OLD AGE SCHEMA ON OLDER ADULTS’
PHYSICAL SYMPTOMS PROCESSING

by

Cecilia Yee Man Poon

A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF ARTS
(PSYCHOLOGY)

December 2007

Copyright 2007 Cecilia Yee Man Poon

ii
Table of Contents

Acknowledgements iii
List of Tables iv
List of Figures v
Abstract vi
Chapter 1: Introduction 1
Chapter 2: Method 12
Chapter 3: Results 22
Chapter 4: Discussion 31
References 41
Appendix 47

iii
Acknowledgements
I would like to thank my advisor and committee members for their valuable
comments and support. I am grateful to those who have given their time generously to
listen to my random musing on research, especially my parents and friends. My
thanks also go to every individual and senior center that participated in my study.

iv
List of Tables
Table 1: Demographic Information 12
Table 2: Word Lists for Modified Stroop Task 18
Table 3: Mood Change due to Induction: Means of CES-D and DACL 22
Table 4: Multiple Comparisons of Attentional Bias to Physical Symptoms 25
Table 5: Comparison of regression slopes of baseline reaction time and
attentional bias to physical symptoms 26

Table 6: Summary of Regression Analysis for Variables Predicting Physical
Symptoms Endorsed for the Past Week 30

Table 7: Summary of Regression Analysis for Variables Predicting Physical
Symptoms Endorsed during the Experiment 30

v
List of Figures

Figure 1: Old age schema activation. Error bars represent standard errors 23
Figure 2: Attentional bias to physical symptoms. Error bars
represent standard errors 24

vi
Abstract
This study examined how situational mood state and old age schema influenced
attention to physical symptoms in older adults. Seventy-one individuals aged 60 or
above participated in an experiment that manipulated mood and old age schema.
Participants completed a modified Stroop task that measured attentional bias to
symptom words. Analysis of variance showed that sad mood and old age schema had
significant main and interaction effects on attention to physical symptoms. Neither
variable affected symptoms reporting. Either sad mood or old age schema reversed
participants’ tendency to divert their attention from physical symptoms. When
combined, they led to an attentional bias towards physical symptoms. Interventions
to reduce attentional focus on physical symptoms among older adults who have a
tendency to somatisize should include strategies to lessen both sad mood and
age-related stereotypes.

1
CHAPTER 1: INTRODUCTION
Cognitive processing of physical symptoms has important implications in health
decision making and experiences of discomfort (e.g. Haug, Musil, Warner, & Morris,
1998; Tessler, Mechanic, & Diamond, 1976; Tessler & Mechanic, 1978). Self-reports
of physical symptoms were consistent and significant predictors of hospitalization,
utilization of health services, and mortality in old age, even when other clinical
characteristics were statistically controlled (Sha et al., 2005). While studies have
shown an association between negative mood and illness-related concepts (e.g.
Gendolla, Abele, Andrei, Spurk, & Richter, 2005), this association has not been
tested experimentally in the older population. Given the higher prevalence of chronic
illness in older adults, this study examined how two variables, sad mood and old age
schema, combined to influence older adults’ processing of physical symptoms.
Mood and Health Related Cognitions
Normal biological processes, acute and chronic organic diseases, as well as
reactions to internal emotional states or external environmental conditions all result
in physiological fluctuations (Pennebaker, 1982). These bodily changes not only
serve as the basis of the symptom experience, but also as important health related
information entering the information processing system. Given limited attentional
capacity, only part of the information from the body is attended to and processed. As
processing resources are allocated to these selected stimuli, these stimuli may have
greater influence on subsequent judgments and behaviors (Fiske & Taylor, 1991). It is
therefore important to understand what influences attention allocated to physical

2
symptoms in older adults, who may rely on such information to judge their health
status and make health care decisions.
Processing of physical symptoms is affected by individual and environmental
characteristics. One of the most frequently studied variables is negative mood state,
which has been found to heighten the experience of physical symptoms (Watson &
Pennebaker, 1989). Research on the relationship between mood and health related
cognitions covers a wide range of topics, including recognition, reporting, and
interpretation of physical symptoms (e.g. Abele & Hermer, 1993; Gendolla, Abele,
Andrei, Spurk, & Richter, 2005; Salovey & Birnbaum, 1989). In most studies,
researchers looked at how negative affectivity (NA) was associated with reports of
more physical symptoms (e.g. Leventhal, Hansell, Diefenbach, Leventhal, & Glass,
1996; Watson & Pennebaker, 1989). Conceptualized as a mood variable that
encompasses a wide range of aversive mood states from anger, disgust, guilt, anxiety,
to depression, NA reflects a predisposition to experience more emotional distress and
disturbances when treated as a personality trait. Thus, this construct is closely related
to the personality trait of neuroticism and trait anxiety (Barlow, 2000).
Some investigators concluded that only dispositional NA, but not situational
mood variations, predicted self-assessed health and physical symptom reporting
(Benyamini, Idler, Leventhal, & Leventhal, 2000; Watson, 2000). Others
demonstrated that situational mood state was more powerful in predicting symptom
reporting than trait affectivity (Leventhal et al., 1996). What further complicated the
matter was that most of these studies did not separate the effect of an anxious mood

3
from that of a depressed mood. Although co-morbidity of anxiety and depression is
common and there has been speculation about “de-differentiation” of the two in late
life, one longitudinal study has demonstrated the two conditions as distinct factors
(Wetherell, Gatz, & Pedersen, 2001). Studies that combined anxious and depressed
mood could not demonstrate how each of them might affect cognitive processing of
physical symptoms. For example, in a longitudinal study that revealed an association
between NA and poorer current self-assessment of health in older adults, NA was
captured by a combination of different mood states, including depression, anxiety,
and happiness (Benyamini et al., 2000).
To our knowledge, only one study by Leventhal and colleagues (1996)
attempted to tease apart the effects of trait and state anxiety and depression on
reports of physical symptoms. In their longitudinal study on middle-aged and older
adults, these researchers found that state depression, but not state anxiety,
significantly influenced future reports of physical symptoms. At the same time,
overall state NA was more powerful than trait NA in predicting reports of physical
symptoms. One limitation of the study was that it did not employ any established and
well-validated scales to assess anxiety or depression, but relied on responses to six
questions gauging how anxious (anxious, afraid, worried) and depressed (depressed,
sad, hopeless) the participant was.
Contrary to mixed findings in studies that employed correlational design and
with different operationalizations of negative mood, experimental studies involving
the induction of negative emotions tended to demonstrate an association between

4
state NA and reports of more physical symptoms, more negative conclusions about
one’s physical health, more pessimism that any action would improve the condition,
and greater feeling of vulnerability to future illnesses (Abele & Hermer, 1993;
Croyle & Uretsky, 1987; Salovey & Birnbaum, 1989). One aspect that distinguished
these mood induction studies from studies that employed a correlational design was
that the negative emotional state induced was specific to sad or depressed mood. In
these studies, participants listened to depressing music (Gendolla et al., 2005, Studies
2a and 4), recalled sad autobiographical memories (Abele & Hermer, 1993; Salovey
& Birnbaum, 1989), or watched sad film clips (Croyle & Uretsky, 1987). Indeed, sad
mood amplified negative symptom related cognitions. In addition, unlike
correlational studies that treated mood as something static, experimental studies
examined the impact of mood change.
An exception to the above association between negative mood and physical
symptom reports in mood induction experiments was a recent paper by Barger,
Burke and Limberg (2007). These researchers concluded from their two experiments
on 311 college students and three other studies that the effect size of induced sad
mood on health reports was negligible. While symptom reports were sensitive to trait
NA, they were not significantly influenced by induced negative mood (Barger et al.,
2007, Study 2). One shortcoming of Barger et al.’s (2007) experiments was that they
did not administer any mood measure prior to mood induction, thus raising the doubt
of whether differences in mood ratings between the two induction conditions could
be attributed solely to the mood induction procedure. Thus, the effect of induced sad

5
mood on symptom reports warranted additional examination and replication.
Attentional Bias towards Physical Symptoms
Researchers often explained this by emphasizing the influence of negative
mood on the basic cognitive process of attention. Mood-congruent selective attention
occurs because of limited cognitive capacity to process information (Bower & Forgas,
2000). Automatic spreading activation may result in greater salience of stimuli with
negative emotional valence when one is in a negative mood. The symptom perception
hypothesis also underpins the interplay between negative affect and self-focus on
attention to symptoms (Watson & Pennebaker, 1989). In one experiment, induced
negative mood and self-focus led to increased attention allocated to physical
symptoms in college students (Gendolla et al., 2005; Study 4).
Support of the influence of negative mood states on physical symptom
processing mostly came from college student samples (Croyle & Uretsky, 1987;
Gendolla et al., 2005; Salovey & Birnbaum, 1989). Processing of physical symptoms
may differ between older and younger adults, because older people have more
chronic medical conditions and have to evaluate and distinguish a wider array of
symptoms that signal the presence of disease against normal age-related
physiological changes (Leventhal & Crouch, 1997). In addition, maintaining
emotional well-being is a salient goal in late life according to the Socio-emotional
Selectivity Theory (SST, see Mather & Carstensen, 2003, for example). Older adults
tend to prefer positive materials and avoid negative ones. In a dot-probe paradigm that
involved presentation of happy and sad human faces, older adults averted their

6
attention from sad faces (Mather & Carstensen, 2003). Older adults also had
attentional preferences toward happy and away from angry faces in an eye-tracking
task (Isaacowitz, Wadlinger, Goren, & Wilson, 2006). One question is whether
transient sad mood would alter this pattern of negativity disengagement, elevating
older adults’ attentional focus on physical symptoms.
Memory Bias towards Physical Symptoms
Access of health related information from memory also contributes to
processing of physical symptoms. The mood-congruence effect asserts that negative
mood states facilitate recall of past events with negative valence. Indeed,
experimentally induced sad mood enhanced recall of sad materials in delayed word
recall and semantic accessibility of sad words in lexical ambiguity tasks, as well as
recall of sad autobiographical memories in older adults (Knight, Maines, & Robinson,
2002). Negative mood states may be associated with retrospective symptom
reporting, which requires access to aversive memories of prior illness episodes or
somatic experience. In one study on health cognition, participants with induced sad
mood rated their recent health as poorer than those with induced happy mood,
supporting the notion that symptom related memories were more readily accessed
when sad mood was induced (Croyle & Uretsky, 1987). In sum, retrospective recall
and reports of physical symptoms may be enhanced because experiences of physical
illness and symptoms are congruent with a negative mood state.
Personality Dispositions and Physical Symptoms
One notable confounding variable to the relationship between mood state and

7
symptoms is individual differences in personality. Neuroticism, often regarded as
almost synonymous to trait NA (Barlow, 2000; Watson & Pennebaker, 1989), has
been consistently found to elicit elaborated reports of physical symptoms and greater
amount of retrospectively recalled physical illnesses and symptoms (e.g. Ellington &
Wiebe, 1999; Lecci & Cohen, 2002). Research on personality suggests that
individuals scoring higher on neuroticism are more likely to experience negative
feelings such as anger, anxiety, depression, and guilt (Watson & Pennebaker, 1989).
Neuroticism may direct attention to bodily sensations and make it more likely for
ambiguous bodily sensations to be interpreted as indicative of alarming illnesses.
Costa and McCrae (1985) noted, however, that trait neuroticism is stable across the
lifespan and becomes less prominent in late life. Trait neuroticism cannot adequately
explain the increase in symptoms reported in old age, which is more likely a result of
changes in objective health rather than hypochondriasis.
Consistent with the opinion above, researchers concluded from two successive
annual interviews in a longitudinal study of community-dwelling older adults that
trait NA was not related to a biased over-report of physical symptoms in older adults
(Mora, Robitaille, Leventhal, Swigar, & Leventhal, 2002). Although trait NA and
self-rated health correlated with reports of prior-week symptoms in these
cross-sectional data, neither trait NA nor self-rated health predicted average number
of physical symptoms reported during illness episodes. Despite such findings, as
individuals high in neuroticism are more prone to negative emotions (Watson &
Pennebaker, 1989), individual variations in neuroticism has to be taken into account

8
when examining the impact of transient mood state on attention to and reports of
physical symptoms.
Dispositional optimism is another personality construct that shares similarity
with trait neuroticism. Studies demonstrated that people who were more optimistic
tend to report less physical symptoms. While this may partly be attributed to the
positive impact of optimism on physical health, it is also possible that people who
are optimistic may pay less attention to aversive stimuli, such as physical symptoms.
In a study on college students, Segerstrom (2001) found that optimism was
associated with greater bias for positive relative to negative stimuli in a modified
Stroop task, as well as slower skin conductance response rates for negative stimuli.
Although the link between optimism and fewer symptoms was reduced to
non-significance once neuroticism was statistically controlled (Scheier, Carver, &
Bridges, 1994), dispositional optimism may still confound the impact of sad mood
on reports of physical symptoms.
Aging Stereotypes and Illness Representation
Extending the study on the influence of negative mood state on symptom
reports in older adults using an experimental approach not only shed light on whether
the association could be generalized to non-college students, but also provided an
opportunity for examining factors unique to the older adult population that may
moderate the impact of sad mood on physical symptoms. Older adults are constantly
exposed to stereotypes of aging in the media (Donlon, Ashman, & Levy, 2005). In
the study by Donlon and colleagues (2005), older adults who watched more

9
television had a more negative outlook on old age than those with less TV viewing.
TV exposure remained the biggest predictive factor on aging stereotypes, after
controlling for age, health, education, and depression.
Stereotypes are schemas that represent organized prior knowledge structures,
which in turn facilitate information processing (Fiske & Taylor, 1991). Stereotypes
of aging, whether positive or negative, constitute the old age schema. Experimental
manipulation of aging stereotypes has been found to suppress memory performance
in older adults (e.g. Hess, Hinson, & Statham, 2004; Levy, 2003). On the contrary,
individuals in the positive aging stereotype manipulation group walked faster and
had better gait compared to the negative aging stereotype group (Hausdorff, Levy, &
Wei, 1999).
Although studies that activated aging stereotypes usually had a clear direction
towards positive or negative stereotypes, the stereotype literature suggested that
merely asking participants to specify their gender or race prior to a task was
sufficient to make discriminated groups, such as women and African Americans,
perform more poorly (Shih, Pittinsky, & Ambady, 1999; Steele & Aronson, 1995,
Experiment 4). When group identity was made salient, individuals became more
susceptible to negative stereotypes associated with that identity. Given the
prevalence of negative stereotypes and ageism towards older people (Donlon et al.,
2005), activating the demographic category of old age may be adequate to make
older adults vulnerable to negative aging stereotypes.
Older individuals have been found to attribute illness and physical symptoms to

10
old age (Leventhal & Crouch, 1997). Older adults who were given one of four
hypothetical illness scenarios were more likely to attribute both mild and severe
physical symptoms to old age than other potential causes (Leventhal & Prohaska,
1986). This resonated with core contents of the old age schema that have been
identified by researchers, such as frailty, illness, and deterioration in health (Crockett
& Hummert, 1987; Levy, 2003).
Mood and Old Age Schema
Although sad mood and aging stereotypes may independently heighten the
attention to physical symptoms at the level of affect and social cognition,
co-occurrence of the two may exacerbate one’s attention to bodily symptoms. When
triggered to think about old age, older adults may focus on negative self-relevant
cognitions about physical impairment. Although sad mood was expected to facilitate
the experience of physical symptoms, negative aspects of the old age schema could
make the influence of sad mood more powerful. Despite older adults’ preference to
stay away from negative information, when old age schema is activated, older adults
who are already sad may have less resources to fend off negative information, and
become more likely to attend to physical symptoms.
Hypotheses
The study adopted a 2 X 2 experimental design, manipulating mood (sad,
neutral) and old age schema (activated, not activated). We predicted that:
1) Older adults in the sad mood condition, compared to those in the neutral
mood condition, would have stronger attentional focus on physical symptom

11
words than neutral words and report more physical symptoms;
2) Older adults in the old age schema condition, compared to those in the
control condition, would have stronger attentional bias to physical symptom
words and report more physical symptoms; and
3) Old age schema and sad mood would have a multiplier effect on biasing
attention towards physical symptom words.

12
CHAPTER 2: METHOD
Participants
Seven-one older adults aged 60 or above (M = 73.79, SD = 7.68) were recruited
from senior centers in Los Angeles and the University of Southern California.
Sixty-one percent of the participants were female. Participants had an average of
16.65 years of education (SD = 2.72). Analysis of variance (ANOVA) and chi-square
values showed that the four groups did not differ significantly demographically.
Table 1 reports sample characteristics. Exclusion criteria included self-reported
diagnosis of depression, color blindness, and poor English reading ability.
Table 1 Demographic Information (n = 71)
Neutral Mood Sad Mood
Variable No old age
schema (n=16)
Old age
schema (n=18)
No old age
schema (n=19)
Old age
schema
(n=18)
Age 73.75 (7.90) 72.94 (7.63) 74.95 (7.76) 73.79 (7.68)
Education 14.88 (1.75) 15.75 (3.14) 15.63 (2.79) 16.25 (2.97)
Ethnicity
% White 63 61 58 50
% Asian 19 28 26 17
% Other 18 11 16 33
Gender
% Female

69

56

53

67
Income 2.27 (1.33) 2.06 (1.53) 2.60 (1.55) 2.25 (1.48)
Diagnosed
Health
problems
1.31 (1.20) 1.94 (1.76) 2.26 (1.97) 1.72 (1.32)
Medications 2.31 (2.02) 3.06 (2.48) 3.21 (3.92) 1.61 (1.61)
Vocabulary 18.19 (1.42) 18.17 (1.15) 17.63 (1.01) 17.89 (0.96)
Note. Means with standard deviations in parentheses. Age and education in years,
health problems and numbers of medications as counts. Household income data
available from 62 of 71 participants. Income coded as 1 = less than 25,000, 2 =
25,000-49,999, 3 = 50,000-74,000, 4 = 75,000-99,999, 5 = 100, 000

13
Measures
Demographic information. Personal information on age, gender, ethnicity,
education, and occupation were obtained from participants in the background
questionnaire.
Neuroticism. Twelve items from the NEO-Five Factor Inventory (NEO-FFI;
Costa & McCrae, 1989) were used to measure trait neuroticism. Participants were
asked to indicate the extent to which they agreed with statements such as ‘‘I rarely
feel fearful or anxious’’ and ‘‘I often get angry at the way people treat me’’ using a
five-point scale ranging from 0 (Strongly Disagree) to 4 (Strongly Agree). Responses
were summed so that higher total scores indicated greater neuroticism. The NEO-FFI
is a popular personality measure with good psychometric properties (Costa &
McCrae, 1989).
Dispositional optimism. The revised Life Orientation Test (LOT-R) was utilized
to measure dispositional optimism (Scheier et al., 1994). The revised version
contained 10 items. Four of these items were fillers and were not scored. There were
three negatively phrased items reflecting a pessimistic disposition and three
optimistic ones. Scores ranged from 6 to 30. Participants were instructed to answer
every question honestly and circle the appropriate letter indicating their level of
agreement on a five-point Likert scale with 1 (I Agree A Lot) to 5 = (I Disagree A
Lot).
Sad mood. The Center for Epidemiological Studies—Depression Scale (CES-D;
Radloff, 1977) was used to measure current mood state of participants. While the

14
original scale asked how participants felt during the past week, modified instructions
to assess current mood state were used (Fox, Knight, & Zelinski, 1998). All verbs in
past tense were changed to present tense, and the instruction was changed to how
participants felt “at the current time”. The present tense CES-D had internal
consistency alphas that ranged from .85 to .93 in older adult participants (Fox et al.,
1998; Knight, Maines, & Robinson, 2000).
In addition to the present tense CES-D, the Depressive Adjective Checklist
(DACL; Lubin, 1981) was used to measure depressed mood. The DACL was often
used in mood induction studies as a manipulation check (Fox et al., 1998; Knight et
al., 2002). Participants had to check off positive and negative adjectives that
described their current emotional state. The scoring counts both negative items
checked and positive items left unchecked, with a higher score indicating greater
negative emotion. Parallel forms of the DACL were used pre-, post-mood induction,
and before the end of the session. Reliability of the DACL ranged from .80 to .93 in
Lubin’s original study (1981). In a more recent study, Cronbach’s alphas ranged
from .87 to .92 in 119 younger adults and 78 older adults (Knight et al., 2002).
English proficiency. The 40-item Shipley (1986) Vocabulary Test was often
used prior to attentional bias tasks that required the processing of visually presented
words (e.g. Snider, Asmundson, & Weiss, 2000). Twenty items from the test acted as
a screening measure of cognitive ability and English proficiency in our study. One
point was credited to each correct response. Average prorated score of the present
sample was 35.9, similar to previous studies (e.g. Knight, Maines, & Robinson,

15
2002).
Symptom reports. Respondents were given two lists of 15 physical symptoms,
such as joint or limp pain and dizziness. Items were chosen from existing symptoms
checklists (e.g. Haug, Musil, Warner, & Morris, 1998; Pennebaker, 1982; Sha et al.,
2005). For the first list, participants were asked: “At this current moment, are you
experiencing these sensations?” For the second list, they were asked: “During the
past week, excluding today, were you experiencing these sensations?” Responses
were rated on a five-point scale from 0 (Not At All) to 4 (Very Much). A current
symptom experience score was calculated by summing the 18 current symptom items.
A retrospective symptom experience score was calculated by summing the 18
retrospective symptom items. Symptom intensity scores were calculated by dividing
symptom experience scores by the number of symptoms endorsed.
Aging expectations. The 12-item Expectations Regarding Aging Scale (ERA-12;
Sarkisian, Steers, Hays, & Mangione, 2005) assessed attitude towards aging. Items
were rated on a 4-point scale from 1 (Definitely True) to 4 (Definitely False). The
ERA-12 achieved internal consistency of .78 in two samples of over 1,000 older
adults aged 65 and above. ERA score was calculated using the formula from
Sarkisian et al.’s study (2005). The range of score was 0 to 100. In our study, all
responses were reverse-coded. Higher scores indicated a more negative view towards
old age. Average scores in this sample was 50.59 (SD = 18.52).
Mood Induction
The mood manipulation consisted of a combination of music and

16
autobiographical recall, which has been found to be effective across 70% of adult
participants (Gerrards-Hesse, Spies, & Hesse, 1994). Negative mood state was
induced by asking participants to vividly recall and write about an emotional event
that happened to them personally and made them feel very sad. Participants in the
control group were asked to vividly recall and write about an unemotional event that
did not happen to them personally and made them feel neither happy nor sad. Either
sad or neutral music was played when the mood induction procedure begins and
throughout the study to retain the induced mood. To maintain sad mood, Barber’s
“Adagio for Strings”, Albinoni’s “Adagio in G minor”, and Prokofiev’s “Russia
Under the Mongolian Yoke (The Field of the Dead)” were played; in the neutral
mood condition, we used Bach’s harpsichord music from the English Suites nos. 2, 3,
and 6 (cf. Fox et al., 1998).
Old Age Schema Activation
We activated old age schema by requesting participants to respond to a series of
age related questions presented as an opinion questionnaire. This approach paralleled
naturally occurring activation of aging stereotypes older adults experienced when
reading about old age related information in daily life. Half of the participants were
asked to respond to eight age-related questions, such as “At what age do you think
the average person becomes old?” Control participants were asked eight similarly
structured questions related to population density, such as, “How many people per
square mile do you think a crowded city has?” Participants were reassured there was
no right or wrong answer to each item.

17
Modified Stroop Task
The modified Stroop task has been used in research on health anxiety (Owens,
Asmundson, Hadjistavropoulos, & Owens, 2004; Williams, Wasserman, & Lotto,
2003), illness-cognitions and hypochondriac tendencies (Lecci & Cohen, 2002), and
chronic pain (Snider et al., 2000). Participants indicated the color of each stimulus
word rather than reading the word aloud. Longer delay implies that the consciously
prioritized task of color naming has been disrupted by selective attention to word
content (Williams, Mathews, & MacLeod, 1996). In our study, participants viewed
18 symptom words and 18 neutral words at the center of a 640 X 480 computer
screen, each preceded by the presentation of a white fixation cross for 1,000
milliseconds (see Appendix). Words were presented in red, yellow, green, and blue.
Order of presentation was randomized, except that the same word would not appear
more than once in succession. Participants had to press one of the four colored keys
to identify word color as quickly and accurately as possible. Twenty practice trials
with xxxxxxx were given to measure baseline processing speed. Feedback was given
in practice trials to ensure participants understood the instructions. Response
accuracy and reaction time (RT) from stimulus onset to pressing of any colored key
were recorded by the computer.
Physical symptom words were selected from existing physical symptom
checklists (e.g. Haug, Musil, Warner, & Morris, 1998; Sha et al., 2005). Neutral
words were matched in frequency and length with physical symptom words (Kucera
& Francis, 1967). To make sure differences in processing speed were not due to

18
schematic relatedness within symptom-related stimuli, neutral words were selected
from the same semantic category of work. Attentional bias to physical symptoms
was calculated by subtracting the average RT to color-name neutral words from
average RT to physical symptom words. Positive scores reflected attentional bias to
physical symptoms. A list of the word stimuli used is presented in Table 2.

Table 2 Word Lists for Modified Stroop Task
Physical symptoms Neutral words
vertigo florist
stiffness salesgirl
dizziness bodyguard
indigestion interviewer
cramp crews
numbness artisans
heaviness comedians
congested announcer
nausea keeper
breathless ballplayer
headache laborers
lump heir
cough chore
bruised peasant
sore tech
fatigue athlete
swollen pirates
pain king

Procedure
To screen out potential participants who might be depressed, the information
sheet handed out during the process of obtaining consent included self-reported

19
diagnosed depression as exclusion criteria. Potential participants who did not consent
to participate were screened out automatically. After giving informed consent,
participants filled out a background questionnaire consisting of demographic
information, personality and mood measures, and a vocabulary test. Participants
were randomly assigned to one of the four groups: control (n = 16), old age schema
only (n = 18), sad mood only (n = 19), and sad mood plus old age schema (n = 18).
Participants completed the combined mood induction procedure, followed by old age
schema manipulation. Sad mood was assessed again before the modified Stroop task.
In addition to symptom and neutral words, the modified Stroop task also included
words related to old age (e.g. aging, elderly, wrinkles) as a manipulation check for
old age schema activation.
Health related questions, including the physical symptom checklists, were given
at the end of the experiment to avoid activating illness-cognition that might dilute the
influence of mood and old age schema. Questions included number of common
medical conditions and medications. Whenever possible, the experimenter copied
information from participants’ prescription lists or pill bottles. Before concluding the
session, participants completed the ERA questionnaire and the CES-D again to
ensure they did not leave the experiment with emotional distress.
Analysis
Demographic information was reported using conventional methods based on
means and standard deviations. To examine the effectiveness of mood induction, 2 X
2 Mood Induction Condition X Old Age Schema Activation Condition repeated

20
measures analysis of variance (ANOVA) with Time as a within subject factor was
run on CES-D or DACL scores. Post-hoc analysis involved Bonferroni multiple
comparisons for each dependent variable. This technique has a conservative control
of Family-wise Error (FWE; probability of making at least one Type 1 error when
performing multiple tests), setting it smaller than or equal to the alpha level of .05.
Other analyses were conducted using the statistical software R for robust
statistics. While conventional ANOV A F-tests are based upon assumptions of equal
variances and normal distribution, reaction times data may not conform to these rules.
The analyses were done using functions described in Wilcox (2002) and Wilcox
(2005). Outliers were identified based on a formula on sample median (M) and
median absolute deviation (MAD), |X- M| / (MAD/.6745), with a critical value of
rejection greater than 2.24, using the function outmgv in R (Wilcox, 2005). This
method was robust to the masking effect on the mean in outlier detection.
Analysis of attentional bias to old age words and physical symptoms was based
on 20% trimmed means. Trimmed means are less susceptible to skewed distributions
than untrimmed means (Wilcox, 2002). To test whether the old age schema
manipulation was effective, a Mood Induction Condition X Old Age Schema
Activation Condition ANOV A was run on attentional bias to old age words, using the
t2way function. Similarly, to examine the attentional bias towards physical symptom
words, a Mood Induction Condition X Old Age Schema ANOVA was performed on
attentional bias to physical symptoms words. All p-values were generated by R,
based on different critical F-values for each analysis. Post-hoc analysis involved

21
linear contrasts on 20% trimmed means for attentional bias to physical symptoms,
using the function mcp2atm. The 95% confidence intervals were adjusted to control
FWE to be at .05 (Wilcox, 2005).
Symptom Reporting. In order to test the impact of sad mood and the old age
schema on symptom reporting, 20% trimmed-mean ANOVAs of Mood Induction
Condition X Old Age Schema were performed on currently experienced physical
symptoms and symptoms experienced during the past week.
Covariates. To examine whether potential confounding variables would
influence the main dependent variables differently in each experimental and control
group, regression slopes of each covariate with the dependent variable were
compared 2 groups at a time based on a percentile bootstrap method, using the
function reg2ci in R. If the slopes were significantly different across groups, the
covariate might have a moderating effect on the influence of sad mood and old age
schema on illness processing; and further statistical testing would be warranted.
Otherwise, the consistency of association between the covariate and the dependent
variable would suggest that including the covariate in the analysis would not
significantly modify the F-values in the original ANOVAs.

22
CHAPTER 3: RESULTS
Effectiveness of Mood Induction
The mood induction procedure was successful in inducing sad mood in older
adults. Significant main effects for time were found for both CES-D scores, F(2, 134)
= 10.64, p < .001, and DACL scores, F(2, 134) = 17.85, p<.001. The Time X Mood
Induction interaction effect was significant for both CES-D scores, F(2, 134) = 16.05,
p < .001, and DACL scores, F(2, 134) = 13.67, p<.001. Neither the Time X Old Age
Schema interactions for CES-D scores, F(2, 134) = 0.45, p = .64, and DACL scores,
F(2, 134) = 0.23, p = .79, nor the 3-way interaction terms for CES-D scores, F(2, 134)
= 0.02, p = .98, and DACL scores, F(2, 134) = 0.50, p = .61,were statistically
significant. Table 3 reports the untrimmed means and standard deviations on mood
measures.
Table 3 Mood Change due to Induction: Means of CES-D and DACL
Group Pre-induction Post-induction Post-experiment
CES-D scores
Neutral mood
No old age schema (n=16)

4.94 (0.71)
a

4.50 (0.61)
a

4.25 (0.55)
a

Old age schema (n=18) 6.78 (0.59)
a
5.78 (0.57)
b
6.06 (0.63)
b

Sad Mood
No old age schema (n=19)

5.68 (0.71)
a

8.32 (0.89)
b

5.22 (0.55)
a

Old age schema (n=18) 3.67 (0.70)
a
5.94 (0.87)
b
3.39 (0.62)
a

DACL scores
Neutral mood
No old age schema (n=16)

1.81 (0.34)
a

1.19 (0.31)
a

1.31 (0.33)
a

Old age schema (n=18) 1.94 (0.48)
a
1.06 (0.33)
a
0.89 (0.24)
b

Sad Mood
No old age schema (n=19)

2.58 (0.41)
a

3.42 (0.49)
a

1.68 (0.32)
b

Old age schema (n=18) 1.89 (0.38)
a
3.11 (0.40)
b
1.17 (0.27)
a

Note. Superscripts in table represent significant contrasts between entries on the
same row with differing superscripts letters. Standard errors are in brackets.

23
Effectiveness of the Activation of Old Age Schema
Attentional bias to old age word in the modified Stroop task was compared
between participants who underwent old age schema activation versus the control
condition. Results of a 2 X 2 ANOV A revealed significant main effect for the old age
schema manipulation, F(1, 67) = 34.80, p < .001, with no significant main effect for
mood condition, F(1, 67) = 2.16, p = .16, or the Mood Induction Condition X Old
Age Schema interaction, F(1, 67) = .35, p = .56. Whether one was in a sad mood or
not, activation of old age schema always yielded greater attention to old age words
than neutral words. Figure 1 shows the 20% trimmed means and standard errors of
attentional bias to old age words for each of the 4 groups.
Figure 1. Old age schema activation. Error bars represent standard errors.

-8
-6
-4
-2
0
2
4
6
8
Neutral Sad
Attentional Bias (ms)
No Old Age Schema
Old Age Schema

24
Attentional Bias to Physical Symptoms
Attentional bias to physical symptoms was computed as average reaction time
(RT) in milliseconds to color-name physical symptoms minus average RT to
color-name neutral words. Positive values indicated a preference for physical
symptom words relative to neutral words. Analysis of RTs was only meaningful for
participants who provided at least 90% of accurate responses (Lecci and Cohen,
2002). Only 63 errors were recorded among a total of 13, 064 trials in our study.
Inaccurate trials were dropped in subsequent analyses. No participant had an
individual error rate greater than 10%. Significant main effects for both mood
induction and old age schema manipulation were found, F(1, 67) = 41.24, p < .001
and F(1, 67) = 39.92, p < .001 respectively. The Mood Induction Condition X Old
Age Schema interaction was also statistically significant, F(1, 67) = 14.68, p < .01.
Figure 2 shows the attentional bias towards physical symptoms.
Figure 2. Attentional bias to physical symptoms. Error bars represent standard errors.

-15
-10
-5
0
5
10
15
20
Neutral Sad
Attentional Bias (ms)
No Old Age Schema
Old Age Schema

25
Post-hoc analysis. Pairwise multiple comparisons showed that participants
experiencing a sad mood paid more attention to physical symptoms than individuals
in a neutral mood, whether their old age schema was activated, t (36) = 5.42, p
< .001, or not, t(35) = 3.57, p < .05. Within the sad mood condition, activation of old
age schema was effective in causing greater interference in performing the
color-naming task, t (37) = 8.29, p < .001. The same effect of old age schema was
not observed in the neutral mood condition, t (34) = 2.60, p = .17. Results of multiple
comparisons of attentional bias to physical symptoms are presented in Table 4.
Table 4 Multiple Comparisons of Attentional Bias to Physical Symptoms
Test statistics Critical value 95% CI of difference
Neutral mood/No old age
schema vs. Neutral mood/
Old age schema
2.60 2.90 -18.90 to 1.02
Neutral mood/ No old age
schema vs. Sad mood/ No
old age schema
3.57* 2.95 -16.69 to -1.59
Neutral mood/ No old age
schema vs. Sad mood/
Old age schema
10.37** 2.99 -32.48 to –17.93
Neutral mood/Old age
schema vs. Sad mood/ No
old age schema
0.07 2.95 -9.36 to 8.96
Neutral mood/Old age
schema vs. Sad mood/
Old age schema
5.42** 2.98 -25.22 to –7.31
Sad mood/ No old age
schema vs. Sad mood/
Old age schema
8.29** 2.86 -21.61 to –10.51
*p < .05
**p < .001

Baseline reaction time as covariate. Effects of mood induction on attentional
bias may be mediated by effects of sad mood on slowing one’s processing speed.

26
Regression slopes of baseline RT and bias to physical symptoms were compared
across groups. As illustrated in Table 5, association between baseline RT and
attentional bias to symptom words was not statistically different across the 4 groups.
Baseline RT did not significantly affect main and interaction effects for sad mood
and old age schema and was not included in the analysis as a covariate.
Table 5 Comparison of regression slopes of baseline reaction time and attentional
bias to physical symptoms
95% CI of difference p-value
Neutral mood/No old age schema vs.
Neutral mood/ Old age schema
-.04 to .05 .84
Neutral mood/ No old age schema vs.
Sad mood/ No old age schema
-.03 to .06 .54
Neutral mood/ No old age schema vs.
Sad mood/ Old age schema
-.04 to .05 .67
Neutral mood/Old age schema vs.
Sad mood/ No old age schema
-.02 to .05 .39
Neutral mood/Old age schema vs.
Sad mood/ Old age schema
-.03 to .04 .58
Sad mood/ No old age schema vs.
Sad mood/ Old age schema
-.04 to .03 .84

Treating participants in the neutral mood condition who received no old age
schema activation as the referent group, older adults had an attentional bias away
from physical symptoms relative to neutral words (trimmed mean = -10.29, SE =
2.08). When old age schema was activated, this negative bias became closer to zero
(trimmed mean = -2.00, SE = 2.99). Similarly, for participants in the sad mood
condition whose old age schema was not activated, significant main effect of sad
mood on attentional bias towards physical symptoms manifested itself by reducing
the negative bias to almost zero (trimmed mean = -2.07, SE = 1.72). Only when both
sad mood and old age schema were induced did participants show a bias towards

27
physical symptoms relative to neutral words (trimmed mean = 13.86, SE = 1.04).
Other covariates. Prior research revealed that neuroticism was associated with
attentional bias to physical symptoms. The effect of old age schema on attentional
bias to physical symptoms could also have been influenced by a generally negative
outlook on aging. Although the 4 groups did not differ significantly in number of
diagnosed medical illness or medications (see Table 1), health status could have an
impact on attention to physical symptoms. Regression slopes of any of the above
variables with attentional bias to physical symptoms did not significantly differ
across the 4 groups. Main and interaction effects for sad mood and old age schema
on attentional bias towards physical symptoms remained significant, whether
baseline reaction time, personality, expectations on aging, and health status were
statistically controlled or not.
Symptom Reporting
Main and interaction effects. A frequency count indicated that less than 20% of
the participants endorsed 4 of the 15 symptoms (hot or cold spells, chest pain, racing
heart, and lump in throat). Thus, a composite score of symptoms was formed without
these 4 items
1
. For physical symptoms experienced during the experiment, there was
neither significant main effects for sad mood and old age schema, F(1, 67) = 0.93, p
= .34, and F(1, 67) = 0.02, p = .90 respectively, nor significant Mood Induction
Condition X Old Age Schema interaction, F(1, 67) = 1.17, p = .29. Likewise,
non-significant results were found for physical symptoms experienced during the

1
Results were not significantly different when analyses were repeated using all 15 items.

28
past week. There were neither significant main effects for sad mood and the old age
schema, F(1, 67) = 0.18, p = .68, and F(1, 67) < 0.01, p = .96 respectively, nor
significant Mood Induction Condition X Old Age Schema interaction, F(1, 67) =
0.59, p = .46.
Number and intensity of symptoms reported. Similar to findings above, there
was no significant main or interaction effect of mood and old age schema on the
number and intensity of physical symptoms reported during the experiment and in
the past week. For number of physical symptoms endorsed during the experiment,
sad mood: F(1, 67) = 0.08, p = .78, old age schema: F(1, 67) = 2.07, p = .16, and
interaction: F(1, 67)= 2.16, p = .15. For number of symptoms experienced during the
past week, sad mood: F(1, 67) = 0.27, p = .61, old age schema: F(1, 67) < 0.01, p =
1.00, and interaction: F(1, 67) = 0.58, p = .46. For the intensity of physical symptoms
reported during the experiment, sad mood: F(1, 67)= 1.05, p = .31, old age schema:
F(1, 67) = 0.35, p = .56, and interaction: F(1, 67)= 1.65, p = .22. For the intensity of
symptoms experienced during the past week, F(1, 67)= 0.29, p = .59, F(1, 67) = 0.02,
p = .88, and F(1, 67)= 0.27, p = .61.
Illness corresponding to symptoms reported. In addition, we examined whether
certain subgroups would show different patterns of symptom reporting, because
individuals with specific illness might have different sensitivity towards symptoms
relevant to their illness (Williams, 2003). We looked at whether a subset of 26
participants suffering from osteoarthritis reported significantly more joint and limp
pain when both sad mood and old age schema were activated. However, the main

29
effects, sad mood: F(1, 22) = 0.12, p = .74, and old age schema: F(1, 22) = 2.35, p
= .18, as well as the interaction effect, F(1, 22) = 3.89, p = .19, were not statistically
significant for pain experienced during the experiment. Similarly, the main effects,
sad mood: F(1, 22) = 0.04, p = .86, and old age schema: F(1, 22) = 1.20, p = .31, as
well as the interaction effect, F(1, 22) = 3.31, p = .24, were not statistically
significant for pain experienced during the past week.
Particular symptoms clusters. Grouping physical symptoms based on their
conceptual closeness to specific illness conditions (e.g. cardiovascular,
gastrointestinal, respiratory, musculoskeletal) and examination of individual
symptom items also failed to yield significant main or interaction effects of sad
mood and old age schema. When we examined the composite score of pain based on
two most frequently endorsed items (joint and limp pain; back pain) for all
participants, there was no significant main or interaction effect for currently
experienced pain, sad mood: F(1, 67) = 0.57, p = .45, old age schema: F(1, 67) =
0.83, p = .37, and interaction: F(1, 67) = 3.96, p = .08; or for pain experienced during
the past week, sad mood: F(1, 67) = 0.31, p = .58, old age schema: F(1, 67) = 0.61, p
= .44, and interaction: F(1, 67) = 0.05, p = .83.
Other predictors of symptom reporting. Given the null findings of sad mood and
old age schema on symptom reporting, we examined whether a few conceptually
relevant variables had an influence on symptoms reporting as prior research
suggested. We examined whether objective health status, personality traits, and
expectations about aging were associated with symptom reports.

30
Regression analysis was conducted using the regci and tsreg functions in R.
Theil-Sen estimates of slope and intercept were computed. These estimators had
smaller standard errors than ordinary least squares estimators when the error term
was heteroscedastic and were more robust to the influence of outliers. Percentile
bootstrap confidence intervals were also computed. From Tables 6 and 7, only
neuroticism had a significant association with symptoms experienced during the past
week, B = 3.28, SE = 1.34, p < .01, while number of medications significantly
correlated with symptoms experienced during the experiment, B = 0.57, SE = 0.31, p
< .05. When the curvature of association with symptom reporting was examined
using the prplot function in R that created partial residual plots of each predictor,
controlling for other predictors in the model, the fitting of smoothers did not seem to
suggest that non-significant findings were due to curvilinear relationship.
Table 6 Summary of Regression Analysis for Variables Predicting Physical
Symptoms Endorsed for the Past Week
Variable B SE B 95% CI
(Constant) -2.05 5.60 -12.23 to 9.05
Neuroticism 3.28** 1.34 0.82 to 5.94
Optimism 0.04 1.10 -2.07 to 2.12
Negative expectations on aging 0.04 0.28 -0.08 to 1.00
Number of medications 0.46 0.03 -0.02 to 0.10
**p < .01
Table 7 Summary of Regression Analysis for Variables Predicting Physical
Symptoms Endorsed during the Experiment
Variable B SE B 95% CI
(Constant) 1.02 4.81 -8.89 to 10.81
Neuroticism 1.55 1.04 -0.42 to 3.53
Optimism -0.69 1.03 -2.77 to 1.43
Negative expectations on aging 0.04 0.03 -0.02 to 0.10
Number of medications 0.57* 0.31 0.12 to 1.26
*p < .05

31
CHAPTER 4: DISCUSSION
Attentional Bias to Physical Symptoms
As predicted, individuals in the sad mood group had a higher average
attentional bias to physical symptoms than the neutral mood group. Because our
cognitive capacity to process information is limited, we have to selectively attend to
important information (Bower & Forgas, 2000). The significant main effect of sad
mood in our study on attentional bias to physical symptoms was consistent with the
notion of mood-congruent selective attention. Physical symptoms are typically
considered as unpleasant information with negative emotional valence. When older
adults were induced to experience sad mood, illness-related cognition might be
activated. However, as discussed below, a closer examination of our findings
suggested that sad mood alone was not sufficient to induce a net bias toward physical
symptoms, because within the sad mood group, the likelihood of attending more to
physical symptom words rather than neutral words was not significantly greater than
zero for older participants whose old age schema was not activated.
The same could be said for individuals in the old age schema group, as opposed
to the non-old age schema group. In our study, older adults in the former group had a
higher average attentional bias to physical symptoms than the latter group. Although
information within the old age schema could be both positive and negative, negative
concepts such as illness and physical decline were very commonly associated with
old age (Crockett & Hummert, 1987; Leventhal & Crouch, 1997). The significant
main effect highlighted that when triggered to think about old age, access to

32
health-related information, such as physical symptoms, might be heightened.
Nevertheless, the fact that old age schema itself did not lead to a net bias towards
physical symptoms in the neutral mood group suggested that it took more than old
age schema to make symptoms information more salient than neutral words.
The Socioemotional Selectivity Theory (Mather & Carstensen, 2003) predicts
that emotional goals of feeling good and avoiding negative feelings are prioritized in
older adults, because advancing age is an obvious sign that time is limited. In line
with the idea of negativity disengagement, our older participants in the neutral mood
group whose old age schema was not activated paid less attention to physical
symptoms than neutral words. However, when there was a mood change from
baseline to sad mood or when old age schema was activated, there was only a
narrowing difference between amount of attention allocated to neutral and
symptom-related words in the modified Stroop task. Put another way, either sad
mood or old age schema eliminated the tendency for older adults to focus away from
physical symptoms, a tendency consistent with SST and the positivity effect.
Nevertheless, a net bias towards physical symptoms was not induced when only one
of the two variables was present.
For a net bias towards physical symptoms to occur, both sad mood and old age
schema had to be present. One mechanism involved in the association between
negative affect and focus on physical symptoms was self-focused attention (Mor &
Winquist, 2002). A person’s attention might be geared towards the self when one was
in a negative mood, as it was adaptive to examine whether something was wrong

33
within the individual, so that one could look for a remedy. Although our study did
not deliberately elicit self-focused attention, the interaction effect for sad mood and
old age schema on attentional bias to physical symptoms could at least in part be
explained by self-relevance of old age schema to older adults. While we did not
specifically ask participants to think about their own aging process, the general
schema about old age could have prompted participants to examine their own
identity as an older person. Thus, activation of old age schema might be regarded as
a trigger for self-focused attention, which appeared to be a necessary condition for
individuals induced into a sad mood to attend more to physical symptoms than
neutral stimuli (Gendolla et al., 2005). Future studies that examine the impact of old
age schema on older adults’ attentional focus may consider measuring or
manipulating self-focused attention to better understand the underlying mechanisms.
The cognitive-behavioral approach to depression has highlighted four
interconnected elements that affected human functioning, namely physiology,
behaviors, thoughts, and emotions (Laidlaw, Thompson, Dick-Siskin, &
Gallagher-Thompson, 2003). When older adults were induced to experience sad
mood, the experience of physical symptoms might be enhanced. In addition,
mood-congruent negative thoughts might be triggered by sad mood. Of note, these
negative thoughts might not necessarily be related to the aging process, which was
often associated with negative aspects of health, such as frailty and illness (Crockett,
& Hummert, 1987). However, once older adults had been prompted to think about
old age, self-relevant cognitions about negative aspects of aging and physical illness

34
might be activated as well, particularly if they were already in a sad mood and were
adopting a negative style of thinking. This implied that perhaps it was not sad mood
and self-focused attention per se, but self-relevant cognition about old age that made
sad mood more powerful in inducing greater attentional bias to physical symptoms.
Thus, only in the combined condition when both sad mood and old age schema were
activated did older participants pay more attention to physical symptoms.
Symptom Reporting
Contrary to our hypothesis, neither experimentally induced sad mood nor
activation of old age schema influenced reports of physical symptoms in our sample.
Studies that examined the impact of mood state on health cognition and symptom
reporting either employed the attentional bias measure or the symptom report measure
as their dependent variable, but not sequentially in the same study (e.g. Gendolla et al.,
2005). The effect of sad mood and old age schema may have dissipated after repeated
exposure to physical symptoms in the modified Stroop task.
Additional analyses showed that current physical symptoms reported had a
significant association with number of medications taken, whereas reports of physical
symptoms in the past week had a significant association with trait neuroticism.
Self-reports of physical symptoms are closely tied to objective measures of illness and
health (e.g. Sha et al., 2005). Number of medications is a relatively objective measure
of physical health. This may explain why it was associated with current symptoms
reported in our study. Neuroticism is conceptualized as a general tendency to

35
experience negative affect (Watson & Pennebaker, 1989). As a personality trait, it may
persist for a longer duration than situational mood state. It is therefore logical for it to
be associated with recall of recently experienced physical symptoms. This also
corroborates with findings that dispositional negative affect is a good predictor of
self-rated health and symptom reporting (Benyamini et al., 2000).
Clinical Implications
As thoughts and feelings have bi-directional influence on each other, both the
presence of sad mood and negative age-related beliefs need to be assessed and
addressed when dealing with older adult clients who show an unrealistic or excessive
focus on their physical symptoms and experience subjective distress. Modification of
negative self-concept has been a common feature in cognitively-oriented
psychotherapy for depression (Laidlaw et al., 2003). Psychoeducation that challenges
myths about old age, as well as ways to cope with negative stereotypes about aging,
may be incorporated into intervention for older adults who focus too much of their
attention on physical symptoms. Development of alternative ways to look at oneself
and old age that are positive and realistic may shift one’s excessive attentional focus
away from physical symptoms. This in turn may improve one’s sense of well-being.
Improvement in mood may then help reduce the amount of negative perceptions about
oneself and old age.

36
Consistent with previous findings, significant association between objective
measure of physical health and currently experienced physical symptoms implies that
older adults are fairly accurate in perceiving their health status (Sha et al., 2005). On
the other hand, the association between trait neuroticism and reporting of recently
experienced physical symptoms may be more indicative of a bias in recall. Physicians
may stop listening to a long list of chronic complaints, because they may feel that
those are harder to treat (Zarit & Zarit, 2006). In a clinical setting, it may be beneficial
for health care providers to ask specifically about “How are you feeling at this current
moment?”, as opposed to the general question of “How are you feeling?” that may
trigger responses that are colored by dispositional reporting style or memory bias.
Future Directions
The cognitive model of depression highlights the presence of negative
self-concept and beliefs about others and the world (Beck, 1976). Although our study
only elicited a transient state of sad mood, one might argue that sad mood might have
triggered negative self-cognition as well. Likewise, negative images from the old age
schema might induce sad feelings. However, because mood and old age schema were
manipulated separately in our study, our findings suggested that two separate
mechanisms operating at the affective and cognitive level were influencing one’s
attentional focus to physical symptoms. Although an elevation in sad mood could have
activated negative self-concepts, it might have been offset by the distraction of the
non-old age schema activation task, which was not self-specific. Studies on mood and

37
attention have illustrated the role of distraction in combating self-focus (Watson &
Pennebaker, 1989). Future studies may examine the relative impact and association
between distraction and old age schema by introducing other control group that
involves a distraction task that does not aim at activating any particular schema.
One question of interest was whether the negativity disengagement seen in older
adults in our sample was unique to old people only. For example, one study found that
younger adults also paid less attention to their physical symptoms when they were not
in a sad mood (Gendolla et al., 2005). However, that study compared positive and
negative mood without a neutral mood condition. Happy college students might have
tuned out physical symptoms for reasons other than negativity disengagement
experienced by older participants. Further studies may examine the joint impact of sad
mood and old age schema in younger adults by involving a neutral mood group, so as
to see if the negativity disengagement buffer was specific to older adults.
While attentional bias to physical symptoms was affected by induced sad mood
and old age schema, current symptom reporting was associated with number of
medications, and retrospective symptom reporting was tied to trait neuroticism.
Allocation of attention is an important first step in information processing. What
remains to be answered is how attention translates into recall and reporting of physical
symptoms. The assumption that greater attention to physical symptoms will result in
greater number of symptoms endorsed needs to be reconsidered. Perhaps when
attention to physical symptoms was facilitated because of priming of symptom words

38
in the modified Stroop task, older adults in our study became more accurate in their
health perception, thus making their report of currently felt symptoms more consistent
with objective health status, instead of inducing an exaggeration of symptoms reported.
In the future, researchers may try to vary the level of attention paid to physical
symptoms using different types of experimental manipulations prior to symptom
reporting and examine their impact on quantity and quality of symptoms reported.
Studies that examined the influence of negative affect on reports of physical
symptoms often treated anxious and sad mood as one single construct, although they
are two distinct concepts even in old age (Wetherell et al., 2001). While this study
attempted to single out sad mood as one of the major variables in symptoms
processing, we did not examine the role of anxiety. Anxiety was found to trigger
greater accessibility of illness cognitions and threatening information (Fox & Knight,
2005; Owens et al., 2004; P.G. Williams et al., 2003). Given the high co-morbidity of
anxiety and depression in old age, future studies that induce sad mood should also
measure the level of anxious mood to determine if anxiety has additional influence on
attention to physical symptoms in older adults.
Limitations
A potential confound in our study was old age related words embedded in the
modified Stroop task as manipulation check for old age schema activation. Presence of
these age related words could have bolstered attentional bias to physical symptoms.

39
However, older adults whose old age schema was not activated prior to the Stroop task
did not demonstrate an attentional bias to physical symptoms that significantly
differed from zero. Addition of these old age words did not seem to have reduced the
effects for sad mood and old age schema on attentional bias to physical symptoms.
Future studies may benefit from a different manipulation check.
In addition, although our sample was ethnically diverse, most participants were
highly educated and their depressed mood scores were quite low. Results may not be
generalizable to less educated samples or older adults whose level of depression was
in the clinical range. One question was whether individuals experiencing different
levels of sad mood would respond differently to experimental manipulation. Given our
sample size and the limited range of depression scores that fell below the clinical range,
we did not find any statistically significant difference in strength of association
between predictor variables and symptom processing at different quartiles of CES-D
scores when we divided our sample into subgroups based on their Time 1 CES-D score,
or elevation in CES-D score from prior to and after mood induction.
Future studies may recruit a bigger sample. A priori power analysis indicated that
for a medium to large effect size to be properly detected in an ANOVA with 4 groups,
at least 72 participants were needed to achieve a power of .80 if we expected a large
effect size (Cohen, 1992). With the large effect obtained for sad mood and old age
schema on attention to physical symptoms, our sample of 71 participants appeared
adequate in detecting differences in attentional bias. It was less clear if we had enough

40
participants to detect differences in symptom reporting, because studies of a similar
nature often found a medium effect size at most (e.g. Barger et al., 2007).
Conclusion
Despite these limitations, this was the first study we were aware of that
investigated the impact of sad mood on physical symptom processing in older adults
by experimentally manipulating mood and old age schema. Apart from the theoretical
value of identifying how stereotypes about aging moderates the association between
sad mood and attention to symptoms, our results have important implications for
designing interventions with older adults. Physical symptoms are important to
self-evaluation of health and decisions related to medical care-seeking and lifestyle
changes. Future research may look at other variables that trigger various thoughts
about old age, and whether intervention that promotes or maintain favorable attitudes
towards old age would alter health perception and decision making in sad older adults.

41
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47
Appendix

Background Questionnaire

Please fill out this questionnaire. Please be advised that all information is completely confidential and
will not be used to personally identify you. Be sure NOT to write your name or Social Security
number anywhere on this questionnaire.

1. Date of Birth: _________________

2. Gender: Male / Female (Please Circle)

3. Race/Ethnicity:
African-American/black ____ Asian-American/Pacific Islander ____
Caucasian/white ____ Latino/Latina ____
Middle Eastern ____ Native American ____
Other (Please Specify) _________________

4. Marital Status: _______________

5. Years of Education: ____________ (e.g. High school = 12, College=16)

6. Current Employment Status: _____________

7. Occupation (Previous job, if retired): _____________

8. Household Income: 1. < $25,000 2. $25,000-49,999 3. $50,000-74,999
4. 75,000-99,999 5. > $100, 000

9. Are you color-blind? Yes / No (Please Circle)

10. Your English reading comprehension is:
Excellent / Good / Below Average / Poor (Please Circle One)

48
NEO-PI-FFI (Neuroticism)

For each statement circle the response that best represents your opinion.

Strongly
Disagree
Disagree Neutral Agree Strongly
Agree
1. I am not a worrier. 0 1 2 3 4
2. I often feel inferior to others. 0 1 2 3 4
3. When I’m under a great deal
of stress, sometimes I feel I’m
going to pieces.
0 1 2 3 4
4. I rarely feel lonely or blue. 0 1 2 3 4
5. I often feel tense and jittery. 0 1 2 3 4
6. Sometimes I feel completely
worthless.
0 1 2 3 4
7. I rarely feel fearful or anxious. 0 1 2 3 4
8. I often get angry at the way
people treat me.
0 1 2 3 4
9. Too often, when things go
wrong, I get discouraged and
feel like giving up.
0 1 2 3 4
10. I am seldom sad or
depressed.
0 1 2 3 4
11. I often feel helpless and want
someone else to solve my
problems.
0 1 2 3 4
12. At times I have been so
ashamed I just
wanted to hide.
0 1 2 3 4

49
LOT-R

Please be honest and accurate as you can throughout. Try not to let your response to one statement
influence your response to other statements. There is no correct or incorrect answer. Answer
according to your own feelings, rather than how you think “most people” would answer. Please circle
your response.

1. In uncertain times, I usually expect the best.
1 2 3 4 5
I agree a lot I agree a little I neither agree or
disagree
I disagree a
little
I disagree a lot

2. It’s easy for me to relax.
1 2 3 4 5

3. If something can go wrong for me, it will.
1 2 3 4 5

4. I’m always optimistic about my future.
1 2 3 4 5

5. I enjoy my friends a lot.
1 2 3 4 5

6. It’s important for me to keep busy.
1 2 3 4 5

7. I hardly ever expect things to go my way.
1 2 3 4 5

8. I don’t get upset too easily.
1 2 3 4 5

9. I rarely count on good things happening to me.
1 2 3 4 5

10. Overall, I expect more good things to happen to me than bad.
1 2 3 4 5

50
CES-D

Below is a list of the ways you may have felt or behaved. For each statement, circle the number that
best describes how you are feeling AT THE CURRENT TIME.

At the current time, right now: Not at all A little Somewhat Very much
a. I am bothered by things that don’t usually
bother me.
1 2 3 4

b. I do not feel like eating; my appetite is poor. 1 2 3 4

c. I feel that I cannot shake the blues even with
help from my family and friends.
1 2 3 4

d. I feel that I am just as good as other people. 1 2 3 4

e. I have trouble keeping my mind on what I am
doing.
1 2 3 4

f. I feel depressed. 1 2 3 4

g. I feel that everything I do is an effort. 1 2 3 4

h. I feel hopeful about the future. 1 2 3 4

i. I think my life has been a failure. 1 2 3 4

j. I feel fearful. 1 2 3 4

k. My sleep is restless. 1 2 3 4

l. I am happy. 1 2 3 4

m. I talk less than usual. 1 2 3 4

n. I feel lonely. 1 2 3 4

o. People are unfriendly. 1 2 3 4

p. I enjoy life. 1 2 3 4

q. I have crying spells. 1 2 3 4

r. I feel sad. 1 2 3 4

s. I feel that people dislike me. 1 2 3 4

t. I cannot get “going”. 1 2 3 4

51
DACL

Below you will find words that describe different kinds of moods and feelings. Check the words that
describe how you feel now. Some of the words may sound alike, but we want you to check all the
words that describe your feelings. Work rapidly and check all of the words that describe how you
feel.

1. _________ Strong
2. _________ Tortured
3. _________ Listless
4. _________ Sunny
5. _________ Destroyed
6. _________ Wretched
7. _________ Broken
8. _________ Lighthearted
9. _________ Criticized
10. _________ Grieved
11. _________ Dreamy
12. _________ Hopeless
13. _________ Oppressed
14. _________ Joyous
15. _________ Weary
16. _________ Droopy

52
Below you will find words that describe different kinds of moods and feelings. Check the words that
describe how you feel now. Some of the words may sound alike, but we want you to check all the
words that describe your feelings. Work rapidly and check all of the words that describe how you
feel.

1. _________ Clean
2. _________ Dispirited
3. _________ Moody
4. _________ Pleased
5. _________ Dead
6. _________ Sorrowful
7. _________ Bleak
8. _________ Light
9. _________ Morbid
10. _________ Heavyhearted
11. _________ Easygoing
12. _________ Gray
13. _________ Melancholy
14. _________ Hopeful
15. _________ Mashed
16. _________ Unlucky

Below you will find words that describe different kinds of moods and feelings. Check the words that
describe how you feel now. Some of the words may sound alike, but we want you to check all the
words that describe your feelings. Work rapidly and check all of the words that describe how you
feel.

1. _________ Downhearted
2. _________ Lively
3. _________ Unfeeling
4. _________ Alone
5. _________ Unhappy
6. _________ Alive
7. _________ Terrible
8. _________ Poor
9. _________ Forlorn
10. _________ Alert
11. _________ Exhausted
12. _________ Heartsick
13. _________ Bright
14. _________ Glum
15. _________ Desolate
16. _________ Composed

53
Shipley

In the test below, the first word in each line is printed in capital letters. Opposite it are four other
words. Circle the word which means the same thing as the first word. A sample has been worked out
for you. If you don’t know, GUESS.

LARGE Red Big silent wet
***************** ************ *********** ********** *******
PERMIT allow sew cut drive
COUCH pin eraser sofa glass
TUMBLE drink dress fall think
CORDIAL swift muddy leafy hearty
IMPOSTOR conductor officer book pretender
FASCINATE welcome fix stir enchant
IGNORANT red sharp uninformed precise
RENOWN length head fame loyalty
MASSIVE bright large speedy low
SMIRCHED stolen pointed remade soiled
CAPTION drum ballast heading ape
JOCOSE humorous paltry fervid plain
RUE eat lament dominate cure
DIVEST dispossess intrude rally pledge
INEXORABLE untidy involatile rigid sparse
LISSOM moldy loose supple convex
PLAGIARIZE appropriate intend revoke maintain
QUERULOUS maniacal curious devout complaining
ABET waken ensue incite placate
PRISTINE vain sound first level

54
Health Questionnaire

Below are some bodily sensations that people experience. Please circle the appropriate number to
indicate whether you feel these sensations.

At this CURRENT moment, are you experiencing these sensations?

Not at all Slightly Moderately Quite a lot Very Much
1. Joint or limb pain 0 1 2 3 4
2. Dizziness 0 1 2 3 4
3. Fatigue 0 1 2 3 4
4. Headaches 0 1 2 3 4
5. Heaviness in
arms/legs
0 1 2 3 4
6. Nausea, gas or
indigestion
0 1 2 3 4
7. Back pain 0 1 2 3 4
8. Hot or cold spells 0 1 2 3 4
9. Shortness of breath 0 1 2 3 4
10. Chest pain 0 1 2 3 4
11. Numbness or
tingling
0 1 2 3 4
12. Racing heart 0 1 2 3 4
13. Abdominal or
stomach pain
0 1 2 3 4
14. Lump in throat 0 1 2 3 4
15. Weakness 0 1 2 3 4

DURING THE PAST WEEK, excluding today, were you experiencing these sensations?

Not at all Slightly Moderately Quite a lot Very Much
1. Joint or limb pain 0 1 2 3 4
2. Dizziness 0 1 2 3 4
3. Fatigue 0 1 2 3 4
4. Headaches 0 1 2 3 4
5. Heaviness in
arms/legs
0 1 2 3 4
6. Nausea, gas or
indigestion
0 1 2 3 4
7. Back pain 0 1 2 3 4
8. Hot or cold spells 0 1 2 3 4
9. Shortness of breath 0 1 2 3 4
10. Chest pain 0 1 2 3 4
11. Numbness or
tingling
0 1 2 3 4
12. Racing heart 0 1 2 3 4
13. Abdominal or
stomach pain
0 1 2 3 4
14. Lump in throat 0 1 2 3 4
15. Weakness 0 1 2 3 4

55
1. Are you CURRENTL Y having a cold/flu? YES / NO

2. Do you CURRENTL Y take any prescribed medication? YES / NO
Please list the medications on your prescription list:
______________________________________________________

3. Are you currently receiving psychological treatment? YES / NO
If yes, please specify what condition(s) you are receiving treatment for:
____________________

4. Have you received any psychological treatment in the past? YES / NO
If yes, when? _______________ For what condition? _____________

5. How would you rate your overall health on a scale of 1-10 (1 = severely ill; 10 = very
healthy)?
1 ----- 2 ----- 3 ----- 4 ----- 5 ----- 6 ----- 7 ----- 8 ----- 9 ----- 10
Severely Quite Average Minor V ery
ill poor complaints healthy

6. Do you need corrective lens? YES / NO
7. Do you need hearing aids? YES / NO
8. Have you ever had a stroke or TIA (mini-stroke)? YES / NO
9. Have you ever had a heart attack? YES / NO
10. Are you currently diagnosed with:
a. Hypertension YES / NO
b. Heart disease YES / NO
c. Diabetes YES / NO
d. Respiratory problems (e.g. asthma, bronchitis/emphysema) YES / NO
e. Liver disease YES / NO
f. Kidney disease YES / NO
g. Arthritis YES / NO
h. Cancer YES / NO
i. Glaucoma/Cataracts YES / NO

11. How many times did you go to your doctor last year (past 12 months) for consultation? _______

12. How many days were you hospitalized last year (past 12 months)? _______

56
ERA-12

This survey has questions about what you expect about aging. Please check the ONE box to the right
of the statement that best corresponds with how you feel about the statement. If you are not sure, go
ahead and check the box that you think BEST corresponds with your feelings.

Definitely
True
Somewhat
True
Somewhat
False
Definitely
False
1. When people get older, they need to
lower their expectations of how
healthy they can be.

2. The human body is like a car, when
it gets old, it gets worn out.

3. Having more aches and pains is an
accepted part of aging.

4. Every year that people age, their
energy levels go down a little more.

5. I expect that as I get older I will
spend less time with friends and
family

6. Being lonely is just something that
happens when people get old.

7. As people get older they worry
more.

8. It’s normal to be depressed when
you are old.

9. I expect that as I get older I will
become more forgetful.

10. It’s an accepted part of aging to
have trouble remembering names.

11. Forgetfulness is a natural
occurrence just from growing old.

12 . It is impossible to escape the mental
slowness that happens with aging.

57
Mood Induction Instructions
Sad Mood Condition
In the following task, please vividly recall and write about an emotional event that happened to you
personally in the past that made you feel sad.

Please remember the emotional aspects of the event and experience the same feelings you had at the
time when the event took place. Try to describe it as clearly as possible.

Below are some guiding questions that may help you with this task:
What was the event? When did the event take place? How long did it last? Who were involved? What
was your reaction to it? Why?

You will have 5-10 minutes to complete this task.

Neutral Mood Condition
In the following task, please vividly recall and write about an unemotional event that did not happen
to you personally in the past and made you feel neither happy nor sad.

Please remember the factual aspects of the event and picture how you actually responded. Try to
describe it as clearly as possible.

Below are some guiding questions that may help you with this task:
What was the event? When did the event take place? How long did it last? Who were involved? What
was your reaction to it? Why?

You will have 5-10 minutes to complete this task.

58
Old Age Schema Activation

Old Age Schema Condition
There is no right or wrong answer to the items below. Please go over each question SLOWLY and
try your best to answer all of them.

1. In what year were you born? _______
2. Do you consider yourself young, middle-aged, or old? ________
3. At what age do you think the average person becomes OLD? ______
4. At what age do you think the average person becomes VERY OLD? ______
5. In your opinion, which of the following individuals are OLD? Please circle up to 3.
Sidney Poitier/ Shirley MacLaine/ Margaret Thatcher/ Pope Benedict XVI/ Madeleine Albright/
Stephen Hawking/ Diane Sawyer/ Donald Trump/ Patti Page/ Clint Eastwood/ Elizabeth Taylor/
Ali/ Margaret Thatcher/ Bill Cosby
6. In your opinion, which of the following individuals are VERY OLD? Please circle up to 3.
Sidney Poitier/ Shirley MacLaine/ Margaret Thatcher/ Pope Benedict XVI/ Madeleine Albright/
Stephen Hawking/ Diane Sawyer/ Donald Trump/ Patti Page/ Clint Eastwood/ Elizabeth Taylor/
Ali/ Margaret Thatcher/ Bill Cosby
7. How would you describe a person whom you consider to be OLD? What other impression
does he/she give you?
_____________________________________________________________________
8. How would you describe a person whom you consider to be VERY OLD? What other
impression does he/she give you?
_______________________________________________________________

59
Non-Old Age Schema Condition
There is no right or wrong answer to the items below. Please go over each question and try your best
to answer all of them.

1. In which city do you live? ________________
2. Do you consider that city to be sparsely, moderately, or densely populated? _______
3. In general, how many people per square mile do you think a CROWDED city has? ________
4. How many people per square mile do you think a VERY CROWDED city has? ________
5. In your opinion, which of the following cities are CROWDED? Please circle up to 3.
Los Angeles/ Tokyo/ Buenos Aires/ Lima/ Beijing/ Toronto/ Hong Kong/ Berlin/ Helsinki/
Seoul/ Boston/ Manila/ Cape Town/ Paris/ Malabo/ Bombay
6. In your opinion, which of the following cities are VERY CROWDED? Please circle up to 3.
Los Angeles/ Tokyo/ Buenos Aires/ Lima/ Beijing/ Toronto/ Hong Kong/ Berlin/ Helsinki/
Seoul/ Boston/ Manila/ Cape Town/ Paris/ Malabo/ Bombay
7. How would you describe a city that you consider to be CROWDED? What other
impression does it give you?
_____________________________________________________________________
8. How would you describe a city that you consider to be VERY CROWDED? What
other impression does it give you?
_____________________________________________________________________

Abstract (if available)

Abstract This study examined how situational mood state and old age schema influenced attention to physical symptoms in older adults. Seventy-one individuals aged 60 or above participated in an experiment that manipulated mood and old age schema. Participants completed a modified Stroop task that measured attentional bias to symptom words. Analysis of variance showed that sad mood and old age schema had significant main and interaction effects on attention to physical symptoms. Neither variable affected symptoms reporting. Either sad mood or old age schema reversed participants' tendency to divert their attention from physical symptoms. When combined, they led to an attentional bias towards physical symptoms. Interventions to reduce attentional focus on physical symptoms among older adults who have a tendency to somatisize should include strategies to lessen both sad mood and age-related stereotypes.

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Asset Metadata

Creator Poon, Cecilia Yee Man (author)

Core Title Influence of sad mood and old age schema on older adults' physical symptoms processing

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 10/22/2007

Defense Date 05/23/2007

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag aging,OAI-PMH Harvest,physical symptoms

Language English

Advisor Knight, Bob G. (committee chair), Meyerowitz, Beth E. (committee member), Wilcox, Rand R. (committee member)

Creator Email ceciliyp@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m880

Unique identifier UC1331602

Identifier etd-Poon-20071022 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-557485 (legacy record id),usctheses-m880 (legacy record id)

Legacy Identifier etd-Poon-20071022.pdf

Dmrecord 557485

Document Type Thesis

Rights Poon, Cecilia Yee Man

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu