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DOI: 10.1177/0146167213480188
2013 39: 636 originally published online 14 March 2013Pers Soc Psychol Bull
Nickola C. Overall and Matthew D. Hammond
Accurate : Depressive Symptoms and Daily Perceptions Within Intimate RelationshipsandBiased
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A longstanding debate involves whether depression produces
negatively biased thinking (Beck, 1967) or more realistic
and accurate judgments (Alloy & Abramson, 1979). Research
supports both positions. Focusing on interpersonal judg-
ments, for example, depressed people are less accurate in
recognizing emotion in facial expressions and overperceive
sadness and anger (Gilboa-Schechtman, Foa, Vaknin,
Marom, & Hermesh, 2008; Leppänen, 2006). However,
depressive symptoms are associated with greater accuracy in
analytically complex tasks that require integrating social
information, such as detecting motivated deception (Lane &
DePaulo, 1999) and avoiding the fundamental attribution
error (Yost & Weary, 1996).
Prior attempts to reconcile these inconsistencies have
focused on the different tasks or contexts that might explain
when depression is associated with bias versus accuracy
(e.g., Andrews & Thomson, 2009). In contrast, we draw
upon recent distinctions between two forms of accuracy—
directional bias and tracking accuracy (Fletcher & Kerr,
2010; Gagné & Lydon, 2004; West & Kenny, 2011)—to test
whether depressive symptoms are associated with both bias
and accuracy. Directional bias reflects the degree to which
judgments over- or undershoot some benchmark, such as
perceiving expressions as more negative than objective
ratings of expression tone. Tracking accuracy, in contrast,
indexes the degree to which perceivers accurately track
changes in the corresponding benchmark, such as detecting
when expressions become more or less negative during an
interaction.
The present research examined whether depressive symp-
toms were associated with directional bias and tracking accu-
racy by assessing daily perceptions of intimate partners’
commitment and behavior across a 3-week period. Using the
partners’ reported commitment and behavior as benchmarks,
we predicted that greater depressive symptoms would be
associated not only with (a) greater directional bias, including
underestimating the partner’s commitment and overestimat-
ing the partner’s negative behavior, but also (b) greater track-
ing accuracy, including more accurately detecting changes in
the partner’s commitment and behavior across days.1 We also
explored the consequences of directional bias and tracking
accuracy for relationship security and depressed mood.
480188PSPXXX10.1177/0146167213480188Person
ality and Social Psychology BulletinOverall and Hammond
1The University of Auckland, New Zealand
Corresponding Author:
Nickola C. Overall, The University of Auckland, Private Bag 92019,
Auckland 1142, New Zealand.
Email: n.overall@auckland.ac.nz
Biased and Accurate: Depressive
Symptoms and Daily Perceptions
Within Intimate Relationships
Nickola C. Overall1 and Matthew D. Hammond1
Abstract
Are depressive symptoms associated with more biased or more accurate interpersonal perceptions? Both members of
committed heterosexual couples (N = 78) reported on their perceptions of their partner’s commitment and behavior daily
across a 3-week period. Using the partner’s reports as the benchmark, participants who reported more depressive symptoms
not only underestimated their partner’s commitment and overestimated their partner’s negative behavior (greater directional
bias) but were also more accurate in tracking changes in their partner’s commitment and behavior across days (greater
tracking accuracy). More negative perceptions of the partner’s commitment and behavior was also associated with increases
in relationship insecurity and depressed mood, particularly when the partner also reported lower commitment and more
negative behavior. These results indicate that depressive symptoms are associated with both more accurate and more biased
interpersonal perceptions and suggest that more accurate detection and more biased magnification of interpersonal threat
has important implications for the maintenance of depressed mood.
Keywords
depression, depressive symptoms, bias, accuracy, relationship perceptions
Received June 19, 2012; revision accepted December 21, 2012
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Overall and Hammond 637
Bias and Accuracy Within Intimate
Relationships
Within intimate contexts, personal well-being and outcomes
depend on the actions and continued investment of the part-
ner (Kelley & Thibaut, 1978). Thus, individuals are moti-
vated to assess their partner’s commitment, and behavior
diagnostic of their partner’s evaluations, because of the
crucial outcomes associated with these judgments, including
acceptance and belonging versus rejection and dissatisfac-
tion (Overall, Fletcher, & Kenny, 2012). The resulting per-
ceptions have important consequences. When people
perceive their partner is committed and responsive, they feel
satisfied and secure in their relationship and constructively
cope with relationship difficulties. When people perceive
their partner as less committed and intentionally hurtful,
they experience chronic insecurities, lower satisfaction, and
react defensively to expected rejection (Murray & Holmes,
2009; Reis, Clark, & Holmes, 2004).
There are individual differences in the extent to which
people are biased and accurate when assessing their part-
ner’s sentiments and behavior. Dispositions that encompass
chronic relationship insecurity, like lower self-esteem and
higher attachment anxiety, are associated with perceiving
less regard and support than the actual regard and support
reported or shown by the partner (e.g., Collins & Feeney,
2004; Murray, Holmes, & Griffin, 2000). Intriguingly, as
with the inconsistent findings regarding depression, rela-
tionship insecurity is also associated with more accurate
perceptions of the partner’s thoughts and feelings (when
compared with the partner’s reported thoughts and feel-
ings) during relationship-threatening conflict discussions
(Simpson et al., 2011).
Overall et al. (2012) reconciled this contradictory pattern
by distinguishing between directional bias and tracking
accuracy. We use their study to illustrate how directional bias
and tracking accuracy is conceptualized and measured.
Overall et al. asked perceivers to judge how positively their
intimate partners regarded them at 14 time points during a
conflict discussion. To assess directional bias and tracking
accuracy, ratings of the actual regard reported by the partner
were also gathered at each time point. Using recent statistical
procedures by West and Kenny (2011), directional bias was
indexed by the mean difference between perceptions of the
partner’s regard and the partner’s actual regard across the
discussion. Perceptions of the partner’s regard were, on aver-
age, lower than the partner’s actual regard, indicating that
perceivers generally underestimated their partner’s regard.
Tracking accuracy was indexed by the association (i.e., cor-
relation) between perceptions of the partner’s regard and the
partner’s actual regard across the discussion (independent of
mean-level differences). This association was strong and
positive indicating that perceivers accurately tracked the ups
and downs of their partner’s changing regard across the
discussion.
Overall et al. (2012) also examined whether levels of
directional bias and tracking accuracy varied according to
how secure individuals were in their relationship. As pre-
dicted, greater insecurity was associated with greater under-
estimation of the partner’s regard (greater directional bias).
More insecure women also more accurately tracked changes
in regard, specifically detecting when their partner’s regard
became more negative during the discussion (tracking accu-
racy). This pattern demonstrates that individuals can be both
biased and accurate; in this case, underestimating their part-
ner’s regard but accurately tracking changes in their part-
ner’s regard. The results also indicate that relationship
insecurity is associated with both greater directional bias and
greater tracking accuracy.
This mix of directional bias and tracking accuracy makes
sense when considering the costs associated with overesti-
mating the partner’s love and acceptance, including the
partner’s dissatisfaction, potential rejection, and failure to
take remedial action (Haselton & Buss, 2000). Intimates
who are relatively cautious in their judgments and vigilantly
monitor signs that their partner’s commitment is waning
should avoid the costs of overestimating acceptance and be
more able to detect possible rejection (Tooby & Cosmides,
1996). Moreover, those whose relationship histories amplify
expectations of rejection should be most alert to how they
are valued (Murray & Holmes, 2009). Accordingly, insecu-
rity about the partner’s regard should motivate more cau-
tious assessment (greater directional bias) and vigilant
monitoring (greater tracking accuracy) of the partner’s cur-
rent acceptance.
Depressive Symptoms and
Perceptions Within Intimate
Relationships
The current research investigated whether depressive symp-
toms are similarly associated with greater directional bias
and enhanced tracking accuracy by comparing perceptions
of the partner’s sentiments and behavior to the sentiments
and behavior reported by the partner. Specifically, we tested
the degree to which individuals with elevated depressive
symptoms were biased in their perceptions of their partner’s
commitment and behavior, and the degree to which they
accurately tracked changes in their partner’s commitment
and behavior across time. We focused on these judgments
because perceptions of the partner’s commitment and behav-
ior are relevant to the interpersonal difficulties associated
with depressive symptoms.
Depressive symptoms are associated with a range of
behaviors that damage relationship well-being, such as
excessive and hostile bids for support and more caustic reac-
tions to conflict (e.g., Davila, Bradbury, Cohan, & Tochluk,
1997; Potthoff, Holahan, & Joiner, 1995; see Rehman,
Gollan, & Mortimer, 2008). Relationship difficulties and
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638 Personality and Social Psychology Bulletin 39(5)
dissatisfaction, in turn, increase depressive symptoms over
time (e.g., Beach, Katz, Kim, & Brody, 2003). Perceptions of
the partner undoubtedly play a central role in these recipro-
cal links. Negative relationship evaluations are intricately
tied to perceptions of the partner’s commitment, including
behavior that signals the partner’s regard and future respon-
siveness (Murray & Holmes, 2009; Overall & Fletcher,
2010; Reis et al., 2004). More negative perceptions of the
partner’s regard and conduct, in turn, triggers defensive and
destructive relationship behavior (Murray & Holmes, 2009;
Reis et al., 2004).
Interpersonal theories of depression (and associated evi-
dence) also suggest that depressive symptoms should create
biased partner perceptions (Coyne, 1976). Depressive symp-
toms are associated with seeking not only reassurance (Starr
& Davila, 2008) but also self-verifying negative information
(Swann, Wenzlaff, Krull, & Pelham, 1992). This unfortunate
combination produces doubts about the authenticity of others’
care and support, which sparks a destructive cycle whereby
consequent hostilely toned reassurance seeking elicits rejec-
tion, which consolidates negative interpersonal expectations
and increases the need for further reassurance (see Joiner &
Timmons, 2009). Accordingly, individuals with elevated
depressive symptoms are likely to actively gather feedback
regarding their partner’s commitment but underestimate that
commitment. They should also be attuned to potential rejec-
tion, and thus perceive the tone and meaning of their partner’s
behavior more negatively than is justified.
For these reasons, we predicted that depressive symp-
toms would be associated with a negative pattern of
directional bias, including underestimating the partner’s
commitment and overestimating the partner’s negative
behavior (when comparing perceptions to the actual com-
mitment and behavior reported by the partner). This predic-
tion is consistent with biases demonstrated outside the
relationship domain. Depressive symptoms are associated
with elaborating or ruminating on the causes and conse-
quences of negative events, and being unable to disengage
processing of negative personally relevant information (see
Gotlib & Joormann, 2010). The predicted pattern is also
consistent with theoretical models that propose depressed
mood arises in response to social loss and adaptively trig-
gers sensitivity toward social threat, avoidance of social
risks, and sustained problem analysis (i.e., rumination) to
facilitate the resolution of social dilemmas and minimize
the possibility of social exclusion (Allen & Badcock, 2003;
Andrews & Thomson, 2009). In support, depression is asso-
ciated with greater attention to socially threatening informa-
tion (e.g., Mathews, Ridgeway, & Williamson, 1996) and
linked with more cautious deliberation of social risks and
less willingness to take those risks (e.g., Badcock & Allen,
2003; Pietromonaco & Rook, 1987).
However, greater vigilance regarding social threat should
not only produce more directional bias in relationship percep-
tions but also more accurate detection and careful monitoring
of interpersonal threat—that is, tracking accuracy. Accordingly,
research outside the relationship domain has found that depres-
sive symptoms are associated with greater motivation to under-
stand others’ attitudes and behavior, integrating more
information when generating impressions, and greater atten-
tion and sensitivity to diagnostic information (e.g., Edwards,
Weary, von Hippel, & Jacobson, 2000; Gleicher & Weary,
1991). Depressive symptoms are also associated with more
accurately distinguishing between genuine versus deceptive
communications from others (Lane & DePaulo, 1999). Thus,
in addition to producing directional bias, depressive symptoms
should activate more accurate tracking of changes in the part-
ner’s commitment and behavior, and in particular more sensi-
tive detection of reductions in the partner’s commitment and
increases in the partner’s negative behavior.
Prior research investigating the links between depressive
symptoms and perceptions of intimate partners do not speak
to our predictions. During couples’ discussions of a relation-
ship or personal difficulty, depressive symptoms have been
associated with lower (Gadassi, Mor, & Rafaeli, 2011; Papp,
Kouros, & Cummings, 2010) and greater (Papp et al., 2010)
accuracy of the partner’s thoughts and feelings, or have not
been associated with accuracy at all (Thomas, Fletcher, &
Lange, 1997). The meaning of these results is hard to unravel
because the methods used have not assessed the type or
direction of potential inaccuracy. Gadassi et al. (2011), for
example, asked independent coders to rate the similarity
between participants’ descriptions of their partners’ thoughts
and feelings during a conflict and the descriptions provided
by the partner (Study 1) and calculated the absolute differ-
ence between individuals’ daily perceptions and their part-
ners’ reported feelings across 21 days (Study 2). For women,
depressive symptoms were associated with lower coded
similarity in the discussion (Study 1) and greater discrepancy
in perceptions across days (Study 2). However, ratings of
similarity and absolute difference scores do not provide any
information about the direction of any bias, such as whether
perceptions are more or less negative (directional bias) than
the partner’s actual thoughts and feelings. In addition, focus-
ing on judgments made at one time point (Papp et al., 2010)
or collapsing similarity assessments across multiple time
points (Gadassi et al., 2011; Thomas et al., 1997) does not
allow an examination of whether individuals are able to
detect changes in their partner’s thoughts, feelings, and
behavior (tracking accuracy).
In the current research, perceptions of the partner’s com-
mitment and behavior, and corresponding benchmark ratings
by the partner, were gathered daily for 3 weeks. We simulta-
neously assessed directional bias and tracking accuracy, and
predicted that greater depressive symptoms would be associ-
ated not only with (a) greater directional bias, including
underestimating the partner’s commitment and overestimat-
ing the partner’s negative behavior, but also (b) greater track-
ing accuracy, including more accurately detecting changes in
the partner’s commitment and behavior across days.
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Overall and Hammond 639
The Consequences of Directional
Bias and Tracking Accuracy
The predicted pattern of directional bias and tracking accu-
racy should have important consequences for how secure
people feel in their relationships. Research by Murray and
colleagues suggests that optimistic perceptions are neces-
sary to maintain a sense of conviction and security within
relationships (e.g., Murray et al., 2011; Murray, Holmes, &
Griffin, 1996). People who perceive their partner in a posi-
tively biased fashion maintain greater relationship satisfac-
tion, experience less conflict, and report fewer doubts about
their relationship. Conversely, when people possess more
negatively biased views of their partner, they experience less
trust and security and poorer relationship quality (also Miller
& Rempel, 2004). Thus, the directional biases we expected
to be associated with depressive symptoms, including under-
estimating the partners’ commitment and overestimating
negative partner behavior, should lead to greater doubts and
insecurities about the relationship.
This prediction captures central elements of the interper-
sonal cycle that sustains the relational difficulties associated
with depression (Coyne, 1976; Joiner & Timmons, 2009);
doubts about the partner’s care and support trigger reassur-
ance seeking, biased perceptions of the partner’s responsive-
ness means any reassurance actually delivered by the partner
fails to reassure, and resulting insecurity escalates reassur-
ance seeking, which pushes the partner away. Joiner (2000)
also outlined that this vicious cycle propagates interpersonal
difficulties and maintains depression. As already noted,
lower relationship quality predicts increases in depressive
symptoms (e.g., Beach et al., 2003). Perceiving lower part-
ner commitment and more negative partner behavior should
also lead to greater depressed mood. Thus, the biases associ-
ated with depressive symptoms are likely to promote and
maintain depressed mood.
Moreover, these damaging effects might be more pro-
nounced when intimates accurately detect lower commit-
ment and more negative partner behavior. Although accurate
knowledge of each other can enhance partners’ felt under-
standing, accuracy can be costly in relationship-threatening
situations. Simpson, Oriña, and Ickes (2003) found that
greater accuracy when the partner’s thoughts and feelings
were threatening for the relationship reduced relationship
closeness. Similarly, in daily life, accurate detection of
declining commitment and growing negativity is likely to
generate relationship insecurity and depressed mood.
Accordingly, underestimating partner commitment and over-
estimating negative partner behavior should foster depressed
mood and relationship insecurity, and this should be particu-
larly the case when these biases accurately track reality—
that is, in the context of actual drops in partner commitment
and increases in negative partner behavior.
To test these ideas, participants were asked to report their
daily feelings of relationship insecurity and depressed mood.
We predicted that more negative perceptions of the partner’s
commitment and behavior would be associated with increases
in relationship insecurity and depressed mood, and these del-
eterious effects would be even more pronounced when nega-
tive perceptions were more accurate—that is, on days that
the partner’s commitment was actually low and the partner
was actually behaving more negatively.
Current Research
To test whether depressive symptoms were associated with
directional bias and tracking accuracy, both partners of com-
mitted heterosexual couples completed a 3-week daily diary
reporting on their own and perceptions of their partner’s
commitment and behavior. Comparing individuals’ percep-
tions of their partner’s commitment and behavior to the
commitment and behavior reported by the partner, we
hypothesized that depressive symptoms would be associated
with both (a) greater directional bias, including underesti-
mating the partner’s commitment and overestimating the
partner’s negative behavior, and (b) greater tracking accu-
racy, including more sensitive detection of reductions in the
partner’s commitment and increases in the partner’s nega-
tive behavior across days.
To test whether the expected pattern of bias and accuracy
cultivated insecurity and depressed mood, daily feelings of
relationship insecurity and depressed mood were gathered.
We predicted that more negative perceptions of the partner’s
commitment and behavior would be associated with increases
in relationship security and depressed mood, and these dam-
aging effects would be more pronounced when negative per-
ceptions were accurate—that is, when the partner also
reported lower commitment and more negative behavior.
Finally, we assessed other factors prior research has tied
to biased relationship perceptions to ensure these variables
were not responsible for any links between depressive symp-
toms and bias and accuracy. We focused on the three most
well-established factors that influence bias within intimate
relationships. First, people tend to assume close others eval-
uate and behave in similar ways to the self (assumed similar-
ity or projection; Kenny & Acitelli, 2001). Second, people
who are happier in their relationships possess more posi-
tively biased perceptions, and vice versa (Fletcher & Kerr,
2010). Third, insecurity in the partner’s acceptance, often
indexed by low self-esteem, produces more negatively
biased perceptions and greater tracking accuracy (e.g.,
Murray & Holmes, 2009; Overall et al., 2012). We predicted
that depressive symptoms would remain significantly associ-
ated with directional bias and tracking accuracy when con-
trolling for these alternative explanations.
Method
Participants
Seventy-eight heterosexual couples who replied to cam-
pus wide advertisements were reimbursed $45NZD for
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640 Personality and Social Psychology Bulletin 39(5)
participating. Participants were on average 22.44 years
old (SD = 4.81) involved in serious romantic relation-
ships (43.6% married or cohabitating) that were on aver-
age 2.57 years in length (SD = 1.96).
Materials and Procedure
During an initial session, couples completed the scales
described below and were given detailed instructions for
completing a 3-week daily diary.
Depressive Symptoms were assessed with the Centre for
Epidemiological Studies Depression Scale (CES-D;
Radloff, 1977) designed for use with nonclinical samples.
The 20-item scale assesses the frequency of symptoms
experienced during the past week (e.g., “I felt depressed,”
“I felt that everything I did was an effort”). Responses
ranged from 0 = rarely or none of the time (less than 1 day)
to 3 = most or all of the time (5-7 days) and were scored
and summed so that higher scores (out of 60) indicate the
presence of more symptoms. Although the CES-D is not a
diagnostic tool, scores ≥ 16 are typically considered evi-
dence of meaningful depressive symptoms. Table 1 dis-
plays descriptive statistics for this sample; 41% of men
and 42% of women scored ≥ 16. As is typical, women
reported higher levels of depressive symptoms, but there
were no significant gender differences in the effects of
depressive symptoms tested below.
Relationship and Self-Evaluations. Participants also completed
the Rosenberg’s (1965) 10-item Self-Esteem Scale (e.g., “On
the whole, I am satisfied with myself”; 1 = not at all, 7 =
extremely), and the 7-item Perceived Relationship Quality
Components Scale (Fletcher, Simpson, & Thomas, 2000) to
assess relationship quality (e.g., “How satisfied are you with
your relationship?” 1 = not at all, 7 = extremely). These
scales were reliable and correlated with depressive symp-
toms in expected ways (see Table 1).
Daily Diary
At the end of the day for the following 21 days, participants
completed a web-based diary record reporting on their
relationship-related feelings and behavior. On average,
participants completed 19.3 diary entries. To assess bias
and accuracy, each diary record asked participants to report
on (a) their own commitment and behavior and (b) percep-
tions of their partner’s commitment and behavior that day
(order counterbalanced across couples). Participants also
reported their feelings of relationship insecurity and
depressed mood.
Commitment. Single items assessed participants’ own com-
mitment (“I was committed to our relationship”) and their
perceptions of their partner’s commitment (“My partner
was committed to our relationship,” 1 = not at all, 7 =
extremely).
Negative Behavior. Four items assessed participants’ own
hurtful and neglectful behavior (e.g., “I acted in a way that
could be hurtful to my partner,” “I was critical or unpleas-
ant toward my partner,” “I wanted to be left alone and/or
spend less time with my partner,” “I withdrew from my
partner and did my own thing,” 1 = not at all, 7 = extremely),
and four items assessed positive and responsive relation-
ship behavior (“I was affectionate and loving toward my
partner,” “I was supportive to my partner,” “I shared and
discussed my feelings and opinions with my partner,” “I
tried to maintain or improve the quality of our relation-
ship”). These items capture the range of destructive and
constructive responses shown to be important within daily
relationship interactions (Rusbult, Verette, Whitney, Slovik,
& Lipkus, 1991). The positive items were reverse-scored
and the eight items were averaged to provide an overall
index of behavior (α = .83), with greater scores reflecting
more negative behavior. The same eight items were
reworded and scored to assess perceptions of the partner’s
negative behavior (e.g., “My partner was critical or unpleas-
ant toward me,” α = .87).
Relationship Insecurity. Participants were asked to rate three
items according to how they felt and thought that day, includ-
ing “I worried about our relationship,” “I felt confident that
my partner loves me” (reverse-coded), and “I felt insecure
about our relationship” (1 = not at all, 7 = extremely). These
items were averaged to assess participants’ feelings of rela-
tionship insecurity (α = .81).
Table 1. Descriptive Statistics and Correlations Across Questionnaire Measures.
Women Men Gender differences Correlations
M (SD)αM (SD)αt d 1 2 3
1. Depressive symptoms 18.10 (10.68) .92 15.23 (7.05) .84 2.25*** .32 .25*** −.61*** −.39***
2. Self-esteem 5.10 (1.18) .91 5.38 (0.95) .86 −2.02*** −.23 −.65*** .24*** .25***
3. Relationship quality 6.12 (0.63) .76 6.12 (0.61) .83 0.02 .00 −.20* .16 .34***
Note: Possible scores range from 0 to 60 for depressive symptoms and 1 to 7 for self-esteem and relationship quality. Gender differences are tested using
paired-samples t tests and effect sizes are indexed by Cohen’s d corrected for the dependence between means. Correlations above the diagonal are for
women; correlations below the diagonal are for men. Bold correlations on the diagonal represent correlations across partners.
*p < .10. ***p < .05.
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Overall and Hammond 641
Depressed Mood. Depressed mood was assessed with items
shown to reliably detect daily changes in depressed mood
(Cranford et al., 2006). Individuals rated how much they had
felt “sad,” “hopeless,” and “discouraged” that day (1 = not at
all, 7 = extremely; α = .87).
Results
The results are organized into three sections. The first sec-
tion presents baseline models assessing directional bias and
tracking accuracy. The second section examines the links
between depressive symptoms and bias and accuracy, and
considers alternative explanations for the effects. The final
section explores the consequences of bias and accuracy for
feelings of relationship insecurity and depressed mood.
Are Perceptions of the Partner’s Commitment
and Behavior Biased or Accurate?
We used West and Kenny’s (2011) Truth and Bias Model to
test the degree to which perceptions of the partner’s daily
commitment and behavior were biased and accurate. The
person making the judgment of their partner’s commitment
and behavior is referred to as the perceiver and their judg-
ments are compared with their partner’s own ratings of com-
mitment and behavior. Our data have a nested structure, with
perceivers and partners multiple ratings of commitment and
behavior across the 21 days (Level 1) nested within dyad
(Level 2). Accordingly, we used multilevel modeling meth-
ods for analyzing repeated-measures data within dyads
(Kenny, Kashy, & Cook, 2006). Using perceptions of com-
mitment to demonstrate, we modeled the associations across
the perceivers’ judgments of their partner’s commitment and
the partners’ actual reported commitment (the Level 1
repeated-measures variables) to test the degree to which
perceptions of the partner’s commitment were biased and
accurate (see Equation 1).
Jij = b0j + b1j (partner j’s actual
commitment on day i) + eij.
In this equation, the judgment of perceiver j of his or
her partner’s commitment (J) on a particular day (i) is a
function of perceiver j’s intercept (b0), the effect of the
partner’s actual commitment for that day (b1), and an error
term (eij) representing random error and all other unmea-
sured biases that influence the perceiver’s judgments. As
specified by West and Kenny (2011), the perceivers’ judg-
ments of the partners’ commitment (the outcome variable)
were centered on the partners’ actual commitment by sub-
tracting the grand mean of partners’ commitment from the
perceivers’ judgment each day. This centering strategy
means that the intercept represents the difference between
the partners’ commitment and the perceivers’ perceptions
of that commitment, and specifies the direction of that bias
(directional bias). A negative intercept would indicate that
perceivers were underestimating their partner’s commit-
ment, whereas a positive intercept would indicate perceiv-
ers were overestimating.
The predictor variable (partner’s actual commitment) was
grand-mean centered across dyads and time points and its
coefficient assesses tracking accuracy—the degree to which
perceiver’s judgments were influenced by the partner’s actual
commitment. A positive coefficient would indicate that per-
ceivers were accurately tracking the degree to which ttheir
partner’s commitment varied across the 21-day diary period.
All analyses were conducted using the MIXED procedure
in SPSS 19. We first used a no-intercept model to simultane-
ously estimate the parameters from Equation 1 for men and
women separately. To test whether the effects significantly
differed across men and women, in a second model, we esti-
mated the fixed effects pooled across men and women, and
tested for gender differences by modeling the main and inter-
action effects of gender (–1 women, 1 men; see Kenny et al.,
2006). Both models allowed the error variances to differ for
men and women and allowed errors for a given time to be
correlated. Both models also allowed directional bias (b0j)
and tracking accuracy (b1j) to vary by male and female per-
ceivers for each dyad (i.e., be random variables) and these
effects to covary within and across dyad members. See
Overall et al. (2012) for associated SPSS syntax.
The results from both models are shown in Table 2. Because
there were no statistically significant gender differences in
directional bias or tracking accuracy (see column marked
Gender Diff. t), we attend to the fixed effects pooled across
men and women shown in the final columns of Table 2. The
average intercept assessing directional bias did not signifi-
cantly differ from zero, indicating that on average, men and
women were not biased in their perceptions of their partner’s
commitment across days. The significant coefficient testing
accuracy indicated that perceivers also accurately tracked
their partner’s commitment across days. Analogous models
examining perceptions of the partner’s negative behavior (see
bottom half of Table 2) also revealed that, on average, perceiv-
ers were not significantly biased and were very accurate in
tracking changes in their partner’s behavior.
Table 3 displays tests of whether bias and accuracy varied
significantly across perceivers. Although on average direc-
tional bias did not differ from zero, there was significant vari-
ation in the degree to which women and men perceivers were
biased in perceptions of their partner’s commitment and
behavior. Similarly, some perceivers were more accurate than
others. The covariances presented in Table 3 also suggested
that women perceivers who were more biased (underestimat-
ing commitment or overestimating negative behavior) also
demonstrated greater tracking accuracy. Directional bias and
tracking accuracy did not significantly covary across partners
with one exception: the more one dyad member under- or
overestimated the negativity of their partner’s behavior, the
less the partner demonstrated the same directional bias.
(1)
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642 Personality and Social Psychology Bulletin 39(5)
In sum, on average, perceivers demonstrated substantial
accuracy in tracking changes in their partner’s commitment
and behavior across days, and did not tend to under- or over-
estimate their partner’s commitment or negative behavior.
However, directional bias and tracking accuracy signifi-
cantly varied across perceivers. The significant variation in
bias and accuracy is important because it indicates that dif-
ferences across perceivers, such as levels of depressive
symptoms, might predict the degree to which perceivers are
biased and accurate.
Are Depressive Symptoms Associated With
Bias and Accuracy?
To test whether perceivers’ depressive symptoms pre-
dicted bias and accuracy, CES-D scores (standardized to
aid interpretation of parameter estimates) were entered as
a predictor of the between-person variability in directional
bias and tracking accuracy (each parameter estimated by
Equation 1). In these analyses, the Level 1 intercept (mod-
eling directional bias) and slope (modeling tracking accu-
racy) were treated as dependent variables predicted by
individual differences in depressive symptoms modeled at
Level 2 (see Equations 2 and 3).
b0j = B00 + B01 (depressive symptoms) + u0j.
b1j = B10 + B11 (depressive symptoms) + u1j.
Equation 2 examines the effect of depressive symptoms
on directional bias (b0j), where B00 represents the Level 2
intercept reflecting average levels of directional bias across
Table 2. Directional Bias and Tracking Accuracy of Perceptions of the Partner’s Daily Commitment and Negative Behavior.
Directional bias and
tracking accuracy
Women perceivers Men perceivers Pooled across men and women
B t r B t r Gender Diff. t B t r
Partner’s commitment
Directional bias .04 0.42 .05 −.14 −1.55 −.17 −1.58 −.05 −0.73 −.09
Tracking accuracy .22 3.94**** .56 .27 6.20**** .75 0.71 .25 6.99**** .70
Partner’s negative behavior
Directional bias −.01 −0.08 −.01 −.05 −0.68 −.08 −0.34 −.03 −0.90 .11
Tracking accuracy .79 19.62**** .93 .70 18.83**** .92 −1.62 .75 28.18**** .94
Note: Fixed effects pooled across men and women are from models estimating the fixed effects constrained to be equal across men and women and test-
ing whether the effects significantly differed by estimating the main and interaction effects of gender (shown in column marked Gender Diff. t). Directional
bias and tracking accuracy did not significantly differ across men and women. Approximate effect sizes were computed using Rosenthal and Rosnow’s
(2007) formula: r = √(t2 / t2 + df). Degrees of freedom for each effect varied from 30.20 to 80.95.
****p < .01.
Table 3. Variances and Covariances of Directional Bias and Tracking Accuracy of Perceptions of the Partner’s Commitment and Negative
Behavior.
Variances and covariances
Partner’s commitment Partner’s negative behavior
Women perceivers Men perceivers Women perceivers Men perceivers
Estimate Wald ZEstimate Wald ZEstimate Wald ZEstimate Wald Z
Variances in bias and accuracy
Directional bias .53 5.36**** .56 5.60**** .37 5.11**** .43 5.58****
Tracking accuracy .09 2.61**** .04 1.84*** .06 2.81**** .06 3.66****
Within-person covariance
Directional bias and tracking
accuracy
−.09 −2.34**** −.02 −0.64 .05 1.91** .01 0.57
Across-partner covariance
Directional bias and
partner’s directional bias
.14 1.73 .14 1.73 −.27 −4.22**** −.27 −4.22****
Tracking accuracy and
partner’s tracking accuracy
−.00 −0.18 −.00 −0.18 .01 0.08 .01 0.08
Directional bias and
partners’ tracking accuracy
.02 0.48 −.01 −0.15 −.02 −0.69 .01 0.40
Note: Tests of variances are one-tailed (see Kenny, Kashy, & Cook, 2006).
**p < .06. ***p < .05.****p < .01.
(2)
(3)
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Overall and Hammond 643
perceivers, B01 is a coefficient testing whether perceivers’
depressive symptoms predict levels of directional bias, and
u0j represents individual variation in bias. We predicted that
greater depressive symptoms would be associated with more
negative directional bias when perceiving commitment (i.e.,
underestimation of the partner’s commitment) and positive
directional bias when perceiving negative behavior (i.e.,
overestimation of the partner’s negative behavior).
Equation 3 also gives the cross-level interaction between
accuracy and perceivers’ depressive symptoms, which
assesses whether tracking accuracy varied according to lev-
els of depressive symptoms. In this equation, the person’s
slope coefficient b1j or tracking accuracy is modeled as a
function of the main effect of accuracy (B10), the moderating
effect of depressive symptoms on accuracy (B11), and an
error term allowing for variation in slopes across perceivers
(u1j). We predicted that greater depressive symptoms would
be associated with greater tracking accuracy of both the part-
ner’s commitment and behavior.
Table 4 displays the results testing whether depressive
symptoms were associated with directional bias and tracking
accuracy when perceiving the partner’s commitment (shown
in left half of Table 4) and negative behavior (right half of
Table 4). As before, the fixed effects did not significantly dif-
fer across men and women (see column marked Gender Diff.
t, ps = .34-.95) and so we attend to and present the effects
pooled across men and women. As predicted, participants
who reported greater depressive symptoms demonstrated
both greater bias and greater tracking accuracy in their per-
ceptions of their partner’s commitment and behavior.
The impact of depressive symptoms on perceptions of
commitment are shown in Figure 1 where the predicted val-
ues of perceptions of the partner’s commitment are plotted at
low (−1 SD) and high (+1 SD) levels of the partner’s actual
commitment (the predictor testing accuracy) for perceivers
who reported low (−1 SD) versus high (+1 SD) levels of
depressive symptoms. Recall that perceivers’ judgments of
the partner’s commitment (on the y axis) are centered on
the partners’ actual commitment, so zero represents no
directional bias, positive values indicate overestimating
commitment, and negative values indicate underestimating
commitment (see key on right side of Figure 1). The slopes
across low versus high levels of partner’s actual commitment
(on the x axis) demonstrate tracking accuracy for perceivers
high (top slope in Figure 1) versus low (bottom slope in
Figure 1) in depressive symptoms.
As predicted, perceivers with high levels of depressive
symptoms tracked changes in their partner’s commitment
across the 21 days more accurately (b = .30, t = 6.40, p <
.001) than perceivers low in depressive symptoms (b = .15,
t = 2.98, p < .01). However, Figure 1 also highlights that this
pattern occurs because perceivers high in depressive symp-
toms were more sensitive to drops in their partner’s commit-
ment. On days when the partner’s actual commitment was
high (see right side of Figure 1), there was no significant
difference in the perceptions of participants low versus high
in depressive symptoms (b = −.09, t = −1.25, p = .22). In
contrast, on days when the partner’s actual commitment was
low (left side of Figure 1), perceivers high in depressive
symptoms underestimated their partner’s commitment (i.e.,
judgments well below zero) whereas perceivers low in
Table 4. The Effects of Depressive Symptoms on Directional Bias and Tracking Accuracy of Perceptions of the Partner’s Commitment
and Negative Behavior.
Effect of depressive
symptoms
Partner’s commitment Partner’s negative behavior
B t r Gender Diff. t B t r Gender Diff. t
Directional bias −0.18 −2.67**** .23 .06 0.10 2.33*** .28 .86
Tracking accuracy 0.07 2.13*** .28 .86 0.09 3.01**** .28 .96
Note: Results are from models estimating the fixed effects pooled across men and women and testing whether the effects significantly differed across men
and women by estimating the main and interaction effects of gender (shown in column marked Gender Diff. t). The effects of depressive symptoms did
not differ across men and women. Approximate effect sizes were computed using Rosenthal and Rosnow’s (2007) formula: r = √(t2 / t2 + df). Degrees of
freedom for each effect varied from 54.23 to 123.13.
***p < .05. ****p < .01.
1.0 Low Depressive Symptoms (–1 SD)
0.2
0.4
0.6
0.8 High Depressive Symptoms (+1 SD)
above0=
overesmate
-0.6
-0.4
-0.2
0.0 0=no bias
below0=
underesmate
Percepons of Partner's Commitment
-1.0
-0.8
Partner’s Actual
Commitment Low (–1 SD)
Partner’s Actual
Commitment High (+1 SD)
Figure 1. The effect of depressive symptoms on perceptions of
partner’s daily levels of commitment across a 21-day period.
Note: Zero represents no directional bias (perceivers’ judgments match
the partner’s commitment at the mean level), positive values indicate
perceivers overestimate the partner’s commitment, and negative values
indicate perceivers underestimate the partner’s commitment. Slopes across
low versus high partner’s actual commitment represent tracking accuracy.
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644 Personality and Social Psychology Bulletin 39(5)
depressive symptoms did not (b = −.27, t = −3.14, p < .01).
This pattern indicates that perceivers with greater depressive
symptoms accurately detected when their partner’s commit-
ment waned across the diary period, but then overestimated
these drops in their partner’s commitment.
The impact of depressive symptoms on perceptions of the
partner’s behavior demonstrated a corresponding pattern.
Shown in Figure 2, perceivers with high levels of depressive
symptoms tracked changes in their partner’s behavior across
the 21 days more accurately (b = .62, t = 12.57, p < .001)
than perceivers low in depressive symptoms (b = .43, t =
9.07, p < .001). However, the key differences between per-
ceivers high versus low in depressive symptoms occurred
when the partner’s negative behavior was high. On days
when the partner reported low levels of negative behavior
(see left side of Figure 2), there was no difference in the
judgments of perceivers low versus high in depressive symp-
toms (b = .03, t = 0.49, p = .62). In contrast, on days when the
partner reported high levels of negative behavior (left side of
Figure 2), perceivers high in depressive symptoms reported
much greater levels of negative behavior (i.e., biased judg-
ments well above zero) whereas perceivers low in depressive
symptoms did not (b = .25, t = 3.80, p < .01). Thus, perceiv-
ers with greater depressive symptoms accurately detected
when their partner’s negative behavior increased but then
exaggerated those increases.
Alternative Explanations
Own Commitment and Behavior. Consistent with assumed sim-
ilarity or projection processes (Kenny & Acitelli, 2001), per-
ceptions of the partner’s commitment and behavior is likely
to be influenced by individuals’ own commitment and
behavior. We reran all analyses controlling for perceivers’
own daily commitment and behavior. Although own com-
mitment (B = .54, t = 15.74, p < .001) and behavior (B = .73,
t = 31.46, p < .001) were strongly related to the correspond-
ing judgments of the partner, depressive symptoms were not
associated with levels of projection when judging the part-
ner’s commitment (B = −.04, t = −1.13, p = .26) or behavior
(B = −.03, t = −1.21, p = .23), and controlling for projection
did not eliminate the interactions shown in Figures 1 (B =
.06, t = 2.19, p < .05) and 2 (B = .04, t = 1.96, p = .05).
Relationship Quality. Depressive symptoms were also associ-
ated with lower relationship quality (see Table 1), and lower
relationship quality was associated with more positive judg-
ments of partner commitment (B = .51, t = 5.38, p < .001)
and more negative perceptions of partner behavior (B = −.36,
t = −4.99, p < .001). Relationship quality did not predict
accuracy, however, and controlling for relationship quality
did not alter the pattern or associated effects shown in Fig-
ures 1 and 2.
Relationship Insecurity. Additional analyses also demon-
strated that the results were not a product of chronic insecu-
rity regarding acceptance (indexed by low self-esteem;
Murray & Holmes, 2009) or more specific daily feelings of
relationship insecurity. Despite being strongly correlated
with depressive symptoms (see Table 1), self-esteem did
not predict bias and accuracy or alter any of the effects
shown in Table 4, and Figures 1 and 2. Daily feelings of
relationship insecurity were associated with directional
bias (B = −.45, t = −10.46, p < .001) and tracking accuracy
(B = .04, t = 2.12, p = .03) in perceiving commitment (in the
same manner depicted in Figure 1) as well as greater bias in
perceiving the partner’s negative behavior (B = .48, t =
27.53, p < .001). Nonetheless, depressive symptoms con-
tinued to significantly predict greater bias (B = −.21 and
.15, t > 2.95, p < .01) and tracking accuracy (B = .08 and
.07, t > 2.35, p < .05) for both commitment and negative
behavior (respectively).
Do Negative Relationship Perceptions Foster
Relationship Insecurity and Depressed Mood?
We predicted that the mix of directional bias and tracking
accuracy demonstrated by individuals with elevated depres-
sive symptoms would foster relationship insecurity and cul-
tivate depressed mood. To test this, we adopted similar
multilevel modeling methods for analyzing repeated-mea-
sures data within dyads (Kenny et al., 2006). Using percep-
tions of the partner’s commitment and relationship insecurity
to illustrate, we regressed perceiver’s relationship insecurity
on (a) perceiver’s relationship insecurity the prior day, so
that any significant effects represented residual change (i.e.,
increases or decreases relative to prior levels) in insecurity,
1.0 Low Depressive Symptoms(–1 SD)
High Depressive Symptoms(+1 SD)
0.2
0.4
0.6
0.8 High Symptoms(+1
above 0=
overesmate
-
-0.6
-0.4
-0.2
0.0 0=no bias
below0=
underesmate
iorr'sNegave Behavicepons of PartnerPerc
-1.0
-0.8
Partner’s Actual Negave
Behavior Low(–1 SD)
Partner’sActual Negave
Behavior High(+1 SD)
Figure 2. The effect of depressive symptoms on perceptions of
the partner’s negative behavior across a 21-day period.
Note: Zero represents no directional bias (i.e., perceiver’s perceptions
match their partner’s reported behavior at the mean level), positive values
indicate that perceivers’ overestimate the partner’s negative behavior, and
negative values indicate perceivers’ underestimate the partner’s negative
behavior. Slopes across low versus high partner’s actual negative behavior
represent tracking accuracy.
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Overall and Hammond 645
(b) perceiver’s perceptions of the partner’s commitment,
(c) the partner’s actual commitment, and (d) the interaction
between perceptions of the partner’s commitment and part-
ner’s actual commitment. All predictors were person-
centered and were allowed to vary by male and female
perceivers for each dyad (i.e., be random variables).2
In these analyses, the main effect of perceptions of the
partner’s commitment tests whether more negative percep-
tions of the partner’s commitment was associated with
within-person increases in relationship insecurity, over and
above the impact of the partner’s actual commitment. The
interaction term tests whether any within-person increases in
relationship insecurity associated with underestimating the
partner’s commitment was greater when negative percep-
tions were more accurate—that is, on days when the part-
ner’s commitment was actually low. Four sets of analyses
tested the links between perceptions of the partner’s commit-
ment or negative behavior and relationship insecurity or
depressed mood. Across analyses, the fixed effects did not
significantly differ across gender (1 exception out of 12; see
Gender Diff. t, Table 5) and so we present the effects pooled
across men and women.
The results are shown in Table 5. As predicted, perceiving
the partner as less committed and behaving more negatively
was associated with increased relationship insecurity and
depressed mood. Moreover, the significant interactions
between perceptions and partner’s actual commitment and
negative behavior for three of the four models indicated that
the associations between more negative perceptions and rela-
tionship insecurity/depressed mood were more pronounced
when more negative perceptions aligned accurately with
lower commitment and more negative behavior reported by
the partner.
To illustrate, Figure 3 plots the significant interaction
between perceptions of the partner’s commitment and the
partner’s actual commitment on changes in daily relationship
security. Perceiving low partner commitment was associated
with greater relationship insecurity regardless of whether the
partner’s actual commitment was high (b = −.57, t = −13.04,
Table 5. The Effects of Perceptions of the Partner’s Commitment and Negative Behavior on Daily Feelings of Relationship Insecurity and
Depressed Mood.
Relationship insecurity Depressed mood
B t r Gender Diff. t B t r Gender Diff. t
Partner’s commitment
Perceptions of partner’s
commitment
−.50 −12.36**** .87 1.35 −.41 −10.02**** .80 2.45***
Partner’s actual commitment −.12 −3.23**** .41 0.88 −.17 −4.05**** .47 −0.37
Perceptions × Actual
commitment
.08 3.71**** .13 −1.57 .02 0.65 .02 0.82
Partner’s negative behavior
Perceptions of partner’s
negative behavior
.45 12.72**** .82 −1.49 .50 12.31**** .81 1.13
Partner’s actual negative
behavior
.06 2.43*** .31 0.79 .03 1.13 .14 1.23
Perceptions × Actual
negative behavior
.07 3.70**** .08 1.06 .05 2.30*** .06 0.37
Note: All analyses controlled for relationship insecurity/depressed mood on the prior day; thus, significant effects represent predicted decreases or in-
creases relative to prior levels of insecurity/depressed mood. Only the focal fixed effects are shown to simplify the presentation. Results are from models
estimating the fixed effects pooled across men and women and testing whether the effects significantly differed by estimating the main and interaction
effects of gender (shown in column marked Gender Diff. t). The majority of effects (11 out of 12) did not significantly differ across men and women. The
one exception is discussed in the text. Approximate effect sizes were computed using Rosenthal and Rosnow’s (2007) formula: r = √(t2 / t2 + df).
***p < .05. ****p < .01.
Daily Feelings of Relaonship
Insecurity
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
Percepon of Partner's
Commitment Low (–1 SD)
Percepon of Partner's
Commitment High (+1 SD)
Partner’s Actual Commitment Low (–1 SD)
Partner’s Actual Commitment High (+1 SD)
Figure 3. The impact of perceptions of partner’s commitment
and partner’s actual commitment on perceiver’s daily feelings of
relationship insecurity.
Note: Analyses control for relationship insecurity on the prior day; thus,
these significant effects represent predicted increases or decreases
relative to prior levels of insecurity.
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646 Personality and Social Psychology Bulletin 39(5)
p < .001) or low (b = −.44, t = −9.88, p < .001), but the effect
of perceiving low commitment was most negative when per-
ceptions accurately reflected lower commitment reported by
the partner (b = −.18, t = −4.54, p < .001).
Analogous patterns were found when modeling percep-
tions of the partner’s negative behavior on relationship inse-
curity and depressed mood (i.e., perceiving more negative
behavior by the partner was associated with greater depressed
mood, particularly when the partner agreed he or she was
behaving more negatively). The only exception was that per-
ceived- and partner-reported commitment independently
predicted greater depressed mood but did not significantly
interact (see right top of Table 5). The single gender differ-
ence (out of 12 effects) also emerged in this model, with the
links between perceptions of the partner’s commitment and
depressed mood stronger for women (B = −.50, t = − 7.70,
p < .01) than men (B = −.31, t = − 7.00, p < .01). Nonetheless,
taken together, the results in Table 5 indicate that more nega-
tive relationship perceptions were associated with greater
relationship insecurity and depressed mood, and there was
good evidence (3 of 4 tests) that this was particularly the case
on days when negative perceptions more accurately corre-
sponded with lower commitment and more negative behav-
ior reported by the partner. This pattern supports that the mix
of directional bias and tracking accuracy that was associated
with elevated depressive symptoms is linked with increased
relationship insecurity and depressed mood.
Discussion
This study examined whether depressive symptoms are
associated with more biased or more accurate social percep-
tions. Both partners of committed heterosexual couples
completed a 3-week daily diary reporting on their own and
perceptions of their partner’s commitment and behavior.
Comparing individuals’ perceptions of their partner to the
commitment and behavior reported by the partner, analyses
modeled the degree to which individuals (a) over- or under-
estimated their partner’s commitment and negative behavior
(directional bias) and (b) accurately detected changes in
their partner’s commitment and negative behavior across
days (tracking accuracy). As predicted, participants who
reported greater depressive symptoms exhibited greater
directional bias, including underestimating their partner’s
commitment and overestimating their partner’s negative
behavior (when compared with the commitment and behav-
ior reported by the partner). However, participants with
greater depressive symptoms also more accurately tracked
changes in their partner’s commitment and behavior across
days. Moreover, this pattern held controlling for a series of
alternative explanations, including perceivers’ own commit-
ment and negative behavior, relationship quality, self-
esteem, and daily levels of relationship insecurity.
The pattern of directional bias and tracking accuracy asso-
ciated with greater depressive symptoms helps to reconcile
prior, seemingly inconsistent, findings. The greater direc-
tional bias is consistent with links between depressive symp-
toms and biased processing of negative interpersonal
information (Gotlib & Joormann, 2010), overestimation of
negative feelings in others (e.g., Gilboa-Schechtman et al.,
2008), and doubts about the sincerity of others’ care and reas-
surance (Joiner & Timmons, 2009). The greater tracking
accuracy is consistent with other research linking depressive
symptoms to more thorough processing of interpersonal
information, including seeking and integrating more informa-
tion (e.g., Edwards et al., 2000; Gleicher & Weary, 1991), and
more accurate attributions and identification of important
interpersonal behavior (e.g., Lane & DePaulo, 1999; Yost &
Weary, 1996).
This mix of greater directional bias and tracking accuracy
reflects a cautious, vigilant approach to assessing others’
motives and behavior, and in particular detecting interper-
sonal threat. Such a perceptual approach is consistent with
recent models that suggest depressive symptoms reflect an
adaptive response to social loss, triggering sensitivity toward
social threat, avoidance of social risks, and associated ana-
lytical processing (i.e., rumination) of interpersonal problems
(see Allen & Badcock, 2003; Andrews & Thomson, 2009).
Indeed, perceptions of the partner’s commitment and behav-
ior are crucial because these signal how likely partners will
continue to be committed and invested in the relationship ver-
sus dissatisfied and rejecting (Murray & Holmes, 2009; Reis
et al., 2004). Vigilant monitoring of changes in these signals
should prevent further social loss by enhancing detection of
any damage to interpersonal connections and subsequent
rejection (Tooby & Cosmides, 1996). For example, when
sensing partners are dissatisfied, intimates typically try to
alter offending self-attributes, and responsive self-regulation
efforts work to improve the partner’s evaluations (Overall &
Fletcher, 2010; Overall, Fletcher, & Simpson, 2006).
However, vigilant monitoring should not only create
more accurate identification of interpersonal threat but also
magnify the import and weight given to that threat.
Accordingly, individuals who reported greater depressive
symptoms more accurately detected when their partner’s
commitment weakened (as reported by the partner), but then
exaggerated the detected drops in their partner’s commit-
ment. An analogous pattern emerged when examining
behavioral signs of the partner’s acceptance and commit-
ment. Although this perceptual pattern may adaptively initi-
ate remedial efforts to prevent interpersonal loss, pushed into
overdrive, this pattern is also likely to incur costs, including
overreacting to what will often be temporary relationship
difficulties, fostering insecurity and propagating depressed
mood, and triggering corrective actions that are dispropor-
tionate to the degree of threat.
First, even satisfied and invested partners will experience
short-term dips in commitment and behave negatively at
times, but return to more positive, loving attitudes and
behavior once the difficulty has passed. Vigilant tracking
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Overall and Hammond 647
coupled with magnifying the significance of any negativity
will likely result in intimates reading “too much” into com-
mon relationship difficulties, and may reduce the ability for
individuals (and their partners) to weather the normal “ups”
and “downs” of relationships (Overall et al., 2012; Simpson
et al., 2003). This may be one central reason individuals with
depressive symptoms react more destructively when experi-
encing relationship problems (Rehman et al., 2008).
Second, perceiving waning partner commitment and
more hurtful, rejecting behavior, particularly in times of con-
flict or difficulty, is associated with reductions in the degree
to which intimates feel secure in their relationship (Murray
& Holmes, 2009). Accordingly, in this study, we found that
more negative perceptions of the partner’s commitment and
relationship behavior were associated with greater increases
in relationship insecurity. Moreover, this association was
particularly pronounced when the partner reported lower
commitment and more negative behavior—that is, when
individuals accurately detected and inflated partner negativ-
ity. More negative perceptions were also associated with
within-person increases in daily depressed mood. This set of
findings suggests that the perceptual biases and sensitivity to
interpersonal threat associated with elevated depressive
symptoms fosters relationship insecurity and propagates
depressed mood and, thus, may play a key role in the persis-
tence of depressive symptoms.
Third, attending to and magnifying the meaning of rela-
tionship threat may fuel unnecessary or disproportionate
remedial actions, such as excessive reassurance seeking to
restore felt-security. The links between depressive symptoms
and excessive reassurance seeking have been well docu-
mented (Joiner & Timmons, 2009). There is also increasing
evidence that others find depressive individuals’ attempts to
seek reassurance aversive and, thus, ultimately are more
rejecting (Benazon, 2000; Katz & Beach, 1997). The percep-
tual vigilance and bias shown in this study may help to
explain why depressed individuals’ reassurance seeking is
excessive and aversive. Overestimating and inflating nega-
tivity means the need for reassurance does not match the
state and quality of the relationship and this mismatch may
become tiresome for partners if their reassurance does little
to improve biased relationship perceptions or sensitivity to
threat. Ironically, the biased and vigilant perceptions shown
here might actually generate declines in partner commitment
and more negative, rejecting partner behavior.
Strengths, Caveats, and Future Directions
The current research extended prior research on several
fronts. The overall pattern reconciles opposing perspectives
and research by demonstrating that depressive symptoms are
associated with both greater bias and greater accuracy when
comparing relationship perceptions to the reports of the part-
ner. The results suggest that these biases are due to a sensi-
tive attunement to important and meaningful contextual
changes, such as when partners are thinking or behaving in
ways that signal potential rejection. The findings also indicate
that this perceptual sensitivity is likely to play an important
role in sustaining depressed mood and generating the relation-
ship difficulties associated with depressive symptoms.
Despite the notable strength of assessing perceptions across
the course of couples’ daily lives, the correlational nature of
the current data prevents causal conclusions. We have focused
on how depressive symptoms influence directional bias and
tracking accuracy. However, prior research has shown recipro-
cal links between depression and relationship difficulties
(Davila et al., 1997; Rehman et al., 2008), supporting that
depression can generate interpersonal stress, which in turn
exacerbates depressive symptoms (Hammen, 1991). Indeed,
we found that negative relationship perceptions were associ-
ated with increases in depressed mood. This raises the possi-
bility that, rather than depressive symptoms shaping bias and
accuracy, processes within the relationship were responsible
for the perceptual sensitivity and bias we found, and these dif-
ficulties caused elevated depressive symptoms. For example,
partners who fail to express commitment or vary widely in
their day-to-day commitment might elicit more vigilant moni-
toring and negative bias as well as greater depressive symp-
toms. However, such within-relationship processes will
strongly influence perceived relationship quality and felt-
security, and control analyses demonstrated these variables
did not account for the associations between depressive symp-
toms and bias and accuracy. Nonetheless, the links between
depressive symptoms and bias and accuracy (and other rela-
tionship difficulties) are likely to be self-perpetuating.
Tracking these reciprocal processes across time is an impor-
tant direction for future research.
A principal challenge when assessing bias and accuracy is
establishing an appropriate benchmark of reality. Our use of
partner reports is consistent with the majority of prior
research examining bias and accuracy within relationships
(see Fletcher & Kerr, 2010). However, self-serving biases
could mean that partners understated their levels of negative
behavior. The results suggest this was not the case. On aver-
age, across the sample, there was no directional bias and per-
ceivers demonstrated substantial tracking accuracy (see
Table 2). This convergence provides strong evidence that our
measures generally captured a shared relationship reality. In
addition, even if bias in the partner reports meant our index
of bias understated or inflated actual directional bias and
tracking accuracy, this would not change the meaning or
implication of our results. Regardless of overall levels, bias
and accuracy significantly differed across high versus low
depressive symptoms, and such differences were associated
with meaningful changes in relationship insecurity and
depressed mood.
Alternative benchmarks that may appear more objective
also face challenges to their validity as markers of reality.
Third-party observations, such as by family and friends, can
be biased because people protect their own relationships by
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648 Personality and Social Psychology Bulletin 39(5)
undervaluing others (Gagné & Lydon, 2004). Trained coders
can also overestimate or underestimate negativity due to the
context and behaviors coded and lack of personal knowledge
regarding the intentions and idiosyncratic meaning of spe-
cific actions (Gagné & Lydon, 2004). Third parties and
objective coders are also only exposed to a limited amount of
couples’ behaviors and interactions, whereas we assessed
naturally occurring interactions across 3 weeks of couples’
daily life. Furthermore, experimental tasks that assess cogni-
tive biases are also uninformative regarding the veracity of
people’s perceptions as they occur in real life. Thus, the use
of partner reports as the benchmark of reality allows assess-
ment of bias and accuracy in the ecological context of peo-
ple’s everyday relationship experiences. Nonetheless, we
expect that the same pattern will be evident using other
benchmarks, and this is a good direction for future research.
Finally, our data do not generalize to clinical populations.
It is possible that clinically diagnosed depression has quali-
tatively different effects on interpersonal perceptions, such
as producing a blanket negative bias that is not sensitive to
context. However, previous research using clinical samples
provide evidence that a similar pattern might emerge. For
example, clinically depressed individuals generally perceive
neutral faces to be more sad (Leppänen, 2006) and are also
faster to identify anger or sadness in changing expressions
(Joormann & Gotlib, 2006). The current methodological
approach and statistical design demonstrates how future
research can simultaneously distinguish between directional
bias and tracking accuracy to clarify the perceptual processes
associated with clinically diagnosed depression.
Conclusion
The current research helps to reconcile the debate regarding
whether depressive symptoms produce more biased or more
accurate interpersonal perceptions. By gathering multiple
assessments of interpersonal perceptions and associated
benchmarks across couples’ daily lives, we demonstrated
that elevated depressive symptoms were associated with
greater bias and greater accuracy. Participants who reported
more depressive symptoms were more accurate in detecting
interpersonal threat, including reductions in their partner’s
commitment and increases in their partner’s negative behav-
ior (as reported by the partner), but then amplified those
threats, including underestimating commitment and overes-
timating the partner’s negativity. This perceptual pattern was
also associated with increases in relationship insecurity and
depressed mood. These results highlight the importance of
examining relationship perceptions and processes in under-
standing the consequences and outcomes of depressive
symptoms.
Acknowledgments
We would like to thank Jeffry A. Simpson and Tessa V. West for
helpful comments on an earlier draft of this article.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article: This
research was supported by a University of Auckland Faculty of
Science Research Development Grant (UoA 3626244) awarded to
the first author.
Notes
1. Comparing perceptions to the partner’s reports is the primary
method used to assess bias and accuracy within relationships
(Fletcher & Kerr, 2010; Gagné & Lydon, 2004). This approach
has two major strengths. First, our method captures variation in
people’s daily experiences of their relationship and thus has
high ecological validity. Second, such experiences influence
important relationship and individual outcomes. For example,
reported commitment is a strong predictor of relationship dis-
solution (Le, Dove, Agnew, Korn, & Mutso, 2010), discrepan-
cies between perceptions and partner reports predict relationship
satisfaction (Fletcher & Kerr, 2010), and perceptions of the
partner shape relationship security and associated behavior
(Murray & Holmes, 2009). We consider potential limitations
and alternatives to this approach in the “Discussion” section.
2. Person-centering isolates within-person changes or fluctua-
tions (e.g., does daily depressed mood vary according to how
negative the partner is perceived to behave?) holding between-
person differences constant (e.g., individual differences in
daily levels of depressed mood or perceptions of the partner’s
behavior). Accordingly, although depressive symptoms
reported at the beginning of the study (i.e., Centre for
Epidemiological Studies Depression [CES-D] Scale scores)
were associated with greater daily relationship insecurity (B =
0.17, t = 2.89, p < .01) and depressed mood (B = 0.31, t = 5.05,
p < .01), and bias and accuracy of perceptions (see Table 4),
controlling for depressive symptoms did not reduce any of the
effects shown in Table 5. The links in Table 5 were also not
moderated by CES-D scores.
References
Allen, N. B., & Badcock, P. B. T. (2003). The social risk hypothesis
of depressed mood: Evolutionary, psychosocial, and neurobio-
logical perspectives. Psychological Bulletin, 129, 887-913.
Alloy, L. B., & Abramson, L. Y. (1979). Judgment of contingency
in depressed and nondepressed students: Sadder but wiser?
Journal of Experimental Psychology-General, 108, 441-485.
Andrews, P. W., & Thomson, J. A., Jr. (2009). The bright side of
being blue: Depression as an adaptation for analyzing complex
problems. Psychological Review, 116 , 620-654.
Badcock, P. B. T., & Allen, N. B. (2003). Adaptive social reasoning
in depressed mood and depressive vulnerability. Cognition &
Emotion, 17, 647-670.
at The University of Auckland Library on May 7, 2013psp.sagepub.comDownloaded from
Overall and Hammond 649
Beach, S. R. H., Katz, J., Kim, S., & Brody, G. H. (2003). Prospec-
tive effects of marital satisfaction on depressive symptoms in
established marriages: A dyadic model. Journal of Social and
Personal Relationships, 20, 355-371.
Beck, A. T. (1967). Depression: Clinical, experimental and theo-
retical aspects. New York, NY: Hoeber.
Benazon, N. R. (2000). Predicting negative spousal attitudes toward
depressed persons: A test of Coyne’s interpersonal model.
Journal of Abnormal Psychology, 109, 550-554.
Collins, N. L., & Feeney, B. C. (2004). Working models of attach-
ment shape perceptions of social support: Evidence from
experimental and observational studies. Journal of Personal-
ity and Social Psychology, 87, 363-383.
Coyne, J. C. (1976). Toward an interactional description of depres-
sion. Psychiatry, 39, 28-40.
Cranford, J. A., Shrout, P. E., Iida, M., Rafaeli, E., Yip, T., &
Bolger, N. (2006). A procedure for evaluating sensitivity to
within-person change: Can mood measures in diary studies
detect change reliably? Personality and Social Psychology
Bulletin, 32, 917-929.
Davila, J., Bradbury, T. N., Cohan, C. L., & Tochluk, S. (1997).
Marital functioning and depressive symptoms: Evidence for
a stress generation model. Journal of Personality and Social
Psychology, 73, 849-861.
Edwards, J. A., Weary, G., von Hippel, W., & Jacobson, J. A.
(2000). The effects of depression on impression formation:
The role of trait and category diagnosticity. Personality and
Social Psychology Bulletin, 26, 462-473.
Fletcher, G. J. O., & Kerr, P. S. G. (2010). Through the eyes of love:
Reality and illusion in intimate relationships. Psychological
Bulletin, 136, 627-658.
Fletcher, G. J. O., Simpson, J. A., & Thomas, G. (2000). The mea-
surement of perceived relationship quality components: A
confirmatory factor analytic approach. Personality and Social
Psychology Bulletin, 26, 340-354.
Gadassi, R., Mor, N., & Rafaeli, E. (2011). Depression and
empathic accuracy in couples: An interpersonal model of
gender differences in depression. Psychological Science, 22,
1033-1041.
Gagné, F. M., & Lydon, J. E. (2004). Bias and accuracy in close
relationships: An integrative review. Personality and Social
Psychology Review, 8, 322-338.
Gilboa-Schechtman, E., Foa, E., Vaknin, Y., Marom, S., & Her-
mesh, H. (2008). Interpersonal sensitivity and response bias in
social phobia and depression: Labeling emotional expression.
Cognitive Therapy Research, 32, 605-618.
Gleicher, F., & Weary, G. (1991). The effect of depression on the
quantity and quality of social inferences. Journal of Personal-
ity and Social Psychology, 61, 105-114.
Gotlib, I. H., & Joormann, J. (2010). Cognition and depression:
Current status and future directions. Annual Review of Clini-
cal Psychology, 6, 285-312.
Hammen, C. L. (1991). The generation of stress in the course of
unipolar depression. Journal of Abnormal Psychology, 100,
555-561.
Haselton, M. G., & Buss, D. M. (2000). Error management theory:
A new perspective on biases in cross-sex mind reading. Jour-
nal of Personality and Social Psychology, 78, 81-91.
Joiner, T. E. (2000). Depression’s vicious scree: Self-propagating
and erosive factors in depression chronicity. Clinical Psychol-
ogy: Science and Practice, 7, 203-218.
Joiner, T. E., & Timmons, K. A. (2009). Depression in its interper-
sonal context. In I. H. Gotlib & C. L. Hammond (Eds.), Hand-
book of depression (pp. 322-339). New York, NY: Guilford.
Joormann, J., & Gotlib, I. H. (2006). Is this happiness I see? Biases in
the identification of emotional facial expressions in depression
and social phobia. Journal of Abnormal Psychology, 115 , 705.
Katz, J., & Beach, S. R. H. (1997). Self-verification and depres-
sive symptoms in marriage and courtship: A multiple pathway
model. Journal of Marriage and Family, 59, 903-914.
Kelley, H. H., & Thibaut, J. W. (1978). Interpersonal relations: A
theory of interdependence. New York, NY: Wiley.
Kenny, D. A., & Acitelli, L. K. (2001). Accuracy and bias in the
perception of the partner in a close relationship. Journal of
Personality and Social Psychology, 80, 439-448.
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data
analysis. New York, NY: Guilford.
Lane, J. D., & DePaulo, B. M. (1999). Completing Coyne’s cycle:
Dysphorics’ ability to detect deception. Journal of Research in
Personality, 33, 311-329.
Le, B., Dove, N. L., Agnew, C. R., Korn, M. S., & Mutso, A. A.
(2010). Predicting nonmarital romantic relationship dissolution:
A meta-analytic synthesis. Personal Relationships, 17, 377-390.
Leppänen, J. M. (2006). Emotional information processing in mood
disorders: A review of behavioural and neuroimaging findings.
Current Opinion in Psychiatry, 19, 34-39.
Mathews, A., Ridgeway, V., & Williamson, D. A. (1996). Evidence
for attention to threatening stimuli in depression. Behaviour
Research and Therapy, 34, 695-705.
Miller, P. J. E., & Rempel, J. K. (2004). Trust and partner-enhanc-
ing attributions in close relationships. Personality and Social
Psychology Bulletin, 30, 695-705.
Murray, S. L., Griffin, D. W., Derrick, J. L., Harris, B., Aloni, M.,
& Leder, S. (2011). Tempting fate or inviting happiness? Unre-
alistic idealization prevents the decline of marital satisfaction.
Psychological Science, 22, 619-626.
Murray, S. L., & Holmes, J. G. (2009). The architecture of interde-
pendent minds: A motivation-management theory of mutual
responsiveness. Psychological Review, 116 , 908-928.
Murray, S. L., Holmes, J. G., & Griffin, D. W. (1996). The self-
fulfilling nature of positive illusions in romantic relationships:
Love is not blind, but prescient. Journal of Personality and
Social Psychology, 71, 1155-1180.
Murray, S. L., Holmes, J. G., & Griffin, D. W. (2000). Self-esteem
and the quest for felt security: How perceived regard regulates
attachment processes. Journal of Personality and Social Psy-
chology, 78, 478-498.
Overall, N. C., & Fletcher, G. J. O. (2010). Receiving regulation
from intimate partners: Reflected appraisal processes in close
relationships. Personal Relationships, 17, 433-456.
at The University of Auckland Library on May 7, 2013psp.sagepub.comDownloaded from
650 Personality and Social Psychology Bulletin 39(5)
Overall, N. C., Fletcher, G. J. O., & Kenny, D. A. (2012). When bias
and insecurity promote accuracy: Mean-level bias and track-
ing accuracy in couples’ conflict discussions. Personality and
Social Psychology Bulletin, 38, 642-655.
Overall, N. C., Fletcher, G. J. O., & Simpson, J. A. (2006). Regu-
lation processes in intimate relationships: The role of ideal
standards. Journal of Personality and Social Psychology, 91,
662-685.
Papp, L. M., Kouros, C. D., & Cummings, M. E. (2010). Emo-
tions in marital conflict interactions: Empathic accuracy,
assumed similarity, and the moderating context of depressive
symptoms. Journal of Social and Personal Relationships, 27,
367-387.
Pietromonaco, P. R., & Rook, K. S. (1987). Decision style in depres-
sion: The contribution of perceived risks versus benefits. Jour-
nal of Personality and Social Psychology, 52, 399-408.
Potthoff, J. G., Holahan, C. J., & Joiner, T. E. (1995). Reassurance
seeking, stress generation, and depressive symptoms: An inte-
grative model. Journal of Personality and Social Psychology,
68, 664-670.
Radloff, L. S. (1977). The CES-D scale: A self-report depression
scale for research in the general population. Applied Psycho-
logical Measurement, 1, 385-401.
Rehman, U. S., Gollan, J., & Mortimer, A. R. (2008). The marital
context of depression: Research, limitations and new direc-
tions. Clinical Psychology Review, 28, 179-198.
Reis, H. T., Clark, M. S., & Holmes, J. G. (2004). Perceived part-
ner responsiveness as an organizing construct in the study of
intimacy and closeness. In D. J. Mashek & A. P. Aron (Eds.),
Handbook of closeness and intimacy (pp. 201-225). Mahwah,
NJ: Erlbaum.
Rosenberg, M. (1965). Society and the adolescent self-image.
Princeton, NJ: Princeton University Press.
Rosenthal, R., & Rosnow, R. L. (2007). Essentials of behavioral
research: Methods and data analysis (3rd ed.). New York, NY:
McGraw-Hill.
Rusbult, C. E., Verette, J., Whitney, G. A., Slovik, L. F., & Lipkus,
I. (1991). Accommodation processes in close relationships:
Theory and preliminary empirical evidence. Journal of Per-
sonality and Social Psychology, 60, 53-78.
Simpson, J. A., Kim, J. S., Fillo, J., Ickes, W., Rholes, W. S., Oriña,
M. M., & Winterheld, H. A. (2011). Attachment and the man-
agement of empathic accuracy in relationship-threatening situa-
tions. Personality and Social Psychology Bulletin, 37, 242-254.
Simpson, J. A., Oriña, M. M., & Ickes, W. (2003). When accuracy
hurts, and when it helps: A test of the empathic accuracy model
in marital interactions. Journal of Personality and Social Psy-
chology, 85, 881-893.
Starr, L. R., & Davila, J. (2008). Excessive reassurance seek-
ing, depression, and interpersonal rejection: A meta-analytic
review. Journal of Abnormal Psychology, 117, 762-775.
Swann, W. B., Wenzlaff, R. M., Krull, D. S., & Pelham, B. W.
(1992). Allure of negative feedback: Self-verification strivings
among depressed persons. Journal of Abnormal Psychology,
101, 293-305.
Thomas, G., Fletcher, G. J. O., & Lange, C. (1997). On-line
empathic accuracy in marital interaction. Journal of Personal-
ity and Social Psychology, 72, 839-850.
Tooby, J., & Cosmides, L. (1996). Friendship and the banker’s par-
adox: Other pathways to the evolution of adaptations for altru-
ism. Proceedings of the British Academy, 88, 119-143.
West, T. V., & Kenny, D. A. (2011). The truth and bias model of
judgment. Psychological Review, 118 , 357-378.
Yost, J. H., & Weary, G. (1996). Depression and the correspondent
inference bias: Evidence for more effortful cognitive process-
ing. Personality and Social Psychology Bulletin, 22, 192-200.
at The University of Auckland Library on May 7, 2013psp.sagepub.comDownloaded from