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The role of age, mood, and time- perspective on the interpretation of emotionally ambiguous information
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The role of age, mood, and time- perspective on the interpretation of emotionally ambiguous information
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Running head: AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION i
THE ROLE OF AGE, MOOD AND TIME-PERSPECTIVE ON THE
INTERPRETATION OF EMOTIONALLY AMBIGUOUS
INFORMATION
by
Christine Juang
A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF ARTS
(PSYCHOLOGY)
December 2013
Copyright 2013 Christine Juang
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION ii
Table of Contents
LSIT OF TABLES ............................................................................................................ iii
LIST OF FIGURES ......................................................................................................... iv
ABSTRACT ....................................................................................................................... v
INTRODUCTION ............................................................................................................ 1
Positivity Bias in Late-Life: The Role of Future Time Perspective ............................ 1
Sad Mood and Interpretation Bias: Mood-Congruence Effect ................................... 3
Older Adults’ Tendency to Interpret Ambiguous Information .................................... 5
Current Study .............................................................................................................. 7
Hypothesis................................................................................................................... 8
METHOD ........................................................................................................................ 10
Participants ................................................................................................................ 10
Measures and Materials ............................................................................................ 10
Procedures ................................................................................................................. 14
Analytic Plan ............................................................................................................. 18
RESULT ........................................................................................................................... 21
Manipulation Check .................................................................................................. 21
Analysis on Interpretation Bias ................................................................................. 24
DISUCSSION .................................................................................................................. 27
Hypothesis 1: Main effects of Age ............................................................................ 27
Hypothesis 2: Main effects of Mood ........................................................................ 30
Hypothesis 3: Interaction Effects of Age and Mood ................................................. 31
Hypothesis 4: The Role of Future Time Perspective ................................................ 32
Limitations ................................................................................................................ 34
Summary & Implications .......................................................................................... 34
REFERENCES ................................................................................................................ 37
APPENDIX ...................................................................................................................... 48
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION iii
List of Tables
Table 1 Demographic Measures by age and mood groups ............................................... 49
Table 2 Mean Interpretation scores by face type .............................................................. 50
Table 3. Total number and percentage of negative interpretations by age x mood group 51
Table 4. Mean valence of selected interpretations by situation type ................................ 52
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION iv
List of Figures
Figure 1. Example of ambiguous faces ............................................................................. 53
Figure 2. Mean sadness ratings across time points by Age x Mood groups ..................... 54
Figure 3. Age x face type interactions for interpretation scores ....................................... 54
Figure 4. Mood x face type interactions for interpretation scores .................................... 56
Figure 5. Main effect of age on the proportion of negative interpretations ...................... 57
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION v
Abstract
Previous studies demonstrated detrimental effects of negative interpretation bias, the
tendency to interpret emotionally ambiguous information negatively. The current study aimed
to understand how age, mood, and future time perspective impact interpretation bias. The
positivity effect suggests that older adults would be less affected by sad mood. Seventy- six
younger and 71 older adults were randomly assigned to sad or neutral mood inductions and
completed ambiguous face and situation tasks to assess their tendency to interpret ambiguous
information. Results demonstrated that older adults interpreted neutral faces more positively.
They also generated more positive interpretations in ambiguous interpersonal situations and
selected more positive interpretations as the most likely across situation type than younger
adults. Sad mood led to negative interpretation bias with neutral expressions. No Age x Mood
interaction effects emerged, suggesting that mood state impacted older and younger adults
alike. These findings supported the positivity effect on appraisals among older adults but did
not support the view that older adults were less impacted by sad mood. However, no main
effects of future time perspective were found in the current study; implications of this null
finding were discussed.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 1
Introduction
Most emotional information people perceive is ambiguous rather than clear (Rozin &
Cohen, 2003), and thus, the ability to make subtle distinctions on information for which the
emotional valence is unclear is vital (Issacowitz & Stanley, 2011). In fact, interpretation of
emotionally ambiguous information has been found to play an essential role in the
development, maintenance, and outcome of emotional disorders (Dearing & Gotlib, 2009;
Butler & Mathews, 1983; Gilboa-Schechtman, Foa, Vaknin, Marom, & Hermesh, 2008). In
particular, studies have shown that negative interpretation bias, or a bias favoring the
selection of negative or threatening interpretations, can be detrimental to mental health.
However, studies on this topic have generally been limited to younger populations, and
findings related to interpretation bias among older populations have not been well established.
Furthermore, while past studies on younger adults suggested that mood impacts the direction
of interpretation, there is a less research studying how mood affects older adults. A key
question is whether older adults are susceptible to the influence of mood and whether current
mood state would contribute to the direction of interpretation. Therefore, the proposed study
aims to examine the influence of mood and age-related factors on the interpretation of
emotionally ambiguous information.
Positivity Bias in Late-Life: The Rol e of Future Time Perspective
The socioemotional selectivity theory (Carstensen, Fung, & Charles, 2003) posited that
older adults become increasingly selective and allocate more resources to emotionally
meaningful goals due to the shortening of their future time perspective, or perceived time left
to live. Therefore, older adults are more selective in the information they attend to, which
results in an increase in the ratio of positive to negative information. This phenomenon is
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 2
commonly referred to as the positivity effect, which has been widely supported in studies on
attention (Mather & Carstensen, 2003; Isaacowitz, Wadlinger, Goren, & Wilson 2006),
memory (Kennedy, Mather, & Carstensen, 2004; Charles, Mather & Carstensen, 2003) and
the appraisal of negative events (Comblain, D’Argembeau, & Van der Linden, 2005).
The positivity effect has been found to be driven by an effortful process to attend more
to positive and less to negative information, as demonstrated in a study manipulating older
adults’ attention allocation (Mather & M. Knight, 2005). This effortful process, according to
the socioemotional selectivity theory, is believed to be the result of limited time perspective
in late-life. In fact, Kellough and B. Knight (2012) experimentally expanded older adults’
time perspective and found that the positivity effect no longer existed, confirming the main
tenet of the theory. Thus, compared to younger adults, it is hypothesized that older adults,
with shorter time perceived left, will interpret emotionally ambiguous information more
positively.
Several studies supported this hypothesis and demonstrated the positivity effect in the
interpretation of stimuli for which the emotional valence is not clear. B. Knight, Maines and
Robinson (2002) found that in a lexical ambiguity task, where participants are asked to spell
out homophones, words that are pronounced the same but differ in meanings, older adults
reported significantly less negative-valence homophones compared to younger adults in the
neutral mood condition. Older adults also interpreted affectively ambiguous or emotionally
neutral pictures more positively than younger adults, as indicated by subjective ratings
(Gruhn & Scheibe, 2008) and lower corrugator and eye-blink startle response (van Reekum,
Schaefer, Lapate, Norris, Greischar, & Davidson, 2011).
In addition, studies on the interpretation of ambiguous facial expressions also
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 3
demonstrated similar findings. For instance, when looking at facial expressions with blended
angry and happy cues, older adults were significantly less likely to report anger (Bucks,
Garner, Tarrant, Bradley, & Mogg, 2008). Another study found that older adults’ perception
of ambiguous faces (blends of happy-sad, happy-angry and happy-fear) were more positive
than younger adults, and this positive interpretation bias was attenuated after experimentally
expanding older adults’ perceived time left to live (Kellough & B. Knight, 2012). Taken
together, data indicated that older adults will interpret emotionally ambiguous information
more positively, with time perspective playing a critical factor.
Sad Mood and Interpretation Bias: Mood-Congruence Effect
Another factor that has been found to impact interpretation bias is individuals’ current
mood state. Bower’s (1981) associative network theory and Beck’s (1976) cognitive model
of depression both predicted that when in a negative mood, individuals have an increased
tendency to interpret emotionally ambiguous information more negatively. Specifically,
Bower (1981) stated that each emotion has a specific node or unit in memory and connects
information or reactions such as automatic patterns, events and appraisals that are associated
with that particular emotion. When an individual is in a certain mood, the corresponding
emotional node activates and spreads activation throughout the memory structure. The mood
allows the individual to retrieve information surrounding the emotional node more readily
and influences the interpretative processes and affect the way people elaborate or draw
inferences from ambiguous situations. Beck (1976) postulated that depressed individuals
have negative schemas that affect perception and interpretation of environmental stimuli,
which increases their tendency to impose negative interpretations on ambiguous stimuli,
situations, and events. Thus, both models predicted that depressed mood would influence the
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 4
direction of interpretation. This hypothesis has been confirmed by numerous studies on
younger adults.
Studies have shown that depressed individuals, either clinically depressed or relatively
dysphoric, are more likely to select negative interpretations. Wisco and Nolen-Hoeksema
(2010) conducted a study asking dysphoric individuals to generate interpretations and select
the most likely interpretation of ambiguous situations. The results indicated that when the
situations are self-referent, depressed patients generated and selected more negative
interpretations. In addition to using vignettes, clinically depressed individuals also tend to
interpret homophones more negatively (Mogg, Bradbury, & Bradley, 2006). Furthermore,
when viewing neutral facial expressions, individuals diagnosed with major depressive
disorder had a higher tendency to identify the emotion as sad compared to normal healthy
controls (Gur et al., 1992). A similar finding was found using emotional prosody as stimuli,
suggesting that depressed patients endorsed a bias toward interpreting neutral prosodic
stimuli as negative (Kan, Mimura, Kamijima, & Kawamura, 2004).
In addition to naturally occurring depressed mood, several studies utilizing depressed
mood induction demonstrated similar patterns of negative interpretation bias. When sad
mood was induced, individuals were more likely to write down words that endorsed sad
meanings in a homophone task than were happy subjects (Halberstadt, Niedenthal, &
Kushner, 1995). Interpretations of behaviors and social interactions were also interpreted as
more negative and less positive among participants from the sad-mood condition, and the
opposite was the case for individuals who underwent positive mood induction (Forgas,
Bower, & Krantz, 1984). The mood congruence effect was also demonstrated in the
perception of facial expressions. When sad mood was induced, individuals perceived more
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 5
sadness and rejections in ambiguous faces (Bouhuys, Bloem, & Groothuis, 1995). Another
study indicated that participants in the sad mood condition interpreted neutral-happy faces
less positively and neutral-sad faces more negatively compared to individuals in the happy
mood condition (Niedenthal, Halberstadt, Margolin, & Innes-Ker, 2000).
This negative interpretation bias also appeared to be universal across cultures, as a study
on Chinese individuals found that when sad mood was induced, participants tended to
classify ambiguous faces in the negative rather than positive emotional categories (Lee, Ng,
Tang, & Chan, 2008). Research studies using either naturally-occurring or
experimentally-induced depressed mood portray a consistent picture that depressed mood
impacts the direction of interpretation of ambiguous information in a negative way. Thus, it is
believed that in a depressed mood, individuals will endorse a negative interpretation bias, at
least in younger adults.
Older Adults’ Tendency to Interpret Ambiguous Information
How then, will older adults interpret emotionally ambiguous information? Under normal
circumstances without mood inductions, according to the socioemotional selectivity theory
(Carstensen et al., 2003), older adults will make more positive interpretations of emotionally
ambiguous information due to their limited time perspective. If this is true, then when time
perspective is experimentally expanded in older adults in neutral mood, the positivity effect
should not be present. The question then becomes whether sad mood affects older adults’
tendency to interpret ambiguous information. Although positive baseline mood does not
appear to facilitate the positivity effect, as indicated by studies controlling for baseline mood
(for a review, see Mather, 2006), it does not imply depressed mood will not affect older
adults’ processing of emotional information. In fact, a meta-analytic review indicated that
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 6
mood congruence effects on memory were more variable in induced elated (positive) mood
but were fairly consistent across clinically depressed and induced depressed individuals
(Matt, Vazquez, & Campbell, 1992). Thus, having higher levels of positive mood may not
facilitate the positivity effect, but sad mood, on the other hand, inhibits or attenuates the
effect.
This notion that older adults can be negatively impacted by sad mood has been
supported by several studies. For instance, one study found that when sad mood is induced,
older adults attend to more physical symptoms compared to the control group, indicating that
sad mood increased the tendency to attend to negative information in late-life (Poon & B.
Knight, 2009). Another study found that although the positivity effect on autobiographical
memory was still present, it was less pronounced in depressed than non-depressed older
adults. Furthermore, the researchers found that with greater severity of depressive symptoms,
there was lessening of the tendency to retrieve more positive than negative memories
(Serrano, Latorre, & Gatz, 2007). Yang and Rehm (1993) also showed similar findings:
clinically depressed older adults recalled more sad memories than did non-depressed older
adults. In addition to mood congruent attention and memory, another study, which to our
knowledge is the only one to specifically examine the influence of mood on ambiguous
information in late-life, also showed support for the mood congruence effect. Using the
lexical ambiguity task, older adults spelled out as many negative words as younger adults,
indicating that the positivity effect no longer existed in the sad mood condition (B. Knight et
al., 2002).
Therefore, based on these studies that demonstrated the mood congruence effect in old
age, it is reasonable to predict that sad mood impacts older adults’ tendency to interpret
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 7
emotionally ambiguous information. However, inconsistent with other findings, one study
found that older adults demonstrated mood incongruent gaze when they were induced with
sad mood, which is indicative of a strong motivation to maintain in positive mood
(Isaacowitz, Toner, Goren, & Wilson, 2008). Thus, it should also be noted that the degree of
impact may be varied by time perspective, because according to the socioemotional
selectivity theory (Carstensen et al., 2003), limited time perspective motivates older adults to
value emotional goals. Thus, older adults whose time perspective is expanded may endorse
negative interpretation bias, but among older adults whose time perspective is limited,
depression may impact older adults less by attenuating or inhibiting the positivity effect,
rather than resulting in negative interpretation bias. Although studies have tested the effects
of depressed mood and time-perspective individually, no studies to our knowledge have
examined interactions of both factors. Therefore, whether or not diminished time perspective
could buffer the level of impact of depressed mood in late-life remains unclear and would be
addressed in the proposed study.
Current Study
Based on previous findings, it is hypothesized that in neutral mood, in comparison to
younger adults, older adults will interpret ambiguous information more positively due to their
limited time perspective, but when older adults are sad, the positivity effect in late-life will
no longer exist due to mood-congruent effect. The study also aims to examine the role of
time perspective and how it interacts with mood. Specifically, the degree to which sad mood
impacts older adults’ processing may be moderated by time-perspective. If time perspective
is found to be protective against sad mood, temporal horizon may be an important issue to
address in the therapeutic context. However, if mood congruence exists regardless of
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 8
individuals’ time perspective, it implies that the positivity bias due to limited time
perspective can only be extended when older adults are in neutral mood. Once older adults
are in an intense and depressed emotional state, positivity bias may no longer exist to serve
as a channel to maintain emotional well-being.
To examine the hypothesis derived and questions raised, (1) both older and younger
adults will be included in the present study in order to make a direct age difference
comparison and confirm the existence of the positivity effect; (2) ambiguous facial
expressions and situations will be used to represent emotionally ambiguous information; (3)
the effect of sad mood on interpretation bias will be explored in laboratory by using mood
induction techniques; (4) time perspective will also be experimentally manipulated among
older adults in order to test the main tenet of socioemotional selectivity theory and its
interaction with depressed mood in late life. Note that time perspective manipulation is only
conducted in older adults, because the main purposes is to test the main tenets of the
socioemotional selectivity theory and examine how depressed mood and time perspective
interacts in late-life emotional processing.
Hypothesis
1. There will be a main effect of mood induction, in which both older and young adults
assigned in the sad mood condition will be more depressed compared to the control mood
condition.
2. For participants without FTP manipulation, there will be a main effect of age, such that
older adults will interpret emotionally ambiguous information more positively than younger
adults.
3. For participants without FTP manipulation, there will be a main effect of mood, such
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 9
that participants in the sad mood group will interpret more negatively than participants in the
neutral mood group.
4. For participants without FTP manipulation, there will be an interaction effect between
age and mood, such that the impact on sad mood will be larger for younger than for older
adults.
5. For older participants, there will be an interaction effect between mood and future time
perspective, such that the impact of sad mood will be larger for participants in the “expanded
FTP” group than in the control group.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 10
Method
Participants
Seventy-six younger adult participants were USC undergraduate students who were
recruited from the USC Psychology Subject Pool. Younger adults ranged from 18 to 29
years-old (M=19.89, SD=1.69) with 76% of them being females. Forty-nine percent of
younger adults identified themselves as Asian, 29% as Whites, 6% as Latinos, 6% as African
Americans, and 9% as others. Younger adults received extra course credit as compensation.
Exclusion criteria included current treatment for mood and anxiety disorders.
Older adult (n=71) participants’ ages ranged from 60 to 94 (M=73.39, SD=7.48).
Sixty-four percent of older adults were females, and 36% are males. The older adult sample
was predominantly white (82%) with 10% African American, 4% Asian, and 4% others.
Older participants were recruited from either the USC Healthy Minds subject pool (n=67) or
an independent-living senior housing in South Pasadena (n=4). They received eight dollars as
compensation. Exclusion criteria for the older adult sample included the presence of
cognitive impairment, and current treatment for mood and anxiety disorder, hearing and
vision difficulty, and reading and writing difficulty. Participants were screened by telephone.
Cognitive impairment or possible dementia was assessed using a brief 10-item cognitive
assessment (TELE; Gatz et al., 2002) based on a cut-off score of 16. Other exclusion criteria
were determined through participants’ self-report.
Measures and Materials
Demographic Information. Information regarding, age, gender, ethnicity, educational
level, primary occupation, and annual income were asked to obtain basic demographic
variables.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 11
Mood.
Center for Epidemiological Studies — Depression Scale. Center for Epidemiological
Studies— Depression Scale (CES-D; Radloff, 1977) contains 20 items assessing depressive
symptoms in the past week. Participants indicated the frequency of the symptoms on a
4-poing scale, with responses ranging from 0 (rarely or none of the time) to 3 (most of the
time). The reliability of CES-D has been well established (Cronbach’s α= 0.85-0.90), and it
has been found that CES-D could discriminate between psychiatric inpatient and general
population well, indicating good discriminant validity (Radloff, 1977). Internal consistency
of this measure in the current study was alpha= 0.87.
Visual Analogue Scale for Sad Mood. Participants’ mood ratings were recorded using
the visual analogue scale (V AS) consisting of a 10-cm line with 11-point rating scale, with 0
being put at the left end of the line indicating “Not sad at all” and 10 at the right end
indicating “Extremely sad.” The V AS scale for sad mood has been used in numerous studies
and proved useful in the assessment of sad mood in both healthy and cognitively impaired
individuals (Cella & Perry, 1986; Kertzman et al., 2004).
Future Time Perspective. We aimed to keep our battery short due to the temporary
effects of mood induction. Thus, our future time perspective assessment was adapted from
the Future Time Perspective Scale (FTP; Carstensen & Lang, 1995), which is a 10-item
measure used to assess the subjective perception of time left. We randomly selected 5-items
to serve as a proxy for FTP measurement. The five items selected were “My future seems
infinite to me,” “I expected that I will set many new goals in the future,” “I could do anything
I want in the future,” “There is plenty of time left in my life to make new plans,” and “As I
get older, I begin to experience that time is limited.” The final item was reverse scored.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 12
Previous studies have shown adequate internal consistency, with Cronbach’s α ranging from
α= .72 to .80 (Fung, Lai, & Ng, 2001). The internal consistency of the adapted measure in
our study was α= .75, which was in the same range of Cronbach’s α reported in previous
studies.
Emotionally Ambiguous Information
Ambiguous Facial Expressions. Images of facial expressions were selected from the
collection of Karolinska Directed Emotional Faces (KDEF; Lundqvist, Flykt, & Ohman,
1998). Nine different clear faces were selected, including 3 happy, 3 sad and 3 angry
expressions, and 9 different subtle faces were selected, including 3 subtle-happy, 3 subtle-sad
and 3 subtle-angry expressions. These 18 faces were included as fillers in the task.
In addition, two types of faces were included to represent ambiguous facial expressions,
including neutral (Yoon & Zinbarg, 2007) and mixed (Buck et al., 2008; Kellough & Knight,
2012). Neutral faces were defined as neither positive nor negative, and mixed faces were
defined as a morphed faces of 50% positive and 50% negative emotions. Six photos of
neutral expressions posed by different actors, with balanced genders, were selected from the
database. Mixed faces were generated using FantaMorph 4.0, a software that produces
images with 10% increments from the first to second picture. Twelve mixed faces were
created, including 6 photos representing for Happy-Sad and 6 photos for Happy-Angry faces
(see Figure X.) In total, 36 facial expressions were selected and generated.
Ambiguous Situations. Ambiguous scenarios were adapted from the Interpretation Bias
Questionnaire (IBQ; Wisco & Nolen-Hoeksema, 2010). The original IBQ included 10
vignettes. Some vignettes from the original measure that were not applicable to older adults
were deleted (e.g., situations involving “taking exams” or “asking professor to write letters of
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 13
recommendation.”), which left four vignettes left from the original measure (e.g., “You’re
walking down the street, and you see one of your friends coming the other way with a group
of people. You wave, but your friend doesn’t respond. Why?”). To investigate other types
of ambiguous situations, we decided to add ambiguous situation that are health- related,
which is relevant to both age groups.
In our pilot work, we included the four original vignettes and four new vignettes of
health-related situation (e.g., “You asked your doctor about your condition, and your doctor
did not respond immediately. Why?”) Nine volunteers completed the 8 vignettes, and
ultimately 5 vignettes were chosen, with 3 interpersonal- related situations from the original
IBQ and 2 health- related vignettes. The selection criterion was vignettes for which
participants generated a mean of at least 3 interpretations as the original authors of IBQ
suggested. See Appendix for the full text of the final 5 vignettes adapted for both older and
younger adults. Participants were asked to write down all the interpretations that came to
mind.
The valence ratings of the interpretations were based on two independent coders. A
coding manual and sample interpretations as anchors were provided to ensure that same
criteria were used. According to Wisco and Nolen-Hoeksema (2010), “negative” was
operationalized as “being any interpretation that reflected poorly upon the participant or had
negative consequences for his/her life,” and “positive” as “including a positive portrayal of
the participant or suggesting beneficial outcomes for him/her.” Coders rated the valence
(positivity and negativity) of each of the interpretations they generated on Likert-type scales
from 1 (not at all) to 5 (extremely).
Coders were blind to the age groups and conditions of the responses. They were also not
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 14
aware of whether responses were from the same participants by randomly ordering the
interpretations they rated to reduce any potential bias. Coders demonstrated adequate
inter-rater reliability. Across the 5 vignettes, the intraclass correlation (ICC) of positivity
ranged from .72- .92, and the ICC of negativity ranged from .84- .94. Rating discrepancies
were resolved by discussing and reaching consensus among the two coders.
Procedures
Participants who were eligible and expressed interest were scheduled for an
appointment in a single- person format or a group format of 2-5 participants. Studies took
place either at a quiet room at the USC Gerontology building or the senior housing in South
Pasadena. Upon arrival, participants were asked to sign consent forms and fill out their
demographic information, CES-D and V AS. To minimize time lost after the experimental
manipulations, participants were given detailed instructions of the two interpretation tasks
and completed the practice trials prior to any experimental manipulations. Older adults who
were randomly assigned to conditions with future time perspective manipulation then
received instructions as described in the following section. Afterwards, participants were
induced with either sad mood or neutral mood. After all necessary instructions for different
manipulations were completed, the experimenter administered tasks on the interpretation of
ambiguous information. Throughout the experiment, mood was assessed periodically using
V AS till the completion of the interpretation tasks. Finally, when the study ended, the
experimenter debriefed all participants on the nature of the study and confirmed that their
mood had returned to their baseline.
Future Time Perspective Manipulation & Check
The underlying assumption of the socioemotional selectivity theory is that older adults
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 15
have a shorter temporal horizon, which is the main factor that causes older adults to become
motivated to maintain positive mood. Thus, to test this hypothesis, the manipulation involved
“expanding” the future time perspective for older adults. The instructions were adopted from
Kellough and B. Knight’s (2012) study, which stated, “Imagine that last week you found out
from your doctor about a new medical advance that ensures you will enjoy 20 more years
beyond the age you expected to live, in reasonably good health.” To sustain the future time
perspective manipulated, after the first interpretation task, older adults received instructions
reminding them that they have 20 more years to live. Manipulation check was assessed via
the FTP scale after the manipulation and after the reminder. No baseline assessment of FTP
was conducted. The instructions for manipulating time perspective took only an additional
60-90 seconds, which ensured minimum difference between the two groups.
Mood Induction & Assessment
Sad Mood Induction. To induce and sustain sad mood throughout the experiment,
participants watched two video clips on the Japanese earthquake in 2011. The content of the
video clips mainly included scenes of grieving for the loss of loved ones. The clips were
excerpted and edited from several news clips and documentaries from CNN, Sky News, and
a Japanese Channel that were found on the internet. Subtitles were provided in parts when the
spoken language was in Japanese. The first clip (total duration= 8 minutes and 3 seconds)
was played before the first interpretation task to serve as the primary mood induction. The
second clip (total duration= 5 minutes and 6 seconds) was played after the first task to serve
as a “mood augmentation” to “boost” sad mood.
The video clips were found most effective in inducing participants’ sad mood in our
pilot study when compared to other mood induction methods, including recalling
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 16
autobiographical memory of sad events (Salovey & Birnbaum, 1989; Levenson, Carstensen,
Frieson, & Ekman, 1991), imagining of death of someone they loved (Chepenik, Cornew, &
Farah, 2007), and watching a film clip from the movie Million Dollar Baby (Knight,
Kellough, & Poon, unpublished). For each method of mood induction, the pilot study
included at least 3 older adults and 4 younger adults. In the pilot study for the two video clips,
the pilot study included 8 younger and 3 older adults. Findings from the pilot study indicated
that levels of sad mood post-induction were significantly higher than other moods, including
happy, angry, fearful, disgusted, anxious mood, suggesting that the film clip primarily
induced sad mood. All participants provided qualitative feedback that the impact of the clips
was minimal and temporary.
After playing the video clips, participants listened to music pieces used in previous
studies to elicit sad mood throughout the experiment to sustain the emotions. These music
pieces included Prokofiev's (1939, track 1) Russia Under the Mongolian Yoke, Barber's (n.d.,
track 2) Adagio for Strings, Albinoni's (n.d., track 1) Adagio, and Sibelius' (n.d., track 4) The
Swan of Tuonela (Fox, Knight, & Zeliniski, 1998).
Neutral Mood Induction. Participants in the neutral mood induction, on the other hand,
watched two video clips from a BBC documentary film on “Satoyama: Japan’s Secret Water
Garden.” The content mainly included scenes regarding the natural scenery, animals and
people around Satoyama. The first clip (total duration= 7 minutes and 35 seconds) was
played before the first interpretation task to serve as the primary mood induction for neutral
mood. The second clip (total duration= 5 minutes and 15 seconds) was played to parallel the
process of sad mood induction. Pilot work of 3 younger and 3 older adults showed that there
were no significant mood changes from pre- to post- induction. Although the mean of happy
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 17
mood was higher than sad, angry, disgusted, anxious, and fearful mood, there were no
significant differences. To sustain neutral mood, harpsichord concertos by Bach (1715;
“English Suites” numbers 2 [tracks 7–12], 3 [tracks 1–6], and 6 [tracks 13–18]) will be
played.
Calm/ Positive Mood Induction. To ensure that participants’ mood is returned to
baseline, at the end of the two interpretation tasks, a calm/ positive mood induction was
conducted. Specifically, for the neutral mood group, participants watched the video clip on
babies. Participants in the sad mood group, on the other hand, watched a film clip on Japan’s
recovery post- earthquake and the same video clip on babies.
Mood Assessment. Participants recorded their level of sad mood on VAS right before
and after the mood induction and between interpretation tasks. In summary, there will be 6
time points for mood assessment, Time 0 (baseline, prior to mood induction), Time1 (after
mood induction, before task 1), Time2 (after task1, prior to mood booster), Time3 (after
mood booster, prior to task 2), Time4 (after task 2, prior to calm/ positive mood induction),
and Time5 (post- calm/ positive mood induction).
Interpretation Tasks
Two interpretation tasks were utilized in this study. Order of task administration was
randomly assigned.
Ambiguous-Face Interpretation Task. The interpretation task was performed via
paper and pencil format. The packet was printed black-and-white, with one photograph of
face per page. Below the photograph was a positivity-negativity grid that had numbers
ranged from -4 to 4, with 0 omitted in the grid. Participants were asked to circle a number
that best represents the emotions they perceived. They were given the instructions below:
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 18
“On the grid below, each number indicates how positive or negative and how intense the
face above is. Negative numbers represent negative emotions, and positive numbers
represent positive emotion. The closer the number is to the end of each line, the higher the
intensity of the emotion (eg., -4= Extremely Negative, -1= Mildly Negative 1= Mildly
Positive, 4= Extremely Positive.)” The number zero was omitted in the grid to force
participants choose between a positive or negative number in order to examine the valence of
participants’ interpretations.
Ambiguous-Situation Interpretation Task. Participants were instructed to imagine
that the vignettes happened to them and were asked to write down all the explanations, with
no limits as to how many explanations they wished to write. Participants were instructed to
write down the explanations in the order they thought of them. Finally, they were asked to
identify which explanation was deemed the most likely in that given situation.
Analytic Plan
Mood Manipulation Check. The effectiveness of mood induction was examined using
a repeated measures analysis of variance (ANOVA), with time of mood assessment as
within-subject factor, mood condition and age group as between-subject factors, and VAS as
the dependent variable.
Future Time Perspective Manipulation Check. To examine whether the FTP
manipulation was successful, we compared the FTP scores after FTP manipulation in three
groups: younger age group, and older age groups with and without FTP manipulation.
Analysis on Interpretation Bias.
Calculation of Interpretation Bias Scores. For the Ambiguous-Face Interpretation Task,
interpretation bias scores were determined by the circled number from the grid. Interpretation
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 19
scores for each subcategory of ambiguous faces (eg., neutral, happy-sad blend, or
neutral-angry blend) were the average of interpretation scores of the facial expressions
belonging to that subcategory. We also averaged the interpretation scores across face types to
obtain an average interpretation score of “ambiguous faces.”
With regards to the Ambiguous-Situation Interpretations, interpretation scores were
determined by the rating of two independent raters. Each explanation generated received a
final rating based on the agreement between the coders. A benign, or positive, interpretation
was operationally defined as explanations that received a rating equal to or above zero. We
then calculated two kinds of scores separately for each vignette: (a) proportion of benign
interpretations (number of benign interpretations generated divided by total number of
interpretations generated) and (b) the final rating of the “selected interpretation” that was
believed to be the most likely explanation. We then calculated both (a) and (b) for each
situation type by averaging the scores from vignettes that either belonged to health- or
interpersonal- related situations. Finally, mean scores of (a) and (b) for “ambiguous situation”
in general were calculated via averaging the scores from the two situation types.
Analysis on Effects of Age, Mood, and Future Time Perspective. To investigate how
age and mood play a role in interpreting emotionally ambiguous information, a repeated
measures analysis of variance (ANOVA) was performed, with age and mood condition as
between-subject factor. The within-subject factor varies by task. For example, for the
ambiguous-face interpretation task, the within-subject factor was the interpretation scores for
the three face types (neutral, happy-sad, and happy-angry). Two repeated measures ANOV A
were performed for the ambiguous- situation interpretation task, with one within- subject
factor being the proportion of benign interpretations and the other being the valence of the
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 20
selected interpretations for the two types of ambiguous situations (health- related and
interpersonal- related).
Initially, we planned to use another repeated measure ANOVA to investigate the role of age
and FTP, but due to the ineffectiveness of our FTP manipulation, this analysis was not
performed. For more information, please refer to the result section on FTP manipulation
check.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 21
Result
Manipulation Check
Sample Characteristics. All participants were randomly assigned to either neutral or
sad mood group. Thirty-Six and 40 younger adults were randomized to the neutral and sad
mood respectively. Thirty-seven older adults were randomized to the neutral mood group,
and 34 older adults in the sad mood group. No significant differences between mood groups
were found in their demographic variables and baseline measures. There were some
differences in the demographic variables between different age groups. Older and younger
participants differed significantly in ethnicity, χ
2
(4, N=146)= 51.36, p < .0001, depressive
symptoms, t(143.10)=5.00, p < .0001, baseline sad mood, t(139.61)= 3.48, p= .001, and
education, t(101.75)= -5.66, p < .0001. See Table 1 for more details.
Mood Induction Manipulation Check. The effectiveness of mood induction was
examined using a repeated measures analysis of variance (ANOV A), with time of mood
assessment as within-subject factor, mood condition and age group as between-subject
factors, and V AS as the dependent variable. The VAS ratings showed a significant Induction
x Time interaction, F(4.49,605.70) = 88.41, p < .0001, η
p
2
=.40, indicating that the mood
induction procedure was successful in producing sad mood. There was also a significant Age
x Time interaction, F(4.49,605.70)= 2.65, p = .03, η
p
2
= .02, with older adults reporting lower
levels of sad mood across all time points, with the exception of Time 2 and Time3. Finally,
there was a significant three way interaction, F(3.68,499.83) = 2.66, p = .04, η
p
2
= .02, where
the age differences were most apparent at baseline (Time 0), Time2, and Time4 in the sad
mood induction group. Averaging the sad mood rating across time points, results indicated a
significant main effect of mood, F(1, 135)= 224.96, p < .0001, η
p
2
= .63. No main effect of
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 22
age nor an Age x Mood interaction were found. See Figure 2 for sad mood ratings at 6 time
points by age and mood groups.
Inclusion criteria based on change in sad mood from baseline to post-induction.
Although the manipulation check suggested that the mood induction procedure was effective
for both age groups, we further reviewed within-person changes in their state mood at Time 0
(baseline) and Time 1 (post-induction) to identify individuals that were either unresponsive
(i.e. change equals zero) or had an unexpected responses (i.e. in the reverse direction) to the
mood inductions. Review of the data indicated that 1 older and 1 younger adult from the
neutral mood group became more sad post induction. Among participants from the sad mood
group, 2 younger adults were not responsive to the induction, 1 younger and 2 older adults’
mood became more positive and less sad post-induction. We excluded these individuals in
subsequent analysis to ensure that the effects of mood state were not diluted. This resulted in
the removal of 4 younger and 3 older adults, such that in total there are 72 younger adults (35
in the neutral mood and 37 in the sad mood group) and 68 older adults (36 in the neutral
mood group and 32 in the sad mood group).
Future Time Perspective Manipulation Check. FTP was assessed twice
post-manipulation, and no differences were found between the FTP scores at two time points.
The average of the two FTP assessment scores was chosen as the dependent variable in the
following analysis. We first compared the FTP score in three groups, younger adult group,
and older adult group with and without FTP manipulation. An ANOVA indicated that the
three groups did not differ on the average score of the two FTP assessments, F(2, 124)=.83,
p= .44, η
p
2
= .01. We performed the same analysis only in participants from the neutral mood
group, and still no differences were found in the three groups, F(1, 71)= .24, p= .62, η
p
2
< .01.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 23
We further examined whether age and mood had an effect on future time perspective.
Unexpectedly, no main effect of age was found in the FTP scores, F(1,121)= .95, p= .33,
η
p
2
< .01. Also surprisingly, mood induction had a significant effect on future time
perspective, F(1,121)=4.34, p < .05, η
p
2
= .04, such that participants in the sad mood group
had a more limited FTP, comparing to participants in the neutral mood group. No Age x
Mood interaction effects were found, F(1,121)= .25, p= .62, η
p
2
< .01. In summary, it was
concluded that FTP manipulation in older adults was not successful and that mood induction
may had an unexpected effect on FTP scores. Hence, no further analysis regarding future
time perspective was performed in the later proportions.
However, the failure to find age differences in FTP led us to compare our FTP scores to
other studies that also measured FTP in both age groups. Given that our FTP measure only
contained 5 items, we doubled our score and compared our data in the neutral mood group to
the data obtained from other studies. Please refer to Table 2 to see the mean, standard
deviation of the FTP scores and the sample size of older and younger adults in each study.
We first compared our scores to older and younger adults from the control group in
Kellough and Knight’s (2012) study. Results revealed that the FTP scores in our younger
adults sample were significantly lower than the younger adult sample in their study, t(98)=
-4.79, p <.0001, d= 1.00. However, no significant differences were found between the older
adult sample, t(88)= -.56, p= .58, d=.12. We then compared the FTP scores to Loeckenhoff,
Cook, Anderson, and Zayas’s (2013) study. We obtained a similar result for our younger
adult sample; that is, younger adults’ FTP scores in our sample were significantly lower than
their study, t(74)= -9.15, p < .0001, d= 2.10. There were also significant differences in the
older adult sample, such that the FTP scores obtained in our older adult sample were
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 24
significantly lower than their older adult sample, t(70)= -3.10, p <.01, d= .73. Finally, we
compared our scores to Thomas, Kim, Goldstein, Hasher, Wong and Ghai’s (2007) study.
Analysis yielded similar to the result reported previously: FTP scores for our younger
[t(102)= -10.68, p < .0001, d= 2.20] and older adults [t(98)= -4.37, p < .0001, d= .94] both
were significantly lower than their counterparts in Thomas and colleagues’ (2007) study. In
summary, based on our data, our younger adults’ FTP appeared to be more limited than the
other samples, whereas older adults’ FTP were equally or even more limited compared to
other older adult sample.
Analysis on Interpretation Bias
Ambiguous Facial Interpretation Task. Interpretation scores of different types of
faces across age and mood groups are shown in Table 2. To investigate the role of age and
mood on different facial expressions, a repeated measure analysis of variance (ANOV A) was
performed, with the types of emotional expressions as within-subject factor (Neutral,
Happy-Sad, and Happy-Angry, Happy, Sad, Angry), mood condition and age group as
between-subject factors, and the interpretation score as dependent variable.
Results indicated that there were significant differences in the interpretation scores
among face types, F(3.86, 508.96)= 1527.46, p= <.0001, η
p
2
= .92, such that happy
expressions were most positive, followed by neutral expressions, then happy-sad and
happy-angry expressions, and finally sad and angry expressions. We also found a significant
Age x Face Type interaction effect, F(3.86, 508.96)=7.97, p< .0001, η
p
2
= .06, where age
differences were most significant in the neutral and happy expressions (see Figure 3). There
was also a significant Mood x Face Type interaction effect, F(3.86, 508.96)=3.19, p< .02,
η
p
2
= .02, such that mood congruence effects were most apparent in neutral and happy
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 25
expressions compared to other emotions (see Figure 4). No main effects of age and mood nor
an age x mood interaction were observed for the average interpretation scores across face
types.
Ambiguous Situation Interpretation Task
Mean Proportion of Negative Interpretations Generated. We then examined the
effects of age and mood on the proportion of negative, neutral and positive interpretations
generated. Negative interpretations are operationalized as interpretations with ratings below
zero. The proportion of negative interpretations was calculated by the number of negative
interpretations divided by the total number of interpretations generated in a given vignette.
See Table 3 for the total number of interpretations and percentage of negative interpretations
by age and mood group.
We performed a repeated measure ANOV A on the proportion of negative interpretations,
with situation type (health- related and interpersonal- related) as within-subject factor and
age and mood as between subject factors Results demonstrated a main effect of age, F(1,
136)= 5.36, p <.03, η
p
2
= .04, such that older adults generated a smaller proportion of negative
interpretations (see Figure 5). No mood main effect or Age x Mood interaction effect
emerged. Results also showed a significant Age x Situation type interaction, F(1, 136)=10.74,
p< .01, η
p
2
= .07, such that older adults generated a significantly lower proportion of negative
interpretations in ambiguous interpersonal situations, whereas no age differences were found
in the ambiguous health- related situations (see Figure 6).
Average Valence of Selected Interpretation. We examined whether there were any age
and mood effects on the valence of the interpretations that participants identified as the “most
likely” explanation. See Table 4 for the average valence of selected interpretations by age
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 26
and mood groups. Results indicated that in general, the valence of selected interpretations in
the interpersonal- related situations were significantly more positive than in health- related
situations, F(1, 131)= 29.02, p< .0001, η
p
2
= .18. We also found a main effect of age, F(1,
131)= 11.20, p< .01, η
p
2
= .08, such that more older adults selected interpretations with more
positive ratings as the most likely explanation than younger adults across situation type (see
Figure 7). No main effect of mood nor interaction effect of age and mood were identified.
Results also did not demonstrate any Age x Situation interaction.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 27
Discussion
The current study aimed at investigating the role of mood, age and future time
perspective (FTP) on the interpretations of emotionally ambiguous information.
Hypothesis 1: Main effects of Age
We hypothesized that there would be a main effect of age, such that older adults
interpret ambiguous information more positively regardless of mood group. This hypothesis
was supported using both faces and vignettes as ambiguous stimuli. Compared to younger
adults, older adults interpreted neutral expressions more positively. This was consistent with
previous findings on age differences regarding the interpretations of neutral expressions
(Gruhn & Scheibe, 2008; van Reekum, et al., 2011). However, age differences were not
significant when interpreting mixed expressions as demonstrated in other studies (Bucks et
al., 2008; Kellough & B. Knight, 2012). This implied that sources of ambiguity differ. As
such, different types of faces provide different levels of emotional cues. For instance, the
ambiguity of mixed facial expressions comes from the competing interpretations of positivity
and negativity, whereas the neutral facial expressions are ambiguous due to the lack of salient
emotional cues. It may be that older adults are less likely to interpret mixed faces more
positively because the recognition of negativity in mixed expressions may serve as
contradictory evidence to a positive interpretation, whereas the absence of contradictory
evidence in neutral expressions may increase the likelihood of a positive interpretation.
Our findings on age differences in the interpretation of clear faces (happy, sad, angry)
aligns with this interpretation. Specifically, older adults interpreted happy faces as more
positive than younger adults, but no age differences emerged for negative faces, including
sad and angry expressions. This finding is consistent with previous findings, such that age
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 28
differences are most evident when the emotional content is positive versus negative
(Carstensen & Mikels, 2005). Hence, age differences are less likely to emerge when the
content of stimuli contains negative information, such as mixed expressions morphed
between positive and negative emotions.
In addition to the ambiguous face task, our results from the ambiguous- situation task
also demonstrated that on average, older adults generated and selected interpretations that
were more positive than did younger adults. Although few studies have directly examined the
interpretations of ambiguous situations, this finding is consistent with previous studies
indicating that older adults’ appraisal of negative events are more positive and less negative.
For instance, when compared to ratings of objective coders, older adults’ appraisals of daily
stressors (Almeida & Horn, 2004) and difficult spousal interactions (Story et al., 2007) were
less severe and more positive. Older adults’ appraisals of conflicts had neutral or positive
meaning which can downplay the negativity of the situation (Diehl et al., 1996). In another
study where participants were asked to answer questions about their initial appraisal and the
perceived stress of a stressor that occurred the prior week, older adults reported less negative
appraisals and lower levels of perceived stress (Boeninger, Shiraishi, Aldwin, & Spiro,
2009).
Upon stratifying the ambiguous situations by types of situation (health- related and
interpersonal- related), our findings indicated that in interpersonal- related situations, older
adults not only generated but also selected more positive interpretations. This finding
supported other research suggesting that older adults experience lower frequency of negative
interpersonal interactions and less intense emotional responses when social conflicts occur
(Charles & Carstensen, 2010; Lefkowitz & Fingerman, 2003). Compared to younger adults,
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 29
older adults may be less likely to perceive the same ambiguous interpersonal situation as
negative, which leads to fewer self-reported negative interactions. Furthermore, because
thoughts are strongly associated with our emotions, these benign thoughts may lead to less
negative affective responses.
Although no study, to our knowledge, directly examined older adults’ responses to
ambiguous social situations directly, one study using the “Cyberball paradigm” found that
older adults appeared to be less sensitive to mild forms of social exclusion where cues of
rejection were more subtle compared to younger adults, whereas when social exclusions were
more clear and severe, no age differences in their affective response emerged (Lockenhoff,
Cook, Anderson, & Zayas, 2013). The authors raised concerns regarding the lack of
sensitivity to negative social cues among older adults, possibly caused by poorer cognitive
functioning. However, our data suggested that although older adults generated more positive
interpretations, they also did not completely disregard possible negative aspects of a given
situation.
On the other hand, in health- related ambiguous situations, no age differences were
found in the proportion of generated benign interpretations. This finding suggested that
health- related situations did not facilitate the “positive interpretation bias” in late-life as
indicated by our other findings. This may reflect the fact that older adults experience more
health issues and utilize more health care (Alemayehu & Warner, 2004), which may increase
the recognition of negative aspects of ambiguous health- related situations among older
adults compared to younger adults who utilize health care less. Interestingly, despite
generating a similar proportion of benign/ negative interpretations, older adults showed a
tendency to select interpretations with more positive ratings in health related situations. This
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 30
was consistent with Lockenhoff and Carstensen’s (2004) predictions that the older adults may
pay more attention to positive and avoid negative information that may potentially be
debilitating in the health- domain. In their review, older adults were found to seek less health-
related information and prefer more emotionally meaningful and positively- valenced
materials. Our study demonstrated that in health-related ambiguous situations, it is not that
older adults did not become aware of negative aspects but that they chose to believe that the
positive was more likely.
In summary, our study suggested that older adults, on average, tend to interpret
emotionally ambiguous information, across stimulus modality, more positively than younger
adults. Additionally, we also demonstrated that it is important to differentiate “subtypes” of
ambiguous information (eg., neutral vs. mixed faces; health- related vs. interpersonal- related
situations). Future studies should assess the boundaries and limits of this “positive
interpretation bias” and investigate the mechanisms in which it is operated on.
Hypothesis 2: Main effects of Mood
We also hypothesized that there would be a main effect of mood, such that participants
in the sad mood group would show a negative interpretation bias compared to participants in
the neutral mood group. This hypothesis was partially supported in the ambiguous facial
expression task, such that neutral and happy expressions were interpreted more negatively in
the sad mood group. However, we did not find mood-congruence for mixed, sad, or angry
faces.
This is consistent with previous findings demonstrating diminished emotional response
for pleasant rather than negative stimuli. For example, Sloan, Strauss & Wisner (2001) found
that patients with major depressive disorder and normal control groups only differed in the
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 31
emotional response of pleasant but not unpleasant stimuli. Another study also found that
clinically depressed individuals were less likely than normal controls to label 50% intensity
happy faces and neutral faces as happy (Surguladze et al., 2004). These studies suggest that
depressed individuals are characterized by diminished emotional response to pleasant stimuli,
which explains symptoms of anhedonia, or the inability to experience pleasure from activities
that were previously enjoyable. Therefore, our results lend support for the diminished
positive identification hypothesis for depression, such that sad mood and depression
diminishes one’s emotional response to pleasant stimuli.
On the other hand, based on our finding, sad mood did not impact the generated and
selected interpretations of ambiguous situations. One possible explanation is that facial and
lexical stimuli are processed differently, which leads to different mood-congruency effects.
For instance, some researchers posited that, comparing to words, pictures are being processed
more automatically and rapidly (Viswanathan & Childers, 2003), and other researchers have
suggested that the influences of mood on cognitive processes are automatic (Bower, 1981).
Vignettes are complicated lexical stimuli that contain story-like information, which requires
more effort to process such information, and thus, the generation and selection of
interpretations of vignettes may be less susceptible to the influence of sad mood. Regardless,
our study demonstrated that state mood can impact individuals’ interpretations of emotionally
ambiguous information, but the degree of its impact may differ by the stimulus valence and
modality.
Hypothesis 3: Interaction Effects of Age and Mood
Our final hypothesis suggested that there would be an interaction effect of mood and age,
with the influence of sad mood stronger in younger than in older adults because of the
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 32
positivity effect. Our data did not support this hypothesis, and in fact, if there is any impact
from sad mood, the impact did not differ from age groups. This echoes with previous studies
demonstrating mood-congruence effects on memory and attention in older adults utilizing
either sad or anxious mood inductions (Knight et al., 2002, Fox & Knight, 2005, Lee &
Knight, 2007). It is true that older adults have age-related enhancements in managing the
surrounding emotional information, but these advantages in emotional well-being may be
attenuated when they are in a negative mood. This finding align with Charles’ (2010)
Strength and Vulnerability Integration Model, such that older adults’ age-related advantages
are less apparent when constrained in conditions where negative emotional experiences are
unavoidable. Although the effectiveness of our mood inductions is nowhere as distressing as
real-life events, we were able to demonstrate mood congruence effects on negative
interpretation bias for both age groups even under a relatively “low dosage” sad mood
condition. Therefore, despite low prevalence of depression among the older population, it
would be unwise to assume that older adults are immune to depression even when faced with
stressful life events, which usually triggers certain level of negative mood.
Hypothesis 4: The Role of Future Time Perspective
We were also unable to investigate the role of FTP directly because the FTP
manipulation did not appear to affect FTP scores. However, it is important to acknowledge
two things when discussing the effectiveness of our FTP manipulation. First, the FTP
measure was half as long as the original measure, and so it is possible that the measurement
was not sensitive to changes in FTP. Secondly, mood induction had an unexpected effect on
FTP, such that sad mood limited participants’ FTP regardless of age group. This procedural
issue limited our ability to interpret FTP findings; hence, we decided to drop this construct in
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 33
our analysis altogether.
However, this finding is inconsistent with previous studies demonstrating that
expanding FTP resulted in the absence of positivity effect among older adults (Kellough &
Knight, 2012). No manipulation check was performed in that study, so it was unclear whether
the manipulation was in fact effective. Additionally, we also found no effects of FTP
conditions on the interpretations. One explanation is that they utilized a relatively more
complex way of rating emotions in faces, whereas in this study, our simplified measure of
asking participants to circle an interpretation score may not have allowed us to detect such
differences.
We further examined the underlying premises of socioemotional selectivity theory
Carstensen et al., 2003), which posits that older adults have a limited future time perspective.
Strikingly, even comparing FTP of older and younger participants in the neutral mood
condition, we did not find any age differences in the level of FTP, which is inconsistent with
theoretical predictions as well as findings from previous studies (Lang & Carstensen, 2002;
Cate & John, 2007; Loeckenhoff et al., 2013, Thomas et al., 2007; Kellough & B. Knight,
2012). Again, our shortened- FTP measure may not have been sensitive to detect the
differences.
We then decided to compare the FTP scores reported in previous studies (Loeckenhoff
et al., 2013, Thomas et al., 2007; Kellough & B. Knight, 2012). Analysis indicated
consistently that our younger adult sample had FTP scores significantly lower than its
counterpart in their study, whereas FTP scores of our older adult sample were either
equivalent or lower than the other studies. Although doubling scores is not equivalent to
using the entire measure, this led us to believe that null findings on age differences are likely
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 34
due to the relatively “limited” FTP among our younger adult sample rather than a more
“expanded FTP” in our older adult sample. Yet no substantial differences were found in the
demographic variables, levels of depressive symptoms, and recruitment methods for younger
adults compared to Kellough and Knight’s (2012) study. Thomas and colleagues (2007) only
reported age, education, and recruitment method, which did not differ from ours. Our
younger sample differed from Lockenhoff and colleagues’ (2013) study in ethnicity
composition and the recruitment method. However, the differences could not explain why
there were also significant differences in the FTP scores compared to the other two studies.
This implied that there are individual differences in FTP, which is not simply a function of
age. Therefore, age differences in FTP should not be automatically assumed; rather, it is
critical to actually measure FTP in order to investigate the mechanisms of age difference.
Limitations
Limitations of this study include unbalanced demographic variables in our sample. There
were significant baseline differences in ethnicity, education, and depressive symptoms
between our older and younger samples. However, the Pearson correlation between these
demographic and outcome variables were not above .3, indicating that these variables had
little effect on participants’ interpretation of ambiguity. In addition, we only assessed for sad
and happy mood as part of our mood manipulation check. Although we did conduct a pilot
study and found that the procedure was specific to eliciting sad mood, given that it is still a
novel procedure, it would still be important to assess for other moods and variables
post-induction to ensure that mood induction had no other unintended effects.
Summary & Implications
Despite the limitations, our investigation contributed to the emotion, aging, and
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 35
interpretation bias literature in several ways. First of all, we investigated the role of age and
mood on the interpretation of emotionally ambiguous information concurrently, which not
only provides empirical data on the effects of age and mood separately but also the
interaction between age and mood. Secondly, the inclusion of distinct types of stimulus
allowed us to investigate the differential impact of age and mood by stimulus modality,
content, and emotional valence. The selection of faces and vignettes in the current study
enhanced the ecological validity of “interpretation bias” that often occur in real life. Thirdly,
this study demonstrated partial evidence for the mood- congruence effect on negative
interpretation bias for both older and younger adults. The effects were contingent upon
stimulus types, which highlighted the complicated nature of mood-congruence effects. Our
findings call for future studies investigating the circumstances under which age and mood
can affect individual’s interpretation bias.
Finally, our finding demonstrated a positive interpretation bias in older adults, which
raised an alternative explanation for why older adults frequently report fewer negative
interpersonal tensions (Birditt, Fingerman, & Almeida, 2005). In addition to actually
experiencing fewer negative encounters, it may be possible that older adults simply do not
perceive certain social situations as negative, whereas for the same interpersonal situations,
younger adults would. Given that the tendency of interpreting emotionally ambiguous
information is closely associated with well-being (Dearing & Gotlib, 2009; Butler &
Mathews, 1983; Gilboa-Schechtman, Foa, Vaknin, Marom, & Hermesh, 2008), this study
also helps explain why older adults have been found to experience higher levels of
well-being than younger adults in both cross-sectional (Kessler & Staudinger, 2009) and
longitudinal studies (Charles, Reynolds & Gatz, 2001; Carstensen et al., 2011). Therefore, in
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 36
addition to better emotion regulation skills, we argue that the appraisals of ambiguous
emotional information are more benign to begin with, which lead to lower levels of negative
affectivity and reduced the need to regulate emotions.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 37
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Appendix
Revised Interpretation Bias Questionnaire (IBQ)
1. You ask your doctor about your condition, and your doctor hasn’t responded
immediately. Why?
2. You call a good friend of yours and leave a message suggesting getting together later in
the week. A few days pass, and you haven’t heard from them. Why haven’t they returned
your call?
3. As you enter your doctor’s office, you saw the doctor looking at the computer screen
frowning. Why?
4. You are having a conversation with one of your friends. Your friend mentions a
gathering a mutual acquaintance is hosting next week. This is the first time you’ve heard
about the gathering. Why?
5. You’re walking down the street, and you see one of your friends coming the other way
with a group of people. You wave, but your friend doesn’t respond. Why?
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 49
Table 1
Demographic Measures by age and mood groups
Demographic
Age Group
Younger Older
Neutral Sad Neutral Sad
M SD M SD M SD M SD
Age (years) 19.94 1.09 19.85 2.11 73.08 8.59 73.74 6.16
Education (years) 14.44 1.36 14.17 1.81 16.76 3.44 16.52 2.71
CES-D 15.11 8.86 15.92 8.80 8.89 6.39 8.94 8.27
Sad Mood 1.47 1.80 2.18 2.01 .97 1.68 .74 1.24
Note: CES-D= Center for Epidemiologic Studies Depression Scale.
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 50
Table 2
Mean Interpretation scores by face type
Face Type
Age Group
Younger Older
Neutral Sad Neutral Sad
M SD M SD M SD M SD
Neutral .19 .55 . -.04 .75 .97 .63 .62 .79
Happy-Sad -.06 .97 -.68 1.09 -.05 .88 -.12 1.19
Happy-Angry -.01 .89 -.35 .99 -.47 .88 -.47 1.04
Happy 3.45 .47 3.03 1.05 3.59 .42 3.50 .56
Sad -3.30 .53 -3.03 .80 -3.20 .66 -3.29 .54
Angry -3.29 .57 -3.06 .82 -3.45 .45 -3.19 .95
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 51
Table 3
Total number and percentage of negative interpretations by age x mood group
Situation
Type
Age Group
Younger Older
Neutral Sad Neutral Sad
M SD M SD M SD M SD
Health-
related
Total Number 3.30 .75 3.59 .93 3.65 1.09 3.59 1.12
% of negative
interpretations
33.33 14.55 36.86 23.51 36.86 18.35 35.31 22.40
Interpersonal
- related
Total Number 3.47 .70 3.41 .95 3.34 1.07 3.31 .94
% of negative
interpretations
37.65 12.91 37.27 19.58 26.43 19.27 24.43 15.26
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 52
Table 4.
Mean valence of selected interpretations by situation type
Situation Type
Age Group
Younger Older
Neutral Sad Neutral Sad
M SD M SD M SD M SD
Health- related -.63 1.69 -.86 1.36 -.22 1.31 -.16 1.39
Interpersonal-
related
-.01 .72 .13 1.01 .51 .66 .47 .79
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 53
Figure 1. Example of ambiguous faces
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 54
Figure 2. Mean sadness ratings across time points by Age x Mood groups
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 55
Figure 3. Age x face type interactions for interpretation scores
*
*
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 56
Figure 4. Mood x face type interactions for interpretation scores
*
*
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 57
Figure 5. Main effect of age on the proportion of negative interpretations
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 58
Figure 6. Age x situation type for proportion of negative interpretations
AGE, MOOD, FTP & EMOTIONALLY AMBIGUOU INFORMATION 59
Figure 7. Main effect of age for the mean valence of selected interpretations
Abstract (if available)
Abstract
Previous studies demonstrated detrimental effects of negative interpretation bias, the tendency to interpret emotionally ambiguous information negatively. The current study aimed to understand how age, mood, and future time perspective impact interpretation bias. The positivity effect suggests that older adults would be less affected by sad mood. Seventy- six younger and 71 older adults were randomly assigned to sad or neutral mood inductions and completed ambiguous face and situation tasks to assess their tendency to interpret ambiguous information. Results demonstrated that older adults interpreted neutral faces more positively. They also generated more positive interpretations in ambiguous interpersonal situations and selected more positive interpretations as the most likely across situation type than younger adults. Sad mood led to negative interpretation bias with neutral expressions. No Age x Mood interaction effects emerged, suggesting that mood state impacted older and younger adults alike. These findings supported the positivity effect on appraisals among older adults but did not support the view that older adults were less impacted by sad mood. However, no main effects of future time perspective were found in the current study
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Juang, Christine
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The role of age, mood, and time- perspective on the interpretation of emotionally ambiguous information
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Master of Arts
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Psychology
Publication Date
12/03/2015
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355052
Document Type
Thesis
Format
application/pdf (imt)
Rights
Juang, Christine
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Tags
emotionally ambiguous information
interpretation bias
older adults
sad mood